Procedure Computation List
Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations.
### Available end points:
- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id
### Available Methods:
- `GET`
- `HEAD`
### Available filters:
- `uuid`
- `title`
- `keywords`
- `abstract`
### How to use filters:
These filters can be used like django query filters using __ for related model relationships.
- `/computations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/computations/?title__startswith!=DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE`
- `/computations/?abstract__contains=HadCM3 model`
GET /api/v2/computations/?format=api&offset=3700
{ "count": 3949, "next": "https://api.catalogue.ceda.ac.uk/api/v2/computations/?format=api&limit=100&offset=3800", "previous": "https://api.catalogue.ceda.ac.uk/api/v2/computations/?format=api&limit=100&offset=3600", "results": [ { "ob_id": 40270, "uuid": "6f5d9b3d55d941a397c58d811619ac62", "title": "Derivation of the ESA Sea Level Climate Change Initiative (Sea_Level_cci): Regional coastline profile of Vertical Land Motions in Europe and SE Asia/Oceania, v1", "abstract": "This dataset has been estimated as the difference between the altimeter coastal sea level SL_cci+ v1.1 dataset (https://catalogue.ceda.ac.uk/uuid/222cf11f49a94d2da8a6da239df2efc4) and tide gauges measurements from the Permanent Service for Mean Sea Level (PMSML) network (https://psmsl.org/)).\r\n\r\nThe altimeter input data are from the Jason-1, Jason-2 and Jason-3 missions during the period Jan. 2002 - May 2018.\r\n\r\nFor more information see the associated Sea Level CCI documentation (https://climate.esa.int/media/documents/SLCCI_CCN2_D1.1_TUM_v2.pdf)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40290, "uuid": "1145230fd72547d68b168b72ee9359c2", "title": "the MIROC team running: experiment esm-pi-cdr-pulse using the MIROC-ES2L model.", "abstract": "The the MIROC team team consisted of the following agencies: Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI).the MIROC team running the \"pulse removal of 100 Gt carbon from pre-industrial atmosphere\" (esm-pi-cdr-pulse) experiment using the MIROC-ES2L model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, MIROC, MIROC-ES2L, esm-pi-cdr-pulse, Amon, Lmon, Omon", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40293, "uuid": "b9a384476daa4c9daf9d01440ea2ff37", "title": "the MIROC team running: experiment abrupt-4xCO2 using the MIROC-ES2H model.", "abstract": "The the MIROC team team consisted of the following agencies: Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI).the MIROC team running the \"abrupt quadrupling of CO2\" (abrupt-4xCO2) experiment using the MIROC-ES2H model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, MIROC, MIROC-ES2H, abrupt-4xCO2, Amon", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40296, "uuid": "fc2b087ef820440184a41a6c66ea79b1", "title": "the MIROC team running: experiment piControl using the MIROC-ES2H model.", "abstract": "The the MIROC team team consisted of the following agencies: Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI).the MIROC team running the \"pre-industrial control\" (piControl) experiment using the MIROC-ES2H model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, MIROC, MIROC-ES2H, piControl, Amon", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40325, "uuid": "c800f7a0b13f495aaf4f0f7f767f156f", "title": "Climatic Research Unit (CRU) procedure to produce the CRU JRA v2.4 data.", "abstract": "The CRU JRA (Japanese reanalysis) data is a replacement to the CRU NCEP dataset, CRU JRA data follows the style of Nicolas Viovy's original dataset rather than that which is available from UCAR.\r\n\r\nThe CRU JRA dataset is based on the JRA-55 reanalysis dataset and aligned where appropriate with the CRU TS dataset version 4.07 (1901-2022).\r\n\r\nAll JRA variables are regridded from their native TL319 Gaussian grid to the CRU regular 0.5° x 0.5° grid, using the g2fsh spherical harmonics routine from NCL (NCAR Command Language), based on the 'Spherepack' code. The exception is precipitation, which is regridded using ESMF 'nearest neighbour': all other algorithms tried exhibited unwanted artifacts.\r\n\r\nThe JRA-55 reanalysis dataset starts in 1958. The years 1901-1957 are constructed using randomly-selected years between 1958 and 1967. Where alignment with CRU TS occurs, the relevant CRU TS data is used.\r\n\r\nOf the ten variables listed above, the last four do not have analogs in the CRU TS dataset. These are simply regridded, masked for land only, and output as CRUJRA. The other six are aligned with CRU TS as follows:\r\n\r\nTMP is aligned with CRU TS TMP. A monthly mean for the JRA data is\r\ncalculated and compared with the equivalent CRU TS mean. The difference\r\nbetween the means is added to every JRA value.\r\n\r\n---\r\n\r\nTMAX and TMIN are aligned with CRUJRA TMP and CRU TS DTR. Firstly, at\r\neach time step, the TMAX-TMP-TMIN triplets are checked and adjusted so\r\nthat TMAX is always >= TMP, and TMIN is always <= TMP. This triplet\r\nalignment is prioritised above DTR alignment. Secondly, monthly JRA DTR\r\nis calculated by first establishing the daily maxima and minima (max and\r\nmin of the subdaily values in TMAX and TMIN respectively), then monthly\r\nmaxima and minima, (means of the daily DTR values), giving JRA monthly\r\nDTR. This is compared with CRU TS DTR and the fractional difference\r\n(factor) calculated as (CRU TS DTR) / (JRA monthly DTR). This factor is\r\nthen used to adjust the DTR of each pair of subdaily TMAX and TMIN\r\nvalues, though not if the triplet alignment would be broken.\r\n\r\n---\r\n\r\nPRE is aligned with CRU TS PRE and WET (rain day counts). Firstly, the\r\nmonthly total precipitation is calculated for JRA and compared to CRU TS\r\nPRE; an adjustment factor is acquired (crupre/jrapre) and all values\r\nadjusted. Precipitation amounts are now aligned at a monthly level, and\r\nthis alignment is prioritised above WET alignment. Secondly, the number\r\nof rain days is calculated for JRA: a day is declared wet if the total\r\nprecipitation is equal to, or exceeds, 0.1mm (the same threshold as CRU\r\nTS WET). If JRA has more wet days than CRU TS, then the driest of those\r\nare reduced to a random amount below 0.1 (an adjustment factor is\r\ncalculated and applied to each time step, to preserve the subdaily\r\ndistribution). If JRA has fewer wet days than CRU TS, then sufficient\r\ndry days are set to a random amount equal to or closely above 0.1mm,\r\nagain using an adjustment factor to preserve the subdaily distribution. \r\nWhere wet day alignment threatens precipitation alignment, the process\r\nis abandoned and the cell/month reverts to the previously-aligned\r\nprecip version. Exception handling is very complicated and cannot be\r\nsummarised here.\r\n\r\n---\r\n\r\nSPFH is aligned with CRU TS VAP. VAP is converted to SPFH, and JRA mean\r\nmonthly SPFH is calculated. The fractional difference (factor) is\r\ncalculated as (CRU TS SPFH) / (JRA monthly SPFH), this factor is then\r\napplied to the JRA subdaily humidity values.\r\n\r\n---\r\n\r\nDSWRF is aligned with CRU TS CLD. CLD is converted to shortwave\r\nradiation, and JRA mean monthly DSWRF is calculated. The fractional\r\ndifference (factor) is calculated as (CRU TS SWR) / (JRA monthly DSWRF),\r\nthis factor is then applied to the JRA subdaily radiation values.\r\n\r\n---\r\n\r\nWhere appropriate, CRUJRA values are kept within physically-appropriate\r\nconstraints (such as negative precipitation), which could result from\r\nregridding as well as adjustments.", "keywords": "Climatic Research Unit, CRU, TS, CY", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40328, "uuid": "64e362ad3e4040d7a2772d16cc2d04ab", "title": "Distributed Lag Non-linear Model (DLNM)", "abstract": "Statistical regression using distributed lag non-linear model is fully described in Gasparrini, Armstrong and Kenward, 2010, and Vicedo-Cabrera, Sera and Gasparrini, 2019.\r\nComputation details for Temperature-attributable mortality (and hospital admission) time series, UK (1900-2099) dataset.\r\nModel setup: natural cubic splines in all dimensions, 3 log-spaced knots in lag dimension, 8 degrees of freedom per year in long-term trend, confounding by day of week.\r\n\r\n- Mortality: temperature knots at 0.1, 0.75, 0.9 quantiles, 21 lag days.\r\n\r\n- Hospital admission: temperature knots at 0.4, 0.9 quantiles, 28 lag days.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40340, "uuid": "677c25df9f324ca3a9e1920ea3c330b1", "title": "TLS2trees: a semi-automated processing pipeline", "abstract": "Plot-level point clouds were processed using TLS2trees which is a set of Python command line tools & designed to be horizontally scalable, e.g., on a High Performance Computing (HPC) facility. Pipeline steps: 1) Point cloud re-processing, 2) semantic segmentation into wood & leaf point classes, 3) instance segmentation into sets of point clouds representing individual trees, 4) Quantitative structural models (QSMs) of individual tree point clouds, & 5) Plot biophysical & AGB estimates.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40363, "uuid": "c51825ce43604d2985bca6861c868b08", "title": "CESM2-WACCM model deployed at NCAR", "abstract": "CESM2-WACCM model deployed at NCAR", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40371, "uuid": "2c99b8a0b15746e9bc97a7f6a331c3c7", "title": "ECMWF IFS Model", "abstract": "The underlying data was produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) IFS model for the SNAPSI project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40378, "uuid": "96543a9250f54e409edeb6225cd28a6d", "title": "NOAA-GFDL SPEAR Model", "abstract": "The underlying data was produced by the National Oceanic and Atmospheric Administration- Geophysical Fluid Dynamics Laboratory (NOAA-GFDL) SPEAR model for the SNAPSI project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40382, "uuid": "a7dbc7a3bfcf4f6b84155a6b15a72805", "title": "Run-mean computation from MASIN and the MetUM 2.2 km from the Iceland Greenland Sea's Project (IGP) field campaign", "abstract": "Each long-run leg is divided into 150-second (~9 km) sections (\"runs\"), over which the flight data is averaged and fluxes are derived. The distance 9 km was chosen as analysis from the Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) project showed this length to be optimal for sampling turbulence over sea ice (i.e. the minimum length required to sample the dominant turbulent length scales - the larger the run length the more likely the calculated fluxes are to be influenced by mesoscale circulations and broad changes in surface characteristics, and the fewer data points will be got)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40387, "uuid": "c90708df097c4e0aa97655e275647317", "title": "CESM2-CAM6 model deployed at NCAR", "abstract": "This data was produced by the CESM2-CAM6 model run by scientists at NCAR for the SNAPSI project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40616, "uuid": "b53ab401d94b4ba0896bc1b17a320bbe", "title": "GlobAlbedo processing chain", "abstract": "The GlobAlbedo project aims at generating multi-sensor multi-annual global land surface albedo products. MERIS and SPOT-VGT level-1 data serves as input data to a processing chain. The function of the processing chain can be summarised as:\r\n processes every single input to some level in several processing steps.\r\n accumulates at least one year of data for each 10º x 10º tile and then calculates products every 8 days as well as every month, as well as seasonal and annual products.\r\n finally retrieves BRDF and albedo for each composite reporting time-step (every 8 days and every month, as well as seasonal and annual products).\r\nFirstly, all inputs are systematically processed from L1 to surface directional reflectances\r\n(SDR). The processing steps to retrieve SDRs are:\r\n pixel classification for cloud, water, etc.. detection\r\n retrieval of aerosol optical thickness\r\n atmospheric correction using retrieved aerosol optical thickness\r\nThe results are SDR values in the same granularity as the inputs. They are not written for distinct products, but just kept in memory and used as input to the next part of the processing chain. The processing steps are\r\n broad-band integration of these SDRs\r\n re-projection of these broad-band SDRs onto the MODIS Sinusoidal grid\r\nThe results of this step are re-projected broadband directional reflectances (BBDR) still in the granularity of the input products. During implementation, it has been decided to store this intermediate product of BBDR tiles on disk, but to remove them subsequently after the BRDF computation (accumulation/inversion). The steps are:\r\n computation of BRDFs every 8-days and every month of the broad-band BBDRs from all sensors by accumulation method, using an additional land cover mask information from Idepix\r\n computation of the albedo from these BRDFs\r\nThe final results are 8-day, monthly, seasonal, and annual composites of broadband\r\nalbedo. \r\nFor more information on the processing please see the product user guide and the ATBD in the docs tab.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40634, "uuid": "048e6ac7c94f41c99164b19127855ca0", "title": "Yellowscan CloudStation computation for UAV Paracou", "abstract": "Export of raw LAS points with Yellowscan CloudStation software, with line adjustment option.Improvement of inter-line matching using BayesMap software (to account for a defect in roll angle of the scanner). Merging and processing of each flight with Lastools software (PC classification with lasground using options -step 15 -wilderness, generation of DTM, DSM and CHM at 1m resolution)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40640, "uuid": "361d0f25744840e5bfec5838e2787ace", "title": "JRC-TOC FAPAR Computation", "abstract": "Look Up Table (LUT) of bidirectional reflectance factors (BRF) representing the AVHRR\r\nNOAA like data are created using the physically-based semi-discrete model of Gobron\r\net al. (1997) to represent the spectral and directional reflectance of horizontally homogeneous plant canopies, as well as to compute the values of FAPAR in each of them.\r\nThe sampling of the vegetation parameters and angular values were chosen to cover a\r\nwide range of environmental conditions. These simulations constitute the basic information used to optimise the formulae. The sampling selected to generate the LUT has\r\nbeen chosen so as to generate a robust global FAPAR algorithm.\r\nOnce this LUT was created, the design of the algorithm consisted in defining the mathematical combination of spectral bands which will best account for the variations of\r\nthe variable of interest (here, FAPAR) on the basis of (simulated) measurements, while\r\nminimising the effect of perturbing factors such as angular effects.\r\nIn the case of bare soil simulations, the Hapke modified soil model of Pinty et al. (1989)\r\nis used with a fixed hot-spot parameter equal to 0.2 and an asymmetry factor equal to\r\n-0.1. The soil data required to specify the lower boundary condition in this model were\r\ntaken from Price (1995). The value of single albedo, for each spectral bands, have been\r\ninverted to obtain the same albedo value as the lambertian assumption is made.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40644, "uuid": "fe462053516f45cca693eda49ccce2d2", "title": "Natural Environment Research Council (NERC) running: experiment volc-pinatubo-full using the UKESM1-0-LL model.", "abstract": "Natural Environment Research Council (NERC) running the \"Pinatubo experiment\" (volc-pinatubo-full) experiment using the UKESM1-0-LL model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, NERC, UKESM1-0-LL, volc-pinatubo-full, AERmon, AERmonZ, Amon, CFday, Eday, EdayZ, Emon, EmonZ, LImon, Lmon, Omon, SIday, SImon, day", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40769, "uuid": "0177eeaec34b43a381345b398f491607", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative, v08.1", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40782, "uuid": "5d12b39a20894334b676bfd237d53236", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative, v07.1", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40831, "uuid": "6964b241bde743c99aa48ef826e2c561", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40883, "uuid": "365ad30b726e4e24ac3e62e9ce6253ee", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40886, "uuid": "2f20786192f34c35b676bf12e8fee01a", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40889, "uuid": "57242b1d7dc540b68f22fbb5379c9b29", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40892, "uuid": "3ff6dd269b0343a8bc4882c607159bb4", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40895, "uuid": "70f07f177ac143569b0ddef73d45fa94", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40898, "uuid": "ca8fe0de2705439697042595beaa8b3f", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40902, "uuid": "47c7c598ef3f4831b14bad3db6bc2656", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40905, "uuid": "1492fbd37dcc40839fb2a28dc6b1b47d", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40908, "uuid": "35fa4ae7d506422fb00d865481d8e72e", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40918, "uuid": "b639c26d0a504375a46f328867cf0efa", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40921, "uuid": "6a213edd00974bb0beafc6adca72959e", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40924, "uuid": "d1856fb8d7c34853b31eefd0ac92f883", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40928, "uuid": "8b0143be3e8744d897e1d304daddeeb5", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40931, "uuid": "80204eb5e68f45cbb4a0242f171e22b4", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40934, "uuid": "909c8c0547254b26859318ccd5dde5d3", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40937, "uuid": "9cb29ddcef2b4bdea5fed353b08cd678", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40940, "uuid": "681eb40e35324c219dcb7e7e55b95fde", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40943, "uuid": "18a6a1d5408f401a8264ffc72b2e49b2", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40946, "uuid": "a2617b07f8504cbeb1396b24d9f009f4", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40949, "uuid": "e85f9e505d634d2b81c595567bb26c6a", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40952, "uuid": "ac49c510137c4e22a222de25e526c6d8", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40955, "uuid": "1eff24731ee746f3885061705d3c2c02", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 40958, "uuid": "793cf4d544c04c7db0e9faa45a0ca652", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12869/?format=api" ] }, { "ob_id": 40963, "uuid": "28a22dee3c9a43939a99bd7b6cb05d3c", "title": "Hadley Centre Hadley Centre Coupled Model Version 3", "abstract": "The Hadley Centre Hadley Centre Coupled Model Version 3 was developed from the earlier HadCM2 model in the period 1997-2000. Various improvements were applied to the 19 level atmosphere model and the 20 level ocean model and as a result the model requires no artificial flux adjustments to prevent excessive climate drift. The atmosphere and ocean exchange information once per day, heat and water fluxes being conserved exactly. The main differences from the previous HadCM2 model are a significantly more sophisticated radiation scheme; the inclusion of the direct impact of convection on momentum; and the inclusion of a new land surface scheme that includes a better representation of evaporation, freezing and melting of soil moisture. It improved on the resolution available from previous Hadley Centre models and included support for interactive couplings between the atmosphere and ocean and the biosphere, atmospheric chemistry, the sulphur cycle and atmospheric aerosols. The HadCM3 model was used by the Hadley Centre to provide input for the IPCC Third Assessment Report.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41077, "uuid": "af799f18cd78484b934f842002d69447", "title": "CCCma CanESM5 Model", "abstract": "The underlying data was produced by the CanESM5 model at the Canadian Centre for Climate Modelling and Analysis (CCCma) for the SNAPSI project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41196, "uuid": "449c965c9157499499a4803580d36220", "title": "Met Office Hadley Centre (MOHC) running: experiment hist-totalO3 using the HadGEM3-GC31-LL model.", "abstract": "Met Office Hadley Centre (MOHC) running the \"historical total ozone-only run\" (hist-totalO3) experiment using the HadGEM3-GC31-LL model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, MOHC, HadGEM3-GC31-LL, hist-totalO3, Amon, Emon, EmonZ, LImon, Lmon, Omon, SImon, day", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41199, "uuid": "14b68a8d460842bea039f732d7bf8284", "title": "Met Office Hadley Centre (MOHC) running: experiment hist-volc using the HadGEM3-GC31-LL model.", "abstract": "Met Office Hadley Centre (MOHC) running the \"historical volcanic-only run\" (hist-volc) experiment using the HadGEM3-GC31-LL model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, MOHC, HadGEM3-GC31-LL, hist-volc, Amon, Emon, EmonZ, LImon, Lmon, Omon, SImon, day", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41201, "uuid": "c6d943bdefe34a19a1518dce9a6843e2", "title": "TCCON GGG2020 Retrieval algorithm", "abstract": "The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers that record direct solar absorption spectra of the atmosphere in the near-infrared. From these spectra, accurate and precise column-averaged abundances of atmospheric constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. The TCCON GGG2020 Data Version is produced using the algorithm as described in the preprint 'The Total Carbon Column Observing Network's GGG2020 Data Version'. Please see the following for more information: https://essd.copernicus.org/preprints/essd-2023-331/.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41215, "uuid": "63273e9e0da44216ba0e6323dc0ef9b8", "title": "OptiSAIL retrieval", "abstract": "The retrieval model OptiSAIL is built around the established components 4SAILH (Scattering of Arbitrarily Inclined Leaves, with 4-stream extension and hot-spot), PROSPECT-D (simulation of leaf spectra, version D including senescence; Féret et al., 2017), TARTES (Two-streAm Radiative Transfer in Snow; Libois et al., 2013), with the addition of an empirical soil reflectance model, a semi-empirical soil moisture model (Philpot, 2010), the Ross-Thick-Li-Sparse BRDF model, and a cloud contamination simulation.", "keywords": "OptiSAIL, canopy, LAI, fAPAR", "inputDescription": null, "outputDescription": null, "softwareReference": 41220, "identifier_set": [] }, { "ob_id": 41221, "uuid": "6351abfd60bd4bb6b2488b2862c4b925", "title": "test compo", "abstract": "compo", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41224, "uuid": "366e9234490b4c80ba4695144fe2e1b7", "title": "NRL NAVGEM model", "abstract": "The underlying data was produced by the NRL NAVGEM model for the SNAPSI project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41253, "uuid": "6c4085cf959b40d193f7152f0d3b22d5", "title": "Processing chain for the GERB-HR-ED01-1-1 rlut 1hrCM Obs4MIPS v1.1 product,", "abstract": "The GERB TOA outgoing longwave radiation (OLR) Obs4MIPs product has been generated from GERB level 2 HR OLR fluxes. There are four main stages. The first ingests the Edition 1 GERB HR OLR data and generates an area weighted flux product at 1° by 1° spatial resolution for every 15-minute time interval. In the second stage these data are averaged over time to produce an hourly averaged product. Each hour interval is defined as the time-centred mean at half-past the hour, e.g. 1030 UTC, comprises the mean of data from 1000 UTC, 1015 UTC, 1030 UTC and 1045 UTC (or from those slots in this window that are available). An hourly average is produced for a 1° by 1° grid cell if there is at least one of the four observation times available for that grid cell. If no available data are available for a particular hour of a day, then the third stage is implemented, and these hours are filled using broadband fluxes derived from the narrowband SEVIRI data corrected to the GERB observations at the monthly hourly 1° scale1. The final processing stage averages the hourly mean fluxes over the days in the month to produce a one degree monthly hourly mean product. The number of filled data points (days per monthly hourly mean) contributing to each monthly mean are used to estimate the uncertainties associated with the product. For more detailed information please see: Bantges, R., Russell, J., & Brindley, H. (2023). GERB-HR-ED01 rlut 1hrCM v1.1. Zenodo. https://doi.org/10.5281/zenodo.10034430.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41254, "uuid": "8f43f9ab978a47aabf828e68bc4f5806", "title": "Processing chain for the GERB-HR-ED01-1-1 rsut 1hrCM Obs4MIPS v1.1 product,", "abstract": "The GERB TOA reflected shortwave radiation (RSW) Obs4MIPs product has been generated from GERB level 2 HR RSW fluxes. There are five main stages. The first is to take the Edition 1 GERB HR SW flux data with the user corrections applied and generate an albedo using knowledge of the incoming SW flux for each location and time. The albedo is then area weighted to create a 1° by 1° spatial resolution albedo for every 15-minute time interval. These data are then averaged over time to produce an hourly averaged albedo product for each hour of each day. Each hour interval is defined as the time-centred mean at half-past the hour, e.g. 1030 UTC comprises the mean of albedos from 1000 UTC, 1015 UTC, 1030 UTC and 1045 UTC (or from those slots in this window that are available). An hourly average albedo is produced for a 1° by 1° grid cell if there is one or more observation from the four observation times available for that grid cell. The averaged albedos are converted back to RSW flux using the incoming solar flux at the midpoint of the hour and 1° cell. The fourth stage identifies days where there are no observations available for the hour and fills them with broadband RSW fluxes derived from the narrowband SEVIRI data, averaged to the daily hourly scale in the same way as the GERB data and corrected to the GERB observations at the monthly hourly 1° scale1. Finally, a monthly mean for each hourly time step is calculated encompassing the full data. The number of filled data points (days per monthly hourly average) contributing to each monthly hourly mean are used to estimate the uncertainties associated with the product. For more detailed information please see: Bantges, R., Russell, J., & Brindley, H. (2023). GERB-HR-ED01 rsut 1hrCM v1.1. Zenodo. https://doi.org/10.5281/zenodo.10034410.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41261, "uuid": "0ee4dc348b3943babe9b19b5a4bf865f", "title": "Met Office Hadley Centre (MOHC) running: experiment hist-sol using the HadGEM3-GC31-LL model.", "abstract": "Met Office Hadley Centre (MOHC) running the \"historical solar-only run\" (hist-sol) experiment using the HadGEM3-GC31-LL model. See linked documentation for available information for each component.", "keywords": "CMIP6, WCRP, climate change, MOHC, HadGEM3-GC31-LL, hist-sol, Amon, Emon, EmonZ, LImon, Lmon, Omon, SImon, day", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41369, "uuid": "8fb75140be014c36923b9307335fc48f", "title": "Computation for the ESA High Resolution Land Cover Climate Change Initiative (High_Resolution_Land_Cover_cci): High Resolution Land Cover Map for Amazonia at 10m spatial resolution for 2019, v1", "abstract": "For information on the derivation of the ESA CCI High Resolution Land Cover Map for Amazonia at 10m spatial resolution for 2019, v1 product see the linked project documentation on the CCI website.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41370, "uuid": "0d3896db10ac4e659db5115b8fa645f3", "title": "Computation for the ESA High Resolution Land Cover Climate Change Initiative (High_Resolution_Land_Cover_cci): High Resolution Land Cover Map for Siberia at 10m spatial resolution for 2019, v1", "abstract": "For information on the derivation of the ESA CCI High Resolution Land Cover Map for Siberia at 10m spatial resolution for 2019, v1 product see the linked project documentation on the CCI website.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41371, "uuid": "9c29d5c4fdca44eba4122417a28ad211", "title": "Computation for the ESA High Resolution Land Cover Climate Change Initiative (High_Resolution_Land_Cover_cci): High Resolution Land Cover and Land Cover Change Maps for Amazonia at 30m spatial resolution, 1990-2019, v1", "abstract": "For information on the derivation of the ESA CCI High Resolution Land Cover and Land Cover Change Maps for Amazonia at 30m spatial resolution, 1990-2019, v1 product see the linked project documentation on the CCI website.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41372, "uuid": "c64308936d94431daef88d04f8f38b13", "title": "Computation for the ESA High Resolution Land Cover Climate Change Initiative (High_Resolution_Land_Cover_cci): High Resolution Land Cover and Land Cover Change Maps for Siberia at 30m spatial resolution, 1990-2019, v1", "abstract": "For information on the derivation of the ESA CCI High Resolution Land Cover and Land Cover Change Maps for Siberia at 30m spatial resolution, 1990-2019, v1 product see the linked project documentation on the CCI website.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41417, "uuid": "722a203405214ccfb77e27ff9b307801", "title": "Computation for ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Retrieval of sea-ice thickness from radar altimetry data", "abstract": "The method used to extract sea-ice thickness from radar altimetry data is based on the\r\npioneering work of Peacock and Laxon, 2004; Laxon et al., 2003 for the ERS-2 mission. The\r\nmethod involves separating the radar echoes returning from the ice floes from those\r\nreturning from the sea surface in the leads between the floes. This step of a surface-type\r\nclassification is crucial and allows for a separate determination of the ice floe and\r\nsea-surface heights. The freeboard that is the elevation of the ice upper side (or ice/snow\r\ninterface) above the sea level can then be computed by deducting the interpolated\r\nsea-surface height at the floe location from the height of the floe. Sea-ice thickness can then\r\nbe calculated from the sea-ice freeboard with the additional information of the snow load.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41436, "uuid": "e30c1e20f6fd4b96a33b4f9a9ceb2fa5", "title": "Fixed concentration experiments with UKESM1-0-LL", "abstract": "The external forcings for each simulation are held at the level they were at in a parent ScenarioMIP simulation at the time the simulations are branched off. In the case of GHGs, that corresponds to constant concentrations and for anthropogenic aerosols it corresponds to constant emissions. The vegetation is dynamic, but each grid cell has a prescribed crop and pasture fraction based on the conditions of their parent simulations at the point of branching-off. Solar and volcanic forcing are set to the forcings used in the pre-industrial control simulations. All simulations are branched from the first initial condition realisation of the parent ScenarioMIP experiment (r1i1p1f2 in CMIP6 nomenclature).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41446, "uuid": "793181872832428784ce64c01fc0f2da", "title": "Derivation of the CH4_S5P_WFMD v1.8 product from the WFM-DOAS Retrieval algorithm", "abstract": "The Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) algorithm is a least-squares retrieval method based on scaling (or shifting) pre-selected atmospheric vertical profiles. The column-averaged dry air mole fractions of methane (denoted XCH4) are derived from the vertical column amounts of methane by normalising with the dry air column, which is obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5). The corresponding vertical columns of CH4 are retrieved from the measured sun-normalised radiance using spectral fitting windows in the SWIR spectral region (2311-2315.5 nm and 2320-2338 nm).\r\n\r\nFor further details see the documentation section.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41450, "uuid": "a56cd2b6603f4c9c97c70da8d5d4e9e4", "title": "Derivation of the ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area products, v1.1", "abstract": "For more information see the documentation at https://climate.esa.int/en/projects/fire/", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41455, "uuid": "e852d5caed0d40f7ad78432f9b42f9a4", "title": "Computation of Permafrost v4 datsets by the ESA Permafrost CCI", "abstract": "Complementing ground-based monitoring networks, the Permafrost CCI project is establishing Earth Observation (EO) based products for the permafrost ECV spanning the last two decades. Since ground temperature and thaw depth cannot be directly observed from space-borne sensors, a variety of satellite and reanalysis data are combined in a ground thermal model. The algorithm uses remotely sensed data sets of Land Surface Temperature (MODIS LST/ ESA LST CCI) and landcover (ESA Landcover CCI) to drive the transient permafrost model CryoGrid, which yields thaw depth and ground temperature at various depths, while ground temperature forms the basis for permafrost fraction. The Land Surface Temperature data sets are employed to determine the upper boundary condition of the differential equation, while its coefficients (e.g. heat capacity and thermal conductivity) are selected according to the landcover information (Westermann et al., 2017). With this, a spatial resolution of the final product of 1 km is possible, corresponding to “breakthrough” according to the WMO OSCAR database.\r\n\r\nInput data: MODIS Land surface temperature is used as the main input for the L4 production for 2003-2021 data. Sensors of auxiliary data are listed in the meta data.\r\nDownscaled and bias corrected ERA reanalyses data based on statistics of the overlap period between ERA reanalysis and MODIS LST are used for data before 2003. Sensors of auxiliary data are listed in the meta data.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41463, "uuid": "a9f25aea12554048bdc4953587accf32", "title": "Derivation of the ESA Climate Change Initiative River Discharge Water Level product, v1.1", "abstract": "For information on the derivation of the Water Level dataset see the project documentation \r\n(https://climate.esa.int/projects/river-discharge)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41472, "uuid": "25b5bb0543104b5cb2570c40f3f511e0", "title": "RegCM4", "abstract": "Regional Climate Modelling with RegCM4\r\nRegCM-4.9.2 is a regional climate model (Giorgi et al 2012) that has been extensively used in Borneo and South East Asia (Gao and Giorgi 2017, Ngo‐Duc et al 2017, Juneng et al 2016, Chung et al 2018, Cruz et al 2017, WANG et al 2020, Jadmiko et al 2017) and for simulations of deforestation effects in India (Lodh 2017), the Amazon (Llopart et al 2018) and other regions.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41489, "uuid": "151eb837a9464275b8c54f158f8bc13b", "title": "The SRON-RemoTeC algorithm used to generate the CO2_GO2_SRFP and CH4_GO2_SRFP (SRON Full Physics) v2.0.2 products.", "abstract": "The SRON-RemoTeC retrieval algorithm retrieves column-averaged methane and carbon dioxide using a 'Full Physics' retrieval technique. \r\n\r\nDetails of the technical aspects of the retrievals can be found in the ATBD (see documentation links)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41492, "uuid": "a572a6dd688e4d5c8e03318eb9c1bdae", "title": "The SRON-RemoTeC algorithm used to generate the CH4_GO2_SRPR (SRON Proxy) v2.0.2 product.", "abstract": "The SRON-RemoTeC retrieval algorithm retrieves column-averaged methane using a 'Proxy' retrieval technique. \r\n\r\n\r\nDetails of the technical aspects of the retrievals can be found in the ATBD (see documentation links)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41497, "uuid": "4bb0a4b1e21d489e8ccb5eadd85330cb", "title": "Computation process for: Deforestation and Climate Change scenarios with a regional climate model over Borneo (2005 – 2100). and RegCM4.", "abstract": "This computation produced simulations of the climate scenario RCP8.5 with and without total deforestation using regional climate model RegCM4. The output was then used for calculations of the Fire Weather Index, and that data is also included.\r\nThe data is in two main formats: netcdf files from the regional climate model, and the txt files with Fire Weather Index.\r\nThe time periods covered are:\r\n2010 – 2029 RCP8.5, Control Land cover\r\n2010 – 2029 RCP8.5, Deforested Land cover\r\n2081 – 2099 RCP8.5, Control Land cover\r\n2081 – 2099 RCP8.5, Deforested Land cover\r\nThe last 15 years of each simulation was used. Each simulation was run for each initial conditions and boundary conditions of the models: HadGEM2-ES, MPI-ESM-MR, CSIRO-MK36, IPSL-CM5A-LR, CNRM-CM5, CanESM2, giving a total of 24 simulations.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41527, "uuid": "6527ec3db937453da915c0bad26d8bc3", "title": "Delft3D 4", "abstract": "Delft3D numerically models hydrodynamics, waves, and sediment transport processes (amongst others).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41570, "uuid": "4d536da9cce344a58056e974001e86cb", "title": "Derivation of the CCI SST Climatology v3 product", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative: Climatology, v3 product was derived from the SST CCI analysis data for the period 1991 to 2020 (30 years).\r\n\r\nFor more information see the SST CCI project documentation", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41572, "uuid": "dcabd9408c9f42888c11746895d7ce09", "title": "Derivation of the CCI SST Analysis v3 product", "abstract": "For information on the derivation of the SST CCI Analysis v3 product, see the SST CCI project documentation", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41575, "uuid": "008b9792168a4cb087393d56aad63e16", "title": "Derivation of the ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Microwave Scanning Radiometer (AMSR) Level 2 Pre-processed (L2P) product, version 3.0", "abstract": "For information on the derivation of the SST CCI AMSR L2P product, see the SST CCI project documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41578, "uuid": "1635572279d7444b875f1154c0bb84ff", "title": "Grid-to-Grid hydrological model", "abstract": "The Grid-to-Grid model (G2G: (Bell et al., 2009)) is a grid-based, spatially distributed hydrological model which has recently been enhanced to take account of recorded monthly abstractions and annual discharges (Rameshwaran et al., 2022). While in practice hydrological modelling has been undertaken for mainland Britain, model estimates for AI-impacted catchments are only available for English catchments, albeit with a modest overlap of the Welsh border.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41579, "uuid": "900a6108c0694a33ad51684d10f58104", "title": "Grid-to-Grid model", "abstract": "The Grid-to-Grid (G2G) is a national-scale grid-based hydrological model which typically operates on a 1km x 1km grid at a 15-minute time-step (Bell et al. 2009), with an optional snow module (Bell et al. 2016). It was originally configured to cover Great Britain (GB) and output natural river flows, but more was more recently extended to cover Northern Ireland (NI), and to take account of anthropogenic influences (abstractions and discharges) where available.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41580, "uuid": "5a5c336989254054b93957c17123f247", "title": "Grid-to-Grid Model", "abstract": "The Grid-to-Grid (G2G) is a national-scale grid-based hydrological model which typically operates on a 1km x 1km grid at a 15-minute time-step (Bell et al. 2009). It was originally configured to cover Great Britain (GB) and output natural river flows, but was more recently extended to cover Northern Ireland (NI), and to take account of anthropogenic influences (abstractions and discharges) where available (Rameshwaran et al. 2022).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41591, "uuid": "268a914f6bfc4d66bf3c68aab16dc437", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV)", "abstract": "Numerical Weather Prediction (NWP) met data was produced by the operational UKV (United Kingdom Variable-resolution) configuration of the Met Office Unified Model.The files contain a basic collection of model-level fields (3-d winds, temperature, etc.) and a selection of single-level fields including mean sea level pressure, cloud and precipitation from the inner, fixed-resolution domain of the UKV model (this covers the UK area at a spatial resolution of 1.5 km). The UKV model uses a rotated-pole coordinate system. ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41595, "uuid": "0e8c2709eb394582849b4855dc7282c4", "title": "Met Office Unified Model global met data", "abstract": "Numerical Weather Prediction (NWP) global met data was produced by the Met Office Unified Model. The files contain a basic collection of model-level fields (3-d winds, temperature, etc.) and a selection of single-level fields including mean sea level pressure, cloud and precipitation.", "keywords": "NAME, NWP, atmospheric dispersion, Numerical Weather Prediction, UM", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41621, "uuid": "6666ae0ed0e94bfda0c302f0fe5bec1b", "title": "The ESA Biomass Climate Change Initiative above ground biomass retrieval algorithm, v5.0", "abstract": "For information on the derivation of the Biomass CCI data, please see the ATBD (Algorithm Theoretical Baseline Document).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41648, "uuid": "c7177c0c7a5448bbbb76dd71bf04509a", "title": "CCI SST Processor v3", "abstract": "For more information on the derivation of the CCI SST v3 datasets see the Algorithm Theoretical Baseline Document (ATBD) at https://climate.esa.int/documents/2367/SST_CCI_D2.1_ATBD_v3.1-signed.pdf", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41668, "uuid": "4e0c93f090dc4b759de8ead14724a35b", "title": "Computation for Wind-Driven Rain", "abstract": "Wind-driven rain is calculated from hourly weather and climate data using an industry-standard formula from ISO 15927–3:2009, which is based on the product of wind speed and rainfall totals. Wind-driven rain is only calculated if the wind would strike a given wall orientation. A wind-driven rain spell is defined as a wet period separated by at least 96 hours with little or no rain (below a threshold of 0.001 litres per m2 per hour).\r\n\r\nThe annual index of wind-driven rain is calculated for a baseline (historical) period of 1981-2000 (corresponding to 0.61°C warming) and for global warming levels of 2.0°C and 4.0°C above the pre-industrial period (defined as 1850-1900). The warming between the pre-industrial period and baseline is the average value from six datasets of global mean temperatures available on the Met Office Climate Dashboard: https://climate.metoffice.cloud/dashboard.html.\r\n\r\nThe magnitudes of 1 in 3 year wind-driven rain spells (i.e. wet spells that would be expected to occur, on average, once every three years) were calculated for the baseline period (1981-2000) and 20-year periods corresponding to 2°C and 4°C of warming. The magnitudes of all wet spells (here, sum of hourly values of the wind-driven rain metric, I) were calculated, and the largest wet spell in each year was found (in the accompanying report, the magnitude of a wet spell is given the symbol Is' [\"Is prime\"] and has units of litres per metre-squared per spell). For each time period, the largest spells in all years and ensemble members were pooled together. A Gumbel distribution was fitted to the pooled data and used to estimate the magnitude of the 1 in 3 year wet spells across the UK.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41673, "uuid": "a95bed741dd3456db375a0234ceaf4f1", "title": "Computation for elevation change grids of Greenland's periphery for the years 1978, 1981, 1985 and 1987.", "abstract": "ArcticDEM mosaic accessed and exported from Google Earth Engine at 2m and resampled (bilinear) to 30m\r\nAeroDEM data downloaded from NCEI site and resampled to 30m resolution Bilinear) https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:0145405 \r\n\r\nCoregistration conducted using the DEMcoreg python scripts of David Shean https://github.com/dshean/demcoreg", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41676, "uuid": "09f4596ecbfc40bf8380b2825ceb0a26", "title": "ECMWF IFS cycle 43r1", "abstract": "", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41686, "uuid": "babbced62c8d448b863e8df64694c84b", "title": "Machine Learning Calving Front locations derived by the ESA Greenland Ice Sheets Climate Change Initiative project.", "abstract": "The CFL product is generated by a deep learning-based model using optical satellite imagery (Sentinel-2). The digitized calving front is stored as vector lines in standard GeoJSON files. Additionally, metadata information on the sensor and processing steps are stored in corresponding attributes in the GeoJSON files. GeoJSON is an open standard format designed for representing simple geographical features (points, line strings, polygons, and collections), along with their non-spatial attributes.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41763, "uuid": "fcc7fa9edc9241da89946c18d4707438", "title": "Met Office Hadley Centre (MOHC) running: experiment hist-piAer using the HadGEM3-GC31-LL model.", "abstract": "Met Office Hadley Centre (MOHC) running the \"hist-piAer\" experiment using the HadGEM3-GC31-LL model. See linked documentation for available information for each component.", "keywords": "CMIP, CMIP6Plus, WCRP, climate change, MOHC, HadGEM3-GC31-LL, hist-piAer, APday", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 41961, "uuid": "cefe18e177704799b6f8b8171057704e", "title": "ESA Snow Climate Change Initiative (snow_cci): SWE, v3", "abstract": "The snow_cci SWE product has been based on the ESA GlobSnow SWE retrieval approach (Takala et al. 2011). The retrieval is based on passive microwave radiometer (PMR) data considering the change of brightness temperature due to different snow depth, snow density, grain size and more. The retrieval algorithm handles data from the sensors SMMR, SSM/I, SSMIS, AMSR-E and AMSR-2. The retrieval methodology combines the satellite passive microwave radiometer (PMR) measurements with ground-based synoptic weather station observations by Bayesian non-linear iterative assimilation. A background snow-depth field from re-gridded surface snow-depth observations and a passive microwave emission model are required components of the retrieval scheme. The GlobSnow algorithm implemented for snow_cci version 3 includes the utilisation of an advanced emission model with an improved forest transmissivity module and treatment of sub-grid lake ice. Because of the importance of the weather station snow-depth observations on the SWE retrieval, there is improved screening for consistency through the time series.\r\n\r\nPassive microwave radiometer data are obtained from the recalibrated enhanced resolution CETB ESDR dataset (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) https://nsidc.org/pmesdr/data/) Algorithm improvements relative to snow_cci v2.0 include improved dry snow detection due to an update of the dry snow detection algorithm, improved SWE retrieval due to implementation of dynamic snow densitites into the retrieval, and improved snow masking, due to an update of the snow mask used for post-processing. The time series has been extended from snow_cci version 2 by two years with data from 2020 to 2022 added.\r\n\r\nSWE products are based on SMMR, SSM/I and SSMIS passive microwave radiometer data for non-alpine regions of the Northern Hemisphere.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 42315, "uuid": "142bd054c1544b1698077ccf8904d273", "title": "Computation for: C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0", "abstract": "The C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0 dataset was generated by combining measurements from several nadir-viewing satellite sensors (GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura, GOME-2/MetOp-A, GOME-2/MetOp-B, TROPOMI/Sentinel-5P, and GOME-2/MetOp-C) into one single cohesive record. This was done using a merging approach developed in the framework of the European Space Agency's (ESA's) Climate Change Initiative Ozone project. Firstly, the separate pixel-based level-2 observation - produced by the GOME-type Direct FITting v4 retrieval algorithm (GODFIT) are converted into level-3 products per sensor i.e. daily and monthly averages on a regular grid of 1x1 degree in latitude and longitude. Before the individual level-3 data records are finally merged into one single product, adjustments are applied in order to minimize possible inter-sensor biases and/or temporal drifts. Due to its notable long-term stability one sensor (OMI/Aura) was selected to serve as a reference for the other instruments, which are then adjusted in terms of a correction that depends on latitude and time. A detailed description of the merging approach, the generation, and the geophysical validation of GTO-ECV is provided in Coldewey-Egbers et al. (2015, 2022), Garane et al. (2018) and Lambert et al. (2022).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 42317, "uuid": "f42a371c84c243e291507a439138f548", "title": "Model contributions to DeepMIP", "abstract": "35 climate model simulations were run from nine coupled climate models (CESM1.2-CAM5, COSMOS-landveg-r2413, GFDL-CM2.1, HadCM3B-M2.1aN, HadCM3BL-M2.1aN, INM-CM4-8, IPSLCM5A2, MIROC4m and NorESM1-F) that have carried out coordinated simulations as part of the Deep-Time Model Intercomparison Project (DeepMIP).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 42319, "uuid": "66b1679c46ef49fdadc0c0c1a590ce63", "title": "Computation for Greenland 1980 and 2010s landcover grids from Landsat 5 and Landsat 8", "abstract": "the tif grids were produced using Google Earth Engine. All summer Landsat imagery was filtered by metadata, followed by topographical correction, resulting in a best-pixel mosaic for Greenland's periphery. Band ratios (NDSI, NDVI, NDWI) were computed and stacked with visible, NIR, and SWIR bands. A principal component analysis was conducted, retaining the first six principal components as bands, which were subsequently classified using a K-means clusterer and refined with a supervised random-forest classifier and a slope threshold was applied to discriminate shadows from dark water bodies more effective.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 42339, "uuid": "6f52e38ef1c84008b5f135015f870b35", "title": "RAL Ozone Profile Algorithm", "abstract": "The RAL retrieval scheme derives profiles of number density on a set of pressure levels, spaced approximately every 4-6 km in altitude (taken from the SPARC-DI grid). The optimal estimation method is used. Averaging kernels are provided on this basis. It is noted that the vertical resolution of the retrieval is relatively coarse compared to the vertical grid and that tropospheric levels in particular have significant bias towards the assumed a priori state. It is therefore important to take account of the characterisation of the retrieval provided by the averaging kernels when comparing these results to other data-sets, particularly where those are more highly vertically resolved.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43008, "uuid": "6d9b55418ae34e2da24ed56008d3dd13", "title": "Computation for Andes glaciers and ice caps outlines during the Little Ice Age (LIA)", "abstract": "This computation took Randolph Glacier Inventory version 6 (RGI_v6) outlines and reshaped them to the extent interpreted to best represent the Little Ice Age (LIA). The output was shape files.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43011, "uuid": "454b933b67204ab189e2c1d98a59fb0c", "title": "EMEP4UK", "abstract": "The EMEP4UK model is an off-line atmospheric chemistry transport model based on the EMEP MSC-W model (www.emep.int) The model, termed EMEP4UK, is capable of representing the UK hourly atmospheric composition at a horizontal scale ranging from 100 km to 1 km. The Weather Research Forecast (WRF) model was used as the main meteorological driver (https://www2.mmm.ucar.edu/wrf/users/).\r\nModel website: http://www.emep4uk.ceh.ac.uk/", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43039, "uuid": "960ba0d151c048b5bd3fa19d0f274390", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative, v09.1", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43043, "uuid": "dbc82a13416647ffba38688918acf3dd", "title": "Catchment metrics were calculated from daily flow datasets from two hydrological models: SHETRAN and HBV.", "abstract": "Catchment metrics were calculated from daily flow datasets from two hydrological models: SHETRAN and HBV. Both models were developed using historical data and then driven using bias corrected Met Office UKCP18 datasets to simulate river flows under climate change scenarios. Two different land use changes were applied: (1) natural flood management (provided by Sayers and Partners) and (2) storylined urban development (Provided by the Urban Development Model team at Newcastle University).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43044, "uuid": "75ca674d027d47b887190d55e9302408", "title": "Daily flows were simulated by two hydrological models: SHETRAN and HBV", "abstract": "Daily flows were simulated by two hydrological models: SHETRAN and HBV. Both models were developed using historical data and then driven using bias corrected Met Office UKCP18 datasets to simulate river flows under climate change scenarios. Two different land use changes were applied: (1) natural flood management (provided by Sayers and Partners) and (2) storylined urban development (Provided by the Urban Development Model team at Newcastle University).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43053, "uuid": "a2fc28adb5724014af898b19e4e24cb1", "title": "Computation for the ESA River Discharge Climate Change Initiative (RD_cci): Altimetry-based River Discharge product, v1.0", "abstract": "Long-term satellite river discharge (RD) time series have been derived at specified locations[1], utilizing the methodology outlined in detail in [2]. \r\n\r\nIn this context, river discharge represents the discharge in cubic meters per second (m3/s) obtained through the rating curve computation facilitated by in-situ discharge and water surface elevation (WSE) merged time series, as computed in [2] over the calibration period (individually defined for each station and summarized in the ATBD [3])\r\n\r\n[1] D.2 Selection of river basins. CCI River Discharge precursor project Document (CCI-Discharge-0004-RP_WP2, Issue 1.0)\r\n[2] D.3. Water Surface Elevation (WL) Algorithm Theoretical Basis Document (ATBD) (CCI-Discharge-0005-ATBD_WL, Issue 1.1)\r\n[3] D.3. River Discharge (Q) from Altimeters and Ancillary data, multispectral images and data combination - Algorithm Theoretical Basis Document (ATBD) (CCI-Discharge-0012-ATBD, Issue 1.1)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43055, "uuid": "56788876eb1a439d9937166ae2c59867", "title": "CityCAT - City Catchment Analysis Tool", "abstract": "The City Catchment Analysis Tool (CityCAT) is a 2-D hydrodynamic flood model, that models complex free-surface flow over a domain, capturing permeable and impermeable surfaces and obstacles to flow such as buildings and other man-made features.\r\n\r\nGlenis, V., Kutija, V., & Kilsby, C. G. (2018). A fully hydrodynamic urban flood modelling system representing buildings, green space and interventions. Environmental Modelling & Software, 109, 272-292. https://doi.org/10.1016/j.envsoft.2018.07.018", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43071, "uuid": "6d38a9f1b40e48b5bae587a69d1bb297", "title": "Data was generated from UKESM1, the UK Earth System Model Version 1, which is a configuration of the Met Office Unified Model. Simulations are described in Damany-Pearce et al. (2022): https://www.nature.com/articles/s41598-022-15794-3.", "abstract": "Data was generated from UKESM1, the UK Earth System Model Version 1, which is a configuration of the Met Office Unified Model. Simulations are described in Damany-Pearce et al. (2022): https://www.nature.com/articles/s41598-022-15794-3.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43079, "uuid": "b2bea2f51f024e3cbe83c1a4dbf355a5", "title": "Mass flow rate ice discharge (MFID) derived by the ESA Greenland Ice Sheets Climate Change Initiative project, v1.0", "abstract": "Ice discharge is calculated from the CCI Ice Velocity (IV) product, the CCI Surface Elevation Change (SEC) product (where it overlaps with the ice discharge gates), and ice thickness from BedMachine. Ice discharge gates are placed 10 km upstream from all marine terminating glacier termini that have baseline velocities of more than 150 m/yr. Results are summed by Zwally et al. (2012) sectors. The methods, including description of \"coverage\", are described in Mankoff et al. 2020. \r\n\r\nFor further details see the documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43081, "uuid": "ed1d0074bf064f319a9acc78e4236435", "title": "ESA Snow Climate Change Initiative: Derivation of SCFG MODIS v3.0 product.", "abstract": "The retrieval method of the Snow_cci SCFG product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFG product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm. The Snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the usage of spatially variable background reflectance and forest reflectance maps instead of global constant values for snow free land and forest, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data, and (v) the update of the global forest canopy transmissivity based on forest density from Hansen et al. (2013) and forest type layers from Land Cover CCI (Defourny, 2019) to assure in forested areas consistency of the SCFG and the SCFV CRDP v3.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/80567d38de3f4b038ee6e6e53ed1af8a) using the same retrieval approach.\r\n\r\nImprovements of the Snow_cci SCFG version 3.0 compared to the Snow_cci version 2.0 include (i) an updated classification of snow free areas and (ii) an update of the constant reflectance value for wet snow based on the analysis of time series of the MODIS reflectance at 0.55 µm. \r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFG product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. A new mask for salt lakes derived from manual delineation based on Terra MODIS data is added in the version 3.0 products from Terra MODIS. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable variable and has been adjusted to account for updates in the retrieval algorithm. Two additional variables are provided for each daily product: the sensor zenith angle per pixel in degree, and the acquisition time per pixel referring to the scan line time of the MODIS granule used for the classification.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43082, "uuid": "85d99c0af1e74b43bd2a02c11cb33a40", "title": "ESA Snow Climate Change Initiative: Derivation of SCFV MODIS v3.0 product.", "abstract": "The retrieval method of the Snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 550 nm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the Snow_cci SCFV retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the adaptation of the retrieval method using of a spatially variable ground reflectance instead of global constant values for snow free land, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data to assure in forested areas consistency of the SCFV and the SCFG CRDP v3.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/e955813b0e1a4eb7af971f923010b4a3/) using the same retrieval approach.\r\n\r\nImprovements of the Snow_cci SCFV version 3.0 compared to the Snow_cci version 2.0 include (i) an update in the pre-classification of snow free areas and (ii) an update of the constant reflectance value for wet snow based on the analysis of time series of the MODIS reflectance at 0.55 µm.\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. A new mask for salt lakes derived from manual delineation based on Terra MODIS data is added in the version 3.0 products from Terra MODIS. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable and has been adjusted to account for updates in the retrieval algorithm. Two additional variables are provided for each daily product: the sensor zenith angle per pixel in degree, and the acquisition time per pixel referring to the scan line time of the MODIS granule used for the classification.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 43083, "uuid": "c4dd70351cb74c94acd9593a80083c4f", "title": "ESA Snow Climate Change Initiative: Derivation of SCFG AVHRR v3.0 product.", "abstract": "Based on the EUMETSAT AVHRR GAC FDR (Global Area Coverage), released in May 2023, a time series (1979–2022) was generated utilising the SCAmod algorithm of Metsämäki et al. (2015). Cloud masking relies on the probability mask of CLARA-A3, an upgrade of the existing cloud albedo and radiation (CLARA) data record developed and generated by EUMETSAT CM SAF, SMHI, which has also been produced from this FDR. \r\n\r\nAs a pre-condition, (FSC (NDSI) > 5%) was implemented based on Normalized Difference Snow Index (NDSI) calculations (Salomonson and Appel, 2006) before utilising the SCAmod algorithm (Metsämäki et al. 2015) for viewable snow (SCFV) and snow on ground (SCFG). A pre-classification was implemented to minimise erroneous results (solar zenith angle > 88°; cloud probability > 80%; water if percentage of pixel > 50; and permanent ice if percentage of pixel > 50). In addition, two thresholds were included to test whether a pixel potentially is snow free or snow covered (snow free if channel 1 > 0.12 or channel 4 > 283 K). \r\n\r\nIn addition, different post-processing steps were implemented to improve the quality of the snow products: for latitudes ±15° and elevations below 1000 m a.s.l. a test was added (channel 1 < 0.30 or channel 4 > 270 K) to remove erroneous data in the tropical regions. A second test considers channel 3b: (channel 1 – channel 3b ≥ 0.2 and channel 3b < 0.1) for the Southern Hemisphere to remove erroneous snow pixels, with an additional adaptation for the globe (channel 1 – channel 3b < 0.1 and channel 3b < 0.2). The erroneous snow pixels with (channel_3a(/b)/channel_1 > 1 and channel_3a(/b)/channel_1 > 1) or (channel_2/channel_1 < 0.999 and channel_4 > 274 K) was removed. Additionally, the pixels with high solar zenith angle (VZA > 75°) and NDSI < 0.5 was removed. Some other criteria were also added in post-processing steps.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ] }