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  • HadCRU_MLE_v1.0 is a dataset of monthly gridded surface temperatures for the Earth during the instrumental period (since 1850). The name ‘HadCRU_MLE_v1.0’ reflects the dataset’s use of maximum likelihood estimation and observational data primarily from the Met Office Hadley Centre and the Climate Research Unit of the University of East Anglia. Source datasets used to create HadCRU_MLE_v1.0 include land surface air temperature anomalies of HadCRUT4, sea surface temperature anomalies of HadSST4, sea ice coverage of HadISST2, the surface temperature climatology of Jones et al. (1999), the sea surface temperature climatology of HadSST3, land mask data of OSTIA, surface elevation data of GMTED2010, and climate model output of CCSM4 for a pre-industrial control scenario. HadCRU_MLE_v1.0 was generated using information from the Met Office Hadley Centre, the Climate Research Unit of the University of East Anglia, the E.U. Copernicus Marine Service, the U.S. Geological Survey, and the University Corporation of Atmospheric Research. The primary motivation to develop HadCRU_MLE_v1.0 was to correct for two biases that may exist in global instrumental temperature datasets. The first bias is an amplification bias caused by not adequately accounting for the tendency of different regions of the planet to warm at different rates. The second bias is a sea ice bias caused by not adequately accounting for changes in sea ice coverage during the instrumental period. Corrections to these biases increased the estimate of global mean surface temperature change during the instrumental period. The new dataset has improvements compared to the Cowtan and Way version 2 dataset, including an improved statistical foundation for estimating model parameters, taking advantage of temporal correlations of observations, taking advantage of correlations between land and sea observations, and accounting for more sources of uncertainty. To properly correct for amplification bias, HadCRU_MLE_v1.0 incorporates the behaviour of the El Niño Southern Oscillation. HadCRU_MLE_v1.0 includes mean surface temperature anomalies for each month from 1850 to 2018 and for each 5° latitude by 5° longitude grid cell. Future versions of HadCRU_MLE may become available to extend the temporal coverage beyond 2018. The maximum likelihood estimation approach allows for the estimated field of surface temperature anomalies to be temporally and spatially complete for the entire instrumental period and for the entire surface of the Earth. A 5° by 5° gridded 1961-1990 temperature climatology for HadCRU_MLE_v1.0 is available, although caution is advised when interpreting this temperature climatology since the source datasets used for temperature climatologies do not correspond perfectly with the source datasets used for temperature anomalies. Other information of HadCRU_MLE_v1.0 is available, including the estimated local amplification factors, the magnitude of the corrections for sea ice bias, and the impact of the El Niño Southern Oscillation on surface temperature anomalies.

  • Version messy_2.54.0p7, release date: 11. April 2019

  • The SRES data sets were published by the IPCC in 2000 and classified into four different scenario families (A1, A2, B1, B2). SRES_B2 storyline describes a world in which the emphasis is on local solutions to economic, social and enviromental sustainability. The global population is increasing at a lower rate than A2. It has an intermediate level of economic development and a less rapid and more diverse technological change than in A1 and B1. The Hadley Centre Circulation Model is a 3-dim AOGCM described by (Gordon et al.,2000 and Pope et al.,2000). The atmospheric component has a 19 levels horizontal resolution, comparable with spectral resolution of T42, while the ocean component has a 20 levels resolution. HADCM3 (http://www.metoffice.gov.uk/research/modelling-systems/unified-model/climate-models/hadcm3 ). The changes of anthropogenic emissions of CO2, CH4, N2O and sulphur dioxide are prescribed according to the above mentioned scenario.

  • The SRES data sets were published by the IPCC in 2000 and classified into four different scenario families (A1, A2, B1, B2). SRES_A2 storyline describes a very heterogeneous world with the underlying theme of self-reliance and preservation of local identities. It results in this scenario a continous increasing population together with a slower economic growth and technological change. The Hadley Centre Circulation Model is a 3-dim AOGCM described by (Gordon et al., 2000 and Pope et al., 2000). The atmospheric component has a 19 levels horizontal resolution, comparable with spectral resolution of T42, while the ocean component has a 20 levels resolution. HADCM3(http://www.metoffice.gov.uk/research/modelling-systems/unified-model/climate-models/hadcm3 ) The changes of anthropogenic emissions of CO2, CH4, N2O and sulphur dioxide are prescribed according to the above mentioned scenario. These data belongs to a set of three ensemble runs, with the HADCM3-model, using the SRES_A2 scenario. They provide monthly averaged values of selected variables for the IPCC-DDC. HadCM3_SRES_A2b and HadCM3_SRES_A2c follow the same experimental design and historical plus future forcings as HadCM3_SRES_A2 (Johns et al. 2003) but starting from initial conditions taken respectively 100 years and 200 years further into the HadCM3 control simulation.

  • The SRES data sets were published by the IPCC in 2000 and classified into four different scenario families (A1, A2, B1, B2). SRES_A2 storyline describes a very heterogeneous world with the underlying theme of self-reliance and preservation of local identities. It results in this scenario a continous increasing population together with a slower economic growth and technological change. The Hadley Centre Circulation Model is a 3-dim AOGCM described by (Gordon et al., 2000 and Pope et al., 2000). The atmospheric component has a 19 levels horizontal resolution, comparable with spectral resolution of T42, while the ocean component has a 20 levels resolution. HADCM3(http://www.metoffice.gov.uk/research/modelling-systems/unified-model/climate-models/hadcm3 ) The changes of anthropogenic emissions of CO2, CH4, N2O and sulphur dioxide are prescribed according to the above mentioned scenario. These data belongs to a set of three ensemble runs, with the HADCM3-model, using the SRES_A2 scenario. They provide monthly averaged values of selected variables for the IPCC-DDC. HadCM3_SRES_A2b and HadCM3_SRES_A2c follow the same experimental design and historical plus future forcings as HadCM3_SRES_A2 (Johns et al. 2003) but starting from initial conditions taken respectively 100 years and 200 years further into the HadCM3 control simulation.

  • The SRES data sets were published by the IPCC in 2000 and classified into four different scenario families (A1, A2, B1, B2). SRES_A2 storyline describes a very heterogeneous world with the underlying theme of self-reliance and preservation of local identities. It results in this scenario a continous increasing population together with a slower economic growth and technological change. The Hadley Centre Circulation Model is a 3-dim AOGCM described by (Gordon et al., 2000 and Pope et al., 2000). The atmospheric component has a 19 levels horizontal resolution, comparable with spectral resolution of T42, while the ocean component has a 20 levels resolution. HADCM3(http://www.metoffice.gov.uk/research/modelling-systems/unified-model/climate-models/hadcm3 ) The changes of anthropogenic emissions of CO2, CH4, N2O and sulphur dioxide are prescribed according to the above mentioned scenario. These data belongs to a set of three ensemble runs, with the HADCM3-model, using the SRES_A2 scenario. They provide monthly averaged values of selected variables for the IPCC-DDC.

  • This experiment contains forecasts from the LMK (COSMO-DE) high resolution model of DWD (2.8km horizontal resoultion and 50 model levels). Model runs are started every 3h at 00, 03, 06, 09, 12, 15, 18 and 21 UTC with a forecast range of +18h. LMK (COSMO-DE) is an operational forecast model of DWD. Therefore, we adapted the output of the model as close as possible to the tigge+ list, but there are some differences; see dataset summaries. For a detailed description of the LMK (COSMO-DE) model, please contact the originator of the data. All datasets for COPS in the database have an output frequency of 15 minutes. If the variables are not provided by LMK (COSMO-DE) with an output frequency of 15 minutes then the hourly output has been linearily interpolated in time. LMK (COSMO-DE) provides only a subset of the TIGGE+ variables with an output frequency of 15 minutes. These are: Total precipitation (all types) (kg/m**2) acc_st 011 002 TPT2 Precipitation: grid-scale only, rain (kg/m**2) acc_st 102 201 SURF Precipitation: grid-scale only, snow (kg/m**2) acc_st 079 002 SURF Precipitation: grid-scale only, graupel (kg/m**2) acc_st 132 201 SURF Precipitation rate: grid-scale only, rain (kg/s/m**2) inst 100 201 SURF Precipitation rate: grid-scale only, snow (kg/s/m**2) inst 100 201 SURF Precipitation rate: grid-scale only, graupel (kg/s/m**2) inst 100 201 SURF Total column water vapour (or precipitable water) (kg/m**2) inst 054 002 SURF Total column cloud water (or cloud water) (kg/m**2) inst 076 002 SURF Total column cloud ice (or cloud ice) (kg/m**2) inst 058 002 SURF W-velocity (m/s) inst 040 002 MUVW Grid descitption: CDOM: xfirst: -2.73 yfirst: -2.927 xsize: 135.0 ysize: 118.0 xinc: 0.025 yinc: 0.025 xnpole: -170.0 ynpole: 40.0 DDOM: xfirst: -5.882 yfirst: -6.685 xsize: 441.0 ysize: 279.0 xinc: 0.025 yinc: 0.025 xnpole: -170.0 ynpole: 40.0

  • The goal of the experiment is to drive FEST, a rainfall-runoff distributed model with continuous soil moisture account, with ensemble forecasts from COSMO-LEPS (CLEPS) and with forecasts from ISACMOL2. The application domain is the Toce-Ticino and Maggia watershed. Hydrograph simulations and alerts are provided for Candoglia (Toce), Solduno (Maggia) and Bellinzona (Ticino). The runs were provided by Politecnico di Milano (PoliMi), Italy.

  • HadCRU_MLE_v1.2 is a dataset of monthly gridded surface temperatures for the Earth during the instrumental period (since 1850). The name ‘HadCRU_MLE_v1.2’ reflects the dataset’s use of maximum likelihood estimation and observational data primarily from the Met Office Hadley Centre and the Climate Research Unit of the University of East Anglia. Source datasets used to create HadCRU_MLE_v1.2 include land surface air temperature anomalies of non-infilled HadCRUT5, sea surface temperature anomalies of HadSST4, sea ice coverage of HadISST2, the surface temperature climatology of Jones et al. (1999), the sea surface temperature climatology of HadSST3, land mask data of OSTIAv2, surface elevation data of GMTED2010, and climate model output of CCSM4 for a pre-industrial control scenario. HadCRU_MLE_v1.2 was generated using information from the Met Office Hadley Centre, the Climate Research Unit of the University of East Anglia, the E.U. Copernicus Marine Service, the U.S. Geological Survey, and the University Corporation of Atmospheric Research. Results of sensitivity tests using alternate sea ice source datasets from the Japanese Meteorological Agency (COBE-SST2) and the National Snow and Ice Data Center (modified G10010v2 appended with G02202v4) are also available. The primary motivation to develop HadCRU_MLE_v1.0 was to better account for spatially nonuniform warming across the planet. HadCRU_MLE_v1.0 better accounts for nonuniform warming by fitting an amplification function to observations to better account for spatially nonuniform warming trends, and by using differences in temperature climatologies and temperature anomalies between open sea and sea ice regions to better account for the impacts of changes in sea ice concentrations. These improvements increased the estimate of global mean surface temperature change during the instrumental period. HadCRU_MLE_v1.2 has additional improvements compared to HadCRUT5 Analysis, including correcting for a small underestimation of LSAT warming between 1961 and 1990, taking advantage of temporal correlations of observations, taking advantage of correlations between land and open sea observations, and better treatment of the El Niño Southern Oscillation. To support publication of the referenced research article in the Quarterly Journal of the Royal Meteorological Society, HadCRU_MLE_v1.2 was created to respond to suggestions by peer reviewers, including extended coverage until the end of 2023 and additional sensitivity tests. HadCRU_MLE_v1.2 includes mean surface temperature anomalies for each month from 1850 to 2023 and for each 5° latitude by 5° longitude grid cell. The maximum likelihood estimation approach allows for the estimated field of surface temperature anomalies to be temporally and spatially complete for the entire instrumental period and for the entire surface of the Earth. A 5° by 5° gridded 1961-1990 temperature climatology for HadCRU_MLE_v1.2 is available, although caution is advised when interpreting this temperature climatology since the source datasets used for temperature climatologies do not correspond perfectly with the source datasets used for temperature anomalies. Other information of HadCRU_MLE_v1.2 is available, including model parameters, the estimated amplification function, the internal variability pattern, the land area fractions, and the impacts of sea ice concentrations and the El Niño Southern Oscillation on surface temperature anomalies. Future versions of HadCRU_MLE may become available to extend the temporal coverage beyond 2023.

  • ICON is a modeling framework for weather, climate, and environmental prediction. It solves the full three-dimensional non-hydrostatic and compressible Navier-Stokes equations on an icosahedral grid and allows seamless predictions from local to global scales. More information about ICON is available at https://www.icon-model.org/. The ICON Code is documented in GitLab: https://gitlab.dkrz.de/icon/icon-model.

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