Displaying 51 - 75 of 227

4-month long 101-ensemble member seasonal attribution experiment (I20_BC16) initialised on 01-November-2015 using the atmosphere-only version of SEAS5 (see Johnson et al., 2019) forced with daily ERA5 SST as in the reference experiment (R16) but with daily SST over the tropical Indian Ocean swapped with that from 2019/20.

Examples

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4-month long 101-ensemble member seasonal attribution experiment (I98_BC20) initialised on 01-November-2019 using the atmosphere-only version of SEAS5 (see Johnson et al., 2019) forced with daily ERA5 SST as in the reference experiment (R20) but with daily SST over the tropical Indian Ocean swapped with that from 2019/20.

Examples

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4-month long 101-ensemble member seasonal attribution experiment (I16_BC20) initialised on 01-November-2019 using the atmosphere-only version of SEAS5 (see Johnson et al., 2019) forced with daily ERA5 SST as in the reference experiment (R20) but with daily SST over the tropical Indian Ocean swapped with that from 2019/20.

Examples

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CAMS atmospheric composition forecast experiment set up to explore data information content in the scope of a ESoWC project. The data is encoded as IEEE single-precision (32-bit floats) circumventing any other lossy compression. This is in contrast to the default 24-bit linear packing used for CAMS in the ECMWF data archive and on the Copernicus Atmosphere Data Store. Explanation of parameter ids can be found at: https://apps.ecmwf.int/codes/grib/param-db/

Examples

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Coupled 32-day experiment, 51 member ensemble, Tco319L137. Start dates covering extended winters 2020/2023, starting on 1st Nov up to 24 April, 1 week apart.

Examples

retrieve, class=rd, stream=enfh, expver=idlq, type=pf, number=1, levtype=sfc, param=2t, hdate=20201101, date=20231101, time=00:00:00, step=24, target='output.grib'

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This is an global forecast experiment for Deltares use case in DestinE (DE370a). It covers the period from 16/07/2023 to 28/07/2023.

Examples

retrieve, class=rd, stream=oper, expver=idev, type=fc, levtype=sfc, param=2t, date=2023-07-16/to/2023-07-28, time=00:00:00, step=0/to/120, target='output.grib'

Download 2m temperature

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This is an global forecast experiment for Deltares use case in DestinE (DE370a). It covers the period of storm Chiara, with initial dates from 03/02/2020 to 16/02/2020.

Examples

retrieve, class=rd, stream=oper, expver=icrv, type=fc, levtype=sfc, param=2t, date=2020-02-03/to/2020-02-16, time=00:00:00, step=0/to/120, target='output.grib'

Download 2m temperature

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Model-level data of operational forecasts reproduced with Cy47R3 experiment suite. Parameters 103 and 104 are convective mass fluxes of rain and snow, and parameters 101 and 102 are large-scale mass fluxes of rain and snow.

Examples

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Deterministic 10-day TCo1279L137 forecast with CY49R1.1 with nudging to model level version of AIFS. 00 UTC starts from 1 June - 30 November 2024.

Examples

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Deterministic 10-day TCo1279L137 forecast with CY49R1.1 with nudging to model level version of AIFS. 00 UTC starts from 1 Dec 2024 - 31 May 2025.

Examples

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Deterministic 10-day TCo1279L137 forecast with CY49R1.1 with nudging to model level version of AIFS. 00 UTC starts from 1 June 2025 onwards.

Examples

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Deterministic 10-day TCo1279L137 forecast with CY49R1.1. Control for nudged experiments, before operational IFS forecast became CY49R1 from mid-November 2024. 00 UTC start from 1 January 2024 to 14 August 2025.

Examples

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noDropsonde experiment (other all usual observation types assimilated) for Observing System Experiment (OSE) looking at ARs affecting western USA DeHaan et al (2023). Experiment from 2019-01-28 to 2019-04-30, control is h4qi.

Examples

retrieve, class=rd, stream=lwda, expver=h4ss, type=fc, levtype=pl, levellist=250, param=131, date=2019-01-30, time=00:00:00, step=0/12/24/48, target='output.grib'

Forecast fields for u-wind @250 hPa, step gives forecast range in hours

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noDropsonde experiment (other all usual observation types assimilated) for Observing System Experiment (OSE) looking at ARs affecting western USA DeHaan et al (2023, WAF, submitted). Experiment from 2020-01-20 to 2020-04-28, control is hd8r.

Examples

retrieve, anoffset=9, class=rd, date=2020-01-20, expver=hd8r, levtype=sfc, step=0/12/24/48, param=137.128, stream=lwda, time=00:00:00, type=fc, target="output.grib"

Forecast fields of integrated water vapour, step gives forecast range in hours

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ECLand offline surface model (CY49R1) run forced by ERA5 reanalysis with CAMAFLOOD activated. For use in ML land emulation experiments.

Examples

retrieve, class=rd, date=2010-01-01, expver=i6aj, levtype=sfc, param=swvl1, stream=oper, time=00:00:00, type=an, target="swvl1_2010_01_01_00.grib"

Extracting a single soil moisture field, type=an

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ECLand offline surface model (CY49R1) run forced by ERA5 reanalysis with CAMAFLOOD activated. For use in ML land emulation experiments.

Examples

retrieve, class=rd, date=2010-01-01, expver=i8ki, levtype=sfc, param=swvl1, stream=oper, time=00:00:00, type=an, target="swvl1_2010_01_01_00.grib"

Extracting a single soil moisture field, type=an

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ecLand offline surface model (CY49R2) run forced by ERA5 reanalysis. For use in ML land emulation experiments.

Examples

retrieve, class=rd, stream=oper, expver=isc8, type=an, levtype=sfc, param=swvl1, date=2000-01-01, time=00:00:00, step=24, target='swvl1_2000_01_01_00.grib'

Extracting a single soil moisture field, type=an

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ecLand offline surface model (CY49R2) run forced by ERA5 reanalysis. For use in ML land emulation experiments.

Examples

retrieve, class=rd, stream=oper, expver=iscb, type=an, levtype=sfc, param=swvl1, date=2000-01-01, time=00:00:00, step=24, target='swvl1_2000_01_01_00.grib'

Extracting a single soil moisture field, type=an

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This dataset contains parameters from 24-month extended-seasonal reforecasts using the ECMWF seasonal forecast system 5 (SEAS5, Johnson et al, 2019). The reforecasts are intialised on 01-May and 01-November with 25 ensemble members and cover the period 1981-2024. Note that these forecasts are not real-time operational products; rather, they are experimental and generated as part of the ASPECT project (https://www.aspect-project.eu).

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The dataset contains the ECMWF Clear Air turbulence (CAT) parameter (units of EDR) on model levels for the SOUTHTRACK flight days. For the different flight days the CAT parameter is produced hourly (step 1 to 24)

Examples

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This dataset contains parameters from four-month long seasonal reforecasts using ECMWF IFS cycle CY49R1 v-version 4 covering the period 1993-2019 and forced with datasets for Leaf Area Index (LAI) and Land Use/Land Cover (LULC) developed in the CONFESS project (https://confess-h2020.eu).

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This dataset contains parameters from four-month long seasonal reforecasts using ECMWF IFS cycle CY49R1 v-version 4 covering the period 1993-2019 and forced with datasets for Leaf Area Index (LAI) and Land Use/Land Cover (LULC) developed in the CONFESS project (https://confess-h2020.eu). The reforecasts uses time varying LULC and climatological LAI based on version climate.v020_ESACCI_LAI of the IFS climate fields and can be compared against the CONTROL experiment (i14x) that uses climatological LAI and fixed LULC.

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noAircraft experiment (other all usual observation types assimilated) for aircraft Observing System Experiment (OSE) see Ingleby et al (2021), https://doi.org/10.1029/2020GL090699 . Experiment from 2019-01-28 to 2019-04-30, control is h4qi.

Examples

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noAircraftT experiment (other all usual observation types assimilated) for aircraft Observing System Experiment (OSE) see Ingleby et al (2021), https://doi.org/10.1029/2020GL090699 . Experiment from 2019-01-28 to 2019-04-30, control is h4qi.

Examples

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Research analysis experiment produced with ECMWF IFS cycle 47R1, at TCo399 (25km), for the EUREC4A field campaign (15.01.2020-14.02.2020). The dropsondes launched in the campaign are denied from the data assimilation.

Examples

retrieve, class=rd, stream=lwda, expver=hfa8, type=an, levtype=ml, levellist=137/to/106, param=T/Q, date=2020-01-16, time=00:00:00, step=0, target='TQ_0utc.grib'

Retrieval of temperature and humidity from the analysis on model levels on original model grid

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