Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tas.v20230327|esgf.dwd.de
version = 20230327
_timestamp = 2023-05-05T11:11:39.149Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = air_temperature_anomaly, pearson_correlation_coefficient_for_anomaly_of_near-surface_air_temperature, mean_squared_error_for_anomaly_of_near-surface_air_temperature
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2025-01-01T12:00:00Z
datetime_stop = 2030-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tas.v20230327
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tas
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 921540
south_degrees = 46.05
time_frequency = 5yr
variables = tasAnom, tasAnom_corr_pea, tasAnom_mse
variable_long_names = Anomaly of Near-Surface Air Temperature, Pearson Correlation Coefficient for Anomaly of Near-Surface Air Temperature, Mean Squared Error for Anomaly of Near-Surface Air Temperature
variable_units = K, 1, K 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tas.v20230327|esgf.dwd.de
version = 20230327
_timestamp = 2023-05-05T11:11:41.849Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = air_temperature_anomaly, pearson_correlation_coefficient_for_anomaly_of_near-surface_air_temperature, mean_squared_error_for_anomaly_of_near-surface_air_temperature
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2023-01-01T12:00:00Z
datetime_stop = 2023-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tas.v20230327
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tas
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 344196
south_degrees = 46.05
time_frequency = yr
variables = tasAnom, tasAnom_corr_pea, tasAnom_mse
variable_long_names = Anomaly of Near-Surface Air Temperature, Pearson Correlation Coefficient for Anomaly of Near-Surface Air Temperature, Mean Squared Error for Anomaly of Near-Surface Air Temperature
variable_units = K, 1, K 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.pr.v20230327|esgf.dwd.de
version = 20230327
_timestamp = 2023-05-05T11:11:37.728Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_precipitation, pearson_correlation_coefficient_for_anomaly_of_precipitation, mean_squared_error_for_anomaly_of_precipitation
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2025-01-01T12:00:00Z
datetime_stop = 2030-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.pr.v20230327
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.pr
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 920472
south_degrees = 46.05
time_frequency = 5yr
variables = prAnom, prAnom_corr_pea, prAnom_mse
variable_long_names = Anomaly of Precipitation, Pearson Correlation Coefficient for Anomaly of Precipitation, Mean Squared Error for Anomaly of Precipitation
variable_units = kg m-2 s-1, 1, kg m-2 s-1 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.pr.v20230327|esgf.dwd.de
version = 20230327
_timestamp = 2023-05-05T11:11:40.434Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_precipitation, pearson_correlation_coefficient_for_anomaly_of_precipitation, mean_squared_error_for_anomaly_of_precipitation
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2023-01-01T12:00:00Z
datetime_stop = 2023-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.pr.v20230327
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.pr
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 343140
south_degrees = 46.05
time_frequency = yr
variables = prAnom, prAnom_corr_pea, prAnom_mse
variable_long_names = Anomaly of Precipitation, Pearson Correlation Coefficient for Anomaly of Precipitation, Mean Squared Error for Anomaly of Precipitation
variable_units = kg m-2 s-1, 1, kg m-2 s-1 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tasmin.v20230718|esgf.dwd.de
version = 20230718
_timestamp = 2023-07-19T14:20:07.551Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_daily_minimum_near-surface_air_temperature, pearson_correlation_coefficient_for_anomaly_of_daily_minimum_near-surface_air_temperature, mean_squared_error_for_anomaly_of_daily_minimum_near-surface_air_temperature
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2025-01-01T12:00:00Z
datetime_stop = 2030-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tasmin.v20230718
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tasmin
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 922896
south_degrees = 46.05
time_frequency = 5yr
variables = tasminAnom, tasminAnom_corr_pea, tasminAnom_mse
variable_long_names = Anomaly of Daily Minimum Near-Surface Air Temperature, Pearson Correlation Coefficient for Anomaly of Daily Minimum Near-Surface Air Temperature, Mean Squared Error for Anomaly of Daily Minimum Near-Surface Air Temperature
variable_units = K, 1, K 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tasmax.v20230718|esgf.dwd.de
version = 20230718
_timestamp = 2023-07-19T14:20:06.302Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_daily_maximum_near-surface_air_temperature, pearson_correlation_coefficient_for_anomaly_of_daily_maximum_near-surface_air_temperature, mean_squared_error_for_anomaly_of_daily_maximum_near-surface_air_temperature
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2025-01-01T12:00:00Z
datetime_stop = 2030-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tasmax.v20230718
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.5yr.tasmax
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 922896
south_degrees = 46.05
time_frequency = 5yr
variables = tasmaxAnom, tasmaxAnom_corr_pea, tasmaxAnom_mse
variable_long_names = Anomaly of Daily Maximum Near-Surface Air Temperature, Pearson Correlation Coefficient for Anomaly of Daily Maximum Near-Surface Air Temperature, Mean Squared Error for Anomaly of Daily Maximum Near-Surface Air Temperature
variable_units = K, 1, K 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tasmin.v20230718|esgf.dwd.de
version = 20230718
_timestamp = 2023-07-19T14:20:13.809Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_daily_minimum_near-surface_air_temperature, pearson_correlation_coefficient_for_anomaly_of_daily_minimum_near-surface_air_temperature, mean_squared_error_for_anomaly_of_daily_minimum_near-surface_air_temperature
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2023-01-01T12:00:00Z
datetime_stop = 2023-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tasmin.v20230718
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tasmin
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 345528
south_degrees = 46.05
time_frequency = yr
variables = tasminAnom, tasminAnom_corr_pea, tasminAnom_mse
variable_long_names = Anomaly of Daily Minimum Near-Surface Air Temperature, Pearson Correlation Coefficient for Anomaly of Daily Minimum Near-Surface Air Temperature, Mean Squared Error for Anomaly of Daily Minimum Near-Surface Air Temperature
variable_units = K, 1, K 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tasmax.v20230718|esgf.dwd.de
version = 20230718
_timestamp = 2023-07-19T14:20:12.560Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_daily_maximum_near-surface_air_temperature, pearson_correlation_coefficient_for_anomaly_of_daily_maximum_near-surface_air_temperature, mean_squared_error_for_anomaly_of_daily_maximum_near-surface_air_temperature
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2023-01-01T12:00:00Z
datetime_stop = 2023-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tasmax.v20230718
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.tasmax
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 345528
south_degrees = 46.05
time_frequency = yr
variables = tasmaxAnom, tasmaxAnom_corr_pea, tasmaxAnom_mse
variable_long_names = Anomaly of Daily Maximum Near-Surface Air Temperature, Pearson Correlation Coefficient for Anomaly of Daily Maximum Near-Surface Air Temperature, Mean Squared Error for Anomaly of Daily Maximum Near-Surface Air Temperature
variable_units = K, 1, K 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.sfcWind.v20230718|esgf.dwd.de
version = 20230718
_timestamp = 2023-07-19T14:20:11.316Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_daily-mean_near-surface_wind_speed, pearson_correlation_coefficient_for_anomaly_of_daily-mean_near-surface_wind_speed, mean_squared_error_for_anomaly_of_daily-mean_near-surface_wind_speed
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2023-01-01T12:00:00Z
datetime_stop = 2023-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.sfcWind.v20230718
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.sfcWind
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 345408
south_degrees = 46.05
time_frequency = yr
variables = sfcWindAnom, sfcWindAnom_corr_pea, sfcWindAnom_mse
variable_long_names = Anomaly of Daily-Mean Near-Surface Wind Speed, Pearson Correlation Coefficient for Anomaly of Daily-Mean Near-Surface Wind Speed, Mean Squared Error for Anomaly of Daily-Mean Near-Surface Wind Speed
variable_units = m s-1, 1, m s-1 2
west_degrees = 4.025

Dataset Metadata
id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.hurs.v20230718|esgf.dwd.de
version = 20230718
_timestamp = 2023-07-19T14:20:08.731Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = dvhYYYY1101
cast_type = dfc2022
cf_standard_names = anomaly_of_near-surface_relative_humidity, pearson_correlation_coefficient_for_anomaly_of_near-surface_relative_humidity, mean_squared_error_for_anomaly_of_near-surface_relative_humidity
data_node = esgf.dwd.de
dataset_id_template_ = ClimatePredictionsDE.%(experiment)s.%(access)s.%(product)s.%(domain)s.%(institute)s.%(driving_model)s.%(cast_package)s.%(cast_type)s.%(ensemble)s.%(rcm_name)s.%(rcm_version)s.%(time_frequency)s.%(variable)s
datetime_start = 2023-01-01T12:00:00Z
datetime_stop = 2023-01-01T12:00:00Z
directory_format_template_ = %(root)s/%(project)s/%(experiment)s/%(product)s/%(access)s/%(domain)s/%(institute)s/%(driving_model)s/%(cast_package)s/%(cast_type)s/%(ensemble)s/%(rcm_model)s/%(rcm_version)s/%(time_frequency)s/%(variable)s/%(version)s
domain = DE-015x01
driving_model = MPI-ESM-LR
east_degrees = 15.875
ensemble = remi1p1
experiment = decadal_qa
experiment_familys = All, Decadal
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.hurs.v20230718
institute = DWD
master_id = ClimatePredictionsDE.decadal_qa.public.output.DE-015x01.DWD.MPI-ESM-LR.dvhYYYY1101.dfc2022.remi1p1.DWD-EPISODES2022.v1-r1.yr.hurs
north_degrees = 55.95
number_of_aggregations = 6
number_of_files = 3
product = output
project = climatepredictionsde
rcm_name = DWD-EPISODES2022
rcm_version = v1-r1
retracted = false
size = 344604
south_degrees = 46.05
time_frequency = yr
variables = hursAnom, hursAnom_corr_pea, hursAnom_mse
variable_long_names = Anomaly of Near-Surface Relative Humidity, Pearson Correlation Coefficient for Anomaly of Near-Surface Relative Humidity, Mean Squared Error for Anomaly of Near-Surface Relative Humidity
variable_units = %, 1, % 2
west_degrees = 4.025