Dataset Metadata
id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0901.sfc20220901.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:56:00.570Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY0901
cast_type = sfc20220901
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 = 2022-10-15T12:00:00Z
datetime_stop = 2023-01-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0901.sfc20220901.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0901.sfc20220901.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1209468
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1001.sfc20221001.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:56:03.461Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY1001
cast_type = sfc20221001
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 = 2022-11-15T12:00:00Z
datetime_stop = 2023-02-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1001.sfc20221001.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1001.sfc20221001.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1209468
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1101.sfc20221101.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:56:06.299Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY1101
cast_type = sfc20221101
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 = 2022-12-15T12:00:00Z
datetime_stop = 2023-03-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1101.sfc20221101.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1101.sfc20221101.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1209468
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:55:57.862Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY0501
cast_type = sfc20230501
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 = 2023-06-15T12:00:00Z
datetime_stop = 2023-09-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1209468
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0901.sfc20220901.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:55:59.209Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY0901
cast_type = sfc20220901
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 = 2022-10-15T12:00:00Z
datetime_stop = 2023-01-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0901.sfc20220901.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0901.sfc20220901.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1208412
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1001.sfc20221001.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:56:02.038Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY1001
cast_type = sfc20221001
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 = 2022-11-15T12:00:00Z
datetime_stop = 2023-02-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1001.sfc20221001.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1001.sfc20221001.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1208412
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1101.sfc20221101.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:56:04.907Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY1101
cast_type = sfc20221101
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 = 2022-12-15T12:00:00Z
datetime_stop = 2023-03-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1101.sfc20221101.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1101.sfc20221101.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1208412
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1201.sfc20221201.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:56:07.690Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY1201
cast_type = sfc20221201
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 = 2023-01-15T12:00:00Z
datetime_stop = 2023-04-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1201.sfc20221201.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY1201.sfc20221201.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1208412
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509|esgf.dwd.de
version = 20230509
_timestamp = 2023-05-11T14:55:56.280Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY0501
cast_type = sfc20230501
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 = 2023-06-15T12:00:00Z
datetime_stop = 2023-09-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr.v20230509
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1208412
south_degrees = 46.05
time_frequency = mon
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.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0101.sfc20230101.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230424|esgf.dwd.de
version = 20230424
_timestamp = 2023-05-04T19:25:42.140Z
access = public, HTTPServer, GridFTP, OPENDAP
cast_package = svhYYYY0101
cast_type = sfc20230101
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 = 2023-02-15T12:00:00Z
datetime_stop = 2023-05-15T12:00:00Z
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 = GCFS21
east_degrees = 15.875
ensemble = remi1p1
experiment = seasonal_qa
experiment_family = All
geo = ENVELOPE(4.025, 15.875, 55.95, 46.05)
geo_units = degrees_east
index_node = esgf.dwd.de
instance_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0101.sfc20230101.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas.v20230424
institute = DWD
master_id = ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0101.sfc20230101.remi1p1.DWD-EPISODES2022.v1-r1.mon.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 = 1209468
south_degrees = 46.05
time_frequency = mon
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