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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
|
9. |
ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0501.sfc20230501.remi1p1.DWD-EPISODES2022.v1-r1.mon.pr
Message
Data Node: esgf.dwd.de
Version: 20230509
Total Number of Files (for all variables): 3
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
|
10. |
ClimatePredictionsDE.seasonal_qa.public.output.DE-015x01.DWD.GCFS21.svhYYYY0101.sfc20230101.remi1p1.DWD-EPISODES2022.v1-r1.mon.tas
Message
Data Node: esgf.dwd.de
Version: 20230424
Total Number of Files (for all variables): 3
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
|