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1,791 to 1,800 of 1,803 Results

LSTM_E1_4_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: 1ced5300bd9667c97f4df42dd4e90a9cb3d169c0d5e250f62b060e6b64652506 Monthly water table depth anomalies generated from the proposed LSTM networks of E1.4 (precipitation anomaly and evapotranspiration anomaly)
LSTM_E1_5_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: a79d79d6bef3880a62d80027442b6633943627c73f67b47149778081bde4b442 Monthly water table depth anomalies generated from the proposed LSTM networks of E1.5 (precipitation anomaly and soil moisture anomaly)
LSTM_E1_6_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: c467a57278ff013e20c4f22fa7163d9f3bec5c372177cd94170dd480a4e3958e Monthly water table depth anomalies generated from the proposed LSTM networks of E1.6 (evapotranspiration anomaly and soil moisture anomaly)
LSTM_E1_7_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: 16ee2fe91b1129b2a79cc76f21d53d62bb566fd33b7d6d8ef8559748e8aadf04 Monthly water table depth anomalies generated from the proposed LSTM networks of E1.7 (precipitation anomaly, evapotranspiration anomaly and soil moisture anomaly)
LSTM_E2_1_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: b7ec5b5accae616765f768c0becd8e2ad6fab4eb1daaaaee9d0af7ee64cdc357 Monthly water table depth anomalies generated from the proposed LSTM networks of E2.1 (precipitation anomaly, soil moisture anomaly and scaled yearly averaged snow water equivalent)
LSTM_E2_2_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: 005b78e53e7a65064e34348b66ff975a8880336d85f8bb383aaa9d8728c7e4d7 Monthly water table depth anomalies generated from the proposed LSTM networks of E2.2 (precipitation anomaly and soil moisture anomaly at the selected pixels and adjacent pixels)
LSTM_E2_3_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: d090fd16b6a96db6e91c6f418d3ac8fa4e793d0c1145269fce502124c7b80b25 Monthly water table depth anomalies generated from the proposed LSTM networks of E2.3 (precipitation anomaly and soil moisture anomaly at the selected pixels close to rivers and river stage anomaly at the adjacent pixels)
TSMP_G2A_monthly_evapotranspiration_anomaly_FZJ-IBG3_TSMP_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: a1260d6aed328110afbf60df25cd63a48ede47973954ce3eaea09c136a81a5b8 Monthly evapotranspiration anomalies calculated from the TSMP-G2A data set
TSMP_G2A_monthly_soil_moisture_anomaly_FZJ-IBG3_TSMP_0.1_degree_v1.1996_2016.nc Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Network Common Data Form - 167.9 MB - SHA-256: 6290fd173e798af8c3aa343c1f44445997042ffbe93dd27c78c3e05dc06eb436 Monthly soil moisture anomalies calculated from the TSMP-G2A data set
TSMP_G2A_yearly_averaged_snow_water_equivalent_FZJ-IBG3_TSMP_0.1_degree_v1.2003_2010.txt Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis Plain Text - 2.5 MB - SHA-256: e85a674dacaaafd8431b78dac8ad82237a1c3eebe89cc736cce963a777389cac Yearly averaged snow water equivalent calculated from the TSMP-G2A data set

LSTM_E1_4_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: 1ced5300bd9667c97f4df42dd4e90a9cb3d169c0d5e250f62b060e6b64652506

Monthly water table depth anomalies generated from the proposed LSTM networks of E1.4 (precipitation anomaly and evapotranspiration anomaly)

LSTM_E1_5_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: a79d79d6bef3880a62d80027442b6633943627c73f67b47149778081bde4b442

Monthly water table depth anomalies generated from the proposed LSTM networks of E1.5 (precipitation anomaly and soil moisture anomaly)

LSTM_E1_6_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: c467a57278ff013e20c4f22fa7163d9f3bec5c372177cd94170dd480a4e3958e

Monthly water table depth anomalies generated from the proposed LSTM networks of E1.6 (evapotranspiration anomaly and soil moisture anomaly)

LSTM_E1_7_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: 16ee2fe91b1129b2a79cc76f21d53d62bb566fd33b7d6d8ef8559748e8aadf04

Monthly water table depth anomalies generated from the proposed LSTM networks of E1.7 (precipitation anomaly, evapotranspiration anomaly and soil moisture anomaly)

LSTM_E2_1_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: b7ec5b5accae616765f768c0becd8e2ad6fab4eb1daaaaee9d0af7ee64cdc357

Monthly water table depth anomalies generated from the proposed LSTM networks of E2.1 (precipitation anomaly, soil moisture anomaly and scaled yearly averaged snow water equivalent)

LSTM_E2_2_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: 005b78e53e7a65064e34348b66ff975a8880336d85f8bb383aaa9d8728c7e4d7

Monthly water table depth anomalies generated from the proposed LSTM networks of E2.2 (precipitation anomaly and soil moisture anomaly at the selected pixels and adjacent pixels)

LSTM_E2_3_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: d090fd16b6a96db6e91c6f418d3ac8fa4e793d0c1145269fce502124c7b80b25

Monthly water table depth anomalies generated from the proposed LSTM networks of E2.3 (precipitation anomaly and soil moisture anomaly at the selected pixels close to rivers and river stage anomaly at the adjacent pixels)

TSMP_G2A_monthly_evapotranspiration_anomaly_FZJ-IBG3_TSMP_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: a1260d6aed328110afbf60df25cd63a48ede47973954ce3eaea09c136a81a5b8

Monthly evapotranspiration anomalies calculated from the TSMP-G2A data set

TSMP_G2A_monthly_soil_moisture_anomaly_FZJ-IBG3_TSMP_0.1_degree_v1.1996_2016.nc

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Network Common Data Form - 167.9 MB - SHA-256: 6290fd173e798af8c3aa343c1f44445997042ffbe93dd27c78c3e05dc06eb436

Monthly soil moisture anomalies calculated from the TSMP-G2A data set

TSMP_G2A_yearly_averaged_snow_water_equivalent_FZJ-IBG3_TSMP_0.1_degree_v1.2003_2010.txt

Dec 13, 2021 - An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis

Plain Text - 2.5 MB - SHA-256: e85a674dacaaafd8431b78dac8ad82237a1c3eebe89cc736cce963a777389cac

Yearly averaged snow water equivalent calculated from the TSMP-G2A data set

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