The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/f37fda03-61d7-4d2a-835f-30fbb63537b1

Shan, Xu; Steele-Dunne, Susan; Ku, Ou; Hahn, Sebastian; Wagner, Wolfgang et. al. (2024): Dataset of ISBA open loop states and ASCAT normalized backscatter and slope data of grid points. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/f37fda03-61d7-4d2a-835f-30fbb63537b1.v1

Dataset

• Land and Water Management
• Environment

Advanced Scatterometer (ASCAT), Interaction Sol-Biosphère-Atmosphère (ISBA), land surface model, microwave remote sensing

2007 to 2019

MIT

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Xu Shan , Susan Steele-Dunne , Ou Ku , Sebastian Hahn , Wolfgang Wagner , Jean-Christophe Calvet , Bertrand Bonan , Albergel Clement

This dataset comprises open loop simulations of the ISBA land surface model and ASCAT normalized backscatter and slope data at grid points (GPIs) containing International Soil Moisture Network stations. The dataset covers the period from 2007 to 2019 and includes a total of 31 GPIs. 

The ISBA land surface model runs on the offline version of SURFEX software (https://www.umr-cnrm.fr/surfex/) using ERA5 forcing data. ASCAT normalized backscatter (“sig”) data are provided at 10am and 10pm every day. If normalized backscatter are not acquired at a particular time, a value of 999 is provided.

ASCAT slope (“slop”) is calculated daily following Hahn et al. (2017). These daily values are provided at 10am in this dataset. The slope value at 10pm is set to 999. 

• 2024-05-02 first online, published, posted

4TU.ResearchData

netCDF4

Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe

• https://www.umr-cnrm.fr/surfex/

• (grant code ALWGO.2018.036)
• A new perspective of global vegetation water dynamics (grant code ALWGO.2018.036) NWO
• (grant code NLeSCC19.00) Netherlands eScience Center

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Department of Geoscience and Remote Sensing, Department of Water Management.
TU Wien.
Meteo France.