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Improved groundwater table and L-band brightness temperature estimates for Northern Hemisphere peatlands using new model physics and SMOS observations in a global data assimilation framework
- Source :
- Remote Sensing of Environment. 246:111805
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- There is an urgent need to include northern peatland hydrology in global Earth system models to better understand land-atmosphere interactions and sensitivities of peatland functions to climate change, and, ultimately, to improve climate change predictions. In this study, we introduced for the first time peatland-specific model physics into an assimilation scheme for L-band brightness temperature (Tb) data from the Soil Moisture Ocean Salinity (SMOS) mission to improve groundwater table estimates. We conducted two sets of model-only and data assimilation experiments using the Catchment Land Surface Model (CLSM), applying (over peatlands only) in one of them a peatland-specific adaptation (PEATCLSM). The evaluation against in-situ measurements of peatland groundwater table depth indicates the superiority of PEATCLSM model physics and additionally improved performance after assimilating SMOS Tb observations. The better performance of PEATCLSM over nearly all Northern Hemisphere peatlands is further supported by the better agreement between SMOS Tb observations and Tb estimates from the model-only and data assimilation runs. Within the data assimilation scheme, PEATCLSM reduces Tb observation-minus-forecast residuals and leads to reduced data assimilation updates of water storage components and, thus, reduced water budget imbalances in the assimilation system. ispartof: Remote Sensing Of Environment vol:246 status: Published online
- Subjects :
- Peat
010504 meteorology & atmospheric sciences
Water table
0208 environmental biotechnology
Water storage
Northern Hemisphere
Soil Science
Climate change
Geology
02 engineering and technology
01 natural sciences
020801 environmental engineering
Data assimilation
Hydrology (agriculture)
Climatology
Brightness temperature
Computers in Earth Sciences
0105 earth and related environmental sciences
Remote sensing
Subjects
Details
- ISSN :
- 00344257
- Volume :
- 246
- Database :
- OpenAIRE
- Journal :
- Remote Sensing of Environment
- Accession number :
- edsair.doi.dedup.....1f4e305e9b9e96e0fbc05b5049e4eeec
- Full Text :
- https://doi.org/10.1016/j.rse.2020.111805