The land-surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. The characterization of the spatial and temporal variability of water and energy cycles is critical to improve our understanding of the land-surface-atmosphere interaction and the impact of land-surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land-surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes
International audienceAbstract. Evaluating land surface models (LSMs) using available observations i...
Land surface variability is important in many hydrologic and land-atmosphere interactions. Anomalous...
Land surface models (LSMs) are integral components of general circulation models (GCMs), consisting ...
Subsurface moisture and temperature and snow/ice stores exhibit persistence on various time scales t...
A land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surf...
Land surface models (LSMs) have traditionally been designed to focus on providing lower-boundary con...
Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Ea...
The beginning of the 21st century is marked by a rapid growth of land surface satellite data and mod...
The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al...
Land data assimilation system (LDAS)-Monde, an offline land data assimilation system with global cap...
International audienceThe task of quantifying spatial and temporal variations in terrestrial water, ...
International audienceAbstract. Evaluating land surface models (LSMs) using available observations i...
Land surface variability is important in many hydrologic and land-atmosphere interactions. Anomalous...
Land surface models (LSMs) are integral components of general circulation models (GCMs), consisting ...
Subsurface moisture and temperature and snow/ice stores exhibit persistence on various time scales t...
A land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surf...
Land surface models (LSMs) have traditionally been designed to focus on providing lower-boundary con...
Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Ea...
The beginning of the 21st century is marked by a rapid growth of land surface satellite data and mod...
The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al...
Land data assimilation system (LDAS)-Monde, an offline land data assimilation system with global cap...
International audienceThe task of quantifying spatial and temporal variations in terrestrial water, ...
International audienceAbstract. Evaluating land surface models (LSMs) using available observations i...
Land surface variability is important in many hydrologic and land-atmosphere interactions. Anomalous...
Land surface models (LSMs) are integral components of general circulation models (GCMs), consisting ...