Sentence examples for multiple land surface from inspiring English sources

The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates.

The Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the NASA Terra and Aqua Earth Observing System satellites, provides multiple land surface temperature (LST) products on a daily basis.

The SEtHyS_Savannah model [Saux-Picart et al., submitted for publication. SEtHyS_Savannah: a multiple source land surface model applied to sahelian landscapes.

In this work, we describe a sequential data assimilation extension of LIS that incorporates multiple observational sources, land surface models and assimilation algorithms.

We are changing the climate by increasing the level of carbon dioxide in the atmosphere; we're reducing the planet's biodiversity, causing what scientists fear may be the sixth mass extinction in its history; and terraforming Earth's land surface with multiple megacities of concrete, steel and glass.

These and other tephras underpin an analysis of land surface stability across multiple scales.

MESH required multiple inputs to provide a complete distributed land surface model.

We look forward to a future where operational data assimilation schemes improve estimates by tracking land surface processes and exploiting multiple types of observations.

Especially under the influences of climate change and city development impacts, such approaches may prevail over the traditional solutions since OUDS can be better integrated in urban landscape for excess surface waters as well as strengthen the efficiency of multiple land use.

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood.

Finally, our results support the potential for monitoring land surface phenology at 30 m spatial resolution in near real-time by combining time series from multiple sensors such as the Landsat Operational Land Imager and the Sentinel 2 MultiSpectral Instrument.