Spaceborne Earth observations are routinely measured by a series of Low Earth Orbit (LEO) and Geostationary satellites and provide crucial information for monitoring and studying the Earth and its environment. However, satellites only measure the radiance emitted or reflected by the Earth. The measured radiances, like other physical measurements, are subject to errors and uncertainties. Therefore, techniques and algorithms are required to transform the data into hyrdological, environmental and geophysical variables and to quantify the uncertainties in both measurements and related products. This session brings together scientists from different fields of the multidisciplinary science of remote sensing to discuss recent advances in:

1. Remote sensing algorithms and techniques that are used to derive hydrological and meteorological variables such as precipitation, solar radiation, temperature, water vapor, cloud physical and micro-physical parameters, vegetation indices, and soil moisture from spaceborne observations
2. Methods to quantify uncertainties in satellite data and products, e.g., estimates of random and systematic errors, calibration and validation of the observations
3. Data assimilation systems to incorporate remotely sensed data into hydrological, weather and climate models
4. Applications of spaceborne observations and products in hydrology, meteorology, environmental science and agricultural practices