Qiaozhen Mu

TL;DR: In this article, an improved version of the global evapotranspiration (ET) algorithm based on MODIS and global meteorology data has been proposed, which simplifies the calculation of vegetation cover fraction, calculating ET as the sum of daytime and nighttime components, adding soil heat flux calculation, improving estimates of stomatal conductance, aerodynamic resistance and boundary layer resistance, separating dry canopy surface from the wet and dividing soil surface into saturated wet surface and moist surface.

TL;DR: An estimate of global land evapotranspiration from 1982 to 2008 is provided using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm, which suggests that increasing soil-moisture limitations on evapOTranspiration largely explain the recent decline of the global land-evapotranpiration trend.

TL;DR: In this article, the authors developed a global remote sensing evapotranspiration (ET) algorithm based on Cleugh et al.'s [Cleugh, H.A., R. Leuning, Q. Mu, S.W. Running (2007) Regional evaporation estimates from flux tower and MODIS satellite data.

TL;DR: In this article, two models were evaluated for their ability to estimate land surface evaporation at 16-day intervals using MODIS remote sensing data and surface meteorology as inputs.

TL;DR: New evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate is presented and it is shown that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually.