Timely monitoring of crop lands is important in order to make agricultural activities more
sustainable, as well as ensuring food security. The use of Earth Observation (EO) data …

The perfect knowledge of yield before harvest has been a wish puzzling human being since
the beginning of agriculture because seasonal forecast of crop yield plays a critical role in …

1 Introduction Traditionally, research for agricultural development and improvement is based
on small plot experiments that are conducted for multiple years on a research station and, on …

Understanding crop responses to climate change is crucial for ensuring food security. Here,
we reviewed∼ 230 statistical crop modeling studies for major crops and summarized recent …

This work compares the performance of six bias correction methods for hydrological
modeling over 10 North American river basins. Four regional climate model (RCM) …

A statistical bias correction methodology for global climate simulations is developed and
applied to daily land precipitation and mean, minimum and maximum daily land …

To improve the prediction of crop yields at an aggregate scale, we developed a data
assimilation-crop modeling framework that incorporates remotely sensed soil moisture and …

We design, apply, and validate a methodology for correcting climate model output to
produce internally consistent fields that have the same statistical intensity distribution as the …

Climate change is expected to alter the hydrological cycle resulting in large-scale impacts
on water availability. However, future climate change impact assessments are highly …

Future climate model scenarios depend crucially on the models' adequate representation of
the hydrological cycle. Within the EU integrated project Water and Global Change (WATCH) …