Data for Nature Climate Change article 'Regional dry-season climate changes due to three decades of Amazonian deforestation'

More than 20% Amazon rainforest has been cleared in the past three decades
triggering important hydroclimatic changes. Small-scale (~few kilometers)
deforestation in the 1980s has caused thermally-triggered atmospheric
circulations that increase regional cloudiness and precipitation
frequency. However, these circulations are predicted to diminish as
deforestation increases. Here we use multi-decadal satellite records and
numerical model simulations to show a regime shift in the regional
hydroclimate accompanying increasing deforestation in Rondônia, Brazil.
Compared to the 1980s, present-day deforested areas in downwind western
Rondônia are found to be wetter than upwind eastern deforested areas
during the local dry season. The resultant precipitation change in the two
regions is approximately ±25% of the deforested area mean. Meso-resolution
simulations robustly reproduce this transition when forced with increasing
deforestation alone, showing a negligible role of large-scale climate
variability. Furthermore, deforestation-induced surface roughness
reduction is found to play an essential role in the present-day dry season
hydroclimate. Our study illustrates the strong scale-sensitivity of the
climatic response to Amazonian deforestation and suggests that
deforestation is sufficiently advanced to have caused a shift from a
thermally- to a dynamically-driven hydroclimatic regime. This submission
pertains to the Nature Climate Change article: Regional dry-season climate
changes due to three decades of Amazonian deforestation. This article uses
several satellite observations and numerical simulations to analyze the
regional hydroclimatic effects of contemporary deforestation in the Amazon
rainforest. This submission includes all the scripts used to generate the
figures, tables and numerically simulated model output reported in the
article. This submission also includes the cloud cover maps (and
associated MATLAB codes) generated using the GridSat dataset which support
the findings of this article. The associated processed land cover maps are
also provided. The user is referred to the README file for full details on
the usage of this submission.