Amazonian deforestation causes systematic changes in regional dry season precipitation. Some of these changes at contemporary large scales (a few hundreds of kilometers) of deforestation have been associated with a ‘dynamical mesoscale circulation’, induced by the replacement of rough forest with smooth pasture. In terms of decadal averages, this dynamical mechanism yields increased precipitation in downwind regions and decreased precipitation in upwind regions of deforested areas. Daily, seasonal, and interannual variations in this phenomenon may exist, but have not yet been identified or explained. This study uses observations and numerical simulations to develop relationships between the dynamical mechanism and the local- and continental-scale atmospheric conditions across a range of time scales. It is found that the strength of the dynamical mechanism is primarily controlled by the regional-scale thermal and dynamical conditions of the boundary layer, and not by the continental- and global-scale atmospheric state. Lifting condensation level and wind speed within the boundary layer have large and positive correlations with the strength of the dynamical mechanism. The strength of these relationships depends on time scale and is strongest over the seasonal cycle. Overall, the dynamical mechanism is found to be strongest during times when the atmosphere is relatively stable. Hence, for contemporary large scales of deforestation this phenomenon is found to be the prevalent convective triggering mechanism during the dry and parts of transition seasons (especially during the dry-to-wet transition), significantly affecting the hydroclimate during this period.
Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert
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.
Cara L. Buck; Jonathan D. Cohen; Field, Brent; Daniel Kahneman; Samuel M. McClure; Leigh E. Nystrom
Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.
This dataset contains all the data, model and MATLAB codes used to generate the figures and data reported in the article (DOI: 10.1002/2014JD022278). The data was generated during September 2013 and February 2014 using the Ocean-Land-Atmosphere Model also provided with this package. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.