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Citation:Khanna, J., and D. Medvigy (2014), Strong control of surface roughness variations on the simulated dry season regional atmospheric response to contemporary deforestation in Rondônia, Brazil, J. Geophys. Res. Atmos., 119, 13,078, doi:10.1002/2014JD022278. Abstract The atmospheric effects of Amazon deforestation have frequently been studied in the context of small scales (≈1 km) and very large scales (hundreds of kilometers). However, analysis of intermediate-scale deforestation (tens of kilometers) has received less attention, despite the fact that it better represents the contemporary landscape in some parts of the Amazon. In this study, the dynamic and thermodynamic effects of contemporary intermediate-scale deforestation in Rondônia, Brazil are investigated through variable resolution Global Circulation Model (GCM) simulations carried out with the Ocean-Land-Atmosphere Model. In particular, the atmospheric response to surface roughness changes brought about by deforestation is emphasized. This study shows that reductions in surface roughness associated with intermediate-scale deforestation give rise to a mesoscale circulation. This circulation is capable of convective triggering, but it also weakens the turbulent exchange of energy between land and atmosphere. Furthermore, this mesoscale circulation has distinct impacts on the hydroclimates of the western and eastern halves of Rondônia, increasing shallow cloudiness in the former while suppressing it in the latter. These results show that the atmospheric response to contemporary intermediate-scale deforestation in Rondônia is likely to be more influenced by differences in surface roughness between forest and forest clearings than by the differences in the surface energy partitioning.

The conventional method of calculating atmospheric temperature profiles using Rayleigh-scattering lidar measurements has limitations that necessitate abandoning temperatures retrieved at the greatest heights, due to the assumption of a pressure value required to initialize the integration at the highest altitude. An inversion approach is used to develop an alternative way of retrieving nightly atmospheric temperature profiles from the lidar measurements. Measurements obtained by the Purple Crow lidar facility located near The University of Western Ontario are used to develop and test this new technique. Our results show temperatures can be reliably retrieved at all heights where measurements with adequate signal-to-noise ratio exist. A Monte Carlo technique was developed to provide accurate estimates of both the systematic and random uncertainties for the retrieved nightly average temperature profile. An advantage of this new method is the ability to seed the temperature integration from the lowest rather than the greatest height, where the variability of the pressure is smaller than in the mesosphere or lower thermosphere and may in practice be routinely measured by a radiosonde, rather than requiring a rocket or satellite-borne measurement. Thus, this new technique extends the altitude range of existing Rayleigh-scatter lidars 10-15 km, producing the equivalent of four times the power-aperture product.

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.