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Renato Ramos da Silva and Roni Avissar

Abstract

A series of numerical simulations were performed to evaluate the capability of the Regional Atmospheric Modeling System (RAMS) to simulate the evolution of convection in a partly deforested region of the Amazon basin during the rainy season, and to elucidate some of the complex land–atmosphere interactions taking place in that region. Overall, it is demonstrated that RAMS can simulate properly the domain-average accumulated rainfall in Rondônia, Brazil, when provided with reliable initial profiles of atmospheric relative humidity and soil moisture. It is also capable of simulating important feedbacks involving the energy partition at the ground surface and the formation of convection. In general, more water in the soil and/or the atmosphere produces more rainfall. However, these conditions affect the onset of rainfall in opposite ways; while higher atmospheric relative humidity leads to early rainfall, higher soil moisture delays its formation. As compared to stratiform clouds, which tend to cover a large area, convective clouds are localized and they let relatively more solar radiation reach the ground surface. As a result, a stronger sensible heat flux is released at the ground surface, which enhances the atmospheric instability and reinforces convection. Simulations using horizontal grid elements 2 and 4 km in size show a delay and decrease of rainfall as compared to simulations with high-resolution grids whose elements are not larger than 1 km and, as a result, afflict RAMS performance. It is concluded that RAMS can be used as a reliable tool to simulate the various hydrometeorological processes involved in land-cover changes as a result of deforestation in this region.

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Renato Ramos da Silva, David Werth, and Roni Avissar

Abstract

State-of-the-art socioeconomic scenarios of land-cover change in the Amazon basin for the years 2030 and 2050 are used together with the Regional Atmospheric Modeling System (RAMS) to simulate the hydrometeorological changes caused by deforestation in that region under diverse climatological conditions that include both El Niño and La Niña events. The basin-averaged rainfall progressively decreases with the increase of deforestation from 2000 to 2030, 2050, and so on, to total deforestation by the end of the twenty-first century. Furthermore, the spatial distribution of rainfall is significantly affected by both the land-cover type and topography. While the massively deforested region experiences an important decrease of precipitation, the areas at the edge of that region and at elevated regions receive more rainfall. Propagating squall lines over the massively deforested region dissipate before reaching the western part of the basin, causing a significant decrease of rainfall that could result in a catastrophic collapse of the ecosystem in that region. The basin experiences much stronger precipitation changes during El Niño events as deforestation increases. During these periods, deforestation in the western part of the basin induces a very significant decrease of precipitation. During wet years, however, deforestation has a minor overall impact on the basin climatology.

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Renato Ramos da Silva, Gil Bohrer, David Werth, Martin J. Otte, and Roni Avissar

Abstract

Meteorological observations and model simulations are used to show that the catastrophic ice storm of 4–5 December 2002 in the southeastern United States resulted from the combination of a classic winter storm and a warm sea surface temperature (SST) anomaly in the western Atlantic Ocean. At the time of the storm, observations show that the Atlantic SST near the southeastern U.S. coast was 1.0°–1.5°C warmer than its multiyear mean. The impact of this anomalous SST on the ice accumulation of the ice storm was evaluated with the Regional Atmospheric Modeling System. The model shows that a warmer ocean leads to the conversion of more snow into freezing rain while not significantly affecting the inland surface temperature. Conversely, a cooler ocean produces mostly snowfall and less freezing rain. A similar trend is obtained by statistically comparing observations of ice storms in the last decade with weekly mean Atlantic SSTs. The SST during an ice storm is significantly and positively correlated with a deeper and warmer melting layer.

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