Robinson I. Negrón Juárez

Tropical cyclones disturb forest ecosystems and have the potential to alter forest structure and species composition as well as ecosystem functions including rates of nutrient cycling and biomass accumulation. Quantifying these forest disturbances is necessary to evaluate the extent and severity of damage for estimating biomass loss, developing regional carbon budgets, and making management decisions following hurricanes. In this study, we quantified forest disturbance (downed and dead and snapped trees) produced by hurricanes using a relationship between field‐measured tree mortality and Landsat data that can be broadly applied to Gulf Coast forest ecosystems impacted by hurricanes. Field‐measured tree mortality data was collected in Gulf Coast forests at 60 inventory plots established to monitor forest disturbance produced by hurricanes Katrina and Rita, which hit the region in 2005, and Hurricane Gustav, which hit the region in 2008. Large‐scale disturbance estimates were obtained by regressing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data that in turn were associated with Forest Inventory and Analysis (FIA) data from the U.S. Forest Service. The use of the general relationship produced a biomass loss from dead trees of 43.9 ± 8.4 Tg C for Hurricane Katrina and 37.9 ± 6.4 Tg C for Hurricane Rita, which are near the upper limit of the expected values reported in our previous studies across a number of different forest types. Our results provide an important contribution for reliable assessments of large‐scale disturbance produced by hurricanes in forest ecosystems. Improving our ability to accurately assess the impacts of hurricanes on forests and on terrestrial carbon cycles is particularly important given that climate projections suggest that hurricane intensity is likely to increase.

Climate change is expected to increase the intensity of extreme precipitation events in Amazonia that in turn might produce more forest blowdowns associated with convective storms. Yet quantitative tree mortality associated with convective storms has never been reported across Amazonia, representing an important additional source of carbon to the atmosphere. Here we demonstrate that a single squall line (aligned cluster of convective storm cells) propagating across Amazonia in January, 2005, caused widespread forest tree mortality and may have contributed to the elevated mortality observed that year. Forest plot data demonstrated that the same year represented the second highest mortality rate over a 15‐year annual monitoring interval. Over the Manaus region, disturbed forest patches generated by the squall followed a power‐law distribution (scaling exponent α = 1.48) and produced a mortality of 0.3–0.5 million trees, equivalent to 30% of the observed annual deforestation reported in 2005 over the same area. Basin‐wide, potential tree mortality from this one event was estimated at 542 ± 121 million trees, equivalent to 23% of the mean annual biomass accumulation estimated for these forests. Our results highlight the vulnerability of Amazon trees to wind‐driven mortality associated with convective storms. Storm intensity is expected to increase with a warming climate, which would result in additional tree mortality and carbon release to the atmosphere, with the potential to further warm the climate system.

Six rainfall datasets are compared over the Amazon basin, Northeast Brazil, and the Congo basin. These datasets include three gauge-only precipitation products from the Climate Prediction Center (CPC), Global Precipitation Climatology Center (GPCC), and Brazilian Weather Forecast and Climate Studies Center (CLMNLS), and three combined gauge and satellite precipitation datasets from the CPC Merged Analysis of Precipitation (CMAP), Global Precipitation Climatology Project (GPCP), and Tropical Rainfall Measuring Mission (TRMM) product. The pattern of the annual precipitation is consistently represented by these data, despite the differences in methods and periods of averaging. Quantitatively, the differences in annual precipitation among these datasets are 5% more than the Amazon domain (0°–15°S, 50°–70°W), 22% more than Northeast Brazil (5°–10°S, 35°–45°W), and 11% more than the Congo domain (5°N–10°S, 15°–30°E). Over the Amazon domain the rainfall variation is well correlated between CPC, TRMM, GPCP, and GPCC (r 2 > 0.9) except for the northwestern Amazon, whereas CMAP and CLMNLS were different from these four datasets. Over the Congo basin, the coefficient of determination between these rainfall datasets is generally below 0.7. The empirical orthogonal functions analysis suggests large discrepancies in interannual and decadal variations of rainfall among these datasets, especially for the Congo basin and for the South American region after 1998. In general, CMAP, GPCC, TRMM, and GPCP significantly agree over the tropical areas in South America.

Hurricanes can devastate thousands of hectares of forested area producing changes beyond simply vegetation damage and biomass loss. This study reports changes in regional climate associated with Hurricane Rita which made landfall on the Gulf Coastal Plain on September 24th, 2005. Results demonstrate that over severely disturbed forested areas, biogeophysical effects produced by Rita created anomalous precipitation patterns, with a decrease in precipitation the following winter, and an increase during the subsequent summer season. The dominant biogeophysical effect was a change in albedo caused by ∼14,000 km² of disturbed forested area (downed and dead, snapped and structurally damaged trees) from Rita, equivalent to a committed carbon release of 32 to 43% of the net annual U.S. sink in forest trees. As recent studies project a likely increase in hurricane intensity during the 21st century, understanding the potential impact of forest damage from hurricanes on regional climate is important.

The extent of evapotranspiration (E _T) over the Brazilian Amazon rainforest remains uncertain because in situ measurement sites do not cover the entire domain, and the fetch of these sites is only of the order of 10³ m. In this investigation we developed an empirical method to estimate E _T over the Brazilian Legal Amazon (BLA). The work was based on an improved physical understanding of what controls E _T over the Amazonia rainforest resulting from analyses of recent in situ observations. Satellite data used in this study include the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the surface radiation budget from the International Satellite Cloud Climatology Project (ISCCP). The empirical model was validated by measurements performed at four upland forest sites. The observed values and the calculated modelled values at these sites had the same mean and variance. On a seasonal scale, regional modelled E _T peaks during the austral spring (September to November), as reported in the literature. In addition, the empirical model allows us to estimate the regional seasonal and interannual distributions of E _T/precipitation rates.