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The Amazon rain forest may undergo significant change in response to future climate change. To determine the likelihood and causes of such changes, the authors analyzed the output of 24 models from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and a dynamic vegetation model, Vegetation-Global-Atmosphere-Soil (VEGAS), driven by these climate output. Their results suggest that the core of the Amazon rain forest should remain largely stable because rainfall in the core of the basin is projected to increase in nearly all models. However, the periphery, notably the southern edge of Amazonia and farther south into central Brazil (SAB), is in danger of drying out, driven by two main processes. First, a decline in precipitation of 11%% during the southern Amazonia's dry season (May-September) reduces soil moisture. Two dynamical mechanisms may explain the forecast reduction in dry season rainfall: 1) a general subtropical drying under global warming when the dry season southern Amazon basin is under the control of subtropical high pressure and 2) a stronger north-south tropical Atlantic sea surface temperature gradient and, to a lesser degree, a warmer eastern equatorial Pacific. The drying corresponds to a lengthening of the dry season by approximately 10 days. The decline in soil moisture occurs despite an increase in precipitation during the wet season, because of nonlinear responses in hydrology associated with the decline in dry season precipitation, ecosystem dynamics, and an increase in evaporative demand due to the general warming. In terms of ecosystem response, higher maintenance cost and reduced productivity under warming may also have additional adverse impact. Although the IPCC models have substantial intermodel variation in precipitation change, these latter two hydroecological effects are highly robust because of the general warming simulated by all models. As a result, when forced by these climate projections, a dynamic vegetation model VEGAS projects an enhancement of fire risk by 20%%-30%% in the SAB region. Fire danger reaches its peak in Amazonia during the dry season, and this danger is expected to increase primarily because of the reduction in soil moisture and the decrease in dry season rainfall. VEGAS also projects a reduction of about 0.77 in leaf area index (LAI) over the SAB region. The vegetation response may be partially mediated by the CO2 fertilization effect, because a sensitivity experiment without CO2 fertilization shows a higher 0.89 decrease in LAI. Southern Amazonia is currently under intense human influence as a result of deforestation and land-use change. Should this direct human impact continue at present rates, added pressure to the region's ecosystems from climate change may subject the region to profound changes in the twenty-first century. [ABSTRACT FROM AUTHOR]

The sensitivity of surface energy and water fluxes to recent land cover changes is simulated for a small region in northern Mato Grosso, Brazil. The Simple Biosphere Model (SiB2) is used, driven by biophysical parameters derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution, to compare the effects of different land conversion types. The mechanisms through which changes in vegetation alter surface fluxes of energy, momentum, water, and carbon are analyzed for both wet and dry seasons. It is found that morphological changes contribute to warming and drying of the atmosphere while physiological changes, particularly those associated with a plant¿s photosynthetic pathway, counterbalance or exacerbate the warming depending on the type of conversion and the season. Furthermore, this study¿s results indicate that initial clearing of evergreen and transition forest to bare ground increases canopy temperature by up to 1.7°C. For subsequent land use such as pasture or cropland, the largest effect is seen for the conversion of evergreen forest to C3 cropland during the wet season,with a 21% decrease of the latent heat flux and 0.4°C increase in canopy temperature. The secondary conversion of pasture to cropland resulted in slight warming and drying during the wet season driven mostly by the change in carbon pathway from C4 to C3. For all conversions types, the daily temperature range is amplified, suggesting that plants replacing forest clearing require more temperature tolerance than the trees they replace. The results illustrate that the effect of deforestation on climate depends not only on the overall extent of clearing but also on the subsequent land use type. [ABSTRACT FROM AUTHOR]

The “cerrado” biome in central Brazil is rapidly being converted into pasture and agricultural crops with important consequences for local and regional climate change and regional carbon fluxes between the atmosphere and land surface. Satellite remote sensing provides an opportunity to monitor the highly diverse and complex cerrado biome, encompassing grassland, shrubland, woodland and gallery forests, and converted areas. In this study, the potential of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data is analyzed to discriminate among these diverse cerrado physiognomies and converted pastures based on their seasonal dynamics and phenology. Four years (2000–03) of MODIS 16-day composited, 250-m resolution vegetation index (VI) data were extracted over a series of biophysically sampled field study sites representing the major cerrado types. The temporal VI profiles over the cerrado formations exhibited high seasonal contrasts with a pronounced dry season from June to August and a wet growing season from November to March. The converted pasture areas showed the highest seasonal contrasts while the gallery forest formation had the lowest contrast. Seasonal VI variations were negatively correlated with woody canopy crown cover and provided a method to discriminate among converted cerrado areas, gallery forests, and the woody and herbaceous cerrado formations. The grassland and shrub cerrado formations, however, were difficult to separate based on their seasonal VI profiles. Maximum discrimination among the cerrado types occurred during the dry season where a positive linear relationship was found between VI and green cover. The annual integrated VI values showed the gallery forests and cerrado woodland as having the highest, and hence most annual productivity, while the more herbaceous shrub and grassland cerrado types were least productive. The cumulative VI profiles of converted cerrado, pasture areas varied distinctly in shape due to their strong dry season inactivity. Furthermore, the annual integrated VI values of the converted pastures differed significantly between the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) MODIS VI products, resulting in large discrepancies in productivity estimates relative to the native cerrado sites. This study shows that the MODIS seasonal–temporal VI profiles are highly useful in monitoring the cerrado biome and conversion-related activities. [ABSTRACT FROM AUTHOR]

Oxygen isotope speleothems have been widely used to infer past climate changes over tropical South America (TSA). However, the spatial patterns of the millennial precipitation and precipitation δ18O (δ18Op) response have remained controversial, and their response mechanisms are unclear. In particular, it is not clear whether the regional precipitation represents the intensity of the millennial South American summer monsoon (SASM). Here, we study the TSA hydroclimate variability during the last deglaciation (20–11 ka ago) by combining transient simulations of an isotope-enabled Community Earth System Model (iCESM) and the speleothem records over the lowland TSA. Our model reasonably simulates the deglacial evolution of hydroclimate variables and water isotopes over the TSA, albeit underestimating the amplitude of variability. North Atlantic meltwater discharge is the leading factor driving the TSA’s millennial hydroclimate variability. The spatial pattern of both precipitation and δ18Op show a northwest–southeast dipole associated with the meridional migration of the intertropical convergence zone, instead of a continental-wide coherent change as inferred in many previous works on speleothem records. The dipole response is supported by multisource paleoclimate proxies. In response to increased meltwater forcing, the SASM weakened (characterized by a decreased low-level easterly wind) and consequently reduced rainfall in the western Amazon and increased rainfall in eastern Brazil. A similar dipole response is also generated by insolation, ice sheets, and greenhouse gases, suggesting an inherent stability of the spatial characteristics of the SASM regardless of the external forcing and time scales. Finally, we discuss the potential reasons for the model–proxy discrepancy and pose the necessity to build more paleoclimate proxy data in central-western Amazon. Significance Statement We want to reconcile the controversy on whether there is a coherent or heterogeneous response in millennial hydroclimate over tropical South America and to clearly understand the forcing mechanisms behind it. Our isotope-enabled transient simulations fill the gap in speleothem reconstructions to capture a complete picture of millennial precipitation/δ18Op and monsoon intensity change. We highlight a heterogeneous dipole response in precipitation and δ18Op on millennial and orbital time scales. Increased meltwater discharge shifts ITCZ southward and favors a wet condition in coastal Brazil. Meanwhile, the low-level easterly and the summer monsoon intensity reduced, causing a dry condition in the central-western Amazon. However, the millennial variability of hydroclimate response is underestimated in our model, together with the lack of direct paleoclimate proxies in the central-west Amazon, complicating the interpretation of changes in specific paleoclimate events and posing a challenge to constraining the spatial range of the dipole. Therefore, we emphasize the necessity to increase the source of proxies, enhance proxy interpretations, and improve climate model performance in the future. [ABSTRACT FROM AUTHOR]

Climate change scenarios vary considerably over the Amazon region, with an extreme scenario projecting a dangerous (from the human perspective) increase of 3.8°°C in temperature and 30%% reduction in precipitation by 2050. The impacts of such climate change on Amazonian land-use dynamics, agricultural production, and deforestation rates are still to be determined. In this study, the authors make a first attempt to assess these impacts through a systemic approach, using a spatially explicit modeling framework to project crop yield and land-use/land-cover changes in the Brazilian Amazon by 2050. The results show that, without any adaptation, climate change may exert a critical impact on the yields of crops commonly cultivated in the Amazon (e.g., soybean yields are reduced by 44%% in the worst-case scenario). Therefore, following baseline projections on crop and livestock production, a scenario of severe regional climate change would cause additional deforestation of 181 000 km2 (++20%%) in the Amazon and 240 000 km2 (++273%%) in the Cerrado compared to a scenario of moderate climate change. Putting an end to deforestation in the Brazilian Amazon forest by 2020 (and of the Cerrado by 2025) would require either a reduction of 26%%--40%% in livestock production until 2050 or a doubling of average livestock density from 0.74 to 1.46 head per hectare. These results suggest that (i) climate change can affect land use in ways not previously explored, such as the reduction of yields entailing further deforestation, and (ii) there is a need for an integrated/multidisciplinary plan for adaptation to climate change in the Amazon. [ABSTRACT FROM AUTHOR]

The variation of air temperature at 2 m above the earth’s surface in South America (SA) between 1948 and 2007 is investigated primarily using the NCEP–NCAR reanalysis. In December–February (austral summer), the majority of SA has a mean temperature between 21° and 24°C during 1948–75, and for 1976–2007 the mean temperature is above 24°C. In June–August (austral winter), warmer temperatures are observed in the tropical region in the recent period. The results indicate that Northeast Brazil (NEB) and central Brazil are warmer in the more recent period. In the last seven years (2001–07) compared to the earlier periods, greater warming is noted in the tropical SA region, mainly in NEB and over the North Atlantic Ocean, and cooling is observed in part of the subtropical SA region. Supporting evidence for the warming in Brazil is given through analyses of station data and observational data. The results presented here indicate that the climate change over SA is likely not predominantly a result of variations in El Niño–Southern Oscillation (the most important coupled ocean–atmosphere phenomenon to produce climate variability over SA). Instead, the climate changes likely occur as a response to other natural variability of the climate and/or may be a result of human activity. However, even without ascertaining the specific causes, the most important finding in this work is to demonstrate that a change in the temperature patterns of SA occurred between 1948 and 2007. [ABSTRACT FROM AUTHOR]

Rainfall in South America as simulated by a 24-ensemble member of the ECHAM 4.5 atmospheric general circulation model is compared and contrasted with observations (in areas in which data are available) for the period 1976–2001. Emphasis is placed on determining the onset and end of the rainy season, from which its length and rain rate are determined. It is shown that over large parts of the domain the onset and ending dates are well simulated by the model, with biases of less than 10 days. There is a tendency for model onset to occur early and ending to occur late, resulting in a simulated rainy season that is on average too long in many areas. The model wet season rain rate also tends to be larger than observed. To estimate the relative importance of errors in wet season length and rain rate in determining biases in the annual total, adjusted totals are computed by substituting both the observed climatological wet season length and rate for those of the model. Problems in the rain rate generally are more important than problems in the length. The wet season length and rain rate also contribute substantially to interannual variations in the annual total. These quantities are almost independent, and it is argued that they are each associated with different mechanisms. The observed onset dates almost always lie within the range of onset of the ensemble members, even in the areas with a large model onset bias. In some areas, though, the model does not perform well. In southern Brazil the model ensemble average onset always occurs in summer, whereas the observations show that winter is often the wettest period. Individual members, however, do occasionally show a winter rainfall peak. In southern Northeast Brazil the model has a more distinct rainy season than is observed. In the northwest Amazon the model annual cycle is shifted relative to that observed, resulting in a model bias. No interannual relationship between model and observed onset dates is expected unless onset in the model and observations has a mutual relationship with SST anomalies. In part of the near-equatorial Amazon, there does exist an interannual relationship between onset dates. Previous studies have shown that in this area there is a relationship between SST anomalies and variations in seasonal total rainfall. [ABSTRACT FROM AUTHOR]

Understanding of climate influence on crop yields can help in the design of policies to reduce climate-related vulnerability in many parts of the world, including the target of this case study—the state of Ceará, Brazil. The study has examined the relationships between climate variations and corn yields and, in addition, has estimated the potential predictability of corn yields in Ceará drawing on the now well-established seasonal predictability of the region’s climate based on prevailing patterns of sea surface temperature (SST), especially in the tropical Atlantic and tropical Pacific Oceans. The relationships between corn yields and climate variables have been explored using observed data for the period of 1952–2001. A linear regression–based corn-yield model was evaluated by comparing the model-simulated yields with the observations using three goodness-of-fit measures: the coefficient of determination, the index of agreement, and the mean absolute error. A comparative performance analysis was carried out on several climate variables to determine the most appropriate climate index for simulating corn yields in Ceará. A weather index was defined to measure the severity of drought and flooding conditions in the growing season for corn. The analysis indicated that the weather index is the best climate parameter for simulating corn yields in Ceará. The observed weather index can explain 56.8% of the variance of the observed corn yields. High potential predictability of the weather index was revealed by the evaluation of an ensemble of 10 runs with the NCEP Regional Spectral Model nested into the ECHAM4.5 atmospheric general circulation model, driven with observed SSTs in each season for the period of 1971–2000. Whereas these runs are based on the actual observed SST pattern in each season, other studies have shown that persistence of SST over several months is sufficient for a true predictive capability. The aim here was to show that the SST-forced component of climate variation does translate into the weather features that are important for crop yields. Indeed, the results demonstrate the striking extent to which the year-to-year changes in SST force local climate characteristics that can specify the year-to-year variations in corn yields. The variance of corn yield explained by the SST-driven model was 49.5%. [ABSTRACT FROM AUTHOR]