Climate change in Central and South America: Recent trends, future projections, and impacts on regional agriculture

This report investigates the climate of two target regions of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS): Central and South America (CA and SA, respectively). The report assesses the implications of climate change for agriculture, with a particular focus on those aspects of climate change that will have greatest impact on the crops currently grown in each region. The study investigated the ability of General Circulation Models (GCMs) and downscaled climate change scenarios to reproduce already observed climates, to establish the reliability of future climate projections, as well as projections of how associated crops might grow under future conditions

Climate change effects on wheat yield and water use in oasis cropland

Agriculture of the inland arid region in Xinjiang depends on irrigation, which forms oasis of Northwest China. The production and water use of wheat, a dominant crop there, is significantly affected by undergoing climate variability and change. The objective of this study is to quantify interannual variability of wheat yield and water use from 1955 to 2006. The farming systems model APSIM (Agricultural Production Systems Simulator) was used to evaluate crop yield, evapotranspiration (ET), and water use efficiency of winter and spring wheat (Triticum aestivum L.) in Xinjiang from 1955 to 2006. The APSIM model was first calibrated and validated using 6 years of experimental data. The validated model was then applied to simulated wheat yield and ET using climatic and soil data for present crop cultivar. Simulated wheat yield under full irrigation have no significant decreasing trend from 1955 to 2006. Simulated growth duration of winter wheat was significantly decreased. Simulated ET of winter wheat was significantly correlated with measured pan evaporation. Simulated ET of winter wheat decreased significantly during the 52 years, with a decrease rate of 0.813 mm year-1. Cluster analysis showed that the variations of ET were mainly determined by solar radiation, nothing to do with the changes in temperature. The results identified the change trend of field ET under historical climate change, and determined the main meteorological factors which affect ET in this oasis. These results provide a measure for water demand, crop production and irrigation management under climate change in the oasis

Climate change impacts on food security in Sub-Saharan Africa: Insights from comprehensive climate change scenarios

Climate change impacts vary significantly, depending on the scenario and the Global Circulation Model (GCM) chosen. This is particularly true for Sub-Saharan Africa. This paper uses a comprehensive climate change scenario (CCC) based on ensembles of 17 GCMs selected based on their relative performance regarding past predictions of temperature and precipitation at the level of 2o x 2o grid cells, generated by a recently developed entropy-based downscaling model. Based on past performance, the effects of temperature and precipitation across the 17 GCMs are incorporated into a global hydrological model that is linked with IFPRI's IMPACT water and food projections model to assess the effects of climate change on food outcomes for the region. For Sub-Saharan Africa, the paper finds that the CCC scenario predicts consistently higher temperatures and mixed precipitation changes for the 2050 period. Compared to historic climate scenarios, climate change will lead to changes in yield and area growth, higher food prices and therefore lower affordability of food, reduced calorie availability, and growing childhood malnutrition in Sub-Saharan Africa.Climate change, hydrology, crop yield, food security,

Food security, farming, and climate change to 2050: Scenarios, results, policy options

As the global population grows and incomes in poor countries rise, so too, will the demand for food, placing additional pressure on sustainable food production. Climate change adds a further challenge, as changes in temperature and precipitation threaten agricultural productivity and the capacity to feed the world's population. This study assesses how serious the danger to food security might be and suggests some steps policymakers can take to remedy the situation.global food security, Climate change, Food prices, Agricultural productivity,

Comparison of statistical and dynamical downscaling methods for seasonal-scale winter precipitation predictions over north India

The main aim of the present study is to analyse the capabilities of two downscaling approaches (statistical and dynamical) in predicting wintertime seasonal precipitation over north India. For this purpose, a canonical correlation analysis (CCA) based statistical downscaling approach and dynamical downscaling approach (at 30 km) with an optimized configuration of the regional climate model (RegCM) nested in coarse resolution global spectral model have been used for a period of 28 years (1982–2009). For CCA, nine predictors (precipitation, zonal and meridional winds at 850 and 200 hPa, temperature at 200 hPa and sea surface temperatures) over three different domains were selected. The predictors were chosen based on the statistically significant teleconnection maps and physically based relationships between precipitation over the study region and meteorological variables. The validation revealed that both the downscaling approaches provided improved precipitation forecasts compared to the global model. Reasons for improved prediction by downscaling techniques have been examined. The improvement mainly comes due to better representation of orography, westerly moisture transport and vertical pressure velocity in the regional climate model. Furthermore, two bias correction methods namely quantile mapping (QM) and mean bias-remove (MBR) have been applied on downscaled RegCM, statistically downscaled CCA as well as the global model products. It was found that when the QM-based bias correction is applied on dynamically downscaled RegCM products, it has better skill in predicting wintertime precipitation over the study region compared to the CCA-based statistical downscaling. Overall, the results indicate that the QM-based bias-corrected downscaled RegCM model is a useful tool for wintertime seasonal-scale precipitation prediction over north India.Peer reviewedFinal Accepted Versio

Projected Climate Impacts to South African Maize and Wheat Production in 2055: A Comparison of Empirical and Mechanistic Modeling Approaches

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were 3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EMMM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EMMM comparisons to provide a fuller picture of crop-climate response uncertainties

Freshwater Resources and Their Management

This chapter explores the future impacts of climate change on freshwater resources and their management, mainly based on research published after the Working Group II Third Assessment Report (TAR; IPCC, 2001). Socio-economic aspects, adaptation issues, implications for sustainable development, as well as uncertainties and research priorities, are also covered. The focus is on terrestrial water in liquid form, due to its importance for freshwater management. Various aspects of climate change impacts on water resources and related vulnerabilities are presented, as well as the impacts on water-use sectors