The economic impact of climate change on Kenyan crop agriculture: A Ricardian approach

This paper measures the economic impact of climate on crops in Kenya. We use cross-sectional data on climate, hydrological, soil and household level data for a sample of 816 households. We estimate a seasonal Ricardian model to assess the impact of climate on net crop revenue per acre. The results show that climate affects crop productivity. There is a non-linear relationship between temperature and revenue on one hand and between precipitation and revenue on the other. Estimated marginal impacts suggest that global warming is harmful for crop productivity. Predictions from global circulation models confirm that global warming will have a substantial impact on net crop revenue in Kenya. The results also show that the temperature component of global warming is much more important than precipitation. Findings call for monitoring of climate change and dissemination of information to farmers to encourage adaptations to climate change. Improved management and conservation of available water resources, water harvesting and recycling of wastewater could generate water for irrigation purposes especially in the arid and semi-arid areas.     

Impacts of agriculture and urbanization on the climate of the Northeastern United States

The climate sensitivity to specification of agricultural and urban land cover was investigated using the climate version of the Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) for 1990 over northeastern United States. The simulations were for 5 yr at a spatial resolution of 36 km. Urbanization resulted in near-surface temperature increases of more than 1 K over the urban sites during both winter and summer. The increase in summer temperature due to urbanization was more widespread than that due to the effect of agricultural land use. The conversion of forest to agricultural land resulted in a decrease in temperature of more than 0.5 K during winter and an increase of more than 1 K during summer over the sites of perturbation. The reduced temperature during winter is related to snow cover. Agricultural lands are covered by snow while the trees in non-agricultural areas protrude through the snow, reducing the albedo of the surface. The warming during summer reflects reduced evaporation. Urbanization also reduces the diurnal temperature range (DTR) by about 0.4 K.     

Measuring the economic impact of climate change on major South African field crops: a Ricardian approach

This study employed a Ricardian model to measure the impact of climate change on South Africa's field crops and analysed potential future impacts of further changes in the climate. A regression of farm net revenue on climate, soil and other socio-economic variables was conducted to capture farmer-adapted responses to climate variations. The analysis was based on agricultural data for seven field crops (maize, wheat, sorghum, sugarcane, groundnut, sunflower and soybean), climate and edaphic data across 300 districts in South Africa. Results indicate that production of field crops was sensitive to marginal changes in temperature as compared to changes in precipitation. Temperature rise positively affects net revenue whereas the effect of reduction in rainfall is negative. The study also highlights the importance of season and location in dealing with climate change showing that the spatial distribution of climate change impact and consequently needed adaptations will not be uniform across the different agro-ecological regions of South Africa. Results of simulations of climate change scenarios indicate many impacts that would induce (or require) very distinct shifts in farming practices and patterns in different regions. Those include major shifts in crop calendars and growing seasons, switching between crops to the possibility of complete disappearance of some field crops from some region.     

Multi-model Bayesian assessment of climate change in the northern annular mode

A typical question in climate change analysis is whether a certain observed climate characteristic, like a pronounced anomaly or an interdecadal trend, is an indicator of anthropogenic climate change or still in the range of natural variability. Many climatic features are described by one-dimensional index time series, like for instance the global mean temperature or circulation indices. Here, we present a Bayesian classification approach applied to the time series of the northern annular mode (NAM), which is the leading mode of Northern Hemisphere climate variability. After a pronounced negative phase during the 1950s and 1960s, the observed NAM index reveals a distinct positive trend, which is also simulated by various climate model simulations under enhanced greenhouse conditions. The objective of this study is to decide whether the observed temporal evolution of the NAM may be an indicator of global warming. Given a set of prior probabilities for disturbed and undisturbed climate scenarios, the Bayesian decision theorem decides whether the observed NAM trend is classified in a control climate, a greenhouse-gas plus sulphate aerosol climate or a purely greenhouse-gas induced climate as derived from multi-model ensemble simulations.The three climate scenarios are well separated from each other in terms of the 30-year NAM trends. The multi-model ensembles contain a weak but statistically significant climate change signal in the form of an intensification of the NAM. The Bayesian classification suggests that the greenhouse-gas scenario is the most probable explanation for the observed NAM trend since 1960, even if a high prior probability is assigned to the control climate. However, there are still large uncertainties in this classification result because some periods at the end of the 19th century and during the “warm” 1920s are also classified in an anthropogenic climate, although natural forcings are likely responsible for this early NAM intensification. This demonstrates a basic shortcoming of the Bayesian decision theorem when it is based on one-dimensional index time series like the NAM index.     

The effect of climate change on carbon in Canadian peatlands

Peatlands, which are dominant features of the Canadian landscape, cover approximately 1.136 million km², or 12% of the land area. Most of the peatlands (97%) occur in the Boreal Wetland Region (64%) and Subarctic Wetland Region (33%). Because of the large area they cover and their high organic carbon content, these peatlands contain approximately 147 Gt soil carbon, which is about 56% of the organic carbon stored in all Canadian soils.A model for estimating peatland sensitivity to climate warming was used to determine both the sensitivity ratings of various peatland areas and the associated organic carbon masses. Calculations show that approximately 60% of the total area of Canadian peatlands and 51% of the organic carbon mass in all Canadian peatlands is expected to be severely to extremely severely affected by climate change.The increase in average annual air temperature of 3–5 °C over land and 5–7 °C over the oceans predicted for northern Canada by the end of this century would result in the degradation of frozen peatlands in the Subarctic and northern Boreal wetland regions and severe drying in the southern Boreal Wetland Region. In addition, flooding of coastal peatlands is expected because of the predicted rise in sea levels. As a result of these changes, a large part of the carbon in the peatlands expected to be severely and extremely severely affected by climate change could be released into the atmosphere as carbon dioxide (CO₂) and methane (CH₄), which will further increase climate warming.     

Transient projections of permafrost distribution in Canada during the 21st century under scenarios of climate change

Most general circulation models (GCMs) project that climate will be warmer in the 21st century, especially in high latitudes. Climate warming will induce permafrost degradation, which would have great impacts on hydrology, ecosystems and soil biogeochemistry, and could destabilize the foundations of infrastructure. In this study, we simulated transient changes of permafrost distribution in Canada in the 21st century using a process-based permafrost model driven by six GCM-generated climate scenarios. The results show that the area underlain by permafrost in Canada would be reduced by 16.0–19.7% from the 1990s to the 2090s. This estimate was smaller than equilibrium projections because the ground thermal regime was in disequilibrium at the end of the 21st century and permafrost degradation would continue. The simulation shows significant permafrost thaw from the top: On average for the area where permafrost exists in all the years during 1990–2100, active-layer thickness increased by 0.3–0.7 m (or 41–104%), the depth to permafrost table increased by 1.9–5.0 m, and the area with taliks increased exponentially. Permafrost was also thawed from the bottom in southern regions.     

The link between abrupt climate change and basin stratigraphy: a numerical approach

To use basin stratigraphy for studying past climate change, it is important to understand the influence of evolving boundary conditions (river discharge and sediment flux, initial bathymetry, sea level, subsidence) and the complex interplay of the redistribution processes (plumes, turbidity currents, debris flows). To provide understanding of this complexity, we have employed source to sink numerical models to evaluate which process dominates the observed variability in a sedimentary record of two coastal Pacific basins, Knight Inlet in British Columbia and the Eel Margin of northern California.During the last glacial period, the Eel River supplied comparatively more sediment with a less variable flux to the ocean, while today the river is dominated by episodic events. Model results show this change in the variability of sediment flux to be as important to the deposit character as is the change in the volume of sediment supply. Due to the complex interaction of flooding events and ocean storm events, the more episodic flood deposits of recent times are less well preserved than the flood deposits associated with an ice-age climate.In Knight Inlet, the evolving boundary conditions (rapidly prograding coastline, secondary transport by gravity flows from sediment failures) are a strong influence on the sedimentary record. The delta and gravity flow deposits punctuate the sedimentary record formed by hemipelagic sedimentation from river plumes. Missing time intervals due to sediment failures can take away the advantage of the otherwise amplified lithologic record of discharge events, given the enclosed nature of the fjord basin.     

Uncertainties in climate change prediction: El Niño-Southern Oscillation and monsoons

The sensitivity of climate phenomena in the low latitudes to enhanced greenhouse conditions is a scientific issue of high relevance to billions of people in the poorest countries of the globe. So far, most studies dealt with individual model results. In the present analysis, we refer to 79 coupled ocean–atmosphere simulations from 12 different climate models under 6 different IPCC scenarios. The basic question is as to what extent various state-of-the-art climate models agree in predicting changes in the main features of El Niño-Southern Oscillation (ENSO) and the monsoon climates in South Asia and West Africa. The individual model runs are compared with observational data in order to judge whether the spatio-temporal characteristics of ENSO are well reproduced. The model experiments can be grouped into multi-model ensembles. Thus, climate change signals in the classical index time series, in the principal components and in the time series of interannual variability can be evaluated against the background of internal variability and model uncertainty.There are large differences between the individual model predictions until the end of the 21st century, especially in terms of monsoon rainfall and the Southern Oscillation index (SOI). The majority of the models tends to project La Niña-like anomalies in the SOI and an intensification of the summer monsoon precipitation in India and West Africa. However, the response barely exceeds the level of natural variability and the systematic intermodel variations are larger than the impact of different IPCC scenarios. Nonetheless, there is one prominent climate change signal, which stands out from model variations and internal noise: All forced model experiments agree in predicting a substantial warming in the eastern tropical Pacific. This oceanic heating does not necessarily lead to a modification of ENSO towards more frequent El Niño and/or La Niña events. It simply represents a change in the background state of ENSO. Indeed, we did not find convincing multi-model evidence for a modification of the wavelet spectra in terms of ENSO or the monsoons. Some models suggest an intensification of the annual cycle but this signal is fairly model-dependent. Thus, large model uncertainty still exists with respect to the future behaviour of climate in the low latitudes. This has to be taken into account when addressing climate change signals in individual model experiments and ensembles.     

Numerical modeling of the response of alluvial rivers to Quaternary climate change

A numerical model, which simulates the dynamics of alluvial river channels on geological (Quaternary) time scales, is presented. The model includes water flow, channel dimensions, sediment transport and channel planform type. A number of numerical experiments, which investigate the response of an alluvial river to imposed sequences of water and sediment supply, with special emphasis on the time lags between these controlling variables, as well as a downstream discharge increase, are presented. It is found that the influence of the time lags can be substantial, having major implications for the reconstructions of palaeo climate based on river channel behavior documented in the geological record. The model is further applied to both a conceptual warm–cold–warm cycle and a reconstructed evolution of the river Meuse, the Netherlands, during the Late Glacial–Holocene warming. Results show that the model is capable of explaining the response of this river, although better validation against palaeoenvironmental data remains necessary.     

The possible response of life zones in China under global climate change

The response of natural vegetation to climate change is of global concern. In this research, an aggregated Holdridge Life Zone System was used to study the possible response of life zones in China under doubled atmospheric CO₂ concentration with the input climatic parameters at 0.5×0.5° resolution of longitude and latitude from NCAR regional climate model 2 (RegCM2) coupled with the CSIRO global climate model. The results indicate that the latitudinal distribution of life zones would become irregular because of the complicated climate change. In particular, new life zones, such as subtropical desert (SD), tropical desert (TDE) and tropical thorn woodland (TTW), would appear. Subtropical evergreen broadleaved forest (SEBF), tropical rainforest and monsoon forest (TRF), SD, TDE and TTW zones would appear in the northeastern China. Cool-temperate mixed coniferous and broadleaved forest (CMC) and warm-temperate deciduous broadleaved forest (WDBF) zones would appear at latitudes 25–35°N. The temperate desert (TD) in the western China would become Tibetan high-cold plateau (THP), SEBF, WDBF and temperate steppe (TS), and a large part of THP would be replaced by TRF, TDE, SEBF, TS and TTW. The relative area (distribution area/total terrestrial area) of CMC, TRF, TDE and TTW zone would increase about 3%, 21%, 3% and 6%, respectively. However, the relative area of SEBF, TS, TD and THP would decrease about 5%, 3%, 19% and 4%, respectively. In all, the relative area of forests (CCF, CMC, WDBF, SEBF, TRF) would increase about 15%, but the relative area of desert (TD, SD, TDE, and TTW) and THP would decrease about 9% and 4%, respectively. Therefore, responses of different life zones in China to climate change would be dramatic, and nationwide corridors should be considered for the conservation of migrating species under climate change.     

Seasonal temperature responses to land-use change in the western United States

In the western United States, more than 79 000 km² has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land–atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs) – RSM, RegCM3, MM5-CLM3, and DRCM – to conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (− 1.4 to − 3.1 °C) and maximum (− 2.9 to − 6.1 °C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest.     

A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change

Hunger knows no boundaries or borders. While much research has focused on undernutrition on a national scale, this report evaluates it at subnational levels for Sub-Saharan Africa (SSA) to pinpoint hotspots where the greatest challenges exist. Undernutrition is assessed with a spatial resolution of 30 arc-minutes by investigating anthropometric data on weight and length of individuals. The impact of climate change on production of six major crops (cassava, maize, wheat, sorghum, rice and millet) is analyzed with a GIS-based Environmental Policy Integrated Climate (GEPIC) model with the same spatial resolution. Future hotspots of hunger are projected in the context of the anticipated climate, social, economic, and bio-physical changes. The results show that some regions in northern and southwestern Nigeria, Sudan and Angola with a currently high number of people with undernutrition might be able to improve their food security situation mainly through increasing purchasing power. In the near future, regions located in Ethiopia, Uganda, Rwanda and Burundi, southwestern Niger, and Madagascar are likely to remain hotspots of food insecurity, while regions located in Tanzania, Mozambique and the Democratic Republic of Congo might face more serious undernutrition. It is likely that both the groups of regions will suffer from lower capacity of importing food as well as lower per capita calorie availability, while the latter group will probably have sharper reduction in per capita calorie availability. Special attention must be paid to the hotspot areas in order to meet the hunger alleviation goals in SSA.     

Future desertification and climate change: The need for land-surface system evaluation improvement

In already drought-stressed areas and places with the potential for desertification as a result of greenhouse-induced change, high quality model-derived climate projections are essential for sustainable management. Today's challenge is how to select from the plethora of models and proposed new analyses the tools most likely to be valid for areas already water-stressed and those threatened by future surface moisture reduction. Here, the land-surface skills of models involved in the IPCC Fourth Assessment Report and new techniques of isotopic enrichment of components of evapotranspiration are analyzed. Both are found to have shortcomings. Surprisingly poor reporting of fundamental components of the land-surface system in standard model output was the largest challenge for widely accepted models. We show that very few of a large group (20) of today's climate models report land-surface water and energy budgets correctly in a well-controlled international experiment and that most fail basic conservation tests. Our analysis of a smaller (5) experiment suggests that isotopic techniques employed in arid zone irrigation management may not transition to evaluation and model improvement. Land-surface conditions important for policy are found to be poorly reported which raises questions about equal weighting given by international assessments to all models: good and bad.     

Simulated circum-Arctic climate changes by the end of the 21st century

This study investigates future changes of the Arctic climate by the end of the 21st century, simulated by the regional climate model HIRHAM forced with the ECHAM5/MPI-OM general circulation model and assuming the SRES A1B emission scenario. This assessment provides the regional patterns of future circulation, temperature, and precipitation in the Arctic by the end of the 21st century. The magnitude of winter and summer temperature and precipitation is projected to increase, while their interannual variability is projected to change seasonally and is regionally dependent. The regional-scale response of the temperature and precipitation is associated with changes in storm tracks and atmospheric baroclinicity. During winter, the regions of strongest baroclinicity are shifted northward and strengthened. Changes in the seasonal temperature and precipitation are accompanied by changes in their extremes. Extreme warm and cold events are significantly projected to change, with relative changes of seasonal precipitation being larger than those of precipitation extremes.     

Increased aridity in the Mediterranean region under greenhouse gas forcing estimated from high resolution simulations with a regional climate model

We use three measures of aridity, the Köppen climate classification, the UNEP aridity index and the Budyko dryness index, to estimate the possible effects of late 21st century climate change on the Mediterranean region under increased greenhouse gas concentrations (A2 and B2 IPCC emission scenarios) as simulated with a high resolution (20 km grid interval) regional climate model (the ICTP RegCM). A basic validation of the reference simulation along with a brief discussion of the surface climate changes for the A2 and B2 scenarios is also provided. Analysis of the changes in all three aridity measures indicates that by the end of the 21st century the Mediterranean region might experience a substantial increase in the northward extension of dry and arid lands, particularly in the central and southern portions of the Iberian, Italian, Hellenic and Turkish peninsulas and in areas of southeastern Europe (e.g. Romania and Bulgaria), the Middle East, northern Africa and major Islands (Corsica, Sardinia and Sicily). Most Ice-Cap areas of the Alps are also projected to disappear. These effects are due to a large warming and pronounced decrease in precipitation, especially during the spring and summer seasons. In addition, fine scale topography and coastline features affect the aridity change signal. We identify the southern Mediterranean as a region particularly vulnerable to water stress and desertification processes under climate change conditions.     

The effect of vegetation in a climate model simulation on the Younger Dryas

The effect of vegetation on the Younger Dryas (YD) climate is studied by comparing the results of four experiments performed with the ECHAM-4 atmospheric general circulation model (AGCM): (1) modern control climate, (2) simulation with YD boundary conditions, but with modern vegetation, (3 and 4) identical to (2), but with paleo-vegetation. Prescribing paleo-vegetation instead of modern vegetation resulted in temperature anomalies (both positive and negative) of up to 4°C in the Northern Hemisphere mid-latitudes, mainly as an effect of changes in forest cover (change in albedo). Moreover, changes in precipitation and evaporation were found, most notably during December–January–February (DJF) in the tropics and were caused by the replacement of forests by grasslands. These results are consistent with other model studies on the role of vegetation changes on climate and they suggest that it is important in paleoclimate simulation studies to prescribe realistic vegetation types, belonging to the period of interest. However, in our case the addition of YD vegetation did not improve the agreement with proxy data in Europe, as the temperatures were increasing during winter compared to the YD simulation with modern vegetation. It must be noted that this increase was not statistically significant. The model-data mismatch suggests that other factors probably played an important role, such as permafrost and atmospheric dust. We infer that during the last glacial-interglacial transition, the time lag between the first temperature increase and the northward migration of trees, estimated at 500–1000 years, could have delayed the warming of the Eurasian continent. The relatively open vegetation that existed during the early stages of the last glacial-interglacial transition had a relatively high albedo, thus tempering warming up of the Eurasian land surfaces.     

Sediment flux sensitivity to climate change: A case study in the Longchuanjiang catchment of the upper Yangtze River, China

Climate change may affect the sediment generation and transportation processes and the consequent sediment flux in a river. The sensitivity of suspended sediment flux to climate change in the Longchuanjiang catchment is investigated with Artificial Neural Networks (ANNs). ANNs were calibrated and validated using sediment flux data from 1960 to 1990 during which the influence from human activities was relatively stable. The established ANN is used to predict the responses of sediment flux to 25 hypothetical climate scenarios, which were generated by adjusting the baseline temperature up to − 1, 1, 2 and 3 °C and by scaling the baseline precipitation by +/− 10% and +/− 20%. The results indicated when temperature remains unchanged, an increase in rainfall will lead to a rise in sediment flux; when rainfall level remains unchanged, an increase in temperature is likely to result in a decrease in sediment flux. Same percentage of changes in rainfall and temperature are likely to trigger higher responses in wetter months than in drier months. However, it is the combination of the change in temperature and rainfall that determines the change of sediment flux in a river. Higher sediment flux is expected to appear under wetter and warmer climate, when higher transport capacity is accompanied by higher erosion rate.     

Aeolian dust experiment on climate impact: An overview of Japan–China joint project ADEC

The Aeolian Dust Experiment on Climate Impact (ADEC) was initiated in April 2000 as a joint five-year Japan–China project. The goal was to understand the impact of aeolian dust on climate via radiative forcing (RF). Field experiments and numerical simulations were conducted from the source regions in northwestern China to the downwind region in Japan in order to understand wind erosion processes temporal and spatial distribution of dust during their long-range transportation chemical, physical, and optical properties of dust and the direct effect of radiative forcing due to dust. For this, three intensive observation periods (IOP) were conducted from April 2002 to April 2004.The in situ and network observation results are summarized as follows: (1) In situ observations of the wind erosion process revealed that the vertical profile of moving sand has a clear size dependency with height and saltation flux and that threshold wind velocity is dependent on soil moisture. Results also demonstrated that saltation flux is strongly dependent on the parent soil size distribution of the desert surface. (2) Both lidar observations and model simulations revealed a multiple dust layer in East Asia. A numerical simulation of a chemical transport model, CFORS, illustrated the elevated dust layer from the Taklimakan Desert and the lower dust layer from the Gobi Desert. The global-scale dust model, MASINGAR, also simulated the dust layer in the middle to upper free troposphere in East Asia, which originated from North Africa and the Middle East during a dust storm in March 2003. Raman lidar observations at Tsukuba, Japan, found the ice cloud associated with the dust layer at an altitude of 6 to 9 km. Analysis from lidar and the radio-sonde observation suggested that the Asian dust acted as ice nuclei at the ice-saturated region. These results suggest the importance of dust's climate impact via the indirect effect of radiative forcing due to the activation of dust into ice nuclei. (3) Studies on the aerosol concentration indicated that size distributions of aerosols in downwind regions have bimodal peaks. One peak was in the submicron range and the other in the supermicron range. The main soluble components of the supermicron peak were Na⁺, Ca²⁺, NO₃⁻, and Cl⁻. In the downwind region in Japan, the dust, sea salt, and a mixture of the two were found to be dominant in coarse particles in the mixed boundary layer. (4) Observation of the optical properties of dust by sky-radiometer, particle shoot absorption photometer (PSAP), and Nephelometer indicated that unpolluted dust at source region has a weaker absorption than originally believed.A sensitivity experiment of direct RF by dust indicated that single scattering albedo is the most important of the optical properties of dust and that the sensitivity of instantaneous RF in the shortwave region at the top of the atmosphere to the refractive index strongly depends on surface albedo. A global scale dust model, MASINGAR, was used for evaluation of direct RF due to dust. The results indicated the global mean RF at the top and the bottom of the atmosphere were − 0.46 and − 2.13 W m^− 2 with cloud and were almost half of the RF with cloud-free condition.     

Quantifying the response of forest carbon balance to future climate change in Northeastern China: Model validation and prediction

In this study, we report on the validation of process-based forest growth and carbon and nitrogen model of TRIPLEX against observed data, and the use of the model to investigate the potential impacts and interaction of climate change and increasing atmospheric CO₂ on forest net primary productivity (NPP) and carbon budgets in northeast of China. The model validation results show that the simulated tree total volume, NPP, total biomass and soil carbon are consistent with observed data across the Northeast of China, demonstrating that the improved TRIPLEX model is able to simulate forest growth and carbon dynamics of the boreal and temperate forest ecosystems at regional scale. The climate change would increase forest NPP and biomass carbon but decrease overall soil carbon under all three climate change scenarios. The combined effects of climate change and CO₂ fertilization on the increase of NPP were estimated to be 10–12% for 2030s and 28–37% in 2090s. The simulated effects of CO₂ fertilization significantly offset the soil carbon loss due to climate change alone. Overall, future climate change and increasing atmospheric CO₂ would have a significant impact on the forest ecosystems of Northeastern China.     

Agricultural irrigation demand under present and future climate scenarios in China

The anticipated change of climatic conditions within the next decades is thought to have far reaching consequences for agricultural cropping systems. The success of crop production in China, the world's most populous country, will also have effects on the global food supply. More than 30% of the cropping area in China is irrigated producing the major part of the agricultural production. To model the effects of climate change on irrigation requirements for crop production in China a high-resolution (0.25°, monthly time series for temperature, precipitation and potential evapotranspiration) gridded climate data set that specifically allows for the effects of topography on climate was integrated with digital soil data in a GIS. Observed long-term trends of monthly means as well as trends of interannual variations were combined for climate scenarios for the year 2030 with average conditions as well as ‘best case’ and ‘worst case’ scenarios.Regional cropping calendars with allowance for multiple cropping systems and the adaptation of the begin and length of the growing season to climatic variations were incorporated in the FAO water balance model to calculate irrigation amounts to obtain maximum yields for the period 1951–1990 and the climate scenarios.During the period 1951–1990 irrigation demand displayed a considerable variation both in temporal and spatial respects. Future scenarios indicate a varied pattern of generally increasing irrigation demand and an enlargement of the subtropical cropping zone rather than a general northward drift of all zones as predicted by GCM models. The effects of interannual variability appear to have likely more impact on future cropping conditions than the anticipated poleward migration of cropping zones.