Regional Climate Change Impact Research Articles

Networked resilience in rural Australia — a role for health promotion in regional responses to climate change

This paper provides a model for how health promotion teams might establish and support regional collaborations of organisations in a broad response to climate change that enables emergence of multiple strategies tailored to regional needs. Complex Adaptive Systems Theory (CAS) and Organisational Learning informed action to foster a Climate Change Collaboration that engaged in strategies to improve transport options, food security and energy sustainability. Social Network Analysis was used to evaluate the degree to which member organisations became networked, the evolution of key network qualities and the way the organisations were affiliated via their participation in emergent strategies. Between 2005 and 2009 a highly connected network of organisations emerged and rapidly evolved to collaborate for action on climate change. There were significant improvements in network density, centralisation, clustering and reciprocity. Member organisations collaborated on a broad range of strategies. Reducing regional impact of climate change is complex. It requires long-term collaboration between organisations that may not usually work together. Sustain Northern Rivers provides a successful model for achieving such collaboration.

The Regional Biogenic Emissions Response to Climate Changes and Ambient CO₂ in Southeast Asia

The emissions of isoprene from vegetation in the tropics have been regarded as one of the major sources of the global biogenic emission budget. As this emission is highly sensitive to temperature, one may expect significant changes to the emissions due to climate change. In this study, we explore the impact of regional climate change to the emissions of isoprene in Southeast Asia. The potential role of the combination of climate change and future atmospheric CO₂ concentration on isoprene emissions are also investigated. The latest generation of Hadley Centre regional climate modelling system, PRECIS (Providing Regional Climates for Impact Studies) was used to investigate the climate change in the region. The climate output dataset from the model was then used as input for the BVOC Emission Model, which was developed by Sheffield University and Lancaster University to estimate the emissions of biogenic volatile organic compounds. The projected temperature changes under the A₂ emission scenario was 2.5⁰C, which accounted an increase of 22% of isoprene emission from 29 to 37 TgC/yr if the CO₂ emission factor was excluded. Incorporation of higher concentration in future CO₂ emissions was found to offset the climate change impact on future emissions of isoprene in the region. With the CO₂ effects, the projected regional isoprene emissions in 2100 dropped from 28 to 25 TgC/yr. These results suggest that future emissions of isoprene in the region is largely buffered by a number of competing factors, which are certainly important to be considered in estimating the isoprene global budget. In a wider perspective, the anticipated high concentration of CO₂ in the future could lead to the disruption of the ozone, organic aerosol and methane formation through the competing influence with warmer climate on isoprene emissions from tropical vegetation.

Impact of Climate Change on Water Resources in Taiwan

This paper establishes a comprehensive assessment model to measure the regional impact of climate change on Taiwan's water resources. Working from future rainfall data simulated by Japan's high-resolution GCM model JMA/MRI TL959L60 in a SRES-A1B scenario, we first apply climate change to an assessment model of renewable water resources to estimate the volume of renewable water resources on a regional basis. We then conduct a water resources system simulation based on estimates of future water needs, regional reservoir effective capacity and renewable water resource volume. This paper uses three water resource assessment indicators: the annual water utilization ratio indicator, the water shortage indicator and the extreme event occurrence indicator. Through fuzzy comprehensive assessment, we divide the evaluation set into five levels: very good (L1), good (L2), fair (L3), poor (L4) and very poor (L5). Results indicate that, given the effects of future climate change (2080-2099) and the increase in water demand, future water resources conditions in northern and eastern Taiwan will not be significantly different from historical levels (1979-1998) and will maintain a ”good” level (L2), while the conditions in southern Taiwan will visibly deteriorate from its historical ”fair” level (L3) to ”poor” (L4); and the future conditions for central Taiwan will be ”poor” (L4). The initiation of adaptation options for water management in southern and central Taiwan would be needed by increasing reservoir capacity and reducing overall water use.

Statistical downscaling of sea-surface wind over the Peru–Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model

The key aspect of the ocean circulation off Peru–Chile is the wind-driven upwelling of deep, cold, nutrient-rich waters that promote a rich marine ecosystem. It has been suggested that global warming may be associated with an intensification of upwelling-favorable winds. However, the lack of high-resolution long-term observations has been a limitation for a quantitative analysis of this process. In this study, we use a statistical downscaling method to assess the regional impact of climate change on the sea-surface wind over the Peru–Chile upwelling region as simulated by the global coupled general circulation model IPSL-CM4. Taking advantage of the high-resolution QuikSCAT wind product and of the NCEP reanalysis data, a statistical model based on multiple linear regressions is built for the daily mean meridional and zonal wind at 10 m for the period 2000–2008. The large-scale 10 m wind components and sea level pressure are used as regional circulation predictors. The skill of the downscaling method is assessed by comparing with the surface wind derived from the ERS satellite measurements, with in situ wind observations collected by ICOADS and through cross-validation. It is then applied to the outputs of the IPSL-CM4 model over stabilized periods of the pre-industrial, 2 × CO2 and 4 × CO2 IPCC climate scenarios. The results indicate that surface along-shore winds off central Chile (off central Peru) experience a significant intensification (weakening) during Austral winter (summer) in warmer climates. This is associated with a general decrease in intra-seasonal variability.

The impact of warming on the appearance of furunculosis in fish of the James Bay region, Quebec, Canada

A regional climate change impact assessment was conducted which investigated the timing of the first appearance of furunculosis caused by the bacterium, Aeromonassalmonicida, in fish of the Ouje-Bougoumou region of northern Quebec, Canada. Historical data were used to assess whether there was a temporal relationship between increased temperatures (observed climate data) and the appearance of furunculosis (traditional environmental knowledge was used to provide context). To project future impacts of climate change, climate models and lake models were used. Regression analysis revealed a significant, positive temporal trend in mean air temperature. The temperature range conducive to A. salmoncida survival coincided with the first appearance of furunculosis. In addition, it is predicted that lake temperatures will remain suitable for the presence of A. salmonicida into the future; it is likely that the disease will persist throughout the twenty-first century. Climate change appears to be a factor explaining the onset of furunculosis; however, other factors/stressors cannot be discounted, such as, the effects past mining activities near the lakes of the Ouje-Bougoumou region have had on the body burden of contaminants in the fish (and the potential effects on the fish immune system).

Model estimates of net primary productivity, evapotranspiration, and water use efficiency in the terrestrial ecosystems of the southern United States during 1895–2007

The effects of global change on ecosystem productivity and water resources in the southern United States (SUS), a traditionally ‘water-rich’ region and the ‘timber basket’ of the country, are not well quantified. We carried out several simulation experiments to quantify ecosystem net primary productivity (NPP), evapotranspiration (ET) and water use efficiency (WUE) (i.e., NPP/ET) in the SUS by employing an integrated process-based ecosystem model (Dynamic Land Ecosystem Model, DLEM). The results indicated that the average ET in the SUS was 710 mm during 1895–2007. As a whole, the annual ET increased and decreased slightly during the first and second half of the study period, respectively. The mean regional total NPP was 1.18 Pg C/yr (525.2 g C/m 2/yr) during 1895–2007. NPP increased consistently from 1895 to 2007 with a rate of 2.5 Tg C/yr or 1.10 g C/m 2/yr, representing a 27% increase. The average WUE was about 0.71 g C/kg H 2O and increased about 25% from 1895 to 2007. The rather stable ET might explain the resulting increase in WUE. The average WUE of different biomes followed an order of: forest (0.93 g C/kg H 2O) > wetland (0.75 g C/kg H 2O) > grassland (0.58 g C/kg H 2O) > cropland (0.54 g C/kg H 2O) > shrubland (0.45 g C/kg H 2O). WUE of cropland increased the fastest (by 30%), followed by shrubland (17%) and grassland (9%), while WUE of forest and wetland changed little from the period of 1895–1950 to the period of 1951–2007. NPP, ET and WUE showed substantial inter-annual and spatial variability, which was induced by the non-uniform distribution patterns and change rates of environmental factors across the SUS. We concluded that an accurate projection of the regional impact of climate change on carbon and water resources must consider the spatial variability of ecosystem water use efficiency across biomes as well as the interactions among all stresses, especially land-use and land-cover change and climate.

Alpine grassland degradation index and its response to recent climate variability in Northern Tibet, China

Northern Tibet is the headstream region for the Yangtze, Nu (Salween River), and Lancang (Mekong River). Sustaining the environmental conditions in the region is vital for Tibet and, as the source of many rivers, the whole of China and much of Asia. The study combines remote sensing data with data from other sources and national standards of grassland degradation index to assess alpine grassland degradation index between 1981 and 2004 in Northern Tibet. A Geographical Information System (GIS) was used to examine trends in grassland degradation index and its response to climate variability, including precipitation, temperature, and solar radiation. The results show that degradation has been very serious. The areas with a significant grassland degradation index trend accounted for 23.3% of the total grasslands in Northern Tibet. During 1981–2004, precipitation variability has benefited the recovery and protection of the grasslands, while temperature and solar radiation variability exacerbated grassland degradation index in Northern Tibet. The impact of regional climate change on grassland degradation index was on the balance more detrimental than positive from 1981 to 2004.

Impact of recent climate change on the hydrology of coastal Mediterranean rivers in Southern France

The purpose of this paper is to analyse the regional impact of recent climate change on the water resources in southern France. We produced spatial reconstructions of the monthly evolutions of temperature, precipitation and water discharge in 15 watersheds of six coastal river basins and examined the major changes based on trend analysis for the last 40 years. In this part of the Mediterranean, the general warming trend was strongly enhanced by changes in the atmospheric circulation patterns, characterized by a northward extension of the subtropical high pressure domain during spring and summer. During these seasons, monthly warming rates could achieve almost twice the mean annual warming rates. Although annual precipitation did not follow clear trends, water discharge significantly decreased in one third of the watersheds and accounted for an estimated 20% reduction of the water resources in this region. This concerns both the highest and lowest watersheds. In the former, the reduction is likely the result of a temperature induced switch of snowfall to rainfall at high altitudes. In the latter, the reduction of discharge seems to come from lower groundwater levels, which may be related to the temperature increase too, but also have other origins. The recent climatic evolution is consistent with most modelling simulations for the future, indicating that the reduction of the water resources will hold on, probably still enhanced by decreases in precipitation.

Dynamics of alpine grassland NPP and its response to climate change in Northern Tibet

Based on the remote sensing and meteorological data collected from the 1981-2004 period, we calculated the alpine grassland Net Primary Productivity (NPP) in Northern Tibet using the Carnegie-Ames-Stanford Approach (CASA), and subsequently analyzed the trend of grassland NPP changes and its response to climate change from 1981 to 2004. The results show that alpine grassland NPP in Northern Tibet was very low in the last 24 years with a relatively large yearly variation. Most of the grassland area (88.61%) in Northern Tibet did not show a significant annual NPP change. The area with a significant decrease of annual NPP variation accounted for only 11.30% of the total grasslands surface, whereas that with a significant increase accounted for 0.09%. In recent years, the precipitation variation in Northern Tibet resulted in an increase of grassland NPP, though solar radiation resulted in decreased grassland NPP. During the 1981-2004 period, total solar radiation, precipitation and temperature, with a decreasing impact magnitude factor, have impacted the grassland NPP in Northern Tibet. The impact of regional climate change on grassland NPP was overall more detrimental than positive.

Spatial variation in seabed temperatures in the Southern Ocean: Implications for benthic ecology and biogeography

The Antarctic seabed has traditionally been regarded as cold and thermally stable, with little spatial or seasonal variation in temperature. Here we demonstrate marked spatial variations in continental shelf seabed temperature around Antarctica, with the western Antarctic Peninsula shelf significantly warmer than shelves around continental Antarctica as a result of flooding of the shelf by Circumpolar Deep Water from the Antarctic Circumpolar Current. The coldest shelf seabed temperatures are in the Weddell Sea, Ross Sea, and Prydz Bay as a consequence of seasonal convection associated with strong air‐sea heat fluxes and sea‐ice formation. These waters constitute the dense precursors of Antarctic Bottom Water, and can descend down the adjacent slope to inject cold water into the Southern Ocean deep sea. Deep sea seabed temperatures are coldest in the Weddell Sea and are progressively warmer to the east. There is a distinct latitudinal gradient in the difference between seabed temperatures on the shelf and in the deep sea, with the deep sea warmer by up to ∼2 K at high latitudes and colder by ∼2 K around sub‐Antarctic islands. These differences have important consequences for benthic ecology and biogeography, understanding the evolutionary history of the Antarctic marine biota, and the impact of regional climate change.

GIS-based high-resolution spatial interpolation of precipitation in mountain–plain areas of Upper Pakistan for regional climate change impact studies

In this study, the baseline period (1960–1990) precipitation simulation of regional climate model PRECIS is evaluated and downscaled on a monthly basis for northwestern Himalayan mountains and upper Indus plains of Pakistan. Different interpolation models in GIS environment are used to generate fine scale (250 × 250 m2) precipitation surfaces from PRECIS precipitation data. Results show that the multivariate extension model of ordinary kriging that uses elevation as secondary data is the best model especially for monsoon months. Model results are further compared with observations from 25 meteorological stations in the study area. Modeled data show overall good correlation with observations confirming the ability of PRECIS to capture major precipitation features in the region. Results for low and erratic precipitation months, September and October, are however showing poor correlation with observations. During monsoon months (June, July, August) precipitation pattern is different from the rest of the months. It increases from south to north, but during monsoon maximum precipitation is in the southern regions of the Himalayas, and extreme northern areas receive very less precipitation. Modeled precipitation toward the end of the twenty-first century under A2 and B2 scenarios show overall decrease during winter and increase in spring and monsoon in the study area. Spatially, both scenarios show similar pattern but with varying magnitude. In monsoon, the Himalayan southern regions will have more precipitation, whereas northern areas and southern plains will face decrease in precipitation. Western and south western areas will suffer from less precipitation throughout the year except peak monsoon months. T test results also show that changes in monthly precipitation over the study area are significant except for July, August, and December. Result of this study provide reliable basis for further climate change impact studies on various resources.

Spatial heterogeneity and sources of soil carbon in southern African savannas

Knowledge of the southern Africa soil carbon pool, its heterogeneity, sources (from trees or grasses), and potential response to climate is extremely limited. In this study the Kalahari Transect (KT) was used as a representative savanna ecosystem to quantitatively evaluate the spatial heterogeneity of the soil carbon pool and its contributing sources. The KT encompasses a dramatic aridity gradient on relatively homogenous soils. Two sites were chosen along the KT, representing dry and wet conditions. In February–March 2005, soil samples were collected at each site along a 300 m transect. Stable carbon isotope (δ 13C) and organic carbon content (%C) of the soils were utilized in the assessment in conjunction with geostatistical analysis of the spatial patterns of soil δ 13C and %C. At the dry savanna site, well-defined patterns in both δ 13C and %C were observed that were related to the distribution of woody vegetation. At the wet savanna site, the spatial patterns of δ 13C and %C were somewhat less pronounced, but still were impacted by the distribution of woody vegetation. The relative contributions from C 3 and C 4 vegetation to the soil carbon pool at the wet site were independent of tree locations, but dependent on woody plant locations at the dry site. At the dry site, ~ 40% of the soil carbon was derived from C 3 vegetation, whereas at the wet site ~ 90% of the soil carbon originated from C 3 vegetation. These results represent an important step in understanding the impact of regional climate change (e.g., rainfall variations) on carbon sequestration in southern Africa by providing quantitative information on soil carbon spatial distributions and sources under different climatic conditions (e.g., different rainfall regimes).

Modeling GCM and scenario uncertainty using a possibilistic approach: Application to the Mahanadi River, India

Climate change impact assessment on water resources with downscaled General Circulation Model (GCM) simulation output is characterized by uncertainty due to incomplete knowledge about the underlying geophysical processes of global change (GCM uncertainties) and due to uncertain future scenarios (scenario uncertainties). Disagreement between different GCMs and scenarios in regional climate change impact studies indicates that overreliance on a single GCM with a scenario could lead to inappropriate planning and adaptation responses. This paper focuses on modeling GCM and scenario uncertainty using possibility theory in projecting streamflow of Mahanadi river, at Hirakud, India. A downscaling method based on fuzzy clustering and Relevance Vector Machine (RVM) is applied to project monsoon streamflow from three GCMs with two green house emission scenarios. Possibilities are assigned to all the GCMs with scenarios based on their performance in modeling the streamflow of the recent past (1991–2005), when there are signals of climate forcing. The possibilities associated with different GCMs and scenarios are used as weights in computing the possibilistic mean of the CDFs projected for three standard time slices 2020s, 2050s, and 2080s. The result shows that the value of streamflow at which the CDF reaches 1 reduces with time, which shows the reduction in probability of occurrence of extreme high flow events in future. Historic record of monsoon streamflow of Mahanadi river also shows similar decreasing trend, which may be due to the effect of high surface warming. Reduction in Mahandai streamflow is likely to pose a major challenge for water resources engineers in meeting water demands in future.

Spatial Scaling Links the Information across Scales: A Review of Methodologies Used in Regional Eco-hydrological Modeling

Spatial scaling has been one of the fundamental problems in eco-hydrological modeling over the past two decades. The input parameters for regional climate change impact research operating at a 1~50 km resolution cannot be directly derived from GCM (general circulation model) operating at a 100~500 km resolution. Conversely, large scale eco-hydrological models can only simulate the grid-based integrated response instead of directly parameterizing the small-scale earth surface processes. Therefore, upscaleing methodology is required to scale up the information derived from the small-scale to the information required for the large-scale models; and downscaling methodology is required to scale down the information from large scale model, i.e. GCM, to the information required for regional eco-hydrological models, which operate at a much smaller scale than the one for a GCM. Several methodologies have been developed over the past two decades to undertake these non-trivial upscaleing and downscaling tasks. in this paper, we discuss how the upscaling and downscaling schemes have been implemented in eco-hydrological modeling. Two primary downscaling schemes are reviewed in this paper. The first is empirical statistical downscaling, which disaggregates the information through establishing the empirical statistical relationships that link the information between small scale and large scale by comparing the large-scale values with long-term historical observation. The second scheme is dynamic downscaling, which disaggregates information by downscaling the information generated from dynamically coupling a RCM (regional climate model) with a GCM. Two upscaling schemes, empirical statistical upscaling and mosaic upscaling, are examined in this paper. Empirical statistical upscaling is achieved by assuming that the sub-grid variability of environmental variables can be represented by a probability density function (PDF), such as the VIC (variable infiltration capacity) model and the gamma distribution model. Mosaic upscaling scheme subdivides a big grid into several patches and the environmental variables are evaluated separately for each patch, and then averaged. We suggest an approach that combines the mosaic and PDF scheme for upscaling the modeling outputs from catchment to global scales.

Fine‐resolution climate projections enhance regional climate change impact studies

A new data set enhances the abilities of researchers and decision‐makers to assess possible future climates, explore societal impacts, and approach policy responses from a risk‐based perspective. The data set, which consists of a library of 112 fine‐resolution climate projections, based on 16 climate models and three greenhouse gas emissions scenarios, is now publicly available. Monthly climate projections from 1950 to 2099 were downscaled to a spatial resolution of ⅛° (about 140 square kilometers per grid cell) covering the conterminous United States and portions of Canada and Mexico.For the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, climate modeling groups produced hundreds of simulations of past and future climates. The colocation of these simulations in a single archive (at the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory (LLNL), established to facilitate assessment of general circulation models, or GCMs) and the conversion of all results to a common data format have made probabilistic, multi‐model projections and impact assessments practical. A remaining issue is that the spatial scale of climate model output is typically too coarse for regional impact studies. Multiple downscaling approaches exist for deriving regional climate from coarse‐resolution model output; these approaches are typically applied on an ad hoc basis to a particular region.

Consistency of Interdecadal Variation in the Summer Monsoon over Eastern China and Heterogeneity in Springtime Surface Air Temperatures

This study investigates the consistency of interdecadal variations in the East Asian summer monsoon (EASM) and changes in the heterogeneous structure of sealland springtime surface air temperature (SAT) over eastern China and the adjacent ocean (including the South China Sea and part of the Western Pacific Ocean). A profile of the summer mean meridional wind over eastern China for the past 40 years shows a coherent interdecadal weakening trend for the EASM. The decadal-scale (11-year running mean) summertime (June-August) wind and springtime (March-May) SAT fields are decomposed using the empirical orthogonal function (EOF) method. The results indicate that both the leading eigen-vector of the decadal-scale meridional wind and that for the SAT over East Asia account for more than 70% of the total variance. Their time coefiicients show a similar trend, with the transition from negative to positive values occurring around 1978; i.e., the EASM turned from a stronger phase to a weaker phase around 1978. The springtime sealland SAT distribution before and after 1978 also showed a shift in interdecadal trends. Therefore, the south-lowlnorth-high nature of the principal component of springtime SAT over eastern China is closely related to the progressive weakening of the EASM. Our results suggest that within the context of the regional impact of global climate change, heterogeneous changes in the regional springtime sea/land SAT in eastern Asia might in part have led to a weakening of the effect of sealland thermal driving on the EASM.

Global Warming and the Summertime Evapotranspiration Regime of the Alpine Region

Changes of the summer evapotranspiration regime under increased levels of atmospheric greenhouse gases are discussed for three Alpine river basins on the basis of a new set of simulations carried out with a high-resolution hydrological model. The climate change signal was inferred from the output of two simulations with a state-of-the-art global climate model (GCM), a reference run valid for 1961–1990 and a time-slice simulation valid for 2071–2100 under forcing from the A2 IPCC emission scenario. In this particular GCM experiment and with respect to the Alpine region summer temperature was found to increase by 3 to 4°C, whereas precipitation was found to decrease by 10 to 20%. Global radiation and water vapor pressure deficit were found to increase by about 5% and 2 hPa, respectively. On this background, an overall increase of potential evapotranspiration of about 20% relative to the baseline was predicted by the hydrological model, with important variations between but also within individual basins. The results of the hydrological simulations also revealed a reduction in the evapotranspiration efficiency that depends on altitude. Accordingly, actual evapotranspiration was found to increase at high altitudes and to the south of the Alps, but to decrease in low elevation areas of the northern forelands and in the inner-Alpine domain. Such a differentiation does not appear in the GCM scenario, which predicts an overall increase in evapotranspiration over the Alps. This underlines the importance of detailed simulations for the quantitative assessment of the regional impact of climate change on the hydrological cycle.

East–west asymmetry in long-term trends of landfast ice thickness in the Hudson Bay region, Canada

Ice cover in the Hudson Bay region (HBR) goes through a complete cryogenic cycle each year. Freeze-up typically occurs in October and November, ice cover reaches its peak thickness from late March to May, and water bodies in the HBR are usually ice-free beginning in early August. In this study, the timing and magnitude of the annual peak in ice thickness were identified for each year from weekly ice observations compiled by the Canadian Ice Service. The Mann-Kendall test was used to determine the statistical significance of the temporal trends, and their magnitude was esti- mated using the Theil-Sen approach. The results indicate an asymmetry in temporal trends of land- fast ice thickness; statistically significant thickening of the ice cover over time was detected on the western side of Hudson Bay, while a slight thinning lacking statistical significance was observed on the eastern side. This asymmetry is related to the variability of air temperature, snow depth, and the dates of ice freeze-up and break-up. Increasing maximum ice thickness at a number of stations is cor- related to earlier freeze-up due to negative temperature trends in autumn. Nevertheless, changes in maximum ice thickness were reciprocal to the variability in the amount of snow covering the ground. These results are in contrast to the projections from general circulation models (GCMs), and to the reduction in sea-ice extent and thickness observed in other regions of the Arctic. This contradiction must be addressed in regional climate change impact assessments.

The west nile virus outbreak in Israel (2000) from a new perspective: The regional impact of climate change

The West Nile Virus (WNV) outbreak in Israel in 2000 appeared after medical and climatic warning signs. Re-analysis of the epidemic from a new viewpoint, the regional impact of global warming, especially the worsening in the summers' heat conditions, is presented. The disease appeared averagely at a lag of 3–9 weeks (strongest correlation = lag of 7 weeks). The minimum temperature was found as the most important climatic factor that encourages the disease earlier appearance. Extreme heat is more significant than high air humidity for increasing WNV cases. An early extreme rise in the summer temperature could be a good indicator of increased vector populations. While 93.5% of cases were in the metropolitan areas, the disease was not reported in the sub-arid regions. The outbreak development was comparable to the cases from Romania (1996) and NYC (1999). Each of those epidemics appeared after a long heatwave.

Impact of regional climate change on human health

The World Health Organisation estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually. Many prevalent human diseases are linked to climate fluctuations, from cardiovascular mortality and respiratory illnesses due to heatwaves, to altered transmission of infectious diseases and malnutrition from crop failures. Uncertainty remains in attributing the expansion or resurgence of diseases to climate change, owing to lack of long-term, high-quality data sets as well as the large influence of socio-economic factors and changes in immunity and drug resistance. Here we review the growing evidence that climate-health relationships pose increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world. Potentially vulnerable regions include the temperate latitudes, which are projected to warm disproportionately, the regions around the Pacific and Indian oceans that are currently subjected to large rainfall variability due to the El Niño/Southern Oscillation sub-Saharan Africa and sprawling cities where the urban heat island effect could intensify extreme climatic events.