RegCM3 nested in HadAM3 scenarios A2 and B2: projected changes in extratropical cyclogenesis, temperature and precipitation over the South Atlantic Ocean

The RegCM3 (Regional Climate Model-version 3) was nested in HadAM3 model to simulate present (1975-1989, referred hereafter as RegHad) and two future climate scenarios (A2 and B2 from 2071 to 2085, referred as RegA2 and RegB2) over the South America (SA) and South Atlantic Ocean (SAO). Projected changes in the air temperature, precipitation, low level circulation and cyclogenesis climatology were investigated. The cyclogenesis were identified using an automatic scheme for tracking based on the minimum of relative vorticity (zeta) from 10-m height wind. During summer, a general decrease (increase) in the precipitation is projected by RegA2 and RegB2 over the northeastern SA (center-west and south Brazil, north Argentina and Uruguay). For winter, an anomalous low level anticyclonic circulation is associated with the reduction in the rainfall over the central part of southern Brazil in RegA2 and RegB2 scenarios. Similar to HadAM3, RegCM3 projects larger warming in A2 scenario. For the present climate, when compared to HadAM3, RegHad defines better both the location of the main cyclogenetic areas and its annual cycle near southwestern SAO. The projections indicate a reduction in the total number of cyclones of -7.2% and -4.7% for RegA2 and RegB2, respectively, while HadAM3 reduction is -4.5% for both scenarios. The decrease is larger for initially intense cyclones (zeta <=-<= 2.5 x 10(-5) s-(1)): -20.9% (RegA2) and -11.3% (RegB2). For the lifetime, distance traveled and mean velocity of the cyclones, the A2 and B2 scenarios present mean values close to the present climate ( 3 days, 1900 km, and 9 m s(-1), respectively). Regarding the initial mean vorticity of the systems, RegB2 simulates values similar to the present climate, but they are initially weaker in RegA2. In general, RegA2 and RegB2 show a large decrease in the number of cyclones over the southern SAO due to an anticyclonic anomaly covering SAO between 30-55A degrees S. The reduction is larger in the scenario with higher concentrations of greenhouse gases (RegA2).

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.

Implications of climate change on mitigation potential estimates for forest sector in India

Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m(2)/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (-5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (-2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS-a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.

A macroeconomic analysis of adaptation to climate change impacts on forests in India

We examine the potential for adaptation to climate change in Indian forests, and derive the macroeconomic implications of forest impacts and adaptation in India. The study is conducted by integrating results from the dynamic global vegetation model IBIS and the computable general equilibrium model GRACE-IN, which estimates macroeconomic implications for six zones of India. By comparing a reference scenario without climate change with a climate impact scenario based on the IPCC A2-scenario, we find major variations in the pattern of change across zones. Biomass stock increases in all zones but the Central zone. The increase in biomass growth is smaller, and declines in one more zone, South zone, despite higher stock. In the four zones with increases in biomass growth, harvest increases by only approximately 1/3 of the change in biomass growth. This is due to two market effects of increased biomass growth. One is that an increase in biomass growth encourages more harvest given other things being equal. The other is that more harvest leads to higher supply of timber, which lowers market prices. As a result, also the rent on forested land decreases. The lower prices and rent discourage more harvest even though they may induce higher demand, which increases the pressure on harvest. In a less perfect world than the model describes these two effects may contribute to an increase in the risk of deforestation because of higher biomass growth. Furthermore, higher harvest demands more labor and capital input in the forestry sector. Given total supply of labor and capital, this increases the cost of production in all the other sectors, although very little indeed. Forestry dependent communities with declining biomass growth may, however, experience local unemployment as a result.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Modelling European winter wind storm losses in current and future climate

Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

Geodetic mass balance of Azarova glacier, Kodar Mountains, eastern Siberia, and its links to observed and projected climatic change

The Kodar Mountains in eastern Siberia accommodate 30 small, cold-based glaciers with a combined surface area of about 19 km2. Very little is known about these glaciers, with the first survey conducted in the late 1950s. In this paper, we use terrestrial photogrammetry to calculate changes in surface area, elevation, volume and geodetic mass balance of the Azarova Glacier between 1979 and 2007 and relate these to meteorological data from nearby Chara weather station (1938-2007). The glacier surface area declined by 20±6.9% and surface lowered on average by 20±1.8 m (mean thinning: 0.71 m a-1) resulting in a strongly negative cumulative and average mass balance of -18±1.6 m w.e. and -640±60 mm w.e.a-1 respectively. The July-August air temperature increased at a rate of 0.036oC a-1 between 1979 and 2007 and the 1980-2007 period was, on average, around 1oC warmer than 1938-1979. The regional climate projections for A2 and B2 CO2 emission scenarios developed using PRECIS regional climate model indicate that summer temperatures will increase in 2071–2100 by 2.6-4.7°C and 4.9-6.2°C respectively in comparison with 1961–1990. The annual total of solid precipitation will increase by 20% under B2 scenario but decline by 3% under A2 scenario. The length of the ablation season will extend from July–August to June-September. The Azarova Glacier exhibits high sensitivity to climatic warming due to its low elevation, exposure to comparatively high summer temperatures, and the absence of a compensating impact of cold season precipitation. Further summer warming and decline of solid precipitation projected under the A2 scenario will force Azarova to retreat further while impacts of an increase in solid precipitation projected under the B2 scenario require further investigation.

Loss potentials associated with European windstorms under future climate conditions

Possible changes in the frequency and intensity of windstorms under future climate conditions during the 21st century are investigated based on an ECHAM5 GCM multi-scenario ensemble. The intensity of a storm is quantified by the associated estimated loss derived with using an empirical model. The geographical focus is ‘Core Europe’, which comprises countries of Western Europe. Possible changes of losses are analysed by comparing ECHAM5 GCM data for recent (20C, 1960 to 2000) and future climate conditions (B1, A1B, A2; 2060 to 2100), each with 3 ensemble members. Changes are quantified using both rank statistics and return periods (RP) estimated by fitting an extreme value distribution using the peak over threshold method to potential storm losses. The estimated losses for ECHAM5 20C and reanalysis events show similar statistical features in terms of return periods. Under future climate conditions, all climate scenarios show an increase in both frequency and magnitude of potential losses caused by windstorms for Core Europe. Future losses that are double the highest ECHAM5 20C loss are identified for some countries. While positive changes of ranking are significant for many countries and multiple scenarios, significantly shorter RPs are mostly found under the A2 scenario for return levels correspondent to 20 yr losses or less. The emergence time of the statistically significant changes in loss varies from 2027 to 2100. These results imply an increased risk of occurrence of windstorm-associated losses, which can be largely attributed to changes in the meteorological severity of the events. Additionally, factors such as changes in the cyclone paths and in the location of the wind signatures relative to highly populated areas are also important to explain the changes in estimated losses.

Estimation of wind storm impacts over Western Germany under future climate conditions using a statistical-dynamical downscaling approach

A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5A degrees N-15A degrees S band, both in summer and especially in winter, reaching up to 6-8A degrees C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4A degrees C and in winter between 3 and 5A degrees C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.

Impact of climate change on the phoma leaf spot of coffee in Brazil

The potential impact of global climate change on the spatial-temporal distribution of phoma leaf spot of coffee in Brazil was evaluated. Maps were prepared with the favorability of the climate to the occurrence of the disease in the current period and future. The future scenarios used were centered for the decades of 2010-2030, 2040-2060, and 2070-2090 (scenarios A2 and B2). These scenarios were obtained from six global climate models (GCM's) provided by the Intergovernmental Panel on Climate Change (IPCC). Assuming the future scenarios outlined by the IPCC, a reduction will occur in the occurrence of climatic favorability of phoma leaf spot in Brazil in both future scenarios (A2 and B2). As with the temporal distribution, the period of greatest risk of phoma leaf spot will tend to diminish in future decades. These planned changes will be larger in the A2 scenario compared to the predicted scenario B2. Despite the decrease in the favorability of phoma leaf spot in the country, some regions still present a potential risk of this disease. Furthermore, the increased frequency of extreme weather was not taken in to account. These will certainly influence the magnitude of potential impacts of climate change on the phoma leaf spot in Brazil.

The impact of climate change on the water sector in the Caribbean

This study econometrically analyses the projected impact of climate change on the water sector of nine Caribbean countries to 2100: Aruba, Barbados, Dominican Republic, Guyana, Montserrat, Jamaica, Netherlands Antilles, Saint Lucia, and Trinidad and Tobago. Overall, all countries, with the exception of Trinidad and Tobago, are expected to suffer aggregate losses as result of climate change in the early periods ca. 2020 under one or more scenarios. Over time, some countries experience declining negative impacts, as in the case of Guyana under the B2 scenario. Some countries, such as the Dominican Republic, is projected to suffer increasing losses under the B2 scenario and, for others, the impacts do not follow a defined trend. The A2 scenario offers the best outcome for all countries, except Jamaica (where BAU is most desirable), Montserrat (which performs most poorly under the A2 scenario), and the Netherlands Antilles, which does best under the B2 case. Overall, relative to 2006, the total demand for water in the Caribbean is expected to fall by 2030 by 11.3% to approximately 12,967 million cubic meters. This is due to the expected fall in agricultural water demand by approximately 36% in that period. However, by 2050, total water demand for the Caribbean will again exceed the 2006 level by approximately 4% to 14,896.33 106 m3. By 2100, water demand will increase almost fivefold to approximately 69,233.69 106 m3. Climate change is expected to affect all countries in the Caribbean. In some cases, there will be positive impacts that may continue to increase over time and, in other cases, the impact will be negative and worsen over time. Overall, the agricultural sector is expected to suffer the worst losses over any scenario, whilst growth in the industrial sectors is expected to be significant and contribute the most to increasing water demand over time.

An assessment of the economic impact of climate change on the Agriculture, Energy and Health sectors in Trinidad and Tobago

This report analyses the agriculture, energy, and health sectors in Trinidad and Tobago to assess the potential economic impacts of climate change on the sectors. The fundamental aim of this report is to assist with the development of strategies to deal with the potential impact of climate change on Trinidad and Tobago. It also has the potential to provide essential input for identifying and preparing policies and strategies to help advance the Caribbean subregion closer to solving problems associated with climate change and attaining individual and regional sustainable development goals. Some of the key anticipated impacts of climate change for the Caribbean include elevated air and sea-surface temperatures, sea-level rise, possible changes in extreme events and a reduction in freshwater resources. The economic impact of climate change on the three sectors was estimated for the A2 and B2 IPCC scenarios until 2050. An exploration of various adaptation strategies was also undertaken for each sector using standard evaluation techniques. The study of the impact of climate change on the agriculture sector focused on root crops, green vegetables and fisheries. For these sectors combined, the cumulative loss under the A2 scenario is calculated as approximately B$2.24 and approximately B$1.72 under the B2 scenario by 2050. This is equivalent to 1.37% and 1.05% of the 2008 GDP under the A2 and B2 scenarios, respectively. Given the potential for significant damage to the agriculture sector a large number of potential adaptation measures were considered. Out of these a short-list of 10 potential options were selected by applying 10 evaluation criteria. All of the adaptation strategies showed positive benefits. The analysis indicate that the options with the highest net benefits are: (1) Building on-farm water storage, (2) Mainstreaming climate change issues into agricultural management and (3) Using drip irrigation. Other attractive options include water harvesting. The policy decisions by governments should include these assessments, the omitted intangible benefits, as well as the provision of other social goals such as employment. The analysis of the energy sector has shown that the economic impact of climate change during 2011-2050 is similar under the A2 (US$142.88 million) and B2 (US$134.83 million) scenarios with A2 scenario having a slightly higher cost (0.737% of 2009 GDP) than the B2 scenario (0.695% of 2009 GDP) for the period. On the supply side, analyses indicate that Trinidad and Tobago’s energy sector will be susceptible to the climate change policies of major energy-importing countries (the United States of America and China), and especially to their renewable energy strategies. Implementation of foreign oil substitution policy by the United States of America will result in a decline in Trinidad and Tobago’s Liquefied Natural Gas (LNG) export (equivalent to 2.2% reduction in 2009 GDP) unless an alternative market is secured for the lost United States of America market. China, with its rapid economic growth and the highest population in the world, offers a potential replacement market for Trinidad and Tobago’s LNG export. In this context the A2 scenario will offer the best option for Trinidad and Tobago’s energy sector. The cost-benefit analysis undertaken on selected adaptation strategies reveal that the benefit-cost ratio of replacing electric water heaters with solar water heaters is the most cost-effective. It was also found that the introduction of Compact Fluorescent Light (CFL) and Variable Refrigerant Volume (VRV) air conditioners surpasses the projected cost of increased electricity consumption due to climate change, and provides an economic rationale for the adoption of these adaptation options even in a situation of increased electricity consumption occasioned by climate change. Finally, the conversion of motor fleets to Compressed Natural Gas (CNG) is a cost-effective adaptation option for the transport sector, although it has a high initial cost of implementation and the highest per capita among the four adaptation options evaluated. To investigate the effect of climate change on the health sector dengue fever, leptospirosis, food borne illnesses, and gastroenteritis were examined. The total number of new dengue cases for the period 2008 to 2050 was 204,786 for BAU, 153,725 for A2 and 131,890 for the B2 scenario. With regard to the results for leptospirosis, A2 and B2 seem to be following a similar path with total number of new cases in the A2 scenario being 9,727 and 9,218 cases under the B2 scenario. Although incidence levels in the BAU scenario coincided with those of A2 and B2 prior to 2020, they are somewhat lower post 2020. A similar picture emerges for the scenarios as they relate to food-borne illnesses and to gastroenteritis. Specifically for food-borne illnesses, the BAU scenario recorded 27,537 cases, the A2 recorded 28,568 cases and the B2 recorded 28,679 cases. The focus on the selected sources of morbidity in the health sector has highlighted the fact that the vulnerability of the country’s health sector to climate change does not depend solely on exogenously derived impacts, but also on the behaviour and practices among the population. It is clear that the vulnerability which became evident in the analysis of the impacts on dengue fever, leptospirosis and food-borne illnesses is not restricted solely to climate or other external factors. The most important adaptation strategy being recommended targets lifestyle, behaviour and attitude changes. The population needs to be encouraged to alter their behaviours and practices so as to minimise their exposure to harmful outcomes as it relates to the incidence of these diseases.