Providing Regional Climates For Impacts Studies Research Articles

Potential overwintering boundary and voltinism changes in the brown planthopper, Nilaparvata lugens, in China in response to global warming

The brown planthopper Nilaparvata lugens (Stal) is a major rice insect pest in China and other Asian countries. This study assessed a potential northward shift in the overwintering boundaries and changes in the overwintering areas and voltinism of this planthopper species in China in response to global warming. Temperature data generated by 15 Global Circulation Models (GCMs) from 2010 to 2099 were employed to analyze the planthopper’s overwintering boundaries and overwintering areas in conjunction with three Special Report on Emissions Scenarios (SRES). Planthopper voltinism from 1961 to 2050 was analyzed in scenario A2 using degree-day models with projections from the regional circulation model (RCM) Providing Regional Climates for Impacts Studies (PRECIS). In both analyses, 1961–1990 served as the baseline period. Both the intermittent and constant overwintering boundaries were projected to shift northward; these shifts were more pronounced during later time periods and in scenarios A2 and A1B. The intermittent overwintering area was modeled to increase by 11, 24 and 44 %, and the constant overwintering area, by 66, 206 and 477 %, during the 2020s, 2050s and 2080s, respectively. Planthopper voltinism will increase by <0.5, 0.5–1.0 and 1.0–1.4 generations in northern, central and southern China, respectively, in 2021–2050. Our results suggest that the brown planthopper will overwinter in a much larger region and will produce more generations under future climate warming scenarios. As a result, the planthopper will exert an even greater threat to China’s rice production in the future.

Uncertainty in Future High Flows in Qiantang River Basin, China

AbstractUncertainties in high flows originating from greenhouse gas emissions scenarios, hydrological model structures, and their parameters for the Jinhua River basin, China, were assessed. The baseline (1961–90) and future (2011–40) climates for A1B, A2, and B2 scenarios were downscaled from the general circulation model (GCM) using the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model with a spatial resolution of 50 km × 50 km. Bias-correction methods were applied to the PRECIS-derived temperature and precipitation. The bias-corrected precipitation and temperature were used as inputs for three hydrological models [modèle du Génie Rural à 4 paramètres Journalier (GR4J), Hydrologiska Byråns Vattenbalansavdelning (HBV), and Xinanjiang] to simulate high flows. The parameter uncertainty was considered and quantified in the hydrological model calibration by means of the generalized likelihood uncertainty estimation (GLUE) method for each hydrological model for the three emissions scenarios. It was found that, compared with the high flows in the baseline period, the high flows in the future tended to decrease under scenarios A1B, A2, and B2. The largest uncertainty was observed in HBV, and GR4J had the smallest uncertainty. It was found that the major source of uncertainty in this study was from parameters, followed by the uncertainties from the hydrological model structure, and the emissions scenarios have the smallest uncertainty contribution to high flows in this study.

Climate variability and its impacts on water resources in the Upper Indus Basin under IPCC climate change scenarios

The output of a regional climate model (RCM), providing regional climate for impact studies (PRECIS), is used as input data to the hydrological model to produce inflow projections at the Tarbela Reservoir on the Indus River. Maximum temperature, minimum temperature and precipitation are investigated for possible climate change in the region. The hydrological model was calibrated for the 1995-2004 period and validated for the 1990-1994 period with almost 90% efficiencies. The projections of inflow to the Tarbela Reservoir show that there is an overall increase of 59.42% and 34.27% to the Tarbela Reservoir during the period of 2040-2069 under the A2 and the B2 scenarios, respectively. There will be much more water available in the future, with the highest inflow and comparatively more water shortage noted in the 2020s under the A2 scenario. Finally, the impacts of changing climates on the operation of Tarbela Dam are investigated.

Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones

End-of-century changes in Caribbean climate extremes are derived from the Providing Regional Climate for Impact Studies (PRECIS) regional climate model (RCM) under the A2 and B2 emission scenarios across five rainfall zones. Trends in rainfall, maximum temperature, and minimum temperature extremes from the RCM are validated against meteorological stations over 1979–1989. The model displays greater skill at representing trends in consecutive wet days (CWD) and extreme rainfall (R95P) than consecutive dry days (CDD), wet days (R10), and maximum 5-day precipitation (RX5). Trends in warm nights, cool days, and warm days were generally well reproduced. Projections for 2071–2099 relative to 1961–1989 are obtained from the ECHAM5 driven RCM. Northern and eastern zones are projected to experience more intense rainfall under A2 and B2. There is less consensus across scenarios with respect to changes in the dry and wet spell lengths. However, there is indication that a drying trend may be manifest over zone 5 (Trinidad and northern Guyana). Changes in the extreme temperature indices generally suggest a warmer Caribbean towards the end of century across both scenarios with the strongest changes over zone 4 (eastern Caribbean).

Variations in extreme temperature and precipitation for a Caribbean island: Trinidad

Temperature and precipitation in situ datasets for the Caribbean island, Trinidad for 1961–2010 were statistically analyzed using the RClimDex software and the Mann-Kendall test for trends. The annual, seasonal, and monthly findings were compared with regional projections; Providing Regional Climates for Impact Studies (PRECIS) and a 20 km atmospheric global circulation model, and a global projection of the Coupled Model Intercomparison Project Phase 3 (CMIP3). Overall, the seasonal and decadal results revealed patterns different from the annual warming. All the temperature indices were found to have warming patterns with the wet season, June to December, generally greater than the dry season, January to May. The warmest decade was 1980s, whereas globally, the decade 2001–2010 was the warmest. There was an increase in the annual maximum 5 day precipitation, RX5day, at the UWI station. During the dry season (1973–2010) at the UFS and UWI stations, the RX5day increased by 8.60 and 7.76 mm per decade, respectively, while the maximum 1-day precipitation, RX1day, increased by 2.92 and 8.90 mm per decade for the UFS and UWI, respectively. The 1980s was the wettest, and during the decade 2001–2010, there were above averages for the consecutive dry days (CDD) and the simple daily intensity index (SDII). The projections on both the regional and global outlooks suggest that this warming pattern will continue in the future. This small-scale study supports that seasonal and decadal analyses, in addition to the annual assessments, are significant for the understanding of the climate variability which is required for vulnerability and adaptation studies for small island states.

Climate variability and its impacts on runoff in the Kosasthaliyar sub-basin, India

&lt;p&gt;Research on the effect of climate variability/climate change on rainfall-runoff modeling is limited in humid tropical regions. Climate change has implications beyond the water resources sector, such as effects on agriculture and fisheries. Hence, such studies are becoming increasingly important. This study uses both historical data acquired in the field and future climate forecasts from General Circulation Model Hadley Centre Coupled Model, version 3 GCM HadCM3. These data are further downscaled using third generation of the Hadley Centre's regional climate model (HadRM3), with Providing REgional Climates for Impacts Studies (PRECIS) software under the three Quantifying Uncertainties in Model Projections (QUMPs). A horizontal resolution of 25 km X 25 km is used by the Centre for Climate Change and Adaptation Research, Anna University Chennai, for the state of Tamil Nadu. These downscaled data are used to study runoff changes due to climate change for the Kosasthaliyar sub-basin in South India. A trend analysis of the hydro-meteorological data for the sub-basin indicates that future rainfall is expected to decrease by approximately 10%, while the mean temperatures will increase by the year 2100. The runoff changes from 2011 to 2040 do not differ from those of the historical period of 1971 to 2000. This study is one of the first attempts to provide information on climate variability and its impacts on runoff in the Kosasthaliyar sub-basin.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt;Resumen&lt;/strong&gt;&lt;/p&gt;&lt;div class="page" title="Page 1"&gt;&lt;div class="section"&gt;&lt;div class="layoutArea"&gt;&lt;div class="column"&gt;&lt;p&gt;&lt;span&gt;La investigación del efecto variabilidad climática/cambio climático en el modelo pluviosidad/escorrentía es limitada en regiones tropicales húmedas, donde el cambio climático tiene implicaciones tanto en los recursos acuíferos, como &lt;/span&gt;&lt;span&gt;en la agricultura y la pesca. Por lo tanto este tipo de estudios han incrementado su importancia. Este estudio utiliza tanto los datos adquiridos en este campo como las predicciones climáticas del Modelo General de Circulación de la Célula de Hadley, en su versión 3GCM HadCM3. Estos datos fueron reducidos luego al utilizar la tercera generación del modelo climático regional del Centro Hadley (HadRM3), con el programa de Estipulación de Climas Regionales para Estudios de Impacto (PRECIS, en inglés), bajo los tres modelos de Cuantificación de la Incertidumbre en Proyecciones (QUMPs, en inglés). El Centro para el Cambio Climático y la Investigación de Adaptación de la Universidad Anna, de Chennai, en el estado Tamil Nadu, utiliza una escala horizontal de 25 kilómetros por 25 kilómetros. Esta reducción de datos se utiliza para estudiar los cambios de escorrentía por el cambio climático en la subcuenca de Kosasthaliyar, al sur de la India. Un análisis de tendencia de los datos hidrometeorológicos en la subcuenca indica que en el futuro la pluviosidad caerá en un 10 %, mientras que la temperatura media se incrementará para el año 2100. Los cambios de escorrentía para el período 2011-2040 no difieren de los del período 1971-2000. Este estudio es uno de los primeros acercamientos para proveer información sobre la variabilidad climática y sus &lt;/span&gt;&lt;span&gt;impactos en la escorrentía de la subcuenca de Khosastaliyar. &lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;

Impact of Climate Change on the Characteristics of Indian Summer Monsoon Onset

A high resolution regional climate modeling system, known as PRECIS (Providing REgional Climate for Impact Studies), developed by Hadley Centre for Climate Prediction and Research, UK, is applied for Indian subcontinent to assess the impact of climate change on the summer monsoon onset characteristics. The present day simulation (1961–1990) with PRECIS is evaluated for the characteristics of onset over Kerala, southernmost part of India, where the monsoon sets in over Indian landmass. The meteorological parameters like precipitation, outgoing long wave radiation (OLR), and low level winds are analysed to study the monsoon onset over Kerala. The model is able to capture the sudden and sharp increase of rainfall associated with the onset. The rapid built-up of convective activity over the southeastern Arabian Sea and Bay of Bengal is well represented by the model. PRECIS simulations, under scenarios of increasing greenhouse gas concentrations and sulphate aerosols, are analysed to study the likely changes in the onset characteristics in future, towards the end of present century (2071–2100). The analysis does not indicate significant difference in the mean onset dates in A2 and B2 scenarios. However, the variability of onset date is likely to be more towards the end of the 21st century especially in A2 scenario.

High-Resolution Probabilistic Projections of Temperature Changes over Ontario, Canada

Abstract Planning of mitigation and adaptation strategies to a changing climate can benefit from a good understanding of climate change impacts on human life and local society, which leads to an increasing requirement for reliable projections of future climate change at regional scales. This paper presents an ensemble of high-resolution regional climate simulations for the province of Ontario, Canada, developed with the Providing Regional Climates for Impacts Studies (PRECIS) modeling system. A Bayesian statistical model is proposed through an advance to the method proposed by Tebaldi et al. for generating probabilistic projections of temperature changes at gridpoint scale by treating the unknown quantities of interest as random variables to quantify their uncertainties in a statistical way. Observations for present climate and simulations from the ensemble are fed into the statistical model to derive posterior distributions of all the uncertain quantities through a Markov chain Monte Carlo (MCMC) sampling algorithm. Detailed analyses at 12 selected weather stations are conducted to investigate the practical significance of the proposed statistical model. Following that, maps of projected temperature changes at different probability levels are presented to help understand the spatial patterns across the entire province. The analysis shows that there is likely to be a significant warming trend throughout the twenty-first century. It also suggests that people in Ontario are very likely to suffer a change greater than 2°C to mean temperature in the forthcoming decades and very unlikely to suffer a change greater than 10°C to the end of this century.

Contribution of Drought to Potential Crop Yield Reduction in a Wheat-Maize Rotation Region in the North China Plain

With consecutive occurrences of drought disasters in China in recent years, it is important to estimate their potential impacts on regional crop production. In this study, we detect the impacts of drought on wheat and maize yield and their changes at a 0.5°×0.5° grid scale in the wheat-maize rotation planting area in the North China Plain under the A1B climate change scenario using the Decision Support System for Agrotechnology Transfer (DSSAT) model and the outputs of the regional climate modeling system – Providing Regional Climates for Impacts Studies (PRECIS). Self-calibrating palmer drought severity index was used as drought recognition indicator. Two time slices used for the study were the baseline (1961–1990) and 40 years of 2011–2050. The results indicate that the potential planting region for double crop system of wheat-maize would expend northward. The statistic conclusions of crop simulations varied considerably between wheat and maize. In disaster-affected seasons, wheat yield would increase in the future compared with baseline yields, whereas in opposite for maize yield. Potential crop yield reductions caused by drought would be lower for wheat and higher for maize, with a similar trend found for the ratio of potential crop yield reductions for both crops. It appears that the negative impact of drought on maize was larger than that on wheat under climate change A1B scenario.

Adaptation strategies to combat climate change effect on rice and mustard in Eastern India

The negative impact of climate change on crop production is alarming as the demand for food is expected to increase in coming years, at a rate of about 2 percent a year. Wet season rice (Oryza sativa) followed by mustard (Brassica juncea) is one of the prominent cropping sequences in Eastern India. Descreases in their productivity due to climate change will not only hamper the regional food security but also affect the global economy. Considering the fact, the present study aims to assess the impact of climate change on productivity of wet-season rice and mustard and to evaluate the effectiveness of agronomic adjustment as adaptation options. Crop growth simulation model (CGSM) is a very effective tool to predict the growth and yield of a crop. One CGSM, namely InfoCrop (Generic Crop Model), was calibrated and validated for the said crops for West Bengal State, Eastern India. After validation, the model was used to predict the yield under elevated thermal condition (1 and 3 °C rise over normal temperature). Moreover, the future weather situation as predicted by PRECIS (Providing Regional Climates for Impacts Studies) model was used as weather input of the CGSM and the yield was predicted for ten selected locations of West Bengal for the year 2025 and 2050. It was observed that the average yield reduction of the wet-season rice would be in the tune of about 20.0 % for 2025 and 27.8 % for 2050. The mustard yield of West Bengal may be reduced by 20.0 to 33.9 % for the year 2025 and up to 40 % for 2050. It was concluded that the negative impact of climate change on mustard grown in winter season will be more pronounced compared to wet-season rice. Adjustment of sowing time will be the simplest and effective adaptation option for both rice and mustard. Increased rate of nutrient application can sustain the rice yield under future climate. The older seedling at the time of transplanting of wet-season rice and increased seed rate of mustard were proved less effective.

Possible future changes in cyclonic storms in the Bay of Bengal, India under warmer climate

The aim of this paper is to study the model's simulated frequency, track, intensity and location of cyclonic storms (CSs) and severe cyclonic storms (SCSs) in the Bay of Bengal (BoB), India. For the purpose, the PRECIS (Providing REgional Climates for Impacts Studies) a regional climate modelling system, of UK Met Office, is used. This model is integrated for the period 1961-1990 (baseline) and the future time period 2071-2100 (High emission scenario, A2). To run the model, the initial and lateral boundary conditions are supplied by UK Met Office. The analysis of frequency, track, intensity and location are carried out for May, June, September and October for the period 1961-1990 and 2071-2100. To evaluate the model's performance in simulating storms frequency during 1961-1990, chi square test is carried out with observed storms for the same period. The model's simulated frequency of storms is an overestimation of observations although the frequency of model's simulated storms during 2071-2100 is less than that of during 1961-1990. In general, model's simulated storms are found moving in the northwest direction from their initial location in all months during 1961-1990 and 2071-2100. In model's simulations, the drop in central pressure is relatively more in the months of May, June, September and October during 2071-2100 compared with that during 1961-1990. During 2071-2100, more intense storms may be possible in the months of May and June compared with that of September and October. It is observed that the model is able to simulate the initial locations of storms during 1961-1990 and 2071-2100 close to observations for the months of June and September, especially.

Uncertainties in SWAT extreme flow simulation under climate change

Uncertainty in climate change impact analysis has been widely recognized. Analyzing it becomes an important task particularly when impact analysis results are used for adaptation purposes. A methodology aiming to investigate the impact of climate change and the separate and combined impacts of several uncertainty sources on future extreme flows in the Lanjiang catchment, East China is proposed. A regional climate model PRECIS (Providing REgional Climates for Impacts Studies) is applied to downscale the General Circulation Model (GCM) outputs and the extreme flows are simulated by the SWAT (Soil and Water Assessment Tool) model. Besides emission scenarios and extreme value models, the main uncertainty source, namely SWAT parameters is taken into account and the sequential uncertainty analysis method is employed to analyze the parameter uncertainties. The SWAT model calibration and validation results indicate that the model has a good performance in Lanjiang catchment. The projected future extreme flows show that the design discharges of small return periods are likely larger than those in the baseline period, while those of large return periods will be likely smaller than those in the baseline period at Misai, Quzhou and Lanxi stations. The uncertainty analysis results show that for small return periods such as 5 years, the uncertainty introduced from the SWAT model parameters is much larger than those from emission scenarios and extreme value models at Misai and Quzhou stations while for large return periods such as 50 years, the uncertainty introduced from all three sources are substantial. However, the already large uncertainty due to SWAT model parameters, emissions scenarios and extreme flow distributions might be dwarfed by GCM uncertainty, which is not concerned in this study.

Changes of rainfall extremes around the haor basin areas of Bangladesh using multi-member ensemble RCM

Haors are large, round-shaped floodplain depressions located in the North-Eastern region of Bangladesh. Extreme events such as heavy rainfall routinely affect the haor basin with flash floods. These haors are predicted to experience severe stress because of changes in rainfall and temperature patterns. The biotic community of the wetlands may not have enough time to adjust itself in such varying temperature and rainfall extremes. This paper evaluates various aspects of the future projections of rainfall and temperature extremes, including magnitudes and frequencies thereof. The impacts of extreme events are examined using Hadley Centre’s high-resolution regional climate model known as PRECIS (Providing REgional Climates for Impact Studies). Daily temperature and rainfall simulations of the 17-member ensembles are generated through Hadley Centre Coupled Model (HadCM3). These simulations are used in Rclimdex—a software specially designed for this study. A total of 12 core climate indices are computed, analyzed, and statistically examined (Mann–Whitney U test) over the space of three time slices—(1) short (2020s, i.e., 2011–2040), (2) medium (2050s, i.e., 2041–2070), and (3) long (2080s, i.e., 2071–2098). Here, the 1980s (1971–2000) are considered as the baseline period. The study has found that the highest significant variability in both rainfalls and temperatures was during the pre-monsoon season when flash floods normally occur. Also, rainy days are projected to be less frequent albeit more intense where the deeply flooded haors are located. Though the annual total rainfall does not show any difference in spatial distribution (except for in magnitude), the seasonal patterns of most extreme events show that the probable affected areas have shifted from North-east to further North. In addition, a significant increase in both RX1 (1-day maximum rainfall) and RX5 (5-day maximum rainfall) are projected during the 2080’s pre-monsoon season near Sunamganj. This projection also indicates the possible frequent occurrence of flash floods with high volumes. Probability distribution frequencies (PDF) show a rightward shift in time indicating an increase in the amount of total rainfall in the future. Exceptions are, however, found in case of PDFs for consecutive dry days (CDD) and consecutive wet days (CWD). The decrease in CWD is found to be more pronounced than that of CDD. All these projections made in this study are expected to contribute further in the advancements of the Master Planning of the haor area that was done by the government of Bangladesh in 2012.

Comparison of interpolation methods for estimating spatial distribution of precipitation in Ontario, Canada

ABSTRACTIn this study, different interpolation techniques in a geographical information system (GIS) environment are analysed and compared for estimating the spatial distribution of precipitation in the province of Ontario, Canada. A high‐resolution regional climate modelling system [Providing Regional Climates for Impacts Studies (PRECIS)] is used to simulate the present (1961–1990) and future (2071–2100) precipitation events for 12 meteorological stations over Ontario. The results verify that for the present case PRECIS simulates well the precipitation events when compared with observed data. The future precipitation events can be projected after the validation of PRECIS. Six interpolation methods are then used to generate spatial distribution of precipitation based on the projections of future precipitation of 12 meteorological stations; they include inverse distance weighting (IDW), global polynomial interpolation (GPI), local polynomial interpolation (LPI), radial basis functions (RBF), ordinary kriging (OK), and universal kriging (UK). Cross‐validation is applied to evaluate the accuracy of interpolation methods in terms of the root mean square error (RMSE). The results indicate that LPI is the optimal method with the least RMSE for interpolating the PRECIS precipitation. LPI is then used to analyse spatial variations of the average annual precipitation for the period of 2071–2100 over Ontario.

Analysis of Future Climate Scenarios over Central Uganda Cattle Corridor

The study employed a Regional Climate Model (RCM), Providing Regional Climates for Impact Studies (PRECIS), to examine the future climate scenarios over the central Uganda cattle corridor districts of Nakaseke and Nakasongola in the near future (2021-2050) and mid-century (2051-2080). The study was guided by two questions: what are the projected temperature and rainfall values for the central Uganda cattle corridor in relation to IPCC Special Report on Emission Scenarios (SRES) A2 and A1B Scenarios for the same periods; how do they compare with the new set of scenarios known as Representative Concentration Pathways (RCPs) in the same area for the same period? The scenarios were obtained using PRECIS software and delta methods using R software according to the AGMIP protocols for SRES and RCP; respectively. Results show both SRES A2 and A1B projecting temperature increases in average monthly, seasonal as well as annual for both near future and mid centuryperiods with A2 showing a mean annual temperature increase of 2.5 to 4.4°C in the near future and 4.5 to 6.0°C in the mid century relative to the 1981-2010 average compared to A1B which shows annual temperature increase of 0.7 -1.7°C in the near future and 1.7-3.5°C in the far future. The same trend is observed for RCP 4.5 and RCP 8.5 but the increments are lower for the RCPs compared to the SRES. Projections for rainfall show a slight increase in annual rainfall in both SRES and RCPs. However more rainfall is projected for the second rainfall season of September to November compared to the usual known season of March to May (MAM). The projections also show a shift in rainfall with the usual dry season of December to February (DJF) now becoming wetter than the 1980-2010 average. This shift is consistent in all the scenarios and has also been observed in other studies done in the region. From the results farmers should be advised to take advantage of the projected increases in rainfall especially.

Assessment of Water Availability under Climate Change Scenarios in Thailand

This paper investigates the potential impact of climate change on future water availability in Thailand. For this study, entire country was divided into nine Hydrological Response Units (HRUs) and the hydrological modeling was performed by Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) for each HRU using the future decadal climate data obtained from the Regional Climate Model (RCM) named Providing Regional Climates for Impact Studies (PRECIS) which was further bias corrected by using ratio method for two emission scenarios A2 and B2. The simulation shows that the water availability in the future decades at the different HRUs varies for the dry and wet season. In case of dry season, the coastal HRUs show a decline in water availability in the near future then tending to increase to the similar amount as of current situation in the late part of century. However, in case of wet season all the HRUs shows an increasing trend of water availability in future. Nonetheless, considering the whole country for dry season the water availability is expected to be decreased in the early part of the century followed by an increasing trend by the end of the century relative to current water availability for both scenarios. Similarly a univocal increasing trend of water availability is expected for wet season indicating the possibility increased frequency and intensity of floods.

Assessing Hydrological Response to Changing Climate in the Krishna Basin of India

Impact of climate change on water balance components in the Krishna river basin are investigated using a semidistributed hydrological model namely Soil and Water Assessment Tool (SWAT). The model is calibrated and validated using the measured stream flow and meteorological data for the period (1970-1990) at a single guage outlet. The model has been used further for hydrologic parameter simulations. Daily climate simulations from regional climate model PRECIS (Providing Regional Climates for Impacts Studies) is used as input for running SWAT and monthly hydrologic parameters such as precipitation, surface flow, water yield, Evapotranspiration (ET) and Potential Evapotranspiration (PET) are generated under the assumption of no change in Land Use and Land Cover (LULC) pattern over time. Simulations at 23 sub-basins of the Krishna basin have been obtained for the control runs (1961-1990) and the for two time slices of future scenarios (2011-2040) and (2041-2070). Model projections indicate increase in the annual discharge, surface runoff and base flow in the basin in mid-century.

Analysis of projected changes in the occurrence of heat waves in Hungary

Abstract. Heat wave events are important temperature-related hazards due to their impacts on human health. In 2004, a Heat Health Warning System including three levels of heat wave warning was developed on the basis of a retrospective analysis of mortality and meteorological data in Hungary to anticipate heat waves that may result in a large excess of mortality. Projected changes in the frequency of different heat wave warning levels are analysed for the 21st century. For this purpose, outputs of regional climate model PRECIS (Providing REgional Climates for Impacts Studies) are used taking into account three different global emissions scenarios (A2, A1B, B2). The results clearly show an increase in occurrence and length of heat waves with respect to the underlying emissions scenarios and regional climate model used. Moreover, the potential season of heat wave occurrences is projected to be lengthened by two months in 2071–2100 compared to 1961–1990.

Analysis of projected drought hazards for Hungary

Abstract. Global climate change may result in severe regional consequences affecting agricultural production potential. One of the essential climatic impacts is associated with drought conditions. Therefore, projected future changes of several drought indices are analyzed for the future period 2071–2100 (compared to 1961–1990, as a reference period) using three different global emission scenarios (A2, A1B, and B2). The monthly time series of the indices have been calculated from the simulation outputs of the regional climate model PRECIS (Providing REgional Climates for Impacts Studies) for Central/Eastern Europe with 25 km horizontal resolution accomplished by the Department of Meteorology, Eötvös Loránd University. According to the results significant drying is projected in the region, especially in summer.

The Precis Caribbean Story: Lessons and Legacies

By the beginning of the current century, there was heightened recognition that the Caribbean is highly vulnerable to the effects of climate change. Yet, there was very little climate change science information for the region and at the scale of the small islands that make up most of the region. To fill the gap, a group of regional scientists representing three institutions and four territories (Barbados, Belize, Cuba, and Jamaica) initiated a project to provide dynamically downscaled climate change information for the Caribbean. The Providing Regional Climates for Impacts Studies (PRECIS)-Caribbean initiative was premised on a shared workload with goals to build regional capacity to provide climate change information for the region from within the region, to provide much needed climate information in the shortest possible time frame, and to create a platform for sharing the information as widely as possible. Ten years later offers the opportunity for retrospection and evaluation, particularly since a phase 2 initiative is being formulated. By both accident and design, the legacies of the PRECIS-Caribbean initiative include i) the positioning of the Caribbean to pose and answer for itself some of the emerging second-generation climate change questions; ii) the emergence of a regional template for capacity building in the sciences through cooperation; iii) an expanded regional capacity to undertake climate science; and iv) a significant body of climate change and climate science knowledge relevant to and at the scale of the Caribbean region.