Present-day and future precipitation in the Baltic Sea region as simulated in a suite of regional climate models

Here we investigate simulated changes in the precipitation climate over the Baltic Sea and surrounding land areas for the period 2071–2100 as compared to 1961–1990. We analyze precipitation in 10 regional climate models taking part in the European PRUDENCE project. Forced by the same global driving climate model, the mean of the regional climate model simulations captures the observed climatological precipitation over the Baltic Sea runoff land area to within 15% in each month, while single regional models have errors up to 25%. In the future climate, the precipitation is projected to increase in the Baltic Sea area, especially during winter. During summer increased precipitation in the north is contrasted with a decrease in the south of this region. Over the Baltic Sea itself the future change in the seasonal cycle of precipitation is markedly different in the regional climate model simulations. We show that the sea surface temperatures have a profound impact on the simulated hydrological cycle over the Baltic Sea. The driving global climate model used in the common experiment projects a very strong regional increase in summertime sea surface temperature, leading to a significant increase in precipitation. In addition to the common experiment some regional models have been forced by either a different set of Baltic Sea surface temperatures, lateral boundary conditions from another global climate model, a different emission scenario, or different initial conditions. We make use of the large number of experiments in the PRUDENCE project, providing an ensemble consisting of more than 25 realizations of climate change, to illustrate sources of uncertainties in climate change projections.     

Future changes in Central Europe heat waves expected to mostly follow summer mean warming

Daily output from the PRUDENCE ensemble of regional climate simulations for the end of the twentieth and twenty-first centuries over Europe is used to show that the increasing intensity of the most damaging summer heat waves over Central Europe is mostly due to higher base summer temperatures. In this context, base temperature is defined as the mean of the seasonal cycle component for those calendar days when regional heat waves occur and is close, albeit not identical, to the mean temperature for July–August. Although 36–47% of future Central Europe July and August days at the end of the twenty-first century are projected to be extreme according to the present day climatology, specific changes in deseasonalized heat wave anomalies are projected to be relatively small. Instead, changes in summer base temperatures appear much larger, clearly identifiable and of the same order of magnitude as changes in the whole magnitude of heat waves. Our results bear important consequences for the predictability of central European heat wave intensity under global warming conditions.     

Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models

Simulation and projection of the characteristics of heat waves over China were investigated using 12 CMIP5 global climate models and the CN05.1 observational gridded dataset. Four heat wave indices (heat wave frequency, longest heat wave duration, heat wave days, and high temperature days) were adopted in the analysis. Evaluations of the 12 CMIP5 models and their ensemble indicated that the multi-model ensemble could capture the spatiotemporal characteristics of heat wave variation over China. The inter-decadal variations of heat waves during 1961–2005 can be well simulated by multi-model ensemble. Based on model projections, the features of heat waves over China for eight different global warming targets (1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0 °C) were explored. The results showed that the frequency and intensity of heat waves would increase more dramatically as the global mean temperature rise attained higher warming targets. Under the RCP8.5 scenario, the four China-averaged heat wave indices would increase from about 1.0 times/year, 2.5, 5.4, and 13.8 days/year to about 3.2 times/year, 14.0, 32.0, and 31.9 days/year for 1.5 and 5.0 °C warming targets, respectively. Those regions that suffer severe heat waves in the base climate would experience the heat waves with greater frequency and severity following global temperature rise. It is also noteworthy that the areas in which a greater number of severe heat waves occur displayed considerable expansion. Moreover, the model uncertainties exhibit a gradual enhancement with projected time extending from 2006 to 2099.     

A projection of extreme climate events in the 21st century over east Asia using the community climate system model 3

A series of coupled atmosphere-ocean-land global climate model (GCM) simulations using the National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) has been performed for the period 1870–2099 at a T85 horizontal resolution following the GCM experimental design suggested in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). First, a hindcast was performed using the atmospheric concentrations of three greenhouse gases (CO₂, CH₄, N₂O) specified annually and globally on the basis of observations for the period 1870–1999. The hindcast results were compared with observations to evaluate the GCM’s reliability in future climate simulations. Second, climate projections for a 100-year period (2000–2099) were made using six scenarios of the atmospheric concentrations of the three greenhouse gases according to the A1FI, A1T, A1B, A2, B1, and B2 emission profiles of the Special Report on Emissions Scenarios. The present CCSM simulations are found to be consistent with IPCC’s AR4 results in the temporal and spatial distributions for both the present-day and future periods. The GCM results were used to examine the changes in extreme temperatures and precipitation in East Asia and Korea. The extreme temperatures were categorized into warm and cold events: the former includes tropical nights, warm days, and heat waves during summer (June–July–August) and the latter includes frost days, cold days, and cold surges during winter (December–January–February). Focusing on Korea, the results predict more frequent heat waves in response to future emissions: the projected percentage changes between the present day and the late 2090s range from 294% to 583% depending on the emission scenario. The projected global warming is predicted to decrease the frequency of cold extreme events; however, the projected changes in cold surge frequency are not statistically significant. Whereas the number of cold surges in the A1FI emission profile decreases from the present-day value by up to 24%, the decrease in the B1 scenario is less than 1%. The frequency and intensity of extreme precipitation events year-round were examined. Both the frequency and the intensity of these events are predicted to increase in the region around Korea. The present results will be helpful for establishing an adaptation strategy for possible climate change nationwide, especially extreme climate events, associated with global warming.     

新疆地区未来气候变化的区域气候模式集合预估

本文基于一套在5个全球气候模式结果驱动下,RegCM4区域气候模式对东亚25 km水平分辨率的集合预估,分析了中、高温室气体典型排放路径（RCP4.5和RCP8.5）下,21世纪不同时期新疆地区的未来气候变化。对模式当代气候模拟结果的检验表明,区域模式的模拟集合（ensR）总体上能够很好地再现当代新疆平均气温、降水和极端气温、降水分布特征。ensR预估21世纪未来新疆平均气温和降水将不断升高或增加,RCP8.5下的变化大于RCP4.5。在21世纪末期RCP8.5下,区域年平均气温和降水将分别增加4.9°C和28%（102 mm）,夏季（6～8月）的升温幅度略高于冬季（12～2月）,降水则以冬季增加为主。极端温度以及高温日数同样将不断升高,其中年日最低气温最小值的增幅总体高于年日最高气温最大值,未来新疆地区的极端冷事件将减少,高温、热浪事件将增加。由极端降水指标日最大降水量反应的强降水事件将普遍增加,连续无降水日数总体以减少为主。积雪变化存在一定区域差异,具体表现为除塔里木盆地外的普遍减少。对总径流量和表层土壤湿度的预估分析表明,二者在新疆地区均以增加为主,但水文干旱在北疆会加重。ensR各模拟间无论是在当代模拟还是未来预估中都表现出较好的一致性,但在变化的具体数量及个别情况下符号均存在一定差异。最后,综合考虑ensR对各要素的预估发现,总体而言新疆未来更趋向于“暖湿化”,但这不会改变其干旱、半干旱气候的本质,而且水文干旱频率在一些地区会增加,未来新疆的水资源状况仍不容乐观。     

An analysis of global model projections over Italy, with particular attention to the Italian Greater Alpine Region (GAR)

This study surveys the most recent projections of future climate change provided by 20 Atmospheric-Ocean General Circulation Models (AOGCMs) participating in the Coupled Model Intercomparison Project 3 (CMIP3) with focus on the Italian region and in particular on the Italian Greater Alpine Region (GAR). We analyze historical and future simulations of monthly-mean surface air temperature (T) and total precipitation (P). We first compare simulated T and P from the AOGCMs with observations over Italy for the period 1951–2000, using bias indices as a metric for estimating the performance of each model. Using these bias indices and different ensemble averaging methods, we construct ensemble mean projections of future climate change over these regions under three different IPCC emission scenarios (A2, A1B, and B1). We find that the emissions pathway chosen has a greater impact on future simulated climate than the criteria used to obtain the ensemble means. Across all averaging methods and emission scenarios, the models project annual mean increase in T of 2–4°C over the period 1990–2100, with more pronounced increases in summer and warming of similar magnitude at high and low elevations areas (according to a threshold of 400 m). The models project decreases in annual-mean P over this same time period both over the Italian and GAR regions. This decrease is more pronounced over Italy, since a small increase in precipitation over the GAR is projected in the winter season.     

SRES A2情景下中国区域21世纪末平均和极端气候变化的模拟

利用Hadley气候预测与研究中心的区域气候模式系统PRECIS单向嵌套该中心全球海-气耦合气候模式HadCM3高分辨率的大气部分HadAM3H,分析了SRES A2情景下2071-2100年相对于气候基准时段（1961-1990年）中国区域的气候变化,包括气温和降水的年际、季节和日时间尺度的变化以及极端气候事件的变化趋势。模拟结果表明：气温呈明显增加趋势,其中新疆和东北地区增温明显。而降水表现了更大的年际变化和季节变化,冬季南方降水减少,但沿黄河流域的降水明显增加,夏季与冬季相比呈现出相反的趋势。此外,连续高温日数呈现增加趋势,而连续霜冻日数呈现减少趋势。连续湿日数也表现出一定的增加趋势。     

Climate change and impacts in the Eastern Mediterranean and the Middle East

The Eastern Mediterranean and the Middle East (EMME) are likely to be greatly affected by climate change, associated with increases in the frequency and intensity of droughts and hot weather conditions. Since the region is diverse and extreme climate conditions already common, the impacts will be disproportional. We have analyzed long-term meteorological datasets along with regional climate model projections for the 21st century, based on the intermediate IPCC SRES scenario A1B. This suggests a continual, gradual and relatively strong warming of about 3.5–7°C between the 1961–1990 reference period and the period 2070–2099. Daytime maximum temperatures appear to increase most rapidly in the northern part of the region, i.e. the Balkan Peninsula and Turkey. Hot summer conditions that rarely occurred in the reference period may become the norm by the middle and the end of the 21st century. Projected precipitation changes are quite variable. Annual precipitation is expected to decrease in the southern Europe – Turkey region and the Levant, whereas in the Arabian Gulf area it may increase. In the former region rainfall is actually expected to increase in winter, while decreasing in spring and summer, with a substantial increase of the number of days without rainfall. Anticipated regional impacts of climate change include heat stress, associated with poor air quality in the urban environment, and increasing scarcity of fresh water in the Levant.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

ENSEMBLES-based assessment of regional climate effects in Luxembourg and their impact on vegetation

Projected future regional climate changes in Luxembourg are assessed based on a six-member ensemble of regional climate models (RCM) from the ENSEMBLES project. The key aspects are projected changes in air temperature and their impacts on vegetation. Up to now, there have been only few assessments of future climate conditions for Luxembourg. As agriculture is the dominant land use in Luxembourg, possible effects on crops and vegetation in general are highly relevant. Different RCMs at 25 km spatial and a daily temporal resolution, ranging from 1961 to 2100 based on the SRES A1B emission scenario are used. To reduce systematic biases in the RCM-derived time series, a bias correction is applied. Multi-model annual mean temperatures are projected to increase by 3.1 °C between the reference time span (1961 to 1990) and the far future (2069 to 2098). Clear change signals are found in seasonal bivariate frequency distributions of air temperature and precipitation. Derived impacts are an elongation of the thermal vegetation period by 6.2 days per decade due to an earlier onset in spring; growing degree day sums show a substantial increase leading to potentially better growth conditions; the earlier onset of the vegetation period causes an increase in late frost risk, especially in the near future (2021 to 2050) projections compared to the reference period.     

北京1960—2008年气候变暖及极端气温指数变化特征

应用均一化逐日气象观测资料,分析了北京地区1960—2008年气候变暖及主要极端气温指数的统计特征。结果表明：近49年来北京年平均气温增温速率约为0.39℃/10a,最高、最低气温变化具有明显的非对称性。霜冻日数和气温年较差呈现下降趋势,暖夜指数及热浪指数呈现上升趋势,除气温年较差外,其他极端气温指数的气候变率均在加大。北京年平均气温及极端气温指数主要存在21年、15～17年及准10年周期特征。年平均气温与极端气温指数之间存在较强相关性,气候变暖突变发生前后某些极端气温指数发生频率表现出明显差异。自1980年起,北京市区极端最高气温及其增温率明显高于近郊和远郊,高温日数市区多于近郊,近郊多于远郊;近、远郊极端最低气温温差高于城、近郊温差。     

基于统计降尺度模型的江淮流域极端气候的模拟与预估

利用江淮流域29个代表站点1961--2000年逐日最高温度、最低温度和逐日降水资料,以及NCEP逐日大尺度环流场资料,引入基于多元线性回归与随机天气发生器相结合的统计降尺度模型SDSM（statistical downscalingmodel）,通过对每个站点建模,确立SDSM参数,并将该模型应用于SRESA2排放情景下HadCM3和cGcM3模式,得到了江淮流域各代表台站21世纪的逐日最高、最低温度和降水序列以及热浪、霜冻、强降水等极端气候指数。结果表明,当前气候下,统计降尺度方法模拟的极端温度指数与观测值有很好的一致性,能有效纠正耦合模式的“冷偏差”,如SDSM对江淮平均的冬季最高、最低温度的模拟偏差较CGCM3模式分别减少3℃和4．5℃。对于极端降水则能显著纠正耦合模式模拟的降水强度偏低的问题,如CGCM3对江淮流域夏季降水强度的模拟偏差为-60．6％,但降尺度后SDSM—CGCM3的偏差仅为-6％,说明降尺度模型SDSM的确有“增加值”的作用。21世纪末期在未来SRESA2情景下,对于极端温度,无论Had．CM3还是CGCM3模式驱动统计模型,江淮流域所有代表台站,各个季节的最高、最低温度都显著增加,且以夏季最为显著,增幅在2—4℃;与之相应霜冻天数将大幅减少,热浪天数大幅增多,各站点冬季霜冻天数减少幅度为5—25d,夏季热浪天数增加幅度为4～14d;对于极端降水指数,在两个不同耦合模式HadCM3和CGCM3驱动下的变化尤其是变化幅度的一致性比温度差,但大部分站点各个季节极端强降水事件将增多,强度增强,SDSM—HadCM3和SDSM-CGCM3预估的夏季极端降水贡献率将分别增加26％和27％。     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

Simulation of extreme precipitation indices in the Yangtze River basin by using statistical downscaling method (SDSM)

In this study, the applicability of the statistical downscaling model (SDSM) in modeling five extreme precipitation indices including R10 (no. of days with precipitation ≥10?mm?day^?1), SDI (simple daily intensity), CDD (maximum number of consecutive dry days), R1d (maximum 1-day precipitation total) and R5d (maximum 5-day precipitation total) in the Yangtze River basin, China was investigated. The investigation mainly includes the calibration and validation of SDSM model on downscaling daily precipitation, the validation of modeling extreme precipitation indices using independent period of the NCEP reanalysis data, and the projection of future regional scenarios of extreme precipitation indices. The results showed that: (1) there existed good relationship between the observed and simulated extreme precipitation indices during validation period of 1991–2000, the amount and the change pattern of extreme precipitation indices could be reasonably simulated by SDSM. (2) Under both scenarios A2 and B2, during the projection period of 2010–2099, the changes of annual mean extreme precipitation indices in the Yangtze River basin would be not obvious in 2020s; while slightly increase in the 2050s; and significant increase in the 2080s as compared to the mean values of the base period. The summer might be the more distinct season with more projected increase of each extreme precipitation indices than in other seasons. And (3) there would be distinctive spatial distribution differences for the change of annual mean extreme precipitation indices in the river basin, but the most of Yangtze River basin would be dominated by the increasing trend.     

Projections of temperature and precipitation extremes in the North Western Mediterranean Basin by dynamical downscaling of climate scenarios at high resolution (1971–2050)

The North Western Mediterranean basin (NWMB) is characterised by a highly complex topography and an important variability of temperature and precipitation patterns. Downscaling techniques are required to capture these features, identify the most vulnerable areas to extreme changes and help decision makers to design strategies of mitigation and adaptation to climate change. A Regional Climate Model, WRF-ARW, is used to downscale the IPCC-AR4 ECHAM5/MPI-OM General Circulation Model results with high resolution (10 km), considering three different emissions scenarios (B1, A1B and A2) for 2001–2050. Model skills to reproduce observed extremes are assessed for a control period, 1971–2000, using the ERA40 reanalysis to drive the WRF-ARW simulations. A representative set of indices for temperature and precipitation extremes is projected. The modelling system correctly reproduces amplitude and frequency of extremes and provides a high degree of detail on variability over neighbouring areas. However, it tends to overestimate the persistence of wet events and consequently slightly underestimate the length of dry periods. Drier and hotter conditions are generally projected for the NWMB, with significant increases in the duration of droughts and the occurrence of heavy precipitation events. The projected increase in the number of tropical nights and extreme temperatures could have a negative effect on human health and comfort conditions. Simulations allow defining specifically vulnerable areas, such as the Ebro Valley or the Pyrenees, and foreseeing impacts on socio-economic activities in the region.     

Potential changes in extremes and links with the Southern Annular Mode as simulated by a multi-model ensemble

We assess the likely changes in climate extremes under enhanced greenhouse gases over the southern extratropics, with emphasis in southern South America and sub-Antarctic seas, through the analysis of extreme indices measured from models participating in the IPCC 4th Assessment Report. We discuss how the anthropogenic climate change under A1B scenario influences both the patterns of mean change of extreme indices and the likelihood of occurrence of severe extreme indices. The likelihood of occurrence of a year with a large number of days with “warm” minimum temperatures is estimated to increase by a factor of 4 by the end of this century over most of the southern extratropics. By that time, the risk of “severe” precipitation intensity is projected to rise in most areas with the exception of the subtropical anticyclones, which experience particularly strong drying. Over the Southern Ocean this likelihood has increased to over 60%. Corresponding estimates of the changing likelihood for very long dry spells show a banded structure with positive ratios to the north of about 50° S and negative ratios in the sub Antarctic seas. In southern South America this risk about doubled between present and future climates. Then, we explore if the Southern Annular Mode influences the occurrence of severe extreme indices during the period 2070–2099. Its positive phase inhibits the extremely warm minimum temperatures in the Southern Ocean, with the exception of the eastern Bellingshausen Sea, and favors severe frost days to the north of the Ross Sea. Temperature indices show very little change induced by the SAM to the north of 50° S. Severe dry spells are inhibited during the positive phase along the sub Antarctic seas, while the mid-latitudes, including most of Patagonia, show the opposite behaviour. The Southern Ocean reveals a non-uniform distribution with both increases and decreases in the occurrence of heavier precipitation during positive SAM.     

FGOALS-g2模式模拟和预估的全球季风区极端降水及其变化

利用LASG/IAP（中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室）全球耦合模式FGOALS-g2,评估了其对全球季风区极端气候指标的模拟能力,并讨论了RCP8.5排放情景下21世纪季风区极端气候指标的变化特征。总体而言,模式对季风区总降水和极端气候指标1997～2014年气候态和年际变率的空间分布均具有一定的模拟能力。偏差主要表现在模式低估了亚洲季风强降水中心,低估了中雨（10～20 mm d-1）和大雨（20～50 mm d-1）的频率而高估了暴雨（>50 mm d-1）频率。在RCP8.5排放情景下,由于可降水量的增加,模式预估的全球季风区极端降水、降水总量和降水强度将持续增加。到2076～2095年,极端降水和降水强度在北美季风区增加最显著（约22%和17%）,降水总量在澳大利亚增加最显著（约37%）。然而,FGOALS-g2对全球季风区平均的日降水量低于1 mm的连续最大天数（CDD）的预估变化不显著,这是由于预估的CDD在陆地季风区将增加,而在海洋季风区将减少。对各子季风区的分析显示,CDD在南美季风区变长最显著,达到30%,在澳洲季风区变短最显著,达到40%,这与两季风区日降水量低于1 mm的降水事件发生频率变化不同有关。     

Sea water surface energy balance in the Arctic fjord (Hornsund,SW Spitsbergen) in May–November 2014

Maize is grown by millions of smallholder farmers in South Asia (SA) under diverse environments. The crop is grown in different seasons in a year with varying exposure to weather extremes, including high temperatures at critical growth stages which are expected to increase with climate change. This study assesses the impact of current and future heat stress on maize and the benefit of heat-tolerant varieties in SA. Annual mean maximum temperatures may increase by 1.4–1.8 °C in 2030 and 2.1–2.6 °C in 2050, with large monthly, seasonal, and spatial variations across SA. The extent of heat stressed areas in SA could increase by up to 12 % in 2030 and 21 % in 2050 relative to the baseline. The impact of heat stress and the benefit from heat-tolerant varieties vary with the level of temperature increase and planting season. At a regional scale, climate change would reduce rainfed maize yield by an average of 3.3–6.4 % in 2030 and 5.2–12.2 % in 2050 and irrigated yield by 3–8 % in 2030 and 5–14 % in 2050 if current varieties were grown under the future climate. Under projected climate, heat-tolerant varieties could minimize yield loss (relative to current maize varieties) by up to 36 and 93 % in 2030 and 33 and 86 % in 2050 under rainfed and irrigated conditions, respectively. Heat-tolerant maize varieties, therefore, have the potential to shield maize farmers from severe yield loss due to heat stress and help them adapt to climate change impacts.     

Do weak AR4 models bias projections of future climate changes over Australia?

Regional climate projections using climate models commonly use an “all-model” ensemble based on data sets such as the Intergovernmental Panel on Climate Change’s (IPCC) 4th Assessment (AR4). Some regional assessments have omitted models based on specific criteria. We use a criteria based on the capacity of climate models to simulate the observed probability density function calculated using daily data, model-by-model and region-by-region for each of the AR4 models over Australia. We demonstrate that by omitting those climate models with relatively weak skill in simulating the observed probability density functions of maximum and minimum temperature and precipitation, different regional projections are obtained. Differences include: larger increases in the mean maximum and mean minimum temperatures, but smaller increases in the annual maximum and minimum temperatures. There is little impact on mean precipitation but the better models simulate a larger increase in the annual rainfall event combined with a larger decrease in the number of rain days. The weaker models bias the amount of mean warming towards lower increases, bias annual maximum temperatures to excessive warming and bias precipitation such that the amount of the annual rainfall event is under-estimated. We suggest that omitting weak models from regional scale estimates of future climate change helps clarify the nature and scale of the projected impacts of global warming.     

The impact of extreme heat on morbidity in Milwaukee, Wisconsin

Given predictions of increased intensity and frequency of heat waves, it is important to study the effect of high temperatures on human mortality and morbidity. Many studies focus on heat wave-related mortality; however, heat-related morbidity is often overlooked. The goals of this study are to examine the historical observed relationship between temperature and morbidity (illness), and explore the extent to which observed historical relationships could be used to generate future projections of morbidity under climate change. We collected meteorological, air pollution, and hospital admissions data in Milwaukee, Wisconsin, for the years 1989–2005, and employed a generalized additive model (GAM) to quantify the relationship between morbidity (as measured by hospital admissions) and high temperatures with adjustment for the effects of potential confounders. We also estimated temperature threshold values for different causes of hospital admissions and then quantified the associated percent increase of admissions per degree above the threshold. Finally, the future impact of higher temperatures on admissions for the years 2059–2075 was examined. Our results show that five causes of admission (endocrine, genitourinary, renal, accidental, and self-harm) and three age groups (15–64, 75–84, >85 years) were affected by high temperatures. Future projections indicate a larger number of days above the current temperature threshold leading to an increase in admissions. Our results indicate that climate change may increase heat-related hospital admissions in the US urban mid-West and that health systems should include heat wave planning.