The Potential Impact of Global Warming on Hail Losses to Winter Cereal Crops in New South Wales

This study was undertaken to determine the impact of potential global warming on the magnitude of hail losses to winter cereal crops within two areas situated on the western slopes of New South Wales, Australia. A model relating historical crop hail losses to climatic variables was developed for each area. These models included seasonal measures of vertical instability, low-level moisture and the height of the freezing level. In both areas, windshear was not found to be an important factor influencing seasonal crop hail losses. The two crop hail loss models were then used in conjunction with upper-air climatic data from three single mixed-layer global climate models (GCMs). Each GCM was run for 1 × CO₂ conditions and for 2 × CO₂ conditions. The enhanced greenhouse effect on climatic variables was taken to be the difference between their values for these two runs. Changes to climatic variables were then translated directly into changes in the percentage value of the winter cereal crop lost due to hail. In both areas, the three GCMs agreed concerning the direction of change in each of the variables used in the crop hail loss model. GCM simulations of the greenhouse effect resulted in a decline in winter cereal crop hail losses, with the exception of one GCM simulation at one location where losses increased slightly. None of the changes due to the enhanced greenhouse effect, however, were significant owing to a large observed seasonal variability of crop hail losses. Also, the simulated seasonal variability of crop hail losses did not change significantly due to the enhanced greenhouse effect. These results depended on two important assumptions. Firstly, it was assumed that the dominant relationships between climatic variables and crop hail losses in the past would remain the same in a future climate. Secondly, it was assumed that the single mixed-layer GCMs used in the study were correctly predicting climate change under enhanced greenhouse conditions.     

Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province,China

Assessing the regional impact of climate change on agriculture, hydrology, and forests is vital for sustainable management. Trustworthy projections of climate change are needed to support these assessments. In this paper, 18 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to simulate regional climate change in Zhejiang Province, Southeast China. Simple graphical approaches and three indices are used to evaluate the performance of six key climatic variables during simulations from 1971 to 2000. These variables include maximum and minimum air temperature, precipitation, wind speed, solar radiation, and relative humidity. These variables are of great importance to researchers and decision makers in climate change impact studies and developing adaptation strategies. This study found that most GCMs failed to reproduce the observed spatial patterns, due to insufficient resolution. However, the seasonal variations of the six variables are simulated well by most GCMs. Maximum and minimum air temperatures are simulated well on monthly, seasonal, and yearly scales. Solar radiation is reasonably simulated on monthly, seasonal, and yearly scales. Compared to air temperature and solar radiation, it was found that precipitation, wind speed, and relative humidity can only be simulated well at seasonal and yearly scales. Wind speed was the variable with the poorest simulation results across all GCMs.     

Uncertainties linked to land-surface processes in climate change simulations

 The impact of climate change on the hydrology of continental surfaces is critical for human activities but the response of the surface to this perturbation may also affect the sensitivity of the climate. This complex feedback is simulated in general circulation models (GCMs) used for climate change predictions by their land-surface schemes. The present study attempts to quantify the uncertainty associated with these schemes and what impact it has on our confidence in the simulated climate anomalies. Four GCMs, each coupled to two different land-surface schemes, are used to explore the spectrum of uncertainties. It is shown that, in this sample, surface processes have a significant contribution to our ability to predict surface temperature changes and perturbations of the hydrological cycle in an environment with doubled greenhouse gas concentration. The results reveal that the uncertainty introduced by land-surface processes in the simulated climate is different from its impact on the sensitivity of GCMs to climate change, indeed an alteration of the surface parametrization with little impact on model climate can affect sensitivity significantly. This result leads us to believe that the validation of land-surface schemes should not be limited to the current climate but should also cover their sensitivity to variations in climatic forcing. Received: 24 June 1999 / Accepted: 20 April 2000     

Downscaling GCMs Using the Smooth Support Vector Machine Method to Predict Daily Precipitation in the Hanjiang Basin

General circulation models (GCMs) are often used in assessing the impact of climate change at global and continental scales. However, the climatic factors simulated by GCMs are inconsistent at comparatively smaller scales, such as individual river basins. In this study, a statistical downscaling approach based on the Smooth Support Vector Machine (SSVM) method was constructed to predict daily precipitation of the changed climate in the Hanjiang Basin. NCEP/NCAR reanalysis data were used to establish the sta...     

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.     

Use of a reservoir water quality model to simulate global climate change effects on fish habitat

A case study was conducted on the potential impacts of climate change on fish habitat in a southeastern reservoir. A reservoir water quality model and one year of baseline meteorologic, hydrologic, and inflow water quality input were used to simulate current reservoir water quality. Total adult striped bass habitat, defined by specific quantitative temperature and dissolved oxygen criteria, was simulated. Daily reservoir volumes with optimal, suboptimal, and unsuitable temperature and DO were predicted for the year. Output from recent runs of atmospheric general circulation models (GCMs), in which atmospheric carbon dioxide concentrations have been doubled, was then used to adjust the baseline inputs to the water quality model. New sets of input data were created for two grid cells for each of three GCMs. All six climate scenarios are predicted to cause overall declines in the available summer striped bass habitat, mostly due to lake water temperatures exceeding striped bass tolerance levels. These predictions are believed to result from the consensus among GCM scenarios that air temperatures and humidity will rise, and the sensitivity of the reservoir model to these parameters. The reservoir model was found to be a promising tool for examining potential climate-change impacts. Some of the assumptions required to apply GCM output to the reservoir model, however, illustrate the problems in using large-scale gridcell output to assess small-scale impacts.     

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.     

Water Resources Implications of Global Warming: A U.S. Regional Perspective

The implications of global warming for the performance of six U.S. water resource systems are evaluated. The six case study sites represent a range of geographic and hydrologic, as well as institutional and social settings. Large, multi-reservoir systems (Columbia River, Missouri River, Apalachicola-Chatahoochee-Flint (ACF) Rivers), small, one or two reservoir systems (Tacoma and Boston) and medium size systems (Savannah River) are represented. The river basins range from mountainous to low relief and semi-humid to semi-arid, and the system operational purposes range from predominantly municipal to broadly multi-purpose. The studies inferred, using a chain of climate downscaling, hydrologic and water resources systems models, the sensitivity of six water resources systems to changes in precipitation, temperature and solar radiation. The climate change scenarios used in this study are based on results from transient climate change experiments performed with coupled ocean-atmosphere General Circulation Models (GCMs) for the 1995 Intergovernmental Panel on Climate Change (IPCC) assessment. An earlier doubled-CO₂ scenario from one of the GCMs was also used in the evaluation. The GCM scenarios were transferred to the local level using a simple downscaling approach that scales local weather variables by fixed monthly ratios (for precipitation) and fixed monthly shifts (for temperature). For those river basins where snow plays an important role in the current climate hydrology (Tacoma, Columbia, Missouri and, to a lesser extent, Boston) changes in temperature result in important changes in seasonal streamflow hydrographs. In these systems, spring snowmelt peaks are reduced and winter flows increase, on average. Changes in precipitation are generally reflected in the annual total runoff volumes more than in the seasonal shape of the hydrographs. In the Savannah and ACF systems, where snow plays a minor hydrological role, changes in hydrological response are linked more directly to temperature and precipitation changes. Effects on system performance varied from system to system, from GCM to GCM, and for each system operating objective (such as hydropower production, municipal and industrial supply, flood control, recreation, navigation and instream flow protection). Effects were generally smaller for the transient scenarios than for the doubled CO₂ scenario. In terms of streamflow, one of the transient scenarios tended to have increases at most sites, while another tended to have decreases at most sites. The third showed no general consistency over the six sites. Generally, the water resource system performance effects were determined by the hydrologic changes and the amount of buffering provided by the system's storage capacity. The effects of demand growth and other plausible future operational considerations were evaluated as well. For most sites, the effects of these non-climatic effects on future system performance would about equal or exceed the effects of climate change over system planning horizons.     

Evaluation of Agricultural Climatic Resource Utilization During Spring Maize Cultivation in Northeast China Under Climate Change

Agricultural climatic resources （such as light,temperature,and water） are environmental factors that affect crop productivity.Predicting the effects of climate change on agricultural climatic resource utilization can provide a theoretical basis for adapting agricultural practices and distributions of agricultural production.This study investigates these effects under the IPCC （Intergovernmental Panel on Climate Change） scenario A1B using daily data from the high-resolution RegCM3 （0.25° ×0.25°） during 1951-2100.Model outputs are adjusted using corrections derived from daily observational data taken at 101 meteorological stations in Northeast China between 1971 and 2000.Agricultural climatic suitability theory is used to assess demand for agricultural climatic resources in Northeast China during the cultivation of spring maize.Three indices,i.e.,an average resource suitability index （Isr）,an average efficacy suitability index （Ise）,and an average resource utilization index （K）,are defined to quantitatively evaluate the effects of climate change on climatic resource utilization between 1951 and 2100.These indices change significantly in both temporal and spatial dimensions in Northeast China under global warming.All three indices are projected to decrease in Liaoning Province from 1951 to 2100,with particularly sharp declines in Isr,Ise,and K after 2030,2021,and 2011,respectively.In Jilin and Heilongjiang provinces,Isr is projected to increase slightly after 2011,while Ise increases slightly and K decreases slightly after 2030.The spatial maxima of all three indices are projected to shift northeastward.Overall,warming of the climate in Northeast China is expected to negatively impact spring maize production,especially in Liaoning Province.Spring maize cultivation will likely need to shift northward and expand eastward to make efficient use of future agricultural climatic resources.     

华北地区气候变化对水资源的影响及2003年水资源预评估

利用华北地区近50年的气候、水资源等相关资料，分析了华北地区水资源及其开发利用状况、气候变化特征及对水资源的影响以及二者之间的相互关系。在此基础上，进一步建立了水资源评估模式，并结合短期气候预测结果，实现了华北地区2003年水资源定量预评估。     

Preparing for Climatic Change: The Water, Salmon, and Forests of the Pacific Northwest

The impacts of year-to-year and decade-to-decade climatic variations on some of the Pacific Northwest's key natural resources can be quantified to estimate sensitivity to regional climatic changes expected as part of anthropogenic global climatic change. Warmer, drier years, often associated with El Niño events and/or the warm phase of the Pacific Decadal Oscillation, tend to be associated with below-average snowpack, streamflow, and flood risk, below-average salmon survival, below-average forest growth, and above-average risk of forest fire. During the 20th century, the region experienced a warming of 0.8 °C. Using output from eight climate models, we project a further warming of 0.5–2.5 °C (central estimate 1.5 °C) by the 2020s, 1.5–3.2°C (2.3 °C) by the 2040s, and an increase in precipitation except in summer. The foremost impact of a warming climate will be the reduction of regional snowpack, which presently supplies water for ecosystems and human uses during the dry summers. Our understanding of past climate also illustrates the responses of human management systems to climatic stresses, and suggests that a warming of the rate projected would pose significant challenges to the management of natural resources. Resource managers and planners currently have few plans for adapting to or mitigating the ecological and economic effects of climatic change.     

气候变化情景生成技术研究综述

简单回顾了气候变化对农业生产影响研究的进展,分析了气候变化情景生成技术研究的必要性,即影响模式与ＧＣＭｓ的嵌套困难及对气候变率和产量变率的认识。指出该技术是目前这一领域研究的关键所在。     

在气候影响研究中引入随机天气发生器的方法和不确定性

通过采用不同的随机天气发生器生成一定气候背景下各种气候变率情景，许多学者在最近的研究中已经认识到气候变率对农作物生长发育影响的重要性。传统的气候影响评估方法直接以大气环流模式的模拟试验结果作为未来气候情景，这样不可能理解如上的重要性。本文着重评述将随机天气发生器应用于气候变化影响研究的一般方法框架，以及作者的具体个例研究方法。文中最后分析了目前该领域研究中还存在的一些不确定性。 在当前的气候变化影响研究中，有不同的方法用来研制一种称为WGEN的典型随机天气发生器的参数化方案及其随机试验方法。不同的研究者也有不同的参数调控方法。通常的思路是通过气候控制试验和2×CO2试验之间的气候变量平均值和方差的变化来扰动随机天气发生器的参数，以生成未来逐日气候变化情景。本文作者根据短期气候预测模式的输出产品建立了一套WGEN的参数化方案及其随机试验方法，并且在时间和空间两个尺度上检验和评估了此参数化方案下WGEN的模拟能力。另外，作者由未来降水的变化，调试随机天气发生器参数，生成了气候变率变化情景。这些参数调节可以产生各种不同类型和定性大小的气候变率变化，用于气候影响评估的敏感性分析。通过如上方法，作为一个个例，文中评估了未来气候变率变化     

Use of general circulation model output in the creation of climate change scenarios for impact analysis

Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO₂ and 1 × CO₂ GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO₂ concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.     

Effects of Climate Change on Evapotranspiration from Paddy Fields in Southern Taiwan

The major objective of this study was to investigate the effects of climate change on evapotranspiration from paddy fields. A sensitivity analysis of meteorological variables at the Kao-Hsiung station, one of meteorological stations in southern Taiwan, was carried out using the modified Penman formula. Forty-eight-year records of temperature, relative humidity, sunshine duration, wind speed, and precipitation depth comprised the database. Trend and persistence analyses of the data were performed using the Mann–Kendall test, the Cumulative Deviation test, Linear Regression, andthe Autocorrelation Coefficient. The results indicated that only temperature and relative humidity have significant long-term trends and persistence. Two climatic scenarios, viz. (1) linear extrapolation of climatic trends and (2) the predictions of General Circulation Models (GCMs), were assumed to investigate the effects of climate change on evapotranspiration. The study revealed that evapotranspiration from paddy fields increased under both climatic scenarios studied.     

Potential Effects of Global Warming on Waterfowl Populations Breeding in the Northern Great Plains

The Prairie Pothole Region (PPR) of the Northern Great Plains is the most important breeding area for waterfowl in North America. Historically, the size of breeding duck populations in the PPR has been highly correlated with spring wetland conditions. We show that one indicator of climate conditions, the Palmer Drought Severity Index (PDSI), is strongly correlated with annual counts (from 1955 to 1996) of both May ponds (R2 = 0.72, p < 0.0001) and breeding duck populations (R2 = 0.69, p < 0.0001) in the Northcentral U.S., suggesting the utility of PDSI as an index for climatic factors important to wetlands and ducks. We then use this relationship to project future pond and duck numbers based on PDSI values generated from sensitivity analyses and two general circulation model (GCM) scenarios. We investigate the sensitivity of PDSI to fixed changes in temperature of 0°C, +1.5°C, +2.5°C, and +4.0°C in combination with fixed changes in precipitation of -10%, +0%, +7%, and +15%, changes spanning the range of typically-projected values for this region from human-induced climatic change. Most (11 of 12) increased temperature scenarios tested result in increased drought (due to greater evapotranspiration under warmer temperatures) and declining numbers of both wetlands and ducks. Assuming a doubling of CO2 by 2060, both the equilibrium and transient GCM scenarios we use suggest a major increase in drought conditions. Under these scenarios, Northcentral U.S. breeding duck populations would fluctuate around means of 2.1 or 2.7 million ducks based on the two GCMs, respectively, instead of the present long-term mean of 5.0 million. May pond numbers would fluctuate around means of 0.6 or 0.8 million ponds instead of the present mean of 1.3 million. The results suggest that the ecologically and economically important PPR could be significantly damaged by climate changes typically projected. We make several recommendations for policy and research to help mitigate potential effects.     

气候变化对澜湄流域上下游水资源合作潜力的影响

澜沧江-湄公河（澜湄）流域南北跨越了25个纬度,流域上下游气候差异明显。同时遭遇干旱或湿润通常不利于上下游水资源合作,而水文气象条件正常或上下游间的干湿条件不一样时有利于缓解流域内的竞争性用水状况。为探究气候变化对澜湄流域上下游水资源合作潜力的影响,基于普林斯顿降水数据集与全球气候模型预估数据,利用标准化降水指数（SPI）和Copula函数计算了历史时期（1985—2016年）与未来时期（2021—2090年）澜湄流域上下游同时面临干旱、湿润以及干湿存在差异的发生概率。基于典型浓度路径RCP4.5和RCP8.5情景的预估结果显示与历史时期相比,未来时期澜湄流域在RCP4.5与RCP8.5情景下具有相似的变化趋势,即：遭遇同期湿润的概率在逐渐增大（最大达到199.5%),遭遇同期干旱的概率则在逐渐减少(最小达到-35.9%),而遭遇干湿差异时期的概率在所有时段均大幅减少（-53.1%~-42.5%)。未来澜湄流域上下游同期湿润概率的增加和遭遇干湿差异概率的减少预计将加大上下游面临水资源竞争的可能性,从而对澜湄流域各国家之间的水资源合作产生不利影响。这一研究可以为澜湄流域水资源合作策略的制定提供科学参考和依据。     

Climate impacts on coal, from resource assessments through to environmental remediation

This paper discusses the coal cycle from exploration through mining to end uses and environmental remediation, primarily from the perspective of elements in the cycle that are most vulnerable to the impacts of climatic change. The differences between resource estimates are noted. Coal transport by rail, barge, and ocean-going vessels are compared. The major end-use technologies are mentioned in the context of the coal value chain. Water availability is identified as a major uncertainty that could be further complicated by climate change. The major flows that are produced by down-stream cleanup of environmental emissions are discussed in terms of the movement of bulk solids. Typical impacts of temperature change, changes in precipitation, sea level rise, and decrease in sea ice in this cycle are summarized. Finally, while noting the negative impacts of climate changes in the Arctic, the opportunities that may arise from these are also discussed.     

Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.     

Sensitivity of evapotranspiration of cotton and sorghum in west Texas to changes in climate and CO2

Summary In regions such as west Texas where water is scarce, changes in the water balance may have a significant impact on agricultural production and management of water resources. We used the mechanistic soil-plant-atmosphere simulation model ENWATBAL to evaluate changes in soil water evaporation (E) and transpiration (T) in cotton and grain sorghum that may occur due to climate change and elevated CO₂ in west Texas. Climatic and plant factors were varied individually, and in combination, to determine their impact onE andT. Of the climatic factors,E was most sensitive to changes in vapor pressure, andT to changes in irradiance. Simulations suggest that if warming is accompanied by higher humidity, the impact of climate change may be minimal. However, if the climate becomes warmer and less humid,ET may increase substantially. Simulations also suggest that enhanced growth due to elevated CO₂ may have a greater impact onET than climatic change.With 9 Figures