Uncertainty in economic models of climate-change impacts

Uncertainty is poorly represented in existing studies of climate-change impacts. Methods that have been used to characterize uncertainty in the literature are described and the limitations of each discussed. It is found that two broad characterizations are useful. A large number of studies are based on several specific scenarios or attempt to randomize selected variables in their deterministic economic models. Other studies describe individual or collective reaction to risk. The first category falls short of an adequate representation of uncertainty by focusing primarily on a few values of variables included to capture variability. The second group of studies tend to focus more on behavior than impacts. What is needed are Monte Carlo type simulations where randomness is apparent in a series of independent draws from a distribution suitably adjusted for climate change. Some of the benefits of improvements in the characterization of uncertainty are discussed.I am thankful to my colleagues at the Economic Research Service (ERS), Linda Atkinson, George Frisvold, Charlie Hallahan, Betsey Kühn, Jan Lewandrowski, John Reilly, Keith Weibe and Olivia Wright for production assistance; to fellow members of the JPCC Working Group II chapter on Agriculture and participants in the IPCC seminar held at ERS for helpful discussions; to Jim Titus and an anonymous reviewer. The views expressed are those of the author and not necessarily those of the U.S. Department of Agriculture.     

Dissecting indices of aridity for assessing the impacts of global climate change

There is great interest in understanding how climate change will impact aridity through the interaction of precipitation changes with rising temperatures. The Aridity Index (AI), Climatic Moisture Deficit (CMD), and Climatic Moisture Surplus (CMS) are metrics commonly used to quantify and map patterns in aridity and water cycling. Here we show that these metrics have different patterns of change under future climate—based on an ensemble of nine general circulation climate models—and the different metrics are appropriate for different purposes. Based on these differences between the metrics, we propose that aridity can be dissected into three different types—hydrological (CMS), agricultural (CMD), and meteorological. In doing this, we propose a novel modified version of the Aridity Index, called AI+, that can be useful for assessing changes in meteorological aridity. The AI?+?is based on the same ratio between precipitation and evapotranspiration as the traditional AI, but unlike the traditional AI, the AI?+?only accounts for changes to precipitation during months when precipitation is less than reference/potential evapotranspiration (i.e. there is a deficit). Moreover, we show that the traditional AI provides a better estimate of change in moisture surplus driven by changes to precipitation during the wet season, rather than changes in deficit that occur during the drier seasons. These results show that it is important to select the most appropriate metric for assessing climate driven changes in aridity.     

Evaluating the effect of ocean-atmospheric indices on drought in Iran

Theoretical and Applied Climatology - This study investigated the relationship between ocean-atmospheric indices and drought in Iran. Using > 30-year precipitation data from 37...     

Comparison of two drought indices in studying regional meteorological drought events in China

The composite-drought index (CI), improved weighted average of precipitation index (IWAP), and the objective identification technique for regional extreme events (OITREE) were employed to detect China's regional meteorological drought events (CRMDEs) during 1961–2010. Compared with existing references, CI and IWAP both showed strong ability in identifying CRMDEs. Generally, the results of CI and IWAP were consistent, especially for extreme and severe CRMDEs. During 1961–2010, although the frequencies of extreme and severe CRMDEs based on CI and IWAP both showed weak decreasing trends, the two mean-integrated indices both showed increasing but not significant trends. However, the results of IWAP were more reasonable than CI’s in two aspects. Firstly, the monthly frequency of extreme and severe CRMDEs based on IWAP showed a clear seasonal variation, which coincided with the seasonal variation of the East Asian monsoon over central–eastern China, whereas the frequency based on CI presented a much weaker seasonal variation. Secondly, the two sets of results were sometimes inconsistent with respect to the start and end times of a CRMDE, and CRMDEs based on CI generally showed two unreasonable phenomena: (1) under non-drought conditions, a severe drought stage could suddenly occur in a large area; and (2) during the following period, drought could alleviate gradually in cases of non-precipitation. Comparative analysis suggested that the IWAP drought index possesses obvious advantages in detecting and monitoring regional drought events.     

气候变化对水资源影响预估常用指标

正全球气候变暖已成共识。自20世纪50年代至今,全球几乎所有地区都在持续变暖。IPCC第五次评估报告(AR5)显示,全球温度将进一步升高[1]。以1986—2005年为基准,预计全球地表温度在2016—2035年将升高0.3～0.7℃,2081—2100年升高0.3～4.8℃[2]。全球变暖导致一系列环境问题:海洋温度及地球表面温度上升,     

Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing,China

Theoretical and Applied Climatology - Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions....     

5种干旱指数在西藏高原地区的适用性评估

为了解不同干旱指标在西藏高原地区的适用性,本文通过利用Pa、MI、SPI、CI和FAO P-M干旱指数对西藏高原月尺度旱情等级进行评估,分析了各指标在描述旱情时的异同,并统计出各种指数的一致性及等级差异。结果表明:近20 a干旱过程中,MI、FAO P-M指数未监测出轻旱等级,而对于中旱、重旱等级,FAO P-M指数表现较好。从空间分布来看,FAO P-M指数在各个地区表现较好。从时间分布来看,FAO P-M指数在不同干旱过程期间,描述的干旱强度和中心位置与实际情况更接近;其次是Pa指数,其他指数综合表现相对较差。5种干旱指数在衡量西藏地区干旱程度上的一致性并不好;从两两指数之间反映干旱程度上出现一致性频次上看出,Pa-FAO P-M指数出现的次数最多,其次是Pa-SPI-CI指数的出现次数,MI-CI指数的出现次数最少。通过差异性分析得出,全区干旱指数不一致率平均大于20%,阿里地区和林芝地区的干旱指数整体不一致率最高,拉萨地区的干旱指数整体不一致率最低。     

伏旱灾害的长期预评估方法

通过天气变化与日月食相关关系和日月食现象信息来源超前可靠的特点，利用近百年天文气象观测、预测资料，建立了伏旱天气预报模式；并对未来10年的伏旱天气及影响进行了预评估。     

伏旱灾害影响中期预评估方法

介绍盛夏降水的EOF预测技术、盛夏旱涝预测方法和伏旱强度与太阳活动关系及预测三种伏旱中期预测方法，这对达州伏旱灾害影响的预评估将会起到补充订正的作用。     

伏旱灾害的长期预评估方法

通过天气变化与日月食相关关系和日月食现象信息来源超前可靠的特点,利用近百年天文气象观测、预测资料,建立了伏旱天气预报模式;并对未来10年的伏旱天气及影响进行了预评估.     

伏旱灾害影响中期预评估方法

介绍盛夏降水的EOF预测技术、盛夏旱涝预测方法和伏旱强度与太阳活动关系及预测三种伏旱中期预测方法,这对达州伏旱灾害影响的预评估将会起到补充订正的作用.     

四种气象干旱指数在新疆区域适用性研究

利用降水量距平百分率(PA)、标准化降水蒸散指数(SPEI)、自适应帕默尔干旱指数(scPDSI)和气象干旱综合指数(MCI)四种气象干旱指数,进行变化趋势、相关性和干旱频率的分析,并与历史灾情进行对比,来研究1961—2020年新疆不同区域干旱指数适用性。结果表明,scPDSI和MCI指数显著上升,干旱程度呈减轻趋势,其干旱监测结果一致率高。PA指数变化趋势均平稳,但与其他三种干旱指数在全频域和高频域干旱监测结果一致率较好。SPEI指数在东疆和南疆东部区域显著下降,干旱程度呈加重趋势,与其它三种指数低频域干旱监测结果存在显著负相关。干旱频率分析结果显示,PA指数的特旱等级判定存在异常情况,特别是南疆和东疆。与历史灾情对比结果显示,MCI指数是对干旱灾害反映最好的。总体上,MCI指数在新疆地区的适用性要优于其它三种干旱指数。近60年来,全疆不同区域的MCI指数均呈上升趋势,各区域的干旱程度均有所减轻。空间上,新疆西北部发生干旱显著比南疆和东疆区域概率大。全疆不同区域在1962—1967年、1974—1977年、1989—1991年、1997年、2020年均发生干旱,并且主要集中在春夏两季较多,其中北疆西部和伊犁河谷区域易出现干旱灾情。     

Spatiotemporal variability of four precipitation-based drought indices in Xinjiang,China

Global increases in duration and prevalence of droughts require detailed drought characterization at various spatial and temporal scales. In this study, drought severity in Xinjiang, China was investigated between 1961 and 2012. Using meteorological data from 55 weather stations, the UNEP (1993) index (I _A), Erinç’s aridity index (I _m), and Sahin’s aridity index (I _sh) were calculated at the monthly and annual timescales and compared to the Penman-Monteith based standard precipitation evapotranspiration index (SPEI_PM). Drought spatiotemporal variability was analyzed for north (NX), south (SX), and entire Xinjiang (EX). I _m could not be calculated at 51 stations in winter as T _max was below 0. At the monthly timescale, I _A, I _m, and I _sh correlated poorly to SPEI_PM because of seasonality and temporal variability, but annual I _A, I _m, and I _sh correlated well with SPEI_PM. Annual I _A, I _m, and I _sh showed strong spatial variability. The 15 extreme droughts denoted by monthly SPEI_PM occurred in NX but out of phase in SX. Annual precipitation, maximum temperature, and relative and specific humidity increased, while air pressure and potential evapotranspiration decreased over 1961–2012. The resulting increases in the four drought indices indicated that drought severity in Xinjiang decreased, because the local climate became warmer and wetter.

     

Spline models of contemporary, 2030, 2060 and 2090 climates for Mexico and their use in understanding climate-change impacts on the vegetation

Spatial climate models were developed for México and its periphery (southern USA, Cuba, Belize and Guatemala) for monthly normals (1961–1990) of average, maximum and minimum temperature and precipitation using thin plate smoothing splines of ANUSPLIN software on ca. 3,800 observations. The fit of the model was generally good: the signal was considerably less than one-half of the number of observations, and reasonable standard errors for the surfaces would be less than 1°C for temperature and 10–15% for precipitation. Monthly normals were updated for three time periods according to three General Circulation Models and three emission scenarios. On average, mean annual temperature would increase 1.5°C by year 2030, 2.3°C by year 2060 and 3.7°C by year 2090; annual precipitation would decrease ?6.7% by year 2030, ?9.0% by year 2060 and ?18.2% by year 2090. By converting monthly means into a series of variables relevant to biology (e. g., degree-days > 5°C, aridity index), the models are directly suited for inferring plant–climate relationships and, therefore, in assessing impact of and developing programs for accommodating global warming. Programs are outlined for (a) assisting migration of four commercially important species of pine distributed in altitudinal sequence in Michoacán State (b) developing conservation programs in the floristically diverse Tehuacán Valley, and (c) perpetuating Pinus chiapensis, a threatened endemic. Climate surfaces, point or gridded climatic estimates and maps are available at http://forest.moscowfsl.wsu.edu/climate/.     

Future impacts of global warming and reforestation on drought patterns over West Africa

This study investigates how a large-scale reforestation in Savanna (8–12°N, 20°W–20°E) could affect drought patterns over West Africa in the future (2031–2060) under the RCP4.5 scenario. Simulations from two regional climate models (RegCM4 and WRF) were analyzed for the study. The study first evaluated the performance of both RCMs in simulating the present-day climate and then applied the models to investigate the future impacts of global warming and reforestation on the drought patterns. The simulated and observed droughts were characterized with the Standardized Precipitation and Evapotranspiration Index (SPEI), and the drought patterns were classified using a Self-organizing Map (SOM) technique. The models capture essential features in the seasonal rainfall and temperature fields (including the Saharan Heat Low), but struggle to reproduce the onset and retreat of the West African Monsoon as observed. Both RCMs project a warmer climate (about 1–2 °C) over West Africa in the future. They do not reach a consensus on future change in rainfall, but they agree on a future increase in frequency of severe droughts (by about 2 to 9 events per decade) over the region. They show that reforestation over the Savanna could reduce the future warming by 0.1 to 0.8 °C and increase the precipitation by 0.8 to 1.2 mm per day. However, the impact of reforestation on the frequency of severe droughts is twofold. While reforestation decreases the droughts frequency (by about 1–2 events per decade) over the Savanna and Guinea coast, it increases droughts frequency (by 1 event per decade) over the Sahel, especially in July to September. The results of this study have application in using reforestation to mitigate impacts of climate change in West Africa.     

The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy

Strategies to mitigate anthropogenic climate change recognize that carbon sequestration in the terrestrial biosphere can reduce the build-up of carbon dioxide in the Earth’s atmosphere. However, climate mitigation policies do not generally incorporate the effects of these changes in the land surface on the surface albedo, the fluxes of sensible and latent heat to the atmosphere, and the distribution of energy within the climate system. Changes in these components of the surface energy budget can affect the local, regional, and global climate. Given the goal of mitigating climate change, it is important to consider all of the effects of changes in terrestrial vegetation and to work toward a better understanding of the full climate system. Acknowledging the importance of land surface change as a component of climate change makes it more challenging to create a system of credits and debits wherein emission or sequestration of carbon in the biosphere is equated with emission of carbon from fossil fuels. Recognition of the complexity of human-caused changes in climate does not, however, weaken the importance of actions that would seek to minimize our disturbance of the Earth’s environmental system and that would reduce societal and ecological vulnerability to environmental change and variability.     

大气水汽的输送和收支及其对副热带干旱的影响

本文利用1979年9月至1984年8月欧洲中期天气预报中心(ECMWF)每日四次的十三层分析资料,研究不同尺度的大气运动对水汽输送和收支的贡献。指出Hadley环流对水汽从副热带向赤道输送和从冬半球向夏半球的输送中起着决定性作用。热带行星波则把水汽从热带输向副热带。在中高纬的水汽向极输送中,天气尺度的波动比行星尺度的波动更重要。在南半球,天气尺度的波动支配着水汽的输送过程。分析和数值试验表明,副热带干旱受到nadley环流和热带行星波异常的强烈影响。