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1.
Jan Kyselý Ladislav Gaál Romana Beranová Eva Plavcová 《Theoretical and Applied Climatology》2011,104(3-4):529-542
The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available. 相似文献
2.
CMIP5全球气候模式对上海极端气温和降水的情景预估 总被引：5，自引：1，他引：4
基于国际耦合模式比较计划第五阶段(Coupled Model Intercomparison Project Phase 5,以下简称CMIP5)28个模式的数值模拟结果和1981~2010年华东和上海气温和降水观测数据,评估了该28个气候模式对华东和上海气温和降水的模拟能力,并预估了RCP4.5(Representative Concentration Pathway 4.5)情景下上海2021~2030年极端气温和降水气候的变化趋势和不确定性。结果表明:与观测值相比,模式对华东和上海年平均气温的模拟大多均值偏高、方差偏低;对年总降水量的模拟大多均值偏高,但方差以华东偏高、上海偏低为主;26个模式的气温变化趋势和12个模式的降水变化趋势与观测值相同。选出8个模式的预估结果表明:与2001~2010年相比,2021~2030年上海冬天极端低温的出现日数(冷夜日数)呈减少趋势,不确定性最小;夏天暖夜日数呈增加的趋势,不确定性较小;其他极端气温事件的变化趋势则存在较大的不确定性,冷夜指标的不确定性最大。强降水发生日数和强降水的强度都呈现增加的趋势,且不确定性较小。 相似文献
3.
Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-to-noise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the inter-model consistency is better for temperature than for precipitation. 相似文献
4.
Summary We use the regional climate model RegCM nested within time-slice atmospheric general circulation model experiments to investigate
the possible changes of intense and extreme precipitation over the French Maritime Alps in response to global climate change.
This is a region with complex orography where heavy and/or extended precipitation episodes induced catastrophic floods during
the last decades. Output from a 30-year simulation of present-day climate (1961–1990) is first analysed and compared with
NCEP reanalysed 700 hPa geopotential heights (Z700) and daily precipitation observations from the Alpine Precipitation Climatology
(1966–1999). Two simulations under forcing from the A2 and B2 IPCC emission scenarios for the period 2071–2100 are used to
investigate projected changes in extreme precipitation for our region of interest. In general, the model overestimates the
annual cycle of precipitation. The climate change projections show some increase of precipitation, mostly outside the warm
period for the B2 scenario, and some increase in the variability of the annual precipitation totals for the A2 scenario. The
model reproduces the main observed patterns of the spatial leading EOFs in the Z700 field over the Atlantic-European domain.
The simulated large scale circulation (LSC) variability does not differ significantly from that of the reanalysis data provided
the EOFs are computed on the same domain. Two similar clusters of LSC corresponding to heavy precipitation days were identified
for both simulated and observed data and their patterns do not change significantly in the climate change scenarios. The analysis
of frequency histograms of extreme indices shows that the control simulation systematically underestimates the observed heavy
precipitation expressed as the 90th percentile of rainday amounts in all seasons except summer and better reproduces the greatest 5-day precipitation accumulation.
The main hydrological changes projected for the Maritime Alps consist of an increase of most intense wet spell precipitation
during winters for both scenarios and during autumn for the B2 scenario. Case studies of heavy precipitation events show that
the RegCM is capable to reproduce the physical mechanisms responsible for heavy precipitation over our region of interest. 相似文献
5.
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least. 相似文献
6.
Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4?C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4?C global warming will occur is 2084.Based on the median results of models that project a 4?C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5?C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation. 相似文献
7.
A. F. Carril C. G. Menéndez A. R. C. Remedio F. Robledo A. S?rensson B. Tencer J.-P. Boulanger M. de Castro D. Jacob H. Le Treut L. Z. X. Li O. Penalba S. Pfeifer M. Rusticucci P. Salio P. Samuelsson E. Sanchez P. Zaninelli 《Climate Dynamics》2012,39(12):2747-2768
The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991–2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons. 相似文献
8.
Using an ensemble of four high resolution (~25 km) regional climate models, this study analyses the future (2021–2050) spatial distribution of seasonal temperature and precipitation extremes in the Ganges river basin based on the SRES A1B emissions scenario. The model validation results (1989–2008) show that the models simulate seasonality and spatial distribution of extreme temperature events better than precipitation. The models are able to capture fine topographical detail in the spatial distribution of indices based on their ability to resolve processes at a higher regional resolution. Future simulations of extreme temperature indices generally agree with expected warming in the Ganges basin, with considerable seasonal and spatial variation. Significantly warmer summers in the central part of the basin along with basin-wide increase in night temperature are expected during the summer and monsoon months. An increase in heavy precipitation indices during monsoon, coupled with extended periods without precipitation during the winter months; indicates an increase in the incidence of extreme events. 相似文献
9.
Recent Progress in Studies of Climate Change in China 总被引：7，自引：0，他引：7
REN Guoyu DING Yihui ZHAO Zongci ZHENG Jingyun WU Tongwen TANG Guoli XU Ying 《大气科学进展》2012,29(5):958-977
An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03℃ (10 yr)-1 to 0.12℃ (10 yr)-1 . This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events. 相似文献
10.
Uncertainty in future climate change presents a key challenge for adaptation planning. In this study, uncertainty arising from internal climate variability is investigated using a new 40-member ensemble conducted with the National Center for Atmospheric Research Community Climate System Model Version 3 (CCSM3) under the SRES A1B greenhouse gas and ozone recovery forcing scenarios during 2000–2060. The contribution of intrinsic atmospheric variability to the total uncertainty is further examined using a 10,000-year control integration of the atmospheric model component of CCSM3 under fixed boundary conditions. The global climate response is characterized in terms of air temperature, precipitation, and sea level pressure during winter and summer. The dominant source of uncertainty in the simulated climate response at middle and high latitudes is internal atmospheric variability associated with the annular modes of circulation variability. Coupled ocean-atmosphere variability plays a dominant role in the tropics, with attendant effects at higher latitudes via atmospheric teleconnections. Uncertainties in the forced response are generally larger for sea level pressure than precipitation, and smallest for air temperature. Accordingly, forced changes in air temperature can be detected earlier and with fewer ensemble members than those in atmospheric circulation and precipitation. Implications of the results for detection and attribution of observed climate change and for multi-model climate assessments are discussed. Internal variability is estimated to account for at least half of the inter-model spread in projected climate trends during 2005–2060 in the CMIP3 multi-model ensemble. 相似文献
11.
利用1961—2022年江西74个气象站平均气温、最高气温、最低气温、降水量、相对湿度、平均风速和日照时数资料,对比分析了1991—2020年和1981—2010年新、旧气候态下气象要素差异,探讨气候平均值改变对气候影响评价和预测业务的影响。结果表明：新气候态下,江西省三类气温的年和季节平均值均上升,年降水量总体增加将弱化气温偏高、降水偏多的变化特征。年和季节平均风速距平山区减小而平原地区增大;年日照时数距平总体增加。极端高温年份减少,极端低温年份增多,其中平均气温和最低气温的极端高（低）温年发生概率的降幅（增幅）比最高气温更大。极端强降水年发生概率在赣西北、赣中大部、赣南西北部等地区夏季减少,赣南中南部地区冬季增大。全省历年极端日高温、低温和强降水事件发生站次总体减少。新、旧气候态的更替会对气候业务产生影响,如冬季气温偏冷的年份增加,偏暖的年份减少,需对冷、暖冬事件进行重新评估,夏季降水增多的变化特征减弱,将导致夏季降水预测量级和趋势发生改变。 相似文献
12.
A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Different types of uncertainties in climate simulations are examined by driving the RCM with different boundary data, applying different emissions scenarios, and running an ensemble of simulations with different initial conditions. Empirical orthogonal functions analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature (SAT) and precipitation variability. The RCM simulations tend to overestimate SAT, especially over the northern part of the domain in winter and over the western part in summer. Statistically significant increases in seasonal SAT under both higher and lower emissions scenarios over the whole RCM domain suggest the robustness of future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, though the changes are not statistically significant. The greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change. 相似文献
13.
Projected changes in South Asian summer monsoon by multi-model global warming experiments 总被引：1，自引：0，他引：1
S. S. Sabade Ashwini Kulkarni R. H. Kripalani 《Theoretical and Applied Climatology》2011,103(3-4):543-565
South Asian summer monsoon (June through September) rainfall simulation and its potential future changes are evaluated in a multi-model ensemble of global coupled climate models outputs under World Climate Research Program Coupled Model Intercomparison Project (WCRP CMIP3) dataset. The response of South Asian summer monsoon to a transient increase in future anthropogenic radiative forcing is investigated for two time slices, middle (2031–2050) and end of the twenty-first century (2081–2100), in the non-mitigated Special Report on Emission Scenarios B1, A1B and A2 .There is large inter-model variability in the simulation of spatial characteristics of seasonal monsoon precipitation. Ten out of the 25 models are able to simulate space–time characteristics of the South Asian monsoon precipitation reasonably well. The response of these selected ten models has been examined for projected changes in seasonal monsoon rainfall. The multi-model ensemble of these ten models projects a significant increase in monsoon precipitation with global warming. The substantial increase in precipitation is observed over western equatorial Indian Ocean and southern parts of India. However, the monsoon circulation weakens significantly under all the three climate change experiments. Possible mechanisms for the projected increase in precipitation and for precipitation–wind paradox have been discussed. The surface temperature over Asian landmass increases in pre-monsoon months due to global warming and heat low over northwest India intensifies. The dipole snow configuration over Eurasian continent strengthens in warmer atmosphere, which is conducive for the enhancement in precipitation over Indian landmass. No notable changes have been projected in the El Niño–Monsoon relationship, which is useful for predicting interannual variations of the monsoon. 相似文献
14.
Anthropogenic greenhouse gas emissions are expected to lead to more frequent and intense summer temperature extremes, not only due to the mean warming itself, but also due to changes in temperature variability. To test this hypothesis, we analyse daily output of ten PRUDENCE regional climate model scenarios over Europe for the 2071–2100 period. The models project more frequent temperature extremes particularly over the Mediterranean and the transitional climate zone (TCZ, between the Mediterranean to the south and the Baltic Sea to the north). The projected warming of the uppermost percentiles of daily summer temperatures is found to be largest over France (in the region of maximum variability increase) rather than the Mediterranean (where the mean warming is largest). The underlying changes in temperature variability may arise from changes in (1) interannual temperature variability, (2) intraseasonal variability, and (3) the seasonal cycle. We present a methodology to decompose the total daily variability into these three components. Over France and depending upon the model, the total daily summer temperature variability is projected to significantly increase by 20–40% as a result of increases in all three components: interannual variability (30–95%), seasonal variability (35–105%), and intraseasonal variability (10–30%). Variability changes in northern and southern Europe are substantially smaller. Over France and parts of the TCZ, the models simulate a progressive warming within the summer season (corresponding to an increase in seasonal variability), with the projected temperature change in August exceeding that in June by 2–3 K. Thus, the most distinct warming is superimposed upon the maximum of the current seasonal cycle, leading to a higher intensity of extremes and an extension of the summer period (enabling extreme temperatures and heat waves even in September). The processes driving the variability changes are different for the three components but generally relate to enhanced land–atmosphere coupling and/or increased variability of surface net radiation, accompanied by a strong reduction of cloudiness, atmospheric circulation changes and a progressive depletion of soil moisture within the summer season. The relative contribution of these processes differs substantially between models. 相似文献
15.
从安徽气候变化看2003年洪涝和高温的必然性 总被引：6，自引：0，他引：6
利用近 50年温度和降水资料研究了安徽夏季气候变化特征 ,解释了 2 0 0 3年夏季洪涝、高温等极端气候事件出现的必然性。研究结果表明 :(1 )近 50年来安徽夏季温度呈下降趋势 ,降水则呈增加趋势 ,两者变化是相协调的。目前夏季温度处于较低的气候基本态 ,降水处于高基本态。 (2 )无论是温度还是降水 ,其变率都在 2 0世纪80年代中后期开始上升 ,目前均处于高气候变率时期。降水的“两高”(高基本态和高气候变率 )结合决定了 2 0 0 3年夏季洪涝出现的必然性 ;温度的较低基本态决定了“凉夏”背景 ,但由于基本态的回升和变率的加大 ,仍会出现像 2 0 0 3年夏季的若干高温天气。 (3)最大熵谱估计表明 ,安徽夏季降水变化的主周期为 2 5年 ,反映了降水的准两年振荡特征 相似文献
16.
Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP 总被引：1，自引：1，他引：0
Ji-Woo Lee Song-You Hong Eun-Chul Chang Myoung-Seok Suh Hyun-Suk Kang 《Climate Dynamics》2014,42(3-4):733-747
This study assesses future climate change over East Asia using the Global/Regional Integrated Model system—Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2 (HG2); the representative concentration pathways (RCP) 4.5 and 8.5 scenarios for the intergovernmental panel on climate change fifth assessment report (AR5). Analyses for the current (1980–2005) climate are performed to evaluate the RMP’s ability to reproduce precipitation and temperature. Two different future (2006–2050) simulations are compared with the current climatology to investigate the climatic change over East Asia centered in Korea. The RMP satisfactorily reproduces the observed seasonal mean and variation of precipitation and temperature. The spatial distribution of the simulated large-scale features and precipitation by the RMP is generally less reflective of current climatic conditions than that is given by the HG2, but their inter-annual variations in East Asia are better captured by the RMP. Furthermore, the RMP shows higher reproducibility of climate extremes including excessive heat wave and precipitation events over South Korea. In the future, strong warming is distinctly coupled with intensified monsoonal precipitation over East Asia. In particular, extreme weather conditions are increased and intensified over South Korea as follows: (1) The frequency of heat wave events with temperature greater than 30 °C is projected to increase by 131 and 111 % in the RCP 8.5 and 4.5 downscaling, relative to the current climate. (2) The RCP 8.5 downscaling shows the frequency and variability of heavy rainfall to increase by 24 and 31.5 %, respectively, while the statistics given by the RCP 4.5 downscaling are similar to those of the current climate. 相似文献
17.
利用1951—2010年中国160站气温、降水资料,分析中国代表性台站冬季和夏季气温、降水的气候值及气候变率在前后30 a的差异,并对结果使用不同方法进行显著性检验。结果表明,季气温气候平均值的变化总体与全球增暖一致,以升温为主,但夏季在秦岭以南及长江中游地区出现显著局部变冷现象;季气温气候变率的变化相对较小,冬季总体不显著,夏季仅有少数台站显著。降水的气候变化总体不明显,季降水气候值变化的空间分布复杂,冬季南方地区、夏季东部地区总体增加,冬、夏季降水气候变率的变化均不显著。理论检验方法（t检验、F检验）与随机模拟方法（EMC法）的显著性检验结果,对气温的差别较小、对降水的差别较大,这与样本距平序列是否服从正态分布有关。EMC法可在确保样本统计特征不变的情况下,通过多次随机模拟,无需考虑其理论统计分布特征,使检验结果更为可靠。 相似文献
18.
We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional
model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the
capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables,
such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated
in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able
to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional
detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are
well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in
mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral
spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures.
Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly
over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however,
the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer.
Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better
reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly
regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation,
we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface
variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from
the A2 and B2 forcing scenarios which are being reported in a separate study. 相似文献
19.
Erik Kjellström Lars Bärring Daniela Jacob Richard Jones Geert Lenderink Christoph Schär 《Climatic change》2007,81(1):249-265
Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries. 相似文献
20.
This paper identifies two sources of uncertainties in model projections of temperature and precipitation: internal and inter-model variability. Eight models of WCRP-CMIP3 and WCRP-CMIP5 were compared to identify improvements in the reliability of projections from new generation models. While no significant differences are observed between both datasets, some improvements were found in the new generation models. For example, in summer CMIP5 inter-model variability of temperature was lower over northeastern Argentina, Paraguay and northern Brazil, in the last decades of the 21st century. Reliability of temperature projections from both sets of models is high, with signal to noise ratio greater than 1 over most of the study region. Although no major differences were observed in both precipitation datasets, CMIP5 inter-model variability was lower over northern and eastern Brazil in summer (especially at the end of the 21st century). Reliability of precipitation projections was low in both datasets. However, the signal to noise ratio in new generation models was close to 1, and even greater than 1 over eastern Argentina, Uruguay and southern Brazil in some seasons. 相似文献