CMIP5 simulated change in the intensity of the Hadley and Walker circulations from the perspective of velocity potential

Based on the simulations of 31 global models in CMIP5, the performance of the models in simulating the Hadley and Walker circulations is evaluated. In addition, their change in intensity by the end of the 21 st century(2080–2099) under the RCP4.5 and RCP8.5 scenarios, relative to 1986–2005, is analyzed from the perspective of 200 h Pa velocity potential.Validation shows good performance of the individual CMIP5 models and the multi-model ensemble mean(MME) in reproducing the meridional(zonal) structure and magnitude of Hadley(Walker) circulation. The MME can also capture the observed strengthening tendency of the winter Hadley circulation and weakening tendency of the Walker circulation. Such secular trends can be simulated by 39% and 74% of the models, respectively. The MME projection indicates that the winter Hadley circulation and the Walker circulation will weaken under both scenarios by the end of the 21 st century. The weakening amplitude is larger under RCP8.5 than RCP4.5, due to stronger external forcing. The majority of the CMIP5 models show the same projection as the MME. However, for the summer Hadley circulation, the MME shows little change under RCP4.5 and large intermodel spread is apparent. Around half of the models project an increase, and the other half project a decrease. Under the RCP8.5 scenario, the MME and 65% of the models project a weakening of the summer southern Hadley circulation.     

Summer Extreme Temperatures over East China during 1984-2004 Simulated by LASG/IAP Regional Climate Model CREM

The authors examine extreme summer temperatures over East China during 1984-2004 using a regional climate model named CREM(the Climate version of Regional Eta-coordinate Model),which was developed by LASG/IAP.The results show that the main features of the extreme summer temperatures over East China are reproduced well by CREM,and the skill for the minimum temperature is higher than that for the maximum temperature,especially along the Yangtze-Huai River Valley(YHV).The simulated extreme temperatures are lower than those of observation,especially for the maximum temperature.The bias of extreme temperatures is consistent with the cold bias of the climatological mean summer surface air temperature.The skill of the model in simulating the interannual variability of extreme temperatures increases from north to south.The simulated interannual variation of the minimum temperature is more reasonable than the maximum temperature.The underestimation of net solar radiation at the surface leads to a cold bias of the climatological mean temperature.Furthermore,the model underestimates the light and moderate rain,while overestimates heavy rain.It causes the simulated minimum temperature more reasonable than the maximum temperature.     

THE INTRASEASONAL VARIABILITY OF SURFACE WIND AND UPPER LAYER THERMAL STRUCTURE IN THE WESTERN TROPICAL PACIFIC WARM POOL REGION DURING THE WINTER OF 1992～1993

In this paper, the hydrographical and meteorological data observed by the R/Vs "Xiang Yang Hong No. 5", "Experiment No. 3"and "Ke Xue No. 1 "during TOGA-COARE IOP are used to analyze the variability of surface wind and upper layer thermal structure, and to reveal the periods of intraseasonal oscillation of surface wind components and certain layers of sea temperature from November 6, 1992 to February 18, 1993 in the western tropical Pacific warm pool region. It is shown that the variation of the sea surface temperature (SST) was inversely correlated to that of surface wind components. It is also indicated from spectral analysis that the significant periods of intraseasonal oscillation of daily mean zonal wind (MZW) were 30-to 60-day and 8-to 9-day long, and that of mean meridional wind (MMW)was 6-to 7-day long. The fluctuation of daily mean sea temperature (MST) in certain layers from surface to the 250 m layer also had the 30-to 60-day low frequency oscillation except for the 150 m layer,and the fluctuations of the daily MST in 100, 150, 200 and 250 m layers had the same 3-day period,their coherence and phase differences were over 0. 90 and between 319° and 353° respectively, which implies the fluctuations of daily MST from 100 to 250 m layers were in phase with each other in the same 3-day period. The analysis of in situ observations revealed a physical evidence of the westerly wind bursts (WWBs) which trigger off the eastward movement of warm water through intraseasonal oscillation and induce the onset of E1 Nino event.     

Changes in Seasonality in China under Enhanced Atmospheric CO2 Concentration

Seasonality changes in China under elevated atmospheric CO 2 concentrations were simulated using nine global climate models,assuming a 1% per year increase in atmospheric CO 2.Simulations of 20th century experiments of season changes in China from the periods 1961 80 to 1981 2000 were also assessed using the same models.The results show that the ensemble mean simulation of the nine models performs better than that of an individual model simulation.Compared the mean climatology of the last 20 years in the CO 2-quadrupling experiments with that in the CO 2-doubling ones,the ensemble mean results show that the hottest/coldest continuous-90-day (local summer/winter) mean temperature increased by 3.4/4.5°C,2.7/2.9°C,and 2.9/4.1°C in Northeast (NE),Southwest (SW),and Southeast (SE) China,respectively,indicating a weakening seasonal amplitude (SA),but by 4.4/4.0°C in Northwest (NW) China,indicating an enlarging SA.The local summer lengthened by 37/30/66/54 days in NW,NE,SW,and SE China,respectively.In some models,the winter disappeared during the CO 2-quadrupling period,judging by the threshold based on the CO 2-doubling period.The average of the other model simulations show that the local winter shortened by 42/36/61/44 days respectively,in the previously mentioned regions.     

Predictability of the East Asian winter monsoon interannual variability as indicated by the DEMETER CGCMS

The interannual variability of East Asian winter monsoon(EAWM) circulation from the Development of a European Multi-Model Ensemble(MME) System for Seasonal to Inter-Annual Prediction(DEMETER) hindcasts was evaluated against observation reanalysis data.We evaluated the DEMETER coupled general circulation models(CGCMs)’ retrospective prediction of the typical EAWM and its associated atmospheric circulation.Results show that the EAWM can be reasonably predicted with statistically significant accuracy,yet the major bias of the hindcast models is the underestimation of the related anomalies.The temporal correlation coefficient(TCC) of the MME-produced EAWM index,defined as the first EOF mode of 850hPa air temperature within the EAWM domain(20-60 N,90-150 E),was 0.595.This coefficient was higher than those of the corresponding individual models(range:0.39-0.51) for the period 1969-2001;this result indicates the advantage of the super-ensemble approach.This study also showed that the ensemble models can reasonably reproduce the major modes and their interannual variabilities for sea level pressure,geopotential height,surface air temperature,and wind fields in Eurasia.Therefore,the prediction of EAWM interannual variability is feasible using multimodel ensemble systems and that they may also reveal the associated mechanisms of the EAWM interannual variability.     

CLIMATOLOGICAL DIAGNOSIS OF WINTER TEMPERATURE VARIATIONS IN GUANGDONG

Using the monthly mean and minimum temperature data of the 36 observation stations in Guang-dong, the climatological features of the temperatures have been analyzed, including characteristics of trends, abrupt changes and periods. And the possible affecting factors on the winter warming in Guangdong have been discussed. The results show that the winter temperatures, particularly the monthly mean minimum temperatures in Guangdong, have a warming trend. The rise of the winter minimum temperatures in Guangdong began in the second half of 1960's and the warming was more evident since the 1980's.     

The Project Siberian High in CMIP5 Models

The Siberian high(SH)experienced a decline from the 1970s to 1990s and a recovery in recent years.The evolution of the SH under global warming is unclear.In this study,41 Coupled Model Intercomparison Project Phase 5(CMIP5)climate models are evaluated in terms of their ability to simulate the temporal evolution of the SH in the 19th and 20th centuries and the spatial pattern of the SH during 1981–2005.The results show that 12models can capture the temporal evolution of the SH center intensity(SHCI)for 1872–2005.The linear correlation coefficient between the SHCI from the Twentieth Century Reanalysis and the simulated SHCI from the multi-model ensemble(MME)of the 12 models is 0.3 on annual and inter-annual scales(above the 99%confidence level).On decadal and multi-decadal time scales,the MME also captures the pronounced reduction(between 1981–2000and 1881–1900 period)and the recovery(during1991–2005)of the SH intensity.Finally,the future evolution of the SH is investigated using the MME of the 12models under the+4.5 and+8.5 W m-2 Representative Concentration Pathway(RCP)scenarios(RCP4.5 and RCP8.5).It is shown that the SHCI,similar to the SHCI in the 20th century,has no significant long-term trend in the 21st century under global warming(RCP8.5 scenario).At the end of 21st century(2081–2100),the SH shows stronger interannual variability than the SH at the end of20th century(1981–2000).The increased interannual variability likely favors the increased interannual variability in winter air temperature over midlatitude Eurasia at the end of 21st century.     

Numerical Simulation of Long-Term Climate Change in East Asia

A 10-yr regional climate simulation was performed using the fifth-generation PSU/NCAR Mesoscale Model Version 3 (MM5V3) driven by large-scale NCEP/NCAR reanalyses. Simulations of winter and summer mean regional climate features were examined against observations. The results showed that the model could well simulate the 10-yr winter and summer mean circulation, temperature, and moisture transport at middle and low levels. The simulated winter and summer mean sea level pressure agreed with the NCAR/NCEP reanalysis data. The model could well simulate the distribution and intensity of winter mean precipitation rates as well as the distribution of summer mean precipitation rates, but it overestimated the summer mean precipitation over North China. The model's ability to simulate the regional climate change in winter was superior to that in summer. In addition, the model could simulate the inter-annual variation of seasonal precipitation and surface air temperature. Geopotential heights and temperature at middle and high levels between simulations and observations exhibited high anomaly correlation coefficients. The model also showed large variability to simulate the regional climate change associated with the El Nino events. The MM5V3 well simulated the anomalies of summer mean precipitation in 1992 and 1995, while it demonstrated much less ability to simulate that in 1998. Generally speaking, the MM5V3 is capable of simulating the regional climate change, and could be used for long-term regional climate simulation.     

长江流域夏季降水的贝叶斯多模式集合概率预测

A Bayesian probabilistic prediction scheme of the Yangtze River Valley (YRV) summer rainfall is proposed to combine forecast information from multi-model ensemble dataset provided by ENSEMBLES project.Due to the low forecast skill of rainfall in dynamic models,the time series of regressed YRV summer rainfall are selected as ensemble members in the new scheme,instead of commonly-used YRV summer rainfall simulated by models.Each time series of regressed YRV summer rainfall is derived from a simple linear regression.The predictor in each simple linear regression is the skillfully simulated circulation or surface temperature factor which is highly linear with the observed YRV summer rainfall in the training set.The high correlation between the ensemble mean of these regressed YRV summer rainfall and observation benefit extracting more sample information from the ensemble system.The results show that the cross-validated skill of the new scheme over the period of 1960 to 2002 is much higher than equally-weighted ensemble,multiple linear regression,and Bayesian ensemble with simulated YRV summer rainfall as ensemble members.In addition,the new scheme is also more skillful than reference forecasts (random forecast at a 0.01 significance level for ensemble mean and climatology forecast for probability density function).     

The Seasonal Climatic Simulation of 9000 Years before Present by Using the IAP Atmospheric General Circulation Model

The seasonal cycle of the climate of 9000 years before present was simulated with the IAP two-level atmospheric general circulation model. The incoming solar radiation was specified from the orbital parameters for 9000 years ago. The boundary conditions of that time were prescribed to the present value because of the small differences between the two. The change in radiation makes temperature to be higher in summer and lower in winter over large areas of the land; and the increased temperature contrast between the land and the ocean strengthens the summer monsoon circulation and increases the precipitation over there. The asymmetry of temperature change between the Northern Hemisphere and the Southern Hemisphere and between summer and winter still exists, which agrees with that get from the previous perpetual experiments.     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature

We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor’s skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.     

A scenario of European climate change for the late twenty-first century: seasonal means and interannual variability

A scenario of European climate change for the late twenty-first century is described, using a high-resolution state-of-the-art model. A time-slice approach is used, whereby the atmospheric general circulation model, HadAM3P, was integrated for two periods, 1960–1990 and 2070–2100, using the SRES A2 scenario. For the first time an ensemble of such experiments was produced, along with appropriate statistical tests for assessing significance. The focus is on changes to the statistics of seasonal means, and includes analysis of both multi-year means and interannual variance. All four seasons are assessed, and anomalies are mapped for surface air temperature, precipitation and snow mass. Mechanisms are proposed where these are dominated by straightforward local processes. In winter, the largest warming occurs over eastern Europe, up to 7°C, mean snow mass is reduced by at least 80% except over Scandinavia, and precipitation increases over all but the southernmost parts of Europe. In summer, temperatures rise by 6–9°C south of about 50°N, and mean rainfall is substantially reduced over the same area. In spring and autumn, anomalies tend to be weaker, but often display patterns similar to the preceding season, reflecting the inertia of the land surface component of the climate system. Changes in interannual variance are substantial in the solsticial seasons for many regions (note that for precipitation, variance estimates are scaled by the square of the mean). In winter, interannual variability of near-surface air temperature is considerably reduced over much of Europe, and the relative variability of precipitation is reduced north of about 50°N. In summer, the (relative) interannual variance of both variables increases over much of the continent.     

Asymmetry of surface climate change under RCP2.6 projections from the CMIP5 models

The multi-model ensemble (MME) of 20 models from the Coupled Model Intercomparison Project Phase Five (CMIP5) was used to analyze surface climate change in the 21st century under the representative concentration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature (SAT) is 1.86°C relative to the pre-industrial level, achieving the target to limit the global warming to 2°C. Associated with the “increase-peak-decline” greenhouse gases (GHGs) concentration pathway of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods: warming during 2006–55 and cooling during 2056–2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cooling period. The warming during 2006–55 is distributed globally, while the cooling during 2056–2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period.     

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.     

Lapwings in Newfoundland

Abstract

Weather observations made at Eureka, on Ellesmere Island in the Canadian High Arctic, have been archived since 1953. The time series, averages, and seasonal cycles of surface temperature, pressure, dew point, relative humidity, cloud cover, wind speed, and direction are presented for the period from 1954 to 2007. Also shown are the time series and averages for the 500 mb temperature, 900 to 500 mb thickness, 500 mb wind speed, and various boundary‐layer stability parameters. Some of the main trends found are 1) an annual average surface warming of 3.2°C since 1972, with summer exhibiting the least warming, 2) a reduction in the frequency of strong anticyclonic events in the winter, 3) a reduction in surface wind speeds except in the summer, 4) a 1.0°C warming in the 500 mb temperature since 1961, with the greatest warming occurring in the spring and summer, and 5) a 10% increase in precipitable water all year round since 1961 but dominated by the spring, summer, and autumn seasons. The importance of open water in the Arctic Ocean for summer temperatures and humidity, of the North Atlantic Oscillation for winter interannual pressure variability, and of precipitable water for winter temperatures are highlighted in this climatology.     

Assessment of the Summer South Asian High in Eighteen CMIP5 Models

The South Asian High(SAH) is one of the most important components of the Asian summer monsoon system. To understand the ability of state-of-the-art general circulation models(GCMs) to capture the major characteristics of the SAH, the authors evaluate 18 atmospheric models that participated in the Coupled Model Intercomparison Project Phase 5/Atmospheric Model Intercomparison Project(CMIP5/AMIP). Results show that the multi-model ensemble(MME) mean is able to capture the climatological pattern of the SAH, although its intensity is slightly underestimated. For the interannual variability of the SAH, the MME exhibits good correlation with the reanalysis for the area and intensity index, but poor skill in capturing the east-west oscillation of the SAH. For the interdecadal trend, the MME shows pronounced increasing trends from 1985 to 2008 for the area and intensity indexes, which is consistent with the reanalysis, but fails to capture the westward shift of the SAH center. The individual models show different capacities for capturing climatological patterns, interannual variability, and interdecadal trends of the SAH. Several models fail to capture the climatological pattern, while one model overestimates the intensity of the SAH. Most of the models show good correlations for interannual variability, but nearly half exhibit high root-mean-square difference(RMSD) values. Six models successfully capture the westward shift of the SAH center in the interdecadal trends, while other models fail. The possible causes of the systematic biases involved in several models are also discussed.     

CMIP5模式对中国东北气候模拟能力的评估

利用CN05观测资料和参与IPCC第五次评估报告的45个全球气候系统模式的模拟结果,分析了新一代全球气候模式对中国东北三省(1961~2005年)气温和降水的模拟能力。结果表明:1)绝大多数模式都能较好地模拟出研究区内显著增温的趋势,对气温的年际变化模拟能力则相对有限;2)所有模式均能很好地再现气温气候态的空间分布特征,且多模式集合模拟结果优于绝大多数单个模式,空间相关系数达到了0.96;3)对于降水的模拟结果,模式间差异较大,多模式集合能较好地再现其空间分布规律(空间相关系数为0.86),对降水年际变化及线性变化趋势的模拟能力则较差。总体来说,多模式集合对东北气候的时空变化特征具有一定的模拟能力,且对气温模拟效果优于降水,对空间分布的模拟能力优于时间变化。     

An assessment of global and regional climate change based on the EH5OM climate model ensemble

An analysis of climate change for global domain and for the European/Mediterranean region between the two periods, 1961–1990 (representing the twentieth century or “present” climate) and 2041–2070 (representing future climate), from the three-member ensemble of the EH5OM climate model under the IPCC A2 scenario was performed. Ensemble averages for winter and summer seasons were considered, but also intra-ensemble variations and the change of interannual variability between the two periods. First, model systematic errors are assessed because they could be closely related to uncertainties in climate change. A strengthening of westerlies (zonalization) over the northern Europe is associated with an erroneous increase in MSLP over the southern Europe. This increase in MSLP is related to a (partial) suppression of summer convective precipitation. Global warming in future climate is relatively uniform in the upper troposphere and it is associated with a 10% wind increase in the subtropical jet cores. However, spatial irregularities in the low-level temperature signal single out some regions as particularly sensitive to climate change. For Europe, the largest near-surface temperature increase in winter is found over its north-eastern part (more than 3°C), and the largest summer warming (over 3.5°C) is over south Europe. For south Europe, the increase in temperature averages is almost an order of magnitude larger than the increase in interannual variability. The magnitude of the warming is larger than the model systematic error, and the spread among the three model realisations is much smaller than the magnitude of climate change. This further supports the significance of estimated future temperature change. However, this is not the case for precipitation, implying therefore larger uncertainties for precipitation than for temperature in future climate projections.