Different Summer Rainfall Anomaly Patterns in Northeast China Associated with Two Kinds of El Ni?o Events

The relationship between summer rainfall anomalies in northeast China and two types of El Ni?o events is investigated by using observation data and an atmospheric general circulation model(AGCM).It is shown that,for different types of El Ni?o events,there is different rainfall anomaly pattern in the following summer.In the following year of a typical El Ni?o event,there are remarkable positive rainfall anomalies in the central-western region of northeast China,whereas the pattern of more rainfall in the south end and less rainfall in the north end of northeast China easily appears in an El Ni?o Modoki event.The reason for the distinct difference is that,associated with the different sea surface temperature anomalies(SSTA)along the equatorial Pacific,the large-scale circulation anomalies along east coast of East Asia shift northward in the following summer after El Ni?o Modoki events.Influenced by the anomalous anticyclone in Philippine Sea,southwesterly anomalies over eastern China strengthen summer monsoon and bring more water vapor to northeast China.Meanwhile,convergence and updraft is strengthened by the anomalous cyclone right in northeast China in typical El Ni?o events.These moisture and atmospheric circulation conditions are favorable for enhanced precipitation.However,because of the northward shift,the anomalous anticyclone in the Philippine Sea in typical El Ni?o cases shifts to the south of Japan in Modoki years,and the anomalous cyclone in northeast China in typical El Ni?o cases shifts to the north of northeast China,leading to the"dipole pattern"of rainfall anomalies.According to the results of numerical experiments,we further confirm that the tropical SSTA in different types of El Ni?o event can give rise to observed rainfall anomaly patterns in northeast China.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Responses of the Southern Ocean mixed layer depth to the eastern and central Pacific El Niño events during austral winter

Based on the Ocean Reanalysis System version 5(ORAS5)and the fifth-generation reanalysis datasets derived from European Centre for Medium-Range Weather Forecasts(ERA5),we investigate the different impacts of the central Pacific(CP)El Niño and the eastern Pacific(EP)El Niño on the Southern Ocean(SO)mixed layer depth(MLD)during austral winter.The MLD response to the EP El Niño shows a dipole pattern in the South Pacific,namely the MLD dipole,which is the leading El Niño-induced MLD variability in the SO.The tropical Pacific warm sea surface temperature anomaly(SSTA)signal associated with the EP El Niño excites a Rossby wave train propagating southeastward and then enhances the Amundsen Sea low(ASL).This results in an anomalous cyclone over the Amundsen Sea.As a result,the anomalous southerly wind to the west of this anomalous cyclone advects colder and drier air into the southeast of New Zealand,leading to surface cooling through less total surface heat flux,especially surface sensible heat(SH)flux and latent heat(LH)flux,and thus contributing to the mix layer(ML)deepening.The east of the anomalous cyclone brings warmer and wetter air to the southwest of Chile,but the total heat flux anomaly shows no significant change.The warm air promotes the sea ice melting and maintains fresh water,which strengthens stratification.This results in a shallower MLD.During the CP El Niño,the response of MLD shows a separate negative MLD anomaly center in the central South Pacific.The Rossby wave train triggered by the warm SSTA in the central Pacific Ocean spreads to the Amundsen Sea,which weakens the ASL.Therefore,the anomalous anticyclone dominates the Amundsen Sea.Consequently,the anomalous northerly wind to the west of anomalous anticyclone advects warmer and wetter air into the central and southern Pacific,causing surface warming through increased SH,LH,and longwave radiation flux,and thus contributing to the ML shoaling.However,to the east of the anomalous anticyclone,there is no statistically significant impact on the MLD.

基于时空综合分型的El Niňo事件对中国东部降水的影响差异

基于1961—2022年中国高分辨率降水格点资料、合成分析和经验正交函数分解方法,揭示了时空综合分型得到的生命史较长-异常中心位置偏东的低频-东部(LF-EP)型和生命史较短-异常中心位置偏西的准两年-中部(QB-CP)型El Niňo事件对中国东部降水的不同影响。结果表明,LF-EP型事件对降水的影响显著且稳定:自发展年秋季到衰减年夏季长达近4个季节,长江以南区域降水持续地显著偏多,且异常雨带中心自衰减年春季起逐步北抬。QB-CP型事件发生时降水异常特征变化更加复杂多变:发展年夏秋季其空间分布与LF-EP型事件中的特征大致相反,长江以南区域降水整体偏少,冬季开始长江以南逐渐有正异常降水出现,且春季以后异常雨带表现出逐渐南退特征,至衰减年夏季发展为华北-长江中下游-华南地区降水异常“正-负-正”分布。进一步通过比较不同类型事件中大尺度水汽输送的差异探讨了其影响不同的可能机制,发现由海温异常纬向位置差异导致的西太平洋区域大气环流直接响应以及衍生模态响应差异是造成中国东部降水异常空间分布特征差异的重要原因。同时,两类时空事件持续性和转相时间的差异也会使得对降水影响的时间尺度出现差别。

Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

Different El Niño Flavors and Associated Atmospheric Teleconnections as Simulated in a Hybrid Coupled Model

A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.

El Niño事件发展期对中国东部夏季极端降水的影响

利用1961−2020年的再分析资料和中国台站观测降水数据集,研究了东部型El Niño事件发展期夏季对中国夏季极端降水的影响.结果表明,东部型El Niño在发展期夏季对中国极端降水的影响主要表现在中国东部地区,造成华北和江南地区极端降水减少,江淮地区极端降水显著增多.进一步分析其中的物理过程发现,当东部型El Niño事件处于发展期夏季时,赤道东太平洋出现显著的海表面温度(sea surface temperature,SST)暖异常,西太平洋区域表现为冷异常,导致反气旋性环流异常.同时,西北太平洋区域存在SST暖异常,对应气旋性环流异常.异常的SST分布激发了“正-负-正(+−+)”的东亚-太平洋型(East Asia-Pacific,EAP)波列异常,对应着“负-正-负(−+−)”的降水配置.在2个异常环流的交汇处有显著的辐合上升运动,为江淮地区带去了充足的水汽.而华北地区主要受到反气旋性环流和蒙古高压的共同控制,并受到来自高纬度地区的异常西北风影响,存在显著的辐散下沉运动,降水的动力条件不足.并且,在东部型El Niño事件发展期夏季,西太平洋副热带高压位置异常偏东,不利于江南地区降水的发生及水汽的输送,进一步造成江南地区极端降水减少.以上结果显示东部型El Niño事件在其发展期夏季对中国极端降水存在重要的影响,为区域极端气候预测提供了理论依据.

Impacts of central-Pacific El Niño and physical drivers on eastern Pacific bigeye tuna

Bigeye tuna Thunnus obesus is an important migratory species that forages deeply,and El Niño events highly influence its distribution in the eastern Pacific Ocean.While sea surface temperature is widely recognized as the main factor affecting bigeye tuna(BET)distribution during El Niño events,the roles of different types of El Niño and subsurface oceanic signals,such as ocean heat content and mixed layer depth,remain unclear.We conducted A spatial-temporal analysis to investigate the relationship among BET distribution,El Niño events,and the underlying oceanic signals to address this knowledge gap.We used monthly purse seine fisheries data of BET in the eastern tropical Pacific Ocean(ETPO)from 1994 to 2012 and extracted the central-Pacific El Niño(CPEN)indices based on Niño 3 and Niño 4indexes.Furthermore,we employed Explainable Artificial Intelligence(XAI)models to identify the main patterns and feature importance of the six environmental variables and used information flow analysis to determine the causality between the selected factors and BET distribution.Finally,we analyzed Argo datasets to calculate the vertical,horizontal,and zonal mean temperature differences during CPEN and normal years to clarify the oceanic thermodynamic structure differences between the two types of years.Our findings reveal that BET distribution during the CPEN years is mainly driven by advection feedback of subsurface warmer thermal signals and vertically warmer habitats in the CPEN domain area,especially in high-yield fishing areas.The high frequency of CPEN events will likely lead to the westward shift of fisheries centers.

Estimating the Yield Loss of Winter Wheat from Drought in the United States Southern Plains Region as Influenced by El Niño-Southern Oscillation (ENSO)

Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.

El Niño-Southern Oscillation (ENSO) Variations and Climate Changes Worldwide

This investigation aims to study the El-Niño-Southern Oscillation (ENSO) events in these three phases: El Niño, La Niña, and neutral. Warm and cold events relate to the Spring/Summer seasons. This paper will search for connections between the ENSO events and climate anomalies worldwide. There is some speculation that those events would be necessary for the climate anomalies observed worldwide. After analyzing the data from the reports to the ENSO, it shows almost periodicity from 1950-2023. We emphasized the occurrence of El Niño two years, when it was most prominent, and the climate anomalies (following NOAA maps), 2015 and 2023. The results indicated that the observed climate anomalies couldn’t be linked to the abnormal events observed. The worldwide temperatures in those years enhanced mostly in 2023. It shows an abnormal behavior compared with all the years scrutinized and analyzed since the records began. Therefore, there must be unknown factors beyond ENSO that rule the worldwide temperatures and the climate anomalies observed.

两类El Nio事件对我国河西走廊地区水文气象要素的影响

在两类El Nio事件下,通过滑动平均,对河西走廊地区降水量、气温及出山径流量与ElNio的相关性进行了研究,并用距平法分析了1959-2005年期间两类El Nio事件对研究区气温、降水量和出山径流量变化的具体影响。结果表明,整个河西地区受El Ni珘no较强影响,在第一类El Nio事件年,高温少雨、出山径流量偏少;第二类El Nio事件年该地区低温多雨、出山径流量较丰。相比高海拔山区,气温在低海拔地区对El Nio响应程度更高,降水对El Nio的响应在山区和低海拔平原区差别不大,均表现出较高的敏感性。与出山径流量相比,降水量和气温对El Nio的响应更高一些。

利用热带测雨卫星的测雨雷达资料对1997/1998年ElNio后期热带太平洋降水结构的研究

利用热带测雨卫星的测雨雷达 (TRMMPR)的探测结果 ,对 1 997 1 998年ElNin～o后期热带太平洋的降水结构进行了研究 ,并对比了非ElNin～o的 1 999年和 2 0 0 0年的同期降水情况 ,取得如下结果 :( 1 ) 1 997 1 998ElNin～o后期与非ElNin～o期间相比 ,1 997 1 998ElNin～o后期 ,热带东、中太平洋层云降水和对流云降水的比例明显增大、平均降水率也增大 ,并且层云强降水的比例增多 ,而层云弱降水比例减少。 ( 2 )在非ElNin～o期间 ,热带东、中太平洋对流云降水系统较为浅薄 ,冻结层高度比西太平洋低约 0 5km ;而在 1 997 1 998ElNin～o后期 ,这种差异明显减小 ,热带东、中太平洋对流云降水和层云降水都变得深厚 ;对流云降水和层云降水的降水率随高度的变化也发生了变化。 ( 3)对大气环流的分析表明 ,对应于降水结构的变化 ,热带太平洋地区的高空辐合辐散分布也发生了改变 ,导致Walker环流在 1 997 1 998ElNin～o后期减弱。

2009/2010年El Nio事件变化特征及其机理

应用TAO(Tropical Atmosphere Ocean project)热带太平洋实测海温和风场资料,分析研究了发生在2009/2010年的El Nio事件的变化特征,讨论了此次El Nio事件发生过程中,赤道东、西太平洋次表层异常海温的变化特征及其传播过程,特别是对赤道太平洋次表层异常海温变化的过程进行了深入分析研究。结果表明,2009/2010年赤道太平洋的增温主要存在两个不同的过程。一是西太平洋暖池(WPWP)区域次表层异常海温沿温跃层东传,以及赤道东太平洋的局地增温导致赤道东太平洋上层海洋增温过程。二是中西太平洋区域的异常西风加强,使得在中太平洋产生强的风场辐合,导致表层较高海温下传(downwelling),使中太平洋次表层异常海温再次升高,从而导致赤道东太平洋表层出现第2次增温过程。这一研究结果表明,2009/2010年赤道太平洋增温过程与以往的El Nio事件过程有所不同,此次事件不仅包括了经典的暖事件形成过程,同时也具备了中部型El Nio(Central Pacific Pattern ElNio,简称CPP El Nio)事件的特征。此次异常海温信号不仅与热带太平洋次表层异常海温信号通道中的异常海温循环有关,还与中西太平洋区域的大气风场异常强迫引起的中太平洋次表层异常海温信号增强过程存在密切关系。

El Nio事件发生和消亡中热带太平洋纬向风应力的动力作用 Ⅱ.模式结果分析

为了分析 ＥＩ Ｎｉｏ事件发生和消亡中热带太平洋纬向风应力的动力作用，建立一个类似于Ｚｅｂｉａｋ的简单热带海洋数值模式，在观测到的风应力异常的强迫下，模拟赤道太平洋地区 １９７１年１月至 １９９８年８月海表温度异常的变化。结果表明，模式对观测的Ｎｉｏ３区海表温度异常（ＳＳＴＡ）有很好的模拟能力。模拟和观测Ｎｉ区ＳＳＴＡ之间的相关系数可达 ０．９０。模式对 Ｅｌ Ｎｉｏ事件期间赤道太平洋海表温度异常随时间变化也有较好的模拟能力。为了分析Ｅｌ Ｎｉｏ期间ＳＳＴＡ的空间分布及其随时间变化的动力学机制，还对１９８６～１９８９年 ＥＮＳＯ循环期间赤道太平洋地区观测的 ＳＳＴＡ的传播特征及其形成机制进行了分析。模式较好地模拟出了观测到的赤道太平洋地区ＳＳＴＡ的传播特征，即从１９８６年底至１９８７年 ４月， ＳＳＴＡ具有向东传播的特征，从 １９８７年 ６月至 １９８８年 ２月具有向西传播的特征。动力学分析的结果表明，赤道中西太平洋地区的缔向风应力异常对 Ｅｌ Ｎｉｏ事件的发生和消亡具有重要作用。赤道中西太平洋地区的西风异常可强迫出东传的Ｋｅｌｖｉｎ波，这个东传的 Ｋｅｌｖｉｎ波对正 ＳＳＴＡ的东传起主要作用，当这个东传的

El Nio事件期间南海环流的异常特征

基于CORA再分析资料对南海环流的季节特征和其受ElNio事件的响应进行了分析。结果表明,冬季整个南海海区表现为一个大的气旋式环流,夏季南海北部是气旋式环流,南部是一个反气旋式环流。通过对南海海区异常流场进行MV-EOF分解,分析其前两个模态,其空间型主要体现了南海环流冬季和夏季的特征,对应的时间系数与Nio3.4_NDJ指数有很好的相关性。通过分析南海环流在1986—2008年间ElNio年份的异常流场和异常流函数场,证明了MV-EOF分解后得到的联合时间系数所反映各阶段南海环流的季节特征与ElNio事件有相关性,即在8月[0],南海南部异常流函数场表现为反气旋式环流,北部为气旋式环流,南海夏季环流被增强,且ElNio事件时间尺度越长,北部的气旋式异常流场的影响范围就越大;在12月[0],南海除了东南部外,其余整个海区异常流函数场主要表现为反气旋式环流,冬季环流被减弱;在8月[+1],南海夏季流场强度都被削弱了。

El Nio位相期间印度洋海温异常对中国南部初夏降水及初夏亚洲季风影响的数值模拟研究

基于中国科学院大气物理研究所的ＩＡＰ ９Ｌ大气环流模式，设计并完成了赤道太平洋暖异常海温和印度洋地区的不同结构异常海温的强迫试验．以研究在 Ｅｌ Ｎｉｏ位相期间印度洋不同海温异常分布对初夏亚洲季风及我国南部地区初夏降水的影响。结果表明：ＥＩＮｉｏ位相期间印度洋异常海温的作用是不可忽视的。在 Ｅｌ Ｎｉｏ位相期间，印度洋不同的海温结构对越赤道气流异常，对印度、中南半岛及中国南方的降水分布有重要的影响。利用ＮＣＥＰ的资料进行合成分析，进一步证实了数值模拟结果的可靠性。

El Nio事件对其衰减阶段夏季中国降水季节内演变的影响及其机理

利用1979—2007年NOAA重建海温逐月资料和中国160站夏季降水资料,使用扩展奇异值分解(extended singular value decomposition,ESVD)方法,研究了冬季热带太平洋海温异常与次年夏季中国降水异常季节内演变型之间的关系,指出前冬El Nio事件是与次年夏季中国降水季节内变化相联系的最重要的热带太平洋海温异常模态。相应的降水异常季节内变化情况为:6月在长江以南为正异常,江淮流域有负异常;7月在华南沿海有负降水异常,而正异常北进到长江流域,华北地区也出现正降水异常;8月在长江南北分别为少雨和多雨。进一步研究前冬El Nio事件与次年春夏印度洋、太平洋海温异常、对流层低层风场异常以及副热带高压等的联系,结果表明:El Nio事件发生的次年春夏,热带西太平洋周边存在东负西正的海温异常分布;西太平洋反气旋异常较强;副高在6月、7月偏西偏北,但在8月迅速南退。虽然与El Nio事件相联系的6月与7月、8月的降水型不同,但是西太平洋反气旋异常带来的充沛水汽造成7月长江流域雨季多雨,8月副高迅速南退带来的又一次长江流域降水,造成了El Nio事件发生次年夏季长江流域涝而华南沿海旱的夏季平均降水异常型。

El Nio/La Nia影响下北部湾海域浮游桡足类种类组成与多样性

以1998年1月至1999年5月对北部湾海域进行的4个航次生态环境综合调查的资料为基础,分析El Nio/La Nia期间北部湾四季浮游桡足类种类组成与多样性,并对其与气候及海洋水文的关系进行初步探讨。结果显示,调查期间共出现浮游桡足类122种,其中32种周年出现,以春(82种)、夏(84种)较多,秋(52种)、冬(67种)较少;四季共出现优势桡足类13种,以广温广盐类型占主导,除微刺哲水蚤(Canthocalanus pauper)外,其余12种为季节性优势种;冬、夏两季受El Nio影响较大,优势种以中型桡足类为主;秋、春季大型桡足类优势地位较高,受La Nia影响明显;北部湾浮游桡足类多样性较高。分析表明,夏季北部湾水温和盐度对浮游桡足类群落多样性有一定影响,但在其他季节,这种影响不明显。

赤道太平洋西风异常与El Nio的关系

分析了 1 980年以来赤道太平洋西风异常观测资料 ,并利用POM海洋模式模拟了赤道太平洋海温对不同类型西风异常的响应。分析和数值模拟试验结果都表明 ,赤道太平洋上的西风异常可以引起赤道中东太平洋海温升高 ,但是ElNi no事件是否能发生 ,则与西风异常的位置、强度和东移有关。只有当赤道中太平洋 ( 1 60°E～ 1 60°W )出现一定强度的西风异常并较快东移 ,才有利于ElNi no发生。

新旧两个版本GAMIL模式对1997/98强El Nio年西太平洋暖池区独特云辐射强迫特征的数值模拟

1997/98年强ElNio背景下西太平洋暖池区云辐射强迫的变化,表现出诸多不同于以往的特征,已经成为检验气候模式性能的一个重要标准。本文基于卫星资料,分析了大气环流模式GAMIL1.0和2.0版对上述现象的模拟能力。结果表明,GAMIL1.0模式对热带地区云辐射特征分布,尤其对西太平洋暖池区的长(短)波云辐射强迫及其异常的模拟结果均和观测接近,但其模拟的长(短)波云辐射以及净云辐射冷却作用的强度均偏强,且模拟的1998年异常亦不如观测明显。GAMIL2.0对热带云辐射强迫空间分布的模拟较GAMIL1.0存在一定改进,但其未能模拟出1998年暖池地区云辐射强迫异常。对比观测发现,暖池区云辐射强迫的模拟偏差主要源自模式对该处云量、云水路径及云垂直结构的模拟偏差。在GAMIL1.0中,它们共同造成模拟的短波云辐射明显偏强,而其相互补偿使长波云辐射模拟略好于前者,导致模拟净云辐射冷却作用过强。在GAMIL2.0中,高估的云水路径致使短波云辐射过强,而其模拟云量、平均云顶高度偏低则导致长波云辐射强迫偏弱。模式的晴空短(长)波辐射通量过高(低),亦对模拟短波云辐射强迫以及净云辐射冷却作用偏强有影响。