CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

Dominant Synoptic Patterns and Their Relationships with PM_(2.5) Pollution in Winter over the Beijing–Tianjin–Hebei and Yangtze River Delta Regions in China

This paper concerns about the episodes of PM_(2.5) pollution that frequently occur in China in winter months. The severity of PM_(2.5) pollution is strongly dependent on the synoptic-scale atmospheric conditions. We combined PM_(2.5) concentration data and meteorological data with the Hybrid Single Particle Lagrangian Integrated Trajectory model(HYSPLIT4) to investigate the dominant synoptic patterns and their relationships with PM_(2.5) pollution over the Beijing–Tianjin–Hebei(BTH) and Yangtze River Delta(YRD) regions in the winters of 2014–17. The transport of PM_(2.5) from the BTH to YRD regions was examined by using cluster analysis and HYSPLIT4. It is found that the level of PM_(2.5) pollution over the BTH region was higher than that over the YRD region. The concentration of PM_(2.5) in the atmosphere was more closely related to meteorological factors over the BTH region. The episodes of PM_(2.5) pollution over the BTH region in winter were related to weather patterns such as the rear of a high-pressure system approaching the sea, a high-pressure field, a saddle pressure field, and the leading edge of a cold front. By contrast,PM_(2.5) pollution episodes in the YRD region in winter were mainly associated with the external transport of cold air, a high-pressure field, and a uniform pressure field. Cluster analysis shows that the trajectories of PM_(2.5) were significantly different under different weather patterns. PM_(2.5) would be transported from the BTH to the YRD within 48 h when the PM_(2.5) pollution episodes were associated with three different kinds of weather patterns: the rear of a highpressure system approaching the sea, the high-pressure field, and the leading edge of a cold front over the BTH region. This suggests a possible method to predict PM_(2.5) pollution episodes based on synoptic-scale patterns.     

Atmospheric Circulation and Dynamic Mechanism for Persistent Haze Events in the Beijing–Tianjin–Hebei Region

In this study, regional persistent haze events(RPHEs) in the Beijing–Tianjin–Hebei(BTH) region were identified based on the Objective Identification Technique for Regional Extreme Events for the period 1980–2013. The formation mechanisms of the severe RPHEs were investigated with focus on the atmospheric circulation and dynamic mechanisms. Results indicated that:(1) 49 RPHEs occurred during the past 34 years.(2) The severe RPHEs could be categorized into two types according to the large-scale circulation, i.e. the zonal westerly airflow(ZWA) type and the high-pressure ridge(HPR) type. When the ZWA-type RPHEs occurred, the BTH region was controlled by near zonal westerly airflow in the mid–upper troposphere.Southwesterly winds prevailed in the lower troposphere, and near-surface wind speeds were only 1–2 ms~(-1). Warm and humid air originating from the northwestern Pacific was transported into the region, where the relative humidity was 70% to 80%, creating favorable moisture conditions. When the HPR-type RPHEs appeared, northwesterly airflow in the mid–upper troposphere controlled the region. Westerly winds prevailed in the lower troposphere and the moisture conditions were relatively weak.(3) Descending motion in the mid-lower troposphere caused by the above two circulation types provided a crucial dynamic mechanism for the formation of the two types of RPHEs. The descending motion contributed to a reduction in the height of the planetary boundary layer(PBL), which generated an inversion in the lower troposphere. This inversion trapped the abundant pollution and moisture in the lower PBL, leading to high concentrations of pollutants.     

On the Contrasting Decadal Changes of Diurnal Surface Temperature Range between the Tibetan Plateau and Southeastern China during the 1980s–2000s

The diurnal surface temperature range(DTR) has become significantly smaller over the Tibetan Plateau(TP) but larger in southeastern China, despite the daily mean surface temperature having increased steadily in both areas during recent decades.Based on ERA-Interim reanalysis data covering 1979–2012, this study shows that the weakened DTR over TP is caused by stronger warming of daily minimum surface temperature(Tmin) and a weak cooling of the daily maximum surface temperature(Tmax); meanwhile, the enhanced DTR over southeastern China is mainly associated with a relatively stronger/weaker warming of Tmax/Tmin. A further quantitative analysis of DTR changes through a process-based decomposition method—the Coupled Surface–Atmosphere Climate Feedback Response Analysis Method(CFRAM)—indicates that changes in radiative processes are mainly responsible for the decreased DTR over the TP. In particular, the increased low-level cloud cover tends to induce the radiative cooling/warming during daytime/nighttime, and the increased water vapor helps to decrease the DTR through the stronger radiative warming during nighttime than daytime. Contributions from the changes in all radiative processes(over-2?C) are compensated for by those from the stronger decreased surface sensible heat flux during daytime than during nighttime(approximately 2.5?C), but are co-contributed by the changes in atmospheric dynamics(approximately-0.4?C) and the stronger increased latent heat flux during daytime(approximately-0.8?C). In contrast, the increased DTR over southeastern China is mainly contributed by the changes in cloud, water vapor and atmospheric dynamics. The changes in surface heat fluxes have resulted in a decrease in DTR over southeastern China.     

A REGIONAL COUPLED AIR–SEA–WAVE MODEL: SIMULATION OF UPPER-OCEAN RESPONSES TO AN IDEALIZED TROPICAL CYCLONE

In this study a coupled air–sea–wave model system, containing the model components of GRAPES-TCM, ECOM-si and WAVEWATCH III, is established based on an air–sea coupled model. The changes of wave state and the effects of sea spray are both considered. Using the complex air–sea–wave model, a set of idealized simulations was applied to investigate the effects of air–sea–wave interaction in the upper ocean. Results show that air–wave coupling can strengthen tropical cyclones while air–sea coupling can weaken them; and air–sea–wave coupling is comparable to that of air–sea coupling, as the intensity is almost unchanged with the wave model coupled to the air–sea coupled model. The mixing by vertical advection is strengthened if the wave effect is considered, and causes much more obvious sea surface temperature (SST) decreases in the upper ocean in the air–sea coupled model. Air–wave coupling strengthens the air–sea heat exchange, while the thermodynamic coupling between the atmosphere and ocean weakens the air–sea heat exchange: the air–sea–wave coupling is the result of their balance. The wave field distribution characteristic is determined by the wind field. Experiments are also conducted to simulate ocean responses to different mixed layer depths. With increasing depth of the initial mixed layer, the decrease of SST weakens, but the temperature decrease of deeper layers is enhanced and the loss of heat in the upper ocean is increased. The significant wave height is larger when the initial mixed layer depth increases.     

Influence of soil moisture in eastern China on the East Asian summer monsoon

The sensitivity of the East Asian summer monsoon to soil moisture anomalies over China was investigated based on ensembles of seasonal simulations(March–September) using the NCEP GCM coupled with the Simplified Simple Biosphere Model(NCEP GCM/SSi B). After a control experiment with free-running soil moisture, two ensembles were performed in which the soil moisture over the vast region from the lower and middle reaches of the Yangtze River valley to North China(YRNC) was double and half that in the control, with the maximum less than the field capacity. The simulation results showed significant sensitivity of the East Asian summer monsoon to wet soil in YRNC. The wetter soil was associated with increased surface latent heat flux and reduced surface sensible heat flux. In turn, these changes resulted in a wetter and colder local land surface and reduced land–sea temperature gradients, corresponding to a weakened East Asian monsoon circulation in an anomalous anticyclone over southeastern China, and a strengthened East Asian trough southward over Northeast China. Consequently, less precipitation appeared over southeastern China and North China and more rainfall over Northeast China. The weakened monsoon circulation and strengthened East Asian trough was accompanied by the convergence of abnormal northerly and southerly flow over the Yangtze River valley, resulting in more rainfall in this region.In the drier soil experiments, less precipitation appeared over YRNC. The East Asian monsoon circulation seems to show little sensitivity to dry soil anomalies in NCEP GCM/SSi B.     

Updated Homogenized Chinese Temperature Series with Physical Consistency

Most methods of homogenization of climate data are applied to time series of a single variable, such as daily maximum temperature(Tmax) or daily minimum temperature(Tmin). Consequently, the physical relationship among different variables, e.g., TmaxTmin, may be distorted after homogenization of climate series of individual variables. The authors develop a solution to improve consistency among diurnal temperature records, while using the Multiple Analysis of Series for Homogenization(MASH) method to homogenize the observation series of daily mean temperature(Tm), Tmin, and Tmax at 545 stations in China for the period 1960–2011, called CHTM2.0. In the previous version of this homogenized dataset based on MASH(CHTM1.0) for the period 1960–2008, there are a few records(0.039% of the total) that are physically inconsistent. For developing CHTM2.0, the authors apply additional adjustments for each day with inconsistent temperature records, in order to hold TmaxTmTmin. Although the additional adjustments are barely influential for estimating long-term climate trends in China as a whole(because very few records are additionally adjusted), the newly introduced solution improves the physical consistency throughout the dataset. It is also helpful for developing more reasonable homogenized climate datasets with regard to physical consistency among multiple variables. Based on CHTM2.0, the annual Tmax/Tm/Tmin series averaged over China for the period 1960–2011 show significant warming trends of about 0.19/0.25/0.34°C per decade, respectively. Large warming trends of up to 0.425/0.596/ 0.704°C per decade occur in northeastern and northwestern China.     

Multi-Fractal Analy is of Daily Air Temperature Time Series in Coastal Areas of China

In this article, the Multi-Fractal Detrended Fluctuation Analysis (MF-DFA) method is adopted to study the temperature, i. e., the maximum temperature (Tmax), mean temperature (Tavg) and minimum (Tmin) air temperature, multifractal characteristics and their formation mechanism, in the typical temperature zones in the coastal regions in Guangdong, Jiangsu and Liaoning Provinces. Following are some terms and concepts used in the present study. Multifractality is defined as a term that characterizes the complexity and self-similarity of objects, and fractal characteristics depict the distribution of probability over the whole set caused by different local conditions or different levels in the process of evolution. Fractality strength denotes the fluctuation range of the data set, and long-range correlation (LRC) measures the stability of the climate system and the trend of climate change in the future. In this research, it is found that the internal stability and feedback mechanism of climate systems in different regions show regional differences. Furthermore, the research also proves that the Tavg, Tmax and Tmin of the above three provinces are highly multifractal. The temperature series multifractality of each province decreases in the order of temperature series multifractality of Liaoning > temperature series multifractality of Guangdong > temperature series multifractality of Jiangsu, and the corresponding long-range correlations follow the same order. It reveals that the most stable temperature series is that of Liaoning, followed by the temperature series of Guangdong, and the most unstable one is that of Jiangsu. Liaoning has the most stable climate system, and it will thus be less responsive to the future climate warming. The stability of the climate system in Jiangsu is the weakest, and its temperature fluctuation will continue to increase in the future, which will probably result in the meteorological disasters of high temperature and heat wave there. Guangdong possesses the strongest degree of multifractal strength, which indicates that its internal temperature series fluctuation is the largest among the three regions. The Tmax multifractal strength of Jiangsu is stronger than that of Liaoning, while the Tavg and Tmin multifractal strength of Jiangsu is weaker than that of Liaoning, showing that Jiangsu has a larger internal Tmax fluctuation than Liaoning does, while it has a smaller fluctuation of Tavg and Tmin than Liaoning does. Guangdong and Liaoning both show the strongest Tmin multifractal strength, followed by Tavg multifractal strength, and the weakest Tmax multifractal strength. However, Jiangsu has the strongest Tmax, followed by Tavg, and the weakest Tmin. The research findings show that these phenomena are closely related to solar radiation, monsoon strength, topography and some other factors. In addition, the multifractality of the temperature time series results from the negative power-law distribution and long-range correlation, in which the long-range correlation influence of temperature series itself plays the dominant role. With the backdrop of global climate change, this research can provide a theoretical basis for the prediction of the spatial-temporal air temperature variation in the eastern coastal areas of China and help us understand its characteristics and causes, and thus the present study will be significant for the environmental protection of coastal areas.     

Changes to the Natural Regional Boundaries in China During 1961-2007

Daily temperature data from 599 stations across China for the years 1961 to 2007 were used to analyze the changes in the natural regional boundaries.The results show that the accumulated temperature ≥ 10℃ and its duration changed dramatically from the end of 1990s to the early 21st century.The amplitude of natu-ral regional boundaries was greater in the 21st century than it was in the 20th century.In the eastern region of China,the climatic zones were migrating generally northward,with the northern edge of the subtropical zone and the eastern section of the warm temperate zone showing an obvious northward shift of up to 1 3° of lati-tude.The climatic zones moved south in the Qing-hai-Tibet Plateau,western Inner Mongolia,and some ar-eas of western Xinjiang,and slightly to the north in other parts of the western region.     

Spatiotemporal Variability of Surface Wind Speed during 1961–2017 in the Jing–Jin–Ji Region,China

Wind speed variations are influenced by both natural climate and human activities. It is important to understand the spatial and temporal distributions of wind speed and to analyze the cause of its changes. In this study, data from 26 meteorological stations in the Jing–Jin–Ji region of North China from 1961 to 2017 are analyzed by using the Mann–Kendall(MK) test. Over the study period, wind speed first decreased by-0.028 m s-1 yr-1(p 0.01) in1961–1991, and then increased by 0.002 m s1-yr1-(p 0.05) in 1992–2017. Wind speed was the highest in spring(2.98 m s-1), followed by winter, summer, and autumn. The largest wind speed changes for 1961–1991 and1992–2017 occurred in winter(-0.0392 and 0.0065 m s-1 yr1-, respectively); these values represented 36% and 58%of the annual wind speed changes. More than 90.4% of the wind speed was concentrated in the range of 1–5 m s-1,according to the variation in the number of days with wind speed of different grades. Specifically, the decrease in wind speed in 1961–1991 was due to the decrease in days with wind speed of 3–5 m s-1, while the increase in wind speed in 1992–2017 was mainly due to the increase in days with wind speed of 2–4 m s-1. In terms of driving factors,variations in wind speed were closely correlated with temperature and atmospheric pressure, whereas elevation and underlying surface also influenced these changes.     

欧亚大陆季节增（融）雪盖面积变化特征分析

利用美国冰雪资料中心(National Snow and Ice Data Center)提供的近40年逐周的卫星反演雪盖资料,定义了各季节新增(融化)雪盖而积指数(fresh snow extent),即增/融雪覆盖率P_(FSE)、增/融雪面积A_(FSE)、欧亚大陆北部增/融雪面积之和T_(FSE),针对欧亚大陆各季节平均的雪盖面积本身(snow extent,P_(SE)、A_(SE)、T_(SE)和其增(融)雪盖面积,分析比较二者的变化特征.结果表明,欧亚大陆各季节平均的雪盖面积和相应增(融)雪盖面积不论是气候态分布还是其年际、十年际变化均有明显不同,其中以冬、春季差别更为明显;夏、秋季二者虽有较好的一致性,但增(融)雪盖面积的变率明显强于雪盖而积本身;另外,冬季欧洲新增雪盖对欧业北部冬季雪盖面积以及其后的春季雪盖都有较显著的影响,而春季欧洲和中纬度亚洲地区的融雪则受到冬、春两季雪盖情况的影响.进一步分析欧亚大陆冬、春两季增(融)雪盖与ENSO关系显示,二者除在个别地区(两伯利业北部、欧洲中东部以及青藏高原)存在较明显关系外,整体上,欧亚大陆北部雪盖变化既不受控于ENSO,也不会显著影响ENSO.     

基于MODIS NDVI和气候信息的草原植被变化监测

对植被的动态监测可以从一定程度上反映气候变化趋势。该文利用2000—2005年MODIS NDVI数据对锡林郭勒盟典型草原植被变化进行动态监测,在此基础上,以降水量、水汽压、平均气温、最高气温、最低气温、日照时数作为气候指标,分析锡林郭勒盟典型草原和荒漠草原MODIS NDVI与同期及前期气候因子的相关性,探讨草原植被变化的气候驱动因子。结果表明:2000—2005年锡林郭勒盟植被改善面积大于退化面积,植被退化面积最大的区域为荒漠草原,占全盟面积的12.84%,植被改善面积最大的区域为典型草原,占全盟面积29.09%。4类草原改善趋势由强到弱的顺序为草甸草原、典型草原、沙地草原、荒漠草原。对于典型草原,其NDVI与最高气温关系最密切,其次为水汽压;对于荒漠草原,其NDVI与最高气温关系最为密切,其次为最低气温。此外,NDVI对气候因子的响应表现出明显的时滞效应。     

中国西北干旱、半干旱区春季地气温差的年代际变化特征及其对华北夏季降水年代际变化的影响

利用我国1951~2000年夏季降水观测资料分析了我国夏季降水的年代际变化特征,表明了我国夏季降水在1976年前后发生了一次明显的气候跃变,在1976年之后华北地区和黄河流域夏季降水明显减少,出现了严重持续干旱,而西北地区从20世纪70年代后期开始,降水增多,且西北地区降水振荡位相要超前于华北地区降水振荡位相5~8年。并且,本文从1960~2000年我国西北干旱、半干旱区的地温、气温观测资料分析了我国西北干旱、半干旱地区的地气温差(Ts-Ta)的变化特征,其结果表明了在20世纪70年代后期以前,我国西北干旱、半干旱地区的地气温差大部分年份偏低,低于平均值,而从70年代后期之后到2000年,我国西北干旱、半干旱地区的地气温差偏高。此外,本文还分析了西北干旱区地气温差变化的最大地区新疆西部春季地气温差与我国夏季降水的相关关系,其正相关区分别位于西北地区、东北地区和长江流域,而负相关区分别位于华北地区东部和西南地区,这表明我国西北干旱、半干旱区春季地气温差可能是华北地区夏季降水年代际变化的原因之一。     

1961-2017年京津冀地区寒潮活动特征

基于1961—2017年京津冀地区126个气象观测站逐日最低气温和降水资料,分析该区域寒潮发生频次时空变化特征,在此基础上通过定义的干湿判别指标分析区域性寒潮的干湿特征。结果表明:(1)京津冀地区单站寒潮年平均发生频次空间分布呈西北多东南少,86%的站点寒潮年发生频次呈减少趋势。(2)1961—2017年寒潮累计发生站次呈显著减少趋势(P<0.001),气候倾向率为-5.7站次·a^(-1),且在1983年发生突变。1961—1971年寒潮累计发生站次出现峰值,从1972年开始锐减,2007—2017年寒潮平均发生站次为历史最少。(3)1961—2017年区域性寒潮发生频次年际变化总体呈递减趋势,气候倾向率为-0.282次·(10 a)^(-1),1960年代冬季区域性寒潮发生频次最多,1970年代秋季和春季最多,2000年代冬季和春季为次高峰期,2011—2017年3个季节最少。区域性寒潮发生频次季节分布中以秋季出现最多、其次是冬季、春季最少;10月、11月寒潮最为活跃。(4)京津冀地区区域性寒潮过程干过程发生频次最多,2011—2017年区域性寒潮过程干湿特征趋向于干过程和湿过程两极化分布。     

基于遥感资料研究合肥城市化对气温的影响

为了探讨城市化进程对城市区域气温的影响程度,利用高分辨陆地卫星影像结合GIS技术揭示了近30年合肥城市化进程及其对气象观测场周边土地利用/覆盖变化（LUCC）的影响过程;进一步分析了1970—2008年合肥气象站与其周边的肥西和肥东气象站观测的年平均、最高和最低3项气温的动态变化特征,并最终建立了合肥气象观测场周边LUCC与气温的关系模型。结果表明,近30年来,合肥建成面积在不断扩大,从而导致了气象观测＂进城＂而先后进行搬迁的现象,继而产生了气温序列的非均一性。1979—2003年期间,合肥观测场由于受到城市扩张影响显著,合肥站3项气温的增温速率均明显大于肥西和肥东站3项气温增温速率。合肥观测场周边半径为4 km缓冲区LUCC对平均气温和最低气温的变化有显著影响。建成面积的增加对平均气温、最低气温有正贡献;而耕地、植被、水体的增加却对平均气温、最低气温存在负贡献。     

A simplified calibrated model for estimating daily global solar radiation in Madinah, Saudi Arabia

Solar radiation is the most important parameter in defining the energy budget at the surface thereby influencing the hydroclimate. Several empirical models based on air temperature are developed and used in several decision-making needs such as agriculture and energy sector. However, a calibration against direct observations is a priori for implementing such models. A calibrated model is developed for Saudi Arabia (Madinah) based on observations during 2007–2011. The model $ \left( {\mathrm{Rs}=A+B\cdot \mathrm{R}{{\mathrm{s}}_0}{{{\left( {{T_{\max }}-{T_{\min }}} \right)}}^C}} \right) $ is used to estimate daily solar radiation and results show a correlation coefficient of 0.94. The calibrated model outperforms the uncalibrated model available for this location. To increase the confidence, the calibrated model is also compared with a simple artificial neural network.     

近57年巴彦淖尔市平均最高最低气温及日较差变化

利用1954年-2010年内蒙古巴彦淖尔市9个台站的月平均最高、最低气温观测资料,对巴彦淖尔市年、季平均最高、最低气温变化趋势的空间分布状况和时间变化特征进行了分析。结果表明,近57年来,巴彦淖尔市年平均最高气温的变化特征呈现北部增暖幅度明显大于南部,且近十年呈弱降温趋势;年平均最低气温与全国各地基本一致,呈明显的变暖趋势;无论是年还是季,平均最低气温的增暖幅度明显大于平均最高气温的增幅;年平均日较差多呈下降趋势,并在北部地区尤为明显,各季平均日较差亦均呈下降趋势,并以冬季的下降幅度为最大;年平均最高气温和最低气温的变化在年代际变化上基本呈现较为一致的变化,即57年来主要的变暖均是从20世纪80年代中期开始,均在90年代后期达到了近57年来的历史新高,最高气温近十年来又略有回落。     

基于均一化观测序列的京津冀地区气候变化格局分析

利用1960~2015年京津冀地区88个国家级气象站观测资料（包括日平均气温、日最高气温、日最低气温、日降水、日平均风速等）,使用MASH（Multiple Analysis of Series for Homogenization）方法剔除台站迁址、仪器变更等因素所致偏差后,生成均一化的观测资料集。基于新资料集计算了各站气温、降水和凤速序列的线性趋势和Morlet小波等统计特征,分析了京津冀地区气候变化格局。结果表明:MASH方法能较准确地检测并校订观测序列中迁站、仪器变更等因素所导致的非均一性;1960~2015年期间京津冀年平均气温显著上升,上升幅度为0.261℃/10 a;降水减少,平均减少11.27 mm/10 a;风速显著减小,平均减小0.193 m s-1（10 a）-1。     

The effect of cloud parametrization and temperature profile on the climate sensitivity to ozone perturbations

A one-dimensional radiative-convective model extending from 0 to 70 km is used to study the sensitivity of surface temperature to perturbations in the ozone profile. Several simulations have been performed for 0₃ reductions in various altitude ranges. For each case, the resulting perturbation in the thermal structure is analysed. These calculations have been repeated for several types of cloud layers with different opacities and altitudes. It is shown that the sensitivity of the surface temperature to ozone changes is dependent on the cloudiness assumed. Ozone decreases in the lower atmosphere (0–30 km) cool the surface, since the greenhouse effect is dominant in this region, and the climate sensitivity is enhanced in the presence of a cloud layer. For higher-altitude 0₃ changes (30–70 km), the sign of the surface temperature variation depends on the cloud characteristics. In fact, the latter result is mostly the consequence of the different equilibrium temperature profiles corresponding to the various types of cloudiness. When high stratospheric ozone is reduced, positive and negative surface temperature changes of several tenths of degree are respectively associated with cold and warm climatic conditions.