Significant Difference in Dimming Magnitude Between Urban and Rural Regions in China and Its Implication for Surface Temperature

The climatology and long term trends of sunshine duration (SSD), total cloud amount (TCC) and surface temperature are studied based on surface observations at 84 stations across China from 1961 to 2009. These stations were classified into metropolis, large city, small city and rural station based on their populations and specific station locations. Difference in SSD and its implication for surface temperature among four station categories are analyzed. Different SSD decreasing rates among four station categories were found. The maximum decreasing rate occurred at metropolis stations (-89.2 h per decade) and the minimum rate occurred at rural station (-54.1 h per decade). TCC also showed a negative trend. The correlation coefficients between decadal variability of SSD and TCC were significantly positive, which implied that the dimming during this period was apparently not explained by TCC. Among all station categories, the maximum temperatures (Tmax) showed a similar positive trend, however, the minimum temperatures (Tmin) increased much faster at urban stations than at rural stations. This suggested that the faster decline of SSD at urban stations could partly dampen the effect of urban heat island on Tmax.     

1980—2009年中国大陆中东部气溶胶-云-辐射变化及其关系

基于中国大陆中东部484个气象站1980—2009年日照时数、总云量、能见度数据,按区域分析了地表太阳辐射长期变化特征及云量和气溶胶对辐射变化的可能影响,深入理解地表太阳辐射变化趋势成因。中国大陆中东部地区地表太阳辐射呈下降趋势（-0.7 Wm-2/10a）。从季节变化分析,下降趋势主要集中于夏季（-2.7 Wm-2/10a）;从区域分析,下降幅度最大的为华北地区（-3.9 Wm-2/10a）,该区云量不明显上升、能见度明显下降,且地表太阳辐射与云量低频部分相关系数（年代际变率）约-0.25,与气溶胶低频部分相关系数达-0.87,以此推测华北地区地表辐射的长期变化是气溶胶与总云量共同作用的结果。华南地区春季辐射上升（4.2 Wm-2/10a）则归因于总云量的下降（-2.1%/10a）。地表太阳辐射与总云量高频部分的相关系数（年际变率）达到-0.85以上,表明地表太阳辐射的年际短期变率主要贡献是来自于总云量的年际变化。     

阿勒泰地区气温日较差的气候变化特征

利用线性趋势法对1961-2008年阿勒泰地区7个气象站点气温日较差进行趋势研究,并根据各因子趋势值,应用相关统计法分析了影响气温日较差呈减小趋势的因子。结果表明：阿勒泰地区四季日较差呈现显著减小趋势,其中冬季最显著,秋季变化最弱。各季节最低气温上升趋势最明显,而最高气温上升趋势较弱。阿勒泰地区与月平均气温日较差相关性最强的因子是日照时数,呈正相关;其次分别为总云量、降水量和水汽压,都呈负相关。年气温日较差与降水量和水汽压相关性最大。     

Dominant east-west pattern of diurnal temperature range observed across Zambia

Diurnal temperature range (DTR) is an important index for climate because of its statistical relationships to greenhouse gases, urban heat, cloud cover, land use change, and aerosol haze layers. This study examines DTR trends across Zambia for the period 1930–2016 using the latest version of high-resolution monthly data (CRU TS v4.01) from the Climatic Research Unit. Non-parametric trend analyses were extensively employed at different spatial and temporal scales to quantify DTR changes. Taken together, results show a dominant east-west pattern with higher DTR values being observed in the western half of the country. Although there are noticeable differences in the magnitude from one month to the other, this east-west pattern is persistent throughout all the months. It is also found that mean annual DTR is negatively correlated with mean annual cloud cover with a strong and statistically significant coefficient of -0.8 but its correlation with precipitation weakens to -0.5 at the α 0.05. Results from the Mann-Kendall trend test shows marginal increments in DTR during all the seasons and they are all statistically significant at the α 0.05. The observed increments can be attributed to a general decrease in cloud cover over Zambia.     

Influence of Changes in Solar Radiation on Changes of Surface Temperature in China

The long-term trends of total surface solar radiation(SSR),surface diffuse radiation,and surface air temperature were analyzed in this study based on updated 48-yr data from 55 observational stations in China,and then the correlation between SSR and the diurnal temperature range(DTR) was studied.The effect of total solar radiation on surface air temperature in China was investigated on the basis of the above analyses.A strong correlation between SSR and DTR was found for the period 1961-2008 in China.The highest correlation and steepest regression line slope occurred in winter,indicating that the solar radiation effect on DTR was the largest in this season.Clouds and water vapor have strong influences on both SSR and DTR,and hence on their relationship.The largest correlations between SSR and DTR occurred in wintertime in northern China,regardless of all-day(including clear days and cloudy days) or clear-day cases.Our results also showed that radiation arriving at the surface in China decreased significantly during 1961-1989(dimming period),but began to increase during 1990-2008(brightening period),in agreement with previous global studies.The reduction of total SSR offset partially the greenhouse warming during 1961-1989.However,with the increase of SSR after 1990,this offsetting effect vanished;on the contrary,it even made a contribution to the accelerated warming.Nonetheless,the greenhouse warming still played a controlling role because of the increasing of minimum and mean surface temperatures in the whole study period of 1961-2008.We estimated that the greenhouse gases alone may have caused surface temperatures to rise by 0.31-0.46℃(10 yr) 1 during 1961-2008,which is higher than previously estimated.Analysis of the corresponding changes in total solar radiation,diffuse radiation,and total cloud cover indicated that the dimming and brightening phenomena in China were likely attributable to increases in absorptive and scattering aerosols in the atmosphere,respectively.     

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.     

1960~2012年中国地区总云量时空变化及其与气温和水汽的关系

基于我国地区543个地面气象台站观测的总云量、平均气温和相对湿度日均值资料,采用正交经验函数（EOF）、气候倾向率和线性趋势分析等方法,研究了1960~2012年总云量的时空变化特征及其与气温和水汽的关系。结果表明:（1）我国地区总云量呈南多北少的带状分布特征,最大值在四川盆地（82%）。近53年来总云量气候倾向率为-0.8%（10a）-1,趋势系数为-0.68,通过了99.9%的信度检验。（2）总云量季节变化特点明显,夏季最多,春秋季次之,冬季最少,其中春季、夏季和秋季有显著的下降趋势。（3）EOF分解的前两个模态表明总云量不仅具有一致减少的变化特征,还具有明显的区域差异。以此同时,平均气温和相对湿度不论在总体变化趋势、地区差异、还是时间演变上,均与总云量保持较高的一致性,进一步证明总云量的变化与气温和水汽有密切关系。     

Comparison between MODIS-derived Day and Night Cloud Cover and Surface Observations over the North China Plain

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover(TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16%higher than the Synop data, and this value was higher at nighttime(15.58%–16.64%) than daytime(12.74%–14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter(29.53%–31.07%) and smallest in summer(4.46%–6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.     

VARIABILITY OF DIURNAL TEMPERATURE RANGE IN EAST AFRICA DURING 1921–2010

This study investigates the long-term spatiotemporal variability of diurnal temperature range(DTR) in East Africa(EA). The study carries out non-parametric trend analysis of gridded DTR monthly data sourced from Climatic Research Unit(CRU). The DTR exhibits mixed signals in space and time over EA. The DTR correlates negatively with rainfall over EA. Reduction in DTR coincides with the summer season in the northern and southern hemispheres respectively, suggesting the influence of cloud cover on it. There was a non-uniform pattern of DTR changes across the region with time. Lake Victoria basin recorded the highest warming rates. The Indian Ocean coast recorded the least spatiotemporal variability in DTR. A reduction in DTR is evident in the two seasons: hot and cold. The start of the study period; 1921—1930, was the coolest decade in the study period. Most parts of EA recorded negative DTR anomalies in 1961—1970. The overall reduction in DTR throughout the study period highlights the ongoing warming which is a global phenomenon. There remains need for investigating the causation of the observed DTR variability for effective monitoring of the variability in future.     

Spatial dependence of diurnal temperature range trends on precipitation from 1950 to 2004

This paper analyzes the spatial dependence of annual diurnal temperature range (DTR) trends from 1950–2004 on the annual climatology of three variables: precipitation, cloud cover, and leaf area index (LAI), by classifying the global land into various climatic regions based on the climatological annual precipitation. The regional average trends for annual minimum temperature (T _min) and DTR exhibit significant spatial correlations with the climatological values of these three variables, while such correlation for annual maximum temperature (T _max) is very weak. In general, the magnitude of the downward trend of DTR and the warming trend of T _min decreases with increasing precipitation amount, cloud cover, and LAI, i.e., with stronger DTR decreasing trends over drier regions. Such spatial dependence of T _min and DTR trends on the climatological precipitation possibly reflects large-scale effects of increased global greenhouse gases and aerosols (and associated changes in cloudiness, soil moisture, and water vapor) during the later half of the twentieth century.     

Empirical estimation of the monthly-mean daily temperature range

Summary ?This is a sequel to a study of the empirical estimation of the annual mean temperature and its range, at any location on land, based on the historical surface climate record. Here the spatial patterns of the daily temperature range (DTR) and its seasonal variation are examined. The DTR is highest in the subtropical deserts and is less at high latitudes, as well as within 30–150 km from an ocean. It is generally higher in winter (summer) at low (high) latitudes. The coastal DTR reduction is explained by sea breezes, onshore advection, and low-level cloud cover. Even large bodies of water, such as Lake Michigan, affect the near-shore DTR. Elevation does not directly affect the DTR, but valleys tend to have a DTR that is 2–6 K larger than adjacent hills or ridges. The main factor affecting the DTR is the afternoon relative humidity, which is dynamically linked to low-level cloud cover. An empirical relationship between DTR and afternoon relative humidity has an uncertainty of about 1.4 K for monthly-mean values. Received March 6, 2002; revised September 20, 2002; accepted November 3, 2002     

Spatiotemporal Variations of Cloud Amount over the Yangtze River Delta, China

Based on the NOAA's Advanced Very High Resolution Radiometer(AVHRR) Pathfinder Atmospheres Extended(PATMOS-x) monthly mean cloud amount data, variations of annual and seasonal mean cloud amount over the Yangtze River Delta(YRD), China were examined for the period 1982–2006 by using a linear regression analysis. Both total and high-level cloud amounts peak in June and reach minimum in December, mid-level clouds have a peak during winter months and reach a minimum in summer, and lowlevel clouds vary weakly throughout the year with a weak maximum from August to October. For the annual mean cloud amount, a slightly decreasing tendency(–0.6% sky cover per decade) of total cloud amount is observed during the studying period, which is mainly due to the reduction of annual mean high-level cloud amount(–2.2% sky cover per decade). Mid-level clouds occur least(approximately 15% sky cover) and remain invariant, while the low-level cloud amount shows a significant increase during spring(1.5% sky cover per decade) and summer(3.0% sky cover per decade). Further analysis has revealed that the increased low-level clouds during the summer season are mainly impacted by the local environment. For example,compared to the low-level cloud amounts over the adjacent rural areas(e.g., cropland, large water body, and mountain areas covered by forest), those over and around urban agglomerations rise more dramatically.     

Detection and attribution of anthropogenic forcing to diurnal temperature range changes from 1950 to 1999: comparing multi-model simulations with observations

Observations show that the surface diurnal temperature range (DTR) has decreased since 1950s over most global land areas due to a smaller warming in maximum temperatures (T _max) than in minimum temperatures (T _min). This paper analyzes the trends and variability in T _max, T _min, and DTR over land in observations and 48 simulations from 12 global coupled atmosphere-ocean general circulation models for the later half of the 20th century. It uses the modeled changes in surface downward solar and longwave radiation to interpret the modeled temperature changes. When anthropogenic and natural forcings are included, the models generally reproduce observed major features of the warming of T _max and T _min and the reduction of DTR. As expected the greenhouse gases enhanced surface downward longwave radiation (DLW) explains most of the warming of T _max and T _min while decreased surface downward shortwave radiation (DSW) due to increasing aerosols and water vapor contributes most to the decreases in DTR in the models. When only natural forcings are used, none of the observed trends are simulated. The simulated DTR decreases are much smaller than the observed (mainly due to the small simulated T _min trend) but still outside the range of natural internal variability estimated from the models. The much larger observed decrease in DTR suggests the possibility of additional regional effects of anthropogenic forcing that the models can not realistically simulate, likely connected to changes in cloud cover, precipitation, and soil moisture. The small magnitude of the simulated DTR trends may be attributed to the lack of an increasing trend in cloud cover and deficiencies in charactering aerosols and important surface and boundary-layer processes in the models.     

Biases in the diurnal temperature range in Central Europe in an ensemble of regional climate models and their possible causes

The study examines how regional climate models (RCMs) reproduce the diurnal temperature range (DTR) in their control simulations over Central Europe. We evaluate 30-year runs driven by perfect boundary conditions (the ERA40 reanalysis, 1961–1990) and a global climate model (ECHAM5) of an ensemble of RCMs with 25-km resolution from the ENSEMBLES project. The RCMs’ performance is compared against the dataset gridded from a high-density stations network. We find that all RCMs underestimate DTR in all seasons, notwithstanding whether driven by ERA40 or ECHAM5. Underestimation is largest in summer and smallest in winter in most RCMs. The relationship of the models’ errors to indices of atmospheric circulation and cloud cover is discussed to reveal possible causes of the biases. In all seasons and all simulations driven by ERA40 and ECHAM5, underestimation of DTR is larger under anticyclonic circulation and becomes smaller or negligible for cyclonic circulation. In summer and transition seasons, underestimation tends to be largest for the southeast to south flow associated with warm advection, while in winter it does not depend on flow direction. We show that the biases in DTR, which seem common to all examined RCMs, are also related to cloud cover simulation. However, there is no general tendency to overestimate total cloud amount under anticyclonic conditions in the RCMs, which suggests the large negative bias in DTR for anticyclonic circulation cannot be explained by a bias in cloudiness. Errors in simulating heat and moisture fluxes between land surface and atmosphere probably contribute to the biases in DTR as well.     

中国天山区域云量的变化及其与降水的关系

基于1961-2008年天山区域24站云量的逐日资料,使用相关和M原K检验等统计方法,分析中国天山区域云量的时空变化特征及其与降水的关系。结果表明：（1）春季、秋季和冬季,伊犁河谷以北总云量最多,夏季则在中天山和东天山的部分区域最多,低云量在夏季占总云量的比重最大;（2）区域平均总云量在春季和秋季呈减少趋势;低云量在各季节均呈增加趋势,尤其在冬季和夏季;（3）总云量的年代际变化不明显,而低云量自20世纪90年代至今,都处在高值期。（4）低云量在春季、夏季和秋季,均在20世纪90年代,而冬季在2000年左右发生了由少到多的气候突变;总云量未发生明显的气候突变。（5）总云量和低云量均和同期降水有较好的相关性。春季低云量和夏季降水,相关系数可达0.52。     

CMIP6模式对中国气温日较差的模拟能力评估北大核心CSCD

利用CRU_TS v4.04观测数据作为验证,对28个CMIP6(Coupled Model Intercomparison Project 6)模式模拟中国区域内气温日较差(Diurnal Temperature Range,DTR)年际变化、气候平均态变化以及不同区域和不同季节尺度变化的能力进行评估。结果表明:在百年尺度上,CMIP6模式能够反映出年际变化中DTR下降的演变趋势,模式与观测之间的相关系数在0.1~0.7,均方根误差在0.6~1.5,Taylor评分(Taylor Score,TS)在0.2~0.7,MRI-ESM2-0模式与观测之间的相关系数(0.65)最大,均方根误差(0.8)最小,TS(0.67)最高,模拟能力最好;在30年气候平均态尺度上,CMIP6模式符合观测呈现的DTR北方地区高、南方地区低,西部地区高、东部地区低,内陆地区高、沿海地区低,高原地区高、平原盆地地区低的空间分布特征,基本可以再现中国大范围区域内DTR下降的空间分布特征,对不同区域和不同季节DTR变化也有较好的模拟,以EC-Earth3模式的模拟能力最好。然而,单模式存在不同程度的高估或低估DTR变化的现象,多模式中位数集合能够模拟出DTR在年际变化和气候平均态变化中的一些特征,对于春季和冬季的模拟,多模式集合优于单模式模拟。     

IMPACT OF SUMMER WARMING ON DYNAMICS-STATISTICS-COMBINED METHOD TO PREDICT THE SUMMER TEMPERATURE IN CHINA

Based on NCEP/NCAR daily reanalysis data, climate trend rate and other methods are used to quantitatively analyze the change trend of China's summer observed temperature in 1983—2012. Moreover, a dynamics-statistics-combined seasonal forecast method with optimal multi-factor portfolio is applied to analyze the impact of this trend on summer temperature forecast. The results show that: in the three decades, the summer temperature shows a clear upward trend under the condition of global warming, especially over South China, East China, Northeast China and Xinjiang Region, and the trend rate of national average summer temperature was 0.27℃ per decade. However, it is found that the current business model forecast(Coupled Global Climate Model) of National Climate Centre is unable to forecast summer warming trends in China, so that the post-processing forecast effect of dynamics-statistics-combined method is relatively poor. In this study, observed temperatures are processed first by removing linear fitting trend, and then adding it after forecast to offset the deficiency of model forecast indirectly. After test, ACC average value in the latest decade was 0.44 through dynamics-statistics-combined independent sample return forecast. The temporal correlation(TCC) between forecast and observed temperature was significantly improved compared with direct forecast results in most regions, and effectively improved the skill of the dynamics-statistics-combined forecast method in seasonal temperature forecast.     

Current and projected water demand and water availability estimates under climate change scenarios in the Weyib River basin in Bale mountainous area of Southeastern Ethiopia

ENSO has been known to influence the trends of summer warming over Southern Africa. In this work, we used observational and reanalysis data to analyze the relationship between ENSO and maximum surface air temperature (SAT_max) trends during the three epochs created by the ENSO phase shifts around 1977 and 1997 for the period 1960 to 2014. We observed that while ENSO and cloud cover remains the dominant factor controlling SAT_max variability, the first two epochs had the predominant La Niña (El Niño)-like events connected to robust positive (negative) trends in cloud fraction. However, this established relationship reversed in the post-1997 La Niña-like dominated epoch which coincided with a falling cloud cover trend. It is established that this deviation from the previously established link within the previous epochs could be due to the post-1998 era in which SAT_min was suppressed while SAT_max was enhanced. The resulting increase in diurnal temperature range (DTR) could have discouraged the formation of low-level clouds which have relatively more extensive areal coverage and hence allowing more solar energy to reach the surface to boost daytime SAT_max. It is noted that these relationships are more pronounced from December to March.     

Variability and Long-Term Trend of Total Cloud Cover in China Derived from ISCCP, ERA-40, CRU3, and Ground Station Datasets

Total Cloud Cover (TCC) over China determined from four climate datasets including the International Satellite Cloud Climatology Project (ISCCP), the 40-year Re-Analysis Project of the European Centre for Medium-Range Weather Forecasts (ERA-40), Climate Research Unit Time Series 3.0 (CRU3), and ground station datasets are used to show spatial and temporal variation of TCC and their differences. It is demonstrated that the four datasets show similar spatial pattern and seasonal variation. The maximum value is derived from ISCCP. TCC value in North China derived from ERA-40 is 50% larger than that from the station dataset; however, the value is 50% less than that in South China. The annual TCC of ISCCP, ERA-40, and ground station datasets shows a decreasing trend during 1984-2002; however, an increasing trend is derived from CRU3. The results of this study imply remarkable differences of TCC derived from surface and satellite observations as well as model simulations. The potential effects of these differences on cloud climatology and associated climatic issues should be carefully considered.     

Decomposition of Fast and Slow Cloud Responses to Quadrupled CO2 Forcing in BCC–AGCM2.0 over East Asia

In this study, the decomposed fast and slow responses of clouds to an abruptly quadrupled CO₂ concentration (approximately 1139 ppmv) in East Asia (EA) are obtained quantitatively by using a general circulation model, BCC–AGCM2.0. Our results show that in the total response, the total cloud cover (TCC), low cloud cover (LCC), and high cloud cover (HCC) all increased north of 40°N and decreased south of 40°N except in the Tibetan Plateau (TP). The mean changes of the TCC, LCC, and HCC in EA were –0.74%, 0.38%, and –0.38% in the total response, respectively; 1.05%, –0.03%, and 1.63% in the fast response, respectively; and –1.79%, 0.41%, and –2.01% in the slow response, respectively. By comparison, we found that changes in cloud cover were dominated by the slow response in most areas in EA due to the changes in atmospheric temperature, circulation, and water vapor supply together. Overall, the changes in the cloud forcing over EA related to the fast and slow responses were opposite to each other, and the final cloud forcing was dominated by the slow response. The mean net cloud forcing (NCF) in the total response over EA was –1.80 W m^–2, indicating a cooling effect which partially offset the warming effect caused by the quadrupled CO₂. The total responses of NCF in the TP, south China (SC), and northeast China (NE) were –6.74 W m^–2, 6.11 W m^–2, and –7.49 W m^–2, respectively. Thus, the local effects of offsetting or amplifying warming were particularly obvious.