中国及其周边地区多种水凝物资料的气候态特征比较

对云的水凝物含量进行研究有利于认识云的辐射性质和强迫效应,以及改善模式的预报性能。利用目前几种较为常用的卫星观测资料（ISCCP、MODIS和CloudSat）和再分析资料（CFSR和ERA-Interim）,对中国及其周边地区的多种水凝物变量,包括积分的云水路径、液水路径和冰水路径,以及分层的液态水含量和冰水含量的气候态水平及垂直分布特征进行了比较研究。结果表明,在总的水凝物含量方面,无论是描述整个中国及其周边地区的水平分布特征和主要变化模态,还是不同海陆区域的月变化特点,MODIS、ERA和CFSR三种资料都显示出较高的一致性,而ISCCP的绝对数值和变化幅度与它们均存在一定差异。在液态水含量方面,无论是水平还是垂直分布,ERA-Interim都有最高的数值,作为观测数据的MODIS和ISCCP则显著偏低。对于冰水含量,不同资料间无论是水平和垂直分布形式还是具体数值都存在明显差异。通过分析不同水凝物资料间气候态分布的差异性特征,有利于认识目前常用的几种水凝物资料的“不确定性”程度,从而更好地估计云的辐射效应,以及理解其在气候变化中所扮演的角色。      

Cloud distributions over the coastal Arctic Ocean: surface-based and satellite observations

All-weather Arctic cloud analyses primarily derived from a surface-based hemispheric all-sky imager are compared against ISCCP D-1 cloud amount, type, and phase during the sunlit polar season. Increasing surface temperatures and decreasing ice cover over the past decade have altered heat and moisture fluxes around the Arctic, providing conditions more conducive for cloud generation. Shipboard and ice camp measurements from field experiments conducted over an 8-year period show cloudy skies in 70–95% of the record. Most of these occurrences are stratiform or multi-level, multi-form cloud, increasing in amount with time through the season. Collocated ISCCP retrievals underestimate cloud amount at small solar zenith angles and overestimate at large angles, sometimes by as much as 50%. Satellite assessments of cloud form classify 95% of scenes as having multiple cloud types, the majority of which are mid-level ice cloud and low-level liquid cloud. Despite large discrepancies in diurnal cloud amount, regional averages of ISCCP pixel cloudiness over the length of the experiments agree within ±5% of surface observations.     

Cloud climate investigations in the Nordic region using NOAA AVHRR data

Summary A method to estimate monthly cloud conditions (monthly cloud frequencies) from multispectral satellite imagery is described. The operational cloud classification scheme SCANDIA (the SMHI Cloud ANalysis model using DIgital AVHRR data), based on high resolution imagery from the polar orbiting NOAA-satellites, has been used to produce monthly cloud frequencies for the entire year of 1993 and some additional months in 1991, 1992, 1994 and 1995. Cloud analyses were made for an area covering the Nordic countries with a horizontal resolution of four km. Examples of seasonal, monthly and diurnal variation in cloud conditions are given and an annual mean for 1993 is presented.Comparisons with existing surface observations showed very good agreement for horizontal cloud distributions but approximately 5% smaller cloud amounts were found in the satellite estimations. The most evident problems were encountered in the winter season due to difficulties in identifying low-level cloudiness at very low sun elevations. The underestimation in the summer season was partly fictious and caused by the overestimation of convective cloud cover by surface observers.SCANDIA results were compared to ISCCP (International Satellite Cloud Climatology Project) cloud climatologies for two selected months in 1991 and 1992. ISCCP cloudiness was indicated to be higher, especially during the month with anticyclonic conditions where a cloudiness excess of more than 10% were found. The regional variation of cloud conditions in the area was found to be inadequately described by ISCCP cloud climatologies. An improvement of the horizontal resolution of ISCCP data seems necessary to enable use for regional applications.The SCANDIA model is proposed as a valuable tool for local and regional monitoring of the cloud climatology at high latitudes. More extensive comparisons with ISCCP cloud climatologies are suggested as well as comparisons with modelled cloudiness from atmospheric general circulation models and climate models. Special studies of cloud conditions in the Polar areas are also proposed.With 14 Figures     

Evaluation of Surface Relative Humidity in China from the CRA-40 and Current Reanalyses

Recently, the China Meteorological Administration (CMA) released a new Global Atmospheric Reanalysis (CRA-40) dataset for the period 1979-2018. In this study, surface relative humidity (RH) from CRA-40 and other current reanalyses (e.g., CFSR, ERA5, ERA-Interim, JRA-55, and MERRA-2) is comprehensively evaluated against homogenized observations over China. The results suggest that most reanalyses overestimate the observations by 15％-30％ (absolute difference) over the Tibetan Plateau but underestimate the observations by 5％-10％ over most of northern China. The CRA-40 performs relatively well in describing the long-term change and variance seen in the observed surface RH over China. Most of the reanalyses reproduce the observed surface RH climatology and interannual variations well, while few reanalyses can capture the observed long-term RH trends over China. Among these reanalyses, the CFSR does poorly in describing the interannual changes in the observed RH, especially in Southwest China. An empirical orthogonal function (EOF) analysis also suggests that the CRA-40 performs better than other reanalyses to capture the first two leading EOF modes revealed by the observations. The results of this study are expected to improve understanding of the strengths and weaknesses of the current reanalysis products and thus facilitate their application.     

ISCCP产品和我国地面观测总云量差异

国际卫星云气候计划ISCCP是国际上较权威和客观的云气候性研究计划, 自1983年以来为研究全球云和辐射平衡、云水资源分布等提供了有价值的数据。在分析总云量卫星和地面两种观测方式差异的基础上, 研究了1984-2006年ISCCP D2产品和我国地面观测云资料数据集总云量空间及时间差异。尽管两套资料能一致揭示我国总云量的分布形势和气候变化特征, 但区域性差异仍比较明显。天基、地基数据可对比格点上, 全国平均而言总云量卫星观测结果比地面观测偏高8.46%, 华南地区差异最小、东北地区差异最大。气候变化趋势分析结果表明:近23年我国总云量呈减少趋势, ISCCP D2产品总云量每年减少速度为0.015%, 小于地面观测的总云量每年减少速度 (0.063%); 东北地区总云量缓慢增多, 而青藏高原、西北地区总云量减少。利用卫星和地面资料均以累积距平法检测出1984—2001年总云量减少、2002-2006年总云量显著增加。     

Preliminary Evaluation of Cloud Fraction Simulations by GAMIL2 Using COSP

The Cloud Feedback Model Intercomparisons Project (CFMIP) Observation Simulator Package (COSP) is adopted in the Grid-point Atmospheric Model of IAP LASG (GAMIL2) during CFMIP at Phase II to evaluate the model cloud fractions in a consistent way with satellite observations. The cloud simulation results embedded in the Atmospheric Model Intercomparison Project (AMIP) control experiment are presented using three satellite simulators: International Satellite Cloud Climatology Project (ISCCP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Overall, GAMIL2 can produce horizontal distributions of the low cloud fraction that are similar to the satellite observations, and its similarities to the observations on different levels are shown in Taylor diagrams. The discrepancies among satellite observations are also shown, which should be considered during evaluation.     

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.     

气象卫星高空间分辨率数据的云量计算与检验

该文利用国家卫星气象中心1998—2008年NOAA卫星的存档数据,在再定标和精定位等数据再处理基础上,利用自行研发的云检测算法及云量计算方法,生成空间分辨率为0.01°×0.01°、时间尺度为10年的逐日云量数据,并利用ISCCP和地面观测数据对计算得到的云参数进行数据质量评估。评估结果显示:利用NOAA数据的抽样云检测结果与ISCCP-DX数据相比,晴空像元检测率具有0.70左右的一致性;有云像元检测率具有60%左右的一致性。卫星计算的总云量与地面观测总云量间的月平均相关系数大于0.70。     

基于CloudSat和ISCCP资料的中国及周边地区云量分布的对比分析

利用2006年7月至2007年6月的CloudSat 2B-GEOPROF-LIDAR产品资料和国际卫星云气候计划(ISCCP)D2月平均云量数据, 统计分析了中国及周边地区午间、凌晨年平均总云量的分布特征, 并对两种探测手段得到的年平均总云量及其昼夜变化进行了对比分析。结果表明, ISCCP与CloudSat总云量的分布形势在午间和凌晨均具有较好的一致性, 即相对多云与少云中心的位置吻合较好。但是, 两种资料得到的总云量在量值上存在一定差异。对于整个研究区域而言, 午间ISCCP较CloudSat平均总云量偏低8.9%, 凌晨偏低15.1%。除了中国北方少云带和日本岛以北海域等区域ISCCP云量高于CloudSat云量外, 其他区域ISCCP云量普遍低于CloudSat云量, 且在青藏高原、帕米尔高原、横断山脉、云贵高原以及印度半岛南端和热带部分岛屿等区域尤其显著。进一步对比表明, ISCCP与CloudSat云量差值总体上随CloudSat云量的增大而呈线性变化, 在CloudSat少云区ISCCP略有偏高, 而在多云区则显著偏低。此外, 对云量昼夜变化的对比分析发现, 青藏高原地区ISCCP云量昼夜变化量显著大于CloudSat。     

基于多源卫星资料的中国地区云宏微观特征研究

利用2007—2016年国际卫星云气候计划（International Satellite Cloud Climatology Project,ISCCP）、云和地球辐射能量系统（Clouds and the Earth''s Radiant Energy System,CERES）和中分辨率成像光谱仪（Moderate Resolution Imaging Spectroradiometer,MODIS）卫星反演云产品,对比分析了不同数据反演的中国地区云系结构的宏微观特征,并采用复合评价指标定量评估了不同数据之间时间和空间上的一致性。结果表明：三套卫星数据都能较好地反演出中国地区总云量呈南高北低、东高西低、夏高冬低的分布特征,但通过比较时间技巧（Temporal Skill,S_T）及空间技巧（Spatial Skill,S_S）复合评价指标及其各项分量发现,与MODIS相比,CERES与ISCCP数据反演的总云量时间序列演变特征明显更为一致,且其评分均有南方优于北方,夏季优于冬季的特征;进一步分析不同高度云量的S_T评分发现,CERES和ISCCP两套数据在南方地区的总云量差异主要来自于低云量的绝对偏差,而北方地区的偏差则同时存在于低云和中云;对比分析MODIS和CERES反演的云滴有效半径发现,高云对应的冰相云一致性较高,而中低云相对应的液相云的偏差则有夏季高于冬季的规律。针对夏季液相和冰相云滴粒径及概率密度分析则表明,相比CERES数据,MODIS对夏季液水和冰水粒子的有效半径在不同地区均有不同程度的高估,液（冰）水谱宽则更宽（窄）。     

A Preliminary Evaluation of Global and East Asian Cloud Radiative Effects in Reanalyses

Cloud radiative effects(CREs) at the top of the atmosphere(TOA) in three reanalysis datasets(the European Center for Medium-Range Weather Forecasts Interim Reanalysis(ERA-Interim), the Japanese 55-yr Reanalysis Project(JRA-55), and the Modern-Era Retrospective Analysis for Research and Applications(MERRA)) are evaluated using recent satellite-based observations. The reanalyses can basically capture the spatial pattern of the annual mean shortwave CRE, but the global mean longwave CRE in ERA-Interim and JRA55 is weaker than observed, leading to overestimations of the net CRE. Moreover, distinct CRE biases of the reanalyses occur in the Intertropical Convergence Zone(ITCZ), coastal Pacific and Atlantic regions, and East Asia. Quantitative examination further indicates that the spatial correlations of CREs and TOA upward radiation fluxes with corresponding observations in ERA-Interim are better than in the other two reanalyses. Although MERRA has certain abilities in producing the magnitudes of global mean CREs, its performance in terms of spatial correlations in winter and summer are worse than for the other two reanalyses. The ability of JRA55 in reflecting CREs lies between the other two datasets. Compared to the global mean results, the spatial correlations of shortwave CRE in East Asia decrease and the biases of regional mean CREs increase in the three reanalyses. This implies that, currently, it is still difficult to reproduce East Asian CREs based on these reanalyses. Relatively, ERA-Interim describes the seasonal variation of East Asian CREs well, albeit weaker than observed. The present study also suggests that in-depth exploration of the ability of reanalysis data to describe aspects relating to cloud properties and radiation is needed using more comprehensive observations.     

我国卫星总云量与地面总云量分布的对比分析

根据国际卫星云气候学计划（ISCCP）的总云量和地面总云量资料,分析并讨论了两者在我国的空间分布和单站年变化中的相关性和差异性,对比了两种总云量的全国分布形势。结果指出,在总趋势大致相似的前提下,卫星总云量图能更好地揭示青藏高原、塔克拉玛干沙漠以及沿海地区的云气候特征。最后还就青藏高原总云量分布特点作了分析。     

Underestimation of the Warming Trend over the Tibetan Plateau during 1998–2013 by Global Land Data Assimilation Systems and Atmospheric Reanalyses

Accurate surface air temperature (T2m) data are key to investigating eco-hydrological responses to global warming. Because of sparse in-situ observations, T2m datasets from atmospheric reanalysis or multi-source observation-based land data assimilation system (LDAS) are widely used in research over alpine regions such as the Tibetan Plateau (TP). It has been found that the warming rate of T2m over the TP accelerates during the global warming slowdown period of 1998–2013, which raises the question of whether the reanalysis or LDAS datasets can capture the warming feature. By evaluating two global LDASs, five global atmospheric reanalysis datasets, and a high-resolution dynamical downscaling simulation driven by one of the global reanalysis, we demonstrate that the LDASs and reanalysis datasets underestimate the warming trend over the TP by 27%–86% during 1998–2013. This is mainly caused by the underestimations of the increasing trends of surface downward radiation and nighttime total cloud amount over the southern and northern TP, respectively. Although GLDAS2.0, ERA5, and MERRA2 reduce biases of T2m simulation from their previous versions by 12%-94%, they do not show significant improvements in capturing the warming trend. The WRF dynamical downscaling dataset driven by ERA-Interim shows a great improvement, as it corrects the cooling trend in ERA-Interim to an observation-like warming trend over the southern TP. Our results indicate that more efforts are needed to reasonably simulate the warming features over the TP during the global warming slowdown period, and the WRF dynamical downscaling dataset provides more accurate T2m estimations than its driven global reanalysis dataset ERA-Interim for producing LDAS products over the TP.     

A comparison of AMIP II model cloud layer properties with ISCCP D2 estimates

The cloud amounts and liquid and ice water paths as a function of height in five Atmospheric Model Intercomparison Project (AMIP) II models have been compared to International Satellite Cloud Climatology Project (ISCCP) d2 observations. The model layer data have been transformed to the ISCCP low, mid and height cloud amount and vertically integrated water values. In addition a simple radiative transfer model has been used to transform both model output and ISCCP cloud amount and water contents into top of atmosphere albedos for the low, mid and high cloud fractions. Overall, most models represent moderately well the spatial, seasonal and interannual variability of total cloud albedo, which is largely a function of the total cloud amount. The models also tend to predict moderately well the spatial, seasonal, and interannual variability of cloud fraction, but fail to display the observed spatial, and especially, seasonal and interannual variability in cloud water path. In particular nearly all models have mid and low cloud water path variabilities, which are much larger than those observed in the ISCCP observations. This increased cloud water path variability seems to compensate partially for smaller underestimates of cloud fraction variability in most models. Furthermore, variations in cloud amount and cloud water path are much more often negatively correlated in models than in the observations. A simple estimate of the influence of cloud overlap suggests that monthly mean model cloud layers are less stacked in the vertical in models than in an observational estimate based upon a combination of satellite and ground-based observations.     

A methodology study of the validation of clouds in GCMs using ISCCP satellite observations

The cloudiness fields simulated by a general circulation model and a validation using the International Satellite Cloud Climatology Project (ISCCP) satellite observations are presented. An adapted methodology is developed, in which the issue of the sub-grid scale variability of the cloud fields, and how it may affect the comparison exercise, is considered carefully. In particular different assumptions about the vertical overlap of cloud layers are made, allowing us to reconstruct the cloud distribution inside a model grid column. Carrying out an analysis directly comparable to that of ISCCP then becomes possible. The relevance of this method is demonstrated by its application to the evaluation of the cloud schemes used in Laboratoire de Météoroligie Dynamique (LMD) general circulation model. We compare cloud properties, such as cloud-top height and cloud optical thickness, analysed by ISCCP and simulated by the LMD GCM. The results show that a direct comparison of simulated low cloudiness and that shown from satellites is not possible. They also reveal some model deficiencies concerning the cloud vertical distribution. Some of these features depend little on the cloud overlap assumption and may reveal inadequate parameterisation of the boundary layer mixing or the cloud water precipitation rate. High convective clouds also appear to be too thick.     

Simulations of Hydrological Cycle Changes Between the LGM and the Present Day over China

Based on the International Satellite Cloud Climatology Project (ISCCP) data in 1983–2006,it is found that there is a high value center of high cloud amount over the Tibetan Plateau (TP),while there is a high value center of middle cloud amount over the Sichuan Basin extending to the coastal area of southeastern China along the same latitude,and a low one over the TP.The present day (PD) and Last Glacial Maximum (LGM) climates are simulated by using the NCAR Community Climate Model (CCM3) nested with a regio...     

Surface mean temperature from the observational stations and multiple reanalyses over the Tibetan Plateau

The Tibetan Plateau (TP), also called the “Third pole”, is sensitive to climate change due to extensive areas at high elevation presently dominated by snow and ice. In this study, observed surface temperature trends at 150 stations over the TP during 1979–2018 are analyzed and compared with surface temperatures from multiple reanalyses (NCEP1, NCEP2, ERA-Interim, MERRA, JRA55). Observed warming at the stations has a mean annual rate of 0.46 °C/decade during 1979–2018. Although all reanalyses underestimate observed temperatures (cold bias), most reproduce much of the inter-decadal variations of surface temperature shown in the observations. Absolute errors of mean surface temperature (reanalysis minus observation) are closely correlated with elevation errors, suggesting that parts of the cold bias can be interpreted by elevation errors of reanalysis. After elevation-temperature correction, about half of the cold bias is typically eliminated, more for both ERA-Interim and JRA55. Compared with the observations, corrected NCEP2 surface temperatures still have larger cold biases, and fail to capture the overall warming over the TP. Since the elevation-temperature correction fails to improve trend magnitudes even when a significant proportion of the bias has been removed, this suggests that a more sophisticated modeling of the lapse rate in each reanalysis is required to realistically model warming trends across complex topography.

     

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.     

中国地区云的气候特征分析

文中对比分析了国际卫星云气候计划(ISCC)的D2资料和地面测站云资料,发现二者总云量的整体分布和气候变化都比较一致,但定量上略有差别,尤其是中国北方地区差别较大。ISCCP资料比较齐全,尤其在站点稀少的高原、荒漠地区比其他云资料更有优势。文中分析了中国云的气候特征,发现在华北地区和南海北部的总云量有减少的趋势;四川盆地、长江三角洲等地区存在低云量异常减少的现象;而在天山、帕米尔高原、柴达木盆地、横断山脉等地区存在低云量增加的趋势。文中特别指出西北山区常年维持着的相对稳定的多云带,云层深厚、含水量大,有利于进行进行人工增雨作业。