对苏联札依齐柯夫用梳齿式无线电探空仪测量自由大气铅直运动方法的改进意见

利用梳齿式无线电探空仪测量自由大气铅直运动的时候,需要知道气球和空气间相对铅直速度W_0。为了计算W_0,本文建议采用关系 ρW_0=aρW+b, (i)以代替札依齐柯夫提出的关系 (W_0/ω)=A+B(ρ_0/ρω_) (ii)式中的ρ是空气密度,ω是无线电探空仪风车转速。由于(i)式中的系数a,b比较容易正确的决定,因此能够得到W_0的正确数值。这样就消除了因W_0不正确而引起的计算空气铅直运动速度W的误差。     

NOAA卫星遥感监测不同作物农田土壤湿度模型

根据对新疆几个主要农作物耕种田土壤含水量和土壤温度观测资料，统计分析了土壤含水量与地温的相互关系。结果表明，同样土质条件下（本试验区均为沙壤土），种植不同作物，其土壤湿度大小所响应的地温要素不同，有的与凌晨地温（T08）相关好，有的对中午地温（T14）反应灵敏；有的和地面日温度相关突出，有的则与浅层地温关系好，总体看，土壤湿度与地面日温差（△T＝T14－T08，近似为日较差）相关最佳，其道理众所周知，是土壤的热惯量差异所致。反言之，不同作物田，即使土壤含水量和其它条件都一样，其△T可能不一样，而且变化最敏感的△T所在深度也不同。本文给出了四种农作物生长田里土壤湿度和地温的响应模式，并推论可以用AVHRR辐射温度（亮温）的日差值Tb代替△T，进而提供一种利用NOAA卫星遥感资料监测不同作物区土壤湿度分布的模型。     

西北4省(区)干旱遥感监测方法——以Erads软件为例

介绍了将DVBS系统接收处理得到的NOAA/AVHRR卫星遥感资料,转入Erads软件,在Erads软件中对图像进行校正、拼接,通过建模运算实现干旱遥感监测的方法和监测流程。利用该方法对2006年7月下旬西北4(省)区的地面旱情进行监测,结果表明利用该工作流程,选择合适的干旱遥感模型可以得到监测区域的旱情,旱情监测结果与地面20 cm土壤相对湿度监测的旱情结果较一致。     

斜压大气中尺度扰动的有限振幅对称不稳定

本文通过一个非地转、非静力的Eady模式讨论了斜压粘性流中的非线性对称不稳定。采用具有常值水平和垂直切变的基本场,考虑扰动沿基本气流方向不变,应用摄动方法,得到了非线性情况下扰动振幅的特性方程。结果表明,当δ>0时(δ是进行稳定性分析时所选取的无量纲小参数),振幅|A(T)|存在两个有意义的平衡点|A|_(b1)=0和|A|_(b2)=(-μ_2/μ_1)~(1/2)(μ_1,μ_2是和流体性质、区域大小以及波参数有关的量),|A|_(b1)为不稳定平衡点,|A|_(b2)为稳定平衡点。因此,不论初态如何,终态都趋于稳定平衡点,出现有限振幅现象。当δ<0时,振幅|A(T)|仅有一个有意义的平衡点|A|_(b1)=0,且为稳定平衡点。线性分析所得结果为非线性结果的特例。     

广东干旱时空分布特征

根据土壤水分平衡模拟模型,采用广东省86个气象站1962～2006年逐日气象资料,模拟逐日土壤水分平衡状况,计算逐日土壤有效含水量,参考缺水指数形式,采用整层土壤有效含水量定义逐日干旱动态指数：DI=1-有效含水量／最大有效含水量。     

用(e-t)作单站晴雨预报

我们通过利用罗城站1973年至1985年共13年每日14时的(e—t)数值大小和点绘的曲线变化与晴雨天气实况统计分析,初步找出了如下一些关系和规律。 1、当天14时(e—t)、(e-t)_1、和(e—t)_2均为正值,则次日有雨。 (e—t)为当天14时的水汽压与气温之差;(e-t)_1,为当天14时(e—t)与前一天14时(e—t)之差;(e—t)_2为当天14时(e—t)_1与前一天14时(e—t)_1之差。经统计,13年中14时(e—t)、 (e—t)_1和(e—t)_2均为正值的共有     

欧空局主被动微波土壤水分融合产品 在甘肃省干旱监测中的应用

选取甘肃省为研究区域,利用自动土壤水分观测站(ASMS) 0～10 cm土壤体积含水量数据对ESA CCI_SM(European Space Agency climate change initiative soil moisture)产品进行质量评估,并基于此产品分析长时间序列土壤体积含水量的时空变化特征,在此基础上,进一步构建土壤水分状态指数(soil moisture condition index,SMCI)应用于干旱监测。结果表明:(1) ESA CCI_SM在陇东地区与自动站土壤水分观测值的相关性最好(R=0. 71),其次是陇中、陇南和甘岷地区,共有92%的站点的R通过0. 01显著性检验。(2) ESA CCI_SM产品较好地呈现了西北部土壤湿度较干燥、东南部较湿润的空间分布特征。土壤体积含水量具有明显季节变化,秋季较高,其次是夏季,冬春季较低。(3)基于ESA CCI_SM产品构建的SMCI较好地监测出2002年7—10月伏秋连旱和2009年4—6月春夏连旱的发生发展过程,该数据产品在陇东和陇中雨养农业区的干旱监测应用较好。     

黄土高原降水对土壤含水量和导热率的影响

基于局地降水是引起黄土高原塬区土壤含水量变化的主要原因,利用黄土高原白庙塬区20052010年观测的土壤含水量和降水资料以及2012年夏季观测的土壤温度和含水量资料,分析了土壤含水量、导热率与降水的相关关系,重点分析了10.0,20.0和40.0 cm土壤含水量的蓄积以及20.0 cm土壤含水量与前期总有效降水的响应。结果表明:(1)不同深度土壤含水量的月变化比较一致,其中降水对5.0 cm土壤含水量的正强迫作用最为显著;(2)10.0 cm和40.0 cm土壤含水量年变化存在两个峰值,分别在3 5月和8 10月;(3)土壤含水量和前期总有效降水的拟合效果在夏季最好,二者在20.0 cm土壤层的相关系数达到0.84,高于其他观测层;(4)在试验前期,土壤含水量迅速增加使得土壤导热率明显升高。持续观测发现虽然土壤导热率会随着降水出现波动,但整体的相关性并不高,没有明显规律。     

基于AMSR-E土壤湿度产品的LIS同化试验

由陆面信息系统 (Land Information System, 简称LIS) 通过NOAH陆面过程模型使用集合卡尔曼滤波开展AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) 土壤湿度同化试验,得到2003年中国区域垂直深度为4层、水平空间分辨率为0.25°×0.25°的土壤湿度试验数据。使用农业气象观测站土壤相对湿度和国家生态系统野外科学观测研究站土壤体积含水量对试验结果进行检验,结果表明:同化过程整体上提高了陆面模型的模拟精度,草地生态系统模拟精度高于作物和森林生态系统;有效的同化过程依赖于AMSR-E土壤湿度的准确性;模拟出的土壤湿度空间分布特征与实际相符。同化试验得到的时空相对连续且精度相对准确的土壤湿度数据是气候变化和干旱监测的重要数据基础。     

基于TVDI的西藏地区旱情遥感监测

西藏大部分地区属干旱或重干旱区,干旱发生较为频繁,是影响农牧业生产最严重的灾害之一。文章利用拉萨接收站的中分辨率成像光谱仪(MODIS)资料提取的归一化植被指数(NDVI)和地表温度(ST),构建ST-IND-VI特征空间,依据该特征空间设计的温度植被旱情指数作为旱情指标,找出适合该地区的旱情判别模式,以2005～2008年6～7月同时段西藏地区卫星资料、气象旱情监测结果以及土壤相对湿度观测数据为例,进行旱情对比分析。结果表明,利用温度植被旱情指数(TVDI)法对西藏地区进行夏季干旱动态监测是可行的。     

Variability patterns of Rossby wave source

Rossby waves (RW) propagation due to a local forcing is one of the mechanisms responsible for wave trains configurations known as teleconnections. The term teleconnection refers to anomalies patterns that are correlated in several regions of the world, causing large-scale changes in atmospheric waves patterns and temperature and precipitation regimes. The aim of teleconnections studies is to provide a better understanding of atmospheric variability and their mechanisms of action in order to identify patterns that can be tracked and predicted. The purpose of this study was to characterize seasonal and spatial variability of atmospheric RW sources. The RW source at 200?hPa was calculated for the four seasons with reanalysis data of zonal and meridional wind. In the Northern Hemisphere (NH), the RW sources were located on East Asia, North America, North Atlantic and Pacific. The main RW sources in the Southern Hemisphere (SH) were located over Intertropical, South Pacific, South Atlantic and South Indian Convergence Zones. Extratropical regions were also identified, mainly to the south of Australia. The vortex stretching term (S1) and the advection of absolute vorticity by the divergent wind (S2) were analyzed to discuss the physical mechanisms for RW generation. In the NH, the source at East Asia in DJF changed to a sink in JJA, related to the dominance of S1 term in DJF and S2 term in JJA. In the SH, the vortex stretching term had the dominant contribution for RW source located to the south of Australia. The main forcing for RW sources at east of Australia was the advection of absolute vorticity by divergent flow. Over South America, both terms contributed to the source in DJF. The main modes of RW source variability were discussed by using empirical orthogonal functions analysis. RW variability was characterized by wave trains configurations in both hemispheres over regions of jet streams and storm tracks, associated with favorable and unfavorable areas for RW generation.     

Drought modes in West Africa and how well CORDEX RCMs simulate them

This study presents the spatial-temporal structure of droughts in West Africa and evaluates the capability of CORDEX regional climate models in simulating the droughts. The study characterize droughts with the standardized evapo-transpiration index (SPEI) computed using the monthly rainfall and temperature data from the Climatic Research Unit (CRU) and CORDEX models simulation datasets. To obtain the spatial-temporal structure of the droughts, we applied the principal component analysis on the observed and simulated SPEIs and retained the first four principal factors as the leading drought modes over West Africa. The relationship between the drought modes and atmospheric teleconnections was studied using wavelet coherence analysis, while the ability of the CORDEX models to simulate the drought modes was quantified with correlation analysis. The analysis of the relationship between drought modes and atmospheric teleconnections is based on SPEI from observation dataset (CRU). The study shows that about 60 % of spatial-temporal variability in SPEI over West Africa can be grouped into four drought modes. The first drought mode features drought over east Sahel, the second over west Sahel, the third over the Savanna, and the fourth over the Guinea coast. Each drought mode is linked to sea surface temperature anomalies (SSTAs) over tropical areas of Pacific, Atlantic, and Indian Oceans. Most CORDEX models reproduce at least two of the drought modes, but only two models (REMO and CNRM) reproduce all the four drought modes. REMO and WRF give the best simulation of the seasonal variation of the drought mode over the Sahel in March-May and June-August seasons, while CNRM gives the best simulation of seasonal variation in the drought pattern over the Savanna. Results of this study may guide in selecting appropriate CORDEX models for seasonal prediction of droughts and for downscaling projected impacts of global warming on droughts in West Africa.     

Simulation of rainfall anomalies leading to the 2005 drought in Amazonia using the CLARIS LPB regional climate models

The meteorological characteristics of the drought of 2005 in Amazonia, one of the most severe in the last 100 years were assessed using a suite of seven regional models obtained from the CLARIS LPB project. The models were forced with the ERA-Interim reanalyses as boundary conditions. We used a combination of rainfall and temperature observations and the low-level circulation and evaporation fields from the reanalyses to determine the climatic and meteorological characteristics of this particular drought. The models reproduce in some degree the observed annual cycle of precipitation and the geographical distribution of negative rainfall anomalies during the summer months of 2005. With respect to the evolution of rainfall during 2004–2006, some of the models were able to simulate the negative rainfall departures during early summer of 2005 (December 2004 to February 2005). The interannual variability of rainfall anomalies for both austral summer and fall over northern and southern Amazonia show a large spread among models, with some of them capable of reproducing the 2005 observed negative rainfall departures (four out of seven models in southern Amazonia during DJF). In comparison, all models simulated the observed southern Amazonia negative rainfall and positive air temperature anomalies during the El Nino-related drought in 1998. The spatial structure of the simulated rainfall and temperature anomalies in DJF and MAM 2005 shows biases that are different among models. While some models simulated the observed negative rainfall anomalies over parts of western and southern Amazonia during DJF, others simulated positive rainfall departures over central Amazonia. The simulated circulation patterns indicate a weaker northeasterly flow from the tropical North Atlantic into Amazonia, and reduced flows from southern Amazonia into the La Plata basin in DJF, which is consistent with observations. In general, we can say that in some degree the regional models are able to capture the response to the forcing from the tropical Atlantic during the drought of 2005 in Amazonia. Moreover, extreme climatic conditions in response to anomalous low-level circulation features are also well captured, since the boundary conditions come from reanalysis and the models are largely constrained by the information provided at the boundaries. The analysis of the 2005 drought suggests that when the forcing leading to extreme anomalous conditions is associated with both local and non-local mechanisms (soil moisture feedbacks and remote SST anomalies, respectively) the models are not fully capable of representing these feedbacks and hence, the associated anomalies. The reason may be a deficient reproduction of the land–atmosphere interactions.     

Assessing Drought Conditions in Cloudy Regions Using Reconstructed Land Surface Temperature

Temperature vegetation dryness index (TVDI) in a triangular or trapezoidal feature space can be calculated from the land surface temperature (LST) and normalized difference vegetation index (NDVI), and has been widely applied to regional drought monitoring. However, thermal infrared sensors cannot penetrate clouds to detect surface information of sub-cloud pixels. In cloudy areas, LST data include a large number of cloudy pixels, seriously degrading the spatial and temporal continuity of drought monitoring. In this paper, the Remotely Sensed Daily Land Surface Temperature Reconstruction model (RSDAST) is combined with the LST reconstructed (RLST) by the RSDAST and applied to drought monitoring in a cloudy area. The drought monitoring capability of the reconstructed temperature vegetation drought index (RTVDI) under cloudy conditions is evaluated by comparing the correlation between land surface observations for soil moisture and the TVDI before and after surface temperature reconstruction. Results show that the effective duration and area of the RTVDI in the study area were larger than those of the original TVDI (OTVDI) in 2011. In addition, RLST/NDVI scatter plots cover a wide range of values, with the fitted dry-wet boundaries more representative of real soil moisture conditions. Under continuously cloudy conditions, the OTVDI inverted from the original LST (OLST) loses its drought monitoring capability, whereas RTVDI can completely and accurately reconstruct surface moisture conditions across the entire study area. The correlation between TVDI and soil moisture is stronger for RTVDI (R = −0.45) than that for OTVDI (R = −0.33). In terms of the spatial and temporal distributions, the R value for correlation between RTVDI and soil moisture was higher than that for OTVDI. Hence, in continuously cloudy areas, RTVDI not only expands drought monitoring capability in time and space, but also improves the accuracy of surface soil moisture monitoring and enhances the applicability and reliability of thermal infrared data under extreme conditions.     

Future pattern of Asian drought under global warming scenario

This study investigates the effect of global warming on drought patterns over Asia at the end of the twenty-first century by a multi-model ensemble method based on daily precipitation data of 15 coupled climate models simulations under SRES A1B scenario, thereby assessing the consistency of responses among different models. The projected precipitation climatology was translated into the change in drought climatology using the effective drought index. The results of the models were consistent in that they project an increase in the mean and the standard deviation of precipitation over most of Asia, and the increase was considerably greater in higher latitude areas. Therefore, it is expected that in future, drought over most of Asia will occur less frequently with weaker intensity and shorter duration than those prevalent currently. However, two special regions were detected. One was the Asian monsoon regions (AMRs: South Asia and East Asia), which showed a greater increase in the standard deviation of precipitation than the mean precipitation, with an amplified seasonal precipitation cycle. As a result, part of the AMRs exhibited slight increases in drought properties such as frequency and intensity. The other region was West Asia. The region showed decreased mean precipitation, especially in its northern part (Syria and its vicinity), and more frequent droughts were projected for this region with enhanced drought intensity and lengthened drought duration. The worsening trends in drought patterns over both regions were more significant in extreme drought, the likelihood of which is relatively higher in summer in West Asia and from spring to summer in the AMRs.     

HAZE-TO-FOG TRANSFORMATION DURING A LONG LASTING, LOW VISIBILITY EPISODE IN NANJING

Haze-to-fog transformation during a long lasting, low visibility episode was examined using the observations from a comprehensive field campaign conducted in Nanjing, China during 4-9 December 2013. In this episode, haze was transformed into fog and the fog lasted for dozens of hours. The impacts of meteorological factors such as wind, temperature (T) and relative humidity (RH) on haze, transition and fog during this episode were investigated. Results revealed significant differences between haze and fog days, due to their different formation mechanisms. Comparison was made for boundary-layer conditions during hazy days, haze-to-fog days and foggy days. Distributions of wind speed and wind direction as well as synoptic weather conditions around Nanjing had determinative impacts on the occurrences and characteristics of haze and fog. Weakened southerly wind in southern Nanjing resulted in high concentration of pollutants, and haze events occurred frequently during the study period. The wind speed was less than 1 m s-1 in the haze event, which resulted in a stable atmospheric condition and weak dispersion of the pollutants. The height of the temperature inversion was about 400 m during the period. The inversion intensity was weak and the temperature-difference was 4°C km-1 or less in haze, while the inversion was stronger, and temperature-difference was about 6°C km-1, approaching the inversion layer intensity in the fog event. Haze event is strongly influenced by ambient RH. RH values increased, which resulted in haze days evidently increased, suggesting that an increasing fraction of haze events be caused by hygroscopic growth of aerosols, rather than simply by high aerosol loading. When RH was above 90%, haze aerosols started to be transformed from haze to fog. This study calls for more efforts to control emissions to prevent haze events in the region.     

How well do the current state-of-the-art CMIP5 models characterise the climatology of the East Asian winter monsoon?

Previous studies have revealed some common biases in coupled general circulation model’s simulations of the East Asian (EA) winter monsoon (EAWM), including colder surface air temperature and more winter precipitation over the EA region. In this study, we examined 41 fully coupled atmosphere–ocean models from fifth phase of the Coupled Model Intercomparison Project (CMIP5), which will be widely used in the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC), and address whether the current state-of-the-art CMIP5 models can characterise the climatology of the East Asian winter monsoon. We also compared the results with the models from third phase of CMIP, which was extensively used in the fourth assessment report of the IPCC. The results show that the cold surface air temperature (SAT) bias is lessened and the precipitation amount decreased with the current CMIP5 models. Moreover, the CMIP5 models performbetter at predicting surface winds and high-level jet streams than the CMIP3 models. Moreover, CMIP5 models show more model consistency in most EAWM parameters, and the interannual variability of the SAT is closer to the observations. We also examined the change in the radiation energy budget in the CMIP5 models and compared with CMIP3 models. Although the improvements are significant, deficiencies still exist in the simulation of the EAWM, e.g., the stronger EA major trough and the stronger zonal sea level pressure gradient.     

近60年华北春季干旱特征及其与北大西洋海表温度的关系

利用观测资料统计分析和CAM5.3数值模拟相结合的方法,基于标准化降水蒸散指数(Standardized Precipitation Evapotranspiration Index, SPEI),分析了1955—2018年华北地区春季干旱特征,并重点探讨了对北大西洋产生的影响。华北春季干旱的主要空间分布型为全区一致型,近60 a春季华北存在22 a偏旱年和14 a偏涝年。华北春季偏旱年主要大气环流特征是大陆暖高压增强、高空西风急流减弱以及华北位于下沉运动区中。观测分析和数值模拟结果均表明,春季北大西洋海温偏暖容易导致华北地区发生干旱。当春季北大西洋偏暖,其上空高度场被抬升,激发出一条自北大西洋经欧亚大陆至华北地区的"+-+"的波列,其波列中心分别位于北大西洋、欧洲大陆-西亚和西北-华北地区上空,这条波列最终导致了西北-华北上空大陆高压增强,华北位于高压底部,上空高度场抬升,西风急流减弱,引发下沉运动,导致空气绝热增温。同时,西风急流减弱导致西南暖湿气流减弱,水汽不易到达华北地区,不利于降水产生,高温少雨有利于干旱发生;当北大西洋偏冷时,波列中心发生了"翻转",由"+-+"转变为"-+-",此时大陆高压减弱,西风急流增强,不利于干旱发生。     

Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River,Cambodia

Cambodia is one of the most vulnerable countries to climate change impacts such as floods and droughts. Study of future climate change and drought conditions in the upper Siem Reap River catchment is vital because this river plays a crucial role in maintaining the Angkor Temple Complex and livelihood of the local population since 12th century. The resolution of climate data from Global Circulation Models (GCM) is too coarse to employ effectively at the watershed scale, and therefore downscaling of the dataset is required. Artificial neural network (ANN) and Statistical Downscaling Model (SDSM) models were applied in this study to downscale precipitation and temperatures from three Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5 scenarios) from Global Climate Model data of the Canadian Earth System Model (CanESM2) on a daily and monthly basis. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were adopted to develop criteria for dry and wet conditions in the catchment. Trend detection of climate parameters and drought indices were assessed using the Mann-Kendall test. It was observed that the ANN and SDSM models performed well in downscaling monthly precipitation and temperature, as well as daily temperature, but not daily precipitation. Every scenario indicated that there would be significant warming and decreasing precipitation which contribute to mild drought. The results of this study provide valuable information for decision makers since climate change may potentially impact future water supply of the Angkor Temple Complex (a World Heritage Site).     

Indicators of Climate Change for the Russian Federation

Observed climate changes over the Russian Federation (RF) territory are considered. Several indicators based on monthly mean temperature and precipitation station data are used to quantify regional climate changes. Some of these are the components of two aggregated indices of climate change, suggested by Karl et al. (1996): the Climate Extremes Index (CEI) and the Greenhouse Climate Response Index (GCRI). For the RF territory as a whole, and for its western part, the "Russian Permafrost Free (RPF) territory" in particular, changes in surface air temperature are investigated, together with changes in precipitation and drought indices, and also the fraction of the Russian territory experiencing climatic anomalies below and/or above certain specified percentiles. Composite indices CEI-3 and GCRI-3 based on three parameters (air temperature, precipitation and drought indices) are examined, as well as the Climate Anomaly Index (CAI), known in Russia as Bagrov's coefficient of "anomality".It is shown, that over the area of the RPF as a whole, air temperature and the occurrence of drought has increased somewhat during the 20th century, while precipitation has decreased; these changes were non-uniform in space. The linear trend accounts for only a small fraction of the total variability, but the role of climate variations on decadal scales seems more substantial. The CEI, determined as the percentage of the area experiencing extreme anomalies (with a 10% or less frequency of occurrence) of either sign, increased for mean annual temperature, decreased for total precipitation and increased slightly for the occurrence of drought conditions; the aggregated index based on all three of these quantities increased slightly. There was also an increase in the GCRI-3 index, which is indicative of an agreement between the observed climate changes and the changes owing to the greenhouse effect as predicted by climatic models.The observed climate changes are too small to enable us confidently to reject a hypothesis that they are a reflection of the natural variability of climatic parameters within the context of a stationary climate. However, there is no doubt about the reality and importance of the observed changes.