南极探空与两套再分析资料的对比分析

基于南极18个站点探空气象观测数据对欧洲中期天气预报中心的再分析数据(ERA-Interim)和美国国家环境预报中心的再分析数据(NECP)在南极地区高层大气的适用性进行验证。结果表明:在南极上空,随着高度抬升,探空气象观测数据与两套再分析数据中四个气象要素的差值均逐渐变大,再分析数据数值愈加偏离实际观测数值。两套再分析数据的位势高度和温度与探空观测数据偏差较小;风向则和探空观测数据相差甚远;两套再分析数据的风速与探空观测数据在300 hPa偏差较大。在季节变化中,南极的春季,再分析数据中的位势高度和温度与探空观测数据相差较大,在其他季节相差相对较小。再分析数据中的风速与探空观测数据在南极的夏季相差较小。再分析数据中的风向与探空观测数据存在较大偏差,且差值没有明显的季节变化。尽管两套再分析数据都存在很大偏差,但ERA-Interim数据整体上优于NCEP数据。对比分析也表明,采用这些再分析资料作为初始条件和边界条件驱动南极区域大气模式将带来较大的误差。未来需要加强南极探空观测,改进再分析资料同化和数值模拟系统。     

A comparative analysis of satellite-observed visible reflectance and 37 GHz polarization difference to assess land surface change over the Sahel zone, 1982–1986

Applicability of visible reflectance to monitor land surface change particularly for arid and semi-arid regions has been studied fairly extensively. Visible reflectance over the Sahel zone from January 1982 to December 1986 has been derived from observations by the advanced very high resolution radiometer (AVHRR) on board the NOAA-7 and NOAA-9 satellites and compared against concurrent observations of 37 GHz polarization difference by the scanning multichannel microwave radiometer (SMMR) on board the Nimbus-7 satellite. Analysis of radiative transfer models suggested a high correlation to exist between these two sets of observations, and the observed spatial and temporal patterns of these data sets did show an overall high correlation. Land surface change resulting from the 1984 drought affected both of these data sets, but not in identical fashion. The present study suggests that potentially new information about physical and biophysical characteristics of the surface could be obtained by synergistic use of these two data sets.     

气象信息科学视算环境及其若干问题

多维动态气象数据的科学视算环境通过多视角的图形、图像表达方式 ,能够直接、准确地展示复杂多样的天气过程及其时空演变 ,辅助解释人员和预报人员形成天气系统的四维空间 /时间结构 ,已成为天气系统分析的重要工具。文中首先讨论了描述天气系统和天气过程的常用图形、图像表达方式 ,然后通过若干典型天气系统数值模拟结果的示例分析 ,介绍了目前气象信息科学视算环境的主要功能 ,最后结合当前的应用状况和气象科学发展的需求 ,讨论了气象信息科学视算环境中的若干问题及其解决方案 ,并展望了未来气象信息科学视算环境的发展前景。     

大气再分析资料中潜在可预报性的特征及其差异

利用1957年9月—2002年8月ECMWF和NCEP/NCAR月平均再分析资料,分别讨论了冬季和夏季SLP(sea level pressure,海平面气压)、500hPa高度、200hPa纬向风和850hPa经向风年际变率的潜在可预报性特征。结果表明:热带地区的潜在可预报性较高,尤其是赤道中东太平洋地区,而中高纬地区的潜在可预报性则较低。比较两套资料潜在可预报性的异同后发现:南半球的差异均明显大于北半球,特别是南极地区;低层变量的差异均大于中高层变量;东亚大陆在冬、夏季均具有一定的潜在可预报性;冬季各变量均表现出东亚冬季风具有较高的年际变率潜在可预报性,且两套资料的差异较小;500hPa位势高度表现的东亚夏季风潜在可预报性在两套资料中较一致,而低层变量(SLP和850hPa经向风)表现的东亚夏季风年际变率潜在可预报性在两套资料中存在较大差异。     

几套全球SST资料集的对比分析与拼接

介绍了最常用的几套海面温度资料集的来源,优点与不足;先用经验正交函数分析法夺其时、空特征分别进行对比、分析,筛选出最相近的两套ＳＳＴ资料集,再对这两套ＳＳＴ资料集的重叠部分（１９８２年１月～１９９７年１２月）以及该部分的Ｎｉｎｏ区海面温度指进行对比,分析,认为这两套海面温度资料集差别不大,可以直接拼接,以满足实时业务的需求。     

Effects of atmospheric boundary layer mixing representations on vertical distribution of passive and reactive tracers

Summary A one-dimensional chemistry-boundary layer model was used to study the effects of differing representations of atmospheric boundary layer (ABL) processes on simulated concentrations of passive and chemically reactive tracers. Two local- and two nonlocal-closure ABL schemes were used to perform numerical simulations during convective conditions in the ABL. Observational data from the First International Statellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) were used to provide initial meteorological conditions while representative chemical concentrations and surface and elevated emission rates were used to provide initial chemical conditions and chemical sources to the one-dimensional model. Two sets of numerical simulations were performed using the four ABL schemes. The first set simulated bottom-to-top mixing characteristics, and the second set simulated top-to-bottom mixing characteristics. Model simulations were performed for 12h starting from 0700LT 11 July 1987.Our analysis indicate that the simulated concentrations of both passive and reactive chemical species were sensitive to the type of ABL scheme used to represent turbulent mixing processes. Characteristic features associated with each scheme (e.g., growth and intensity of mixing in the ABL) contributed to the differences among the simulated species concentrations. For some of the chemical species these differences were large, particularly in the surface layer and in the interfacial layers of the ABL. In turn, differences caused by the differing mixing representations resulted in different chemical production/destruction rates. As a consequence, the simulated species concentrations differed among the simulations. We also found that chemical species concentrations were more sensitive to the type of ABL scheme in the bottom-to-top mixing simulations than in the top-to-bottom simulations.With 10 Figures     

Machine Learning of Weather Forecasting Rules from Large Meteorological Data Bases

Discovery of useful forecasting rules from observational weather data is an outstanding interesting topic.The traditional methods of acquiring forecasting knowledge are manual analysis and investigation performed by human scientists.This paper presents the experimental results of an automatic machine learning system which derives forecasting rules from real observational data.We tested the system on the two large real data sets from the areas of centra! China and Victoria of Australia.The experimental results show that the forecasting rules discovered by the system are very competitive to human experts.The forecasting accuracy rates are 86.4% and 78% of the two data sets respectively     

V7版和V8版TOMS大气臭氧资料比较分析

目前使用的TOMS(Total Ozone Mapping Spectrometer)大气臭氧资料大多为V7版本和V8版本,文章利用1978年11月至2001年12月的版本7和版本8算法反演得到的TOMS臭氧资料,比较分析了两个版本资料之间差异的时空分布特性。结果表明,TOMS公布的V8版本资料与V7版本资料虽然有较好的相关性,但是在数值上存在明显的时空分布差异,尤其在极区更为明显。     

LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project

The datasets of two Ocean Model Intercomparison Project(OMIP)simulation experiments from the LASG/IAP Climate Ocean Model,version 3(LICOM3),forced by two different sets of atmospheric surface data,are described in this paper.The experiment forced by CORE-II(Co-ordinated Ocean–Ice Reference Experiments,Phase II)data(1948–2009)is called OMIP1,and that forced by JRA55-do(surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis)data(1958–2018)is called OMIP2.First,the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described.Second,the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation.We find that the mean states,interannual variabilities,and long-term linear trends can be reproduced well by the two experiments.The differences between the two datasets are also discussed.Finally,the usage of these data is described.These datasets are helpful toward understanding the origin system bias of the fully coupled model.     

四川区域融合降水产品的质量评估

本文利用四川省156个国家地面气象观测自动站2018年逐小时降水资料,从降水产品与观测值的对比、降水产品误差空间特征、降水产品误差月变化、不同降水量级的误差特征等方面,对国家气象信息中心研制的中国区域1h、0.05° × 0.05°分辨率的地面-卫星-雷达三源融合实时降水产品和地面-卫星二源融合快速降水产品在四川区域的适用性进行对比评估。研究结果表明,两套融合降水产品能较好的反映四川区域年内小时降水的时空变化特征,与站点观测降水相比,两套融合降水产品均存在一定程度的低估,且随着降水量级的增大,均方根误差值也相应增大。两套融合降水产品相比,融合了雷达资料的三源融合降水产品各项指标均优于二源融合降水产品,数据质量更高。      

The treatment of atmospheric dispersion data in the presence of noise and baseline drift

Recently large quantities of data from many different field experiments have become available to facilitate the examination of various proposed models of atmospheric dispersion. However, these data sets are invariably corrupted by some form of random noise and, also, significant baseline drift is often recorded. Consequently, these problems require careful consideration and treatment before the data can be used in model testing. In many papers, the noise is simply treated by thresholding but this is unacceptable since many valid readings are discarded. This paper examines the performance of two different noise removal methods that are more soundly based, both physically and mathematically. The first is a Wiener filter with certain modifications, and the second is a maximum entropy inversion technique. A comparison of the results of applying these methods is presented, with the emphasis on the practical treatment of the numerical and computational problems that arise. The problem of baseline drift is treated initially by applying a number of subjective fits. Subsequently the noise removal methods are applied. In general, it is found that the maximum entropy method performs better than the Wiener filter for the data sets examined here.     

A multi-data set comparison of the vertical structure of temperature variability and change over the Arctic during the past 100?years

We compare the daily, interannual, and decadal variability and trends in the thermal structure of the Arctic troposphere using eight observation-based, vertically resolved data sets, four of which have data prior to 1948. Comparisons on the daily scale between historical reanalysis data and historical upper-air observations were performed for Svalbard for the cold winters 1911/1912 and 1988/1989, the warm winters 1944/1945 and 2005/2006, and the International Geophysical Year 1957/1958. Excellent agreement is found at mid-tropospheric levels. Near the ground and at the tropopause level, however, systematic differences are identified. On the interannual time scale, the correlations between all data sets are high, but there are systematic biases in terms of absolute values as well as discrepancies in the magnitude of the variability. The causes of these differences are discussed. While none of the data sets individually may be suitable for trend analysis, consistent features can be identified from analyzing all data sets together. To illustrate this, we examine trends and 20-year averages for those regions and seasons that exhibit large sea-ice changes and have enough data for comparison. In the summertime Pacific Arctic and the autumn eastern Canadian Arctic, the lower tropospheric temperature anomalies for the recent two decades are higher than in any previous 20-year period. In contrast, mid-tropospheric temperatures of the European Arctic in the wintertime of the 1920s and 1930s may have reached values as high as those of the late 20th and early 21st centuries.     

Knowledge extraction from large climatological data sets using a genome-wide analysis approach: application to the 2005 and 2010 Amazon droughts

Today, the volume of data generated in almost all disciplines, particularly in meteorology and climate science, is dramatically increasing. Among the challenges generated by this “data deluge” is the development of efficient knowledge discovery strategies. Here, we show that statistical and computational tools used to analyze large data sets of genome-wide studies can be fruitfully applied to a climatic context. Although not as powerful as some techniques already in use by climatologists, these tools are simple and robust, and can easily be adapted to detect early warning signals for extreme events like droughts or be used to filter large data sets before applying other more advanced and computationally expensive methods. We test this approach in our investigation of the causes of the Amazon droughts of 2005 and 2010. Our results highlight the major role played in these extreme events by the warming of the sea’s surface temperature, mainly in the tropical North Atlantic. Our findings are in agreement with several analyses published in the literature. The main message we convey is that free and open-source data mining and visualization techniques routinely used in genetic studies can be useful in helping scientists to extract knowledge from large climatic data sets, particularly in regions of the world that are vulnerable to climate change but where the availability of technical expertise is critically scarce.     

Correlates of vulnerability to climate-induced distribution changes in European avifauna: habitat, migration and endemism

Accelerated climatic change will alter species’ distributions substantially by the end of the 21st Century and studies modeling distribution change using Climatic Envelope Modeling (CEM) are increasingly crucial for understanding long-term biotic implications of climate change. However, most CEM studies generate either all-species means, which are of limited practical use, or copious species-specific predictions that make it hard to draw general conclusions about those groups most vulnerable. Intermediate analyses that are half way between these two extremes are necessary to establish the relative vulnerability of species to change based on factors that can be related directly to policy and practice, including habitat associations and ecological traits such as endemism and migration status. Here we use species-specific CEM data to analyse changes in geographical distribution, range size, and overlap between current and potential ranges, for all 431 bird species breeding regularly in Europe. Future range sizes are predicted to be 80 % of current range sizes, with an average overlap of 39 %. However, we show that change varies significantly according to habitat, current range size, and endemism status, with no differences according to migration status. Coastal, wetland and upland birds will be significantly worse off under CEM scenarios than birds associated with woodland, farmland and heathland, while urban birds and those using multiple habitats doing best. Birds with small ranges show more severe, and spatially more complex, distribution shifts. The identification of species groups most vulnerable to climate change means that CEM predictions can now be used to inform policy and management, especially where initiatives are based on species grouped according to such variables or where habitat-specific policies are in place.     

Sensitivity of the Earth’s radiation budget to interannual variations in cloud amount

 Using two pairs of coincident long-term satellite derived cloud and earth radiation budget data sets (Nimbus-7 ERB/Nimbus-7 Cloud Climatology and ERBE Scanner/ISCCP-C2), estimates are made of the sensitivity of the top of the atmosphere radiation budget to interannual variations in the total cloud amount. Both sets of analyses indicate that the largest net warming due to interannual cloud cover changes occurs over desert regions, while the largest net cooling occurs in areas of persistent marine stratiform cloud. There is generally a large amount of cancellation between the large shortwave cooling and longwave warming effects in tropical convection regions. However, the Nimbus-7 analysis identifies an area of net warming in the tropical eastern Pacific Ocean which is shown to be associated with the 1982–83 ENSO event. In the zonal mean the Nimbus-7 data sets indicate that interannual cloud cover changes lead to a net warming at low latitudes and net cooling polewards of 25° in both hemispheres. In contrast, the analysis of the ERBE and ISCCP data sets indicates net cooling everywhere except for the Northern Hemisphere equatorwards of 20 °N. For the spatial average between 60 °N and 60 °S the ratio of the shortwave and longwave effects is 0.94 in the Nimbus-7 analysis (i.e. clouds cause a small net warming) and 1.21 in the ERBE-ISCCP analysis (i.e. a net cooling). Given their improved spatial and temporal sampling the analysis using the ERBE and ISCCP data sets should be the more reliable. However, the large differences between the two analyses still raises some issues concerning the confidence with which the sign of the effect of clouds on the radiation budget at these time scales is currently known. Received: 24 October 1995 / Accepted: 8 August 1996     

Land-use and climate change within assessments of biodiversity change: A review

Projected changes in biodiversity are likely inadequately estimated when climate and land-use change effects are examined in isolation. A review of studies of the effects of these drivers singly and in combination highlights little discussed complexities in revising these estimates. In addition to considering interactions, different characterisations of climate change, land-use change and biodiversity greatly influence estimates. Habitat loss leading to decreased species richness is the most common land-use change and biodiversity relationship considered with less attention being given to other land-use changes (e.g. other conversions, fragmentation, different management intensities) and biodiversity characterisations and responses (e.g. selected groups of species, increased species richness). Characterisations of more complex relationships between climate change, land-use change and biodiversity however are currently limited by a lack of process understanding, data availability and inherent scenarios uncertainties.     

黄海西部海洋工程风、浪设计参数的分析和计算

使用黄海西部站点观测、船舶记录及海洋调查资料，建立计算海面风速的转换关系式。综合转换风速、台风报告或台风风场计算风速，分七个区块建立年最大风速序列；藉助极值Ⅰ型概率分布，推导了各区不同重现期的大风极值。开发使用美国SOWM波浪谱模式产品，推导了二个格点上不同重现期的波高极值，该值与近海波浪计算值一起组成合理的极端波高分布。     

The Statistical Prediction Of Offshore Winds From Land-Based Data For Wind-Energy Applications

Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and forverification. As a first step, the two datasets were separated into ninepercentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes. The binning procedure ensured that both training and test sets fairly represented the overall data distribution.To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random selection from the same data, but maintaining the (approximate) 70-30 split in each bin. This procedure served to ensure that conclusions were not based on a single randomly-selected case. Two statistical methods are employed:multiple linear regression (MLR), and Classification and Regression Trees(CART). MLR produces excellent results using only land-based predictors.The CART results are similar to those from MLR, and tend to be slightly better.Retired     

Interdecadal modulation of the relationship between ENSO,IPO and precipitation: insights from tree rings in Australia

Australian climate-proxy reconstructions based on tree rings from tropical and subtropical forests have not been achieved so far due to the rarity of species producing anatomically distinct annual growth rings. Our study identifies the Australian Red Cedar (Toona ciliata) as one of the most promising tree species for tree-ring research in Australasia because this species exhibits distinct annual tree rings, a prerequisite for high quality tropical dendroclimatology. Based on these preliminary studies, we were able, for the first time in subtropical and tropical Australia, to develop a statistically robust, precisely dated and annually resolved chronology back to AD1854. We show that the variability in ring widths of T. ciliata is mainly dependent on annual precipitation. The developed proxy data series contains both high- and low-frequency climate signals which can be associated with the El Niño Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO). A comparison of different data sets (Brisbane precipitation, tree rings, coral luminescence record from the Great Barrier Reef, ENSO and IPO) revealed non-stationary correlation patterns throughout the twentieth century but little instability between the new tree-ring chronology and Brisbane precipitation.