Spatio-temporal regression kriging model of mean daily temperature for Croatia

High resolution gridded mean daily temperature datasets are valuable for research and applications in agronomy, meteorology, hydrology, ecology, and many other disciplines depending on weather or climate. The gridded datasets and the models used for their estimation are being constantly improved as there is always a need for more accurate datasets as well as for datasets with a higher spatial and temporal resolution. We developed a spatio-temporal regression kriging model for Croatia at 1 km spatial resolution by adapting the spatio-temporal regression kriging model developed for global land areas. A geometrical temperature trend, digital elevation model, and topographic wetness index were used as covariates together with measurements from the Croatian national meteorological network for the year 2008. This model performed better than the global model and previously developed models for Croatia, based on MODIS land surface temperature images. The R2 was 97.8% and RMSE was 1.2 °C for leave-one-out and 5-fold cross-validation. The proposed national model still has a high level of uncertainty at higher altitudes leaving it suitable for agricultural areas that are dominant in lower and medium altitudes.     

过去近50年全球变暖纬向平均模

Zonal mean annual temperature trends were estimated using four reanalysis and three analysis grid datasets. The trends over land and for the entire globe were estimated from 1958-2001 and 1979-2007, respectively. Estimates of temperature trends over land from Climate Research Unit (CRU) analysis data indicate more intense warming moving northward, at a rate of about 3.5ºC per century at 65ºN, then declining further to the north. CRU estimates indicated dramatic warming over the latitudes of the Antarctic Peninsula, with a localized cooling trend at 45ºS. A global estimate was conducted by comparing estimates of the reanalysis datasets. Temperature distribution trends of the reanalysis data were similar to those generated by land observations but with large bias in the Polar Regions. The bias could be reduced by comparing these estimates with those from the analysis data at high latitudes. Extreme warming trends were estimated at rates of 2.9ºC-3.5ºC per century in the Arctic and 3.2ºC-4.7ºC per century in the Antarctic for 1958-2001. Surface warming was even more intense in the Northern Hemisphere for 1979-2007, with extreme arctic warming rates ranging from 8.5ºC-8.9ºC per century, as estimated by the analysis and reanalysis datasets. Trends over Antarctica for this period were contradictory, as Japan Meteorological Agency (JMA) reanalysis (JRA-25) indicated a cooling trend at about -7ºC per century, while other reanalysis datasets showed sharp warming over the continent.     

全球地面降水月值历史数据集研制

全球降水历史数据是开展气候、水循环等研究的基础。收集整理全球12个数据源降水历史月值资料,通过站号、站名甄别不同数据源中相同台站,对344个通过相关系数、一致率、均值t检验、方差F检验的台站多源资料进行拼接,尽可能多地融合各套数据产品优势,最终形成全球降水历史月值数据集(CMA Global PrecipitationV1.0, CGP)。数据集重点解决当前国际数据产品在东亚地区站点稀少、同时应用多套数据应用门槛较高等问题。数据集收录3.1万个台站共计1.87×107组月降水记录, 4152个台站序列长度达百年。与美国大气海洋局(NOAA)的全球降水数据集(GHCN-M V2.0)对比,CGP新增1万个站点、0.5×107组有效观测记录和1030条百年序列,其中141条百年序列通过多源整合技术获取。CGP的站点和数据量优势主要体现在东亚、东欧、西伯利亚等站点稀疏地区。基于CGP分析的全球降水时空特征与国际同类产品的结果较一致。新增的数据虽然没有改变全球降水分布的总体特征,但对区域性的百年降水变化检测有一定影响。基于CGP的全球降水百年序列结果显示,20世纪前半叶全球降水量偏小,近20年是1900年以来全球降水量最大的时期,各纬度带、各个国家或地区的降水长期变化趋势呈现显著的差异。      

Annual cycle of the mid-tropospheric easterly jet over West Africa

Summary The paper examines the annual cycle of the mid-tropospheric easterly jet (MTJ) over West Africa against the background of many reviews indicating different locations and characteristics of the jet and considering it as a summer feature. NCEP–NCAR reanalysis zonal wind datasets for the period 1971–2000 and upper air datasets over the region are used. The results exhibit realistic spatial structure of the easterly jet. The long-term mean of the datasets suggests that the jet over West Africa is not only a summer feature but can also be found in winter with the same order of magnitude in the wind velocity at the core. The jet axis is located at about lat. 2° N close to the Guinean Coast in winter and at lat. 14° N in summer. The meridional oscillation of the jet suggests that as it advances northward, it maintains an altitude of 700 hPa in winter and transits in mid-spring to 650 hPa and reaches 600 hPa in summer. In the retreat, it displaces to 650 hPa at the end of September rather sharply to reach 700 hPa in October. The jet’s core has been observed to have a northeast–southwest orientation from season to season, covering a longitude of 29° from its southernmost to the northernmost positions.     

中国区域高分辨率多源降水观测产品的融合方法试验

高质量、高分辨率降水产品研制对于数值天气模式检验、水文陆面模拟、山洪地质灾害监测有着重要意义。利用中国近4万自动气象站逐时降水资料、中国雷达定量降水估计和CMORPH卫星反演降水产品,开展0.05°×0.05°和0.01°×0.01°两种高分辨率下的三源降水融合方法研究试验,探讨如何有效引入雷达高分辨率信息来提高降水产品质量。一方面,在0.05°分辨率上,先以自动气象站观测降水数据为基准,采用概率密度函数（PDF）匹配法订正雷达和卫星估测降水产品的系统偏差,将雷达降水产品的偏差从-0.05 mm/h降至-0.008 mm/h;再采用贝叶斯模型平均（BMA）方法融合雷达和卫星降水产品,形成0.05°分辨率的中国区域覆盖完整且最优的联合降水背景场。此外,在0.01°分辨率上,以0.05°分辨率的卫星-雷达贝叶斯模型平均联合降水产品为背景,采用1 km雷达估测降水的空间结构信息进行降尺度,亦能有效提高0.01°分辨率背景场的质量。然后,分别以不同分辨率的卫星-雷达联合降水产品为背景,采用统计方法量化误差估计,再采用最优插值方法融入地面观测。通过2419个中国国家级气象台站的独立样本检验,评估了多种类型的降水资料及融合试验产品在中国地区的质量。结果表明,两种分辨率的三源融合试验产品的精度均优于任何单一来源的降水产品,特别是在站点稀疏地区,降水精度均较融合前有显著提高,达到了较好的融合效果,其中在0.05°分辨率上采用“概率密度函数+贝叶斯模型平均+最优插值”方法的三源融合降水产品整体质量最好,而0.01°分辨率上基于“概率密度函数+贝叶斯模型平均+降尺度+最优插值”方法的三源融合降水产品在强降水监测上更有优势。      

土壤数据集对全球陆面过程模拟的影响

基于通用陆面模式（Common Land Model, CoLM）,首次评估了两套最新的全球土壤数据集GSDE（Global Soil Dataset for Earth System Model）和SG（SoilGrids）对全球陆面过程模拟的影响。比较分析了两套数据中砂粒、粘粒、砾石、有机碳的含量和容重这五个土壤属性在全球分布上的差异以及这种差异造成的对模式估计的土壤特性参数、水力热力变量的影响。结果表明,土壤特性参数在全球的空间分布主要受土壤粒径分布（砂粒、粉粒和粘粒）影响,同时也受砾石、有机碳和容重的影响。土壤资料对全球模拟结果影响主要体现在区域差异,对水文学变量的影响（R_e最大达到±100%）大于对土壤热力学变量的影响（R_e<±10%）,对地表辐射变量的影响较小（R_e<±5%）。其中,土壤体积含水量在加拿大中部及西北部、俄罗斯东南部及中西部和澳大利亚中部地区模拟结果相差较大,总径流在低纬地区模拟结果出现较大的差异,热力学变量在非洲北部、加拿大西北部以及俄罗斯中北部的差异稍大。将模拟的土壤体积含水量与站点观测相比,两套数据的表现接近,与站点观测相比都存在一定的偏差,但SG更接近观测,其中在Molly Caren站点（39°57′N,83°27′W）上SG相比GSDE整体提高约0.01～0.02。本研究表明,模式模拟结果受不同土壤数据集的影响显著,可优先考虑诸如SG较准确的土壤数据。土壤属性对陆面模拟的影响需进一步研究。     

Baroclinic Instability in the Generalized Phillips’ Model Part II: Three-layer Model

The nonlinear stability of the three-layer generalized Phillips model, for which the velocity in each layer is constant and the top and bottom surfaces are either rigid or free, is studied by employing Arnol’d’s variational principle and a prior estimate method. The nonlinear stability criteria are established. For com-parison, the linear instability criteria are also obtained by using normal mode method, and the influences of the free parameter, β parameter and curvature in vertical profile of the horizontal velocity on the linear in-stability are discussed by use of the growth rate curves.The comparison between the nonlinear stability criterion and the linear one is made. It is shown that in some cases the two criteria are exactly the same in form, but in other cases, they are different. This phenom-enon, which reveals the nonlinear property of the linear instability features, is explained by the explosive resonant interaction (ERI). When there exists the ERI, i.e., the nonlinear mechanisms play a leading role in the dynamical system, the nonlinear stability criterion is different from the linear one; on the other hand, when there does not exist the ERI, the nonlinear stability criterion is the same as the linear one in form.     

Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013

Two homogenized datasets of daily maximum temperature (Tmax), mean temperature (Tm), and minimum temperature (Tmin) series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization (MASH) method, and includes 753 stations for the period 1960–2013. The other is CHHTD1.0, based on the Relative Homogenization test (RHtest), and includes 2419 stations over the period 1951–2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include: (1) different algorithms for creating reference series for adjusting the candidate series—more neighboring stations used in MASH and hence larger-scale regional signals retained; (2) different algorithms for calculating the adjustments—larger adjustments in RHtest in general, partly due to the individual local reference information used; and (3) different rules for judging inhomogeneity—all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.     

Air temperature trend and the impact on winter wheat phenology in Romania

Air temperature variability and trends in Romania were analysed using monthly, seasonal, and annual datasets. Temperature data of winter wheat season were also analysed. The Mann-Kendall test, Sen’s slope estimate, the sequential version of the Mann-Kendall test, the Pettitt test and spatial and temporal hierarchical cluster analyses were used. First, the datasets were checked for changing points. The 106-year period was divided into two long periods of 100 years each to verify the importance of a very short interval in changing of general trends; after that it was divided into three shorter periods of 35–36 years each. The main conclusions are as follows: the 6 years making up the difference between the two long periods are very important in the context of the recent global warming; the three shorter periods analysis indicate some fluctuations rather than continuous warming. The latest short period is the most relevant for global warming. Spatial hierarchical cluster analysis indicated the existence of two distinctive groups. One of them, which includes stations in the south-east part of the country, seems to be influenced by the Black Sea surface temperature. Temporal hierarchical cluster analysis reveals that annual data series have the closest relation with the summer data series. Further, the impact of temperature changes on winter wheat phenology was determined using a phenology simulation performed with the model from the Decision Support System for Agrotechnology Transfer v. 4.0.2.0 platform. Earlier occurrences of anthesis and maturity were noticed for several regions in the country.     

HYSPLIT模式轨迹计算误差分析

基于NCEP 1°×1°再分析资料GDAS和NCEP2.5°×2.5°再分析资料GBL,利用美国NOAA 空气资源实验室ARL研发的一种用于计算和分析大气污染物输送、扩散轨迹的混合单粒子拉格朗日综合轨迹模式HYSPLIT,对2010年3月12日12时和田站距地100 m高度空气质点的3 d前向轨迹进行了模拟,分析了轨迹计算中的积分误差和分辨率误差.此次轨迹模拟试验中,积分误差对轨迹计算误差的贡献很小.随着积分时间的延长,积分误差略有增大.积分误差并未随着驱动数据分辨率的提高而减小.分辨率误差在积分的各个时刻并不相同,它与地形高度与天气系统有关.在轨迹模式中,轨迹计算基于风速在时间和空间上的线性插值,轨迹模拟的不确定性也与插值有关.使用不同分辨率的驱动数据对轨迹计算结果影响显著,分辨率误差对轨迹计算误差的贡献远大于积分过程中截断近似等带来的积分误差.     

An ocean–atmosphere interaction mechanism for the active break cycle of the Asian summer monsoon

A typical active–break cycle of the Asian summer monsoon is taken as beginning with maximum SST (pentad 0) over the north Bay of Bengal when the oceans to its west and east from longitude 40°–160°E, and between latitudes 10° and 25°N (area A) also has maximum SST. During this pentad the recently found “Cold Pool” of the Bay of Bengal (between latitudes 3°N and 10°N) has its minimum SST. An area of convection takes genesis over the Bay of Bengal immediately after pentad 0 in the zone of large SST gradient north of the Cold Pool and it pulls the monsoon Low Level Jetstream (LLJ) through peninsular India. Convection and the LLJ westerlies then spread to the western Pacific Ocean during pentads 1–4 taken as the active phase of the monsoon during which convection and LLJ have grown in a positive feed back process. The cyclonic vorticity to the north of the LLJ axis is hypothesized to act as a flywheel maintaining the convection during the long active phase against the dissipating effect of atmospheric stabilization by each short spell of deep convection. By the end of pentad 4 the SST over area A has cooled and the convection weakens there, when the LLJ turns clockwise over the Arabian Sea and flows close to the equator in the Indian ocean. A band of convection develops at pentad 5 between the equator and latitude 10°S over the Indian ocean and it is nourished by the cyclonic vorticity of the LLJ now near the equator and the moisture supply through it. This is taken as the break monsoon phase lasting for about three to four pentads beginning from pentad 5 of a composite active–break cycle of 40 day duration. With reduced wind and convection over the area A during the break phase, solar radiation and light winds make the SST there warm rapidly and a new active–break cycle begins. SST, convection, LLJ and the net heat flux at the ocean surface have important roles in this new way of looking at the active–break cycle as a coupled ocean–atmosphere phenomenon.     

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.     

Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations

A linear analysis is applied to a multi-thousand member “perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction.net . A principal component analysis of model radiative response reveals two dominant independent feedback processes, each largely controlled by a single parameter change. The leading EOF was well correlated with the value of the entrainment coefficient—a parameter in the model’s atmospheric convection scheme. Reducing this parameter increases high vertical level moisture causing an enhanced clear sky greenhouse effect both in the control simulation and in the response to greenhouse gas forcing. This effect is compensated by an increase in reflected solar radiation from low level cloud upon warming. A set of ‘secondary’ cloud formation parameters partly modulate the degree of shortwave compensation from low cloud formation. The second EOF was correlated with the scaling of ice fall speed in clouds which affects the extent of cloud cover in the control simulation. The most prominent feature in the EOF was an increase in longwave cloud forcing. The two leading EOFs account for 70% of the ensemble variance in λ—the global feedback parameter. Linear predictors of feedback strength from model climatology are applied to observational datasets to estimate real world values of the overall climate feedback parameter. The predictors are found using correlations across the ensemble. Differences between predictions are largely due to the differences in observational estimates for top of atmosphere shortwave fluxes. Our validation does not rule out all the strong tropical convective feedbacks leading to a large climate sensitivity.     

天气尺度波列对长江中下游6月梅雨的影响

采用1979—2007年6月NCEP/NCAR2.5°×2.5°逐日再分析资料和中国743站逐日降水资料,利用相关分析、合成分析等方法,分析了天气尺度波列的特征及其对长江中下游6月梅雨的影响。结果表明:当长江中下游6月梅雨较少时,东亚及西太平洋区域存在一个天气尺度波列;该波列的延伸距离较短(从黄河河套地区经过长江中下游至南海、菲律宾海一带),维持时间也很短,且仅仅在500 h Pa以下较强。诊断及个例分析表明,当该波列异常显著时,长江中下游梅雨降水明显减少,而其南部区域降水则增多,说明该波列对预报长江中下游降水具有重要的指示意义。     

A 10-Yr Global Land Surface Reanalysis Interim Dataset (CRA-Interim/Land): Implementation and Preliminary Evaluation

A land surface reanalysis dataset covering the most recent decades is able to provide temporally consistent initial conditions for weather and climate models, and thus is crucial to verifying/improving numerical weather/climate forecasts/predictions. In this paper, we report the development of a 10-yr China Meteorological Administration (CMA) global Land surface ReAnalysis Interim dataset (CRA-Interim/Land; 2007–2016, 6-h intervals, approximately 34-km horizontal resolution). The dataset was produced and evaluated by using the Global Land Data Assimilation System (GLDAS) and NCEP Climate Forecast System Reanalysis (CFSR) global land surface reanalysis datasets, as well as in situ observations in China. The results show that the global spatial patterns and monthly variations of the CRA-Interim/Land, GLDAS, and CFSR climatology are highly consistent, while the soil moisture and temperature values of the CRA-Interim/Land dataset are in between those of the GLDAS and CFSR datasets. Compared with ground observations in China, CRA-Interim/Land soil moisture is comparable to or better than that of GLDAS and CFSR datasets for the 0-10-cm soil layer and has higher correlations and slightly lower root mean square errors (RMSE) for the 10-40-cm soil layer. However, CRA-Interim/Land shows negative biases in 10-40-cm soil moisture in Northeast China and north of central China. For ground temperature and the soil temperature in different layers, CRA-Interim/Land behaves better than the CFSR, especially in East and central China. CRA-Interim/Land has added value over the land components of CRA-Interim due to the introduction of global precipitation observations and improved soil/vegetation parameters. Therefore, this dataset is potentially a critical supplement to the CRA-Interim. Further evaluation of the CRA-Interim/Land, assimilation of near-surface atmospheric forcing variables, and extension of the current dataset to 40 yr (1979–2018) are in progress.     

On the Nonlinear Stability of Three-Dimensional Quasigeostrophic Motions in Spherical Geometry

Nonlinear Mobility criteria for the motions geoverned by three-dimensional quasigeostrophic model in spherical geometry are obtained by using Arnol’d’s variational principle and a priori estimate method. The results gained in this paper are parallel to Arnol’d’s second theorem and better than the known results. Especially, under the approxima-tion of vertically integrated nondivergency, criteria corresponding to Arnol’d’s second theorem are first established by a detailed analysis.     

东亚地区低频振荡的经向传播及中纬度的低频波动

本文利用1981年6—9月欧洲中期天气预报中心(ECMWF)网格点资料分析了东亚地区低频(准40天)振荡的传播特性与结构特征,发现在120°E经度上的高空(低空)副热带地区有一个低频纬向风(经向风)经向传播的分离带(汇合带),指出中纬度低频纬向风振荡是准地转的,且高低空振荡同位相。同时揭示出:亚洲地区中纬度(35°N)高空低频纬向风的向东传播是波长为60—90个经度、移速为1.5—2.0个经度/d的中纬度低频波动东移的结果。这种低频涡旋移至东亚沿海地区常会发展,这种发展可能与急流中心附近正压不稳定能量的供给有关。     

An analogue-based method to downscale surface air temperature: application for Australia

 A statistical model (SM) has been developed to downscale large-scale predictors given by general circulation models (GCMs); emphasis has been put on local surface air temperature in two areas of interest: the south-west corner (SWC) of Western Australia and the Murray-Darling Basin (MDB) in southeastern Australia. This is a complementary approach to the dynamical modelling of climate change using high-resolution nested regional models. The analogue technique was chosen for this study as it has proven successful in the past for mid-latitude climate and, in particular, for forecasting in Australia. Furthermore, the analogue technique is successful in reproducing spells of anomalous events. The development and validation datasets used for both predictors and predictants cover the 1970–1993 period. Predictors are extracted from a dataset of operational analyses for the Australian region. Several predictors have been assessed alone and combined. Mean sea level pressure and temperature at 850 hPa have been identified as the most useful combination. Predictants have come from quality controlled stations with daily temperature extremes for the 1970–1993 period. Twenty two stations in the SWC and 29 in the MDB have been selected. The sensitivity of the SM has been tested to several internal parameters. The number of atmospheric predictors and the geographical domain on which large-scale fields are used are key factors that maximise the skill of the SM. Several metrics have been tested taking into account the state of the predictors on the day or, in order to describe the evolution of the atmosphere, over several days. This latter has been particularly useful in improving the representation of anomalous spells as it partially incorporates the auto-correlation of surface temperature. The correlation obtained between the observed local temperature series and the reconstructed series ranges between 0.5 and 0.8. Best results are obtained in summer and for maximum temperature. The reproduction of spells is satisfactory for most stations. The SM is then applied to large-scale fields obtained from a GCM forced by observed sea surface temperature; the improvement gained when using the SM instead of relying on the surface temperature calculated by the GCM is shown. Received: 14 December 1999 / Accepted: 10 January 2001     

Methodological Development of the Conditional Sampling Method. Part II: Quality Control Criteria of Relaxed Eddy Accumulation Flux Measurements

Determination of biosphere–atmosphere exchanges requires accurate quantification of the turbulent fluxes of energy and of a wide variety of trace gases. Relaxed Eddy Accumulation (REA) is a method that has received increasing attention in recent years, because it does not require any rapid sensor for the scalar measurements as the Eddy Correlation method (EC) does. As in all micrometeorological studies, REA measurements in the atmospheric surface layer are valid under some restrictive conditions so as to be representative of a specific ecosystem. These conditions are the homogeneity of the underlying surface, stationary and horizontally homogeneous turbulence. For most experiments these conditions are not fully satisfied. Data uncertainties can also be related to not fulfilling the method principles or to the technical characteristics of the REA system itself. In order to assess REA measurement quality, a methodological approach of data analysis is developed in this study. This methodological analysis is based on the establishment of criteria for data quality control. A set of them, deduced from the mean and turbulent flow, are called ‘Dynamic criteria’ and are designated to control the stationarity and homogeneity of the w function and the validation of Taylor’s hypothesis. A second set (‘REA operational criteria’) is designed to check the sampling process and, more precisely, the homogeneity of the negative and positive selection process throughout the sampling period. A third set of criteria (‘Chemical scalar criteria’) concerns the scalar measurements. Results of the criteria application to data measured at two different experimental sites are also presented. Cut-off limits of criteria are defined based on their statistical distribution and shown to be specific for each site. Strictness of each criterion, defined by the percentage of flagged samples, is analysed in conjunction with the meteorological conditions and atmospheric stability. It is found that flagged samples mainly correspond to neutral and stable nocturnal conditions. During daytime, nearly free convection conditions can also yield poor quality data.     

A Comparison of Three Kinds of Multimodel Ensemble Forecast Techniques Based on the TIGGE Data

Based on the ensemble mean outputs of the ensemble forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts),JMA (Japan Meteorological Agency),NCEP (National Centers for Environment...