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.

     

中国探空观测与多套再分析资料气温序列的对比研究

为比较中国探空观测与再分析气温的差异,利用中国118站850—30 hPa经质量控制和均一化处理后逐月气温和NCEPv1、NCEPv2、ERA-40、ERA-Interim、JRA55、20CR、MERRA和CFSR等8套再分析月平均气温,通过对比1981—2010年探空观测与多套再分析气温序列的平均偏差、相关系数、标准差和变化趋势,分析两者在数值、年际变率、离散度及长期变化的差异。结果表明,中国探空温度原始序列存在较为显著的非均一性,均一化对原始气温序列总体为负订正,对流层上层至平流层下层(200—100 hPa)订正值最为显著。均一化气温去除了原始序列中由仪器换型和系统升级等因素导致的系统误差,与再分析气温相关较原始序列明显提高。再分析气温与均一化气温偏差约1℃,多数再分析气温较均一化气温在对流层偏低、平流层偏高。再分析与均一化气温年际变率较为一致,正相关达到显著。多数再分析与均一化气温均在对流层中低层呈上升趋势、平流层中层呈下降趋势。对流层上层和平流层下层不确定性较大。总体上,ERA-Interim、JRA55和MERRA与其他再分析相比更相近中国均一化探空气温。      

Evaluation of Reanalysis Products with in situ GPS Sounding Observations in the Eastern Himalayas

Previous studies have shown that reanalysis products contain large uncertainties in the Tibetan Plateau(TP),and the biases are location dependent.Therefore,these products must be evaluated with in situ observations prior to their applications.In this study,the authors compare the results of several reanalysis projects with independent sounding observations recorded in the Yarlung Tsangpo River valley in the Eastern Himalayas in June 2010.These reanalysis projects include Climate Forecast System Reanalysis(CFSR),Interim European Centre for Medium Range Weather Forecasts Reanalysis(ERA- Interim),Japanese 25-year Reanalysis(JRA-25),Modern Era Retrospective Analysis for Research and Applications(MERRA),National Center for Environmental Prediction and the Department of Energy Reanalysis 2(NCEP-R2),and NCEP Final Analysis(FNL).Statistical quantities such as average,mean bias(MB),root-mean-square difference(RMSD),and correlation coefficient(R) of temperature,specific humidity,u-wind,and v-wind between 100 hPa and 650 hPa were calculated.The authors determined that the performance of each product differed with variables at different levels.The average profiles of the variables were captured by the reanalysis products,with large biases appearing at lower levels.ERA-Interim and NCEP-R2 showed the best and worst performances,respectively,for all variables.This study suggests that users should select appropriate reanalysis products according to their specific purposes for TP research.     

四套土壤湿度再分析数据在中国西北东部—华北—江淮地区的适用性研究

基于1992~2010年全国778个农业气象站土壤湿度观测资料、ERA-Interim、JRA55、NCEP-DOE R2和20CR土壤湿度再分析资料,通过平均差值、相关系数、差值标准差、标准差比四个参数,利用Brunke排名方法和EOF(Empirical Orthogonal Function)分析,对四套土壤湿度再分析资料在中国西北东部—华北—江淮区域的适用性进行了分析。主要结论如下:不同季节的平均偏差空间分布上,JRA55资料同观测数据的平均偏差在±0.08m~3 m~(-3)之间,春、夏季西北东部JRA55土壤湿度偏小,ERA-Interim、NCEP-DOE R2、20CR资料较观测数据偏湿,华北南部、江淮地区平均偏差小于西北东部、华北北部。在年际变化上,各个季节ERA-Interim资料同观测资料最为接近,能稳定地再现西北东部、华北、江淮地区土壤湿度干湿变化趋势,反映出重要的旱涝年。整体而言,四套再分析资料中ERA-Interim资料同观测资料接近,JRA55、NCEP-DOE R2资料次之,20CR资料最差。     

RegCM4对中国东部区域气候模拟的辐射收支分析

利用卫星和再分析数据,评估了区域气候模式Reg CM4对中国东部地区辐射收支的基本模拟能力,重点关注地表净短波(SNS)、地表净长波(SNL)、大气顶净短波(TNS)、大气顶净长波(TNL)4个辐射分量。结果表明:1)短波辐射的误差值在夏季较大,而长波辐射的误差值在冬季较大。但各辐射分量模拟误差的空间分布在冬、夏季都有较好的一致性。2)对于地表辐射通量,SNS表现为正偏差(向下净短波偏多),在各分量中误差最大,区域平均误差值近50 W/m2;SNL表现为负偏差(向上净长波偏多);对于大气顶辐射通量,TNS和TNL分别表现为"北负南正"的误差分布和整体正偏差。3)利用空间相关和散点线性回归方法对4个辐射分量的模拟误差进行归因分析,发现在云量、地表反照率、地表温度三个直接影响因子中,云量模拟误差的贡献最大,中国东部地区云量模拟显著偏少。     

江苏省土壤湿度观测资料与再分析资料对比分析研究

利用江苏省2010—2015年的60个站点土壤湿度观测资料,对欧洲中心ERA-Interim再分析资料(ERA)和美国宇航局再分析资料(MERRA)的两套土壤湿度数据在江苏地区的可靠性进行了评估。结果表明:相比于ERA再分析资料,MERRA较好地再现出江苏省次表层年平均土壤湿度的空间分布特征,但是两种资料的次表层和深层土壤湿度的数值均小于观测。ERA和MERRA基本都能揭示出江苏省次表层土壤湿度的季节变化特征,但是深层土壤湿度与观测仍有较大差距。在时间演变方面,ERA次表层土壤湿度与站点观测在研究时段内较为接近,EOF分析揭示出1979—2016年江苏省次表层土壤湿度存在区域一致型与南北偶极型两个主要的年代际变率模态。但是对于深层土壤湿度时间演变而言,两种再分析资料都与观测有较大的差距。总体而言,再分析资料的次表层土壤湿度与站点观测较为接近,但是由于再分析资料陆面模式中地下水等影响深层土壤湿度的关键过程刻画较为简单,使得深层土壤湿度与观测有较大的差距。     

An Evaluation of Temperature and Precipitation Surface-Based and Reanalysis Datasets for the Canadian Arctic, 1950–2010

The spatial and temporal consistency of seasonal air temperature and precipitation in eight widely used gridded observation-based climate datasets (CANGRD, CRU-TS3.1, CRUTEM4.1, GISTEMP, GPCC, GPCP, HadCRUT3, and UDEL) and eight reanalyses (20CR, CFSR, ERA-40, ERA-Interim, JRA25, MERRA, NARR, and NCEP2) was evaluated over the Canadian Arctic for the 1950–2010 period. The evaluation used the CANGRD dataset, which is based on homogenized temperature and adjusted precipitation from climate stations, as a reference. Dataset agreement and bias were observed to exhibit important spatial, seasonal, and temporal variability over the Canadian Arctic with the largest spread occurring between datasets over mountain and coastal regions and over the Canadian Arctic Archipelago. Reanalysis datasets were typically warmer and wetter than surface observation-based datasets, with CFSR and 20CR exhibiting biases in total annual precipitation on the order of 300?mm. Warm bias in 20CR exceeded 12°C in winter over the western Arctic. Analysis of the temporal consistency of datasets over the 1950–2010 period showed evidence of discontinuities in several datasets as well as a noticeable increase in dataset spread in the period after approximately 2000. Declining station networks, increased automation, and the inclusion of new satellite data streams in reanalyses are potential contributing factors to this phenomenon. Evaluation of trends over the 1950–2010 period showed a relatively consistent picture of warming and increased precipitation over the Canadian Arctic from all datasets, with CANGRD giving moistening trends two times larger than the multi-dataset average related to the adjustment of the station precipitation data. The study results indicate that considerable care is needed when using gridded climate datasets in local or regional scale applications in the Canadian Arctic.     

4种再分析月降水数据在内蒙古地区的适用性分析

利用1981—2020年气象台站的实测降水数据,对CRA40、ERA5、JRA55和MERRA2这4种再分析月降水数据在内蒙古地区的降水分布特征,与实测降水的相关性和误差进行分析。结果表明：（1）内蒙古地区4种再分析降水数据的空间分布与台站降水基本一致,误差分析表明CRA40与MERRA2的数据质量较高,ERA5次之,而JRA55数据质量相对较差。（2）CRA40和MERRA2在1983—1986年存在明显的降水低估,ERA5在2005年之后的内蒙古中东部出现明显的降水低估,JRA55在115°E以东存在明显降水高估,在115°E以西则以降水低估为主。（3）4种再分析月降水数据的年内最大均方根误差和绝对误差均集中在6—8月,与台站降水相关系数的年内最小值均出现在7月,内蒙古夏季汛期是再分析降水误差产生的主要时段。     

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.     

Tropical intraseasonal rainfall variability in the CFSR

While large-scale circulation fields from atmospheric reanalyses have been widely used to study the tropical intraseasonal variability, rainfall variations from the reanalyses are less focused. Because of the sparseness of in situ observations available in the tropics and strong coupling between convection and large-scale circulation, the accuracy of tropical rainfall from the reanalyses not only measures the quality of reanalysis rainfall but is also to some extent indicative of the accuracy of the circulations fields. This study analyzes tropical intraseasonal rainfall variability in the recently completed NCEP Climate Forecast System Reanalysis (CFSR) and its comparison with the widely used NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2). The R1 produces too weak rainfall variability while the R2 generates too strong westward propagation. Compared with the R1 and R2, the CFSR produces greatly improved tropical intraseasonal rainfall variability with the dominance of eastward propagation and more realistic amplitude. An analysis of the relationship between rainfall and large-scale fields using composites based on Madden-Julian Oscillation (MJO) events shows that, in all three NCEP reanalyses, the moisture convergence leading the rainfall maximum is near the surface in the western Pacific but is above 925?hPa in the eastern Indian Ocean. However, the CFSR produces the strongest large-scale convergence and the rainfall from CFSR lags the column integrated precipitable water by 1 or 2?days while R1 and R2 rainfall tends to lead the respective precipitable water. Diabatic heating related to the MJO variability in the CFSR is analyzed and compared with that derived from large-scale fields. It is found that the amplitude of CFSR-produced total heating anomalies is smaller than that of the derived. Rainfall variability from the other two recently produced reanalyses, the ECMWF Re-Analysis Interim (ERAI), and the Modern Era Retrospective-analysis for Research and Applications (MERRA), is also analyzed. It is shown that both the ERAI and MERRA generate stronger rainfall spectra than the R1 and more realistic dominance of eastward propagating variance than R2. The intraseasonal variability in the MERRA is stronger than that in the ERAI but weaker than that in the CFSR and CMORPH.     

Testing WRF capability in simulating the atmospheric water cycle over Equatorial East Africa

Uncertainties in simulating the seasonal mean atmospheric water cycle in Equatorial East Africa are quantified using 58 one-year-long experiments performed with the Weather Research and Forecasting model (WRF). Tested parameters include physical parameterizations of atmospheric convection, cloud microphysics, planetary boundary layer, land-surface model and radiation schemes, as well as land-use categories (USGS vs. MODIS), lateral forcings (ERA-Interim and ERA40 reanalyses), and domain geometry (size and vertical resolution). Results show that (1) uncertainties, defined as the differences between the experiments, are larger than the biases; (2) the parameters exerting the largest influence on simulated rainfall are, in order of decreasing importance, the shortwave radiation scheme, the land-surface model, the domain size, followed by convective schemes and land-use categories; (3) cloud microphysics, lateral forcing reanalysis, the number of vertical levels and planetary boundary layer schemes appear to be of lesser importance at the seasonal scale. Though persisting biases (consisting of conditions that are too wet over the Indian Ocean and the Congo Basin and too dry over eastern Kenya) prevail in most experiments, several configurations simulate the regional climate with reasonable accuracy.     

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.     

Observational characteristics of cloud radiative effects over three arid regions in the Northern Hemisphere

Cloud–radiation processes play an important role in regional energy budgets and surface temperature changes over arid regions. Cloud radiative effects (CREs) are used to quantitatively measure the aforementioned climatic role. This study investigates the characteristics of CREs and their temporal variations over three arid regions in central Asia (CA), East Asia (EA), and North America (NA), based on recent satellite datasets. Our results show that the annual mean shortwave (SW) and net CREs (SWCRE and NCRE) over the three arid regions are weaker than those in the same latitudinal zone of the Northern Hemisphere. In most cold months (November–March), the longwave (LW) CRE is stronger than the SWCRE over the three arid regions, leading to a positive NCRE and radiative warming in the regional atmosphere–land surface system. The cold-season mean NCRE at the top of the atmosphere (TOA) averaged over EA is 4.1 W m^–2, with a positive NCRE from November to March, and the intensity and duration of the positive NCRE is larger than that over CA and NA. The CREs over the arid regions of EA exhibit remarkable annual cycles due to the influence of the monsoon in the south. The TOA LWCRE over arid regions is closely related to the high-cloud fraction, and the SWCRE relates well to the total cloud fraction. In addition, the relationship between the SWCRE and the low-cloud fraction is good over NA because of the considerable occurrence of low cloud. Further results show that the interannual variation of TOA CREs is small over the arid regions of CA and EA, but their surface LWCREs show certain decreasing trends that correspond well to their decreasing total cloud fraction. It is suggested that combined studies of more observational cloud properties and meteorological elements are needed for indepth understanding of cloud–radiation processes over arid regions of the Northern Hemisphere.     

中国区域探空资料与再分析资料风速场的对比分析

利用中国高空探空资料和NCEP/NCAR、ERA以及MERRA三种再分析资料,讨论了再分析资料风速场在中国区域的适用性问题。结果表明:在中国区域的年平均场上,高空风速在我国对流层高层和中层均存在长期减弱的趋势,在我国东部和南部地区的对流层低层也存在减弱趋势,ERA-interim资料和MERRA资料适用性相对较好。再分析资料风速在多年年平均场上普遍小于探空风速。在对流层高层,1980年代至1990年代ERA-interim资料适用性好,而21世纪以后,NCEP/NCAR的适用性较好;在对流层中层和低层,NCEP/NCAR资料适用性较好。在中国区域的季节平均场上,高空风速在冬季的对流层高层和中层中普遍存在增加的趋势,而在春季、夏季和秋季的对流层高层和中层存在减小的趋势。探空资料与再分析资料在冬季偏差最小,在夏季偏差最大。在对流层中层和低层,NCEP/NCAR资料和MERRA资料在冬季的可信度相对较好,MERRA资料在夏季的可信度相对较好;在对流层高层和平流层低层,ERA-interim资料和MERRA资料在四季中的可信度都相对较好。     

利用多种再分析资料对比分析青藏高原夏季大气水汽含量变化情况

利用ERA-Interim、MERRA和NCEP/NCAR三套再分析资料,分析1979~2014年夏季青藏高原大气水汽含量的时空变化特征,同时对比了各套资料异同点,结果表明:(1) ERA-Interim和MERRA资料均显示出夏季青藏高原大气水汽含量呈现显著的上升趋势,在1994~1995年前后发生明显突变,大气水汽含量由偏低时期向偏高时期转变;而NCEP/NCAR资料并没有出现类似的显著上升趋势和突变年份;ERA-Interim资料与MERRA资料的夏季青藏高原湿池指数之间的相关性明显强于NCEP/NCAR资料与它们任何一个之间的相关性。(2)夏季青藏高原大气水汽含量呈现出自高原东南边缘地区向西北部递减的分布形式。其中,MERRA与ERA-Interim资料显示的水汽含量分布更为相似,而NCEP/NCAR资料反映的水汽含量在高原中部往北递减不明显,湿度中心较为分散。(3)从空间分布上,MERRA与ERA-Interim资料显示青藏高原大部分地区夏季水汽含量均呈显著的增加趋势,而NCEP/NCAR资料仅在高原东北部小部分区域存在显著的增加趋势。(4)从夏季青藏高原大气水汽含量的年际变化特征分析来看,ERA-Interim和MERRA资料相对于NCEP/NCAR资料也更为接近。      

A comparative study of the Indian summer monsoon hydroclimate and its variations in three reanalyses

This study examines the Indian summer monsoon hydroclimate in the National Centers for Environmental Prediction (NCEP)-Department of Energy (DOE) Reanalysis (R2), the Climate Forecast System Reanalysis (CFSR), and the Modern Era Retrospective-Analysis for Research and Applications (MERRA). The three reanalyses show significant differences in the climatology of evaporation, low-level winds, and precipitable water fields over India. For example, the continental evaporation is significantly less in CFSR compared to R2 and MERRA. Likewise the mean boreal summer 925?hPa westerly winds in the northern Indian Ocean are stronger in R2. Similarly the continental precipitable water in R2 is much less while it is higher and comparable in MERRA and CFSR. Despite these climatological differences between the reanalyses, the climatological evaporative sources for rain events over central India show some qualitative similarities. Major differences however appear when interannual variations of the Indian summer monsoon are analyzed. The anomalous oceanic sources of moisture from the adjacent Bay of Bengal and Arabian Sea play a significant role in determining the wet or dry year of the Indian monsoon in CFSR. However in R2 the local evaporative sources from the continental region play a more significant role. We also find that the interannual variability of the evaporative sources in the break spells of the intraseasonal variations of the Indian monsoon is stronger than in the wet spells. We therefore claim that instead of rainfall, evaporative sources may be a more appropriate metric to observe the relationship between the seasonal monsoon strength and intraseasonal activity. These findings are consistent across the reanalyses and provide a basis to improve the predictability of intraseasonal variability of the Indian monsoon. This study also has a bearing on improving weather prediction for tropical cyclones in that we suggest targeting enhanced observations in the Bay of Bengal (where it is drawing the most moisture from) for improved analysis during active spells of the intraseasonal variability of the Indian monsoon. The analysis suggests that the land–atmosphere interactions contribute significant uncertainty to the Indian monsoon in the reanalyses, which is consistent with the fact that most of the global reanalyses do not assimilate any land-surface data because the data are not available. Therefore, the land–atmosphere interaction in the reanalyses is highly dependent on the land-surface model and it’s coupling with the atmospheric model.     

Comparison of products from ERA-40, NCEP-2, and CRU with station data for summer precipitation over China

Summer precipitation products from the 45-Year European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis (ERA-40), and NCEP-Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis (NCEP-2), and Climatic Research Unit (CRU) TS 2.1 dataset are compared with the corresponding observations over China in order to understand the quality and utility of the reanalysis datasets for the period 1979–2001. The results reveal that although the magnitude and location of the rainfall belts differ among the reanalysis, CRU, and station data over South and West China, the spatial distributions show good agreement over most areas of China. In comparison with the observations in most areas of China, CRU best matches the observed summer precipitation, while ERA-40 reports less precipitation and NCEP-2 reports more precipitation than the observations. With regard to the amplitude of the interannual variations, CRU is better than either of the reanalyses in representing the corresponding observations. The amplitude in NCEP-2 is stronger but that of ERA-40 is weaker than the observations in most study domains. NCEP-2 has a more obvious interannual variability than ERA-40 or CRU in most areas of East China. Through an Empirical orthogonal function (EOF) analysis, the main features of the rainfall belts produced by CRU agree better with the observations than with those produced by the reanalyses in the Yangtze-Huaihe River valley. In East of China, particularly in the Yangtze-Huaihe River valley, CRU can reveal the quasi-biennial oscillation of summer precipitation represented by the observations, but the signal of ERA-40 is comparatively weak and not very obvious, whereas that of NCEP-2 is also weak before 1990 but very strong after 1990. The results also suggest that the magnitude of the precipitation difference between ERA-40 and the observations is smaller than that between NCEP-2 and the observations, but the variations represented by NCEP-2 are more reasonable than those given by ERA-40 in most areas of East China to some extent.     

青藏高原及周边UTLS水汽时空特征的多源资料对比

利用Aura卫星微波临边观测仪(Microwave Limb Sounder,MLS)数据,评估了ERA-I、MERRA、JRA-55、CFSR和NCEP2等5套再分析资料的水汽数据在青藏高原及周边上对流层-下平流层(Upper Troposphere and Lower Stratosphere,UTLS)的质量,然后选取其中质量较好的两套水汽数据,分析它们对青藏高原及周边UTLS水汽的时空分布和演变的表征能力。结果表明,与MLS数据相比,5套再分析资料中在UTLS普遍偏湿,最大偏湿在上对流层215 hPa,约为165%,而在下平流层,ERA-I和MERRA与MLS的差异相对较小。总的来看,ERA-I和MERRA表征的水汽与MLS更为接近。进一步的对比表明,ERA-I和MERRA中青藏高原及周边水汽含量的时空分布与MLS较为接近,夏季能够表征青藏高原在纬向和经向上的水汽高值区,冬季能够表征对流层顶、西风急流中心附近的水汽梯度带,而且MERRA的结果要好于ERA-I。ERA-I、MERRA和MLS中青藏高原地区的水汽季节演变都表现为冬季1-2月水汽含量低,夏季7-8月水汽含量高,水汽的季节变化在200~300 hPa最大。MLS资料显示,在青藏高原地区对流层顶附近,存在随时间向上向极的水汽传输信号。相较而言,ERA-I对向上水汽传输信号的表征更好,而MERRA对下平流层(100 hPa)向极水汽传输信号的表征更好。     

环渤海区域再分析资料地面风速场的适用性对比分析

利用环渤海区域的气象站资料和NCEP/NCAR、NCEP/DOE、CFSR、ERA Interim、JRA-55共5种再分析资料,讨论了再分析资料近地面10 m平均风速场在环渤海区域的适用性问题。结果表明：JRA资料与观测站的相关系数最大,ERA资料与23站均方根误差的平均最小;再分析资料与气象站观测资料的相关系数在山东半岛和辽东半岛高于其他地区、冬半年大于夏半年。环渤海区域地面10 m平均风速场JRA和ERA两套资料的适用性较好。由于ERA-Interim的水平分辨率更高,所以在强风过程分析中确定使用ERA Interim再分析资料。