FY-4A AGRI辐射率资料偏差特征分析及订正试验

风云四号A星（Fengyun-4A,简称FY-4A）作为我国最新一代静止气象卫星,各方面技术指标都体现了“高、精、尖”特色,处于国际领先地位。其上搭载的多通道扫描成像辐射计（Advanced Geosynchronous Radiation Imager,简称AGRI）较上一代静止卫星风云二号的可见光红外自旋扫描辐射仪观测精度更高、扫描时间更短,充分体现AGRI观测资料将有效提高“一带一路”沿线国家和地区的天气预报和灾害预警水平。偏差订正是卫星资料处理的重要环节之一,因此本文通过在WRFDA v3.9.1（Weather Research and Forecasting model’s Data Assimilation v3.9.1）搭建AGRI同化接口,利用RTTOV v11. 3辐射传输模式和GFS全球预报系统（Global Forecast System）分析场研究了FY-4A AGRI红外通道8～14晴空辐射率资料的偏差特征并进行偏差订正对比试验,分析了卫星天顶角对AGRI资料偏差订正的影响,为将来实现AGRI红外通道辐射率资料在中尺度模式中的同化应用奠定基础。结果表明:（1）通道8～10及14为正偏差,通道11～13为负偏差。水汽通道9和10偏差及其标准差相对较小,偏差海陆差异不明显。通道11～14探测高度较低,陆地上观测受地表发射率影响大,质量控制时可剔除这些通道陆地上的观测。（2）各通道偏差随卫星天顶角变化的拟合直线斜率都小于0.035,对比试验结果表明偏差与卫星天顶角的关系不明显,预报因子中无需考虑卫星天顶角的作用。（3）通道8及11～14的偏差随着目标亮温的变化比水汽通道9～10明显,偏差有较强的目标亮温依赖特征。（4）根据分析的偏差特征对2018年5月13日18时（协调世界时,下同）至15日18时进行变分偏差订正试验,系统性偏差得到了有效的订正。     

FY 2F红外亮温资料模拟与偏差分析

为了实现西太平洋及东亚区域FY-2F可见红外自旋扫描辐射计(VISSR)资料的直接同化,本文利用飓风天气预报模式(WRF For Hurricane,HWRF)和快速辐射传输模式(Community Radiative Transfer Model,CRTM)对FY-2F的亮温资料进行了模拟。在有云情况下,中高纬度锋面云系模拟的相对较好,而低纬热带云团模拟偏差较大。对于晴空条件下模拟的红外1、2、4通道(IR1、2、4)亮温,受陆地下垫面发射率不均匀的影响模拟偏差较大,且辐射传输模式平均而言低估了地表发射率。海洋下垫面的资料模拟情况要明显好于陆地。IR4通道在白天受太阳短波影响观测亮温偏高。去除受云污染的资料仅保留晴空观测资料,通过格点统计插值(Community Gridpoint Statistical Interpolation,GSI)质量控制和偏差订正,IR2通道平均偏差减小约50%,IR3通道平均偏差从3.7 K减小到0.34 K。而IR1通道质量较好,偏差订正前后几乎没有变化。     

辐射传输模式对地基微波辐射计观测亮温的模拟能力分析

提供高时间分辨率大气温度湿度廓线的地基微波辐射计近年来广泛使用,多通道观测亮温的数据质量是大气廓线产品合理性的基本保障。一般定期液氮绝对定标可以更好维护亮温数据质量,但实际操作颇为不易。辐射传输模式作为一种辅助工具,可以检验和认识地基微波辐射计观测亮温的数据质量。本文针对三个辐射传输模式:MonoRTM、ARTS和MWRT,结合北京探空观测资料、北京观象台和河北香河站同类型的德国RPG地基微波辐射计观测资料,分析比较了三个模式的模拟与观测亮温差异,评估不同辐射传输模式对地基微波辐射计观测的模拟能力。地基微波辐射计14个通道观测亮温与模式模拟的差异统计比较发现:三个模式的模拟结果与地基微波辐射计大部分通道的观测亮温都很接近,与观测结果具有很好一致性（如相关系数高达0.99）,而对温度通道ch8（51.26 GHz）和ch9（52.28 GHz）,三个模式模拟与观测相关系数明显较低（<0.80）,并且存在显著的绝对偏差（4～5 K）,表明模式在这两个通道的模拟能力有待提高。三个模式中,MonoRTM模式在温度通道ch8、ch9和ch10（53.86 GHz）存在明显的系统性偏差,尤其是ch8高达5 K;ARTS模式对水汽通道ch1（22.24 GHz）的模拟能力相对较弱;MWRT模拟与观测亮温在多个通道上相对更为接近和稳定,尤其系统性偏差最小。此外,探空廓线与地基观测站的空间位置不一致,对地基微波辐射计水汽通道的模拟结果影响较为显著,而对水汽不敏感的温度通道影响甚微。两地观测亮温与模式模拟的比对,初步表明北京观象台地基微波辐射水汽通道的观测质量有待改进。     

ERA再分析陆面温度资料在浙江省的适用性

利用浙江省2016年71个气象台站观测的日平均气温和地表(0cm)温度资料对ERA再分析陆面温度资料的适用性进行了初步评估,通过计算2套再分析资料(ERA5和ERA-Interim)与观测资料之间的相关系数、平均偏差、平均绝对偏差、均方根误差和纳什效率系数等统计参数,综合评估了ERA再分析资料在浙江省的适用性。结果表明:①ERA2套再分析资料与观测值均较为接近,均能够较好地再现浙江省2m气温的时空分布特征且变化相关系数均高于0.98,日绝对偏差较小。②对于地表温度,2套再分析资料的适用性要差于气温,主要表现在2套再分析地表温度均低于观测值,且夏季的偏差显著大于其他季节,但绝大多数站点相关系数高于0.9,均方根误差高于2℃。总体来说,2套ERA再分析陆面温度资料对浙江省具有较好的适用性,ERA5整体上优于ERA-Interim,地表温度的改善更明显。     

中国地球系统模式对全球地表入射短波辐射和大气逆辐射的模拟效果评估

以云和地球辐射能量系统(CERES)数据集为准,量化了中国地球系统模式对地表入射短波辐射和大气逆辐射时空变化的模拟性能,明确了多模式间模拟结果存在不确定性的区域。结果表明：中国模式均能模拟出北半球地表入射短波辐射和大气逆辐射“夏高冬低”的季节变化特征。陆地上,中国模式对两个辐射分量月均值的模拟结果与CERES相当,在海洋上低于CERES结果。中国模式能模拟出地表入射短波辐射下降、大气逆辐射上升的年际变化趋势。对于2001—2014年均值,中国模式模拟的地表入射短波辐射在海洋和陆地上较CERES分别偏低3.3和3.0 W·m^-2,模拟的大气逆辐射在海洋上与CERES结果相当,在陆地上较CERES低1.3 W·m^-2。除南北纬30°附近之外,中国模式在其他纬度均低估地表入射短波辐射,以热带和北极最为明显。模式对大气逆辐射的模拟偏差呈纬向波动特征,模拟误差大值出现在高大山脉处。中国模式模拟地表入射短波辐射不确定性极大的区域分布在热带雨林和南极洲沿海,模拟大气逆辐射不确定性极大的区域分布在格林兰岛、青藏高原、安第斯山脉和南极洲沿海。     

黄土高原地区两种再分析资料的模拟效果分析

为了研究两种再分析资料(NCEP和ERA Interim)对中尺度模式WRF模拟结果的影响,利用地面观测资料和探空资料,通过NCEP/WRF和ERA/WRF两组模拟试验,探讨了这两种再分析资料在黄土高原地区对WRF模式模拟结果的影响。结果表明,两组试验都能准确地模拟出2 m气温、相对湿度和地表温度的日变化,且ERA/WRF的模拟效果较好;由于黄土高原地形复杂,两组试验对10 m风速的模拟都不好;两组试验对地表辐射和地表通量的模拟结果相当,都能大致模拟出辐射各分量和地表通量的日变化,模拟偏差主要出现在正午时段;两组试验对大气边界层结构的模拟结果相似,对位温和比湿的模拟效果较好,与观测值的相关系数都在0.8以上,对风速的模拟效果稍差,与观测值的相关系数分别为0.64和0.60,NCEP/WRF对大气边界层结构的模拟结果比ERA/WRF好。     

青藏高原冬春多源积雪资料年际变化尺度上的适用性分析

青藏高原冬春积雪变化具有显著的年际变化特征,其对中国东部夏季降水预测具有一定指示意义。由于特殊的复杂地形,青藏高原气象站点分布稀疏且不均匀,再分析数据和卫星数据提供的高原积雪资料的不确定性是影响和制约积雪变化及其天气气候效应研究中的一个关键问题。本文基于青藏高原台站观测、再分析（ERA5和NOAA-V3）和卫星反演（MODIS雪盖以及IMS雪盖）的多源积雪资料,采用偏差分析、均方根误差以及相关分析等多元统计方法重点检验了多源高原积雪数据在描述积雪年际变化特征方面的不确定性。通过比较不同积雪资料的时空分布和变化特征,以期提升多源高原积雪资料适用性的认知,并为相关研究提供有意义的参考。分析结果表明：（1）就再分析数据给出的积雪资料而言,ERA5雪深资料相较NOAA-V3雪深,对高原站点观测雪深的描述效果更好。除了高原中东部分站点外,ERA5雪深数据的平均偏差和平均均方根误差均较小,而NOAA-V3雪深数据的平均偏差和均方根误差在整个高原范围内均存在一定程度的高估;（2）再分析（ERA5和NOAA-V3）和卫星反演（MODIS雪盖以及IMS雪盖）积雪数据和高原站点雪深均在年际变化特征上具有较...     

基于梯度提升树的大气分层透过率快速计算方法

大气透过率的计算是红外辐射传输计算的核心,RTTOV（Radiative Transfer for TOVS）通过建立大气廓线中温度、水汽、臭氧和其他气体浓度等参数与卫星通道透过率的统计关系,可实现卫星通道透过率和大气顶辐射率的快速准确计算。但在一些复杂吸收波段,如水汽波段,RTTOV的计算误差较大。为提高RTTOV在水汽敏感波段的计算精度,利用机器学习中的梯度提升树（Gradient Boosting Tree,GBT）方法,选取从ECMWF（European Centre for Medium-Range Weather Forecasts）的IFS-137（The Integrated Forecast System,137-level-profile）廓线集中挑选的1406条廓线和由此计算的透过率真值作为样本,选取风云三号气象卫星上搭载的红外分光计（InfraRed Atmospheric Sounder,IRAS）通道12（7.33 μm）进行个例研究,分别建立陆地和海洋晴空大气等压面至大气层顶透过率的快速计算模型（GBT模型）。通过和透过率、亮温真值的比较,验证了GBT模型。比较结果显示,GBT模型预测的透过率平均绝对误差（Mean Absolute Error,MAE）为:陆地0.0012,海洋0.0009;均方对数误差（Mean Squared Logarithmic Error,MSLE）为:陆地0.0215,海洋0.0095,均小于RTTOV直接计算的透过率的误差（陆地、海洋的MAE分别比RTTOV小0.0008和0.0010,MSLE分别比RTTOV小0.0135和0.0227）;由GBT模型计算的亮温MAE分别为:陆地0.0949 K,海洋0.0634 K,均方根误差（Root Mean Square Error,RMSE）分别为:陆地0.1352 K,海洋0.0831 K,也都小于RTTOV直接模拟的晴空亮温误差（陆地、海洋的MAE分别比RTTOV小0.1685 K和0.1466 K,RMSE分别比RTTOV小0.1794 K和0.1685 K）。本研究的结果表明,在IRAS红外水汽波段,GBT预测的透过率和亮温误差比RTTOV小。机器学习有提高水汽波段正演精度的潜力,或可为辐射传输的快速计算提供可行的替代方法。      

IAP/LASG全球海-陆-气耦合系统模式的纬向平均大气气候态分析(英文)

分海洋和陆地两种情况来讨论IAP/LASG全球海-陆-气耦合系统模式（GOAL）四个版本的结果,并与观测资料进行对比分析。一些重要的大气变量包括表面空气温度,海平面气压和降水率用来评估GOALS模式模拟当代气候和气候变率的能力。总的来说,GOALS模式的四个版本都能够合理地再现观测到的平均气候态和季节变化的主要特征。同时评估也揭示了模式的一些缺陷。可以清楚地看到模拟的全球平均海平面气压的主要误差是在陆地上。陆地上表面空气温度模拟偏高主要是由于陆面过程的影响。值得注意的是降水率模拟偏低主要是在海洋上,而中高纬的陆地降水在北半球冬天却比观测偏高。 通过模式不同版本之间的相互比较研究,可以发现模式中太阳辐射日变化物理过程的引入明显地改善了表面空气温度的模拟,尤其是在中低纬度的陆地上。太阳辐射日变化的引入对热带陆地的降水和中高纬度的冬季降水也有较大改进。而且,由于使用了逐日通量距平交换方案（DFA）,GOALS模式新版本模拟的海洋上的温度变率在中低纬度有了改善。 比较观测和模拟的年平均表面空气温度的标准差,可以发现GOALS模式四个版本都低估了海洋和陆地上的温度变率,文中还对影响观测和模拟温度变率差异的可能原因进行了探讨。     

CMIP6与CMIP5对历史大气层顶和地表辐射收支模拟的时空对比

基于云和地球辐射能量系统观测数据集（CERES),对比分析了耦合模式比较计划第五（CMIP5）和第六阶段（CMIP6）模拟的历史大气层顶和地表辐射收支的年际变化和空间分布,明确了多模式间不确定性大的关键区域。结果表明：在年际尺度上,除地表向上长波辐射外,CMIP6的辐射分量的集合均值较CMIP5更接近于CERES观测值,全球地表向下短波辐射的高估和大气逆辐射的低估在CMIP6中分别降低了1.9 W/m²和3.3 W/m²。除大气逆辐射外,CMIP6的辐射分量在多模式间的一致性较CMIP5提高。在北极,CMIP6对大气层顶反射短波、大气层顶出射长波和地表向下短波辐射的模拟偏差较CMIP5大。在南北纬60°,CMIP6对大气逆辐射的模拟偏差较CMIP5大。其他区域CMIP6的辐射分量更接近CERES观测值。CMIP6模拟的地表向下短波辐射和大气逆辐射的不确定性较大区域面积较CMIP5减小,但不确定性极大区域面积无变化。地表净辐射的不确定性空间分布在两代CMIP间变化甚小。青藏高原、赤道太平洋、热带雨林、阿拉伯半岛和南极洲沿海依然是地球系统模式模拟辐射收支不确定性极大的关键区域。     

江淮地区ERA-Interim再分析与观测温度资料对比分析

通过对比江淮地区1992-2016年08和20时的ERA-Interim再分析资料与观测资料的温度要素,发现它们在垂直方向上的偏差存在从低层到高层先减小后增大的特点,对流层低层各站偏差的空间差异明显,到中高层各站偏差趋于一致。偏差存在明显年际变化,500 hPa及以上等压面在2000年前后再分析资料比观测资料存在由偏低向偏高的转折;除地面外,其他高度上两种资料的平均绝对偏差均呈显著减小趋势。在偏差的月际分布上,地面和500 hPa以上高度再分析资料普遍比观测资料偏高,各高度上平均绝对偏差在8-9月最小。进一步对各天气现象下两种资料比较发现,雪、雨夹雪、冰粒子和冻雨天气发生时,地面至1000 hPa和850 hPa上再分析资料比观测资料偏高;大雾天气发生时,再分析资料比观测资料在1000 hPa偏高幅度明显高于地面。可见,在江淮地区使用ERA-Interim再分析温度资料判别降水相态时,大气边界层和850 hPa温度需慎重使用,近地层虚假逆温对大雾判别会产生很大影响。     

ERA5再分析数据适用性初步评估

利用山东省及周边地区10个站点的地面和高空观测资料对ERA5再分析资料的适用性进行了初步评估。结果表明：再分析的海平面气压和2 m温度与实况资料的相关性明显优于2 m相对湿度和10 m风场;高空温度和相对湿度在对流层中低层的适用性要好于高层,而位势高度和风场在中高层适用性较好;海平面气压再分析与实况的相关有着最明显的季节变化,2 m温度、2 m相对湿度和10 m风速则在部分站点有较明显的季节变化,而10 m风向的相关系数更多地表现出站点之间的差异,高空要素的适用性,季节和区域差异不明显。另外,对比发现,ERA5的适用性总体上要优于ERA-Interim再分析资料,地面和对流层低层的相对湿度、风场提高更为明显。     

Latitudinal and Scan-dependent Biases of Microwave Humidity Sounder Measurements and Their Dependences on Cloud Ice Water Path

The relationship between differences in microwave humidity sounder(MHS)–channel biases which represent measured brightness temperatures and model-simulated brightness temperatures, and cloud ice water path(IWP) as well as the influence of the cloud liquid water path(LWP) on the relationship is examined. Seven years(2011–17) of NOAA-18 MHS-derived measured brightness temperatures and IWP/LWP data generated by the NOAA Comprehensive Large Array-data Stewardship System Microwave Surface and Precipitation Products System are used. The Community Radiative Transfer Model, version2.2.4, is used to simulate model-simulated brightness temperatures using European Center for Medium-Range Weather Forecasts reanalysis data as background fields. Scan-angle deviations of the MHS window channel biases range from-1.7 K to1.0 K. The relationships between channels 2, 4, and 5 biases and scan angle are symmetrical about the nadir. The latitudedependent deviations of MHS window channel biases are positive and range from 0–7 K. For MHS non-window channels,the latitudinal deviations between measured brightness temperatures and model-simulated brightness temperatures are larger when the detection height is higher. No systematic warm or cold deviations are found in the global spatial distribution of difference between measured brightness temperatures and model-simulated brightness temperatures over oceans after removing scan-angle and latitudinal deviations. The corrected biases of five different MHS channels decrease differently with respect to the increase in IWP. This decrease is stronger when LWP values are higher.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

Evaluation of water and energy budgets in regional climate models applied over Europe

This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.     

Sunglint impact on atmospheric soundings from hyperspectral resolution infrared radiances

The mid-wave infrared band(3-5 μm) has been widely used for atmospheric soundings.The sunglint impact on the atmospheric parameter retrieval using this band has been neglected because the reflected radiances in this band are significantly less than those in the visible band.In this study,an investigation of sunglint impact on the atmospheric soundings was conducted with Atmospheric InfraRed Sounder observation data from 1 July to 7 July 2007 over the Atlantic Ocean.The impact of sunglint can lead to a brightness temperature increase of 1.0 K for the surface sensitive sounding channels near 4.58 μm.This contamination can indirectly cause a positive bias of 4 g kg-1 in the water vapor retrieval near the ocean surface,and it can be corrected by simply excluding those contaminated channels.     

利用ERA5资料进行桂林地区GNSS水汽反演精度分析

由于桂林地区地基GNSS站并未配置气象传感器，致使大量GNSS观测数据无法在大气水汽（PWV）监测中发挥作用.针对这一情况，本文将欧洲中期天气预报中心（ECMWF）最新发布的ERA5再分析资料中测站处的气压和温度气象数据加入到GNSS水汽反演中，并将反演结果与利用地面气象站反演的GNSS水汽做对比，以此评估ERA5在桂林地区反演GNSS水汽的精度和适用性.结果表明：1）以桂林地区2017年10个地面气象站的实测气压和温度数据为参考值，ERA5地表气压和温度的年均偏差分别为-0.35 hPa和0.86 K，年均均方根误差（RMSE）分别为0.65 hPa和1.66 K，该精度可用于GNSS水汽反演；2）以2017年6—7月GNSS利用地面气象站反演的PWV为参考值，ERA5反演的GNSS PWV的偏差和RMSE分别为0.17 mm和0.35 mm，且两者具较好的相关性和一致性.由此表明，ERA5地表温压产品可应用于桂林地区GNSS水汽反演，这些研究结果可为桂林地区的GNSS水汽反演及数据源的选用提供重要的参考依据.     

Simulation of the atmospheric circulation in the Weddell Sea region using the limited-area model REMO

Summary ?To analyse the applicability of a limited-area atmosphere model to the Southern Ocean, a one-year simulation for 1985 is performed using the REgional MOdel REMO at 55-km horizontal grid-spacing implemented for the Antarctic regions of the Weddell, Bellingshausen and Amundsen Seas. To evaluate the performance of REMO, a comparison of model results to observations and to reanalysis/analysis data sets is carried out. REMO is initialized and driven at the lateral and lower boundaries by data of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA15). Overall, REMO is an appropriate tool for further climate studies in Antarctic regions. It reproduces reasonably well basic spatial patterns and the seasonal cycle of the atmospheric circulation. However, the simulated mean sea level pressure (MSLP) is predominantly lower than the MSLP provided by observations and by ERA. Considerable temperature differences in the lower troposphere over sea ice in winter cause discrepancies between the REMO and ERA pressure fields in the mid-troposphere too. The precipitation rate P of the REMO simulation agrees qualitatively well with main features of the observed climatological spatial distribution described in literature. The seasonal cycle of P in the inner Weddell Sea reflects the Antarctic semi-annual oscillation. Concerning the forcing fields, the ERA sea ice surface temperatures in winter are generally higher than satellite derived surface temperatures. Although the differences are 10 to 15 K in the southern Weddell Sea, this deficiency of the ERA data hardly influences the mean large-scale circulation. Received October 10, 2001; revised April 22, 2002; accepted May 12, 2002