秦岭—大巴山高分辨率气温和降水格点数据集的建立及其对区域气候的指示

本文建立了秦岭—大巴山高分辨率(～29 m×29 m)的气候格点数据集,包括逐月气温和降水、年均温和年降水、春夏秋冬气温和降水。空间插值方法采用国际上较为先进的ANUSPLIN软件内置的薄盘光滑样条函数,以经度、纬度和海拔为独立变量。空间插值结果与流行的WorldClim 2.0气候格点数据集具有一致性,但是比后者更精确、分辨率更高、细节更突出。本文揭示和证实:秦岭南麓是最冷月气温的0℃分界线。秦岭—大巴山气温具有明显的垂直地带性。6月气温直减率最大,为0.61℃/100 m;12月气温直减率最小,为0.38℃/100 m;年均气温直减率为0.51℃/100 m。夏季和秋季降水从西南向东北递减,强降水中心出现在大巴山西南坡。冬季降水从东南向西北递减。大巴山是年降水1000 mm分界线,夏季降水500mm分界线;秦岭是年降水800 mm分界线,夏季降水400 mm分界线。与大尺度大气环流对比揭示:秦岭—大巴山气温和降水空间分布主要受到东亚季风和地形因子的控制。本文进一步明确了秦岭和大巴山的气候意义:大巴山主要阻挡夏季风北上,影响降水空间分布;秦岭主要阻挡冬季风南下,影响冬季气温空间分布。本文建立的高分辨率气候格点数据集,加深了对区域气候的认识,并将有多方面的用途。     

ERA-Interim和NCEP/NCAR再分析资料在我国东南近海适用性分析

利用我国东南近海5个浮标站观测资料,对2012—2016年ERA-Interim和NCEP/NCAR再分析资料10 m风、2 m气温、海平面气压的适用性进行了评估。结果表明:NCEP/NCAR的再分析10 m风适用性更好,ERA-Interim的2 m气温适用性更好,海平面气压两者差异不大。风速再分析值与观测值具有较好的一致性,相关系数达0.8～0.9,但再分析风速总体上有偏小的趋势,平均偏差在-1.3～0 m/s之间,均方根误差在1.5～3 m/s。再分析资料的平均风向有顺时针偏差的趋势,温州浮标偏右达14°以上,均方根误差大多在40°～50°。不管风速还是风向,5个浮标站中均以舟山浮标的再分析值与观测值最为接近;分析还表明,再分析资料的冬季风代表性相对较差,这是造成风速和风向系统性偏差的主要原因。再分析资料与观测2 m气温相关系数均在0.95以上,且有偏高的趋势,NCEP偏高更为明显,有4个浮标站平均偏差达1～2℃,而ERA-I仅1个浮标站偏差1～2℃,4个在1℃以内。春季和冬季气温偏高最为明显,春季升温过程存在异常偏高的可能,秋季气温与观测值最为接近。海平面气压适用性较好,总体优于10 m风和2 m气温,且季节间差异也不大。     

长序列北极海冰覆盖数据集对比分析

国家卫星气象中心使用2011年至今的风云三号卫星数据开发了一套基于Nasa Team2（NT2）算法的北极海冰密集度数据集,并可实时业务更新。将该数据集与其他国家不同机构业务运行并实时更新多种同类型数据集进行横向对比分析,其中包括:（1）美国冰雪中心基于Nasa Team（NT）算法以及SSM/I、SSMIS数据制作的1978年至今25 km分辨率全球极区海冰覆盖数据集;（2）美国冰雪中心基于Boot Strap（BS）算法以及SSM/I、SSMIS数据制作的1978年至今25 km分辨率全球极区海冰覆盖数据集;（3）美国NOAA基于多种卫星资料、地面观测数据以及海冰模型制作的2004年至今4 km分辨率北半球海冰覆盖数据集（IMS）。对比表明,上述数据集在北极地区不同的时空范围内存在一定的偏差。以分辨率较高的IMS数据集为基准,对其他3种长序列数据集进行初步评价,总体最大偏差超过100×104 km2,其中,NT2数据集过估较明显。经过与IMS数据集多年各月监测最大值的对比订正,NT2数据集过估情况得到改善。在此基础上的分析结果表明,NT、BS、NT2等3种数据集与IMS数据集相比,过估区域主要分布在海岸线附近,夏季过估比冬季更加明显,少估区域与算法、月份相关性明显,夏季少估面积也较冬季更大。NT、BS、NT2等3种数据集之中,NT2数据集与IMS数据集偏差最小,NT数据集次之,BS数据集与IMS数据集偏差最大。结果表明使用风云三号卫星数据的北极海冰覆盖数据集精度与国外3种同类型数据集相当。     

基于全球气象再分析资料的InSAR对流层延迟改正研究

气压、温度和水汽含量等大气物理参数的时空变化导致的对流层延迟是制约合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar,InSAR)高精度应用的重要因素之一.最新研究显示气象再分析资料在补偿对流层延迟影响方面具有巨大的应用潜力,这促使我们对其有效性和鲁棒性做进一步的研究和探索.本文首先推导了利用气象再分析资料对InSAR进行对流层延迟校正的算法;然后以美国南加州地区的ENVISAT ASAR数据为例,分析了基于两种气象再分析资料(ERA-Interim和North American Regional Reanalysis,NARR)校正InSAR对流层延迟改正的效果;通过与MERIS水汽延迟改正结果比较,验证了该方法的有效性.实验结果表明:(1)不能简单忽略干延迟,可通过气象再分析资料进行有效估计;(2)通过与MERIS水汽产品获得的对流层延迟比较发现,气象再分析资料能够取得接近于MERIS的改善效果;(3)对ERA-Interim和NARR两种气象再分析资料而言,虽然后者具有更高的时间和空间分辨率,但在改正InSAR对流层延迟方面并没有表现出比前者更明显的优势;(4)气象再分析资料可以很好地估计与地形强相关的垂直分层延迟,但对于小尺度的湍流混合延迟的捕捉能力有限.综合分析认为,气象再分析资料的优势在于其数据可随时获得、免费和全球覆盖,它可以显著减弱大尺度的垂直分层延迟对干涉图相位的影响,从而有助于InSAR获取更真实可靠的地形高程和地表形变信息.     

Spatial distribution and temporal trends of rainfall and erosivity in the Eastern Africa region

Soil erosion by water is one of the main environmental concerns in the drought‐prone Eastern Africa region. Understanding factors such as rainfall and erosivity is therefore of utmost importance for soil erosion risk assessment and soil and water conservation planning. In this study, we evaluated the spatial distribution and temporal trends of rainfall and erosivity for the Eastern Africa region during the period 1981–2016. The precipitation concentration index, seasonality index, and modified Fournier index have been analysed using 5 × 5‐km resolution multisource rainfall product (Climate Hazards Group InfraRed Precipitation with Stations). The mean annual rainfall of the region was 810 mm ranging from less than 300 mm in the lowland areas to over 1,200 mm in the highlands being influenced by orography of the Eastern Africa region. The precipitation concentration index and seasonality index revealed a spatial pattern of rainfall seasonality dependent on latitude, with a more pronounced seasonality as we go far from the equator. The modified Fournier index showed high spatial variability with about 55% of the region subject to high to very high rainfall erosivity. The mean annual R‐factor in the study region was calculated at 3,246 ± 1,895 MJ mm ha^?1 h^?1 yr^?1, implying a potentially high water erosion risk in the region. Moreover, both increasing and decreasing trends of annual rainfall and erosivity were observed but spatial variability of these trends was high. This study offers useful information for better soil erosion prediction as well as can support policy development to achieve sustainable regional environmental planning and management of soil and water resources.     

马斯克林高压的变化特征

利用历史天气图和NCEP再分析资料,普查了1980～2002年出现在华北平原地区的回流天气过程.依据500 hPa环流形势,对华北平原的回流天气形势分为两种:两槽一脊型和高纬低压带型.针对不同的天气分型对产生回流天气的动力条件、水汽来源进行了合成诊断分析.结果表明:涡度和散度的垂直分布与一般的降水过程不同,低层存在辐散和反气旋环流;自东北南下经渤海回流到华北平原的空气是比较干的.该文分析结果有助于预报业务人员了解回流天气,提高华北回流天气的预报准确率.     

吉林省浑江市幅1∶50 000水系沉积物测量原始数据集

吉林省浑江市幅1∶50 000水系沉积物测量共采集1961件水系沉积物样品, 采样粒级为-10目~+80目, 平均采样密度为5.1个/km²。采用发射光谱法(AES)、泡沫塑料吸附石墨炉原子吸收分光光谱法(GFAAS)、原子荧光法(AFS)及等离子体质谱法(ICP-MS)分析了Au、Ag、Cu、Pb、Zn、As、Sb、Bi、Hg、W、Sn、Mo、Cd、Co、Cr、Ni 等16种元素, 形成吉林省1∶50 000浑江市幅水系沉积物测量原始数据集。数据集包含有1961件样品以及其16元素的原始数据表1个(Excel), MapGIS格式图集1套(含有1张矿产地质图、1张采样点位图、16张单元素地球化学图、16张单元素异常图)。通过本数据集新发现单元素地球化学异常403处, 综合异常24处, 结合地质、物探、化探、遥感及已有成矿线索圈定金矿找矿靶区3处、铜及多金属找矿靶区2处。本文数据集为该区域提供了一套基础性的数据资源, 为基础地质及其他领域应用提供基础地球化学依据。     

基于四种再分析资料的1988-2015年中国近海月均风速特征评估

This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.     

Argo光盘数据集的研制与应用

早期的Argo数据光盘主要基于文件系统的数据管理,都没有提供对查询结果的保存和打印功能,更没有引入数据库系统对浮标数据进行综合管理.文中针对Argo数据共享和分发过程中存在的不足,特别是Argo光盘数据集所存在的问题,提出了改进方法.并引进数据库技术对Argo光盘数据集进行了补充和完善:提出了使用Winrar压缩软件对光盘数据资料进行压缩,从而解决了日益增加的Argo数据与光盘容量有限的矛盾,可以更好的满足Argo数据分发和共享的需求.为了充分发挥Argo光盘数据集的功能,文中还针对Argo资料用户对图形文件的需求,利用VC++和Matlab混合编程的方法,开发了Argo视图软件.最后,基于数据库技术研制完成了一张包含了1997-2006年全球海洋上全部Argo剖面浮标观测的Argo光盘数据集,并系统介绍了该数据集的结构、功能和应用过程等.     

Comparison of surface wind stress characteristics over the Tropical Atlantic (10°N–40°S) in fields derived from the UWM/COADS, NCEP/NCAR and QuikSCAT datasets

A comparison of monthly wind stress derived from winds of NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis and UWM/COADS (The University of Wisconsin-Milwaukee/Comprehensive Ocean-Atmosphere Data Set) dataset (1950–1993), and of NCEP/NCAR reanalysis and satellite-based QuikSCAT dataset (2000–2006), is made over the South Atlantic (10°N–40°S). On a mean seasonal scale, the comparison shows that these three wind stress datasets have qualitatively similar patterns. Quantitatively, in general, from about the equator to 20°S in the mid-Atlantic the wind stress values are stronger in NCEP/NCAR data than those in UWM/COADS data. On the other hand, in the Intertropical Convergence Zone (ITCZ) area the wind stress values in NCEP/NCAR data are slightly weaker than those in UWM/COADS data. In the South Atlantic, between 20° S–40°S, the QuikSCAT dataset presents complex circulation structures which are not present in NCEP/NCAR and UWM/COADS data. The wind stress is used in a numerical ocean model to simulate ocean currents, which are compared to a drifting-buoy observed climatology. The modeled South Equatorial Current agrees better with observations between March–May and June–August. Between December–February, the South Equatorial Current from UWM/COADS and QuikSCAT experiments is stronger and more developed than that from NCEP/NCAR experiment. The Brazil Current, in turn, is better represented in the QuikSCAT experiment. Comparison of the annual migration of ITCZ at 20° and 30°W in UWM/COADS and NCEP/NCAR data sources show that the southernmost position of ITCZ at 30°W in February, March and April coincides with the rainy season in NE Brazil, while the northernmost position of ITCZ at 20°W in August coincides with the maximum rainfall of Northwest Africa.