中国区域温度和降水不同空间插值方法精度对比

利用国家气象信息中心基于最优插值法(Optimal Interpolation,OI)、ANUSPLIN插值法(AV 2.0)、普通克里格法(Ordinary Kriging,OK)的1.0°×1.0°与0.5°×0.5°格点化的1961—2004年中国区域月温度和月降水资料及1961—2004年美国NCDC的GHCN 5.0°×5.0°月降水资料,对中国大陆地区温度和降水不同插值方法空间插值数据的精度及时间序列进行了对比研究。结果表明:在1961—2004年平均气候态下,中国区域不同插值法插值后的降水和温度空间分布型较一致,年循环变化也较一致。在中国区域、东部区域和西部区域,OI与AV 2.0方法插值的降水场绝对误差分别为2.15 mm、1.28 mm和0.00 mm,OK与AV 2.0方法插值的温度场绝对误差分别为0.20℃、0.05℃和0.45℃。对于中国区域降水场时间序列,AV 2.0和OI方法插值的降水与GHCN不同季节的降水变化趋势较一致,且不同插值方法插值的夏季降水量差异较大,冬季降水量差异较小。1961—2004年AV 2.0与OI方法插值的降水场相关系数在0.22—0.98之间变化,冬季和春季降水场相关性较高,夏季和秋季降水场相关性较低;个别年份秋季和冬季插值后降水量的偏差稍大,最大偏差达3.08 mm,1961—2004年平均降水量偏差为0.64 mm。AV 2.0与OK方法插值的年平均温度差值小于0.54℃,且多年时间序列变化趋势较一致。     

基于ANUSPLIN软件的逐日气象要素插值方法应用与评估

气象要素是资源、环境、灾害以及全球变化等领域研究的数据基础,格点化数据在未来研究应用中显得日益重要。本文基于中国境内667个基本和基准地面气象观测站点的基本气象资料,使用ANUSPLIN专用气候插值软件对1961-2006年逐日气温、降水进行插值,并利用未参与插值的全国1667个加密站点对插值结果的准确性进行检验,同时与反向距离权重法和普通克吕格法等插值方法的结果进行对比。结果表明,利用667个站点使用ANUSPLIN软件进行逐日平均气温插值有92.0%的误差在2.0℃以内,75.0%的误差在1.0℃以内,0.9%的误差在5.0℃以上,平均绝对误差为0.8℃;对逐日降水进行插值,75.0%的误差小于5.0mm,85%的误差小于10.0mm,平均绝对误差为6.4mm,误差大小与降水量呈现出正相关性,对局地强降水的插值效果不好,这可能与参与局部拟合插值的样本数太少有关;同时,夏季的温度插值误差小于冬季,而冬季的降水误差小于夏季。将ANUSPLIN的局部薄盘样条插值结果分别与反向距离权重法和普通克吕格法的插值结果进行对比,显示ANUSPLIN软件的插值误差最小。结果同样表明,适当增加站点数量和提高DEM精度可进一步提高ANUSPLIN软件的插值精度。     

复杂地形下浙江夏季气候要素空间插值方法评价

利用1988—2017年浙江省68个国家气象观测站气温和降水数据,分别采用ANUSPLIN、反距离加权(IDW)和普通克里格(O-kriging)3种方法,估算夏季平均气温和降水量空间插值。同时,应用交叉验证方法评价3种方法的精度差异,并进行空间误差分析,探讨符合浙江复杂地形条件和气候背景下的气象要素空间插值最优方法。结果表明:(1)3种方法对气温和降水的插值精度总体接近,空间分布较为一致,但对于要素空间异质性大的区域,ANUSPLIN在细节上的表现明显优于IDW和O-kriging方法。(2)ANUSPLIN对气温和降水的插值精度均高于IDW和O-kriging,气温的平均绝对误差(MAE)和均方根误差(RMSE)均小于0.5℃,其中气温RMSE表现为:ANUSPLIN(0.381℃)O-kriging(0.459℃)IDW(0.463℃)。降水RMSE表现为:ANUSPLIN(37.8 mm)O-kriging(42.2 mm)IDW(49.1 mm)。(3)平原地区的平均气温插值误差低于山区;降水误差空间分布沿海地区误差最大,出现明显低估值。总体来说,ANUSPLIN更适合浙江复杂地形条件和气候背景下的气象要素空间插值处理。     

基于逐时降水站点资料空间插值方法对比研究

自动站降水资料的格点化是目前气象业务及研究亟需解决的问题,空间插值方法是数据格点化最直接有效的方法。本文选取3个降水个例分别作为大范围强降水、大范围弱降水和局地强对流3种类型降水的典型代表,采用8种常用的插值方法,设计3组试验,通过交叉检验对比8种插值方法降水的插值效果及站点密度对插值效果的影响。结果表明:高密度站点试验表明(站点平均距离约为9.0 km),8种插值方法降水的插值效果依次为CR、IW、NN、LP、KR、TL、MQ和SP,8种插值方法之间的差异小于样本间的差异,即插值效果主要取决于站点的分布而不是插值的方法。低密度站点试验表明(站点平均距离约为30.0 km),大范围降水个例(包括大范围强降水和大范围弱降水)插值的均方根误差(Root Mean Square Error,RMSE)显著增大,不同插值方法之间的差异也增大;而局地强对流个例中,插值后均方根误差增大幅度较小,不同插值方法之间的差异较小。利用CR、IW和NN等3种插值方法开展站点密度敏感性试验,试验表明站点密度提高有利于减小降水插值误差,但站点平均距离达13.0 km甚至更密时,降水误差减小的趋势变缓。     

基于ANUSPLIN的京津冀区域逐日气温格点数据集建立方法研究

为建立一个高精度、高空间分辨率的逐日气温格点数据集,满足公共气象服务对于精确信息及实时信息的需要,利用2018年6—8月京津冀区域以及临近省区共3 974个国家级及区域气象观测站质控后的逐日气温资料,采用ANUSPLIN软件对逐日气温数据进行空间内插,得到了京津冀区域逐日气温格点数据集（0.01°×0.01°）,并分别利用反距离权重插值法、普通克里金插值法、样条函数法对逐日气温数据进行空间插值,采用相关系数（Corr）、平均绝对误差（MAE）、平均相对误差（MRE）等作为评估指标来检验插值精度。结果表明：1）ANUSPLIN软件满足了空间插值对精度及曲面平滑度的要求,能直观体现京津冀区域气温由北向南递增的空间分布特征;2）4种插值方法中,基于ANUSPLIN软件的插值结果最优,相关系数平均达0.97,其样本误差在1 ℃之内占比为90.59%,MAE为0.46 ℃,MRE为1.81%;3）插值误差较大的区域位于冀北高原、燕山丘陵及太行山脉一带,高海拔、低站点密度等是造成插值误差的主要原因。基于ANUSPLIN插值方法建立的逐日气温格点数据集具有分辨率高、空间插值误差小的优势,ANUSPLIN对气温的空间分布具有较好的预测能力。     

基于Shepard和OI方法对雨量计逐时资料的分析

引入地形影响效应的日降水量气候分析场,分别运用Shepard和最优插值(OI)两种插值方法对广东和广西2007年5月20日—8月30日汛期小时雨量计降水量进行插值,得到0.125°×0.125°分辨率的规范化网格资料。结果表明:无论是直接插值还是用降水比率(地形影响效应的日降水量气候分析场)插值,两种方法均能很好地体现广东和广西雨量计站点观测降水的季内变化和日变化特征。虽然用直接插值方法比用降水比率插值方法得到的降水空间分布更为平滑,但估值精度没有用降水比率插值方法高。通过交叉检验进一步表明,总体上OI方法优于Shepard方法,而考虑地形影响效应的降水比率OI方法为最优,能有效提高相关性,并减少均方根误差和系统误差。     

近38年中国气温和降水的1 km网格数据集

对中国38年的气温和降水进行了空间插值分析,选取最优模型去生成1km网格数据集,为中国大陆的植被分布、气候变化和环境生态等研究提供支持。基于国家气象中心839个气象站的逐日气温和降水数据,用经度、纬度和海拔作为ANUSPLIN软件插值的3个变量,对降水进行开平方预处理,采用3次样条的薄盘光滑样条法,得到了1980—2017年中国大陆月平均气温和月累计降水1km网格插值数据集。数据集的广义交叉验证均方根(RTGCV)和均方根误差(RMSE)具有年周期性和明显的季节变化特征;各站点的平均误差(MBE)的频率分布近似正态分布,绝对误差(MAE)的空间分布也符合中国大陆气候的变化特征。数据集在精准度和时间序列上较新,且提供公共下载服务,可为全国陆地生态系统的研究提供信息支持。     

基于局部薄盘光滑样条函数的重庆地区气温空间插值

利用薄盘光滑样条函数的曲面拟合程序ANUSPLIN和数字高程模型（DEM）,对2017年12月31日21时至2018年12月31日20时重庆1 000个台站的气温要素进行空间插值,结果显示：以经、纬度为函数自变量,海拔高度为协变量,样条次数为2的三变量局部薄盘光滑样条函数作为插值方案,实现了对站点稀少的山脉地带气温的插值估算,且插值结果明显表现出气温随高度的梯度变化;从独立性检验结果可以看出,插值气温的平均绝对误差和均方根误差分别为069 ℃和078 ℃,相关系数为0995,说明研究所采用的气温插值方案对重庆是适用的。     

黑河流域降水统计——动力降尺度问题研究

依据区域气候模式RIEMS2.0输出的3 km高分辨率数据和站点降水记录分析了中国西北黑河流域降水的动力降尺度和统计—动力降尺度问题,检验了多种因子组合下多元线性回归（MLR）和贝叶斯模式平均（BMA）降尺度模型,评估了降尺度降水的均方根误差、相关系数、方差百分率及“负降水”偏差率等方面的统计特征。结果表明,动力降尺度降水相关系数最高,误差也最大,降水方差达到观测值的1.5～2倍;除相关系数外,统计—动力降尺度模型的几个统计特征均最优,纯统计模型次之。检验表明,仅用700 hPa位势高度场、经向风和比湿等构建的统计降尺度模型估计的站点降水相关系数较低,均方根误差也较大。当在统计降尺度模型中引入模式降水因子后站点降水的估计得到明显改善,其中MLR类模型的降水相关系数和方差百分率均明显高于BMA类模型,均方根误差二者相当,但前者“负降水”出现频次明显大于后者,“负降水”偏差主要出现在降水稀少的冬半年及黑河中、下游干旱或极端干旱区,上游出现频率较低,其中MLR类模型“负降水”出现频次明显高于BMA类模型,后者仅出现在黑河中、下游地区。包含模式降水因子的统计—动力降尺度模型能减少“负降水”出现...     

国家级格点实况分析产品在江苏地区的适用性评估分析

利用国家级格点实况分析资料与地面气象站实况数据,采用误差分析、技巧评分等方法评估了2017年7月至2018年6月逐时的格点实况产品在江苏地区的地面2 m气温、2 m相对湿度、10 m风和降水要素的一致性和准确性,同时采用MODE检验方法对格点降水产品空间分布偏差进行了分析。结果表明:2 m气温格点实况与自动站观测基本一致,平均绝对误差在0.5~0.8℃,均方根误差在0.8℃左右,其中日最高气温误差较小。格点实况和自动站2 m相对湿度之间的平均绝对误差在5%左右,均方根误差在6%~7%,表现出较高的准确性和稳定性。格点实况10 m风向准确率达到70%左右,而风速准确率仅为56%,与气象站点观测相比有明显差异。格点降水产品的全年有无降水准确率为90%~98%,对于晴雨检验存在带来较大影响的可能。格点实况产品对小雨级别降水的准确率最高,随着降水量级增大,格点实况降水场相比站点观测存在较多的降水漏报,因此,对于降水分量级检验还不适合用格点实况场来替代气象站点观测。设计了一种基于空间形态的降水准确率评分方法对降水空间落区进行检验,格点实况降水场的空间形态准确率评分在0.9左右,较准确地反映了实际降水空间分布。因而,格点实况数据在江苏平原地区都有较高的精度,误差在可接受的范围内,基本可以代替自动站观测作为预报和模式检验的真实实况场,但也存在以下几个方面的问题:(1)格点2 m气温、2 m相对湿度产品在江苏的丘陵地带误差较大,降水产品在海岛气象站准确性较低;(2)格点降水产品一定程度地弱化了大雨以上量级降水强度;(3)格点实况风速产品误差较大,与业务服务需求有一定差距。     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.