匹配域投影降尺度方法在黄河流域夏季降水预测中的应用

文章采用黄河流域夏季降水数据和BCC-CGCM模式资料,利用匹配域投影降尺度方法对黄河流域夏季降水进行预测,得到以下结论:(1)交叉验证期,匹配域投影降尺度方法对黄河流域夏季降水的预测效果要好于原始模式预测,且较模式直接输出的要素预测稳定;分月预测比夏季整体预测效果要好。(2)匹配域投影降尺度方法对各个区域的预测能力不同,在夏季(6—8月)预测中,预测较好区域比较分散,而分月预测中,预测较好的区域比较集中。月份不同,降尺度方法对于不同地区的预测能力也不同。(3)2009—2013年的独立样本检验表明,匹配域投影降尺度方法对于黄河流域夏季降水的预测效果要明显好于模式直接输出的要素预测。尤其6和7月的降尺度预测较模式直接输出的要素预测有较大提高。     

春季海温对中国夏季降水影响的诊断研究和预测试验

文中利用季降水异常集合的典型相关预测模式 ,以全球春季 (3～ 5月 )海温场作为因子场 ,对中国夏季降水场进行了诊断研究 ,并对 1998,1999及 2 0 0 0年这几个典型的中国夏季降水进行了回报试验。结果表明 ,春季海温与中国夏季降水之间存在较好的关系 ,春季海温在较大程度上决定了中国夏季降水雨带及其分布类型。考虑面积因子的集合典型相关预测方案对中国夏季降水具有较强的回报能力 ,此模式不仅能诊断出降水场和海温场中一些比较典型的空间模态和时间变化规律 ,而且可以再现 1998和 2 0 0 0年中国大部分地区的旱涝灾害。揭示了全球春季海温的异常变化在中国夏季 (6～ 8月 )降水异常中的作用。     

匹配域投影降尺度方法在河南省夏季降水预测中的应用及检验

根据河南省夏季降水数据和BCC-CGCM、ECMWF-SYSTEM4模式资料,利用匹配域投影降尺度方法对河南省夏季降水进行预测,结果表明:1)匹配域投影降尺度方法对河南省夏季降水具有较好的预测能力,且较原始模式稳定。除了河南省中部地区外,其他大部分地区的Ps评分都在60分以上。2)在交叉验证期,两个模式的降尺度预测Ps评分分别比原始模式的提高了20.2%和16.3%,但ECMWF-SYSTEM4模式降尺度预测的平均分达到了71.2分,较BCC-CGCM模式的降尺度预测平均分偏高1.6分。在交叉验证期的26年中,有62%以上的年份,降尺度预测方法都对原始模式有正的订正技巧。3)2009—2013年的独立样本检验表明,匹配域投影降尺度方法比原始模式预测Ps评分提高了40%左右,表明该降尺度方法对夏季降水具有较好的预测能力。4)该方法可以在业务上应用,图形界面程序的研发,更方便了业务应用。     

基于BCC第二代短期气候预测模式系统的中国夏季降水季节预测评估

利用BCC第二代气候预测模式系统1996-2015年提前1～3个月的回报试验结果,评估了模式在季节尺度上预测中国夏季降水空间分布和降水异常的能力,分析了模式预报效果的年际差异,并探讨了模式预测误差产生的可能原因。结果表明,模式对中国夏季降水的季节预测具有一定的技巧,西南至长江中下游南部、黄淮平原西部、东北北部及藏北高原等地区季节预测技巧较高,同时,模式对降水距平预报效果整体较好,其中在长江中下游、黄淮地区、华南地区、西北地区及东北北部距平符号一致率较高。而模式对降水季节预测的偏差主要表现为我国东部降水量强度预测偏小,对夏季降水异常的预报技巧有限,且不同年份模式的预测效果差异较大。模式对夏季西太平洋及印度洋高海温区范围预测偏小,对副热带高压和东亚地区低层水汽辐合的强度预测偏弱,从而导致风场与环流场的配置与观测不一致,使得模式对我国东部夏季降水预测显著偏少。从模式预测效果年际差异来看,当华南地区实况降水量偏多、长江中下游及东北地区降水量偏少时,模式具有较高的预测技巧,反之,模式的预报技巧较低。分析中国东部降水与海温的相关关系发现,夏季西北太平洋、热带西太平洋和北印度洋是影响中国东部夏季降水的关键区域,模式中西北太平洋海温偏低对模式预报技巧具有重要影响,海温场、高度场、风场及水汽通量散度场不同的相互配置导致中国东部夏季降水的分布及强度差异,而模式不能合理把握各物理量场间相互作用过程,从而影响模式的预报效果。因此,改进模式对外强迫因子与降水异常相关关系的预测能力是提高我国夏季降水季节预测技巧的主要途径。     

应用IAP9L-AGCM对2002年中国夏季气候的预测及效果检验

利用中科院大气所9层大气环流格点模式(IAP9L—AGCM)和IAP—ENSO预测系统对2002年中国夏季气候进行实时集合预测及其检验。结果显示，IAP9L—AGCM较好地预测出了2002年夏季我国大范围旱涝的分布形势，如华南、我国西部多雨，黄河和长江流域之间大范围干旱等；850hPa减弱的夏季风、青藏高原辐散中心以及北太平洋上空的异常气旋性环流中心亦被较好地预报出来；不足的是，模式对降水异常细致分布的预测能力有限。预测结果还表明，该模式对夏季(6—8月)平均降水的预报技巧要高于月平均状况，且月平均预报的准确度从6—8月依次递减。     

CWRF降尺度提高BCC_CSM1.1m对中国夏季降水跨季度动力预测能力

利用CWRF模式(Climate-Weather Research and Forecasting model)对国家气候中心BCC_CSM1.1m业务预测模式短期气候预测结果进行中国区域降尺度,并使用1991—2010年3—8月逐日气温降水观测数据评估预测能力。结果表明:CWRF预测地面2 m气温、降水气候平均态的空间分布比BCC_CSM1.1m更接近观测,分布误差更小;在保持总体技巧不低于BCC_CSM1.1m的同时,CWRF对我国华东和华中地区的降水年际变化预测准确率更高;对不同强度的降水预测CWRF表现均优于BCC_CSM1.1 m模式,尤其在极端降水预测准确率上更优。总之,得益于更高的空间分辨率和优化的低空物理过程模拟,CWRF降尺度可以提高中国夏季跨季度降水预测能力。     

应用耦合模式进行2003年度气候预测试验

利用中国科学院大气物理研究所IAP/LASG GOALS 4.0耦合模式,引进外强迫因子(温室气体、太阳活动及硫酸盐气溶胶)变化的影响后进行了2003年度集合预测试验研究.结果表明:GOALS耦合模式预测出了2003年夏季淮河流域的降水正异常,也较好地描述了中国区域大气环流场的变化.说明GOALS 4.0耦合模式在我国的短期气候预报业务中具有一定的预测能力.但该版模式分辨率还嫌太粗,无法细致地描述我国区域的降水分布.     

基于聚类分区的中国夏季降水预测模型

文章基于近邻传播客观聚类方法对中国夏季降水进行了气候分区,以中国不同分区的夏季降水为预测对象,使用前期的海温和海平面气压场为预测因子,利用图像标签算法提取高相关封闭区域的预测因子信息。结合最小二乘回归法建立预测模型。采用Ps评分、距平符号一致率和距平相关系数三种评分方法检验了该预测模型,比较了四种不同的因子配置方案的预测能力。研究结果表明,利用冬春季海温的演变特征结合海平面气压的年际变化为预测因子的分区预测模型效果较好,在1982—2009年期间的平均交叉检验平均Ps得分为81.4,距平符号一致率为63%,距平相关系数为0.35,2010—2014期间的独立样本预测检验的平均评分分别为77.1,58%和0.19,且逐年回报效果较为稳定,表明该方法对中国夏季降水有较好的预测效果。研究结果显示,该预测模型能较好地预测出2014年中国夏季降水南多北少的分布特征。     

基于LSTM网络的中国夏季降水预测研究

基于BCC-CSM季节气候预测模式系统历史回报数据和国家气象信息中心提供的中国地面降水月值数据,通过多方法对比并讨论了影响预测结果的因素,利用长短期记忆（Long Short-Term Memory,LSTM）网络预测2014年和2015年中国夏季降水。结果表明:LSTM网络的预测效果较逐步回归、BP神经网络及模式输出结果有一定优势。参数调优对于LSTM网络预测效果影响较大,重要参数有隐含层节点数、训练次数和学习率。选择合适的起报月份数据有助于提升季节预测的准确性,利用4月起报的数据预测夏季降水效果较好。海冰分量因子对降水季节预测有正贡献。在2014年、2015年夏季降水回报试验中,LSTM网络对降水整体形势有一定的预测能力,Ps评分分别为74分、71分,距平符号一致率分别为55.63%、55.25%,Ps评分的均值高于同期全国会商及业务模式。     

黄淮地区夏季降水的统计降尺度预测

利用1991-2011年黄淮地区夏季降水、NCEP/NCAR再分析资料和国家气候中心第2代动力气候模式（BCC_CSM1.1m）夏季回报结果,研究黄淮地区夏季降水降尺度预测模型和可预报性来源。诊断发现,黄淮地区夏季降水与同期南亚高压、乌拉尔山附近阻塞高压、西风急流、西太平洋赤道上空200 hPa纬向风场呈明显正相关。分析BCC_CSM1.1m对夏季环流的回报结果发现,模式对200 hPa和500 hPa位势高度场、200 hPa纬向风场和850 hPa经向风场上影响黄淮地区夏季降水的部分关键区域有较好的模拟能力。利用模式预报技巧较高且对黄淮地区夏季降水的影响有物理含义的环流特征作为预测因子,对比预测因子进行独立性筛选前后分别建立的降尺度预测模型发现,黄淮地区夏季降水预测与实况的距平符号一致率由61%提高到72%。预测技巧来源分析发现,降尺度预测能力与BCC_CSM1.1m对影响黄淮地区夏季降水的3个关键因子乌拉尔山附近环流、南亚高压、西太平洋赤道上空西风强弱的预测技巧密切相关,尤其是模式对西太平洋赤道上空西风的模拟能力起到决定性作用。     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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.     

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.     

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