北京冬季雾霾天气下颗粒物及其化学组分的粒径分布特征研究

为探究太行山沿线城市秋冬季细颗粒物（PM2.5）污染特征,选取典型工业城市济源市为研究对象,依据不同时间段内气象因子对PM2.5小时浓度变化的影响特征、PM2.5污染等级、冬季采暖开始（2021年11月15日）前后污染物增长速率的差异等,将2021年10月至2022年3月划分为4个阶段,并运用多元线性回归模型对不同阶段PM2.5与气象因子小时数据进行分析。结果表明,第一阶段（2021年10月1日至11月14日）26.1%的PM2.5小时浓度变化由气象因子决定,单因子与PM2.5的相关性均在36%以下;第二阶段（2021年11月15日至12月31日）72.4%的PM2.5小时浓度变化由气象因子决定,风向、相对湿度、能见度3项因子对PM2.5影响显著,且PM2.5与相对湿度和能见度的相关性均达到最高（61.5%和73.1%）;第三阶段（2022年1月1～31日）53.2%的PM2.5小时浓度变化由气象因素决定,相对湿度和风速对PM2.5的小时值变化影响不显著,这与该阶段大气稳定性高、污染物与大气扩散能力双向反馈效应显著有关;第四阶段（2022年2月1日至3月31日）32.2%的PM2.5小时浓度变化由气象因素决定,受沙尘及扬尘影响,风速对PM2.5小时变化影响不显著。济源市秋冬季污染过程中颗粒物组分以NO₃⁻ 、NH₄⁺、OC、SO₄²⁻为主,其中二次无机离子（SO₄²⁻、NO₃⁻、NH₄⁺）占比在65.7%以上,二次污染严重。颗粒物组分浓度增速整体表现为NO₃⁻、S、EC、Cl⁻随污染程度加重增速减缓,SO₄²⁻、OC 、K⁺、NH₄⁺增速随污染程度加重呈现“慢快慢”的变化趋势。

     

山西2006年雨季天气气候特征分析

2005年6月17～24日,华南地区发生了连续多日的暴雨天气过程,其显著特征是存在着南北两条雨带,北支雨带(福建中北部)由准静止的梅雨锋造成,南支雨带(广东中东部)发生在锋前暖区之中,这种连续多日共存的双雨带现象引起了气象学家的广泛关注.为了探究锋面和锋前暖区暴雨的成因,加深这两类不同性质暴雨的认识,利用NCEP每6 h一次的1°×1°经纬度再分析资料以及华南地区加密观测的逐小时地面降水等资料,以此次连续多日维持的双雨带降水过程为例,详细分析了锋面附近与锋前暖湿区内暴雨系统的主要物理差异.结果发现:梅雨锋暴雨和锋前暖区暴雨不仅在中尺度雨团活动、系统动力结构、大气不稳定机制和大气加热结构等存在明显的差异,而且在水汽输送、中尺度环境以及与暴雨有关的垂直环流之间也存在着不同点,这些差异可能是造成锋前暖区暴雨难以模拟和预报的主要原因.     

南海月平均流的计算

本文用一个二维全流方程模式,计算了南海1—12月的逐月平均流。所得的南海逐月环流的总趋势以及一些中小尺度的涡旋现象不仅与海洋观测相一致,也与已有的一些研究结果相吻合。而且,计算所得的海洋场和海面起伏场均很好地反映出南海的季节性变化特征,特别是高海暖流的存在在计算中又进一步得到了证实。文中对南海海流的机理也作了一此初步探讨。     

Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG （GAMIL）

Seasonal prediction of Asian-Australian monsoon （A-AM） precipitation is one of the most important and challenging tasks in climate prediction. In this paper, we evaluate the performance of Grid Atmospheric Model of IAP LASG （GAMIL） on retrospective prediction of the A-AM interannual variation （IAV）, and determine to what extent GAMIL can capture the two major observed modes of A-AM rainfall IAV for the period 1979-2003. The first mode is associated with the turnabout of warming （cooling） in the Nifio 3.4 region, whereas the second mode leads the warming/cooling by about one year, signaling precursory conditions for ENSO.
We show that the GAMIL one-month lead prediction of the seasonal precipitation anomalies is primarily able to capture major features of the two observed leading modes of the IAV, with the first mode better predicted than the second. It also depicts the relationship between the first mode and ENSO rather well. On the other hand, the GAMIL has deficiencies in capturing the relationship between the second mode and ENSO. We conclude： （1） successful reproduction of the E1 Nifio-excited monsoon-ocean interaction and E1 Nifio forcing may be critical for the seasonal prediction of the A-AM rainfall IAV with the GAMIL; （2） more efforts are needed to improve the simulation not only in the Nifio 3.4 region but also in the joining area of Asia and the Indian-Pacific Ocean; （3） the selection of a one-tier system may improve the ultimate prediction of the A-AM rainfall IAV. These results offer some references for improvement of the GAMIL and associated seasonal prediction skill.     

南、北半球环状模月内活动的主要时间尺度

基于“大气环状活动带” 的概念, 利用逐日再分析资料对南、 北半球环状模 (简称SAM、 NAM) 的季节活动特征及月内活动的主要时间尺度 (Submonthly timescales) 进行了研究, 结果表明, NAM具有冬季强、 夏季弱的年循环特征, 而SAM则表现出明显的准半年循环特征。并且, 逐年的功率谱分析进一步显示: NAM的月内活动的主要时间尺度以准1周和准2周为主, 且它们具有共生性, 准3周为相对次要的周期; 而SAM的月内活动周期与NAM相似, 准2周和准1周较强, 准3周次之。NAM和SAM的月内活动在不同特征时间尺度上的空间特征及其时间演变值得进一步研究。     

Testing the Ability of Numerical Model to Simulate Climate and Its Change With 4D-EOF Analysis

The four-dimensional empirical orthogonal function (4D-EOF), which in reality is a simple combination of three-dimensional EOF (3D-EOF) and extended EOF (EEOF), is put forward in this paper to test the ability of numerical model to simulate climate and its change. The 4D-E0F analysis is able to reveal not only the horizontal characteristic pattern of analyzed variable, and its corresponding annual and inter-annual variations, but also the vertical structural characteristics. The method suggested is then used to analyze the monthly mean 100-, 500-, 70G-, and 1000-hPa geopotential height fields (4941 grids and grid spacing 60 km) and their anomaly fields in 1989-1998 simulated by the MM5V3 from the RMIP (Regional Climate Model Inter-comparison Project for East Asia)-II, as well as their counterparts (used as the observed fields) from the NCEP/NCAR re-analysis dataset in the same period. The ability of MM5V3 in simulating East Asian climate and its change is tested by comparing the 4D-EOF analysis results of the simulated and observed datasets. The comparative analyzed results show that the horizontal pattern of the first eigenvector of the observed monthly mean geopotential height fields and its vertical equivalent barotropic feature were well simulated; the simulations of the first two eigenvectors of the observed monthly mean geopotential height anomaly fields were also successful for their horizontal abnormal distributions and significant equivalent barotropic features in the vertical were well reproduced; and furthermore, the observed characteristics, such as the variation with height, the annual and inter-annual variations of the monthly mean geopotential height/anomaly fields were also well reflected in the simulation. Therefore, the 4D-EOF is able to comprehensively test numerical model's ability of simulating the climate and its change, and the simulation ability of MM5V3 for the climate and its change in East Asia in the 1990s was satisfactory.     

THE IMPACT OF NOAA SATELLITE SOUNDING DATA ON THE SYSTEMATIC FORECAST ERROR OF B-MODEL

This paper is to examine the impact of satellite data on the systematic error of operational B-model in China.Em-phasis is put on the study of the impact of satellite sounding data on forecasts of the sea level pressure field and 500 hPaheight.The major findings are as follows.(1)The B-model usually underforecasts the strength of features in the sea level pressure(SLP)field,i.e.pressuresare too low near high pressure systems and too high near low pressure systems.(2)The nature of the systematic errors found in the 500 hPa height forecasts is not as clear cut as that of the SLPforecasts,but most often the same type of pattern is seen,i.e.,the heights in troughs are not low enough and those inridges are not high enough.(3)The use of satellite data in the B-model analysis/forecast system is found to have an impact upon the model'sforecast of SLP and 500 hPa height.Systematic errors in the vicinity of surface lows/500 hPa troughs over the oceansare usually found to be significantly reduced.A less conclusive mix of positive and negative impacts was found for allother types of features.     

新冠肺炎流行病学模型的最优参数化

现如今,新冠肺炎(COVID-19)严重威胁着世界各国人民的生命健康.许多流行病学模型已经被用于为政策制定者和世界卫生组织提供决策参考.为了更加深刻的理解疫情趋势的变化特征,许多参数优化算法被用于反演模型参数.本文提议使用结合了高斯-牛顿法和梯度下降法的Levenberg-Marquardt(LMA)算法来优化模型参数...     

Impact of land–sea thermal contrast on interdecadal variation in circulation and blocking

The impact of asymmetric thermal forcing associated with land–sea distribution on interdecadal variation in large-scale circulation and blocking was investigated using observations and the coupled model intercomparison project outputs. A land–sea index (LSI) was defined to measure asymmetric zonal thermal forcing; the index changed from a negative to a positive anomaly in the 1980s. In the positive phase of the LSI, the 500 hPa geopotential height decreased in the polar regions and increased in the mid-latitudes. The tropospheric planetary wave activity also became weaker and exerted less easterly forcing on the westerly wind. These circulation changes were favorable for westerly wind acceleration and reduced blocking. In the Atlantic, the duration of blocking decreased by 38 % during the positive LSI phase compared with that during the negative phase; in Europe, the number of blocking persisting for longer than 10 days during the positive LSI phase was only half of the number during the negative phase. The observed surface air temperature anomaly followed a distinctive “cold ocean/warm land” (COWL) pattern, which provided an environment that reduced, or destroyed, the resonance forcing of topography and was unfavorable for the development and persistence of blocking. In turn, the responses of the westerly and blocking could further enhance continental warming, which would strengthen the “cold ocean/warm land” pattern. This positive feedback amplified regional warming in the context of overall global warming.     

A multi-model study of atmosphere predictability in coupled ocean–atmosphere systems

Of great importance for guiding numerical weather and climate predictions, understanding predictability of the atmosphere in the ocean − atmosphere coupled system is the first and critical step to understand predictability of the Earth system. However, previous predictability studies based on prefect model assumption usually depend on a certain model. Here we apply the predictability study with the Nonlinear Local Lyapunov Exponent and Attractor Radius to the products of multiple re-analyses and forecast models in several operational centers to realize general predictability of the atmosphere in the Earth system. We first investigated the predictability characteristics of the atmosphere in NCEP, ECMWF and UKMO coupled systems and some of their uncoupled counterparts and other uncoupled systems. Although the ECMWF Integrated Forecast System shows higher skills in geopotential height over the tropics, there is no certain model providing the most precise forecast for all variables on all levels and the multi-model ensemble not always outperforms a single model. Improved low-frequency signals from the air − sea and stratosphere − troposphere interactions that extend predictability of the atmosphere in coupled system suggests the significance of air − sea coupling and stratosphere simulation in practical forecast development, although uncertainties exist in the model representation for physical processes in air − sea interactions and upper troposphere. These inspire further exploration on predictability of ocean and stratosphere as well as sea − ice and land processes to advance our understanding of interactions of Earth system components, thus enhancing weather − climate prediction skills.