GTS1型数字式电子探空仪基值测定过程中故障分析及处理

对探空仪施放前最重要的工作——基值测定中出现的问题及成因作出阐述,通过实例提出相应的应对措施,从而为各地在进行高空综合探测时提供参考。     

乌鲁木齐及周边城市空气质量变化特征及影响因素分析

利用美英等国5个海气耦合气候模式对黑龙江省(主要包括哈尔滨、齐齐哈尔、牡丹江和佳木斯4个地区)年、季平均气温前后近100 a进行模拟和预测结果,预估黑龙江省哈尔滨、齐齐哈尔、牡丹江和佳木斯4个城市气候变暖情景下未来100 a的采暖降温气候条件.可以为黑龙江省适应未来气候变化提供依据,为政府决策和能源公司做长远规划提供参考.     

编纂《气象志》的四大原则

由于了解气象国情的需要,近年来我国各省、市、自治区气象局,都在负责编纂《气象志》。《气象志》作为《地方志》的专志之一,是《地方志》编纂工作的创举,责任重大但缺乏经验。虽各地曾提出过编写专志的普遍原则,但并未提出过编写《气象志》的特殊原则。而此项特殊原则系编《气象志》所不可或缺的。为适应此项需要,本文特阐述编纂《气象志》的四个总体大原则,即时代先进性原则、志实原则、统属原则和体例原则。至于编纂《气象志》的一些具体原则,如叙事原则、供资原则、存史原则、传人原则及著录原则等将另文阐述。     

Interannual variability of the sea surface salinity and its related freshwater flux in the tropical Pacific: A comparison of CMIP5 and CMIP6

This paper assesses the interannual variabilities of simulated sea surface salinity (SSS) and freshwater flux (FWF) in the tropical Pacific from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). The authors focus on comparing the simulated SSS and FWF responses to El Niño–Southern Oscillation (ENSO) from two generations of models developed by the same group. The results show that CMIP5 and CMIP6 models can perform well in simulating the spatial distributions of the SSS and FWF responses associated with ENSO, as well as their relationship. It is found that most CMIP6 models have improved in simulating the geographical distribution of the SSS and FWF interannual variability in the tropical Pacific compared to CMIP5 models. In particular, CMIP6 models have corrected the underestimation of the spatial relationship of the FWF and SSS variability with ENSO in the central-western Pacific. In addition, CMIP6 models outperform CMIP5 models in simulating the FWF interannual variability (spatial distribution and intensity) in the tropical Pacific. However, as a whole, CMIP6 models do not show improved skill scores for SSS interannual variability, which is due to their overestimation of the intensity in some models. Large uncertainties exist in simulating the interannual variability of SSS among CMIP5 and CMIP6 models and some improvements with respect to physical processes are needed.摘要通过比较CMIP5和CMIP6来自同一个单位两代模式模拟, 表明CMIP5和CMIP6均能较好地模拟出热带太平洋的海表盐度 (SSS) 和淡水通量 (FWF) 对ENSO响应的分布及其响应间的关系. 与CMIP5模式相比, 大部份CMIP6模式模拟的SSS和FWF年际变化分布均呈现改进, 特别是纠正了较低的中西太平洋SSS和FWF变化的空间关系. 但是, 整体上, CMIP6模式模拟的SSS年际变化技巧没有提高, 与SSS年际变率的强度被高估有关. CMIP5和CMIP6模式模拟SSS的年际变化还存在较大的不确定性, 在物理方面需要改进.     

中国近海海平面变化趋势的对比分析

本文分析了近40年的中国近海验潮站资料海表面高度的线性变化趋势,并与卫星高度计资料进行了对比。通过对验潮站资料的分析发现,中国海域无论是近40年(1970~2013年)、还是近20年(1993~2013年)海平面均显著上升。各海区近20年的海平面上升有加速的趋势,且各时段上升速率大于全球平均海平面上升率。但是,受到海平面的年际和年代际变化的影响,近10年海平面上升趋势放缓。同时,本文也分析了不同季节海平面变化的趋势,北部海域秋季最大,冬季最小;南海海域春季最大,秋季最小。通过AVISO资料和验潮站资料的对比可以发现,AVISO资料在描述近20年海平面变化的线性趋势上与验潮站资料接近,较大的差异主要是由验潮站地表发生升降引起的。同时,通过对比也发现了用验潮站资料估算海域平均的海平面高度变化会有一定的误差,在黄海、渤海、东海海域验潮站估计的数值偏高,而在南海海域则偏低。     

慢特征分析法在气象上的应用进展

气候系统具有非平稳特征,根本原因在于其外强迫随时间发生改变,因此外部驱动力的分析对于理解气候系统的动力学特征至关重要,而如何有效提取系统外部驱动信息是一个亟待解决的前沿科学问题。最近几年,在生物神经学领域中应用的一种提取非平稳信号中外强迫信息的方法——慢特征分析法(Slow Feature Analysis,SFA),在气象领域中也得到了初步成功的尝试,结果显示出此方法对气候系统的外强迫信息分析及有关动力学机制的探究有较好的应用前景。本文主要介绍SFA方法的理论思想及实施步骤,并通过一个理想的非平稳时间序列检验其提取外强迫信息的能力,结果证明在衰减的Logistic模型中,可利用SFA算法提取出模型中的外强迫,且与真实外强迫的相关系数可达0.99;此外,还介绍将该方法应用于Arosa臭氧时间序列,分析其提取的外强迫信息的动力学特征;并介绍了在气候时间序列建模中引入外强迫因子的预测效果。     

基于GRAPES四维变分的静止轨道微波观测系统模拟试验研究

地球静止轨道微波观测同时具有高频次、大视场和穿透云雨的全天候观测能力,因此中国在规划第二代静止轨道气象卫星“风云四号”系列时已经明确提出对静止轨道微波观测的需求。基于中国候选的50、118、183、380和425 GHz五频段静止轨道微波辐射计载荷方案,开展了地球静止轨道微波观测系统模拟试验,理解其观测时间分辨率、频段选取和观测误差对台风预报的影响。试验基于GRAPES全球四维变分同化系统,同化静止轨道微波模拟观测资料,以2018年台风“玛利亚”和“山竹”为例分析了静止轨道微波资料同化对台风预报的影响。试验结果表明,对于静止轨道微波资料同化应用,提高观测资料的时间分辨率、增加通道数量和降低噪声水平能够有效提升台风数值预报性能。      

A model for retrieval of dual linear polarization radar fields from model simulation outputs

An algorithm for retrieving polarimetric variables from numerical model fields is developed. By using this technique, radar reflectivity at horizontal polarization~ differential reflectivity, specific differential phase shift and correlation coefficients between the horizontal and vertical polarization signals at zero lag can be derived from rain, snow and hail contents of numerical model outputs. Effects of environmental temperature and the melting process on polarimetric variables are considered in the algorithm. The algorithm is applied to the Advanced Regional Prediction System （ARPS） model simulation results for a hail storm. The spatial distributions of the derived parameters are reasonable when compared with observational knowledge. This work provides a forward model for assimilation of dual linear polarization radar data into a mesoscale model.     

西藏色齐拉山地区立体气候特征初步分析

利用西藏色齐拉山地区不同海拔高度的8个自动站和3个实测气象站1年的近地面观测资料,分析了该地区气温、地温、降水量、湿度和风速等气象要素的季节变化特征,探讨了东、西坡局地气候特征差异形成的原因。结果表明：色齐拉山地区1月为最冷月、7月为最暖月;月平均最高气温、最低气温与平均气温的季节变化一致。气温日较差大年较差小。年平均气温直减率东、西坡分别为0．54℃／100m和0．73℃／100m,西坡大于东坡。地气温差冬季西坡大于东坡,夏季东坡大于西坡。年、月平均地温直减率西坡仍大于东坡;东坡除夏季7、8月份外,地温直减率小于气温直减率;西坡除冬季（12月和1月）,地温直减率大于气温直减率。降水量东坡比西坡多,海拔2500m以上地区4～10月降水总量随着海拔高度的升高呈增加趋势,增加率为20．9mm／100m。空气相对湿度冬季低夏季高,年变化呈单峰型。东、西坡冬季风速较强夏季相对较弱,初春风速最大。东、西坡气候差异与海拔高度、坡向、下垫面性质有关。     

Variability of Atlantic Meridional Overturning Circulation in FGOALS-g2简

The variability of Atlantic Meridional Overturning Circulation （AMOC） in the pre-industrial control experiment of the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 （FGOALS-g2） was investigated using the model outputs with the most stable state in a 512-yr time window from the total 1500-yr period of the experiment. The period of AMOC in FGOALS-g2 is double peaked at 20 and 32 years according to the power spectrum, and 22 years according to an auto-correlation analysis, which shows very obvious decadal variability. Like many other coupled climate models, the decadal variability of AMOC in FGOALS-g2 is closely related to the convection that occurs in the Labrador Sea region. Deep convection in the Labrador Sea in FGOALS-g2 leads the AMOC maximum by 3-4 years. The contributions of thermal and haline effects to the variability of the convection in three different regions [the Labrador, Irminger and Greenland-Iceland- Norwegian （GIN） Seas] were analyzed for FGOALS-g2. The variability of convection in the Labrador and Irminger Seas is thermally dominant, while that in the colder GIN Seas can be mainly attributed to salinity changes due to the lower thermal expansion. By comparing the simulation results from FGOALS-g2 and 11 other models, it was found that AMOC variability can be attributed to salinity changes for longer periods （longer than 35 years） and to temperature changes for shorter periods.