A Study of the Extended-range Forecast for the Low Frequency Temperature and High Temperature Weather over the Lower Reaches of Yangtze River Valley in Summer

Based on the observational data, the variations of Intraseasonal Oscillation (ISO) of the daily temperatures and its relationships to the high temperature in summer over the lower reaches of the Yangtze River Valley (LYRV) were studied for the period of 1979-2011. It is found that the daily temperatures over LYRV in May-August was mainly of periodic oscillations of 1525, 3060 and 6070 days, and the interannual variation of the intensity of its 3060-day oscillation had a strongly positive correlation with the number of days with daily highest temperature over 35 ℃ in July-August. Low frequency components of daily temperature in the LYRV, and the principal components of the Eastern Asian 850 hPa low frequency temperature, over a time period ranging from 1979 to 2000, were used to establish the Extended Complex Autoregressive model (ECAR) on an extended-range forecast of the 3060-day low frequency temperature over the LYRV. A 11-year independent real-time extended-range forecast was conducted on the extended-range forecast of low frequency component of the temperature over the LYRV in May-August, for the period ranging from 2001 to 2011. These experimental results show that this ECAR model, which is based on a data-driven model, has a good forecast skill at the lead time of approximately 23 days, with a forecast ability superior to the traditional autoregressive (AR) model. Hence, the development and variation of the leading 3060-day modes for the Eastern Asian 850 hPa low frequency temperatures and temporal evolutions of their relationships to low frequency components of the temperature over the LYRV in summer are very helpful in predicting the persistent high temperature over the LYRV at a 20 to 25 days lead.     

IPCC AR6报告解读：极端天气气候事件变化

与IPCC第五次评估报告（AR5）相比,在第六次评估报告（AR6）评估中,观测的极端天气气候事件变化证据,特别是归因于人为影响的证据加强。人类活动造成的气候变化已影响到全球每个区域的许多极端天气气候事件。随着未来全球变暖进一步加剧,预估极端热事件、强降水、农业生态干旱的强度和频次以及强台风（飓风）比例等将增加,越罕见的极端天气气候事件,其发生频率的增长百分比越大。这些结论再次凸显了应对气候变化和极端天气气候事件的必要性和紧迫性。     

承德市臭氧污染气象条件预报方法研究

利用2014-2016年承德市环境监测站和气象站的数据,分析了气象条件对承德市O₃-8h浓度的影响,探讨了臭氧污染气象条件的预报方法。结果表明：4-7月是承德市O₃-8h浓度较高的月份,O₃浓度的日变化特征为午后浓度高而夜间浓度低;O₃污染的天气形势为500 hPa受高压脊和偏西气流影响,850 hPa有强暖平流和20℃以上的高温,地面受低压前部和高压后部之间的偏南气流影响;有利于O₃-8h出现高浓度的气象因子为日平均气温大于23℃、日最高气温大于28℃、日平均海平面气压995-1007 hPa、日平均水汽压18-28 hPa、偏南风大于1 m·s^-1。利用气象因子综合评分建立臭氧污染指数,与O₃-8h浓度的相关系数高达0.7553,说明臭氧污染指数能较好地预报臭氧污染天气。     

河西走廊东部一次霜冻天气过程成因及其对农业的影响

2016年5月15日清晨河西走廊东部发生区域性强霜冻天气,对农林业生产造成了2004年以来最为严重的灾害。本文利用实时MICAPS常规观测资料、物理量场和河西走廊东部区域内6个国家自动气象观测站和93个区域气象站观测资料,对这次冻害天气过程的天气学成因进行分析,在此基础上分析了霜冻对农业的影响。结果表明强冷空气爆发是造成冻害的直接原因;0 cm地面温度和气温≤0 ℃持续时间长,导致农林作物深度冻伤;前期气温偏高使得农林作物发育期提前,加之霜冻出现时间偏迟,农林作物抵抗冻害的能力明显下降,冻害影响加重;冻害发生后,温度急剧上升、湿度迅速减小,作物水分强烈蒸腾,作物细胞失去受损,导致受灾程度加重。     

我国华东与西南县域主要气象敏感性疾病变化特征及其医疗费用研究

摘要：针对目前医疗费用不断上涨的现实问题,基于安徽省阜南县和贵州省锦屏县相关医疗机构的全部住院数据和气象资料,首先分析两县疾病谱特征,然后从季节和24节气角度,分析两县主要气象敏感性疾病（因天气和气候异常变化而诱发或加重的相关疾病）住院人次和医疗费用的变化特征以及人体舒适度对当地主要气象敏感性疾病发病的影响。结果表明,阜南县和锦屏县人群中住院人数最多的疾病分别是循环和呼吸系统两大类气象敏感性疾病,医疗费用最高的前六位疾病都包含循环、呼吸和消化系统疾病,其三者医疗费用总和分别占两县总医疗费用的44.9%和45.8%,因此,从降低医疗费用的角度来看加强这三类主要气象敏感性疾病的预防十分重要。此外,三种系统疾病医疗费用呈现出明显的季节变化特征：其中,循环系统疾病的医疗费用在季节转换期间明显高于各季节内,呼吸系统疾病冬春季的医疗费用远高于夏秋季节,消化系统疾病夏季医疗费用最高。两县9月的体感温度最接近人体最佳舒适温度,而此时上述三类疾病的住院人次及医疗费用也是相对低点。此研究结果可为当地相关疾病的适时防控、有效降低医疗费用提供科学依据。     

Development of Artificial Intelligence Technology in Weather Forecast

Numerical weather prediction, which is the major basis of current weather forecast, has some shortcomings, such as the understanding of the law of atmospheric motion, the assimilation and application of observation data, the expression of model physics, etc., leading to the forecast error of weather. The rapid development of artificial intelligence technology in recent years provides a new possibility for the advancement and innovation of weather forecast. In this paper, the background of the development of artificial intelligence, the current situation of the application of artificial intelligence technology to weather forecast and the future development trend are mainly described to account for this possibility. After that, the idea for development of weather forecast technology based on the integration of artificial intelligence and numerical forecast is put forward. Particularly, this study stresses that, in order to advance the AI algorithm of weather forecast in the future, it is requested to focus on the nonlinear and chaotic characteristics of atmospheric motion leading to the uncertainty of forecast. Starting from the essence of mathematics and physics, we need to realize the hybrid modeling of mathematics and physics, not only to establish the framework of input-output mapping, but also to provide solutions to the bottleneck problems of weather forecast.     

1904～1907年拉萨气候特征再分析

通过对以《有泰拉萨天气日志》为主的历史文献资料的深入挖掘 ,作者分析了 1 90 4年 2月 9日～ 1 90 7年 4月 1 7日拉萨的气候特征 :气候温暖 ,暖冬现象显著 ,而且 1 90 5年气温高于 1 90 4年 ;干旱气候占主导地位 ,间有多雨期 ;天气多变 ,多风 ,有雾 ;水灾、雪灾、干旱等自然灾害严重。拉萨与全球同时段的气候变化大体一致。     

Application of the hydrologic visibility concept to estimate rainfall measurement quality of two planned weather radars

This paper presents a practical application of the “hydrologic visibility” concept to select the future site of two planned weather radars of the French national network ARAMIS. This selection was realised by simulating the errors in radar rainfall measurement due to interactions of the radar beam with relief, and to the vertical variation of the radar reflectivity with altitude. Results show the interest of these simulations to optimise the radar location according to the objectives of radar coverage. Beyond these results, this paper highlights aspects interesting for hydrology: this type of simulation can be used to assess the radar measurement quality before initiating a quantitative exploitation of radar data, and before making a comparison or a combination with rain gauge data.     

A data-based regional scale autoregressive rainfall-runoff model: a study from the Odra River

This paper aims to compare the performances of multivariate autoregressive (MAR) techniques and univariate autoregressive (AR) methods applied to regional scale rainfall-runoff modelling. We focus on the case study from the upper and middle reaches of the Odra River with its main tributaries in SW Poland. The rivers drain both the mountains (the Sudetes) and the lowland (Nizina Śląska). The region is exposed to extreme hydrologic and meteorological events, especially rain-induced and snow-melt floods. For the analysis, four hydrologic and meteorological variables are chosen, i.e., discharge (17 locations), precipitation (7 locations), thickness of snow cover (7 locations) and groundwater level (1 location). The time period is November 1971–December 1981 and the temporal resolution of the time series is of 1 day. Both MAR and AR models of the same orders are fitted to various subsets of the data and subsequently forecasts of discharge are derived. In order to evaluate the predictions the stepwise procedure is applied to make the validation independent of the specific sample path of the stochastic process. It is shown that the model forecasts peak discharges even 2–4 days in advance in the case of both rain-induced and snow-melt peak flows. Furthermore, the accuracy of discharge predictions increases if one analyses the combined data on discharge, precipitation, snow cover, and groundwater level instead of the pure discharge multivariate time series. MAR-based discharge forecasts based on multivariate data on discharges are more accurate than AR-based univariate predictions for a year with a flood, however, this relation is reverse in the case of the free-of-flooding year. In contrast, independently of the occurrence of floods within a year, MAR-based discharge forecasts based on discharges, precipitation, snow cover, and groundwater level are more precise than AR-based predictions.     

祁连山东部沙尘暴天气成因及气候规律分析

利用我国沙尘暴多发区 ,甘肃省祁连山东部民勤、武威等 4站建站以来近 5 0a的气象资料 ,详细分析了祁连山东部沙尘暴天气发生的成因 ,造成的危害情况及变化规律 ,指出土地沙漠化和大风是造成沙尘暴的主要原因 ,并提出沙尘暴天气的防御对策。