Predicted changes in fire weather suggest increases in lightning fire initiation and future area burned in the mixedwood boreal forest

Forecasting future fire activity as a function of climate change is a step towards understanding the future state of the western mixedwood boreal ecosystem. We developed five annual weather indices based on the Daily Severity Rating (DSR) of the Canadian Forest Fire Weather Index System and estimated their relationship with annual, empirical counts of lightning fire initiation for 588 landscapes in the mixedwood boreal forest in central-eastern Alberta, Canada from data collected between 1983 and 2001 using zero-inflated negative binomial regression models. Two indices contributed to a parsimonious model of initiation; these were Seasonal Severity Rating (SSR), and DSR-sequence count. We used parameter estimates from this model to predict lightning fire initiation under weather conditions predicted in 1 × CO₂ (1975–1985), 2 × CO₂ (2040–2049) and 3 × CO₂ (2080–2089) conditions simulated by the Canadian Regional Climate Model (CRCM). We combined predicted initiation rates for these conditions with existing empirical estimates of the number of fire initiations that grow to be large fires (fire escapes) and the fire size distribution for the region, to predict the annual area burned by lightning-caused fires in each of the three climate conditions. We illustrated a 1.5-fold and 1.8-fold increase of lightning fire initiation by 2040–2049 and 2080–2089 relative to 1975–1985 conditions due to changes in fire weather predicted by the CRCM; these increases were calculated independent of changes in lightning activity. Our simulations suggested that weather-mediated increases in initiation frequency could correspond to a substantial increase in future area burned with 1.9-fold and 2.6-fold increases in area burned in 2040–2049 and 2080–2089 relative to 1975–1985 conditions, respectively. We did not include any biotic effects in these estimates, though future patterns of initiation and fire growth will be regulated not only by weather, but also by vegetation and fire management.     

Assessing the impact of weather and climate in Australia

Weather and climate have a significant impact on the Australian society and environment. While the impacts of major changes in the Australian climate likely to occur from the enhanced greenhouse effect have been reported in the literature fewer studies have addressed the impact of the climate's natural variability. Ways in which weather and climate and its variability impact on the decision making process are described and methods available to assess the sensitivity of the economy and the natural environment are also presented. Methods which are being developed to determine the value of weather and climate information to decision makers are briefly described. The El Niño Southern Oscillation is a strong contributor to the variability of the Australian climate. It is used to illustrate the impact of climate variability on both the economy and natural environment of Australia. Finally, the extent to which there is political awareness of the impact of climate variability on the Australian society and environment is briefly examined.     

江西省天气预报员现状调查分析与对策建议

随着研究型业务和智能网格预报技术的不断深入,天气预报员的作用也将发生较大调整或转型.文中采用问卷调查方式,围绕学历、职称、预报业务与科研等方面总结了江西省、市、县三级预报员的现状,分析了当前预报员在业务发展中存在的问题与不足,提出了推进预报业务流程改革,进一步优化预报员队伍,坚持科技创新与研究型业务建设,加强团队建设与预报员岗位培训等优化人才队伍的对策建议.     

夏季湖北电网气象敏感负荷预测模型研究

利用2009-2010年湖北电网日用电负荷资料和气象资料,提出了基于电网负荷的分解算法,将电网日最大负荷分解为基础负荷与气象敏感负荷2个主要分量.其中,气象敏感负荷与气温、相对湿度及风速的综合气象敏感负荷条件指数相关.提出了基于权重指数的湖北省面平均气象敏感负荷条件指数的算法.利用相关比法,分析了湖北省气象敏感负荷与面均气象敏感负荷条件指数的非线性关系.基于均方偏差最小原理和非线性最小二乘法,建立了夏季湖北电网气象敏感负荷与面均气象敏感负荷条件指数的多项式预测关系模型.经2010年9月模型应用检验表明,预测平均误差低于6％.该模型可用于夏季湖北省电力专业气象服务工作.     

Projection of fire potential to future climate scenarios in the Alpine area: some methodological considerations

In Europe, wildfires are an issue not only for the Mediterranean area, but also in the Alpine regions in terms of increasing number of events and severity. In this study we evaluate the impact of climate change on the fire potential in the Alps in the past and in future scenarios. The Fine Fuel Moisture Code (FFMC) of the Canadian Forest Fire Danger Rating System, which successfully distinguishes among recorded fire/no fire events, is applied to projections of Regional Climate Models (RCMs) calculated on the SRES scenario A1B. We compare two different techniques: 1) a single model run of the COSMO-CLM RCM at 18 km resolution, and 2) a combination of 25-km resolution RCMs from the ENSEMBLES project, combined with the Multimodel SuperEnsemble technique and a new probabilistic Multimodel SuperEnsemble Dressing. The single-model RCM allows for a greater coherence among the input parameters, while the Multimodel techniques permit to reduce the model biases and to downscale to a higher resolution where long term records of observations are available. The projected changes with the Multimodel in the scenario give an estimation of increasing wildfire potential in the mid XXI century. In particular the frequency of severe wildfire potential days is shown to increase dramatically. The single (independent) COSMO model gives a weaker signal and in some regions of the study area the predicted changes are opposite to the ones by the Multimodel. This is mainly due to increasing precipitation amounts simulated especially in the northern parts of the Alps. However, there are also some individual models included in the Multimodel ensemble that show a similar signal. This confirms the ambiguity of any impact study based on a single climate model due to the uncertainty of the projections of the climate models.     

安龙"4.15"瓦斯爆炸与天气条件分析

煤矿井内瓦斯爆炸需要具备一定条件：井内存在毒瓦斯、并有相当的浓度，有触发火源，环境气象要素差（压、温、湿、通风等）。通过安龙“4．15”瓦斯爆炸前天气及气象要素分析，为研究煤矿瓦斯爆炸提供“粗线条”式的气象因素参考，为减少煤矿安全生产事故提供参考。     

Future heat vulnerability in California, Part I: projecting future weather types and heat events

Excessive heat significantly impacts the health of Californians during irregular but intense heat events. Through the 21st century, a significant increase in impact is likely, as the state experiences a changing climate as well as an aging population. To assess this impact, future heat-related mortality estimates were derived for nine metropolitan areas in the state for the remainder of the century. Here in Part I, changes in oppressive weather days and consecutive-day events are projected for future years by a synoptic climatological method. First, historical surface weather types are related to circulation patterns at 500mb and 700mb, and temperature patterns at 850mb. GCM output is then utilized to classify future circulation patterns via discriminant function analysis, and multinomial logistic regression is used to derive future surface weather type at each of six stations in California. Five different climate model-scenarios are examined. Results show a significant increase in heat events over the 21st century, with oppressive weather types potentially more than doubling in frequency, and with heat events of 2?weeks or longer becoming up to ten times more common at coastal locations.     

Use of regionalisation approach to develop fire frequency curves for Victoria,Australia

It is important to perform fire frequency analysis to obtain fire frequency curves (FFC) based on fire intensity at different parts of Victoria. In this paper fire frequency curves (FFCs) were derived based on forest fire danger index (FFDI). FFDI is a measure related to fire initiation, spreading speed and containment difficulty. The mean temperature (T), relative humidity (RH) and areal extent of open water (LC2) during summer months (Dec–Feb) were identified as the most important parameters for assessing the risk of occurrence of bushfire. Based on these parameters, Andrews’ curve equation was applied to 40 selected meteorological stations to identify homogenous stations to form unique clusters. A methodology using peak FFDI from cluster averaged FFDIs was developed by applying Log Pearson Type III (LPIII) distribution to generate FFCs. A total of nine homogeneous clusters across Victoria were identified, and subsequently their FFC’s were developed in order to estimate the regionalised fire occurrence characteristics.     

最优化方法在天气预报中的应用

本文根据最优化方法原理,提出了选择非线性最优预报因子和建立非线性预报方程的办法。试验表明:用此方法选出来的非线性预报因子和建立的方程比线性的好。最后还指出了此方法可推广到预报量离散的情况,建立非线性的判别方程,同时可用于长、中、短期天气预报。     

Impact of climate and socioeconomic changes on fire carbon emissions in the future: Sustainable economic development might decrease future emissions

Fires and their associated carbon and air pollutant emissions have a broad range of environmental and societal impacts, including negative effects on human health, damage to terrestrial ecosystems, and indirect effects that promote climate change. Previous studies investigated future carbon emissions from the perspective of response to climate change and population growth, but the compound effects of other factors like economic development and land use change are not yet well known. We explored fire carbon emissions throughout the 21st century by changing five factors (meteorology, biomass, land use, population density, and gross domestic product [GDP] per capita). Compared to the historical period (2006–2015), global future fire carbon emissions decreased, mainly caused by an increase in GDP per capita, which leads to improvement in fire management and capitalized agriculture. We found that the meteorological factor has a strong individual effect under higher warming cases. Fires in boreal forests were particularly expected to increase because of an increase in fuel dryness. Our research should help climate change researchers consider fire-carbon interactions. Incorporating future spatial changes under diverse scenarios will be helpful to develop national mitigation and adaptation plans.     

秋季林火成因及人工增雨效果分析

针对爱辉区2001年秋季森林大火，分析其成因，提出了人工增雨的防灾手段，并对其效果及发展前景进行了分析。     

The stochastic weather model in the system of deterministic and stochastic modeling of runoff and nutrient load

The estimation is carried out of the distribution functions of annual runoff and nutrient load on the Russian part of the Gulf of Finland (the Baltic Sea) formed by different pollution sources. The stochastic weather model is used for the estimation.