由于对地形地貌特征、临界雨量、汇流时间和重现期等洪水特征因子的认识不足，干旱半干旱地区中小流域的洪水预报准确率有待提高。因此，本文选取甘肃省夏河县（位于半干旱区）和永昌县（位于干旱区）为研究对象，对夏河县（2015年）86个沿河村落的34个小流域和永昌县（2014年）395个沿河村落的240个过水断面的洪水特征要素进行了野外调查，并采用“铁一院”法、瞬时单位线法和地区经验公式法计算了两个区域的汇流时间、设计暴雨和设计洪水，推算了洪水预警值。然后基于计算结果，采用机器学习方法（线性回归、随机森林和神经网络），建立了针对干旱和半干旱地区的洪水预警模型，并对各模型进行了评价分析。结果表明，准备转移雨量与暴雨时程分配、临界雨量和主沟比降之间存在线性相关性，且线性回归模型能较准确地计算预警降雨量。为进一步验证回归模型适用性，使用该模型反演分析甘肃省合作市34个调查流域的准备转移雨量，平均绝对误差仅为0.56 mm。

为构建准确的干旱预测模型，选择具有物理意义的预测因子和采用高效的预测方法至关重要。与传统预测技术相比，机器学习算法因其高效性和可靠性，在气候预测中被广泛应用。本文基于1960—2022年湖北省70个国家气象站逐月气象要素数据，以及国家气候中心与美国国家海洋和大气管理局提供的大气环流和海温指数，采用标准化降水蒸散指数判断是否干旱作为目标变量，运用特征选择方法筛选出11个指数作为输入变量。在此基础上，分别使用分类回归树和随机森林两种机器学习算法，构建了湖北省夏季干旱预测模型。随机选取47 a数据作为训练集，并利用剩余16 a数据作为测试集，对预测结果进行检验。结果表明，分类回归树和随机森林模型对干旱是否发生的预测准确率分别为88%和81%。此外，两种算法建模时均将亚洲纬向环流指数列为最重要的变量，表明该指数在湖北省夏季干旱预测中具有关键作用。通过构建两种机器学习算法预测模型，为湖北省夏季干旱预测提供了客观有效的新思路，对湖北省防旱减灾具有重要意义。

California has experienced devastating autumn wildfires in recent years. These autumn wildfires have coincided with extreme fire weather conditions during periods of strong offshore winds coincident with unusually dry vegetation enabled by anomalously warm conditions and late onset of autumn precipitation. In this study, we quantify observed changes in the occurrence and magnitude of meteorological factors that enable extreme autumn wildfires in California, and use climate model simulations to ascertain whether these changes are attributable to human-caused climate change. We show that state-wide increases in autumn temperature (∼1 °C) and decreases in autumn precipitation (∼30%) over the past four decades have contributed to increases in aggregate fire weather indices (+20%). As a result, the observed frequency of autumn days with extreme (95th percentile) fire weather—which we show are preferentially associated with extreme autumn wildfires—has more than doubled in California since the early 1980s. We further find an increase in the climate model-estimated probability of these extreme autumn conditions since ∼1950, including a long-term trend toward increased same-season co-occurrence of extreme fire weather conditions in northern and southern California. Our climate model analyses suggest that continued climate change will further amplify the number of days with extreme fire weather by the end of this century, though a pathway consistent with the UN Paris commitments would substantially curb that increase. Given the acute societal impacts of extreme autumn wildfires in recent years, our findings have critical relevance for ongoing efforts to manage wildfire risks in California and other regions.

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.

The purpose of this paper is to quantify climatic controls on the area burned by fire in different vegetation types in the western United States. We demonstrate that wildfire area burned (WFAB) in the American West was controlled by climate during the 20th century (1916–2003). Persistent ecosystem‐specific correlations between climate and WFAB are grouped by vegetation type (ecoprovinces). Most mountainous ecoprovinces exhibit strong year‐of‐fire relationships with low precipitation, low Palmer drought severity index (PDSI), and high temperature. Grass‐ and shrub‐dominated ecoprovinces had positive relationships with antecedent precipitation or PDSI. For 1977–2003, a few climate variables explain 33–87% (mean = 64%) of WFAB, indicating strong linkages between climate and area burned. For 1916–2003, the relationships are weaker, but climate explained 25–57% (mean = 39%) of the variability. The variance in WFAB is proportional to the mean squared for different data sets at different spatial scales. The importance of antecedent climate (summer drought in forested ecosystems and antecedent winter precipitation in shrub and grassland ecosystems) indicates that the mechanism behind the observed fire–climate relationships is climatic preconditioning of large areas of low fuel moisture via drying of existing fuels or fuel production and drying. The impacts of climate change on fire regimes will therefore vary with the relative energy or water limitations of ecosystems. Ecoprovinces proved a useful compromise between ecologically imprecise state‐level and localized gridded fire data. The differences in climate–fire relationships among the ecoprovinces underscore the need to consider ecological context (vegetation, fuels, and seasonal climate) to identify specific climate drivers of WFAB. Despite the possible influence of fire suppression, exclusion, and fuel treatment, WFAB is still substantially controlled by climate. The implications for planning and management are that future WFAB and adaptation to climate change will likely depend on ecosystem‐specific, seasonal variation in climate. In fuel‐limited ecosystems, fuel treatments can probably mitigate fire vulnerability and increase resilience more readily than in climate‐limited ecosystems, in which large severe fires under extreme weather conditions will continue to account for most area burned.

The time fluctuations of forest fires occurring in Basilicata, a region situated in Southern Italy, between 2004 and 2023 were investigated using various analytical approaches. Analysis revealed a clustering of fire occurrences over time, as indicated by a significantly high coefficient of variation. This suggests that the fire sequence does not follow a Poisson distribution and instead exhibits a clustered structure, largely driven by the heightened frequency of events during the summer seasons. The analysis of monthly forest fire occurrences and total burned area indicates a significant correlation between the two. This correlation is reinforced by shared patterns, notably an annual cycle that appears to be influenced by meteorological factors, aligning with the yearly fluctuations in the region’s weather conditions typical of a Mediterranean climate. Furthermore, the relationship between the Standardized Precipitation Evapotranspiration Index (SPEI) and forest fires revealed that the accumulation period of the SPEI corresponds to the cycle length of the fires: longer cycles in fire occurrences align with higher accumulation periods in SPEI data.

Recent fire seasons have fueled intense speculation regarding the effect of anthropogenic climate change on wildfire in western North America and especially in California. During 1972–2018, California experienced a fivefold increase in annual burned area, mainly due to more than an eightfold increase in summer forest‐fire extent. Increased summer forest‐fire area very likely occurred due to increased atmospheric aridity caused by warming. Since the early 1970s, warm‐season days warmed by approximately 1.4 °C as part of a centennial warming trend, significantly increasing the atmospheric vapor pressure deficit (VPD). These trends are consistent with anthropogenic trends simulated by climate models. The response of summer forest‐fire area to VPD is exponential, meaning that warming has grown increasingly impactful. Robust interannual relationships between VPD and summer forest‐fire area strongly suggest that nearly all of the increase in summer forest‐fire area during 1972–2018 was driven by increased VPD. Climate change effects on summer wildfire were less evident in nonforested lands. In fall, wind events and delayed onset of winter precipitation are the dominant promoters of wildfire. While these variables did not change much over the past century, background warming and consequent fuel drying is increasingly enhancing the potential for large fall wildfires. Among the many processes important to California's diverse fire regimes, warming‐driven fuel drying is the clearest link between anthropogenic climate change and increased California wildfire activity to date.