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Drought Dynamics From Meteorological Stress to Agricultural Impacts Using Physically-Based Remote Sensing Indices in the Horn of Africa 基于物理遥感指数的非洲之角干旱动态:从气象压力到农业影响
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-17 DOI: 10.1002/joc.70178
Nasser A. M. Abdelrahim, Shuanggen Jin

Drought significantly affects agriculture and ecology in the Horn of Africa (HOA), whereby livelihoods largely depend on rainfed farming. This study aims to analyze drought propagation and its impacts on vegetation and crop productivity, with a specific focus on recovery dynamics. Over the period 2000–2022, we developed and integrated a suite of physically based remote sensing indices, including the Drought Propagation Index (DPI), Crop Stress Index (CSI), Soil Moisture Deficit (SMD), Water Deficit Index (WDI), and Drought Recovery and Rate Index (DRRI), into a novel framework. The performance of this integrated framework was further evaluated against the conventional Standardised Precipitation Index (SPI) to validate its ability for capturing drought propagation and agricultural impacts. The findings identify the eastern and southeastern HOA as major drought hotspots, experiencing severe droughts 70%–100% of the time and exhibiting worsening temporal trends. SPI was strongly correlated with DPI (r = 0.67, p < 0.05), thus proving to be reliable. Vegetation indices showed significant reductions during droughts, while DPI positively correlated with NDVI at 0.56 and EVI at 0.54. Crop production was reduced by 30%–35% in Somalia, especially for maize and sorghum, whereas Ethiopia showed more resistance because of irrigation. The mean recovery time exceeded 2 months during the 2010 and 2016 droughts in southeastern HOA, indicating low resilience, whereas northern areas recovered faster. This framework offers practical recommendations for drought mitigation, drought-resistant crops, and adaptive resource management to deal with vulnerabilities.

干旱严重影响非洲之角(HOA)的农业和生态,那里的生计主要依赖雨养农业。本研究旨在分析干旱传播及其对植被和作物生产力的影响,并特别关注恢复动态。在2000-2022年期间,我们开发并整合了一套基于物理的遥感指数,包括干旱传播指数(DPI)、作物胁迫指数(CSI)、土壤水分亏缺指数(SMD)、水分亏缺指数(WDI)和干旱恢复和速率指数(DRRI),并将其整合到一个新的框架中。根据传统的标准化降水指数(SPI)进一步评估了这一综合框架的性能,以验证其捕捉干旱传播和农业影响的能力。结果表明,东部和东南部地区为主要干旱热点地区,70% ~ 100%的时间经历严重干旱,且时间趋势日益恶化。SPI与DPI呈强相关(r = 0.67, p < 0.05),证明其是可靠的。DPI与NDVI呈显著正相关,分别为0.56和0.54。索马里的农作物产量下降了30%-35%,尤其是玉米和高粱,而埃塞俄比亚由于灌溉而表现出更强的抗性。2010年和2016年干旱期间,HOA东南部地区的平均恢复时间超过2个月,表明恢复能力较低,而北部地区恢复较快。该框架为缓解干旱、种植抗旱作物和适应性资源管理提供了切实可行的建议,以应对脆弱性。
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引用次数: 0
Study the Impact of Intraseasonal Oscillations on Water Vapour Transport in Central Africa: The Case of 25–70 Day Oscillations 中非季节内振荡对水汽输送的影响研究:以25-70天振荡为例
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-16 DOI: 10.1002/joc.70150
Audryck Nzeudeu Siwe, Alain Tchakoutio Sandjon, Lucie A. Djiotang Tchotchou, Claudin Wamba Tchinda, Derbetini A. Vondou, Armand Nzeukou

The impact of the amplitude characteristic of the intra-seasonal oscillation (ISO) on water vapour transport is examined for the March–May (MAM) and September–November (SON) seasons. The ISO temporal indices are constructed from daily anomalies of the first two principal components of the empirical orthogonal function (EOF) applied on outgoing longwave radiation anomalies, filtered for 25–70 days. A threshold method subsequently applied to the normalised ISO amplitude using the first two EOF components is used to identify extreme events associated with ISO peaks. This allows identifying 129 (119) strong ISO events (sISOs) and 39 (40) weak ISO events (wISOs) during the MAM (SON) season. The findings revealed in MAM that, during sISO events, the southern part of the domain experiences a strengthening of the moisture convergence on the Atlantic coast, to the south-east, associated with a westerly moisture transport. In addition, sISO induces negative anomalies in the horizontal component of moist static energy (MSE) advection. wISO are characterised by a predominance of significant moisture divergence to the east of the domain and in the centre of the Congo Basin, accompanied by moisture transport from the Indian Ocean. This event generates positive moisture advection anomalies, fuelled by a zonal influx of MSE. In contrast, the two examined ISO events exhibit opposing patterns of moisture transport during the SON season. Specifically, a dipole structure emerges with divergence anomalies in the north coinciding with convergence anomalies in the south during the sISO. Analysis of the zonal components of moisture transport indicates a reinforcement during wISO events in both seasons, due to the reinforcement of the African Easterly Jet (AEJ). During wISOs, stronger low-level westerlies facilitate increased moisture import from the Atlantic Ocean. Furthermore, compared to sISO events, wISOs are associated with more intense northern and southern components of the AEJ. Finally, uncentred pattern correlation coefficients between strong and weak ISO events and the different phases of the Madden-Julian Oscillation (MJO) vary depending on the season and the specific MJO phase.

研究了3 - 5月(MAM)和9 - 11月(SON)季节内振荡(ISO)振幅特征对水汽输送的影响。ISO时间指数是由经验正交函数(EOF)的前两个主成分的日异常构建的,应用于输出长波辐射异常,过滤25-70天。阈值方法随后应用于使用前两个EOF分量的标准化ISO振幅,用于识别与ISO峰值相关的极端事件。这可以在MAM (SON)季节识别129(119)个强ISO事件(sISOs)和39(40)个弱ISO事件(wISOs)。MAM的研究结果表明,在sISO事件期间,该区域的南部经历了大西洋沿岸向东南方向的水汽辐合加强,与西风水汽输送有关。此外,湿静能平流的水平分量也出现了负异常。wISO的特征是在该区域以东和刚果盆地中心以显著的水汽辐散为主,并伴有来自印度洋的水汽输送。这一事件产生了正的水汽平流异常,由MSE纬向涌入推动。相比之下,两个检验的ISO事件在SON季节表现出相反的水汽输送模式。具体来说,在sISO期间,出现了一个偶极子结构,北方辐散异常与南方辐合异常重合。水汽输送的纬向分量分析表明,由于非洲东风急流(AEJ)的增强,两个季节wISO事件的水汽输送都有所加强。在wISOs期间,较强的低层西风带促进了从大西洋输入的水分增加。此外,与sISO事件相比,wiso与更强烈的AEJ北部和南部组成部分相关。最后,强弱ISO事件与麦登-朱利安涛动(MJO)不同阶段之间的非中心模式相关系数随季节和特定MJO阶段而变化。
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引用次数: 0
Simulated Impact of Vegetation Greening on Summer Arctic Cyclone Intensity in the Northern Eurasia Margin in WRFs WRFs中欧亚大陆北部边缘植被绿化对夏季北极气旋强度的模拟影响
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-05 DOI: 10.1002/joc.70175
Shengwang Yang, Chuhan Lu, Fei Xin, Yang Kong

With the emergence of the ‘Arctic amplification’ phenomenon in recent years, vegetation in the circum-Arctic region has exhibited significant greening trends, while summer Arctic cyclones have also shown a notable increase in both frequency and intensity. To explore the potential relationship between Arctic vegetation changes—particularly in the northern margin of the Eurasian continent (NME)—and the intensification of Arctic cyclone activity under the backdrop of accelerated Arctic warming, this study investigates the impact of vegetation greening on the intensity of summer Arctic cyclones in this region. Using GIMSS 3G+ NDVI data from 1982 to 2022, combined with the WRF numerical weather model, the analysis reveals that, compared to the 1980s, tundra regions such as the central and eastern parts of the NME experienced the most pronounced increase in vegetation, corresponding to significant warming in these areas. As temperatures rose markedly, the north–south land-sea temperature gradient in the NME intensified, enhancing atmospheric baroclinicity in coastal regions. Consequently, cyclone intensity increased accordingly. The rise in the Green Vegetation Fraction (GVF) led to an increase in the Leaf Area Index (LAI) while reducing surface albedo, allowing the surface to absorb more shortwave solar radiation. This process plays a critical role in driving the rise in near-surface temperatures and the development of cyclones.

近年来,随着“北极放大”现象的出现,环北极地区的植被呈现出明显的绿化趋势,夏季北极气旋的频率和强度也显著增加。为了探讨在北极加速变暖的背景下,北极植被变化(特别是欧亚大陆北缘)与北极气旋活动加剧之间的潜在关系,本文研究了该地区植被绿化对夏季北极气旋强度的影响。利用1982 - 2022年的GIMSS 3G+ NDVI数据,结合WRF数值天气模式,分析表明,与20世纪80年代相比,NME中部和东部等冻原地区的植被增加最为明显,对应于这些地区的显著变暖。随着气温的显著升高,东北东半球南北陆海温度梯度增强,沿海地区大气斜压性增强。因此,气旋强度相应增加。绿色植被分数(GVF)的增加导致叶面积指数(LAI)的增加,同时降低地表反照率,使地表吸收更多的短波太阳辐射。这一过程在推动近地表温度上升和气旋发展方面起着关键作用。
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引用次数: 0
Impact of Drought-Flood Abrupt Alternation on Vegetation Productivity in Karst and Non-Karst Regions of Southern China 中国南方喀斯特与非喀斯特地区旱涝突变对植被生产力的影响
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-04 DOI: 10.1002/joc.70173
Meiling Zheng, Jianyu Fu, Yan Jin, Yadong Ji, Shengkun Dong, Bingjun Liu

Drought-flood abrupt alternation (DFAA)—characterised by rapid transitions between drought and flood events—is an extreme compound natural hazard that threatens ecosystems, particularly in fragile environments such as karst regions. Soil moisture is a key indicator of surface hydrological processes, directly regulating vegetation growth and recovery. This study utilises the Standardised Soil Moisture Index (SSMI) to identify DFAA events and applies Granger causality analysis to reveal soil moisture-vegetation interactions. The impact of DFAA on vegetation productivity is quantified, with a comparative analysis between karst and non-karst regions in southern China. The results indicate that: (1) From 2000 to 2020, SSMI showed a significant upward trend. Drought-to-flood events were more frequent, intense, and longer in duration than flood-to-drought events. Both types of events also exhibited substantial spatial heterogeneity. (2) SSMI and NDVI were positively correlated, with the strongest correlation reaching 0.32 at a 60-day lag. Bidirectional causality between SSMI and NDVI was predominant, affecting 49.24% of the study area. (3) Flood-to-drought events synergistically intensified drought–flood stress, whilst drought-to-flood events mitigated stress effects. Consequently, vegetation recovery was slower after flood-to-drought events, particularly in hydrologically vulnerable karst regions.

旱涝突变(DFAA)是一种极端的复合自然灾害,威胁着生态系统,特别是在喀斯特地区等脆弱环境中,其特征是干旱和洪水事件之间的快速过渡。土壤水分是地表水文过程的关键指标,直接调节植被的生长和恢复。本研究利用标准化土壤水分指数(SSMI)识别DFAA事件,并运用格兰杰因果分析揭示土壤水分与植被的相互作用。量化了DFAA对植被生产力的影响,并对南方喀斯特和非喀斯特地区进行了比较分析。结果表明:(1)2000 - 2020年,SSMI呈显著上升趋势。干旱到洪水的事件比洪水到干旱的事件更频繁、更激烈、持续时间更长。这两种类型的事件也表现出明显的空间异质性。(2) SSMI与NDVI呈显著正相关,滞后60 d时相关性最强,达0.32。SSMI与NDVI之间的双向因果关系占主导地位,影响49.24%的研究区。③水旱事件协同加剧了旱涝胁迫,而旱涝事件则缓解了旱涝胁迫效应。因此,在水旱交替后,植被恢复速度较慢,特别是在水文脆弱的喀斯特地区。
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引用次数: 0
The Joint Occurrence Probability of Compound Drought and Heatwaves: A Copula-Based Multivariate Analysis of Duration and Severity in China 中国复合干旱和热浪联合发生概率——基于持续时间和严重程度的copula多元分析
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-03 DOI: 10.1002/joc.70176
Xin Li, Suyan Wang, Fan Wang, Ying Huang, Jiayao Li

Compound drought and heatwave (CDHW) events are complex climate extremes driven by global climate change, making it challenging to estimate their comprehensive risk using univariate statistics. To address this challenge, we construct a two-dimensional joint function based on the duration and severity of CDHWs using China as a case study, enabling assessment of joint occurrence probability under diverse scenarios. Whilst previous studies have conducted multi-dimensional risk assessments, most have focused on individual variables or examined specific aspects of drought-heatwave relationships. By simultaneously integrating duration and severity through a bivariate joint function, our approach advances this line of research and provides a comprehensive multi-dimensional framework for assessing the compound characteristics of CDHWs. The results revealed that for China as a whole, changes in the severity threshold had a greater impact on extreme CDHWs, and the joint occurrence probability of severe CDHWs (events with a duration exceeding 7 days and a severity surpassing the 80th, 90th, or 95th percentile) was more sensitive to the severity. The conditional probability rose more rapidly for short-term events (3 days) than for long-term events (5–7 days). When the duration exceeded 7 days and the severity exceeded different thresholds, the joint occurrence probability of CDHWs was within the range of 2%–6%. Amongst the different regions, the duration and severity had varying impacts on the joint occurrence probability. The extreme CDHWs in North China, Northeast China, and western Northwest China were more strongly influenced by the duration. Jianghuai, South China, Southwest China, eastern Northwest China, and the Tibetan Plateau were more prone to longer-lasting extreme CDHWs. In these areas, when CDHWs lasting more than 7 days occurred, changing the severity threshold had a greater impact on their extremity. In North China in 1997, the longest CDHW had joint return periods of over 1000 years when both duration and severity exceeded thresholds, and over 500 years when either exceeded thresholds. The findings demonstrate the variations in the impacts of duration and severity on the joint probability of CDHWs in different regions of China.

复合干旱和热浪(CDHW)事件是由全球气候变化驱动的复杂极端气候事件,利用单变量统计估计其综合风险具有挑战性。为了应对这一挑战,我们以中国为例,构建了基于cdhw持续时间和严重程度的二维联合函数,从而能够评估不同情景下的联合发生概率。虽然以前的研究进行了多维风险评估,但大多数研究都侧重于单个变量或检查干旱-热浪关系的特定方面。通过双变量联合函数同时整合持续时间和严重程度,我们的方法推进了这一研究方向,并为评估cdhw的复合特征提供了一个全面的多维框架。结果表明,从整体上看,严重阈值的变化对极端cdhw的影响较大,严重cdhw(持续时间超过7 d,严重程度超过第80、90和95百分位)的联合发生概率对严重程度更为敏感。短期事件(3天)的条件概率比长期事件(5-7天)的条件概率上升得更快。当持续时间超过7 d且严重程度超过不同阈值时,cdhw的联合发生概率在2% ~ 6%之间。在不同区域,持续时间和严重程度对联合发生概率的影响不同。华北、东北和西北西部的极端高温天气受持续时间的影响更为强烈。江淮、华南、西南、西北东部和青藏高原更容易发生持续时间较长的极端cdhw。在这些地区,当发生持续7天以上的cdhw时,改变严重程度阈值对其肢体的影响更大。1997年华北地区最长的CDHW在持续时间和严重程度均超过阈值时,联合回归周期均超过1000年,超过阈值时均超过500年。研究结果表明,持续时间和严重程度对中国不同地区cdhw联合概率的影响存在差异。
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引用次数: 0
Exploring the Efficacy of Multivariate Air Masses as a Predictor of Electricity Demand: A Case Study in the Northeastern United States 探索多变量气团作为电力需求预测器的功效:美国东北部的一个案例研究
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-02 DOI: 10.1002/joc.70170
Cameron C. Lee, Erik Tyler Smith

In many midlatitude regions, human thermal comfort and electricity demand are strongly linked via the use of heating and air conditioning. Human biometeorological research has shown that the relationship between humans and their thermal comfort is quite complex, and a multitude of different thermal comfort metrics have been developed to examine it. Based upon prior research that has shown air masses (AMs) influence human thermal comfort, herein we examine whether AMs from version 2 of the gridded weather typing classification (GWTC-2) can be used to model electricity demand anomalies in the northeastern United States. Results show that AMs are indeed significant predictors of demand, especially in the summer and winter. In summer, concurrently humid and warm conditions demand up to 77 GWh/day more electricity and are associated with a near 13-fold increase in the risk of an electricity demand spike in some months, whereas a dry-warm AM does not show any significant results. In some winter months, electricity demand rises by 39 GWh/day when a dry-cool AM occurs, with an 18× risk of an electricity demand spike. When used in modelling, the AMs are generally slightly better predictors than dry-bulb temperature, and model electricity demand with minimal bias, small errors, and explain about 94% of the variability in day-to-day electricity demand. Although this study is limited in scope, with this proof-of-concept established, future research should expand the examination of AMs in electricity demand modeling to include more geographic regions, other pertinent industry outcomes (e.g., capacity), and more advanced modeling techniques.

在许多中纬度地区,人类的热舒适和电力需求通过供暖和空调的使用紧密联系在一起。人体生物气象学研究表明,人体与其热舒适之间的关系非常复杂,并且已经开发了许多不同的热舒适指标来检查它。基于先前的研究表明气团(AMs)会影响人体热舒适,本文研究了网格天气类型分类(GWTC-2)版本2中的气团是否可以用于模拟美国东北部的电力需求异常。结果表明,AMs确实是需求的显著预测因子,特别是在夏季和冬季。在夏季,同时潮湿和温暖的条件下需要高达77千兆瓦时/天的电力,并且在某些月份电力需求峰值的风险增加了近13倍,而干燥温暖的AM则没有显示出任何显著的结果。在某些冬季月份,当干冷AM发生时,电力需求每天增加39gwh,电力需求峰值的风险为18倍。当在建模中使用时,AMs通常比干球温度稍好一些,并且以最小的偏差和较小的误差来模拟电力需求,并解释了大约94%的日常电力需求变化。虽然这项研究的范围有限,但随着概念验证的建立,未来的研究应该扩大对电力需求模型中AMs的检查,以包括更多的地理区域,其他相关的行业结果(例如,容量)和更先进的建模技术。
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引用次数: 0
Topographic Setting Drives the Imprint of the Madden–Julian Oscillation (MJO) on Tree Growth in the Northern Sierra Nevada 地形环境驱动马登-朱利安涛动(MJO)对北内华达山脉树木生长的影响
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-02 DOI: 10.1002/joc.70162
George Rhee, Diana Thatcher, Katarina Warnick, Josh Carrell, Ashleigh Ford, Jessie George, Victoria Harris, Patrick Lemis, April Radford, R. Stockton Maxwell, Grant L. Harley

Understanding how large-scale tropical climate patterns, such as the Madden–Julian Oscillation (MJO), influence tree growth is crucial for improving regional climate projections and water resource management. We investigate whether tree growth from conifer forests in the northern Sierra Nevada, United States can serve as a proxy for MJO variability. Increment cores were collected from Pinus jeffreyi (site = JSJ; n = 21) and Abies magnifica (site = JSR; n = 44) trees growing on opposite slopes, resulting in chronologies that spanned 1690–2022 and 1673–2022, respectively. We used these records to assess climate drivers of tree growth from local (e.g., temperature, precipitation, drought) to broad scales (e.g., ocean–atmosphere conditions over the Indo-Pacific, MJO indices). Both records exhibit significant correlations (p < 0.05) with local climate variables, particularly moisture availability, though with key differences in sensitivity most likely related to species-specific traits and topographic setting. As such, JSJ, positioned on a south-facing slope, has markedly stronger connections with large-scale climate drivers, including zonal (u) and meriodional (v) winds, sea-level pressure (SLP) and sea surface temperature (SST), particularly across the tropical Pacific, while the JSR (from a north-east facing slope) shows more localised responses. Notably, JSJ demonstrated significant correlations with multiple MJO indices (p < 0.01), marking the first documented link between MJO dynamics and tree-ring data, whereas no significant MJO correlations were found for JSR. We show that relationships between JSJ and early MJO phases (1–3) have strengthened in recent decades, while those with later phases (6–8) peaked in the early 2000s but have since weakened. These findings suggest that the MJO influences tree growth through its modulation of atmospheric rivers and precipitation patterns, with key shifts aligning with California's ongoing drought. This study provides the first published evidence of an MJO signal in tree rings, offering the potential to develop a novel proxy for past MJO variability. We underscore the importance of understanding tropical–extratropical climate linkages and their impact on regional ecosystems, with implications for improving climate projections and managing water resources under future climate scenarios.

PACS: 0000, 1111

MSC2000 Classification: 0000, 1111.

了解大尺度热带气候模式,如麦登-朱利安涛动(MJO)如何影响树木生长,对于改善区域气候预测和水资源管理至关重要。我们调查了美国内华达山脉北部针叶林的树木生长是否可以作为MJO变异性的代理。从生长在相对斜坡上的jeffreyi Pinus (site = JSJ; n = 21)和Abies magnifica (site = JSR; n = 44)树木中采集增量岩心,得到的年代学分别为1690-2022年和1673-2022年。我们利用这些记录来评估树木生长的气候驱动因素,从局部(如温度、降水、干旱)到大尺度(如印度洋-太平洋的海洋-大气条件、MJO指数)。两种记录都显示出与当地气候变量的显著相关性(p < 0.05),特别是水分有效性,尽管在敏感性上存在关键差异,这很可能与物种特有的特征和地形环境有关。因此,位于南向斜坡上的JSJ与大尺度气候驱动因素有明显更强的联系,包括纬向风(u)和经向风(v)、海平面压力(SLP)和海温(SST),特别是在整个热带太平洋,而JSR(来自东北面斜坡)表现出更局部的响应。值得注意的是,JSJ显示出与多个MJO指数的显著相关性(p < 0.01),这标志着MJO动态与树轮数据之间的第一个有记录的联系,而JSR没有发现显著的MJO相关性。研究表明,近几十年来,JSJ和早期MJO阶段(1-3)之间的关系得到了加强,而后期阶段(6-8)的关系在21世纪初达到顶峰,但此后减弱。这些发现表明,MJO通过调节大气河流和降水模式来影响树木生长,关键变化与加州持续的干旱一致。该研究首次提供了树木年轮中MJO信号的公开证据,为开发过去MJO变化的新代理提供了潜力。我们强调了解热带-温带气候联系及其对区域生态系统的影响的重要性,这对改善未来气候情景下的气候预测和水资源管理具有重要意义。PACS: 0000, 1111 MSC2000分类:0000,1111。
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引用次数: 0
Spatial and Temporal Patterns of Rainfall Anomalies and Their Relationship With Global Climate Indices in Rio Grande do Norte, Brazil 巴西北部大德州降水异常的时空格局及其与全球气候指数的关系
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-02 DOI: 10.1002/joc.70154
Daris Correia dos Santos, Gilmar Bristot, Josemir Araújo Neves

This study analysed the climate variability of the Rainfall Anomaly Index (RAI) and its relationship with global climate indices in Rio Grande do Norte (RN), Brazil, using monthly precipitation data from 115 weather stations (1963–2023). RN experienced significant changes in precipitation, with both positive and negative anomalies over the decades. Principal Component Analysis (PCA) revealed 12 components explaining 73.15% of the total variance, whereas the K-means algorithm identified three homogeneous regions corresponding to the state's climatology. Pearson's correlation coefficient showed that teleconnections such as the Atlantic Multidecadal Oscillation (AMO), Tropical North Atlantic (TNA), and Niño indices had a direct relationship with rainfall patterns, whereas the Global Mean Land/Ocean Temperature Index (LOTI) and Solar Flux exhibited an inverse relationship, suggesting that higher solar radiation and global temperatures are linked to fewer anomalous rains. The Niño indices showed substantial variation during extreme drought events in 1966, 1982–83, 1987–88, 1991–92, 1997–98, and 2015–16. Wavelet coherence analysis revealed interannual and interdecadal periodicities in rainfall anomalies, particularly in region R3, characterised by low rainfall and frequent droughts. The findings emphasise the importance of understanding extreme climate patterns over time to improve climate prediction and resource management in the region.

利用1963-2023年巴西115个气象站的逐月降水资料,分析了巴西北部里约热内卢地区降雨异常指数(RAI)的气候变率及其与全球气候指数的关系。近几十年来,南北极降水变化显著,既有正距平,也有负距平。主成分分析(PCA)揭示了12个分量,解释了总方差的73.15%,而K-means算法则确定了与该州气候相对应的3个均匀区域。Pearson相关系数表明,大西洋多年代际涛动(AMO)、热带北大西洋(TNA)和Niño等遥相关指数与降雨模式有直接关系,而全球平均陆地/海洋温度指数(LOTI)和太阳通量呈反比关系,表明太阳辐射和全球温度的升高与异常降雨的减少有关。1966年、1982-83年、1987-88年、1991-92年、1997-98年和2015-16年极端干旱期间Niño指数变化较大。小波相干分析揭示了降雨异常的年际和年代际周期性,特别是在降雨少、干旱频繁的R3地区。这些发现强调了了解一段时间内的极端气候模式对于改善该地区的气候预测和资源管理的重要性。
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引用次数: 0
Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach 探索海表极端温度对印度气候带极端降水的影响:一个复杂的网络方法
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-11-02 DOI: 10.1002/joc.70172
Venuthurla Manohar Reddy, Litan Kumar Ray, Velpuri Manikanta

The present study investigates the impact of Sea Surface Temperature (SST) extremes on precipitation extremes in India's six homogeneous climate regions from 1981 to 2020. A wavelet-based complex network analysis was used to explore the connections between precipitation extremes and SST extremes. The Maximum Overlap Discrete Wavelet Transform (MODWT) technique was employed for time series decomposition to identify these links across different temporal scales. Spearman correlation was then used to determine the relationships between SST extremes and precipitation extremes at the grid level. Complex networks were then constructed for each of India's climate regions, focusing on both positive and negative correlations with various global sea regions. Results reveal that precipitation extremes at shorter time scales are predominantly driven by proximal oceanic regions such as the Bay of Bengal (BOB), Arabian Sea (ARS), and Eastern Indian Ocean (EIO), reflecting strong monsoon–SST coupling through moisture convergence and synoptic convection processes. As the time scale increases, remote SST influences from the Atlantic (NAO, EAO), Pacific (EPO, NPO, SPO), and Southern Hemisphere oceans (SIO, SAO, SOO) become increasingly dominant, highlighting the role of atmospheric teleconnections, jet stream modulation, and cross-equatorial moisture transport. Interannual scales show the widest and most diverse SST control, whilst decadal-scale influence is generally weak and region-specific. The regional analysis demonstrates distinct propagation pathways of SST influence, with West Central India showing consistent multiscale sensitivity, Central Northeast and Northeast India transitioning from local to global control, and South Peninsular India retaining strong regional dominance. These insights underscore the necessity of integrating both regional and global SST indices into forecasting frameworks for improved prediction and climate adaptation strategies in India.

本文研究了1981 - 2020年印度6个均匀气候区海温极端值对降水极端值的影响。采用基于小波的复杂网络分析方法探讨了降水极端值与海温极端值之间的关系。采用最大重叠离散小波变换(MODWT)技术进行时间序列分解,在不同时间尺度上识别这些链接。然后使用Spearman相关来确定海温极值与降水极值在栅格水平上的关系。然后为印度的每个气候区域构建了复杂的网络,重点关注与各种全球海洋区域的正相关和负相关。结果表明,在较短时间尺度上,极端降水主要受孟加拉湾(BOB)、阿拉伯海(ARS)和东印度洋(EIO)等近洋区域驱动,反映了水汽辐合和天气对流过程中强烈的季风-海温耦合。随着时间尺度的增加,来自大西洋(NAO、EAO)、太平洋(EPO、NPO、SPO)和南半球海洋(SIO、SAO、SOO)的海温影响日益占主导地位,突出了大气遥相关、急流调制和跨赤道水分输送的作用。年际尺度表现出最广泛和最多样化的海温控制,而年代际尺度的影响一般较弱且具有区域特异性。区域分析表明,海温影响的传播路径不同,印度中西部表现出一致的多尺度敏感性,印度东北部中部和东北部从局部控制向全球控制过渡,印度南半岛保持强大的区域主导地位。这些见解强调了将区域和全球海温指数纳入预测框架的必要性,以改进印度的预测和气候适应战略。
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引用次数: 0
Building a High-Resolution Climate Gridded Dataset in Complex Terrain: Validating Different Methods in the Abruzzo Region in Italy 在复杂地形中建立高分辨率气候网格数据集:意大利Abruzzo地区不同方法的验证
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-10-27 DOI: 10.1002/joc.70153
Carina I. Argañaraz, Andreu Salcedo-Bosch, Simone Lolli, Gabriele Curci

Recent climate change motivates the creation of high-resolution and high-quality reference datasets of essential environmental variables as the necessary base for adaptation planning. To obtain these maps, a widely used procedure is to interpolate in situ observations, for which several different methods were developed in the past decades. In this study, we calculate gridded daily maps of precipitation and temperature at the regional scale in Abruzzo (central Italy), comparing different interpolation methods: universal kriging, radial basis function and gradient boosting forest. We validated the results against an independent set of stations from the same network used to produce the gridded dataset (1994–2013). The interpolated values were also compared with those obtained from two widely used global datasets (CHELSA and WorldClim). Universal kriging achieved the best performance, with a daily root mean square error of ~0.45 mm/day for precipitation and ~1.2°C for temperature. Seasonality affects the bias values, being larger in winter for precipitation and in summer for temperature, as well as in isolated stations in mountainous areas. Our gridded dataset (ADAMO, ~0.01° and daily resolution) shows decreased bias with respect to the global databases. There was a considerable discrepancy for precipitation (RMSE ≥ 60 mm/month for CHELSA and WorldClim, while ADAMO was 35 mm/month), and a too strong altitude effect for temperature, especially in WorldClim. Temperature increased its RMSE in summer compared to winter error, more pronounced in global datasets, while precipitation had an increase in winter with respect to summer, more evident in the ADAMO dataset. These results show that in regions with large topographic variability, the implementation of datasets with diffuse local observations is expected to be more accurate than global datasets. This is particularly relevant for fields such as climatology, ecology and biology that require climate information with high accuracy.

最近的气候变化促使创建高分辨率和高质量的基本环境变量参考数据集,作为适应规划的必要基础。为了获得这些地图,一种广泛使用的程序是插入原位观测,为此在过去几十年中开发了几种不同的方法。在本研究中,我们计算了意大利中部Abruzzo地区区域尺度的降水和温度网格日图,比较了不同的插值方法:通用克里格、径向基函数和梯度增强森林。我们针对同一网络的一组独立台站验证了结果,这些台站用于生成网格数据集(1994-2013)。还将插值值与两个广泛使用的全球数据集(CHELSA和WorldClim)的值进行了比较。通用克里格法取得了最好的效果,降水日均方根误差为~0.45 mm/d,温度日均方根误差为~1.2°C。季节性影响偏差值,冬季降水偏大,夏季气温偏大,山区孤立站偏大。我们的网格数据集(ADAMO, ~0.01°和日分辨率)相对于全球数据库显示偏差减少。降水量差异较大(CHELSA和WorldClim的RMSE≥60 mm/月,而ADAMO的RMSE为35 mm/月),海拔对温度的影响太强,尤其是WorldClim。夏季气温的RMSE比冬季误差增加,在全球数据集中更为明显,而冬季降水的RMSE比夏季增加,在ADAMO数据集中更为明显。这些结果表明,在地形变异性较大的地区,使用分散的局部观测数据集比使用全球数据集更准确。这对于需要高精度气候信息的气候学、生态学和生物学等领域尤为重要。
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引用次数: 0
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International Journal of Climatology
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