Search Results (14)

Due to global warming, extreme temperature events have become increasingly prevalent, posing significant threats to both socioeconomic development and human safety. While previous studies have extensively examined the influence of individual climatic circulation systems on extreme temperature, the combined effects of multiple concurrent circulation patterns remain poorly understood. Using daily temperature data from 29 meteorological stations in Chongqing (1960–2019), this study employs linear trend analysis, correlation analysis, and random forest (RF) models to analyze spatiotemporal variations in the intensity and frequency of extreme temperature. We selected 21 climate indicators from three categories—atmospheric circulation, sea surface temperature (SST), and sea-level pressure (SLP)—to identify the primary drivers of extreme temperatures and quantify their respective contributions. The key findings are as follows: (1) All extreme intensity indices exhibited an increasing trend, with the TXx (annual maximum daily maximum temperature) showing the higher trend (0.03 °C/year). The northeastern region experienced the most pronounced increases. (2) Frequency indices also displayed an upward trend. This was particularly evident for the TD35 (number of days with maximum temperature ≥35 °C), which increased at an average rate of 0.16 days/year, most notably in the northeast. (3) The Western Pacific Subtropical High Ridge Position Index (GX) and Asia Polar Vortex Area Index (APV) were the dominant climate factors driving intensity indices, with cumulative contributions of 26.0% to 33.4%, while the Western Pacific Warm Pool Strength Index (WPWPS), Asia Polar Vortex Area Index (APV), North Atlantic Subtropical High Intensity Index (NASH), and Indian Ocean Warm Pool Strength Index (IOWP) were the dominant climate factors influencing frequency indices, with cumulative contributions of 46.4 to 49.5%. The explanatory power of these indices varies spatially across stations, and the RF model effectively identifies key circulation factors at each station. In the future, more attention should be paid to urban planning adaptations, particularly green infrastructure and land use optimization, along with targeted heat mitigation strategies, such as early warning systems and public health interventions, to strengthen urban resilience against escalating extreme temperatures. Full article

Sea surface temperature (SST) is considered a strong indicator of climate change, being an essential parameter for long-range weather and climate forecasting. Another important indicator of climate change is sea level (SL), which has a longer history of systematic instrumental observations. This paper aims to examine the relationships between low-latitude variations in ocean characteristics (SST and SL) and surface air temperature (SAT) anomalies in the Arctic and mid-latitudes, and discuss the possibility of using SST and SL as predictors to forecast seasonal SAT anomalies. Archives of meteorological observations, atmospheric and oceanic reanalyses, and long-term series of tide gauge data on SL were used in this study. An analysis of relationships between seasonal SAT in different mid-to-high latitude regions and SST made it possible to identify areas in the ocean that have the greatest influence on SAT patterns. The most commonly identified area is located in the tropical North Atlantic. Another area was found in the Indo-Pacific warm pool. The predictive potential of the relationships identified between ocean characteristics (SST and SL) and SAT will be used to build deep learning models aimed at predicting climate variability in mid-to-high latitudes. Full article

The Tianshan Mountains are located in the hinterland of the Eurasian continent, spanning east to west across China, Kazakhstan, Kyrgyzstan, and Uzbekistan. As the primary water source for Central Asia’s arid regions, the Tianshan mountain system is pivotal for regional water security and is highly sensitive to the nuances of climate change. Utilizing ERA5 precipitation datasets alongside 24 atmospheric circulation indices, this study delves into the variances in Tianshan’s precipitation patterns and their correlation with large-scale atmospheric circulation within the timeframe of 1981 to 2020. We observe a seasonally driven dichotomy, with the mountains exhibiting increasing moisture during the spring, summer, and autumn months, contrasted by drier conditions in winter. There is a pronounced spatial variability; the western and northern reaches exhibit more pronounced increases in precipitation compared to their eastern and southern counterparts. Influences on Tianshan’s precipitation patterns are multifaceted, with significant factors including the North Pacific Pattern (NP), Trans-Niño Index (TNI), Tropical Northern Atlantic Index (TNA*), Extreme Eastern Tropical Pacific SST (Niño 1+2*), North Tropical Atlantic SST Index (NTA), Central Tropical Pacific SST (Niño 4*), Tripole Index for the Interdecadal Pacific Oscillation [TPI(IPO)], and the Western Hemisphere Warm Pool (WHWP*). Notably, NP and TNI emerge as the predominant factors driving the upsurge in precipitation. The study further reveals a lagged response of precipitation to atmospheric circulatory patterns, underpinning complex correlations and resonance cycles of varying magnitudes. Our findings offer valuable insights for forecasting precipitation trends in mountainous terrains amidst the ongoing shifts in global climate conditions. Full article

The nonstationarity of extreme precipitation is now well established in the presence of climate change and low-frequency variability. Consequently, the implications for urban flooding, for which there are not long flooding records, need to be understood better. The vulnerability is especially high in coastal cities, where the flat terrain and impervious cover present an additional challenge. In this paper, we estimate the time-varying probability distributions for hourly and daily extreme precipitation using the Generalized Additive Model for Location Scale and Shape (GAMLSS), employing different climate indices, such as Atlantic Multi-Decadal Oscillation (AMO), the El Niño 3.4 SST Index (ENSO), Pacific Decadal Oscillation (PDO), the Western Hemisphere Warm Pool (WHWP) and other covariates. Applications to selected coastal cities in the USA are considered. Overall, the AMO, PDO and WHWP are the dominant factors influencing the extreme rainfall. The nonstationary model outperforms the stationary model in 92% of cases during the fitting period. However, in terms of its predictive performance over the next 5 years, the ST model achieves a higher log-likelihood in 86% of cases. The implications for the time-varying design rainfall in coastal areas are considered, whether this corresponds to a structural design or the duration of a contract for a financial instrument for risk securitization. The opportunity to use these time-varying probabilistic models for adaptive flood risk management in a coastal city context is discussed. Full article

Surface air temperature (SAT) variability is investigated for advancing our understanding of the climate patterns over the Kingdom of Saudi Arabia (KSA). SAT variability reveals significant warming trends, particularly from 1994 onward, as demonstrated by nonlinear and linear trend analysis. This warming is linked to global climate patterns, which serve as significant indicators for studying the effects of climate change on surface air temperature patterns across the KSA. The empirical orthogonal function (EOF) method is employed for analyzing SAT due to its effectiveness in extracting dominant patterns of variability during the winter (DJF) and summer (JJA) seasons. The first mode (EOF1) for both seasons shows positive variability across the KSA, explaining more than 45% of the variance. The second mode (EOF2) indicates negative variability in central and northern regions. The third mode (EOF3) describes positive variability but with lower variance over time. PC1 is used to describe the physical mechanism of SAT variability and correlations with global sea surface temperature (SST). The physical mechanism shows that the variability in Mediterranean troughs during the winter season and high pressure over the Indian Ocean and central Asia controls SAT variability over the KSA. The correlation coefficients (CCs) were calculated during the winter and summer season between the SAT of the KSA and six teleconnection indices, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Atlantic Meridional Mode (AMM), Pacific Warm Pool (PWP), North Atlantic Oscillation (NAO), and Tropical North Atlantic (TNA) SST for the period from 1994 to 2022. ENSO shifts from positive to negative correlations with SAT from winter to summer. IOD shows a diminished correlation with SAT due to the absence of upper air dynamics. PWP consistently enhances surface warming in both seasons through upper air convergence during both seasons. AMM and NAO have a non-significant impact on SAT; however, TNA contributes warming over central and northern parts during winter and summer seasons. The seasonal SAT variations emphasize the significant role of ENSO, PWP, and TNA across the seasons. The findings of this study can be helpful for seasonal predictability in the KSA. Full article

Rainfall erosivity (RE) is a critical factor influencing soil erosion, and soil erosion is closely related to land ecosystem health and long-term sustainable utilization. To ensure regional stable food supply and ecological balance, it is crucial to study the spatiotemporal distribution and influencing factors of RE. This study focuses on China and its three natural regions using daily precipitation data from 611 stations from 1960 to 2020. The study analyses the spatiotemporal changes in RE. Rainfall events were classified as moderate, large, and heavy based on rainfall intensity. The RE contribution from different rainfall levels to the total RE was analyzed, and the key climatic drivers closely linked to RE were identified using random forest. The results demonstrate that (1) on a national scale, RE shows a significant increasing trend, marked by an 81.67 MJ·mm·ha⁻¹·h⁻¹/decade. In the subregions, the Eastern Monsoon Region (EMR) and Qinghai–Tibet Plateau Region (QTR) show a significant increasing trend, with a greater change rate in EMR of 108.54 MJ·mm·ha⁻¹·h⁻¹/decade, and the Northwest Arid Region (NAR) shows a nonsignificant upwards trend. (2) The average RE increases northwest–southeast nationwide, ranging from 60.15 MJ·mm·ha⁻¹·h⁻¹ to 31,418.52 MJ·mm·ha⁻¹·h⁻¹. The RE contribution generated by different rainfall levels to the total RE exhibits spatial variations. The dominant types show that EMR is influenced by heavy RE, NAR is dominated by large RE, and QTR is affected by moderate RE. (3) The REs are associated with teleconnection indices, but the impact of these indices varies in different regions. The Western Hemisphere Warm Pool has the greatest impact on the EMR, while the North Atlantic Oscillation and Atlantic Multidecadal Oscillation are the factors influencing RE in NAR and QTR, respectively. (4) On a national scale, for every 1 mm increase in annual total rainfall, the RE increased by 8.54 MJ·mm·ha⁻¹·h⁻¹, a sensitivity of 8.54 MJ·mm·ha⁻¹·h⁻¹/mm. For the three subregions, there are differences in the sensitivity of RE to changes in annual precipitation. The highest sensitivity is found in EMR, at 8.71 MJ·mm·ha⁻¹·h⁻¹/mm, which is greater than the sensitivity indices in NAR (6.19 MJ·mm·ha⁻¹·h⁻¹/mm) and QTR (3.60 MJ·mm·ha⁻¹·h⁻¹/mm). This study can provide theoretical references for future regional soil erosion prediction and sustainable agricultural development in China. Full article

In order to better understand the extent to which global climate variability is linked to the frequency and intensity of heat waves and overall changes in temperature throughout the United States (US), correlations between long-term monthly mean, minimum, and maximum temperatures throughout the contiguous US on the one hand and low-frequency variability of multiple climate indices (CIs) on the other hand are analyzed for the period from 1948 to 2018. The Pearson’s correlation coefficient is used to assess correlation strength, while leave-one-out cross-validation and a bootstrapping technique (p-value) are used to address potential serial and spurious correlations and assess the significance of each correlation. Three parameters defined the sliding windows over which surface temperature and CI values were averaged: window size, lag time between the temperature and CI windows, and the beginning month of the temperature window. A 60-month sliding window size and 0 lag time resulted in the highest correlations overall; beginning months were optimized on an individual site basis. High (r ≥ 0.60) and significant (p-value ≤ 0.05) correlations were identified. The Western Hemisphere Warm Pool (WHWP) and El Niño/Southern Oscillation (ENSO) exhibited the strongest links to temperatures in the western US, tropical Atlantic sea surface temperatures to temperatures in the central US, the WHWP to temperatures throughout much of the eastern US, and atmospheric patterns over the northern Atlantic to temperatures in the Northeast and Southeast. The final results were compared to results from previous studies focused on precipitation and coastal sea levels. Regional consistency was found regarding links between the northern Atlantic and overall weather and coastal sea levels in the Northeast and Southeast as well as on weather in the upper Midwest. Though the MJO and WHWP revealed dominant links with precipitation and temperature, respectively, throughout the West, ENSO revealed consistent links to sea levels and surface temperatures along the West Coast. These results help to focus future research on specific mechanisms of large-scale climate variability linked to US regional climate variability and prediction potential. Full article

Sea surface temperatures and vertical wind shear are essential to tropical cyclone formation. TCs need warm SSTs and low shear for genesis. Increasing SSTs and decreasing VWS influences storm development. This work analyzes SST and VWS trends for the Caribbean, surrounding region, and the Atlantic hurricane main developing region from 1982–2020. Storm intensity increases significantly during this period. Annual and seasonal trends show that regional SSTs in the MDR are warming annually at 0.0219 °C yr⁻¹ and, per season, 0.0280 °C yr⁻¹. Simultaneously, VWS decreases during the late rainfall season, at 0.056 m/s yr⁻¹ in the MDR and 0.0167 m/s yr⁻¹ in the Caribbean and surrounding area. The Atlantic Warm Pool is expanding at 0.51 km² per decade, increasing upper atmospheric winds and driving VWS changes. Correlations of large-area averages do not show significant relationships between TC intensity, frequency, and SSTs/VWS during the LRS. The observed changes appear to be associated with regional warming SSTs impacting TC changes. Plain Language Abstract: Tropical cyclone (TC) formation requires warm ocean waters and low wind shear. Changes to sea surface anomalies and wind shear influences are essential to understanding storm development and intensification. The ability to forecast storm changes is vital to human lives and livelihoods. This work analyzes sea surface temperatures (SSTs) and vertical wind shear (VWS) trends in the Caribbean, surrounding areas, and the Atlantic main developing region (MDR). We found increasing SSTs, decreasing wind shears, an expanding Atlantic Warm Pool (AWP), and increased storm intensity during the Atlantic hurricane season. Full article

Global climate change has readjusted a global-scale precipitation distribution in magnitude and timing. In mountainous areas, meteorological stations and observation data are very limited, making it difficult to accurately understand the response of precipitation to global climate change. Based on ECMWF Reanalysis v5 precipitation products, Berkeley Earth global temperature, and typical atmospheric circulation indexes, we integrated a gradient descent-nonlinear regression downscaling model, cross wavelet transform, and wavelet correlation method to analyze the precipitation response in Tianshan to global climate change. This study provides a high-resolution (90 m × 90 m) precipitation dataset in Tianshan and confirms that global warming, the North Pacific Pattern (NP), the Western Hemisphere Warm Pool (WHWP), and the Atlantic Multidecadal Oscillation (AMO) are related to the humidification of Tianshan over the past 40 years. The precipitation in Tianshan and global temperature have a resonance period of 8–15 months, and the correlation coefficient is above 0.9. In Tianshan, spring precipitation is determined mainly by AMO, North Tropical Atlantic Sea Level Temperature, Pacific Interdecadal Oscillation (PDO), Tropical North Atlantic Index, WHWP, NP, summer by NP, North Atlantic Oscillation, and PDO, autumn by AMO, and winter by Arctic Oscillation. This research can serve the precipitation forecast of Tianshan and help in the understanding of the regional response to global climate change. Full article

Risk analysis using climate-induced yield losses (CIYL) extracted from long-term yield data have been recognized in China, but the research focusing on the time-series characteristics of risk and the circulation signals behind yield losses still remains incomplete. To address these challenges, a case study on winter wheat production in Henan province, north China was conducted by using annual series of yield in 17 cities during 1988–2017 and monthly series of 15 types of large-scale oceanic-atmospheric circulation indices (LOACI). A comprehensive risk assessment method was established by combining the intensity, frequency, and variability of CIYL and principal component analysis (PCA). The results showed that the westernmost Henan was identified as the area of higher-risk. PCA and Mann–Kendall trend tests indicated that the southern, northern, eastern, and western areas in Henan province were classified as having different annual CIYL variations in these four sub-regions; the decreasing trend of CIYL in northern area was the most notable. Since the 2000s, a significant decline in CIYL was found in each sub-region. It should be noted that the key LOACI, which includes Tropical Northern Atlantic Index (TNA), Western Hemisphere warm pool (WHWP), and Southern oscillation index (SOI), indicated significant CIYL anomalies in some months. Furthermore, the regional yield simulation results using linear regression for the independent variables of year and various LOACI were satisfactory, with the average relative error ranging from 3.48% to 6.87%. Full article

The tropical Atlantic Warm Pool is one of the main drivers of the marine intertropical convergence zone and the associated coastal Northeast Brazilian and West-African monsoons. Its meridional displacement is driven by the solar cycle, modulated by the atmosphere and ocean interactions, whose nature and respective proportions are still poorly understood. This paper presents a climatological study of the upper ocean and lower atmosphere contributions to the warm pool seasonal migration, using an Ocean General Circulation Model (OGCM). First, we provide quantitative, albeit simple, pieces of evidence on how the large amplitude of migration in the west, compared to the east, is mainly due to the strong east–west contrast of the background meridional SST gradient intensities, which is maintained by equatorial and eastern tropical upwellings. Our main results consist first in identifying a diagnostic equation for the migration speed of the two meridional boundary isotherms of the Warm Pool, expressed in terms of the various mixed-layer heat fluxes. We then evidence and quantify how, in general, the migration is forced by air–sea fluxes, and damped by ocean circulation. However, remarkable controls by the ocean are identified in some specific regions. In particular, in the northwestern part of the Warm Pool, characterized by a large temperature inversion area, the boreal spring northward movement speed depends on the restitution of the solar heating by the thermocline. Additionally, over the southern part of the Warm Pool, our study quantifies the key role of the equatorial upwelling, which, depending on the longitude, significantly accelerates or slows down the summer poleward migration. Full article

This study investigated the number of tropical cyclones (TCs) that affected Puerto Rico during the June-November hurricane season in the period 1980–2016, and their contribution to the total precipitation. Special attention was dedicated to assessing the role of atmospheric-oceanic teleconnections in the formation of TCs that affect this island. The HURDAT2 tropical cyclone climatology database and the multi-source weighted set precipitation (MSWEPv2) data with a spatial resolution of 0.1° × 0.1° were used. A total of 92 TCs within a 500-km radius of Puerto Rico were identified for the study period. Contrary to what was expected, a similar percentage of affectation was found between those TCs formed under El Niño and La Niña conditions. Regarding the North Atlantic Oscillation, a 23.91 % of the 92 TCs that affected Puerto Rico formed under the negative phase, while the 13.04% during the positive phase, which is explained in agreement with previous findings with the weakening and shift to the south and west of the Azores High during the negative phase of North Atlantic Oscillation. The role of the Sea Surface Temperature on the genesis of TCs that affected Puerto Rico was also assessed through the Atlantic Meridional Mode and the Atlantic Warm Pool area. It is confirmed that the affectation of TCs in Puerto Rico is highly related to the eastward extension of the Atlantic Warm Pool and the Sea Surface Temperature gradient in the tropical North Atlantic region. Indeed, a northward shift in latitude and longitude in genesis position was found from July to November. Finally, a monthly analysis revealed that in August and September the maximum mean rain contribution from TC was ~17% for the grid but with values in the 20–30% interval. Full article

This study quantifies the amount of rainfall supplied by tropical cyclones (TCs) to Cuba. It uses the long–term global gridded Multi–Source Weighted–Ensemble Precipitation (MSWEP) v2 data set, with a resolution of 0.1° in latitude and longitude, and a temporal resolution of 3 h during the hurricane seasons from 1980–2016. During this study period, 146 TCs were identified within a 500–km radius of Cuba. The contribution of TCs to the total precipitation over Cuba during the cyclonic season was ~11%. The maximum contribution occurs in October and November, representing 18% and 28% of the total precipitation, respectively. The interannual precipitation contribution shows a positive correlation (~0.74) with the number of TCs, but without a significant trend for the period. A climatological spatial analysis of the rainfall associated with TCs revealed great heterogeneity, although the major contribution was observed along the southern coast of the eastern and central provinces of Cuba, and in the western province of Pinar del Río. No significant difference was observed between the number of TCs that affected Cuba and their rainfall contribution under the positive and negative phases of the El Niño Southern Oscillation. However, the negative phase of the NAO led to an increase in the genesis of TCs that later affected Cuba, which led to a greater contribution to precipitation compared to that obtained from TCs during the positive phase of this oscillation. Our results also confirm that anomalous warmth of the tropical Atlantic Ocean, revealed through the Atlantic Meridional Mode, and enlargement of the Atlantic Warm Pool, enhances the genesis in the North Atlantic Basin of the TCs that affect Cuba, which was associated with an increase of the rainfall contribution to the total precipitation compared to that calculated for TCs formed during the opposite phases. Full article

May-to-July and February-to-April represent peak rainy seasons in two sub-regions of Northeast Brazil (NEB): Eastern NEB and Northern NEB respectively. In this paper, we identify key oceanic indexes in the tropical South Atlantic for driving these two rainy seasons. In Eastern NEB, the May-to-July rainfall anomalies present a positive relationship with the previous boreal winter sea surface temperature anomalies (SSTA) in the southeast tropical Atlantic (20°–10° S; 10° W–5° E). This positive relationship, which spread westward along the southern branch of the South Equatorial Current, is associated with northwesterly surface wind anomalies. A warmer sea surface temperature in the southwestern Atlantic warm pool increases the moisture flux convergence, as well as its ascending motion and, hence, the rainfall along the adjacent coastal region. For the Northern NEB, another positive relationship is observed between the February-to-April rainfall anomalies and the SSTA of the previous boreal summer in the Atlantic Niño region (3° S–3° N; 20° W–0°). The negative remote relationship noticeable between the Northern NEB rainfall and the concomitant Pacific Niño/Niña follows cold/warm events occurring during the previous boreal summer in the eastern equatorial Atlantic. The southeastern tropical Atlantic and Atlantic Niño SSTA indexes may, then, be useful to predict seasonal rainfall over the Eastern and Northern NEB, respectively, for about a 6 month leading period. The ability of both southeastern tropical Atlantic and Atlantic Niño SSTA indexes to forecast the Eastern and Northern NEB rainfall, with about a 6 month lead time, is improved when these indexes are respectively combined with the Niño3 (5° S–5° N; 150°–90° W) and the northeast subtropical Atlantic (20° N–35° N, 45° W–20° W), mainly from the 1970’s climate shift. Full article