International Journal of Climatology最新文献

Urbanisation has significantly intensified the urban heat island (UHI) effect, particularly in rapidly growing cities like Kuala Lumpur. This study develops 1-km resolution projections of land surface temperature (LST) using a machine learning-based downscaling approach that integrates CMIP6 global climate model (GCM) simulations with urbanisation projections under different shared socioeconomic pathways (SSPs). A random forest (RF) model was trained on 1-km resolution MODIS LST data and urbanisation ratio datasets to estimate GCM-simulated Earth skin temperature (T_s) biases. The trained model was then applied to future urbanisation scenarios to project LST anomalies from 2030 to 2090. The analysis revealed a strong positive correlation of 0.785 between the urbanisation ratio and LST anomalies. The RF model accurately predicted LST anomalies with a root mean square error of 1.63°C and a Kling-Gupta Efficiency of 0.76. The future projections of LST using the multimodel mean of all GCMs revealed an increase in average LST in Kuala Lumpur from 0.7°C (CI: 0.4°C–0.7°C) for SSP1-2.6 to 1.3°C (CI: 1.2°C–2.9°C) for SSP5-8.5. The projections of UHI showed an increase ranging from 1°C to 1.9°C for SSP1-2.6 and from 2.5°C to 3°C for SSP5-8.5 by 2090 compared to 2030. The results also highlight spatial heterogeneity in UHI expansion, with central urban zones experiencing the most significant warming. This study emphasises the necessity of integrating urban planning strategies, such as increased green spaces, improved urban design, and heat mitigation policies, to address the rising urban temperatures.

Fine particulate matter (PM_2.5 ≤ 2.5 μm) poses a significant environmental and public health challenge in Saudi Arabia, where sparse ground-based monitoring stations hinder comprehensive assessments of PM_2.5 hotspots, trends and impacts. Climate change is expected to exacerbate air quality by influencing atmospheric circulation, dust storm frequency and pollutant dispersion. Therefore, this study focuses on identifying pollution hotspots, temporal variations, calculating trends and factors influencing PM_2.5 pollution, along with source and transport pathways using Washington University-based newly updated Global Estimates (V6.GL.02) of monthly PM_2.5, the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2), and ERA5 reanalysis data. In addition, future projections of PM_2.5 components, specifically dust, were analysed using the ensemble mean of five CMIP6 Global Climate Models (GCMs) under the Shared Socioeconomic Pathways (SSP: 1–2.6, 2–4.5 and 5–8.5) from 2023 to 2100. Results show consistent spatial patterns annually and seasonally, with PM_2.5 hotspots (annual mean > 60 μg/m³) identified over eastern Saudi Arabia, the Riyadh metropolitan area, coastal Makkah, Madinah and Tabuk. Notably, PM_2.5 across all 13 provinces exceeded the annual limits of Saudi Air Quality Standard (SAAQS ≤ 15 μg/m³), World Health Organization (WHO) AQS (WHOAQS ≤ 5 μg/m³) and European Environmental Air Quality Standard (EEAQS ≤ 12 μg/m³) by factors of 2–4, 7–12 and 3–4 times, respectively. Pearson's correlation and multiple regression analysis demonstrate that various climate variables across Saudi Arabia significantly influence PM_2.5. Annual and seasonal PM_2.5 increased during 2001–2010 and 2000–2022 but declined between 2011 and 2020. PM_2.5 is primarily influenced by dust, followed by black carbon (BC), sulfate and sea salt, originating from local sources, neighbouring regions (e.g., Iraq, Kuwait and Syria), and distant regions such as North/East Africa and South Asia. Dust is projected to increase in 2030–2049 under all SSPs. In 2050–2069, they continue to rise under SSP1-2.6 and SSP2-4.5 but decline under SSP5-8.5. By 2070–2100, dust decreases under SSP1-2.6 while increasing slightly under SSP2-4.5 and SSP5-8.5. This study underscores climate-driven PM_2.5 risks and transboundary contributions, urging targeted mitigation in Saudi Arabia.

The spatial unevenness of precipitation significantly impacts local hydrological cycles and exacerbates natural hazards. However, the underlying mechanisms governing such variability over complex terrains remain poorly understood. This study bridges this gap by employing a spatial unevenness index to investigate environmental conditions and fine-scale characteristics of precipitation events with different spatial unevenness over the steep terrains in North China. Results show that strongly uneven precipitation events are associated with unstable atmospheric stratification and high convective available potential energy (CAPE). Both cold-top–warm-bottom temperature anomalies and wet-bottom–dry-top humidity anomalies enhance atmospheric instability. Under the thermodynamic influence of complex terrain, these events cluster along the mountains and predominantly occur in the afternoon, coinciding with diurnal peaks in both precipitation frequency and intensity. In contrast, weakly uneven precipitation events are mainly driven by synoptic-scale forcing, featured with lower-tropospheric convergence, upper-tropospheric divergence, and strong large-scale upward motion. Warm anomalies in the upper troposphere and abundant moisture transported by anomalous low-level southerly winds are crucial to these events. Spatially, weakly uneven precipitation events spread extensively across North China, covering both mountains and plains. Maximum precipitation amount occurs at the foot of mountains, highlighting the blocking and uplifting effects of topography. For this type, precipitation amount and frequency peak in the early morning, whereas intensity peaks in the afternoon. These findings advance our understanding of precipitation unevenness and provide a scientific basis for improving flood forecasting and water resource management in complex terrains.

Vapour pressure deficit (VPD) is a crucial determinant of land-atmosphere interactions; however, its long-term dynamics in intensively irrigated deltaic regions are not well comprehended. This study analyzes three decades (1990–2020) of VPD variability in Egypt's Nile Delta, a transitional area affected by both Mediterranean humidity and Saharan aridity, utilising MERRA-2, GLDAS and ERA5 reanalysis datasets, which have been validated against data from 16 ground stations (r > 0.95; Willmott's d > 0.94). Trend analyses utilising the Modified Mann–Kendall test indicate a statistically significant increase in atmospheric aridity (+0.08 to +0.09 kPa decade⁻¹, p < 0.01), with the most substantial increases observed in summer (+0.114 kPa decade⁻¹). Spatial heterogeneity is apparent, with consistently high VPD in the southern and eastern regions of the Delta, whereas coastal areas experience some moderation due to maritime influence. Partial correlation analyses reveal that increasing air temperatures and decreasing relative humidity are the principal factors driving these changes, further exacerbated by soil moisture depletion, which collectively hastens the shift towards enhanced atmospheric aridity. This study highlights the importance of explicitly integrating VPD into climate diagnostics, irrigation management and adaptation planning by characterising the Nile Delta as a representative agroecosystem under deltaic conditions. The changing trajectory of the Delta serves as a regional warning and a globally pertinent case study on how a warming climate intensifies atmospheric water demand and alters agricultural resilience in intensively irrigated deltaic regions.

Mexico has a critically important photovoltaic potential with which to produce renewable energy. However, there are few studies on how future climatic conditions might affect these potential energy resources. Here, we present an analysis of PVP over Mexico under present and future conditions with different climate-change scenarios. For this, we are using the latest regional climate models (RCMs): RegCM4 and REMO2015 from CORDEX–CORE. The RegCM4 and REMO2015 models were driven by ERA-Interim and four different general circulation models (GCMs) for two representative concentration pathways (RCP) scenarios. We consider four 20-year periods: present-day conditions (PD, for 1995–2014), near-term future conditions (NT, for 2021–2040), mid-term future conditions (MT, for 2041–2060), and long-term future conditions (LT, for 2080–2099). Our results suggest that PVP could decrease (between ~2% and ~6%) over Mexico for the mid- and long-term future, mainly during summer and autumn, possibly due to changes in temperature induced by an increase in warming under a high-emission scenario. Also, we found that in regions where PVP and solar irradiance changes are positive, the radiation term could have a greater influence on PVP changes than the efficiency solar cell term. Contrarily, in regions where we found positive changes in solar irradiance and the PVP change was negative, the efficiency solar cell term might exercise more influence on PVP changes than the solar irradiance term. On the other hand, following a low emission path, some regions of the country might experience a small PVP increase (~4%). This work represents the first assessment of PVP in Mexico using two RCMs. The findings could help identify suitable areas for photovoltaic systems and provide helpful information for renewable energy planning and climate adaptation in the energy sector, thereby contributing to the energy transition of the country.

Previous studies have found that the freezing level height (FLH) increases under the background of global warming, with negative effects on the global cryosphere, especially over mountain regions. In this study, with observation and model simulations, global FLH changes are updated to 2023. It is found that there are relatively smaller positive FLH trends and changes over the Tropics, but higher FLH changes over the extra-Tropics with maximum FLH rises over high latitudes in the northern hemisphere. The temporal FLH variations are largely driven by the variability of tropical sea surface temperature. Comparison with glacier mass balance records indicates that these observed FLH changes over Arctic and high mountain stations have led to significant glacier mass losses, with accelerated losses in recent decades. Based on model simulations, tropical middle to high troposphere temperature shows maximum increases over the last several decades of the 21st century.

Multi-decadal changes in solar activity and cloudiness significantly influence Earth's climate, yet their pre-industrial dynamics (before 1900) remain poorly understood. This study explores the relationship between total cloud cover (TCC), solar forcing, and mean annual temperature variability in the Mediterranean region, focusing on both the pre-industrial and the modern era (1982–2022). Leveraging 41 years of contemporary cloud data from the European Organisation for the Exploitation of Meteorological Satellites and historical records from Italy's Benevento Observatory (dating back to 1870), we identify a marked decline in annual TCC across both periods, coupled with rising mean temperatures. Regional analyses highlight substantial disparities in TCC reductions, with declines of up to 10% per decade in Sicily (Italy) and northern Tunisia. A pivotal change-point in cloud dynamics emerges around 2001, marked by a transition in the relationship between galactic cosmic rays (GCRs) and TCC from consistent positive correlations (1982–2001) to spatially varied patterns thereafter. This shift coincides with a notable reduction in high-cloud coverage (HCC) over the central and eastern Mediterranean. While causality remains uncertain, correlations point to GCRs and North Atlantic thermohaline circulation (NA-THC) anomalies as potential modulators of regional cloud dynamics. Contrasting pre-industrial (r = 0.46) and modern (r = −0.69) correlations underscore the complexity of cloud cover responses, highlighting the role of atmospheric circulation and the need for further investigation into these dynamics and their implications for climate variability.

Both summer heavy precipitation events and droughts have occurred frequently over Southwest China (SWC) in recent decades. However, few studies have focused on polarised changes in precipitation extremes and underlying mechanisms. This study statistically analyzes spatiotemporal variations of sub-daily precipitation extremes (SPEs) at 338 meteorological stations over SWC during the summers of 1971–2024. The results reveal that SPEs exhibit simultaneous increases in both wet and dry extremes. The SPE risks for 20-year and 50-year return periods increased by 2–8 and 4–17 times in 2001–2024 compared with those in 1971–2000, respectively. Precipitation intensity at 1–3 h intervals shows a more pronounced upward trend than at 6–12 h intervals, with 3.4% versus 2.7% per decade. Wet SPEs show a nearly consistent upward trend across SWC, with larger magnitudes in Chongqing, southern Sichuan, and southern Yunnan. Remarkable increases in dry SPEs occur in Yunnan and southern Guizhou. The study suggests that enhanced and westward-extended Western Pacific Subtropical High (WPSH), combined with enhanced and eastward-extended South Asian High (SAH), are key factors driving increased wet SPEs in a warmer climate, while extraordinary westward extension of the WPSH is conducive to forming dry SPEs. In the era of global warming, increases in saturated vapor pressure, specific humidity, water vapor convergence, and convective available potential energy are associated with substantial increases in wet SPEs over SWC. Simultaneously, the increased SVP makes it more difficult for water vapor to reach saturation, triggering occurrences of dry SPEs. Our findings provide a scientific basis for decision-makers adapting to SPEs and offer valuable insights for further in-depth research.

Renewable energy sources present significant temporal variability, which imposes difficulties for their integration into national power grids. This integration could be facilitated by an optimised distribution of renewable capacity that exploits their complementarity. This study brings a comprehensive analysis of the complementarity of wind, solar and hydroelectric resources on the interannual scale over Argentina using 38 years of reanalysis-based data and streamflow measurements. The impact of low-frequency ocean–atmosphere variations on these resources is also assessed in this study. We found little potential for complementarity between solar, wind and hydro resources for the current spatial distribution of renewable capacity in Argentina. This result highlights the need to study different options for coping with the intermittency of these resources, including different spatial schemes for future capacity additions. Climatic drivers exert significant control over wind, solar and hydro resources. The Antarctic Oscillation (AAO) index shows anticorrelations with wind speeds. Streamflows over northern Patagonia show also negative relationships with the AAO, and a positive relationship with the El Niño/Southern Oscillation. Streamflows over southern Patagonia show positive relationships with Southern Blob (SB) and AAO indices driven by variations in temperature and precipitation. The solar resource shows strong links with all ocean-rooted climate indices during winter. These results provide an insight into the potential predictability of renewable energy resources on the interannual scale.