International Journal of Climatology最新文献

Several damaging tropical cyclones (TCs) have occurred recently over the South Indian Ocean (SIO) region, causing enormous social and economic losses. Yet, while many studies have examined SIO TC characteristics using observations and reanalysis, only a few have assessed these characteristics specifically for this region in climate models, and fewer have investigated their projections under climate change. Here we do this for a historical (1980–2010) and future (2020–2050) period, using multimodel simulations from the High Resolution Model Intercomparison Project, as well as examine biases in the historical period relative to a reanalysis (ERA5). The models have horizontal resolutions of 25–50 km, which has enabled an improved ability to represent tropical cyclones globally in previous studies. TempestExtremes software is employed to detect tropical storm and cyclone tracks. In cases where TempestExtremes cannot be applied due to a lack of requisite variables in a dataset, we instead examine extreme wind speeds in that dataset. For the historical period, we find considerable variation in model biases compared to ERA5, which itself exhibits realistic spatial patterns of tracks and their monthly distribution. Models do at least agree on positive biases in track frequency east of Madagascar and somewhat in the Mozambique Channel. However, the models and ERA5 only produce Category 3 tropical cyclones at best. Wind speeds for 25 km resolution models have much larger positive biases than for 50 km ones, suggesting the former can simulate even higher-category tropical cyclones. Considerable intermodel variation is also found in track changes between the future and historical periods. No systematic intercategory pattern of change exists, and low signal-to-noise may obscure any such patterns in the limited timespan of available data. Thus, no meaningful conclusions can be drawn regarding changes in track intensity. Nevertheless, track frequency broadly decreases across models for the region, as does accumulated cyclone energy. An east-to-west shift in track location from east of Madagascar toward the Mozambique Channel is also implied by track frequency and wind speed changes. Our findings provide information to potentially improve storm resiliency in this vulnerable region.

The Coordinated Regional Downscaling Experiment (CORDEX) offers a framework for regional climate downscaling experiments over continental-based domains that overlap; this allows for conducting multimodel analysis. However, a question is raised about the uncertainty due to domain selection. This study aims to evaluate the sensitivity of CORDEX simulations to the choices of domain, downscaling regional climate model (RCM) and driving global model (GCM) over a Middle East study region, including Jordan. Understanding these sensitivities helps assess simulation uncertainties and enhance regional climate change projections. Taylor diagrams and variance decomposition analyses were used to analyse seasonal temperature and precipitation climatologies. The results indicate that the domain contribution to variance is negligible, whereas the choice of GCM and RCM strongly influences simulations. Variance in temperature is significantly impacted by the driving model (GCM), whereas RCM has a higher influence on precipitation, which reflects their large-scale versus local nature. The results of this study support the development of multidomain ensembles since projections produced by the same GCM–RCM model combination are consistent across different overlapping domains. On the other hand, this approach facilitates the consideration as well as a comprehensive quantification of the uncertainties arising from the utilization of multiple GCMs and RCMs within such an ensemble. This improves the reliability of regional climate information, thus facilitating the development of effective adaptation strategies and mitigation plans.

Due to their significant influence on large-scale atmospheric circulation and climate anomalies, the variability of Arctic sea ice and Eurasian snow cover during late autumn and their combined effects have garnered increasing attention. This study aims to investigate the physical mechanism underlying the covariation among the Barents-Kara Seas (BKS) sea ice concentration (SIC), Eurasian snow cover extent (SCE) and the ensuing winter Eurasian surface air temperature (SAT). The statistics results of singular value decomposition suggest a significant linkage between the decreased BKS SIC, zonal “negative–positive” dipole SCE anomalies over Eurasia in November and cold Eurasian SAT in January–February (JF). Observational diagnosis analyses about the meridional moisture, heat transport and surface heat flux demonstrate that subpolar Eurasian anticyclonic circulation plays a crucial role in connecting the predominant modes of SIC and SCE. Furthermore, the BKS SIC and Eurasian SCE anomalies can jointly excite upward-propagating planetary waves into the stratosphere, while simultaneously reducing the subpolar meridional temperature gradient. This results in westerly wind deceleration and favours the continuous planetary wave propagation. Consequently, the stratospheric polar vortex is significantly weakened, along with negative Northern Annular Mode anomalies propagating downward from the stratosphere to troposphere. Negative-phase Arctic Oscillation anomalies correspondingly develop during JF, resulting in widespread cold anomalies over the Eurasian continent. These results are further confirmed by numerical sensitivity experiments from the Community Atmosphere Model forced by the above mentioned SIC and SCE anomalies. The empirical hindcast model analyses further suggest that the prediction skill of JF Eurasian SAT is enhanced when both the November BKS SIC and Eurasian SCE signals are considered.

Elevation-dependent warming (EDW) has been a topic of intense debate due to limited observed data in global highland areas. This study aims to fill this gap by utilizing CRU and ERA5 datasets from 1981 to 2021 to explore the trends of climate change and its elevation dependency. The anomalies of temperature indicators (T_mean, T_max, and T_min) in both ERA5 and CRU showed significant warming trends over global highlands. Moreover, the response of temperature indicators to elevation across global highlands is not spatially uniform. The linear regression model based on the elevation showed significant warming signals for the temperature indicators at various elevations over the global highlands. On a regional scale, T_mean and T_max predominantly showed linear EDW over EU highlands, while T_mean in Asian highlands exhibited EDW signals at 4–5 km. T_min showed EDW at 2.5–5.5 km with ERA5 and 3–5 km with CRU. In the Andes, EDW was prominent at 2.5–4 km. Overall, EDW signals are evident in all studied regions but vary across them. While assessing the driving factors, the results of this study indicate that total column water vapour (TCWV), snow depth (SD), snow albedo, and normalized difference vegetation index (NDVI) correlated positively with the temperature indicators. These findings emphasize the significance of elevation-specific interactions between environmental factors and temperature in forecasting temperature changes in mountainous areas. Additionally, temperature exhibited coherence with teleconnection indices from the Atlantic and Pacific Oceans. Asian and European (EU) highlands exhibited interzonal coherence with the Pacific and Atlantic Oceans, while North American (NA) highlands showed coherence, followed by South American (SA) highlands. These findings provide a comprehensive understanding of EDW and its implications for highland regions globally, including the potential for more severe depletion of snow/ice resources in a warmer future.

In the Earth's general circulation, polar jets act as baroclinic pumps of angular momentum and heat. Reanalysis datasets indicate that shear changes near jets induce upward displacements of the jet cores, suggesting a weakening thermodynamic pumping over the last 50 years. From secondary flow theory, a well-established principle in fluid dynamics, an increased frequency of heatwaves and persistent winter storms is expected. The ageostrophic wind shear between 700 and 50 hPa indicates the strength of this secondary circulation. The weakening tendency during the reanalysis period also exists in multimodel simulations under the RCP8.5 emissions scenario for the 21st century. The reduction between the periods 2005–2025 and 2081–2100 reaches 18%, 5.3% and 19%, respectively, for the North America, Mid-Europe and East Asia sectors of the Northern Hemisphere polar jet. Within this background, cold-surge events are the result of synergic co-working of several factors. The occurrence trend for transitional season winter extreme events also is examined. The winter extremes seemingly have larger temperature drops. However, in a warming climate, they emerge more rapidly from extreme cold states. The storm tracks, especially over North America, have equatorward extensions, indicating that winter storms can reach lower latitudes. Due to the temperature-dependence of air viscosity, secondary flows decrease more slowly than the main zonal flow. This imposes an important adjustment to the traditional polar amplification effects on midlatitude winter extremes. During a warmer winter (the primary manifestation of a warmer climate), spatially uniform positive trends in cold extreme events are not expected. There are, however, regions experiencing more winter extremes. These regions show consistent patterns in both the reanalysis period and the remainder of the 21st century.

Drought is one of the most devastating threats to the livelihoods of the southern African population, who mainly rely on rain-fed agriculture for income. Previous studies have highlighted that the Botswana High influences drought over the region; however, its influence on the spatial modes of drought remains unknown. This study examines the spatiotemporal structures of drought modes (DMs) over southern Africa and their link with the Botswana High in observation, reanalysis and Model for Prediction Across Scales (MPAS). To characterize droughts, the study uses the 3-month scale standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). Spatiotemporal characteristics of the DMs are identified using empirical orthogonal function (EOF) analysis on SPI and SPEI. EOF analysis is also used to identify the spatiotemporal characteristics of the Botswana High. The relationship between each DM and the Botswana High is quantified using correlation and R² analysis. In all the datasets (Climate Research Unit (CRU), European Centre for Medium-Range Weather Forecasts version 5 (ERA5), 20th Century reanalysis II (20C) and MPAS), the most dominant five DMs (hereafter DM1–DM5) over southern Africa jointly explain more than 60% of the interannual variability in the 3-month scale summer droughts for SPEI and SPI. CRU, ERA5 and MPAS agree that the Botswana High correlates with the interannual variability of DM1, with a stronger correlation in ERA5 (r = −0.85) compared to MPAS (r = −0.42) and CRU (r = −0.35). Additionally, wet years (+ve SPEI and SPI) are characterized by a weak Botswana High and drought years (−ve SPEI and SPI) by a strong Botswana High. The wet and dry years correspond to the −ve and +ve phases of El Niño–Southern Oscillation (ENSO), respectively. Given this, the results of this study suggest that the Botswana High might be a teleconnection pattern through which ENSO signals influence DM1 over the region.

In recent decades, India has witnessed an increase in the intensity, frequency, and spread of extreme weather events. The widespread increase in extreme precipitation over the Western Coast of India is a matter of great concern. The factors contributing to such devastating extreme precipitation remain unclear due to the variability present in meteorological and oceanic variables and associated large-scale circulations. Using reanalysis and observed datasets, we attempted to identify a combination of dynamic, thermodynamic, and cloud microphysics processes contributing to the anomalous precipitation from August 1 to 10, 2019 against its climatology. Our key findings highlight the crucial role of warm sea surface temperatures (anomaly >1.4°C), outgoing longwave radiation (anomaly <−50 W·m⁻²), and atmospheric temperature (anomaly over the ocean is >1.6°C) in enhancing the moisture-holding capacity of the atmosphere by almost 10%. This elevated moisture, propelled by intensified low-level winds (anomalies exceeding 4 m·s⁻¹), leads to a shift from ocean to land. Notably, we observe that vertical updrafts (anomalies >−0.4 m·s⁻¹) contribute to increased atmospheric instability and moisture convergence. The presence of an ample amount of cloud hydrometeors, with anomalies surpassing 2.5 × 10⁻⁴ kg·kg⁻¹, establishes conditions conducive to sustained intense precipitation. Our findings deepen our understanding of the complex relationships between ocean and atmospheric dynamics, and wind patterns, and emphasize their pivotal influence on regional weather patterns and land surface hydrology.

In this study, we investigate the changing relationship between the boreal winter Arctic Oscillation (AO) and eastern African precipitation. The results show that the negative correlation has significantly weakened since the late 1970s. And the Arabian anticyclonic circulation changed concurrently with the AO. In the mid-high troposphere, the anomalous anticyclone centred over the Arabian Peninsula in 1980–2020 moved northeastward and weakened compared to 1950–1979. Correspondingly, the anomalous downward motion over eastern Africa significantly weakened compared with that in 1950–1979, corresponding to insignificant precipitation. A further analysis suggests that AO-related Rossby wave trains in the upper troposphere may modulate the Arabian anticyclone. From 1950 to 1979, the wave activity preferred propagating eastward from the Mediterranean to Russia along a high-latitude path. In contrast, during 1980–2020, it tended to emanate southeastward towards Saudi Arabia, with a notably stronger and more eastward extension than in the earlier period.

This study investigates the relationship between sea surface temperature (SST) anomalies in the subtropical Atlantic Ocean, as represented by the Southern Atlantic subtropical dipole (SASD), and SST anomalies in the tropical Pacific Ocean, identified by the El Niño-Southern Oscillation (ENSO). Contrary to the previously held notion of a weak relationship between SASD and ENSO as suggested by earlier literature, our analysis reveals a substantial inverse correlation between the two. This correlation exhibits significant multi-decadal variability, which has notably intensified over the most recent two decades compared with the preceding two decades. This intensification in the SASD–ENSO inverse correlation may be attributed to the shift in ENSO regime from predominance of eastern Pacific El Niño to central Pacific El Niño events around the turn of the century. This transition triggers wavetrains that propagate along different paths, consequently influencing the South Atlantic subtropical high and inducing alterations in anomalous SST patterns in the subtropical Atlantic Ocean. These findings advance our comprehension of the interactions between South Atlantic and Pacific SST variations, which strongly influence rainfall patterns, particularly in South America and southern Africa. Understanding such teleconnection holds promise for improving sub-seasonal to seasonal precipitation predictions in these regions.