International Journal of Climatology最新文献

Using ERA5 reanalysis data, this study explores the interannual variability of the occurrence frequency of the stronger Kunming quasi-stationary front during in winter over the period 1980–2021 and the main causes of the variability. The results indicate that the occurrence frequency is significantly modulated on interannual timescales by southwesterly anomalies over the warmer region west of 103° E and northeasterly anomalies over the colder region east of 106° E. When the stronger southwesterly anomalies over the warmer region are comparable with stronger northeasterly anomalies over the colder region, the inhomogeneities of horizontal convergence and diabatic heating are strengthened near the frontal zone. This anomalous circulation causes a higher-than-normal occurrence frequency of the stronger Kunming quasi-stationary front in winter. The East Asian winter monsoon (EAWM) and circumglobal teleconnection (CGT) are the two most important controls on the interannual variability of the occurrence frequency of the stronger Kunming quasi-stationary front. Both the CGT and EAWM modulate the inhomogeneities of horizontal convergence and diabatic heating on the west flank of the front, and the EAWM further regulates diabatic heating over the east flank of the front.

High humidity combined with high temperature decreases the human body's capability to dissipate heat, causing serious health issues. While increased attention has been paid to changes in humid-heat extremes under the current climate and in the future, the causes of near-surface humid-heat extremes over the Yangtze River Delta region are still unclear. Here we investigate the relationships between quasi-stationary waves (QSWs), which are atmospheric Rossby waves with phase speed close to zero, and humid-heat extremes over the Yangtze River Delta region during the summer from 1959 to 2021. Additionally, the potential physical processes that link them are also explored. We find that the QSWs with wavenumber 1–8 present different vertical structures: Wave 1–2 are baroclinic, while Wave 3–8 are barotropic. Wave 1, 3, 5, 6, 7 and 8 show phase-locking behaviour. When the amplitudes of Wave 1, 3, 5 and 6 are higher, the frequency of humid-heat extremes near the surface at specific locations tends to be higher than the norm. The high-amplitude waves in different wavenumbers modulate near-surface temperature and/or humidity in various ways, ultimately resulting in anomalously intensive humid-heat extremes.

Precipitation and temperature extremes from daily data indexed using the CLIMDEX methodology were calculated over the Central American region. The data comprises the coarsened versions of the Climate Hazards and Infrared Precipitation with stations (CHIRPs) and the corresponding data set for temperature (CHIRTs) from the year 1981 to 2020 and 1983 to 2016, respectively. The objective is to detect trend patterns in extremes in recent periods, use novel statistical techniques for assessing the trend significance and study the monthly and annual trends for each of the indices. Trends of extreme temperature indices show more consistent, robust and widespread significant results according with the observed warming of the region. Significant extreme precipitation indices trends are more localized, and therefore harder to analyse, but it seems that one robust result from several indices is the trend toward more intense extreme precipitation events in Costa Rica. The findings of this work suggest possible impacts in human and environmental systems across the region.

Sea surface temperature (SST) has an important local and remote influence on global climate through the distribution and transport of heat and moisture. As a result of climate forcing, significant changes occur in the SSTs, which result in many natural disasters such as supercharged storms, higher wind speeds, heavier precipitation and flooding. This study investigates the spatiotemporal changes and underlying atmospheric mechanisms of the Black Sea (BLS) surface temperature. For this purpose, National Oceanicand Atmospheric Administration (NOAA) high-resolution SST data (0.25°), which were verified with buoy observations, were used for the period 1982–2021. To investigate the circulation impacts, the relationship between North Atlantic Oscillation and East Atlantic/West Russia (EA/WR) phases and SSTs of the western BLS (WBLS) and eastern BLS (EBLS) was analysed. According to the results, SST values increased from 1.64°C (in winter) to 2.52°C (in summer) during the 40-year period. Significant SST increases are shown in the EBLS during the summer and fall months. Statistically significant negative correlations (p < 0.05) were found between EA/WR and winter (r = −0.57) and summer (r = −0.56) SSTs in the EBLS. During winter, surface high located in the eastern Anatolia causes southerly winds, which blows from the terrestrial areas to the EBLS and result in above-normal SST values. During summer (under negative EA/WR phases), the Azores high-pressure centre extends to the Balkan Peninsula and WBLS and as a consequence, a significant amount of moisture associated with high sea surface temperature (>27°C, above-normal 2.0°C) develops low-level moisture convergence. Proper synoptic conditions, strong instability conditions between the surface and upper levels, and orographic forcing enable the occurrence of convective cloud cells. The movement of these cells to the northeastern part of Turkiye by strong northwesterly winds causes extreme precipitation and associated flash-flood events in a limited area where land–sea interaction occurs (i.e., Artvin, Rize and Hopa provinces of Turkiye).

Climate zones are expected to shift in response to climate change, which significantly influences vegetation distribution and provides essential guidance for human activities including production, lifestyle and economic development. Quantifying the shifts in climate zones due to global warming is therefore crucial. The primary metric for categorizing climate zones is the number of days with a daily mean temperature above 10°C (DT10). Utilizing DT10 and the ERA5 reanalysis data, it is observed that climate zones in China have gradually shifted northward over the past 65 years. Notably, the interdecadal changes in the climate zones differ between the eastern and western regions divided by the 110°E longitude. The western regions show minimal shifts, whereas the eastern regions, particularly the central and southern parts of Northeast China, exhibit obvious northward shifts. Consequently, the simulation capabilities of 41 CMIP6 models for Chinese climate zones were assessed, and it was found that 11 models demonstrated robust performance. These models were further used to analyse interdecadal variations and project future shifts in climate zones in China. The results show that the spatial pattern of climate zones in China can be well captured by the CMIP6 models, except for ACCESS-CM2, FGOALS-g3 and GFDL-CM4. Each CMIP6 model seems to be more suitable for specific climatic zones concerning trends and decadal variations in China. By 2100, a northward shift is projected for all climate zones in the east of 110°E under SSP2-4.5 and SSP5-8.5 emission scenarios, particularly in northern China. It should be noted that the potential disappearance of the northern subtropical belt, likely to be replaced by the middle subtropical belt in the future.

Precipitation is one of the main components of the hydrological cycle and its precise quantification is fundamental to providing information for the understanding and prediction of physical processes. Precipitation observations based on ground-based devices (manual and automatic rain gauges) are highly accurate but have limited spatial coverage. On the other hand, remote sensing products cover large areas but with lower accuracy. In this context, this study aims to provide a more accurate monthly precipitation estimating product, with lower latency than other products but without directly relying on field data. The methodology consists of applying a machine learning method (k-nearest neighbours algorithm) to satellite-based remote sensing data (IMERG Early Run product) and re-analysis-based (MERRA-2) variables with a particular connection to precipitation. The method was applied over the Brazilian territory, which features a large range of precipitation regimes. This methodology resulted in the development of an adjusted IMERG product (IMERG BraMaL). Compared with the original IMERG products (Early Run and Final Run), IMERG BraMaL has improved the evaluated metrics between ground-based and satellite data in almost all analyses. For instance, KGE (Kling-Gupta efficiency) went from lower values (0.70 and 0.82 for Early and Late Run, respectively) to values above 0.86 in the IMERG BraMaL. The adjusted product also presented superior performance statistics compared with other global precipitation products (CHIRPS, PERSIANN-CDR, and MSWEP). The main advantages of IMERG BraMaL compared with IMERG Final Run are (i) much faster availability to the end-users; (ii) non-dependency on any field data, allowing its application in areas where rain gauge data is unavailable or of low quality; (iii) the non-relationship of errors to local features; and (iv) the much-improved estimations in regions in Brazil where, historically, satellite-based products usually underestimate the observed data.

This study examines the temporal and spatial variability of near-surface air temperature and the canopy layer urban heat island (UHI_CL) of Kuwait City. Observations collected at 12 locations across the country of Kuwait and for the period 2010–2022 are analysed on an hourly and 3-hourly basis to provide monthly and diurnal insights of the city's UHI_CL characteristics. Research on Kuwait's UHI_CL was first conducted by Nasrallah et al. (International Journal of Climatology, 10, 401–405). Results presented here have been afforded the benefit of additional stations and more extensive data compared with the earlier study. Mean positive UHI_CL intensities, ranging from 1.1°C to 3.8°C at night, are observed consistently across all months, owing to the prevalence of clear skies from winter to summer. Negative UHI_CL intensities, indicating a typical daytime urban cool island (UCI_CL), are most prominent on summer days, exhibiting a mean hourly magnitude range between 0.6°C and 2.6°C that extends into the early parts of the evening. Heat and cool island effects are maintained up to wind speeds approaching 10 m s⁻¹ at the urban periphery. A coastal site near the city demonstrates strong influences of the Arabian Gulf temperatures and associated sea and land breeze effects on UHI_CL development. The results can be used for comparison with other desert locales, in the evaluation of urban climate models, for urban planning policies and improving local weather forecasts. This study honours in memoriam Dr. Hassan Nasrallah, who produced the first UHI_CL study in the Arab World.

Global climate projections show that humid heat extremes will expand toward the higher latitudes, making the midlatitudes hotspots for these extremes. Therefore, a thorough explanation of their regional characteristics becomes crucial, given that the changes in these extremes can potentially render a large proportion of the global population at risk. Here, we perform the first analysis of historical and projected changes in the intensity and frequency of humid heat extremes and quantify the population exposure to these extremes in Turkey, using long-term simulations from the non-hydrostatic mesoscale model of Consortium for Small-scale Modeling (COSMO-CLM) under the RCP8.5 emission scenario. We portray not only the nationwide changes in the humid heat extremes and population exposure but also their regional aspects by exploiting the K-means clustering algorithm. Our results suggest significant future increases in the intensity and frequency of these extremes over a wide geographical area, which includes the surroundings of Adana, Antalya, Izmir, Sakarya, Ordu and Diyarbakir, most of which are coastal locations. Over most of these regions, severe humid heat stress is expected to last nearly a month every year, with almost 56% of the land area is projected to experience local historical upper tail heat stress conditions for at least an additional 10 consecutive hours. Further, we explicate a significant rise in the number of people exposed to severe humid heat stress, concentrated along most coastal regions, by as much as 1.6 million person-days. More than 20% of Turkey's population may confront severe humid heat stress for at least 1 h, with that percentage falling to 4.15% for at least five consecutive hours, which indicates that people will not only endure more intense humid heat stress but also be exposed to these conditions consecutively over a period of many hours.

Climate change is associated with the modification of the polar jet stream, cyclone tracks and corresponding circulation patterns over midlatitudes. To apply these synoptic changes on regional climate, the changing sensitivity of a specific location to different pressure centre regions must be studied. An automated, objective circulation pattern detection method was developed to investigate the evolution of cyclonic and anticyclonic influence at any specific point within the European domain. The algorithm was used to assign each location to influencing low- or high-pressure centres within the domain. Pressure centre displacements and the frequency redistribution among different centres were studied for each location. The 180-year (January 1836–December 2015) mean sea level pressure dataset on the European domain with a 0.703° × 0.702° spatial and daily temporal resolution was obtained from NOAA 20th Century Reanalysis project. The presented method can apply the continental-scale changes to specific locations. A significant increase of anticyclonic influence was found in southern and central Europe, in line with the northward displacement of Atlantic cyclones. Hundred and eighty year (180-year) change of the number of days with anticyclonic versus cyclonic influence was found to be between +10% and 15% in the Mediterranean and +2% and 10% in most of Europe. The increasing anticyclonic influence in central Europe was strongest in the spring and the winter and was most attributable to the eastern European anticyclone. Results highlight the importance of research on the dynamical climate response of anticyclonic pressure systems.

Stationarity, a cornerstone in hydraulic design, is now under scrutiny due to anthropogenic activities and climate change. Numerous studies have sought to identify non-stationarity (NS); however, a comprehensive assessment of time invariance in all statistical properties of a time series is less explored. This study presents a non-overlapping block-stratified random sampling (NBRS) framework leveraging the strengths of several nonparametric tests to assess NS. The NBRS approach exclusively detects NS and distinguishes between various forms of stationarity, including weak and strict. A variant of NBRS is proposed in this study to identify the underlying stochastic process(es) influencing NS in hydroclimatic extremes. Furthermore, a nonparametric clustering approach is used to unveil spatial clusters showcasing NS due to shifts in mean, variance, distribution of time series or a combination of these factors. A comparative assessment of the modified NBRS approach with traditional trend and change point methods is also performed. The proposed methodology is applied to assess the presence of NS in 28 hydroclimatic indices derived for the west-central river basins of India, exhibiting diverse physio-climatic settings, for the study period 1973–2021. The modified NBRS approach rigorously explores NS within extreme hydroclimatic indices, conclusively pinpointing its root causes and profound implications for hydrologic design. The applicability of the modified NBRS approach to gridded and point datasets is also demonstrated. The findings highlight the limitations of conventional trend and change point tests in capturing time-invariant characteristics in heteroscedastic variables (such as streamflow and rainfall extremes) compared to the NBRS approach. The research reveals that NS in rainfall and streamflow extremes primarily results from distributional shifts, whilst temperature extremes are influenced by changes in mean and distribution properties. This research deepens our understanding of the evolving patterns in hydroclimatic extremes in a changing climate.