International Journal of Climatology最新文献

Amidst the backdrop of climate change, the monsoon rainfall pattern is experiencing alterations over time. A precise evaluation of monsoon rainfall distribution throughout the season is crucial for effective water management in agriculture, conducting drought assessments, and evaluating associated risks. Our study focused on analysing dry and wet spells within the Indian meteorological subdivisions over the past 73 years (1951–2023). It examines the spatial distribution of southwest monsoon rainfall and dry days, revealing a correlation between limited rainfall and extended dry periods, especially noticeable in regions like Western Rajasthan and Jammu & Kashmir. Vulnerability to drought is evident in regions with moderate monsoon rainfall and a high frequency of dry days. The study reveals that 65% of meteorological subdivisions experience over 60 dry days during the monsoon season, underscoring the need for a detailed analysis of dry day patterns. July and August are vital for Indian agriculture, as crop growth relies on consistent monsoonal rainfall; extended dry spells during this period cause moisture stress, affecting key stages like flowering and grain filling. The study reveals an alarming trend, with 44% of meteorological subdivisions showing an increase in dry days during August, and 29% exhibiting a similar trend for the overall monsoon season. The study also investigated the relationship between dry days and ENSO events, finding that Central and Northwest India are predominantly affected by moderate to strong events, resulting in a high probability of increased dry days. This increase in dry spells, driven by shifts in monsoon variability and intensity, reduces water availability during the growing season and raises the risk of crop failure. These findings emphasise the importance of implementing effective mitigation strategies to address the challenges posed by prolonged dry spells and their detrimental impact on crop yields.

The term ‘break’ is traditionally meant only for dry spells occurring after monsoon onset in the region. Simply put, the daily rainfall of the monsoon pauses across the region for a few days, which is called a ‘break spell’, and the revised pattern is called ‘active’. Researchers have suggested that standardised anomalies of three consecutive days of rainfall prevail when categorising active and break spells. This study examined break spells and active spells at interannual, intraseasonal, and decadal scales by examining the frequency and spatial distribution of three consecutive days of rainfall occurrences of different intensities linked to break and active events over the mainland Indochina region. The difference in the surface-to-upper wind circulation between active spells with excessive moist convection and intense break events with less rainfall was explained by various atmospheric parameters. During active phases, the easterly jet migrated south, while subtropical westerly entered lower latitudes during the break. During break spellings, the upper and lower troposphere jet winds will be weaker and dislocated over the study area but stronger during active time. La Niña encourages more break days than active days and distinguishing between vertical meridional circulation and intense break events with a heat trough-type circulation and active spells with moist convection is crucial for developing suitable prediction tools.

Rainfall erosivity is one of the most dynamic factors in the soil erosion process. The increase in soil erosion caused by high rainfall erosivity, and the subsequent loss of soil nutrients, can lead to reduced food production and ecosystem services. This research program under the New South Wales (NSW) Climate Change Adaptation Strategy, assesses rainfall pattern change, rainfall erosivity and erosion risk across NSW under future climate conditions. Daily rainfall erosivity and erosion risk were modelled by Revised Soil Loss Universal Equation (RUSLE) approach and compared with that driven by observed rainfall data. Future rainfall erosivity and soil erosion risk change were investigated from daily precipitation projection of the updated NSW and Australian Regional Climate Modelling (NARCliM1.5) for two future scenarios, RCP4.5 and RCP8.5, from the historical (1986–2005) to far future (2060–2079) periods. The annual average rainfall erosivity is projected to increase about 8% under RCP 4.5 and further decrease 5% under RCP 8.5 in NSW due to the predicted temperature rises. More frequent heavy rainfall events are projected to occur during summer (December–January–February), and the rainfall from these extreme rainfall events is expected to account for 51% of the total annual rainfall in the far future. NARCliM-derived results underestimate annual rainfall erosivity compared with observation-derived erosivity. There are greater instability (root mean squared error [RMSE]: 803.2) and erosivity uncertainty (Bias: 16%~48%) in high rainfall zones. At a monthly scale, dry months (June–July–August) are becoming drier, while wet months (December–January–February) are becoming wetter and more erosive. 67% of NSW is predicted to experience increased rainfall erosivity under RCP4.5, whereas most of NSW will shift to drought and its consequent effects under the high-end emission scenario (RCP 8.5). To address the dual challenges of excessive wetness in coastal and north-east NSW and increasing aridity in Western NSW, it is necessary to develop climate change adaptation management strategies based on high-risk areas and monthly or seasonal conditions. With the emerging launch of NARCliM2.0, we anticipate further improvements of these predictions will be achieved by more accurate models and data at higher spatial and temporal resolutions.

Summer snow plays an essential role in Arctic hydrology and in maintaining mass and energy balance of sea ice. However, there are great challenges in retrieving long-term summer snow depths over Arctic sea ice. Here, we proposed a combined novel five-variable long short-term memory (hereafter CN5VLSTM) model based on brightness temperature data to yield warm-season snow depth estimates. Then, year-round snow depth estimates were obtained for the first time. The CN5VLSTM model and five additional snow depth methods were assessed during the warm season based on the ice mass balance buoy (IMB), Alfred Wegener Institute (AWI) snow buoy (AWI-SB) and Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) snow buoy (MOSAiC-SB). According to the three buoy products, the accuracy of the CN5VLSTM-derived snow depth was highest among the five snow depth estimates with RMSEs of 10.2, 16.4, and 10.1 cm, respectively. Except for in May, the Arctic snow depth showed mainly a downward trend in warm months, and a significant downward trend was found in the Central Arctic. Excluding the Barents Sea, Kara Sea and Canadian Archipelago, the average year-round snow depth decreased in the other subregions, and a significant negative trend was observed in the East Siberian and Chukchi Seas. Snowfall was an important factor that was related to the changes in snow depth in the East Siberian and Chukchi Seas. This study can provide new insights into the evolution characteristics of summer snow depth.

The Coupled Model Inter-comparison Project phase 6 (CMIP6) provides a suite of general circulation models (GCMs) and Socioeconomic Shared Pathways (SSPs) primarily for continental-scale climate assessments. However, adapting these models for sub-national assessments, particularly in countries with varied geography like Ecuador, and for complex variables such as precipitation, introduces challenges, including uncertainties in selecting appropriate GCMs and SSPs. To address these issues, we adopt a biogeographical approach that integrates regional climatic variations. Our analysis explores 26 GCMs, four SSP scenarios and four 20-year time frames from WorldClim to evaluate discrepancies between the GCM precipitation projections, historical data and national climate projections across five Ecuadorian bioregions. This approach enabled us to sort the GCMs by annual precipitation medians, classify their monthly precipitation using Dynamic Time Warping (DTW) clustering, and develop ensembles highlighting both the largest and average precipitation anomalies within and beyond the bioregions. Among the 26 models examined, 16 projected an increase in annual precipitation in Ecuador, especially during the wet seasons, with the BCC-CSM2-MR model showing peak values, notably in the Choco region and eastern Amazon basin. Conversely, 10 models, with CMCC-ESM2 showing the largest decreases, projected reduced precipitation across almost all Ecuadorian territories, except the Choco region. The largest reductions were in the Amazon basin, raising concerns about reduced precipitation. Discrepancies, primarily in the Andes and Galapagos bioregions, reveal the challenges posed by their complex topography and insular environments. While the GCMs captured spatial patterns of ENSO, our research was constrained to 20-year averages, making direct comparison with historical records infeasible, highlighting the need for further research with shorter time frames and finer spatial resolutions. The variability in precipitation was linked to geographical factors, GCM configurations and unexpected SSP outcomes. Therefore, selecting GCMs and climatic indices tailored to specific bioregions is recommended for effective climate change impact assessments.

Based on the tropical cyclone (TC) best-track datasets from the China Meteorological Administration during 1949–2020 and the fifth generation ECMWF atmospheric reanalysis (ERA5) datasets, we investigate the characteristics of super typhoons (SuperTYs) over the western North Pacific (WNP) and associated mechanism in this study. The results show that SuperTYs are prone to occur in autumn over the WNP, nearly 30% of the autumn TCs develop into SuperTYs, and autumn SuperTYs account for more than half of the annual total. This is due to both favourable oceanic and atmospheric conditions. In southeastern WNP, the sea surface temperature (SST) in autumn is higher than that in summer, inducing zonal circulation anomalies and enhancing low-level westerlies. Consequently, the monsoon trough strengthens and extends eastward, favouring enhanced autumn typhoon occurrence in the southeastern WNP. This southeastward shift facilitates TCs to remain over the warm ocean for a longer period and makes them more prone to develop into SuperTYs. Furthermore, TCs tend to take westward-moving tracks in autumn due to stronger easterly steering flows compared with summer, resulting in more TCs passing over the South China Sea (SCS) to the east of the Philippines where the vertical wind shear (VWS) is relatively weaker and prone to develop into superTYs.

Precipitation, a crucial component of the Earth system processes, regulates the spatiotemporal cyclicity of water, energy, and carbon fluxes. Accurate precipitation datasets leverage the understanding of precipitation dynamics and are vital for hydro-climatological studies. South Asian monsoon is a complex, multi-scale interacting, synoptic, and ocean–land–atmosphere coupled system, contributing to significant spatial and temporal variability in summer monsoonal rainfall across India. This study evaluates four types of gridded (observational, satellite, reanalysis, and hybrid) precipitation products in their ability to replicate Indian Summer Monsoonal Rainfall (ISMR) characteristics using the India Meteorological Department (IMD) 0.25° gridded data as the baseline. A comparative assessment is performed in this study that uses several continuous and interval-based performance measures to evaluate the overall rainfall magnitude detectability and time-matched capturing of rainfall events. A new metric, rank score, is developed by aggregating multiple measures to find the best product. The analyses based on several performance measures indicate that MSWEP is the best dataset (rank one) that closely approximates the occurrence and magnitude of IMD-based rainfall events, while APHRODITE, CHIRPS, and IMDAA are ranked as the next best set of products. PGF is ranked the lowest among all products evaluated and is not recommended for applications. Nonetheless, APHRODITE suffers from strong negative biases, while the reanalysis (IMDAA, ERA5-Land, PGF) datasets show significant positive biases. Among the products evaluated, APHRODITE, ERA5-Land, and IMDAA have shown a limited ability to detect excess, normal, and deficit monsoon years, respectively. In general, the performance of satellite-based data products is superior to that of reanalysis datasets in accurately characterising the monsoon years. ERA5-Land is noted to be the best-performing dataset among the reanalysis products. The comprehensive comparative assessment carried out in this study benefits the selection and use of appropriate gridded precipitation products for hydroclimatic modelling, climate variability, and change studies.

The crossroad between built-up areas and extreme heat generates severe consequences on both socio-ecological systems and the natural environment, and the cities are the most vulnerable. The impact is already significant in the present climate and it will be exacerbated under climate change in many regions, including Romania and especially its southern part. The heatwaves (HWs) are a major risk for our cities as they put constant pressure on population, infrastructure and services for several consecutive days. The urban HWs in 41 Romanian cities are analysed in terms of magnitude, amplitude, duration, number and frequency, as well as the variability of the yearly occurrence of the first and last HW events. The study focuses on the warm season (May–September) and refers to the observed variability (1961–2020) and future projections (2021–2050). The main findings reveal that the occurrence of HWs is not conditioned by geographical and climatic conditions and the cities in any region may experience public health risks associated with extreme heat. This requires permanent monitoring of the phenomena, including the present characteristics and estimating future variations according to different scenarios. Considering the increasing frequency and intensity of extreme heat events expected soon, there is a clear need for region-specific adaptation, and policymakers should prioritise strategies to protect vulnerable people.