Weather and Climate Extremes最新文献

This research compares two different methods of tracing cyclones in the North Indian Ocean (NIO)- (i) Commonwealth Scientific and Industrial Research Organisation (CSIRO) Direct Detection (CDD) and Okubo-Weiss-Zeta parameter (OWZ) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) model data. Many CMIP5 models are evaluated against TC observations from the International Best Track Archive for Climate Stewardship (IBTrACS) and a statistical Generalised Additive Model for climate change projections in the past (1970–2000). Estimates of TCs' potential future occurrence in the NIO are evaluated using CMIP5 models (2070–2 100). When compared to historical tracks, the geographic distribution of TCs generated by both detection techniques is consistent with what would be expected, and the frequency of TCs in the models is, with a few exceptions, consistent with observations. Generally, the OWZ plan results in more TCs per unit time than the CDD scheme. Though there are significant differences between the two tracking techniques, a small number of models have TC counts that are virtually similar. Compared to the CDD plan, the OWZ scheme generally has higher performance in the NIO area.

Windstorms are among the most impacting natural hazards affecting Western and Central Europe. Information on the associated impacts and losses are essential for risk assessment and the development of adaptation and mitigation strategies. In this study, we compare reported and estimated windstorm losses from five datasets belonging to three categories: Indices combining meteorological and insurance aspects, natural hazard databases, and loss reports from insurance companies. We analyse the similarities and differences between the datasets in terms of reported events, the number of storms per dataset and the ranking of specific storm events for the period October 1999 to March 2022 across 21 European countries. A total of 94 individual windstorms were documented. Only 11 of them were reported in all five datasets, while the large majority (roughly 60%) was solely recorded in single datasets. Results show that the total number of storms is different in the various datasets, although for the meteorological indices such number is fixed a priori. Additionally, the datasets often disagree on the storm frequency per winter season. Moreover, the ranking of storms based on reported/estimated losses varies in the datasets. However, these differences are reduced when the ranking is calculated relative to storm events that are common in the various datasets. The results generally hold for losses aggregated at European and at country level. Overall, the datasets provide different views on windstorm impacts. Thus, to avoid misleading conclusions, we use no dataset as “ground truth” but treat all of them as equal. We suggest that these different views can be used to test which features are relevant for calibrating windstorm models in specific regions. Furthermore, it could enable users to assign an uncertainty range to windstorm losses. We conclude that a combination of different datasets is crucial to obtain a representative picture of windstorm associated impacts.

Understanding the predictability of marine heatwaves (MHWs) and identifying the sources of their forecast errors are essential for enhancing their forecast accuracy. In the summer of 2018, a powerful MHW struck the Yellow Sea, resulting in significant economic losses for the sea cucumber culture industry in China's coastal areas. However, the ability to predict the evolution of this MHW remains uncertain. In this study, several forecast experiments were conducted based on a deterministic ocean forecast model to address this issue. The results demonstrate that this MHW can be effectively predicted with a lead time of less than 3 days. Specifically, the mean MHW forecast accuracy is 0.66 and the mean absence/presence accuracy is 0.79 at a 3-day lead time. Beyond a 3-day lead time, the MHW forecast accuracy steadily decreases, which is primarily due to the overpredicted “False Alarms” during its growth and decay phases. The overpredicted “False Alarms” are largely attributed to uncertainties in predicting wind and air temperature related to two typhoons passing through the Yellow Sea. Additionally, anomalous ocean circulation induced by atmospheric forcing uncertainties may also trigger MHW forecast errors through advection. Future efforts involving parameter optimization, air-sea coupling, ensemble forecasts and integration with artificial intelligence-based weather forecasts are suggested to improve the prediction of MHWs. Our findings may provide implications for stakeholders in preparation for any future occurrences of MHWs in the Yellow Sea.

With global warming accelerating, the heavily populated and rapidly urbanized coastal regions of the Pearl River Delta (PRD) and the Yangtze River Delta (YRD) stand as representative areas with mounting concerns about extreme heat stress. This study analyzes differentiated effects of temperature (TAS) and relative humidity (RH) on human heat stress measured by wet-bulb globe temperature (WBGT) in those urban regions based on machine learning and mathematical derivation, while also examining the impacts of global warming and urbanization on prospective heat risks. To generate fine-scale climate projections targeted at the PRD and YRD, two global projections forced by Representative Concentration Pathway (RCP) 8.5 scenario are dynamically downscaled using non-hydrostatic Regional Climate Model version 4.7 (RegCM4), with the urban density and extent updated every year based on Shared Socioeconomic Pathways 5-8.5 (SSP5) scenario, thereby incorporating the transient urban growth into future projections. The bias-corrected downscaled simulations effectively capture the distinct interdependencies between TAS and RH on WBGT across different regions, similar to the observed patterns during the historical period. While the absolute contribution of TAS to WBGT is larger than RH regardless of warming levels and regions, the relative increase in RH becomes more pronounced with warming. Under RCP8.5 scenario, unprecedentedly extreme WBGT is projected to emerge in the far future (2080–2099). In contrast, the effect of urbanization appears to be more dominant in the near future (2030–2049) as urban density under SSP5 scenario is projected to peak around the 2040s and gradually decrease afterwards. The reduction of RH is found in the intensely urbanized areas locally, but it does not significantly lower WBGT because the positive contribution of increased TAS is more dominant. As a result, highly urbanized regions still exhibit higher WBGT compared to other areas. In addition, urban heat island effect is more pronounced for compact areas with high urban density (i.e., PRD) and at night. Despite the smaller temperature increase from urban heat island effect compared to global warming, it can play a critical role in exacerbating heat stress, adding to the already dangerous humid and hot conditions.

Summer extreme heat events happen frequently in northern China during recent decades, which have serious impacts on the society and ecosystem. The present study reveals that there is a synergistic effect of the preceding winter positive mid-latitude North Atlantic SST anomaly (pMNA SSTA) and summer negative tropical eastern Indian Ocean SST anomaly (nTEI SSTA) on strengthening the summer extreme heat events in northern China. The extreme heat events are stronger and more frequent when the two factors cooccur, and the probability of a strengthened extreme heat events is higher, which indicates a synergistic effect of the two factors. The preceding winter pMNA SSTA and summer nTEI SSTA exert their synergistic effect through a series of coupled oceanic-land-atmospheric bridges. The preceding winter pMNA SSTA could lead to an anomalous anticyclone over central Asia via the eastward propagating Rossby wave, which decreases snowfall and the subsequent snow cover there. The negative snow cover anomaly may persist into spring and induce a local anomalous anticyclone in spring via the snow-hydrological effect, which decreases the precipitation over the southern flank of the anomalous anticyclone. The decreased soil moisture persists into summer and induces the eastward propagating Rossby wave, and favors the increase of atmosphere thickness over northern China. The summer nTEI SSTA can also induce the anomalous anticyclone over northern China via the northeastward Rossby wave propagation. Thus, the two factors exhibit evident synergistic effect on the atmospheric circulation anomaly over northern China. The anomalous anticyclone corresponds to the increased atmosphere thickness, which favors the increase of air temperature in northern China and strengthening of extreme heat events. Therefore, the preceding winter pMNA SSTA and summer nTEI SSTA have significant synergistic effect on strengthening the summer extreme heat events in northern China.

This study investigates the hazard of East Asian Atmospheric Rivers (ARs) by applying the AR scale to AR catalog. When AR scale is categorized into five ranks from Category 1 (Cat1) to Category 5 (Cat5) by considering the duration and intensity of each AR event, with Cat5 having the most hazardous hydrological impact, Cat5 ARs are most frequently found in East Asian summer, along the northwestern boundary of the western North Pacific subtropical high. More frequent Cat5 ARs than Cat1 to Cat4 ARs are robustly found in eastern China, Korea, and western Japan, due to the slowly-varying monsoonal flow during the East Asian summer monsoon, which transports a large amount of moisture to the region. Since Cat5 ARs often lead to large event-total rainfall, it explains a close relationship of East Asian summer ARs to heavy rainfall events. This finding helps to better understand the potential hydrological impacts of ARs in East Asia.

Tropical cyclone (TC) peripheral downdrafts and urbanization can promote extreme heatwave (HW) events in the Greater Bay Area (GBA), a highly urbanized coastal area in China. However, the roles of synoptic patterns and urbanization in the HW events remain unclear, particularly for the joint occurrences of the tropical cyclone and heatwave (TC-HW) extremes. Here, we identify three synoptic patterns closely related to TC-HW events, namely: the northeastern Taiwan TC pattern (P4), the southeastern Taiwan TC pattern (P6), and the eastern Taiwan-Philippine Sea TC pattern (P7), as these patterns could enhance HWs through strong downdrafts, strong solar radiation, and low humidity, thereby favoring the maintenance of TC-HW events. Among the three patterns, P6 is most conducive to the occurrence of TC-HW compound events in the GBA. Moreover, the urban-rural temperature disparities under the TC-HW events are unique than those on the days without TC-HW events, i.e., the daily maximum temperature at rural and suburban stations is higher than that at urban stations. This unique feature is the opposite of the urban heat island and is mainly attributed to the rural subsidence warming induced by the TCs and Foehn effects. These results indicate that the spatial distribution of HW in coastal area is substantially modulated by TCs, which is meaningful to understanding the features and underlying mechanism of compound TC-HW events and adapting to their impacts.

2020 and 1998 are the strongest Meiyu years in recent decades. The characteristics of the super-strong Meiyu precipitation and water vapor sources in 2020 and 1998 were compared, and the atmospheric circulation anomalies and the forcing factor SST were examined. (1) In 2020, the Meiyu duration, accumulated precipitation, and number of rainstorm days were greater than in 1998, and the highest since 1961. The Meiyu period in 2020 experienced 11 rainstorm processes. In 1998, a typical “second Meiyu” phenomenon occurred, and the area of heavy rainfall in 1998 was located further southward than that in 2020 (2) The contribution of the Bay of Bengal-South China Sea (BOB-SCS) to the total supply of water vapor in 2020 and 1998 was 43.0% and 42.0%, respectively, i.e., much higher than that of the climatological mean (25.5%). In 2020, the sources that provide most water vapor were the BOB, SCS, and central Pacific Ocean, while in 1998 were the Arabian Sea, BOB, and the western Pacific Ocean. (3) During the Meiyu period in 2020 and 1998, the position of atmospheric circulation pattern “two ridges and one trough” are different. Analysis of the vertical structure revealed that the specific humidity intensity above the area of heavy rainfall in 1998 was weaker than that in 2020, and the low-level convergence zone was further south and not as strong as in 2020. The positions of the western Pacific subtropical high (WPSH) and the western North Pacific anticyclone (WNPAC) in 1998 were both further south than those in 2020, which resulted in the more southerly locations of the southwesterly jet stream and rain belt. It should be pointed out that, the important contributions of the SST anomalies in the equatorial central eastern Pacific and the tropical Indian Ocean to the anomalous WNPAC in 1998 and 2020, respectively.