Weather and Climate Extremes最新文献

The 2022-23 hydrological year in the Lake Titicaca, Desaguadero River, and Lake Poopó hydrological system (TDPS) over the South American Altiplano constituted a historically dry period. This drought was particularly severe during the pre-wet season (October–December), when the TDPS and the adjacent Andean-Amazon region experienced as much as 60% reductions in rainfall. Consequently, Titicaca Lake water levels decreased by 0.05 m from December to January, which is part of the rising lake level period of normal conditions. Such conditions have not been seen since the El Niño-related drought of 1982-83. Using a set of hydroclimatic, Sea Surface Temperature (SST) and atmospheric reanalysis datasets, we find that this new historical drought was associated with enhanced southerly moisture flux anomalies, reducing the inflow of moisture-laden winds from the Amazon basin to the TDPS. Such anomalies in moisture transport were not seen since at least the 1950s. The atmospheric dynamics associated with this drought are related to La Niña SST anomalies via subtropical teleconnections associated with Rossby wave trains towards South America, further extended by subtropical Atlantic Ocean SST anomalies. This feature reduced the atmospheric moisture inflow from the Amazon and weakened the development of the Bolivian High in the upper troposphere. These results document a new atmospheric mechanism related to extreme droughts in the TDPS associated with La Niña SST anomalies during the pre-wet season. This goes beyond the traditional understanding of El Niño events, especially the strongest ones, being associated with dry conditions in the TDPS during the wet season (December–March).

Drought is projected to intensify under warming climate and will continuously threaten global food security. Assessing the risk of yield loss due to drought is key to developing effective agronomic options for farmers and policymakers. However, little has been known about determining the likelihood of reduced crop yield under different drought conditions and defining thresholds that trigger yield loss at the regional scale in Australia. Here, we estimated the dependence of yield variation on drought conditions and identified drought thresholds for 12 Australia's key wheat producing regions with historical yield data by developing bivariate models based on copula functions. These identified drought thresholds were used to investigate drought statistics under climate change with an ensemble of 36 climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that drought-induced yield loss was region-specific. The drought thresholds leading to the same magnitude of wheat yield reduction were smaller in regions of southern Queensland and larger in Western Australia mainly due to different climate and soil conditions. Drought will be more frequent and affect larger areas under future warming climates. Based on our results, we advocate for more effective crop management options, particularly in regions where wheat yield is vulnerable to drought in Australia. This will mitigate potential drought impacts on crop production and safeguard global food security.

The Yangtze River basin experienced record-breaking high temperatures in July–August 2022, leading the China Meteorological Administration to issue its first ever “red heat warning”. We use simulations from the Detection and Attribution Model Intercomparison Project (DAMIP) of the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the role of anthropogenic drivers in this extreme event. We have demonstrated that the strong Western Pacific Subtropical High (WPSH), attributed to internal variability, serves as the clear proximate driver for such extreme event, whether in the factual world or in the counterfactual world. When considering similar circulation patterns in 2022, the results show that anthropogenic forcing has contributed to the 2022-like heatwave by a factor about 7 compared to natural forcing under the present climate of the past 30 years. Specifically, the anthropogenic greenhouse gases made the event about 10 times more likely, while anthropogenic aerosols had negative effect. The results were similar but differed in exact contribution values when specific circulation regimes of 2022 were not considered. In general, global warming caused by anthropogenic activities has made extreme summer heatwaves far more frequent, especially in recent decades.

During summer 2020, Southern China experienced an extremely dry and hot summer, which was identified as one of the top ten domestic weather and climate extreme events in 2020 by China Meteorological Administration. Summer mean precipitation, surface air temperature (TAS), and number of hot days (NHD) were about 25% dryer, 1.5 °C warmer, and 11 days larger than the 1981–2010 climatologies. These are the 4th largest precipitation deficit, the highest TAS, and the 2nd highest NHD in the 1961–2020 record. The large-scale circulation anomalies over the West Pacific increased the likelihood of the extreme hot and dry summer. Anthropogenic influences on this extreme summerwere investigated using 525-member ensembles of the atmosphere-only HadGEM3-GA6 model and the multi-model ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Anthropogenic forcings doubled (increased by 27%) the probability of precipitation deficits, and increased occurrence more than ${10}^6$ times for both TAS anomaly (50 times probability higher) and NHD anomaly (6 times probability higher) in HadGEM-GA6 (CMIP6). That means that the 2020-like TAS and NHD anomalies would not occur without anthropogenic forcings, and there is weak evidence that human influences decrease rainfall over Southern China. However, the precipitation deficit increased the likelihood of exceeding the observed thresholds for both TAS and NHD by about 17 (4) and 9 (1) times in HadGEM3-GA6 (CMIP6), respectively. Under SSP2-4.5 and SSP5-8.5 scenarios in the future, 2020-like hot but wet extreme summer increases in magnitude and frequency, while the frequency of dry summer declines.

Nigeria's growing population faces an increasing heat burden with potential health risks. The Universal Thermal Comfort Index (UTCI) links outdoor conditions and human well-being but lacks comprehensive insitu data in developing regions like Nigeria. ERA5-HEAT reanalysis offers a solution with gridded UTCI and MRT data, but validation is crucial. Thus, this study evaluates the ERA5-HEAT UTCI against data from nine Nigerian weather stations and analysed the spatio-temporal patterns of heat stress trends. Results showed that ERA5-HEAT demonstrated reasonable statistical performance and captured the temporal characteristics and patterns of UTCI across Nigeria's climatic zones. Seasonal variations show heat stress levels from "slightly cold" to "moderate" at 0600 LST and "moderate" to "very strong" at 1500 LST. Geographical consistency exists within each season over the decades, with a critical "very strong" heat stress period during March-May. Additionally, there has been an increasing spatial expansion of areas experiencing higher heat stress levels across the country. Latitudinally, stable patterns exist across decades at 0600 LST for each season. Seasons show distinct UTCI values, and at 1500 LST, more variability and category transitions occur along latitudes. Furthermore, the results indicate significant positive trends and occasional non-significant negative trends over the 40-year period. Notably, during 0600 LST, the Guinea and Sahel regions exhibit relatively higher positive trends than the Sudan region in all seasons, whereas at 1500 LST, high positive trends are prominent in DJF and MAM seasons, indicating increased heat stress during peak seasons. These positive deviations in UTCI are associated with adverse effects on human health, including increased mortality rates.

The Canadian province of British Columbia (BC) is subjected to large-scale, destructive floods. The most dramatic was a mid-November 2021 event when atmospheric rivers (ARs) linked to high-intensity storms caused heavy rainfall in southwestern BC, triggering catastrophic flooding. This study examines 37 floods from 2000 to 2021 using information from over 250 climatological stations and compares events with the mid-November 2021 flood. The dates of the floods showed a bi-modal pattern: a primary season (spring to early summer, 16 floods) and a secondary season (fall to early winter, 21 floods). Five mechanisms controlled these floods: heavy rainfall, rapid snowmelt, severe ice jam, rain-on-snow, and a mixture of snowmelt and ice jam; the mid-November 2021 flood was mainly driven by heavy rainfall. Of the 37 floods, those affected by either heavy rainfall (18 floods) or rain-on-snow (10 floods) were used to derive a relationship between the average daily precipitation amount over the duration of an event and the associated integrated water vapour transport $\left(\overline{IVT}\right)$. Flood events showed a strong linear relationship between these variables with R² $\ge 0.85$, p < 0.05, and values of these parameters were significantly higher for the mid-November 2021 flood than for > 90% of the others, although they were not the highest. The mid-November 2021 flood was also one of the four rainfall-related floods that occurred in the secondary season with $\overline{IVT}$ > 400 kg m⁻¹ s⁻¹. The frequency of flood events over the last five years of the study period has slightly decreased when considering flood events with unknown insured cost. In contrast, insured costs of these events have increased, suggesting that present-day floods are becoming more impactful and may require changes to flood management strategies to reduce costs.

The occurrence of extreme storm surges and precipitation simultaneously or successively can lead to compound flooding. The interaction between extreme storm surges and precipitation holds significant implications for understanding the potential contributing to compound flood risk in coastal areas. This study examines the likelihood of joint occurrence for compound extreme storm surges and precipitation along the China's coastline using observations and model data sets based on tail dependence. We assess the complete characteristics of the tail dependence from observations at the spatio-temporal scale. Subsequently, we perform a principal component analysis to classify the compound flood into 6 synoptic patterns based on the mean sea level pressure data in two typical points (Xiamen and Shijiusuo). We analyze the structure dependence of both observed and simulated surge data and compare the dependence between the historical and the future tail dependence. The result shows that the Yellow Sea and East China Sea exhibit higher dependence compared to the Bohai Sea and South China Sea. The southeastern sea of China has more significant seasonal variation in dependence relative to the northern sea of China. The result indicates that the dominant weather type in Xiamen is associated with low sea pressure and high land pressure, while the type in Shijiusuo is located at the southern edge of a low-pressure center. Projected probabilities of future compound events (2015–2050) have shown substantial increases of 23.9%, 25.38%, 58.21%, and 119.47% over the current period (1979–2014), according to climate models CMCC-CM2-VHR4, GFDL-CMC192-SST, ECEarth3P-HR, and HadGEM3-GC31-HM, respectively. These findings emphasize the correlation between extreme precipitation and storm surges, contributing to a deeper understanding of the compound flood and promoting disaster prevention and control.

The Tinderbox Drought (2017–2019) was one of the most severe droughts recorded in Australia. The extreme summer air temperatures (>40 °C) combined with drought, contributed to the unprecedented Black Summer bushfires in 2019–20 over southeast Australia. Whilst the temperature extremes were largely driven by synoptic processes, it is important to understand to what extent interactions between land and atmosphere played a role. In this study, we use the WRF-LIS-CABLE land-atmosphere coupled model to examine the impacts of changes in leaf area index (LAI) and albedo by contrasting simulations with climatological and time-varying LAI and albedo. We analyse the impact of these biophysical feedbacks on temperature extremes and fire risk during the Tinderbox Drought and the Black Summer bushfires. Remote-sensing data showed a decrease in LAI (0.1–4.0 m² m⁻²) over the three years of the drought along the southeast coast of Australia relative to the long-term climatology, while albedo increased inland (0.02–0.14). These changes in LAI and albedo were accompanied by an overall decrease in daily maximum temperature (T_max) in the vast majority of interior regions (by ∼0.5 °C) and, in the 2019–20 summer, by a clear increase in T_max in the coastal regions of up to ∼1 °C. Increased albedo explained most of the decreases in T_max inland, whereas increases in T_max along the coasts were mostly associated with LAI declines. The magnitude of the impact of biophysical changes on temperature demonstrates the potential impact that would be missed in simulations that assumed fixed vegetation properties. Finally, we only found a small impact from LAI and albedo changes on the fire risk (as measured by the fuel moisture index) preceding the Black Summer bushfires, suggesting these biophysical feedbacks did not significantly modulate fire risk. Our results have implications for coupled simulations relying on climatological LAI and albedo, including operation weather and seasonal climate predictions.

The motivation of our study is to provide forecasters and users complementary guidance and tools to identify and predict atmospheric conditions that could lead to life-threatening flash floods. Using hourly and sub-hourly rainfall datasets, proximity radiosondes, ERA5 reanalysis of extreme rainfall events in the UK during 2000–2020, and case studies in 2021, we observe a three-layered atmospheric structure, consisting of Moist Absolute Unstable Layers (MAULs) embedded in a conditional unstable layer sandwiched between a stable upper layer and a near-stable low layer. Based on our analysis, we propose a conceptual model to describe the atmospheric properties of a ‘rainfall extreme’ environment, with a particular focus on the thermodynamics associated with sub-hourly rainfall production processes. We then set this model within a wider framework to describe the precursor synoptic and mesoscale environments necessary for sub-hourly rainfall extremes in the mid-latitudes. We show that evolution of the Omega block and Rex Vortex couplet provides the optimal environmental conditions for sub-hourly rainfall extremes. These results provide the potential to develop a ‘4-stage’ warning system to assist in the identification and forecasting of life threatening short-duration extreme rainfall intensities and flash floods.

Dry and humid-heat extremes are two types of heat extremes, each exhibiting unique climatological characteristics and impacts on different sectors of society. Using historical simulations and projections produced under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) by models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we show a comparative assessment of the future changes in dry- and humid-heat extremes over global land. Relative to 1995–2014, projections for the mid-term future (2041–2060) and long-term future (2081–2100) periods suggest that most global regions will experience an increase in frequency and intensity of both dry- and humid-heat extremes, especially the tropical regions. In these future periods, the peak occurrences of dry- and humid-heat extremes in mid-to high-latitude regions often occur within the same month. However, there will be a one-to two-month gap between the peak occurrences of dry- and humid-heat extremes in tropical regions, primarily due to monsoonal circulations that introduce variability by causing dry-heat extremes before the onset of monsoons and humid-heat extremes as the monsoons commence. This suggests the need for sector-specific adaptation strategies during different periods of the year for tropical regions. Under both future scenarios, whether considering individual exposure or land area, the average level of exposure to extreme humid-heat days is projected to increase more significantly compared to dry-heat days. The above results highlight the risks associated with the intensification of humid heat in future climate scenarios and warrant the development of effective strategies to mitigate the adverse effects.