Under global warming,understanding the impact of urbanization on the characteristics of different heatwaves is important for sustainable development.In this study,we investigated the changes of heatwaves characteristi...Under global warming,understanding the impact of urbanization on the characteristics of different heatwaves is important for sustainable development.In this study,we investigated the changes of heatwaves characteristics in the Yangtze River Delta urban agglomeration(YRDUG)and analyzed the influencing mechanisms of urbanization.Results showed that:(1)the duration,frequency,and intensity of NHWs(Nighttime Heatwaves)and CHWs(Daytime-nighttime compound Heatwaves)had shown a significant increase and the CHWs showed the greatest increasing trend.Furthermore,the NHWs exhibited higher durations,frequencies,and intensities compared to DHWs(Daytime Heatwaves);(2)Since 1990,the DHWs and CHWs were greater in urban areas than in rural areas,NHWs had been more pronounced in rural areas than in urban centers;and(3)Cloud cover,solar radiation,etc.affected heatwaves.Furthermore,in the process of urbanization,the increase in impervious area and the decrease in green land exacerbated heatwaves.Considering the combined effect of DHWs and NHWs,CHWs continued to increase.展开更多
A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study em...A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.展开更多
Marine heatwaves(MHWs)are extreme ocean events characterized by anomalously warm upper-ocean temperatures,posing significant threats to marine ecosystems.While various factors driving MHWs have been extensively studie...Marine heatwaves(MHWs)are extreme ocean events characterized by anomalously warm upper-ocean temperatures,posing significant threats to marine ecosystems.While various factors driving MHWs have been extensively studied,the role of ocean salinity remains poorly understood.This study investigates the influence of salinity on the major 2013-2014 MHW event in the Northeast Pacific using reanalysis data and climate model outputs.Our results show that salinity variabilities are crucial for the development of the MHW event.Notably,a significant negative correlation exists between sea surface temperature anomalies(SSTAs)and sea surface salinity anomalies(SSSAs)during the MHW,with the SSSAs emerging simultaneously with SSTAs in the same area.Negative salinity anomalies(SAs)result in a shallower mixed layer,which suppresses vertical mixing and thus sustains the upper-ocean warming.Moreover,salinity has a greater impact on mixed layer depth anomalies than temperature.Model sensitivity experiments further demonstrate that negative SAs during MHWs amplify positive SSTAs by enhancing upper-ocean stratification,intensifying the MHW.Additionally,our analysis indicates that the SAs are predominantly driven by local freshwater flux anomalies,which are mainly induced by positive precipitation anomalies during the MHW event.展开更多
Sub-seasonal prediction of regional compound heatwaves and their predictability sources remain unclear.In this study,the underlying mechanisms for the long-lasting compound heatwave over Southern China during July 1–...Sub-seasonal prediction of regional compound heatwaves and their predictability sources remain unclear.In this study,the underlying mechanisms for the long-lasting compound heatwave over Southern China during July 1–18,2010,and the major sources of its sub-seasonal prediction skill are identified.The results show that both the development and decay of this compound heatwave are mainly dominated by atmospheric processes(i.e.,adiabatic heating associated with anticyclonic circulation),whereas land-atmosphere coupling processes play an important role in sustaining the heatwave.A further analysis indicates that by inducing anomalous anticyclonic circulations over Southern China,the tropical intraseasonal oscillations with periods of 30–60 days and 10–30 days facilitate the occurrence and maintenance of the heatwave during its entire and second half periods,respectively.The NCEP Climate Forecast System Version 2 shows a low skill in predicting the 2010 compound heatwave over Southern China when the lead time is longer than 2 pentads,which is largely attributed to the model’s bias in representing the intensity and phase of intra-seasonal oscillations.展开更多
Marine heatwave(MHW)events refer to periods of significantly elevated sea surface temperatures(SST),persisting from days to months,with significant impacts on marine ecosystems,including increased mortality among mari...Marine heatwave(MHW)events refer to periods of significantly elevated sea surface temperatures(SST),persisting from days to months,with significant impacts on marine ecosystems,including increased mortality among marine life and coral bleaching.Forecasting MHW events are crucial to mitigate their harmful effects.This study presents a twostep forecasting process:short-term SST prediction followed by MHW event detection based on the forecasted SST.Firstly,we developed the“SST-MHW-DL”model using the ConvLSTM architecture,which incorporates an attention mechanism to enhance both SST forecasting and MHW event detection.The model utilizes SST data from the preceding 60 d to forecast SST and detect MHW events for the subsequent 15 d.Verification results for SST forecasting demonstrate a root mean square error(RMSE)of 0.64℃,a mean absolute percentage error(MAPE)of 2.05%,and a coefficient of determination(R^(2))of 0.85,indicating the model’s ability to accurately predict future temperatures by leveraging historical sea temperature information.For MHW event detection using forecasted SST,the evaluation metrics of“accuracy”,“precision”,and“recall”achieved values of 0.77,0.73,and 0.43,respectively,demonstrating the model’s capability to capture the occurrence of MHW events accurately.Furthermore,the attention-enhanced mechanism reveals that recent SST variations within the past 10 days have the most significant impact on forecasting accuracy,while variations in deep-sea regions and along the Taiwan Strait significantly contribute to the model’s efficacy in capturing spatial characteristics.Additionally,the proposed model and temporal mechanism were applied to detect MHWs in the Atlantic Ocean.By inputting 30 d of SST data,the model predicted SST with an RMSE of 1.02℃and an R^(2)of 0.94.The accuracy,precision,and recall for MHW detection were 0.79,0.78,and 0.62,respectively,further demonstrating the model’s robustness and usability.展开更多
Marine heatwaves(MHWs)have become increasingly frequent and persistent in the context of global warming and the related underlying mechanisms are strongly region-dependent.We employed the NOAA(National Oceanic and Atm...Marine heatwaves(MHWs)have become increasingly frequent and persistent in the context of global warming and the related underlying mechanisms are strongly region-dependent.We employed the NOAA(National Oceanic and Atmospheric Administration)CRW(Coral Reef Watch)daily mean sea surface temperature dataset spanning from 1985 to 2022 to comprehensively analyze the fundamental attributes and evolving patterns of marine heatwaves in the offshore waters of China.Eight pronounced marine heatwaves from frequently affected sensitive regions were investigated to explore their formation mechanisms.The relationship between the occurrences of marine heatwave and large-scale climate mode in the region was explored.Results show that the western Pacific subtropical high plays an essential role in triggering marine heatwaves in Chinese offshore waters,with an anomalous downward shortwave radiation flux acting to warm the sea surface,which is remotely associated to the large-scale sea surface temperature state.Distinct mechanisms for the MHWs were identified in the northern and southern offshore waters of China.MHWs in high latitudes(such as the Bohai Sea and the Yellow Sea)mainly occur during the negative phase of the Pacific Decadal Oscillation(PDO),while those in low latitudes(such as the South China Sea)are more common in about 5-month lags behind the El Niño,for which we purposed a mechanism to describe the main differences in the formation of MHWs in China and discussed the related implications.展开更多
Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in differen...Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.展开更多
India is highly vulnerable to climate change and is going to increase its average annual temperature over the next few decades.The impact of heatwaves and related mortality is a concern for the country.In this paper,w...India is highly vulnerable to climate change and is going to increase its average annual temperature over the next few decades.The impact of heatwaves and related mortality is a concern for the country.In this paper,we aim to study the heatwaves and heat stress-related Heat Index vulnerability using heat index temperature.In this analysis,a heat in-dex temperature is calculated based on temperature and relative humidity for six different states(Delhi,West Bengal,Punjab,Uttar Pradesh,Andhra Pradesh,and Madhya Pradesh)of India to determine the heat stress vulnerability for which heat cramps and heat strokes are possible.Our analysis shows that most of the heatwaves and severe heatwaves occurred during 2010 for all the states.The heatwaves are observed only in the summer months.All the states of our study reached the Extreme Caution category of the Heat Index showing the Danger to Extreme Danger category dur-ing April to June.Future projection scenarios show an increase in heat stress-related vulnerability.SSP2-4.5 scenario showed that Delhi,Punjab,and West Bengal reached an Extreme Danger state during June for which death due to heat strokes is possible under continued exposure to heatwaves.The HI related vulnerability of SSP5-8.5 is like SSP2-4.5 except for Andhra Pradesh which shows an Extreme Danger state in May and June during which heat strokes are possi-ble under continued exposure to heatwaves.This study provides spatial variability of heat stress and Heat Index vulner-ability which may help adopt future strategies for heat-related policy implication.展开更多
Marine heatwaves(MHWs)in the East China Sea(ECS),especially those occurring on the ocean bottom(referred to as bottom marine heatwaves,BMHWs),can significantly affect regional ecosystems.However,our understanding of t...Marine heatwaves(MHWs)in the East China Sea(ECS),especially those occurring on the ocean bottom(referred to as bottom marine heatwaves,BMHWs),can significantly affect regional ecosystems.However,our understanding of the seasonal variations in the MHWs in the ECS remains limited.This study investigates the characteristics of MHWs in the ECS in summer and winter using high-resolution oceanic reanalysis.Our analyses reveal distinct spatial patterns of BMHWs in these seasons.During summer,the Taiwan Warm Current plays a crucial role in transporting warm water northward,potentially leading to intense BMHWs on the central ECS shelf.These BMHW events usually occur independently of surface warming due to strong stratification in summer.Conversely,winter BMHWs are more prevalent in coastal regions under the influence of coastal currents and typically feature consistent warming from surface to bottom with a deepened mixed layer.These findings inform the coherent vertical structure and driving mechanisms of MHWs in the ECS,which are essential for predicting and managing these extreme events in the future.展开更多
Marine heatwaves(MHWs),which can exert devastating socioeconomic and ecological impacts,have attracted much public interest in recent years.In this study,we evaluate the sub-seasonal forecast skill of MHWs based on th...Marine heatwaves(MHWs),which can exert devastating socioeconomic and ecological impacts,have attracted much public interest in recent years.In this study,we evaluate the sub-seasonal forecast skill of MHWs based on the Nanjing University of Information Science&Technology Climate Forecast System version 1.1(NUIST CFS1.1)and analyze the related physical processes.Our results show that the model can accurately forecast the occurrence of MHWs on a global scale out to a lead time of 25 days.Notably,even at lead times of 51–55 days,the forecast skill in most tropical regions,as well as in the northeastern and southeastern Pacific,is superior to both random forecasts and persistence forecasts.Accurate predictions of sea level pressure,zonal currents,and mixed-layer depth are important for MHW forecasting.Furthermore,we also conduct forecast skill assessments for two well-documented MHW events.Due to its ability to correctly forecast the changes in heat flux anomalies at a lead time of 25 days,the model can accurately forecast the strong MHW event that occurred in the South China Sea in May–October 2020.However,the forecasting results were less than optimal for the strong MHW event that occurred along the Australian west coast in January–April 2011.Although the model accurately forecasts its occurrence,the forecast of its intensity is poor.Additionally,when the lead time exceeds 10 days,forecasts of the relevant physical processes of this MHW event are also inaccurate.展开更多
With the intensification of global warming,marine heatwaves(MHWs)have emerged as a significant extreme hazard,garnering widespread attention and creating a pressing need for accurate prediction.The development of arti...With the intensification of global warming,marine heatwaves(MHWs)have emerged as a significant extreme hazard,garnering widespread attention and creating a pressing need for accurate prediction.The development of artificial intelligence,particularly the application of deep learning to sea surface temperature(SST),has significantly improved the feasibility of predictions.This study utilizes SST and Outgoing Longwave Radiation(OLR)data to train a 3D U-Net model for predicting MHWs in the South China Sea(SCS)with lead times ranging from 1 to 7 days,based on the characteristics of intraseasonal weather processes.Analysis of MHWs occurrences from 1982 to 2023 reveals distinct seasonal patterns,with summer MHWs primarily concentrated in the northern and central SCS,and the highest temperature centers located in the Gulf of Tonkin and west of the Philippines.The 2023 MHW forecast results demonstrate that the 3D U-Net model achieves low error rates and high correlation coefficients with observational data.Incorporating OLR data enhances forecast accuracy compared to SST-only inputs,and training the model exclusively with summer data further improves prediction accuracy.These findings indicate that the proposed method can significantly enhance the accuracy of MHW forecasts.展开更多
The Yangtze River Valley(YRV) of China experienced record-breaking heatwaves in July and August 2022. The characteristics, causes, and impacts of this extreme event have been widely explored, but its seasonal predicta...The Yangtze River Valley(YRV) of China experienced record-breaking heatwaves in July and August 2022. The characteristics, causes, and impacts of this extreme event have been widely explored, but its seasonal predictability remains elusive. This study assessed the real-time one-month-lead prediction skill of the summer 2022 YRV heatwaves using 12operational seasonal forecast systems. Results indicate that most individual forecast systems and their multi-model ensemble(MME) mean exhibited limited skill in predicting the 2022 YRV heatwaves. Notably, after the removal of the linear trend, the predicted 2-m air temperature anomalies were generally negative in the YRV, except for the Met Office Glo Sea6 system, which captured a moderate warm anomaly. While the models successfully simulated the influence of La Ni?a on the East Asian–western North Pacific atmospheric circulation and associated YRV temperature anomalies, only Glo Sea6 reasonably captured the observed relationship between the YRV heatwaves and an atmospheric teleconnection extending from the North Atlantic to the Eurasian mid-to-high latitudes. Such an atmospheric teleconnection plays a crucial role in intensifying the YRV heatwaves. In contrast, other seasonal forecast systems and the MME predicted a distinctly different atmospheric circulation pattern, particularly over the Eurasian mid-to-high latitudes, and failed to reproduce the observed relationship between the YRV heatwaves and Eurasian mid-to-high latitude atmospheric circulation anomalies.These findings underscore the importance of accurately representing the Eurasian mid-to-high latitude atmospheric teleconnection for successful YRV heatwave prediction.展开更多
Under global warming,understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress.This study investigates dry and wet heatwave shifts in easte...Under global warming,understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress.This study investigates dry and wet heatwave shifts in eastern China over recent decades.Spatial trend analysis displays pronounced warming in inland midlatitudes and the Yangtze River Valley,with increased humidity in coastal regions.EOF results indicate intensifying dry heatwaves in northern China,while the Yangtze River Valley sees more frequent dry heatwaves.On the other hand,Indochina and regions north of 25°N also experience intensified wet heatwaves,corresponding to regional humidity increases.Composite analysis is conducted based on different situations:strong,frequent dry or wet heatwaves.Strong dry heatwaves are influenced by anticyclonic circulations over northern China,accompanied by warming SST anomalies around the coastal midlatitudes of the western North Pacific(WNP).Frequent dry heatwaves are related to strong subsidence along with a strengthened subtropical high over the WNP.Strong and frequent wet heatwaves show an intensified Okhotsk high at higher latitudes in the lower troposphere,and a negative circumglobal teleconnection wave train pattern in the upper troposphere.Decaying El Niño SST patterns are observed in two kinds of wet heatwave and frequent dry heatwave years.Risk analysis indicates that El Niño events heighten the likelihood of these heatwaves in regions most at risk.As global warming continues,adapting and implementing mitigation strategies toward extreme heatwaves becomes crucial,especially for the aforementioned regions under significant heat stress.展开更多
We chose a definition of heatwaves (HWs) that has ~4-year recurrence frequency at world hot spots. We first examined the 1940-2022 HWs climatology and trends in lifespan, severity, spatial extent, and recurrence frequ...We chose a definition of heatwaves (HWs) that has ~4-year recurrence frequency at world hot spots. We first examined the 1940-2022 HWs climatology and trends in lifespan, severity, spatial extent, and recurrence frequency. HWs are becoming more frequent and more severe for extratropical mid- and low-latitudes. To euphemize HWs, we here propose a novel clean energy-tapping concept that utilizes the available nano-technology, micro-meteorology knowledge of temperature distribution within/without buildings, and radiative properties of earth atmosphere. The key points for a practical electricity generation scheme from HWs are defogging, insulation, and minimizing the absorption of infrared downward radiation at the cold legs of the thermoelectric generators. One sample realization is presented which, through relay with existing photovoltaic devices, provides all-day electricity supply sufficient for providing air conditioning requirement for a residence (~2000-watt throughput). The provision of power to air conditioning systems, usually imposes a significant stress on traditional city power grids during heatwaves.展开更多
In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since 1961.In this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in th...In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since 1961.In this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV,focusing on the city of Shanghai.We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming.During mid-summer of 2022,an enhanced western Pacific subtropical high(WPSH)and anomalous double blockings over the Ural Mountains and Sea of Okhotsk,respectively,were associated with the persistently anomalous high pressure over the YRV,leading to the extreme HW.The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale.Also,the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern.Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH.At the subseasonal time scale,the anomalously frequent phases 2-5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden-Julian Oscillation suppressed the convection over the YRV and also contributed to the HW.Therefore,the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales.展开更多
Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast s...Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves(MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean(TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Nino-Southern Oscillation(ENSO). The forecast skills for the MHWs over the tropical Indian Ocean(TIO), tropical Atlantic Ocean(TAO), and tropical Northwest Pacific(NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window(less than 17 months) occurs for the TAO and NWP.Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer.展开更多
This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2...This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.展开更多
Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongl...Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend.展开更多
Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurren...Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurrences of heatwaves between the grid cells in East Asia and Eastern Europe,even though they are geographically far away from each other.By further composite analysis,this study revealed that hot events first occurred in Eastern Europe,typically with a time lag of3-4 days before the East Asian heatwave events.An eastward propagating atmospheric wave train,known as the circumglobal teleconnection(CGT)pattern,bridged the sequent occurrences of extreme events in these two remote regions.Atmospheric blockings,amplified by surface warming over Eastern Europe,not only enhanced local heat extremes but also excited a CGT-like pattern characterized by alternative anomalies of high and low pressures.Subsequent downstream anticyclones in the middle and upper troposphere reduced local cloud cover and increased downward solar radiation,thereby facilitating the formation of heatwaves over East Asia.Nearly half of East Asian heatwave events were preceded by Eastern European heatwave events in the 10-day time range before East Asian heatwave events.This investigation of heatwave teleconnection in the two distant regions exhibits strong potential to improve the prediction accuracy of East Asian heatwaves.展开更多
Daily maximum/minimum temperatures and relative humidity records from 510 stations in China for the period 1960–2008 were used to investigate geographical patterns and temporal variations of heatwave （HW） events. D...Daily maximum/minimum temperatures and relative humidity records from 510 stations in China for the period 1960–2008 were used to investigate geographical patterns and temporal variations of heatwave （HW） events. Dry and wet HW events were compared by different definitions. Regionally, both dry and wet HW events are commonly located in southeastern China in the monsoon area, with neither type occurring in the northeast part of Northeast China and Southwest China, while the north-northwest region of the country experiences dry HW events and a few wet HW events. In the southeast of the country, site dry HW events occurred from April to September and mostly in June, while site wet HW events occurred from April to October and mostly in September. In total, 163 regional wet HW events were identified. The ten longest regional wet HW events lasted for more than 20 days, while the mean duration for 163 events was about 11 days. For the top ten events, six occurred after the 1990s, compared with four before this time. Global surface warming was clear since 1979, but the frequency and severity of regional wet HW events were relatively low in the 1980s, increasing remarkably since the 1990s. Possible reasons for this might be the strong interdecadal and interannual variations in regional atmospheric circulations, as well as water transport related directly to temperature contrasts in different regions, rather than global-mean temperature changes.展开更多
基金National Natural Science Foundation of China,No.42271037Natural Science Foundation of Anhui Province,No.2408085MD095+2 种基金Key Research and Development Program Project of Anhui Province,No.2022m07020011University Synergy Innovation Program of Anhui Province,No.GXXT-2021-048Science Foundation for Excellent Young Scholars of Anhui,No.2108085Y13。
文摘Under global warming,understanding the impact of urbanization on the characteristics of different heatwaves is important for sustainable development.In this study,we investigated the changes of heatwaves characteristics in the Yangtze River Delta urban agglomeration(YRDUG)and analyzed the influencing mechanisms of urbanization.Results showed that:(1)the duration,frequency,and intensity of NHWs(Nighttime Heatwaves)and CHWs(Daytime-nighttime compound Heatwaves)had shown a significant increase and the CHWs showed the greatest increasing trend.Furthermore,the NHWs exhibited higher durations,frequencies,and intensities compared to DHWs(Daytime Heatwaves);(2)Since 1990,the DHWs and CHWs were greater in urban areas than in rural areas,NHWs had been more pronounced in rural areas than in urban centers;and(3)Cloud cover,solar radiation,etc.affected heatwaves.Furthermore,in the process of urbanization,the increase in impervious area and the decrease in green land exacerbated heatwaves.Considering the combined effect of DHWs and NHWs,CHWs continued to increase.
基金supported by the National Natural Science Foundation of China [grant number 42030605]the National Key R&D Program of China [grant number 2020YFA0608004]。
文摘A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.
基金The Laoshan Laboratory under contract Nos LSKJ202202403 and LSKJ202202402the National Natural Science Foundation of China under contract Nos 42030410 and 42406202+3 种基金the Natural Science Foundation of Jiangsu Province under contract No.BK20240718the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technologythe Jiangsu Innovation Research Group under contract No.JSSCTD202346the Jiangsu Funding Program for Excellent Postdoctoral Talent under contract No.2023ZB690.
文摘Marine heatwaves(MHWs)are extreme ocean events characterized by anomalously warm upper-ocean temperatures,posing significant threats to marine ecosystems.While various factors driving MHWs have been extensively studied,the role of ocean salinity remains poorly understood.This study investigates the influence of salinity on the major 2013-2014 MHW event in the Northeast Pacific using reanalysis data and climate model outputs.Our results show that salinity variabilities are crucial for the development of the MHW event.Notably,a significant negative correlation exists between sea surface temperature anomalies(SSTAs)and sea surface salinity anomalies(SSSAs)during the MHW,with the SSSAs emerging simultaneously with SSTAs in the same area.Negative salinity anomalies(SAs)result in a shallower mixed layer,which suppresses vertical mixing and thus sustains the upper-ocean warming.Moreover,salinity has a greater impact on mixed layer depth anomalies than temperature.Model sensitivity experiments further demonstrate that negative SAs during MHWs amplify positive SSTAs by enhancing upper-ocean stratification,intensifying the MHW.Additionally,our analysis indicates that the SAs are predominantly driven by local freshwater flux anomalies,which are mainly induced by positive precipitation anomalies during the MHW event.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(42105015)+3 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515010659)Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(SML2023SP209)Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021001)Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(2020B1212060025)。
文摘Sub-seasonal prediction of regional compound heatwaves and their predictability sources remain unclear.In this study,the underlying mechanisms for the long-lasting compound heatwave over Southern China during July 1–18,2010,and the major sources of its sub-seasonal prediction skill are identified.The results show that both the development and decay of this compound heatwave are mainly dominated by atmospheric processes(i.e.,adiabatic heating associated with anticyclonic circulation),whereas land-atmosphere coupling processes play an important role in sustaining the heatwave.A further analysis indicates that by inducing anomalous anticyclonic circulations over Southern China,the tropical intraseasonal oscillations with periods of 30–60 days and 10–30 days facilitate the occurrence and maintenance of the heatwave during its entire and second half periods,respectively.The NCEP Climate Forecast System Version 2 shows a low skill in predicting the 2010 compound heatwave over Southern China when the lead time is longer than 2 pentads,which is largely attributed to the model’s bias in representing the intensity and phase of intra-seasonal oscillations.
基金The National Natural Science Foundation of China under contract Nos 42376175,42090044 and U2006211。
文摘Marine heatwave(MHW)events refer to periods of significantly elevated sea surface temperatures(SST),persisting from days to months,with significant impacts on marine ecosystems,including increased mortality among marine life and coral bleaching.Forecasting MHW events are crucial to mitigate their harmful effects.This study presents a twostep forecasting process:short-term SST prediction followed by MHW event detection based on the forecasted SST.Firstly,we developed the“SST-MHW-DL”model using the ConvLSTM architecture,which incorporates an attention mechanism to enhance both SST forecasting and MHW event detection.The model utilizes SST data from the preceding 60 d to forecast SST and detect MHW events for the subsequent 15 d.Verification results for SST forecasting demonstrate a root mean square error(RMSE)of 0.64℃,a mean absolute percentage error(MAPE)of 2.05%,and a coefficient of determination(R^(2))of 0.85,indicating the model’s ability to accurately predict future temperatures by leveraging historical sea temperature information.For MHW event detection using forecasted SST,the evaluation metrics of“accuracy”,“precision”,and“recall”achieved values of 0.77,0.73,and 0.43,respectively,demonstrating the model’s capability to capture the occurrence of MHW events accurately.Furthermore,the attention-enhanced mechanism reveals that recent SST variations within the past 10 days have the most significant impact on forecasting accuracy,while variations in deep-sea regions and along the Taiwan Strait significantly contribute to the model’s efficacy in capturing spatial characteristics.Additionally,the proposed model and temporal mechanism were applied to detect MHWs in the Atlantic Ocean.By inputting 30 d of SST data,the model predicted SST with an RMSE of 1.02℃and an R^(2)of 0.94.The accuracy,precision,and recall for MHW detection were 0.79,0.78,and 0.62,respectively,further demonstrating the model’s robustness and usability.
基金Supported by the National Natural Science Foundation of China(No.41905089)the Laoshan Laboratory(No.LSKJ202202404)+1 种基金the Startup Foundation for Introducing Talent of NUIST,Jiangsu Innovation Research Group(No.JSSCTD202346)the Undergraduates Innovation and Entrepreneurship Training Program of Jiangsu Province(No.202310300087Y)。
文摘Marine heatwaves(MHWs)have become increasingly frequent and persistent in the context of global warming and the related underlying mechanisms are strongly region-dependent.We employed the NOAA(National Oceanic and Atmospheric Administration)CRW(Coral Reef Watch)daily mean sea surface temperature dataset spanning from 1985 to 2022 to comprehensively analyze the fundamental attributes and evolving patterns of marine heatwaves in the offshore waters of China.Eight pronounced marine heatwaves from frequently affected sensitive regions were investigated to explore their formation mechanisms.The relationship between the occurrences of marine heatwave and large-scale climate mode in the region was explored.Results show that the western Pacific subtropical high plays an essential role in triggering marine heatwaves in Chinese offshore waters,with an anomalous downward shortwave radiation flux acting to warm the sea surface,which is remotely associated to the large-scale sea surface temperature state.Distinct mechanisms for the MHWs were identified in the northern and southern offshore waters of China.MHWs in high latitudes(such as the Bohai Sea and the Yellow Sea)mainly occur during the negative phase of the Pacific Decadal Oscillation(PDO),while those in low latitudes(such as the South China Sea)are more common in about 5-month lags behind the El Niño,for which we purposed a mechanism to describe the main differences in the formation of MHWs in China and discussed the related implications.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFE0136000 and 2024YFC3013100)the Joint Meteorological Fund(Grant No.U2342211)+1 种基金the Joint Research Project for Meteorological Capacity Improvement(Grant No.22NLTSZ004)the National Meteorological Information Center(Grant No.NMICJY202301)。
文摘Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.
文摘India is highly vulnerable to climate change and is going to increase its average annual temperature over the next few decades.The impact of heatwaves and related mortality is a concern for the country.In this paper,we aim to study the heatwaves and heat stress-related Heat Index vulnerability using heat index temperature.In this analysis,a heat in-dex temperature is calculated based on temperature and relative humidity for six different states(Delhi,West Bengal,Punjab,Uttar Pradesh,Andhra Pradesh,and Madhya Pradesh)of India to determine the heat stress vulnerability for which heat cramps and heat strokes are possible.Our analysis shows that most of the heatwaves and severe heatwaves occurred during 2010 for all the states.The heatwaves are observed only in the summer months.All the states of our study reached the Extreme Caution category of the Heat Index showing the Danger to Extreme Danger category dur-ing April to June.Future projection scenarios show an increase in heat stress-related vulnerability.SSP2-4.5 scenario showed that Delhi,Punjab,and West Bengal reached an Extreme Danger state during June for which death due to heat strokes is possible under continued exposure to heatwaves.The HI related vulnerability of SSP5-8.5 is like SSP2-4.5 except for Andhra Pradesh which shows an Extreme Danger state in May and June during which heat strokes are possi-ble under continued exposure to heatwaves.This study provides spatial variability of heat stress and Heat Index vulner-ability which may help adopt future strategies for heat-related policy implication.
基金The National Natural Science Foundation of China under contract No.42030410the Laoshan Laboratory under contract Nos LSKJ202202404 and LSKJ202202403+2 种基金the Startup Foundation for Introducing Talent of Nanjing University of Information Science and TechnologyJiangsu Innovation Research Group under contract No.JSSCTD202346Jiangsu Funding Program for Excellent Postdoctoral Talent under contract No.2023ZB690。
文摘Marine heatwaves(MHWs)in the East China Sea(ECS),especially those occurring on the ocean bottom(referred to as bottom marine heatwaves,BMHWs),can significantly affect regional ecosystems.However,our understanding of the seasonal variations in the MHWs in the ECS remains limited.This study investigates the characteristics of MHWs in the ECS in summer and winter using high-resolution oceanic reanalysis.Our analyses reveal distinct spatial patterns of BMHWs in these seasons.During summer,the Taiwan Warm Current plays a crucial role in transporting warm water northward,potentially leading to intense BMHWs on the central ECS shelf.These BMHW events usually occur independently of surface warming due to strong stratification in summer.Conversely,winter BMHWs are more prevalent in coastal regions under the influence of coastal currents and typically feature consistent warming from surface to bottom with a deepened mixed layer.These findings inform the coherent vertical structure and driving mechanisms of MHWs in the ECS,which are essential for predicting and managing these extreme events in the future.
基金supported by National Natural Science Foundation of China(Grant Nos.42030605 and 42088101)National Key R&D Program of China(Grant No.2020YFA0608004)High Performance Computing of Nanjing University of Information Science&Technology for their support of this work。
文摘Marine heatwaves(MHWs),which can exert devastating socioeconomic and ecological impacts,have attracted much public interest in recent years.In this study,we evaluate the sub-seasonal forecast skill of MHWs based on the Nanjing University of Information Science&Technology Climate Forecast System version 1.1(NUIST CFS1.1)and analyze the related physical processes.Our results show that the model can accurately forecast the occurrence of MHWs on a global scale out to a lead time of 25 days.Notably,even at lead times of 51–55 days,the forecast skill in most tropical regions,as well as in the northeastern and southeastern Pacific,is superior to both random forecasts and persistence forecasts.Accurate predictions of sea level pressure,zonal currents,and mixed-layer depth are important for MHW forecasting.Furthermore,we also conduct forecast skill assessments for two well-documented MHW events.Due to its ability to correctly forecast the changes in heat flux anomalies at a lead time of 25 days,the model can accurately forecast the strong MHW event that occurred in the South China Sea in May–October 2020.However,the forecasting results were less than optimal for the strong MHW event that occurred along the Australian west coast in January–April 2011.Although the model accurately forecasts its occurrence,the forecast of its intensity is poor.Additionally,when the lead time exceeds 10 days,forecasts of the relevant physical processes of this MHW event are also inaccurate.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)。
文摘With the intensification of global warming,marine heatwaves(MHWs)have emerged as a significant extreme hazard,garnering widespread attention and creating a pressing need for accurate prediction.The development of artificial intelligence,particularly the application of deep learning to sea surface temperature(SST),has significantly improved the feasibility of predictions.This study utilizes SST and Outgoing Longwave Radiation(OLR)data to train a 3D U-Net model for predicting MHWs in the South China Sea(SCS)with lead times ranging from 1 to 7 days,based on the characteristics of intraseasonal weather processes.Analysis of MHWs occurrences from 1982 to 2023 reveals distinct seasonal patterns,with summer MHWs primarily concentrated in the northern and central SCS,and the highest temperature centers located in the Gulf of Tonkin and west of the Philippines.The 2023 MHW forecast results demonstrate that the 3D U-Net model achieves low error rates and high correlation coefficients with observational data.Incorporating OLR data enhances forecast accuracy compared to SST-only inputs,and training the model exclusively with summer data further improves prediction accuracy.These findings indicate that the proposed method can significantly enhance the accuracy of MHW forecasts.
基金jointly supported by the National Key Research and Development Program of China (2023YFC3007503)the Joint Research Project for Meteorological Capacity Improvement (22NLTSZ002)+4 种基金the National Natural Science Foundations of China (Grant Nos.42375064, 41975102, 41730964, 42175047)the China Meteorological Administration Key Innovation Team for Climate Prediction (CMA2023ZD03)the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)the Special Project of Innovation and Development of China Meteorological Administration (CXFZ2024J004)the China Yangtze Power Co.,Ltd.Research Project (Grant No.2423020054)。
文摘The Yangtze River Valley(YRV) of China experienced record-breaking heatwaves in July and August 2022. The characteristics, causes, and impacts of this extreme event have been widely explored, but its seasonal predictability remains elusive. This study assessed the real-time one-month-lead prediction skill of the summer 2022 YRV heatwaves using 12operational seasonal forecast systems. Results indicate that most individual forecast systems and their multi-model ensemble(MME) mean exhibited limited skill in predicting the 2022 YRV heatwaves. Notably, after the removal of the linear trend, the predicted 2-m air temperature anomalies were generally negative in the YRV, except for the Met Office Glo Sea6 system, which captured a moderate warm anomaly. While the models successfully simulated the influence of La Ni?a on the East Asian–western North Pacific atmospheric circulation and associated YRV temperature anomalies, only Glo Sea6 reasonably captured the observed relationship between the YRV heatwaves and an atmospheric teleconnection extending from the North Atlantic to the Eurasian mid-to-high latitudes. Such an atmospheric teleconnection plays a crucial role in intensifying the YRV heatwaves. In contrast, other seasonal forecast systems and the MME predicted a distinctly different atmospheric circulation pattern, particularly over the Eurasian mid-to-high latitudes, and failed to reproduce the observed relationship between the YRV heatwaves and Eurasian mid-to-high latitude atmospheric circulation anomalies.These findings underscore the importance of accurately representing the Eurasian mid-to-high latitude atmospheric teleconnection for successful YRV heatwave prediction.
基金supported by the National Natural Science Foundation of China(Grant Nos.42120104001,42192563 and 42005010)the Hong Kong RGC General Research Fund 11300920.
文摘Under global warming,understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress.This study investigates dry and wet heatwave shifts in eastern China over recent decades.Spatial trend analysis displays pronounced warming in inland midlatitudes and the Yangtze River Valley,with increased humidity in coastal regions.EOF results indicate intensifying dry heatwaves in northern China,while the Yangtze River Valley sees more frequent dry heatwaves.On the other hand,Indochina and regions north of 25°N also experience intensified wet heatwaves,corresponding to regional humidity increases.Composite analysis is conducted based on different situations:strong,frequent dry or wet heatwaves.Strong dry heatwaves are influenced by anticyclonic circulations over northern China,accompanied by warming SST anomalies around the coastal midlatitudes of the western North Pacific(WNP).Frequent dry heatwaves are related to strong subsidence along with a strengthened subtropical high over the WNP.Strong and frequent wet heatwaves show an intensified Okhotsk high at higher latitudes in the lower troposphere,and a negative circumglobal teleconnection wave train pattern in the upper troposphere.Decaying El Niño SST patterns are observed in two kinds of wet heatwave and frequent dry heatwave years.Risk analysis indicates that El Niño events heighten the likelihood of these heatwaves in regions most at risk.As global warming continues,adapting and implementing mitigation strategies toward extreme heatwaves becomes crucial,especially for the aforementioned regions under significant heat stress.
文摘We chose a definition of heatwaves (HWs) that has ~4-year recurrence frequency at world hot spots. We first examined the 1940-2022 HWs climatology and trends in lifespan, severity, spatial extent, and recurrence frequency. HWs are becoming more frequent and more severe for extratropical mid- and low-latitudes. To euphemize HWs, we here propose a novel clean energy-tapping concept that utilizes the available nano-technology, micro-meteorology knowledge of temperature distribution within/without buildings, and radiative properties of earth atmosphere. The key points for a practical electricity generation scheme from HWs are defogging, insulation, and minimizing the absorption of infrared downward radiation at the cold legs of the thermoelectric generators. One sample realization is presented which, through relay with existing photovoltaic devices, provides all-day electricity supply sufficient for providing air conditioning requirement for a residence (~2000-watt throughput). The provision of power to air conditioning systems, usually imposes a significant stress on traditional city power grids during heatwaves.
基金the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030004)the National Natural Science Foundation of China(Grant No.42175056)+3 种基金the Natural Science Foundation of Shanghai(Grant No.21ZR1457600)Review and Summary Project of China Meteorological Administration(Grant No.FPZJ2023-044)the China Meteorological Administration Innovation and Development Project(Grant No.CXFZ2022J009)the Key Innovation Team of Climate Prediction of the China Meteorological Administration(Grant No.CMA2023ZD03).
文摘In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since 1961.In this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV,focusing on the city of Shanghai.We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming.During mid-summer of 2022,an enhanced western Pacific subtropical high(WPSH)and anomalous double blockings over the Ural Mountains and Sea of Okhotsk,respectively,were associated with the persistently anomalous high pressure over the YRV,leading to the extreme HW.The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale.Also,the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern.Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH.At the subseasonal time scale,the anomalously frequent phases 2-5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden-Julian Oscillation suppressed the convection over the YRV and also contributed to the HW.Therefore,the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.42192562 and 42030605)。
文摘Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves(MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean(TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Nino-Southern Oscillation(ENSO). The forecast skills for the MHWs over the tropical Indian Ocean(TIO), tropical Atlantic Ocean(TAO), and tropical Northwest Pacific(NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window(less than 17 months) occurs for the TAO and NWP.Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer.
基金The National Natural Science Foundation of China under contract Nos 42275024 and 42105040the Key R&D Program of China under contract No.2022YFE0203500+3 种基金the Guangdong Basic and Applied Basic Research Foundation under contract Nos 2023B1515020009 and 2024B1515040024the Youth Innovation Promotion Association CAS under contract No.2020340the Special Fund of South China Sea Institute of Oceanology of the Chinese Academy of Sciences under contract No.SCSIO2023QY01the Science and Technology Planning Project of Guangzhou under contract No.2024A04J6275.
文摘This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.
基金Supported by the National Natural Science Foundation of China(Nos.41821004,42276025)the Natural Science Foundation of Shandong Province(No.ZR2021MD027)+1 种基金the National Key Research and Development Program of China(No.2022YFE0140500)the Project of“Development of China-ASEAN blue partnership”started in 2021.
文摘Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend.
基金Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004)National Natural Science Foundation of China (42275020)+1 种基金Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (311021001)Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies (2020B1212060025)。
文摘Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurrences of heatwaves between the grid cells in East Asia and Eastern Europe,even though they are geographically far away from each other.By further composite analysis,this study revealed that hot events first occurred in Eastern Europe,typically with a time lag of3-4 days before the East Asian heatwave events.An eastward propagating atmospheric wave train,known as the circumglobal teleconnection(CGT)pattern,bridged the sequent occurrences of extreme events in these two remote regions.Atmospheric blockings,amplified by surface warming over Eastern Europe,not only enhanced local heat extremes but also excited a CGT-like pattern characterized by alternative anomalies of high and low pressures.Subsequent downstream anticyclones in the middle and upper troposphere reduced local cloud cover and increased downward solar radiation,thereby facilitating the formation of heatwaves over East Asia.Nearly half of East Asian heatwave events were preceded by Eastern European heatwave events in the 10-day time range before East Asian heatwave events.This investigation of heatwave teleconnection in the two distant regions exhibits strong potential to improve the prediction accuracy of East Asian heatwaves.
基金supported jointly by the National Natural Science Foundation of China (Grant No.40975039),GYHY201006018the Key Technologies R&D Program (Grant No. 2009BAC51B00)
文摘Daily maximum/minimum temperatures and relative humidity records from 510 stations in China for the period 1960–2008 were used to investigate geographical patterns and temporal variations of heatwave （HW） events. Dry and wet HW events were compared by different definitions. Regionally, both dry and wet HW events are commonly located in southeastern China in the monsoon area, with neither type occurring in the northeast part of Northeast China and Southwest China, while the north-northwest region of the country experiences dry HW events and a few wet HW events. In the southeast of the country, site dry HW events occurred from April to September and mostly in June, while site wet HW events occurred from April to October and mostly in September. In total, 163 regional wet HW events were identified. The ten longest regional wet HW events lasted for more than 20 days, while the mean duration for 163 events was about 11 days. For the top ten events, six occurred after the 1990s, compared with four before this time. Global surface warming was clear since 1979, but the frequency and severity of regional wet HW events were relatively low in the 1980s, increasing remarkably since the 1990s. Possible reasons for this might be the strong interdecadal and interannual variations in regional atmospheric circulations, as well as water transport related directly to temperature contrasts in different regions, rather than global-mean temperature changes.
