This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West...This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection scheme.Results show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel.In general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances.Moreover,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical conditions.The typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper trough.The impact of assimilating AGRI radiances on typhoon intensity forecasts is small.On the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.展开更多
Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets s...Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets show consistency in statistically significant trends, with a warming trend of 0.07—0.08 ℃ per decade from 1890 to2013. However, in shorter epochs(such as 1961—2013 and 1981—2013), HadISST1 exhibits stronger warming rates than those of COBE SST2. Both datasets experienced a sudden decrease in the global hiatus period(1998—2013), but the cooling rate of HadISST1 is lower than that of COBE SST2. These differences are possibly caused by the different observations sources which are incorporated to fill with data-sparse regions since 1982. Different data sources may lead to higher values in HadISST1 from 1981 to 2013 than that in COBE SST2. Meanwhile, the different data sources and bias adjustment before the World War II may also cause the large divergence between COBE SST2 and HadISST1,leading to lower SST from 1891 to 1930. These findings illustrate that the long-term linear trends are broadly similar in the centennial-scale in the China Seas using different datasets. However, there are large uncertainties in the estimate of warming or cooling tendency in the shorter epochs, because there are different data sources, different bias adjustment and interpolation method in different datasets.展开更多
Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation det...Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.展开更多
Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technolo...Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technology(NUISTCFS1.0).This assessment is based on the seven-month(May to November)hindcasts consisting of nine ensemble members during 1982–2019.The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere.The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations,although the seasonal mean TC frequency and accumulated cyclone energy(ACE)are underestimated in all basins due to the low resolution(T106)of the atmospheric component in the model.NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic(NA)and eastern North Pacific(ENP),which have a good relationship with indexes based on the sea surface temperature.In the western North Pacific(WNP),NUIST-CFS1.0 can closely capture ACE,which is significantly correlated with the El Ni?o–Southern Oscillation(ENSO),while it has difficulty forecasting the interannual variation of TC frequency in this area.When the WNP is further divided into eastern and western subregions,the model displays improved TC activity forecasting ability.Additionally,it is found that biases in predicted TC genesis locations lead to inaccurately represented TC–environment relationships,which may affect the capability of the model in reproducing the interannual variations of TC activity.展开更多
The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameteri...The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.展开更多
Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spat...Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.展开更多
The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation(QBO)during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset(CRA-40)is evaluated by comparing two widely u...The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation(QBO)during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset(CRA-40)is evaluated by comparing two widely used reanalysis datasets,ERA-5 and MERRA-2.CRA-40 demonstrates a comparable performance with ERA-5 and MERRA-2 in characterizing the winter and spring circulation in the lower and middle Arctic stratosphere.Specifically,differences in the climatological polar-mean temperature and polar night jet among the three reanalyses are within±0.5 K and±0.5 m s^(–1),respectively.The onset dates of the stratospheric sudden warming and stratospheric final warming events at 10 hPa in CRA-40,together with the dynamics and circulation anomalies during the onset process of warming events,are nearly identical to the other two reanalyses with slight differences.By contrast,the CRA-40 dataset demonstrates a deteriorated performance in describing the QBO below 10 hPa compared to the other two reanalysis products,manifested by the larger easterly biases of the QBO index,the remarkably weaker amplitude of the QBO,and the weaker wavelet power of the QBO period.Such pronounced biases are mainly concentrated in the period 1981–98 and largely reduced by at least 39%in 1999–2019.Thus,particular caution is needed in studying the QBO based on CRA-40.All three reanalyses exhibit greater disagreement in the upper stratosphere compared to the lower and middle stratosphere for both the polar region and the tropics.展开更多
To explain the recent three-year La Niña event from 2020 to 2022,which has caused catastrophic weather events worldwide,Fasullo et al.(2023)demonstrated that the increase in biomass aerosol resulting from the 201...To explain the recent three-year La Niña event from 2020 to 2022,which has caused catastrophic weather events worldwide,Fasullo et al.(2023)demonstrated that the increase in biomass aerosol resulting from the 2019-20 Australian wildfire season could have triggered this multi-year La Niña.Here,we present compelling evidence from paleo-proxies,utilizing a substantial sample size of 26 volcanic eruptions in the Southern Hemisphere(SH),to support the hypothesis that ocean cooling in the SH can lead to a multi-year La Niña event.This research highlights the importance of focusing on the Southern Ocean,as current climate models struggle to accurately simulate the Pacific response driven by the Southern Ocean.展开更多
The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown th...The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.展开更多
The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to...The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to investigate the interactions among atmospheric CO_(2),the physical climate system,and the carbon cycle of the underlying surface for a better understanding of the Earth system.Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations.The Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0)has successfully fixed a two-way coupling of atmospheric CO_(2)with the climate and carbon cycle on land and in the ocean.Using CAS-ESM2.0,we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment.This paper examines the modeled CO_(2)by comparison with observed CO_(2)at the sites of Mauna Loa and Barrow,and the Greenhouse Gases Observing Satellite(GOSAT)CO_(2)product.The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO_(2)during the period 1850-2014,and in capturing the seasonal cycle of CO_(2)at the two baseline sites,as well as over northern high latitudes.These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions,even though uncertainties remain in the processes involved.This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate,which will provide significant scientific support for climate research and China’s goal of carbon neutrality.展开更多
Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variat...Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variations over the middle reaches of the Yangtze River basin.For all three types of terrain(i.e.,mountain,foothill,and plain),the amount of TR and SDHR both maximize in June/July,and the contribution of SDHR to TR(CST)peaks in August(amount:23%;frequency:1.74%).Foothill rainfall is characterized by a high TR amount and a high CST(in amount);mountain rainfall is characterized by a high TR frequency but a small CST(in amount);and plain rainfall shows a low TR amount and frequency,but a high CST(in amount).Overall,stations with high TR(amount and frequency)are mainly located over the mountains and in the foothills,while those with high SDHR(amount and frequency)are mainly concentrated in the foothills and plains close to mountainous areas.For all three types of terrain,the diurnal variations of both TR and SDHR exhibit a double peak(weak early morning and strong late afternoon)and a phase shift from the early-morning peak to the late-afternoon peak from May to August.Around the late-afternoon peak,the amount of TR and SDHR in the foothills is larger than over the mountains and plains.The TR intensity in the foothills increases significantly from midnight to afternoon,suggesting that thermal instability may play an important role in this process.展开更多
The present study explored how the Indian Ocean Dipole (IOD) influences October-November-December (OND) rainfall over Tanzania in recent decade following the 2011 abrupt change. The study spans 50 years, from 1973 to ...The present study explored how the Indian Ocean Dipole (IOD) influences October-November-December (OND) rainfall over Tanzania in recent decade following the 2011 abrupt change. The study spans 50 years, from 1973 to 2022. Notable abrupt changes were observed in 1976 and 2011, leading us to divide our study into two periods: 1976-2010 and 2011-2022, allowing for a close investigation into the existing relationship between OND IOD and OND rainfall and their associated large-scale atmospheric circulations. It was found that the relationship between OND IOD and OND rainfall strengthened, with the correlation changed from +0.73 during 1976-2010 to +0.81 during 2011-2022. Further investigation revealed that, during 1976-2010, areas that received above- normal rainfall during positive IOD experienced below-normal during 2011- 2022 and vice versa. The same pattern relationship was observed for negative IOD. Spatial analysis demonstrates that the percentage departure of rainfall across the region mirrors the standardized rainfall anomalies. The study highlights that the changing relationship between OND IOD and OND rainfall corresponds to the east-west shift of Walker circulation, as well as the north-south shift of Hadley circulation. Analysis of sea surface temperature (SST) indicates that both positive and negative IOD events strengthened during 2011-2022 compared to 1976-2010. Close monitoring of this relationship across different timescales could be useful for updating OND rainfall seasonal forecasts in Tanzania, serving as a tool for reducing socio-economic impacts.展开更多
Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distri...Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distribution. This work investigated the changes in the frequency and pattern of extreme rainfall over Uganda, using daily datasets sourced from Climate Hazard Group InfraRed Precipitation with Station (CHIRPS-v2) for the period 1981 to 2022. The study utilized the extreme weather Indices provided by the Expert Team on Climate Change Detection and Indices (ETCCDI). Attention was directed towards September to November (SON) rainfall season with precise analysis of four indices (Rx1day, Rx5day, R95p, and R99p). The Sequential Mann-Kendall (SQMK) non-parametric test was applied to identify abrupt changes in SON extreme rainfall trends. Results showed that October consistently recorded the highest count of extreme rainfall days across all four indices. The long-term analysis revealed fluctuations in extreme rainfall events across years, with certain periods exhibiting heightened intensity. The analysis portrayed a shift in the decadal variations and region-specific distribution of extreme rainfall, with Eastern Uganda and areas around Lake Victoria standing out compared to other regions. The findings further revealed an increase in extreme rainfall for all indices in the recent decade (2011-2022) with 2019/2020 standing out as the extreme years of SON for the study period. While trendlines suggested a slight increase in intense daily rainfall events, the SQMK tests revealed statistical significance in the trend of prolonged periods of intense daily rainfall. This study contributes to the understanding of the spatiotemporal variability and trends of extreme rainfall events over Uganda during the SON season, which is crucial for the assessment of climate change impacts and adaptation strategies. It provides valuable information for seasonal extreme rainfall forecasting, development of early warning systems, flood risk management, and disaster preparedness plans.展开更多
基金primarily supported by the Chinese National Natural Science Foundation of China(Grant No. G42192553)Open Fund of Fujian Key Laboratory ofSevere Weather and Key Laboratory of Straits Severe Weather(Grant No. 2023KFKT03)+6 种基金the Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory(Grant No. 2023BHR-Y20)the Open Fund of the State Key Laboratory of Remote Sensing Science (Grant No. OFSLRSS202321)the Program of Shanghai Academic/Technology Research Leader(Grant No. 21XD1404500)the Shanghai Typhoon Research Foundation (Grant No. TFJJ202107)the Chinese National Natural Science Foundation of China (Grant No. G41805016)the National Meteorological Center Foundation (Grant No. FY-APP-2021.0207)the High Performance Computing Center of Nanjing University of Information Science&Technology for their support of this work
文摘This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection scheme.Results show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel.In general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances.Moreover,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical conditions.The typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper trough.The impact of assimilating AGRI radiances on typhoon intensity forecasts is small.On the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.
基金jointly supported by the National Key Research and Development Program of China[grant number 2019YFC1510004]the National Natural Science Foundation of China(NSFC)[grant number 41975108]the NSFC-Shandong Joint Fund for Marine Science Re-search Centers[grant number U1606405].
基金National Key Basic Research Program of China(2016YFA0602200,2012CB955203,2013CB430202)
文摘Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets show consistency in statistically significant trends, with a warming trend of 0.07—0.08 ℃ per decade from 1890 to2013. However, in shorter epochs(such as 1961—2013 and 1981—2013), HadISST1 exhibits stronger warming rates than those of COBE SST2. Both datasets experienced a sudden decrease in the global hiatus period(1998—2013), but the cooling rate of HadISST1 is lower than that of COBE SST2. These differences are possibly caused by the different observations sources which are incorporated to fill with data-sparse regions since 1982. Different data sources may lead to higher values in HadISST1 from 1981 to 2013 than that in COBE SST2. Meanwhile, the different data sources and bias adjustment before the World War II may also cause the large divergence between COBE SST2 and HadISST1,leading to lower SST from 1891 to 1930. These findings illustrate that the long-term linear trends are broadly similar in the centennial-scale in the China Seas using different datasets. However, there are large uncertainties in the estimate of warming or cooling tendency in the shorter epochs, because there are different data sources, different bias adjustment and interpolation method in different datasets.
基金jointly sponsored by the National Key Research and Development Program of China(Grant Nos.2018YFC1506701 and 2017YFC1502102)the National Natural Science Foundation of China(Grant No.41675102)。
文摘Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.
基金This work was supported by the National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disaster[Grant No.2019YFC1510004]the National Natural Science Foundation of China[Grant Nos.41975108 and 42105022]+2 种基金NOAA[Grant No.NA18OAR4310298]the Natural Science Foundation of Jiangsu[Grant No.BK20190781]the National Natural Science Foundation of China–Shandong Joint Fund for Marine Science Research Centers[Grant No.U1606405].
基金supported by the National Key Research and Development Program of China[grant number 2020YFA0608000]the National Natural Science Foundation of China[grant number 42030605].
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFA0608000)the Nature Science Foundation of China(Grant Nos.42005002,42030605,and 42105003)。
文摘Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technology(NUISTCFS1.0).This assessment is based on the seven-month(May to November)hindcasts consisting of nine ensemble members during 1982–2019.The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere.The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations,although the seasonal mean TC frequency and accumulated cyclone energy(ACE)are underestimated in all basins due to the low resolution(T106)of the atmospheric component in the model.NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic(NA)and eastern North Pacific(ENP),which have a good relationship with indexes based on the sea surface temperature.In the western North Pacific(WNP),NUIST-CFS1.0 can closely capture ACE,which is significantly correlated with the El Ni?o–Southern Oscillation(ENSO),while it has difficulty forecasting the interannual variation of TC frequency in this area.When the WNP is further divided into eastern and western subregions,the model displays improved TC activity forecasting ability.Additionally,it is found that biases in predicted TC genesis locations lead to inaccurately represented TC–environment relationships,which may affect the capability of the model in reproducing the interannual variations of TC activity.
基金supported by the National Natural Science Foundation of China(Grant Nos.42175099,42027804,42075073)the Innovative Project of Postgraduates in Jiangsu Province in 2023(Grant No.KYCX23_1319)+3 种基金supported by the National Natural Science Foundation of China(Grant No.42205080)the Natural Science Foundation of Sichuan(Grant No.2023YFS0442)the Research Fund of Civil Aviation Flight University of China(Grant No.J2022-037)supported by the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(Earth Lab)。
文摘The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.
基金supported by the National Key R&D Program of China (Grant No.2019YFA0607202)the National Natural Science Foundation of China (Grant Nos. 42021004 and 42005143)+2 种基金support by the Postgraduate Research&Practice Innovation Program of Jiangsu Province (Grant No. KYCX21_0978)support by the Open Research Fund Program of the Key Laboratory of Urban Meteorology,China Meteorological Administration (Grant No. LUM-2023-12)the 333 Project of Jiangsu Province (Grant No. BRA2022023)
文摘Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41975048, 42030605, and 42175069)the Natural Science Foundation of Jiangsu Province (Grant No.BK20191404)
文摘The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation(QBO)during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset(CRA-40)is evaluated by comparing two widely used reanalysis datasets,ERA-5 and MERRA-2.CRA-40 demonstrates a comparable performance with ERA-5 and MERRA-2 in characterizing the winter and spring circulation in the lower and middle Arctic stratosphere.Specifically,differences in the climatological polar-mean temperature and polar night jet among the three reanalyses are within±0.5 K and±0.5 m s^(–1),respectively.The onset dates of the stratospheric sudden warming and stratospheric final warming events at 10 hPa in CRA-40,together with the dynamics and circulation anomalies during the onset process of warming events,are nearly identical to the other two reanalyses with slight differences.By contrast,the CRA-40 dataset demonstrates a deteriorated performance in describing the QBO below 10 hPa compared to the other two reanalysis products,manifested by the larger easterly biases of the QBO index,the remarkably weaker amplitude of the QBO,and the weaker wavelet power of the QBO period.Such pronounced biases are mainly concentrated in the period 1981–98 and largely reduced by at least 39%in 1999–2019.Thus,particular caution is needed in studying the QBO based on CRA-40.All three reanalyses exhibit greater disagreement in the upper stratosphere compared to the lower and middle stratosphere for both the polar region and the tropics.
基金the National Key Research and Development Program of China(Grant No.2020YFA0608803)the National Natural Science Foundation of China(Grant Nos.41975107,41875092 and 42005020).
文摘To explain the recent three-year La Niña event from 2020 to 2022,which has caused catastrophic weather events worldwide,Fasullo et al.(2023)demonstrated that the increase in biomass aerosol resulting from the 2019-20 Australian wildfire season could have triggered this multi-year La Niña.Here,we present compelling evidence from paleo-proxies,utilizing a substantial sample size of 26 volcanic eruptions in the Southern Hemisphere(SH),to support the hypothesis that ocean cooling in the SH can lead to a multi-year La Niña event.This research highlights the importance of focusing on the Southern Ocean,as current climate models struggle to accurately simulate the Pacific response driven by the Southern Ocean.
基金supported by the National Key Technologies R&D Program of China[grant number 2022YFC3002803]the National Science Fund for Distinguished Young Scholars[grant number 41925021].
基金supported by the National Key R&D Program of China(Grant No.2019YFA0606703)the National Natural Science Foundation of China(Grant No.41975116)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.Y202025)。
文摘The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.
基金supported by the National Natural Science Foundation of China[grant number 42088101] and the National Natural Science Foundation of China[grant number 42005020].
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106500]the Youth Innovation Promotion Association of the Chinese Academy of Sciences[grant number 2022076]the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab)[grant number 2023-EL-ZD-00012].
基金the National Key Research and Development Program of China(Grant No.2022YFE0106500)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.2022076)+1 种基金the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab2023-EL-ZD-00012)。
文摘The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to investigate the interactions among atmospheric CO_(2),the physical climate system,and the carbon cycle of the underlying surface for a better understanding of the Earth system.Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations.The Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0)has successfully fixed a two-way coupling of atmospheric CO_(2)with the climate and carbon cycle on land and in the ocean.Using CAS-ESM2.0,we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment.This paper examines the modeled CO_(2)by comparison with observed CO_(2)at the sites of Mauna Loa and Barrow,and the Greenhouse Gases Observing Satellite(GOSAT)CO_(2)product.The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO_(2)during the period 1850-2014,and in capturing the seasonal cycle of CO_(2)at the two baseline sites,as well as over northern high latitudes.These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions,even though uncertainties remain in the processes involved.This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate,which will provide significant scientific support for climate research and China’s goal of carbon neutrality.
基金supported by the National Natural Science Foundation of China(Grant Nos. U2142202, 41975056, 42230612, and 41975058)Youth Innovation Promotion Association,Chinese Academy of Sciencesthe National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility”(EarthLab)
文摘Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variations over the middle reaches of the Yangtze River basin.For all three types of terrain(i.e.,mountain,foothill,and plain),the amount of TR and SDHR both maximize in June/July,and the contribution of SDHR to TR(CST)peaks in August(amount:23%;frequency:1.74%).Foothill rainfall is characterized by a high TR amount and a high CST(in amount);mountain rainfall is characterized by a high TR frequency but a small CST(in amount);and plain rainfall shows a low TR amount and frequency,but a high CST(in amount).Overall,stations with high TR(amount and frequency)are mainly located over the mountains and in the foothills,while those with high SDHR(amount and frequency)are mainly concentrated in the foothills and plains close to mountainous areas.For all three types of terrain,the diurnal variations of both TR and SDHR exhibit a double peak(weak early morning and strong late afternoon)and a phase shift from the early-morning peak to the late-afternoon peak from May to August.Around the late-afternoon peak,the amount of TR and SDHR in the foothills is larger than over the mountains and plains.The TR intensity in the foothills increases significantly from midnight to afternoon,suggesting that thermal instability may play an important role in this process.
文摘The present study explored how the Indian Ocean Dipole (IOD) influences October-November-December (OND) rainfall over Tanzania in recent decade following the 2011 abrupt change. The study spans 50 years, from 1973 to 2022. Notable abrupt changes were observed in 1976 and 2011, leading us to divide our study into two periods: 1976-2010 and 2011-2022, allowing for a close investigation into the existing relationship between OND IOD and OND rainfall and their associated large-scale atmospheric circulations. It was found that the relationship between OND IOD and OND rainfall strengthened, with the correlation changed from +0.73 during 1976-2010 to +0.81 during 2011-2022. Further investigation revealed that, during 1976-2010, areas that received above- normal rainfall during positive IOD experienced below-normal during 2011- 2022 and vice versa. The same pattern relationship was observed for negative IOD. Spatial analysis demonstrates that the percentage departure of rainfall across the region mirrors the standardized rainfall anomalies. The study highlights that the changing relationship between OND IOD and OND rainfall corresponds to the east-west shift of Walker circulation, as well as the north-south shift of Hadley circulation. Analysis of sea surface temperature (SST) indicates that both positive and negative IOD events strengthened during 2011-2022 compared to 1976-2010. Close monitoring of this relationship across different timescales could be useful for updating OND rainfall seasonal forecasts in Tanzania, serving as a tool for reducing socio-economic impacts.
文摘Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distribution. This work investigated the changes in the frequency and pattern of extreme rainfall over Uganda, using daily datasets sourced from Climate Hazard Group InfraRed Precipitation with Station (CHIRPS-v2) for the period 1981 to 2022. The study utilized the extreme weather Indices provided by the Expert Team on Climate Change Detection and Indices (ETCCDI). Attention was directed towards September to November (SON) rainfall season with precise analysis of four indices (Rx1day, Rx5day, R95p, and R99p). The Sequential Mann-Kendall (SQMK) non-parametric test was applied to identify abrupt changes in SON extreme rainfall trends. Results showed that October consistently recorded the highest count of extreme rainfall days across all four indices. The long-term analysis revealed fluctuations in extreme rainfall events across years, with certain periods exhibiting heightened intensity. The analysis portrayed a shift in the decadal variations and region-specific distribution of extreme rainfall, with Eastern Uganda and areas around Lake Victoria standing out compared to other regions. The findings further revealed an increase in extreme rainfall for all indices in the recent decade (2011-2022) with 2019/2020 standing out as the extreme years of SON for the study period. While trendlines suggested a slight increase in intense daily rainfall events, the SQMK tests revealed statistical significance in the trend of prolonged periods of intense daily rainfall. This study contributes to the understanding of the spatiotemporal variability and trends of extreme rainfall events over Uganda during the SON season, which is crucial for the assessment of climate change impacts and adaptation strategies. It provides valuable information for seasonal extreme rainfall forecasting, development of early warning systems, flood risk management, and disaster preparedness plans.
