Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostation...Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models.展开更多
A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcast...A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.展开更多
The study investigated the effects of global direct radiative forcing due to carbonaceous aerosol on the climate in East Asia, using the CAM3 developed by NCAR. The results showed that carbonaceous aerosols cause nega...The study investigated the effects of global direct radiative forcing due to carbonaceous aerosol on the climate in East Asia, using the CAM3 developed by NCAR. The results showed that carbonaceous aerosols cause negative forcing at the top of the atmosphere （TOA） and surface under clear sky conditions, but positive forcing at the TOA and weak negative forcing at the surface under all sky conditions. Hence, clouds could change the sign of the direct radiative forcing at the TOA, and weaken the forcing at the surface. Carbonaceous aerosols have distinct effects on the summer climate in East Asia. In southern China and India, it caused the surface temperature to increase, but the total cloud cover and precipitation to decrease. However, the opposite effects are caused for most of northern China and Bangladesh. Given the changes in temperature, vertical velocity, and surface streamflow caused by carbonaceous aerosol in this simulation, carbonaceous aerosol could also induce summer precipitation to decrease in southern China but increase in northern China.展开更多
A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM...A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.展开更多
This study simulates the effective radiative forcing （ERF） of tropospheric ozone from 1850 to 2013 and its effects on global climate using an aerosol-climate coupled model, BCC_AGCM2.0. I_CUACE/Aero, in combination ...This study simulates the effective radiative forcing （ERF） of tropospheric ozone from 1850 to 2013 and its effects on global climate using an aerosol-climate coupled model, BCC_AGCM2.0. I_CUACE/Aero, in combination with OMI （Ozone Monitoring Instrument） satellite ozone data. According to the OMI observations, the global annual mean tropospheric col- umn ozone （TCO） was 33.9 DU in 2013, and the largest TCO was distributed in the belts between 30°N and 45°N and at approximately 30°S; the annual mean TCO was higher in the Northern Hemisphere than that in the Southern Hemisphere; and in boreal summer and autumn, the global mean TCO was higher than in winter and spring. The simulated ERF due to the change in tropospheric ozone concentration from 1850 to 2013 was 0.46 W m-2, thereby causing an increase in the global annual mean surface temperature by 0.36°C, and precipitation by 0.02 mm d-1 （the increase of surface temperature had a significance level above 95%）. The surface temperature was increased more obviously over the high latitudes in both hemispheres, with the maximum exceeding 1.4°C in Siberia. There were opposite changes in precipitation near the equator, with an increase of 0.5 mm d- 1 near the Hawaiian Islands and a decrease of about -0.6 mm d- 1 near the middle of the Indian Ocean.展开更多
“I call on all leaders worldwide to declare a State of Climate Emergency in their own countries until carbon neutrality is reached.”–António GUTERRES(United Nations Secretary General),12 December,2020 There is...“I call on all leaders worldwide to declare a State of Climate Emergency in their own countries until carbon neutrality is reached.”–António GUTERRES(United Nations Secretary General),12 December,2020 There is no shortcut to a carbon neutral society;solutions are urgently required from both energy&industrial sectors and global ecosystems.While the former is often held accountable and emphasized in terms of its emissions reduction capability,the latter(recently termed natural climate solutions)should also be assessed for potential and limitations by the scientific community,the public,and policy makers.展开更多
This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studi...This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.展开更多
Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SI...Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SINTEX-F coupled model is used to build a statistical model to predict the cyclogenesis frequency over the South China Sea and the western North Pacific. The SINTEX-F coupled model has relatively good prediction skill for some circulation features associated with the cyclogenesis frequency including sea level pressure, wind vertical shear, Intertropical Convergence Zone and cross-equatorial air flows. Predictors derived from these large-scale circulations have good relationships with the cyclogenesis frequency over the South China Sea and the western North Pacific. A multivariate linear regression(MLR) model is further designed using these predictors. This model shows good prediction skill with the anomaly correlation coefficient reaching, based on the cross validation, 0.71 between the observed and predicted cyclogenesis frequency. However, it also shows relatively large prediction errors in extreme tropical cyclone years(1994 and 1998, for example).展开更多
This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seaso...This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 C during winter than of 4.9 C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.展开更多
An atmospheric general circulation model BCC_AGCM2.0 and observation data from ARIS were used to calculate the effective radiative forcing（ERF） due to increased methane concentration since pre-industrial times and i...An atmospheric general circulation model BCC_AGCM2.0 and observation data from ARIS were used to calculate the effective radiative forcing（ERF） due to increased methane concentration since pre-industrial times and its impacts on climate. The ERF of methane from 1750 to2011 was 0.46 W m^-2 by taking it as a well-mixed greenhouse gas, and the inhomogeneity of methane increased its ERF by about 0.02 W m^-2.The change of methane concentration since pre-industrial led to an increase of 0.31 ℃ in global mean surface air temperature and 0.02 mm d 1in global mean precipitation. The warming was prominent over the middle and high latitudes of the Northern Hemisphere（with a maximum increase exceeding 1.4℃）. The precipitation notably increased（maximum increase of 1.8 mm d^-1） over the ocean between 10°N and 20° N and significantly decreased（maximum decrease 〉-0.6 mm d^-1） between 10° S and 10° N. These changes caused a northward movement of precipitation cell in the Intertropical Convergence Zone（ITCZ）. Cloud cover significantly increased（by approximately 4%） in the high latitudes in both hemispheres, and sharply decreased（by approximately 3%） in tropical areas.展开更多
Recent advances in the bridging roles played by the Tibetan Plateau(TP)are reviewed in terms of the remote influence of circulation anomalies over the North Atlantic Ocean on Asian monsoon and El Niño-Southern Os...Recent advances in the bridging roles played by the Tibetan Plateau(TP)are reviewed in terms of the remote influence of circulation anomalies over the North Atlantic Ocean on Asian monsoon and El Niño-Southern Oscillation(ENSO)events,and in a clear link between the tropical oceans and Asian climate anomalies.The authors firstly introduce how the winter and spring anomalies in the North Atlantic Ocean affect the seasonal transition over the South Asian monsoon region and subsequent ENSO events on the interannual timescale.A distinct negative sensible heating-baroclinic structure in May over the TP is found to provide an intermediate bridging effect in this Atlantic-Asian-Pacific connection.In summer,the North Atlantic Oscillation is significantly correlated with the variations of East China summer rainfall,and it is the TP’s latent heating that plays the bridging role within.On the other hand,such a TP bridging effect also exists in the connection from the tropical oceans to extreme precipitation events over eastern China in summer,and from the midlatitude wave train to the biweekly oscillation of South China rainfall in spring.展开更多
This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset(SCSSMO)and investigates the associated oceanic and atmospheric processes,utilizing the hindcasts of the National Centers for E...This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset(SCSSMO)and investigates the associated oceanic and atmospheric processes,utilizing the hindcasts of the National Centers for Environmental Prediction(NCEP)Climate Forecast System version 2(CFSv2).Typically,the SCSSMO is accompanied by an eastward retreat of the western North Pacific subtropical high(WNPSH),development of the cross-equatorial flow,and an increase in the east-west sea surface temperature(SST)gradient.These features are favorable for the onset of westerlies and strengthening of convection and precipitation over the South China Sea(SCS).A more vigorous SCSSMO process shows a higher predictability,and vice versa.The NCEP CFSv2 can successfully predict the onset date and evolution of the monsoon about 4 pentads(20 days)in advance(within 1–2 pentads)for more forceful(less vigorous)SCSSMO processes.On the other hand,the climatological SCSSMO that occurs around the 27th pentad can be accurately predicted in one pentad,and the predicted SCSSMO occurs 1–2 pentads earlier than the observed with a weaker intensity at longer leadtimes.Warm SST biases appear over the western equatorial Pacific preceding the SCSSMO.These biases induce a weaker-thanobserved WNPSH as a Gill-type response,leading to weakened low-level easterlies over the SCS and hence an earlier and less vigorous SCSSMO.In addition,after the SCSSMO,remarkable warm biases over the eastern Indian Ocean and the SCS and cold biases over the WNP induce weaker-than-observed westerlies over the SCS,thus also contributing to the less vigorous SCSSMO.展开更多
In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift an...In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift and intensification of the western Pacific subtropical high(WPSH). Under these conditions, China experienced its hottest summer since 1961,and was hit by a series of high-impact extreme weather and climate events. From 9 June to 2 July, southern China experienced an unprecedented extreme precipitation event that exceeded the well-known 1998 summer precipitation event in both duration and impact scope, resulting in devastating floods in the Yangtze River basin. Subsequently, in early to midJuly, the Huanghe-Huaihe Basin suffered from a severe drought–flood abrupt alternation event, heavily affecting Henan and Shandong. Meanwhile, southern China underwent a widespread heatwave event lasting 74 days, ranking as the second most intense since 1961. From late July to the end of August, northern China faced unusually frequent heavy precipitation events, with cumulative precipitation reaching the second highest for the same period since 1961, causing floods in many rivers of northern China. This study provides a timely summary and assessment of the characteristics and impacts of these extreme events. It serves as a reference for climate change research, including mechanism analysis, numerical simulation,and climate event attribution, and also offers valuable insights for improving meteorological disaster prevention and mitigation strategies.展开更多
The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of ...The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.展开更多
Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasona...Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasonal precipitation anomalies during summer in China and reveals the contributions of possible driving factors.The results suggest that while single-model ensembles(SMEs)exhibit constrained predictive skills within a limited forecast lead time of three pentads,the MME illustrates an enhanced predictive skill at a lead time of up to four pentads,and even six pentads,in southern China.Based on both deterministic and probabilistic verification metrics,the MME consistently outperforms SMEs,with a more evident advantage observed in probabilistic forecasting.The superior performance of the MME is primarily attributable to the increase in ensemble size,and the enhanced model diversity is also a contributing factor.The reliability of probabilistic skill is largely improved due to the increase in ensemble members,while the resolution term does not exhibit consistent improvement.Furthermore,the Madden–Julian Oscillation(MJO)is revealed as the primary driving factor for the successful prediction of summer precipitation in China using the MME.The improvement by the MME is not solely attributable to the enhancement in the inherent predictive capacity of the MJO itself,but derives from its capability in capturing the more realistic relationship between the MJO and subseasonal precipitation anomalies in China.This study establishes a scientific foundation for acknowledging the advantageous predictive capability of the MME approach in subseasonal predictions of summer precipitation in China,and sheds light on further improving S2S predictions.展开更多
In the context of global warming, the increasing wildfire frequency has become a critical climate research focus in North America. This study used the Community Earth System Model(CESM 1.2) to investigate the impacts ...In the context of global warming, the increasing wildfire frequency has become a critical climate research focus in North America. This study used the Community Earth System Model(CESM 1.2) to investigate the impacts of 20thcentury wildfires on North American climate and hydrology. Summer represents the peak wildfire season in North America, with the Gulf of Mexico and Midwest regions experiencing the most severe effects. Wildfires not only damage vegetation during the fire season but also extend prolonged impacts into non-fire periods, showing distinct seasonal variations. In spring, wildfires increase surface albedo, triggering a cooling effect through enhanced snow cover and delayed snowmelt. Conversely, summer and autumn surface warming stems primarily from wildfire-suppressed vegetation transpiration. Warming near the Gulf of Mexico enhances moisture transport and precipitation, particularly in summer and autumn. Reduced evaporation and increased precipitation from the Gulf of Mexico significantly altered the hydrological cycle across North America, leading to increased runoff continent-wide.展开更多
Forecasting tropical cyclone(TC)activities has been a topic of great interest and research.Taiwan Island(TW)is one of the key regions that is highly exposed to TCs originated from the western North Pacific.Here,the au...Forecasting tropical cyclone(TC)activities has been a topic of great interest and research.Taiwan Island(TW)is one of the key regions that is highly exposed to TCs originated from the western North Pacific.Here,the authors utilize two mainstream reanalysis datasets for the period 1979-2013 and propose an effective statistical seasonal forecasting model-namely,the Sun Yat-sen University(SYSU)Model-for predicting the number of TC landfalls on TW based on the environmental factors in the preseason.The comprehensive predictor sampling and multiple linear regression show that the 850-hPa meridional wind over the west of the Antarctic Peninsula in January,the 300-hPa specific humidity over the open ocean southwest of Australia in January,the 300-hPa relative vorticity over the west of the Sea of Okhotsk in March,and the sea surface temperature in the South Indian Ocean in April,are the most significant predictors.The correlation coefficient between the modeled results and observations reaches 0.87.The model is validated by the leave-one-out and nine-fold cross-validation methods,and recent 9-yr observations(2014-2022).The Antarctic Oscillation,variabilities of the western Pacific subtropical high,Asian summer monsoon,and oceanic tunnel are the possible physical linkages or mechanisms behind the model result.The SYSU Model exhibits a 98%hit rate in 1979-2022(43 out of 44),suggesting an operational potential in the seasonal forecasting of TC landfalls on TW.展开更多
Active atmospheric convection on the monsoon coast is crucial for the Earth’s climate system.In particular,the upscale convective growth(UCG)from ordinary isolated convection to organized convective system is a key p...Active atmospheric convection on the monsoon coast is crucial for the Earth’s climate system.In particular,the upscale convective growth(UCG)from ordinary isolated convection to organized convective system is a key process causing severe weather,but its activities on the monsoon coast are less understood because of the lack of fine-resolution datasets.For the first time,we present the climatology of UCG on a typical monsoon coast using kilometer-mesh radar data from southern China.The UCG undergoes pronounced subseasonal and diurnal variations in the early-summer rainy season.The subseasonal UCG increase is attributed to the onshore flows shifting from easterlies in April to monsoon southwesterlies in June.UCG becomes vigorous following summer monsoon onset,with hotspots near windward coastal mountains.Daytime UCG first peaks near noontime along coastal land,where onshore flows are destabilized by boundary-layer heating and mountains.Afternoon inland peaks and off-coast minimums are recognized due to land–sea thermal contrast and sea-breeze circulation.Nighttime UCG is revived at the coast by nocturnally enhanced southerlies,followed by offshore activity as the convergence of land-breeze northerlies shifts seaward.The UCG thus responds strongly to changing atmospheric conditions,land heating/cooling,and thermally driven local circulations.Our results may help clarify the predictability of monsoon coastal convection.展开更多
The inherent black-box nature of machine learning(ML) models limits their interpretability and broader application in heavy precipitation forecasting. Evaluating the reliability of these models involves analyzing the ...The inherent black-box nature of machine learning(ML) models limits their interpretability and broader application in heavy precipitation forecasting. Evaluating the reliability of these models involves analyzing the link between predictions and predictors. In this study, ERA5 reanalysis data, CERES satellite observations, and ground-based meteorological observatories were utilized to compile more comprehensive multi-type predictors for developing a Bayesian optimized XGBoost model for the nowcasting of heavy precipitation in the Guangdong-Hong Kong-Macao Greater Bay Area during the pre-summer rainy season. A comparison of model performance with different combinations of input features and classical machine learning algorithms demonstrated that the Bayesian optimized XGBoost model achieved the best overall performance, with an average Critical Success Index of 68.30%. Permutation Importance(PI) and shapley Additive Explanations(SHAP) methods were utilized to interpret feature effects in heavy precipitation forecasting. The results indicated that precipitable water vapor(PWV), cloud, relative humidity, and seasonal and diurnal variables had more significant effects on the model output as individual features. Furthermore, the collective influence of derivatives from PWV and meteorological parameters(e.g., temperature, relative humidity, pressure and dew point temperature)showed a significant enhancement over their individual impacts, indicating synergistic interactions among these predictors.Applying explainable artificial intelligence(XAI) to ML models helps understand how models utilize features for forecasting, enhances the reliability of forecasts, and guides feature selection and the mitigation of overfitting phenomena.展开更多
基金supported by the National Natural Science Foundation of China (NSFC) (Grant No.42205044)Feng Yun Application Pioneering Project (FY-APP) Innovation Center for Feng Yun Meteorological Satellite (FYSIC) Special Project (FY-APP-XC-2023.04)the Wuxi University Research Start-up Fund for Recruited Talent。
文摘Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models.
文摘A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.
基金supported by Na-tional Basic Research Program of China (Grant No.2006CB403707)the public Meteorology Special Foundation of MOST (Grant No. GYHY200706036)the National Key Technology R & D Program (Grant No.2007BAC03A0)
文摘The study investigated the effects of global direct radiative forcing due to carbonaceous aerosol on the climate in East Asia, using the CAM3 developed by NCAR. The results showed that carbonaceous aerosols cause negative forcing at the top of the atmosphere （TOA） and surface under clear sky conditions, but positive forcing at the TOA and weak negative forcing at the surface under all sky conditions. Hence, clouds could change the sign of the direct radiative forcing at the TOA, and weaken the forcing at the surface. Carbonaceous aerosols have distinct effects on the summer climate in East Asia. In southern China and India, it caused the surface temperature to increase, but the total cloud cover and precipitation to decrease. However, the opposite effects are caused for most of northern China and Bangladesh. Given the changes in temperature, vertical velocity, and surface streamflow caused by carbonaceous aerosol in this simulation, carbonaceous aerosol could also induce summer precipitation to decrease in southern China but increase in northern China.
文摘A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.
基金supported by the National Natural Science Foundation of China(Grant No.41575002)
文摘This study simulates the effective radiative forcing （ERF） of tropospheric ozone from 1850 to 2013 and its effects on global climate using an aerosol-climate coupled model, BCC_AGCM2.0. I_CUACE/Aero, in combination with OMI （Ozone Monitoring Instrument） satellite ozone data. According to the OMI observations, the global annual mean tropospheric col- umn ozone （TCO） was 33.9 DU in 2013, and the largest TCO was distributed in the belts between 30°N and 45°N and at approximately 30°S; the annual mean TCO was higher in the Northern Hemisphere than that in the Southern Hemisphere; and in boreal summer and autumn, the global mean TCO was higher than in winter and spring. The simulated ERF due to the change in tropospheric ozone concentration from 1850 to 2013 was 0.46 W m-2, thereby causing an increase in the global annual mean surface temperature by 0.36°C, and precipitation by 0.02 mm d-1 （the increase of surface temperature had a significance level above 95%）. The surface temperature was increased more obviously over the high latitudes in both hemispheres, with the maximum exceeding 1.4°C in Siberia. There were opposite changes in precipitation near the equator, with an increase of 0.5 mm d- 1 near the Hawaiian Islands and a decrease of about -0.6 mm d- 1 near the middle of the Indian Ocean.
基金This work was jointly supported by the National Basic Research Program of China(2016YFA0602701)the National Natural Science Foundation of China(41975113)+1 种基金the Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(2020B1212060025)the Guangdong Provincial Department of Science and Technology(2019ZT08G090)。
文摘“I call on all leaders worldwide to declare a State of Climate Emergency in their own countries until carbon neutrality is reached.”–António GUTERRES(United Nations Secretary General),12 December,2020 There is no shortcut to a carbon neutral society;solutions are urgently required from both energy&industrial sectors and global ecosystems.While the former is often held accountable and emphasized in terms of its emissions reduction capability,the latter(recently termed natural climate solutions)should also be assessed for potential and limitations by the scientific community,the public,and policy makers.
基金Under the jointly auspices of the Special Public Research for Meteorological Industry (No. GYHY200806009)Wind Energy Resources Detailed Survey and Assessment WorkEU-China Energy and Environment Program (No. Europe Aid/ 123310/D/Ser/CN)
文摘This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.
基金Specialized Science and Technology Project for Public Welfare Industry(GYHY200906015)National Basic Research Program of China(973 Program,2010CB428606)Key Technologies R&D Program of China(2009BAC51B05)
文摘Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SINTEX-F coupled model is used to build a statistical model to predict the cyclogenesis frequency over the South China Sea and the western North Pacific. The SINTEX-F coupled model has relatively good prediction skill for some circulation features associated with the cyclogenesis frequency including sea level pressure, wind vertical shear, Intertropical Convergence Zone and cross-equatorial air flows. Predictors derived from these large-scale circulations have good relationships with the cyclogenesis frequency over the South China Sea and the western North Pacific. A multivariate linear regression(MLR) model is further designed using these predictors. This model shows good prediction skill with the anomaly correlation coefficient reaching, based on the cross validation, 0.71 between the observed and predicted cyclogenesis frequency. However, it also shows relatively large prediction errors in extreme tropical cyclone years(1994 and 1998, for example).
文摘This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 C during winter than of 4.9 C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.
基金supported by the National Natural Science Foundation of China (41575002, 91644211)
文摘An atmospheric general circulation model BCC_AGCM2.0 and observation data from ARIS were used to calculate the effective radiative forcing（ERF） due to increased methane concentration since pre-industrial times and its impacts on climate. The ERF of methane from 1750 to2011 was 0.46 W m^-2 by taking it as a well-mixed greenhouse gas, and the inhomogeneity of methane increased its ERF by about 0.02 W m^-2.The change of methane concentration since pre-industrial led to an increase of 0.31 ℃ in global mean surface air temperature and 0.02 mm d 1in global mean precipitation. The warming was prominent over the middle and high latitudes of the Northern Hemisphere（with a maximum increase exceeding 1.4℃）. The precipitation notably increased（maximum increase of 1.8 mm d^-1） over the ocean between 10°N and 20° N and significantly decreased（maximum decrease 〉-0.6 mm d^-1） between 10° S and 10° N. These changes caused a northward movement of precipitation cell in the Intertropical Convergence Zone（ITCZ）. Cloud cover significantly increased（by approximately 4%） in the high latitudes in both hemispheres, and sharply decreased（by approximately 3%） in tropical areas.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research[grant number 2020B0301030004]the National Natural Science Foundation of China[grant number 91937302].
文摘Recent advances in the bridging roles played by the Tibetan Plateau(TP)are reviewed in terms of the remote influence of circulation anomalies over the North Atlantic Ocean on Asian monsoon and El Niño-Southern Oscillation(ENSO)events,and in a clear link between the tropical oceans and Asian climate anomalies.The authors firstly introduce how the winter and spring anomalies in the North Atlantic Ocean affect the seasonal transition over the South Asian monsoon region and subsequent ENSO events on the interannual timescale.A distinct negative sensible heating-baroclinic structure in May over the TP is found to provide an intermediate bridging effect in this Atlantic-Asian-Pacific connection.In summer,the North Atlantic Oscillation is significantly correlated with the variations of East China summer rainfall,and it is the TP’s latent heating that plays the bridging role within.On the other hand,such a TP bridging effect also exists in the connection from the tropical oceans to extreme precipitation events over eastern China in summer,and from the midlatitude wave train to the biweekly oscillation of South China rainfall in spring.
基金jointly supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030004)the National Natural Science Foundation of China(Grant Nos.42088101,41975074 and 42175023)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20100304)the Second Comprehensive Scientific Investigation on the Tibetan Plateau of China(2019QZKK0208)the Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(Grant No.2020B1212060025)。
文摘This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset(SCSSMO)and investigates the associated oceanic and atmospheric processes,utilizing the hindcasts of the National Centers for Environmental Prediction(NCEP)Climate Forecast System version 2(CFSv2).Typically,the SCSSMO is accompanied by an eastward retreat of the western North Pacific subtropical high(WNPSH),development of the cross-equatorial flow,and an increase in the east-west sea surface temperature(SST)gradient.These features are favorable for the onset of westerlies and strengthening of convection and precipitation over the South China Sea(SCS).A more vigorous SCSSMO process shows a higher predictability,and vice versa.The NCEP CFSv2 can successfully predict the onset date and evolution of the monsoon about 4 pentads(20 days)in advance(within 1–2 pentads)for more forceful(less vigorous)SCSSMO processes.On the other hand,the climatological SCSSMO that occurs around the 27th pentad can be accurately predicted in one pentad,and the predicted SCSSMO occurs 1–2 pentads earlier than the observed with a weaker intensity at longer leadtimes.Warm SST biases appear over the western equatorial Pacific preceding the SCSSMO.These biases induce a weaker-thanobserved WNPSH as a Gill-type response,leading to weakened low-level easterlies over the SCS and hence an earlier and less vigorous SCSSMO.In addition,after the SCSSMO,remarkable warm biases over the eastern Indian Ocean and the SCS and cold biases over the WNP induce weaker-than-observed westerlies over the SCS,thus also contributing to the less vigorous SCSSMO.
基金supported by the National Natural Science Foundation of China (Grant Nos.42005029 and 41701103)the China Meteorological Administration Special Foundation for Innovation and Development (Grant No.CXFZ2024Q007)。
文摘In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift and intensification of the western Pacific subtropical high(WPSH). Under these conditions, China experienced its hottest summer since 1961,and was hit by a series of high-impact extreme weather and climate events. From 9 June to 2 July, southern China experienced an unprecedented extreme precipitation event that exceeded the well-known 1998 summer precipitation event in both duration and impact scope, resulting in devastating floods in the Yangtze River basin. Subsequently, in early to midJuly, the Huanghe-Huaihe Basin suffered from a severe drought–flood abrupt alternation event, heavily affecting Henan and Shandong. Meanwhile, southern China underwent a widespread heatwave event lasting 74 days, ranking as the second most intense since 1961. From late July to the end of August, northern China faced unusually frequent heavy precipitation events, with cumulative precipitation reaching the second highest for the same period since 1961, causing floods in many rivers of northern China. This study provides a timely summary and assessment of the characteristics and impacts of these extreme events. It serves as a reference for climate change research, including mechanism analysis, numerical simulation,and climate event attribution, and also offers valuable insights for improving meteorological disaster prevention and mitigation strategies.
基金supported by the National Key Program for Developing Basic Science(Nos.2022YFF0801702 and 2022YFE0106600)the National Natural Science Foundation of China(Nos.42175060 and 42175021)the Jiangsu Province Science Foundation(No.BK20250200302).
文摘The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.
基金sponsored by the National Natural Science Foundation of China(Grant Nos.42175052 and U2442206)the Joint Research Project for Meteorological Capacity Improvement(Grant No.23NLTSQ007,23NLTSZ003)+2 种基金the Innovative Development Special Project of the China Meteorological Administration(Grant No.CXFZ2023J002)the National Key R&D Program of China(Grant No.2023YFC3007700,2024YFC3013100)the China Meteorological Administration Youth Innovation Team(Grant No.CMA2024QN06)。
文摘Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasonal precipitation anomalies during summer in China and reveals the contributions of possible driving factors.The results suggest that while single-model ensembles(SMEs)exhibit constrained predictive skills within a limited forecast lead time of three pentads,the MME illustrates an enhanced predictive skill at a lead time of up to four pentads,and even six pentads,in southern China.Based on both deterministic and probabilistic verification metrics,the MME consistently outperforms SMEs,with a more evident advantage observed in probabilistic forecasting.The superior performance of the MME is primarily attributable to the increase in ensemble size,and the enhanced model diversity is also a contributing factor.The reliability of probabilistic skill is largely improved due to the increase in ensemble members,while the resolution term does not exhibit consistent improvement.Furthermore,the Madden–Julian Oscillation(MJO)is revealed as the primary driving factor for the successful prediction of summer precipitation in China using the MME.The improvement by the MME is not solely attributable to the enhancement in the inherent predictive capacity of the MJO itself,but derives from its capability in capturing the more realistic relationship between the MJO and subseasonal precipitation anomalies in China.This study establishes a scientific foundation for acknowledging the advantageous predictive capability of the MME approach in subseasonal predictions of summer precipitation in China,and sheds light on further improving S2S predictions.
基金National Natural Science Foundation of China(42175022)。
文摘In the context of global warming, the increasing wildfire frequency has become a critical climate research focus in North America. This study used the Community Earth System Model(CESM 1.2) to investigate the impacts of 20thcentury wildfires on North American climate and hydrology. Summer represents the peak wildfire season in North America, with the Gulf of Mexico and Midwest regions experiencing the most severe effects. Wildfires not only damage vegetation during the fire season but also extend prolonged impacts into non-fire periods, showing distinct seasonal variations. In spring, wildfires increase surface albedo, triggering a cooling effect through enhanced snow cover and delayed snowmelt. Conversely, summer and autumn surface warming stems primarily from wildfire-suppressed vegetation transpiration. Warming near the Gulf of Mexico enhances moisture transport and precipitation, particularly in summer and autumn. Reduced evaporation and increased precipitation from the Gulf of Mexico significantly altered the hydrological cycle across North America, leading to increased runoff continent-wide.
基金jointly supported by the Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 316323005]the Guangdong Basic and Applied Basic Research Foundation[grant numbers 2023A1515010741 and 2024B1515020035]the Science and Technology Planning Project of Guangdong Province[grant number 2023B1212060019]。
文摘Forecasting tropical cyclone(TC)activities has been a topic of great interest and research.Taiwan Island(TW)is one of the key regions that is highly exposed to TCs originated from the western North Pacific.Here,the authors utilize two mainstream reanalysis datasets for the period 1979-2013 and propose an effective statistical seasonal forecasting model-namely,the Sun Yat-sen University(SYSU)Model-for predicting the number of TC landfalls on TW based on the environmental factors in the preseason.The comprehensive predictor sampling and multiple linear regression show that the 850-hPa meridional wind over the west of the Antarctic Peninsula in January,the 300-hPa specific humidity over the open ocean southwest of Australia in January,the 300-hPa relative vorticity over the west of the Sea of Okhotsk in March,and the sea surface temperature in the South Indian Ocean in April,are the most significant predictors.The correlation coefficient between the modeled results and observations reaches 0.87.The model is validated by the leave-one-out and nine-fold cross-validation methods,and recent 9-yr observations(2014-2022).The Antarctic Oscillation,variabilities of the western Pacific subtropical high,Asian summer monsoon,and oceanic tunnel are the possible physical linkages or mechanisms behind the model result.The SYSU Model exhibits a 98%hit rate in 1979-2022(43 out of 44),suggesting an operational potential in the seasonal forecasting of TC landfalls on TW.
基金the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030004)the National Natural Science Foundation of China(Grant Nos.42275002 and 42275006)+1 种基金the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.ZDJ2024-01 and ZDJ2024-25)the Science and Technology Planning Project of Guangdong Province(Grant No.2023B1212060019).
文摘Active atmospheric convection on the monsoon coast is crucial for the Earth’s climate system.In particular,the upscale convective growth(UCG)from ordinary isolated convection to organized convective system is a key process causing severe weather,but its activities on the monsoon coast are less understood because of the lack of fine-resolution datasets.For the first time,we present the climatology of UCG on a typical monsoon coast using kilometer-mesh radar data from southern China.The UCG undergoes pronounced subseasonal and diurnal variations in the early-summer rainy season.The subseasonal UCG increase is attributed to the onshore flows shifting from easterlies in April to monsoon southwesterlies in June.UCG becomes vigorous following summer monsoon onset,with hotspots near windward coastal mountains.Daytime UCG first peaks near noontime along coastal land,where onshore flows are destabilized by boundary-layer heating and mountains.Afternoon inland peaks and off-coast minimums are recognized due to land–sea thermal contrast and sea-breeze circulation.Nighttime UCG is revived at the coast by nocturnally enhanced southerlies,followed by offshore activity as the convergence of land-breeze northerlies shifts seaward.The UCG thus responds strongly to changing atmospheric conditions,land heating/cooling,and thermally driven local circulations.Our results may help clarify the predictability of monsoon coastal convection.
基金Science and Technology Development Fund of Macao Special Administrative Region (0009/2024/RIB1)Guangdong Major Project of Basic and Applied Basic Research Foundation(2020B0301030004)。
文摘The inherent black-box nature of machine learning(ML) models limits their interpretability and broader application in heavy precipitation forecasting. Evaluating the reliability of these models involves analyzing the link between predictions and predictors. In this study, ERA5 reanalysis data, CERES satellite observations, and ground-based meteorological observatories were utilized to compile more comprehensive multi-type predictors for developing a Bayesian optimized XGBoost model for the nowcasting of heavy precipitation in the Guangdong-Hong Kong-Macao Greater Bay Area during the pre-summer rainy season. A comparison of model performance with different combinations of input features and classical machine learning algorithms demonstrated that the Bayesian optimized XGBoost model achieved the best overall performance, with an average Critical Success Index of 68.30%. Permutation Importance(PI) and shapley Additive Explanations(SHAP) methods were utilized to interpret feature effects in heavy precipitation forecasting. The results indicated that precipitable water vapor(PWV), cloud, relative humidity, and seasonal and diurnal variables had more significant effects on the model output as individual features. Furthermore, the collective influence of derivatives from PWV and meteorological parameters(e.g., temperature, relative humidity, pressure and dew point temperature)showed a significant enhancement over their individual impacts, indicating synergistic interactions among these predictors.Applying explainable artificial intelligence(XAI) to ML models helps understand how models utilize features for forecasting, enhances the reliability of forecasts, and guides feature selection and the mitigation of overfitting phenomena.
