Abstract:In this study,the 5th generation European Centre Hamburg general circulation model(ECHAM5) and global assimilation and prediction system(GRAPES),independently developed by the China Meteorological Administration,were used to simulate the stratospheric temperature during the period of January 1-6,2010.The results from the two models were then compared and analyzed,referring to the global final analysis(FNL) data.Through a series of comparisons,it was shown that the temperature variations at 50 hPa simulated by ECHAM5 and FNL varied little over time,whereas the simulations performed by GRAPES were significantly elevated in the Southern Hemisphere.The regional warming projected by GRAPES seemed too distinct and uncontrolled to be reasonable,although the warming pattern remained fairly stable with a value between 5 and 15 K relative to the start time.The temperature difference projected by ECHAM5 and FNL was small at the start time on the global scale.Over time,the values become larger in more locations,indicating a significant warming projected by GRAPES.In the Southern Hemisphere,where the warming by GRAPES was dominant,the maximal temperature difference was larger than 24 K at 30-60°S latitude,30-60°E longitude for the final two simulation days,then increased to more than 12 K over the entire Antarctic continent.The temperature initial condition comparison between ECHAM5 and GRAPES shows that they are significantly similar,especially in the Southern Hemisphere,with the difference values being about zero.Moreover,although the ozone profile of ECHAM5 was used in GRAPES,the warming in the Southern Hemisphere simulated by GRAPES still existed.Therefore,the errors produced by GRAPES were not significantly related to either factor.Atmospheric vapor and heating rate may also be factors leading to stratospheric warming,but in this preliminary study these factors could not be investigated,due to a number of technical problems.Further research focusing on the impact of factors such as vapor,heating rate,temperature,etc.will be conducted to further investigate the reasons for the simulated temperature errors produced by GRAPES.

Abstract:Ozone absorption of ultraviolet radiation is a main heat source and plays an important role in radiation balance of stratosphere.Solar cycle,especially ultraviolet radiation,can directly affect the stratospheric heating rate.According to the data from SIM(Spectral Irradiance Monitor) on the satellite SORCE,it indicates that the reduction of ultraviolet radiation is more than four to six times as prior research results in the weak solar activity years from 2004 to 2007.The variation of ultraviolet radiation can affect the stratospheric heating rate by changing ozone distribution.Through qualitative research,ozone concentration mixing ratio shows strong positive anomaly in lower stratosphere,and also indicates positive correlation with solar heating rate in upper stratosphere in the strong solar activity years.In addition,lots of studies of stratospheric radiation balance used the annual average data.However,BD(Brewer-Dobson) circulation relates with planetary wave effects and atmospheric thermal radiation plays a main role in stratospheric radiation balance in winter.To understand the essence,analysis of summer stratosphere is particularly significant.Thus,the main purpose of this paper is using the data of SIM and the mode of atmospheric radiation model to quantitatively study the effects of variations of ultraviolet radiation and ozone concentration mixing ratio in the solar cycle on the ozone heating rate(OHR) and the net heating rate(NHR).Based on the BCC-RAD Model,OHR and NHR in stratosphere in the Northern Hemisphere in summer are calculated by using the ERA-Interim monthly reanalysis data from European Centre for Medium-Range Weather Forecasts(ECMWF) during 1979-2013 and the solar spectral irradiance data from National Oceanic and Atmosphere Administration(NOAA) from 2004 to 2010.Variations of zonal mean OHR(NHR) in stratosphere in the 11-yr solar cycle are discussed,and the causes of differences between the strong and weak solar activity years are discussed.The results can be summarized as follows:Compared to the weak solar activity years,the ultraviolet radiation is stronger in the strong solar activity years,which results in the positive anomalies of OHR and NHR in whole stratosphere,and the anomalies increase with height.Ozone concentration mixing ratio shows negative(positive) anomaly in lower(upper) stratosphere,which leads to the similar pattern of both OHR and NHR,and slightly upward migration(because of the efficiency of ozone absorption in ultraviolet increases with height).As for OHR and NHR in upper stratosphere,the ultraviolet radiation plays a main role at stratopause,and ozone takes the most important part in other spaces.In this paper,the effects of ultraviolet radiation to ozone in chemistry are not discussed.In order to systematically study the influence of solar cycle on stratosphere,it needs to use chemical climate model for more detail simulation analysis.

Abstract:Based on the NCEP/NCAR reanalysis data and the HadISST monthly mean sea surface temperature(SST) data from 1961 to 2013,this paper investigates the characteristics of tropical central Pacific SST anomaly(SSTA) and tropical Indian Ocean Basin Mode(IOBM),and their combined influences on climate in eastern China during summer half-year.Results demonstrate that the tropical central Pacific SSTA pattern index(CPI) and IOBM index(IOBMI) are almost independent of each other in sense of statistics.When the CPI and IOBMI have same signs(referred to PPNN cases) and opposite signs(referred to PNNP cases),the tri-pole and dipole SSTA patterns are observed in tropical India Ocean and Pacific Ocean,respectively.Mechanisms behind different anomalous rainfall patterns in eastern China are different in PPNN and PNNP cases.In PPNN cases,moisture can be transported from Maritime Continent(MC) to the Yangtze-Huaihe River basin.The anomalous circulations in eastern China are generated and maintained due to Gill response of atmosphere to the tropical SSTA.The anomalous vertical circulation cells over region from MC northward to the Yangtze-Huaihe River show some connections between anomalous thermal forcing over MC and rainfall anomalies over the Yangtze-Huaihe River basin.However,in PNNP cases,no moisture is transported into the Yangtze River.Due to the significant westward shift of location of SSTA center in Pacific,the corresponding anomalous circulations also shift westward as a Gill response of atmosphere to central Pacific SSTA pattern.Meanwhile,Rossby wave energy can propagate into region south of the Yangtze River from MC,facilitating the maintenance of anomalous anti-cyclonic circulation over region south of the Yangtze River.These results are beneficial to us for better understanding the causes of rainfall anomalies and the role of SSTA patterns over Indo-Pacific region in inducing precipitation anomalies in eastern China.

Abstract:With the development of social economy and the improvement of people's living standard,the demand of country and society for the short-term climate prediction is increasing.Though current methods including statistic,dynamical-statistic and numerical methods for the prediction of surface air temperature in wintertime are more,the prediction lead time is usually short and the forecast skill is not stable.For example,the seasonal prediction of climate model for winter temperature is still low outside the tropics and the most models cannot give reliable results in many areas of China.So it is very important to carry prediction experiment of winter air temperature and expand valid prediction lead time,in order to meet the needs of the society.Based on NCC(National Climate Center of China) monthly surface air temperature data of 160 stations in China and NCEP/NCAR monthly mean reanalysis data during 1979-2015,the predictive factors are selected from early winter geopotential height at 500 hPa and velocity potential at 850 and 200 hPa during 1979/1980-2008/2009.Considering the combination of different predictive factors and their independence,the monthly rolling forecasting models are separately established by the multi-variable regression ensemble,the cross validation test ensemble and the monthly rolling prediction ensemble,in order to perform independent predictive tests for the winter temperature in China during 2010/2011-2014/2015.The velocity potential can reflect the external forcing source of atmospheric system,and 500 hPa height can denote the basic state of atmospheric circulation.Although the memory of internal evolution within atmosphere circulation is about a week or so,the initial time potential function at 850 and 200 hPa can reflect variations of the upper and lower level boundary forcing anomalies and their influences on the future atmosphere.Besides,it is simple and practical to select factors from the predictands on the above three levels.
Results show that the multi-variable regression ensemble(ENC1) may increase predictable station number.Combined using of the multi-variable regression ensemble and the cross validation test ensemble(ENC2) can improve stability and prediction skill,which is negatively affected by unstable statistic relationship between predictor and predictand.The comprehensive ensemble of multi-variable regression,cross validation test and monthly rolling prediction(ENC3) can not only increase the predictable station number,but also make the prediction more stable,which improves the feasibility and stability of objective quantitative prediction of short-term climate.Although the data used in establishment of prediction model are less and not complex,the final prediction model,through the comprehensive application of the three ensemble methods,has a certain predictive ability for the winter surface air temperature in China,and the prediction lead time is relatively long.Therefore,the statistic model established here will make the long-lead prediction reliable and effective with valuable skill,which is very important in practical use in short-range climate prediction.In addition,the comprehensive application of multi-ensemble methods can also be employed to correct the numerical model products by the establishment of dynamic statistical forecasting model.

Abstract:In this study,the characteristics of intraseasonal evolution of precipitation in the rainy season of Jiangnan(24-30°N,110-120°E) and its interannual and interdecadal variations are researched,using daily precipitation data for the period of 1961-2008,based on the analysis of climatic characteristics of precipitation over southeastern China.The results are as follows:
1)A significant twin-peak feature in the intraseasonal evolution of precipitation in Jiangnan is demonstrated,with mid-April and mid-June as the twin-peak periods.The peak precipitation first appears in Jiangnan in mid-to late April,then extends southward.Southern China reaches its peak precipitation period in early to mid-June,after which the heavy precipitation center moves northward,and Jiangnan experiences the second precipitation peak in mid-to late June.Meanwhile,the precipitation in the Jianghuai area(32-35°N) shows a single peak type.The first peak of the Jiangnan rainy season appears very early,and this is the first sign of the rainy season in eastern China.The second peak is the performance of the main rain belt moving northward.
2)The correlation coefficient between the regional averaged twin-peak precipitation in Jiangnan and actual precipitation is 0.69,which indicates that the twin-peak precipitation shows the intraseasonal evolution features of the Jiangnan rainy season.The precipitation intensity of the Jiangnan rainy season mainly depends on the precipitation intensity of the bimodal peak in the rainy season(April-June),and this also shows that the twin-peak precipitation characteristics in the Jiangnan area can reflect the change characteristics of the actual precipitation.
3)The twin-peak precipitation of the Jiangnan rainy season displays significant interannual and interdecadal variations.The interannual periods are found every 2-3 years,and strong signals are mainly centered in the late 1960s to 1970s and mid-1980s to the beginning of the 21st century,while the interdecadal periods are shown every 8-10 years on the whole time domain,and their strong signals are centered in the early 1980s to late 1990s.
4)On the interdecadal scale,although the intraseasonal features of precipitation display a significant twin-peak precipitation pattern in the Jiangnan rainy season,the characteristics of the intraseasonal evolution also show skipped-significant features.A twin-peak precipitation pattern is notable in the 1960s,1980s and the beginning of the 21st century,while in the 1970s and 1990s the twin-peak pattern is insignificant.

Abstract:Immense heat of about 1 PW(1 PW=1 015 W) is transported by Atlantic Meridional Overturning Circulation(AMOC) from the low-latitude to high-latitude North Atlantic(HNA),and then released to the local atmosphere through surface turbulent heat flux,thus dominating the pattern of the local climate and climate changes over the Northern Hemisphere on multiple scales.Based on limited observations,previous works have observed a weakening trend in the turbulent heat flux of the HNA over the last part of 20th century,and have proposed that it is a result of global warming.To confirm these findings,in this study we investigate the response of HNA turbulent heat flux to global warming based on four warming scenario experiments of 13 CMIP5 models.The results show that the HNA turbulent heat flux significantly decreases under a warming climate,and that its weakening magnitude is larger under warmer scenarios.For the strongest warming scenario of Rcp 8.5,the multi-model averaged reduced magnitude of the HNA turbulent heat flux reaches about 40 W·m²,which is nearly 1/3 of the value before warming.Furthermore,the results of multi-model consistently show a stronger weakening of the HNA turbulent heat flux in winter.The multi-model averaged reduced magnitude of the HNA turbulent heat flux in winter is close to about 43 W·m^-2,but the value in summer is only about 10 W·m^-2,signifying that its magnitude in summer is less than 1/4 that in summer.The weakened HNA turbulent heat flux under warming is attributed to the weakened AMOC and its related reduced oceanic heat transport to the HNA.The results of a water-hosing experiment,using a fully coupled climate model of CCSM3,confirm the dominant contributions of weakened AMOC to reduced HNA turbulent heat flux under warming.The reduced turbulent heat flux of the HNA is a key factor to understanding the climate changes of the Northern Hemisphere under warming.

Abstract:In this study,to explore the strength and structure of sea breeze under cloudy conditions over Hainan Island,the 3D high-resolution numerical simulation of sea breeze on July 5,2012 was conducted by means of non-hydrostatic mesoscale model WRF,coupled with the Noah land-surface model.Hainan Island is a tropical island with oval topography.The frequency of occurrence of sea breeze is high throughout the island,due to its geographical location and unique topography.In addition,cloudy skies under weak stable weather conditions are conducive to the triggering of sea breeze,according to previous researches regarding the statistical analysis of sea breeze over Hainan Island.Therefore,it is significant to study the structure of sea breeze circulation on July 5,2012,when the sea breeze observed was conspicuous,and there was a large number of clouds over the island during the evolution of the sea breeze.Compared with the observational data,the results show that the evolution and characteristics of sea breeze can be reasonably simulated by WRF.The evolution of sea breeze under cloudy conditions resembles sea breeze under clear conditions.Formed at 12:00 BST throughout the whole island,sea breeze circulation was strong during the time range of 15:00-18:00 BST in flat areas,and strong during 13:00-18:00 BST in mountainous areas.A significant convergence line was finally observed on the island at 18:00 BST.Strong convective weather could be easily triggered under the convergence of sea breezes for the deep convective instability energy and abundant water vapor,i.e.the convergence zone of sea breezes is the main potential precipitation area.The complex terrain has direct and indirect effects on the structure of sea breeze circulation.It determines the distribution of the low-level horizontal wind field,then affects the characteristics of sea breeze in all directions indirectly.The sea breeze circulation becomes clear,the sea breeze front is almost perpendicular to the ground and its strength enhances,then the sea breeze convection can last for a longer time,indirectly due to the blocking and lifting effect of the mountain.At the same time,the valley breeze circulation forms and disappears almost simultaneously along with the sea breeze.Therefore,the valley breeze circulation interacts with the sea breeze circulation on the same side of the mountain.On one hand,this can cause frontolysis of the sea breeze front when the valley breeze strengthens suddenly,otherwise it causes frontogenesis of the sea breeze when the valley breeze weakens.On the other hand,the circulation becomes more pronounced and strengthened when the valley breeze overlaps with the sea breeze.However,in flat areas,the dynamic and thermal effects of the terrain are weak.The sea breeze pattern in flat areas is more regular than in mountain areas.Sea breezes from different directions gather together,and some convective clouds merge in the convergence of sea breezes.Furthermore,the variation of sea breeze circulation mainly depends on the interaction with sea breezes from different directions.

Abstract:GRAPES(Global/Regional Assimilation and Prediction Enhanced System) is a new generation numerical weather prediction model in China,and its ability to forecast cold wave processes occurred from December 2011 to February 2012 is tested by using conventional station observation data and NCEP-FNL reanalysis data.The results are shown as follows:GRAPES can forecast the significant cooling,the circulation patterns of upper and lower altitudes,and the invasion of cold advection in the four cold wave processes occurred in the winter of 2011/2012.The prediction effect is worse in the cold wave occurred on 22 February than the other three.As for the forecast of strong cooling,the prediction results are bad in parts of Xinjiang,the Yunnan-Guizhou Plateau and the Sichuan Basin in the cold wave processes occurred on 18 January,5 February and 14 February.It also shows a large deviation in eastern China in the cold wave occurred on 22 February.There are forecast deviations of strength and location of blocking high,East Asian trough and other systems at 500 hPa in the cold wave occurred on 22 February.The large deviations in cold and warm advection forecast in the four cold waves exist in Xing'an Mountains in Northeast China and south of the Yangtze River basin.Forecast results of range and strength of both cold advection in Xinjiang,Greater Khingan Range and Liaoning and warm advection in south of the Yangtze River basin are larger than observations in the cold wave occurred on 22 February,leading to the large temperature forecast deviation,which may be related to the error of model physical process in the terrain region.

Abstract:Based on the daily mean temperature data of 1960-1999 at 175 meteorological stations over China,this paper firstly analyzes the characteristics of the two climate backgrounds(Climate background A contained the years from 1960 to 1989,while the climate background B contained the years from 1970 to 1999).Monte Carlo significance test method is applied to examine the difference in winter and summer under the two climate backgrounds.Respectively based on the two different climate backgrounds,the study applies climate percentile method to analyze the variation characteristic of the extreme temperature over China from 2000 to 2010.The result showed that the difference of winter average temperature under the two climate backgrounds is more significant than the difference in summer.The extreme low temperature events in winter(summer) happen less frequently than extreme high temperature events in winter(summer) over China.Because the climate background B contained the years from 1980 to 2000 and the global warming was most serious during this period,when we use climate background B as the background during 2000-2010,the extreme low temperature events in winter(summer) happen more frequently than using climate background A as the background.The situation of extreme high temperature in winter(summer) is contrary to the situation of extreme low temperature events in winter(summer) from 2000 to 2010.These results are consistent with the trends of global warming.

Abstract:By using the conventional meteorological data,NCEP 1°×1° reanalysis data,Satellite Images data and CINRAD/SA data,the reason for the failure of the foecast and the cause of the heavy rainfall after Saola Typhoon landing is analyzed.Asymmetric distribution of precipitation by Typhoon Saola has been analyzed from circulation background,change of vertical structure,steering flows,environmental vertical windshear,physical quantity diagnosis and so on.The results show that:The main reason for the large deviation of typhoon rainstorm forecast and actual situation is that little attention has been paid to the change of the vertical structure of typhoon and its impact on the precipitation area during the forecasting process.The stable circulation background of high latitude provides favorable conditions of asymmetric distribution of typhoon precipitation;the change of steering flows in the vertical tilted the typhoon center southward with height;the steering flows and environmental vertical wind shear are the reasons which caused the typhoon center southward with height;The change of the vertical wind shear indicates the heavy rainfall region,which reflects the stronger convection and rain on the left of downshear;In addition,while the typhoon center southward with height,the distribution of the vorticity has to been changed,so the heavy rainfall happened in the southern Fujian proivince.Therefore,it is important to pay attention to the change of this vertical structure of typhoon.

Abstract:Based on the reanalysis data with horizontal resolution of 0.75°×0.75° from the European Center of Medium-range Weather Forecast(ECMWF),this paper investigates the wind energy and wind speed in the narrow area along the coastal line of China,and discusses the distribution characteristics of wind energy and wind speed in different regions and different seasons.The Weather Research Forecast(WRF) model is used to simulate the influence of sea surface temperature(SST) increase and urbanization development on wind energy in east coast of China.Results show that:(1)The wind energy has significant spatiotemporal differences among different coastal regions of China,with obvious seasonal variations.In spring,the wind energy in Bohai gulf is obviously larger than that in other regions(coastal areas of East China,southeastern China and north of South China Sea).In summer,the wind energy in Bohai gulf is clearly smaller than that in other regions and it is slightly larger in coastal area of East China.In autumn,the wind energy in coastal areas of southeastern China and north of South China Sea is significantly larger.In winter,the wind energy is similar in the four coastal regions of China.Generally,the wind energy is larger(smaller) in autumn and winter(spring and summer),and the wind energy in summer is significantly smaller than that in winter.(2)Interannual variation of wind speed has obvious differences in different coastal areas of China and different seasons.Besides the wind speed has an increasing trend in coastal area of southeastern China in winter,it has a slow decreasing trend in other areas in each season,but the range of reduction is very small.(3)Numerical simulations show that the effects of SST increasing on the wind speed in different seasons are different.The wind speed in Bohai Gulf,Shandong peninsula,Beibu Gulf coast and Hangzhou Bay increases with the increase of SST in spring.The regions of significant wind speed change are different with different SST increasing in summer,but the wind speed in most coastal areas increases with the increase of SST.The increasing of SST has great impacts on the wind speed in summer and autumn.Wind speed increases with SST increasing in autumn and winter,with more stable areas of influence.The wind speed increases in coastal areas of southeastern China and East China in autumn,and it does in coastal areas of Bohai gulf and north of South China Sea in winter.(4)The development of urbanization results in the increases of surface friction force,causing the tropical cyclone that lands on China is rapidly weakening in summer and autumn,in such a way that the wind speed decreases in coastal areas of China.

Abstract:Based on the daily precipitation data at 77 stations in Jiangnan area of China and the NCEP/NCAR reanalysis data,the different time scale low frequency precipitation in Jiangnan area and the principal component of 850 hPa low frequency meridional wind in East Asia are employed to construct a multivariable lagged regression(MLR) model,which is applied to complete the daily extended range forecast test for the low frequency precipitation in Jiangnan area during May-July of 2011.Results show that the average prediction skill of the 50-70 d low frequency precipitation in Jiangnan area is up to 0.76,which is able to predict accurately the period of persistent heavy rainfall and the conversion of positive and negative phase of low frequency precipitation.The hindcast experiments from 2001 to 2012 show that the MLR model can predict well the low frequency precipitation in Jiangnan area ahead 30 days in the years of stronger or normal 50-70 d oscillation.The model results also show that the development and evolution of 850 hPa low frequency meridional wind are the outstanding signals for the change of low frequency precipitation in the next 30 days and can be considered a key factor of extended range heavy precipitation prediction in Jiangnan area in early summer.

Abstract:The Global Positioning System (GPS) demonstrates a novel and practical approach which is well-known globally,representing high-precision,high-vertical-resolution,and long-time sustain ability in different weather conditions proposed in early 1990s.The Constellation Observation System of Meteorology Ionosphere and Climate (COSMIC) program has been designed to provide advances in climatology,and space weather by using GPS satellites.The gathered data provides notable advances on the probing of neutral atmosphere and ionosphere.In addition,it is regarded as a robust solution for numerical weather prediction and the monitoring the climate changes.Before acquiring the atmospheric temperature and vapor pressure data by the COSMIC program,it seems to be necessary to control the quality of the spatial distribution characteristics.In this paper,to identify the existing differences in the quality of observations for between the land and ocean areas,the evolution characteristics including latitude and altitude coordinates as well as the quality of the atmospheric temperature and vapor pressure data obtained from COSMIC program are analyzed and assessed with the help of conventional radiosonde observations provided by National Centers for Environmental Prediction(NCEP) throughout the world,respectively.The results show that the temperature data retrieved by the COSMIC program is slightly lower than the NCEP observations over China.Moreover,the values of Root Mean Square Error(RMSE)for the temperature and vapor pressure data is negligible.In the global scale,there is a significant difference between the quality of the temperature and vapor pressure data retrieved from the COSMIC atmospheric data with the given latitudes and altitudes.Moreover,the quality differences in the horizontal and vertical distribution for the retrieved data from COSMIC atmospheric retrieved data are significant over land and ocean area.In general,the atmospheric temperature and vapor pressure data retrieved from COSMIC program demonstrates to be reliable and accurate,in which can be used for numerical weather prediction.On the other hand,the special distribution characteristics of quality of atmospheric temperature and vapor pressure using COSMIC atmospheric retrieved data can be regarded as a base for the quality control of observations as well.

Abstract:Plumb wave activity flux,T-N wave activity flux and local E-P wave activity flux are widely used to analyze the propagation of Rossby wave in atmospheric dynamics.The differences in characteristics and applicability among three types of Rossby wave activity fluxes are discussed in a case study of a cold wave in January 2016.Plumb wave activity flux with strong zonal component and weak meridional component is suitable for the analysis of Rossby waves with small amplitude in the zonally symmetric westerly.T-N wave activity flux with improved meridional component based on Plumb wave activity flux is appropriate for analyzing Rossby waves in the zonally asymmetric westerly.T-N wave activity flux derived on the multi-year average climatic field of current month can more successfully indicate wave propagation anomaly in current season.Local E-P wave activity flux can illustrate the modulating effect of transient waves on background field (stationary waves),but can not reflect the evolution of long waves.

Abstract:Cloud fraction is the basis for the application of meteorological satellites.Compared with traditional methods,the existing methods based on Machine Learning(ML) showing better performance in the utilization of all of the characteristics and optical parameters of the satellite cloud.However,at present there has been no cloud classification standard large sample set,which is a critical problem in this area.This forces researchers to build their own small databases,but in the process of building it,samples of some categories are difficult to label,while those of some relative categories are easy to label,thus the distribution of the sample set is complex and uneven,causing the ML to inhibit cloud detection and cloud fraction performance.In order to resolve this problem,in this paper,based on NSMC's HJ-1A/B satellite imagery data,the Transfer Learning (TL) approach is used for cloud detection.More specifically,the researchers labeled a large number of thick cloud samples,built six sets,and used these as auxiliary sample sets;they then labeled a small number of thin cloud samples,built one set,and used this as a task sample set.The results of the study show that TL,when combined with Extreme Learning Machine (ELM),can utilize the knowledge of the sample sets' auxiliary thick cloud to improve the ELM's thin cloud identification accuracy,which was only trained by the thin cloud sample set.This shows that the TL algorithm would be a good choice in a greater number of categories of cloud classification work when the sample set is complex and uneven.