Abstract:ENSO is the strongest interannual variability in our climate system.It has profound impacts on global climate.Since El Niño-Modoki was revealed in 2007,more and more efforts have been made in the climate community to investigate the different types of ENSO events and their influences.Those different ENSO events are known as the EP-type(Eastern Pacific-type) and CP-type(central Pacific-type) ENSO.Following established methodology,we adopt the EP-type ENSO index(EPI) for boreal summer in the present paper.By employing methods including composite analysis,linear regression,and EOF decomposition,we investigate the simultaneous relationships between EP-type ENSO and precipitation anomalies in the Maritime Continent(MC) by using the monthly mean data from the NECP/NCAR reanalysis,global SST data from the Hadley Center,and CAMP monthly mean precipitation data for the period 1979-2013.
The results demonstrate that EPI and CPI in boreal summer are able to describe the main features of EP-type and CP-type ENSO,respectively,although the EPI and CPI are not perfectly independent of each other in a statistical sense because the correlation coefficient of EPI with CPI was found to be 0.30.During some years,EPI is relatively smaller.But,the spatial pattern of anomalous SST still looks like EP-type ENSO.In these years,the anomalous precipitation averaged over the MC region is negative.Usually,we expect a strong negative correlation between canonical ENSO and rainfall anomalies in Indonesia.However,we find that the time series of the regional mean precipitation anomaly over the MC is weakly correlated with the EPI.These results are inconsistent with one another.
By examining the anomalous circulations case by case,we find that this weak correlation is induced by some co-occurrences of the EP-type El Niño(La Niña) with more(less) than normal rainfall in the Indonesian region in some years.After removing the Niño4 signal from SST anomalies,we find that both the SST anomaly(SSTA) and rainfall anomalies are independent of the Niño4 signal.The EPI independent of Niño4 is calculated.Then,the co-occurrences of positive EPI with positive anomalous rainfall in the MC can still be observed in some years.By performing composite analyses,we found that there are two mechanisms that link the SSTAs in the eastern equatorial Pacific to precipitation anomalies in the MC region.One is canonical,which is characterized by the anomalous Walker circulation with its ascending(descending) branch over the east equatorial Pacific and the descending(ascending) branch over the MC region in years when EP-type El Niño(La Niña) events occur.We refer to this as the direct connection mechanism.The other is quite different from the direct connection mechanism.When an EP-type El Niño event occurs in certain years,significant anomalous heating is observed in both the MC and the region east of the Philippines,and significant anomalous cooling in the South Pacific Convergence Zone(SPCZ),respectively.These two anomalous diabatic forcing centers force the atmosphere to respond,inducing a northwest-southeast vertical circulation bridging these two centers,which anomalously weakens the descent of the atmosphere in the MC and intensifies the descending motion in the SPCZ,resulting in the anomalous Walker circulation along the equator being stopped in the SPCZ east of 160°E.In this way,positive anomalous rainfall events occur in the MC when the EPI is positive.This anomalous northwest-southeast vertical circulation,with its upward motion branches over the MC and the region east of the Philippines,and a downward motion branch over the SPCZ,connects the EP-type ENSO-induced Walker circulation,with its downward motion over the SPCZ and upward motion over the east equatorial Pacific.The anomalous adiabatic forcing in the SPCZ is crucial in interfering with the influences of EP-type ENSO on rainfall variations in the MC region.This linkage of EP-type ENSO with rainfall anomalies in the MC via anomalous forcing in the SPCZ is referred to as the indirect connection mechanism,in relation to EP-type ENSO with rainfall variations in the MC.
The results in the present paper are highly meaningful in terms of improving our understanding of the mechanisms behind the relationships of ENSO with climate variations in the MC region,and even in East Asia.

Abstract:Stratosphere-troposphere exchange(STE) is a process not only involving transport from the troposphere to stratosphere,but also from the stratosphere to troposphere.STE is very important to the variation of water vapor and atmospheric chemical compositions.Correspondingly,it also plays an important role in the radiation balance and climate changes in the global climate system.Deep convection occurs frequently in summer.The strong upward flow in deep convective cloud can transport the atmosphere of the lower troposphere quickly to the upper troposphere,and even to the lower stratosphere.Thus,it is very important in the process of STE.To date,this conclusion has been reached largely with the help of aircraft observations.
STE is a process that includes complex physical,chemical and dynamic processes.The time scale of STE can be climatological,synoptic,meso,and turbulent,while the spatial scale varies from local to global.Therefore,STE is a highly complex process,and to study such a complex process,using models to quantitatively simulate the transport processes is a good method.FLEXPART is a Lagrangian diffusion model.It is widely used in the transport of air pollution,the mesoscale transport of smoke from forest fires,as well as global STE.
In this study,firstly,data on deep convection in China and surrounding areas for the period 2005-2012 were collected.The source of the data-collected 24 times a day and at a spatial resolution of 0.1°-was the FY-2 satellite.Through statistical analysis,the interannual variation of the deep convection was determined.One year of minimum convection and one year of maximum convection were selected from the overall study period.Then,the domain(15-30°N,75-135°E)was selected to represent China and its surrounding areas.In order to understand the bidirectional exchange characteristics of troposphere-to-stratosphere transport(TST)and stratosphere-to-troposphere transport(STT)in summer in this region,the atmospheric circulation status of the two selected years from June to August was simulated using FLEXPART.The statistical and model results were analyzed,revealing the following:
In the summer season of 2009,deep convection occurred least frequently;while in the summer season of 2010,it occurred most frequently.The atmospheric circulation from June to August 2009 and 2010 was simulated using FLEXPART,and it was found that the area south of 30°N and the area north of 30°N possessed different characteristics of STE.In the area north of 30°N,TST and STT were active;whereas,in the area south of 30°N they were far less active than the area north of 30°N.However,the net transport (TST minus STT)was roughly equal.From June to August,in the area south of 30°N,the net transport was from the troposphere to stratosphere;while in June,in the area north of 30°N,the net transport was from the stratosphere to troposphere.In July and August,the net transport was from the troposphere to stratosphere.Comparing the TST and TST-minus-STT of summer 2009 and 2010,it was found that the total amount of TST and TST-minus-STT from June to August 2010 was more than that in 2009.This means that the transportation from the troposphere to stratosphere was larger in 2010 than in 2009.The TST and TST-minus-STT might be positively correlated with the deep convection activity,and this will be investigated in future work.

Abstract:Ozone research has been a hot spot in research on climate change because stratospheric ozone can directly affect the earth system and climate change by absorbing solar ultraviolet radiation.The ozone valley over the Tibetan Plateau in summer has a significant impact on local climate.Against the background of energy conservation and emissions reduction,studying the characteristics and possible mechanism of ozone change in the future can provide theoretical support for the future development of relevant policies.
To understand future ozone trends over the Tibetan Plateau in summer and their possible mechanism,version 3 of the Whole Atmosphere Community Climate Model(WACCM3),with a horizontal resolution of 1.9°×2.5°(longitude×latitude)and vertical resolution of 1.1 km in the upper troposphere and lower stratosphere region,was used to simulate three emissions scenarios of the Special Report of the Intergovernmental Panel on Climate Change(IPCC).The three emissions scenarios were A1B("[which] describes a future world of very rapid economic growth,global population that peaks in mid-century and declines thereafter,and the rapid introduction of new and more efficient technologies.Major underlying themes are convergence among regions,capacity building,and increased cultural and social interactions,with a substantial reduction in regional differences in per capita income.Direction of technological change in the energy system is a balance across all sources."),A2("[which] describes a very heterogeneous world.The underlying theme is self-reliance and preservation of local identities.Fertility patterns across regions converge very slowly,which results in continuously increasing global population.Economic development is primarily regionally oriented and per capita economic growth and technological change are more fragmented and slower than in other storylines."),and B1("[which] describes a convergent world with the same global population that peaks in mid-century and declines thereafter,as in the A1 storyline,but with rapid changes in economic structures toward a service and information economy,with reductions in material intensity,and the introduction of clean and resource-efficient technologies.The emphasis is on global solutions to economic,social,and environmental sustainability,including improved equity,but without additional climate initiatives.").
The simulation results showed that,under A1B,A2 and B1,2001-2099 global total ozone has an increasing trend,which means ozone recovery.The increasing trend of total ozone under A2 is strongest,and the increasing trend of total ozone under B1 is weakest.In the three emissions scenarios,total ozone over the Tibetan Plateau area(26-38°N,75-105°E) shows an increasing trend,but the speed of recovery is slower than that of the global total ozone;that is,the ozone valley over the Tibetan Plateau will significantly deepen.Total chlorine content over the Tibetan Plateau in summer and the chloride concentration at 70 hPa near the center of the ozone valley over the Tibetan Plateau in summer showed decreasing trends for the next 100 years.Meanwhile,the ascending branch of local Hadley Circulation over the Tibetan Plateau in summer has a decreasing trend.These two factors lead to an increase in total ozone over the Tibetan Plateau in summer in the future.On the other hand,the intensity of the South Asia high in the future will enhance,the divergence near the South Asian high will strengthen,and the ozone flux divergence near the South Asian high will strengthen too,which may be the reason for the deepening of the ozone valley over the Tibetan Plateau.
In summary,in the period 2001-2099,based on the A1B,A2 and B1 emissions scenarios,total ozone is expected to increase over the Tibetan Plateau,caused by pollutants reduction and a weakening of local Hadley Circulation;the deepening of the ozone valley over the Tibetan Plateau may be controlled by the enhancement of the South Asia high.

Abstract:To date,land surface data assimilation systems have tended to focus on the four-dimensional variational or ensemble Kalman filter assimilation methods using remote sensing data.Considering the advantages of the ensemble square-root filter(EnSRF)over the ensemble Kalman filter,we adopt this assimilation method,using observations without disturbance,in the present study.Following the initial construction of WRF-EnSRF in the WRF model,the WRF-EnSRF land surface data assimilation system was preliminarily constructed,along with a system for different data sources,such as radar,satellites and automatic weather stations(AWSs).Considering the latter of these data sources(i.e.,AWSs),there are many advantages over other sources,such as the dense distribution of sites,real-time recording,the convenience of the observational data as model variables,and so on.
The present work begins by testing the WRF-EnSRF land data assimilation system,and then uses AWS data to complete the WRF-EnSRF land data assimilation.Finally,the validity and feasibility of the system is verified.The EnSRF algorithm used in this paper assumes that when the observation error is not related,assimilate the observational data in an orderly way;namely,assimilate each piece of observational data one-by-one.When a piece of observational data is assimilated,the analysis field will be used as the new background field for assimilating the next piece of data.With time,all observational data are assimilated and the system sets the analysis field as the next period's initial field and then carries out the next period's ensemble forecast.The system then analyzes the next period's observational data,and the process recycles.This study uses the comparatively mature Noah land surface model of the WRF model.This model includes a four-layer soil module and a one-layer vegetation module,and can forecast soil humidity and temperature.Its initial temperature field and humidity field are both from the information provided by the large-scale field after interpolation.
Based on the simulation of the actual example(A Mei-yu front rainstorm),the data of 70 AWSs in Jiangsu Province are assimilated.Using different observational data,this paper discusses what kind of data has the best effect.Furthermore,the paper discusses the accuracy of the analysis field in different areas.The main results can be summarized as follows:
(1)The first test uses different kinds of observational data:10 cm depth soil temperature;20 cm depth soil temperature;and surface temperature.The test uses these data by permutation and combination,with or without initial disturbance intensity,enabling it to identify which kind of data is best for assimilation.The paper reports the root-mean-square error(RMSE)of the variables and pictures the analysis field of each scheme.The data selection test results,comprising the RMSE of the analysis field and the true field,show that when assimilating surface temperature data,and the initial disturbance intensity is 1 K,the assimilation effect is as expected.
(2)To discuss the accuracy of the analysis field in different areas,we choose two areas for comparison:one is a high-precipitation area (32-33°N,119.5-120.5°E),and the other a low-precipitation area (33.5-34.5°N,118.5-119.5°E).Compared to the low-precipitation area,the analysis field of soil temperature and soil humidity in the high-precipitation area is closer to the true field.However,the analysis field of surface temperature in both the high-and low-precipitation area is not ideal.For both areas,the assimilation effect is closer to the real value as soil depth deepens.
(3)After assimilation of surface temperature and 10 cm depth soil temperature data at the same time,we choose the analysis field of the last assimilation time as the background field,and then perform the ensemble forecast.In the end,the forecast result is proven to be effective.So,in conclusion,the result of the WRF-EnSRF land data assimilation system using AWS data applied to a practical case is satisfactory,and the analysis field and ensemble forecast are accurate.The prediction results for the soil temperature field,soil moisture field,surface temperature field and the surface layer wind field all have different degrees of improvement compared with the control test.
Overall,this study shows that the performance of the system,as applied in actual assimilation,is relatively good,and the system can be used in the forecasting of soil humidity and temperature.

Abstract:High-resolution weather forecasting is a growing societal demand.However,the limited spatial resolution of existing models still cannot meet such a demand,so downscaling is widely applied.There are two types of downscaling:dynamical downscaling and statistical downscaling.A large computing cost is required by dynamical downscaling,and statistical downscaling is generally more acceptable because of its relative simplicity and practicability,along with its many flexible methods.More accurate forecast results can be obtained by the statistical downscaling method of establishing the function between the low-resolution raw model output and the high-resolution predicting variables.In addition,rainfall data are discontinuous and follow a non-normal distribution.So,it is important to establish a statistical downscaling model suitable for daily precipitation.
Based on the ensemble forecasts of 1-7-day daily accumulated precipitation from the ECMWF,JMA,NCEP and UKMO in the TIGGE datasets,as well as an hourly merged precipitation product over China as the observed data,a forecasting study on daily precipitation over China by means of statistical downscaling was conducted.Firstly,a spatial sliding window was used to increase moderate and heavy rainfall samples.Then,the statistical downscaling technique was used to improve the precipitation forecast by constructing different regression equations based on different categories of rainfall.
The results show that statistical downscaling is more effective in increasing the anomaly correlation coefficient(ACC) and the equitable threat score(ETS),and decreasing the RMSE,as compared to the bilinear interpolation method,because the observed data are added to the function to correct the statistical downscaling model.The improvement in the forecast through statistical downscaling differs among models,lead times,and rainfall levels,and depends upon the forecasting ability of the particular model.The forecasting ability of heavy rain via the statistical downscaling approach of constructing a single equation is poor-even inferior to the bilinear method.However,the forecast results after the categorized regression are more accurate than those obtained via direct regression,because the former can substantially improve the forecasting ability of different threshold values and the whole area,as reflected in the following aspects:
The ACC of the categorized regression at the 168-h lead time is greater than 0.6-even larger than the ACC of direct regression at the 24-h lead time.In addition,the increasing amplitude of the ACC of the categorized regression method increases with lead time.The RMSE of the precipitation forecast increases with lead time,and the error of the categorized regression method is only 9.5 mm·d^-1 at the 168-h lead time-much smaller than the uncategorized regression method.However,forecast data with a larger ACC do not always yield a smaller RMSE,because the RMSE also depends on the magnitude of rainfall.The ETS of different threshold values of the categorized regression are larger than those produced via direct regression.The increasing amplitude of the ETS when using categorized regression decreases with the magnitude of rainfall.The ETS of less than 10 mm rainfall using categorized regression increases significantly because samples of light rain are ample.
In short,the categorized rainfall regression method is a more reasonable technique for high-resolution weather forecasting.Further correction to categorized-regression downscaling forecasts of precipitation may reduce the occurrence of false alarms considerably.

Abstract:Two numerical simulations whose integration times are 144 h are performed using a linearized non-divergent barotropic vorticity equation model to investigation into the formation process of a wave train induced by the energy dispersion of a complex structure non-isolated vortex.In the initial field a tropical cyclone (TC) vortex and a mesoscale vortex coexist,which forms a complex structure pattern in the first simulation.
The results in the first simulation show that a TC-high-low wave train may be created by the energy dispersion of the complex structure non-isolated vortex.The formation of the wave train was composed of three stages: (1) an asymmetric structure in the east-west direction in the TC area emerged,(2) a high dispersion system occurred,was maintained and strengthened to the east of the TC vortex,and (3) a low dispersion system occurs and then intensifies to the east of the high dispersion system.
In the initial field there is only one tropical cyclone vortex,which forms an isolated circular vortex pattern rather then a complex structure pattern in the second simulation.The results in the second simulation show that a TC-high-low wave train can be identified.Compared with the case of the isolated circular vortex,three differences exhibit in the case of the complex structure vortex.Firstly,the first stage of the wave train formation is significantly shortened.Secondly,the dispersion high is stronger.Thirdly,the dispersion low has a larger spatial scale.
The results have following application prospects.
(1) TC is often located on the southern side of the subtropical high,the dispersion high system occurs on the east side of the TC,while TC moves from the east to the west under the influence of the steering flow.Sometimes the dispersion high can be connected with the subtropical high,which extends to the south,and TC track turns abruptly to the north from the west.In most cases,the subtropical high and the dispersion high is far away from each other,therefore they cannot be connected.The results in this paper show that the dispersion high is stronger in the case of complex structure configuration vortex,it will be in favor of their connection and leads to the unusual track of the TC.
(2) Normally there is less moisture with low probability of a new TC genesis in the dispersion high area,and vice versa.The results in this paper show that in the case of the complex structure vortex the dispersion low system extends to a large area,and the high probability region of a new TC genesis will be enlarged as well.

Abstract:By studying the characteristics of ice pellets,it is possible to understand freezing weather more comprehensively.Such research also contributes to freezing-weather warning and forecasting capabilities.However,due to a lack of observational data,among other concerns and reasons,there has been little relevant research on ice particles in China.Accordingly,in the present study,a comprehensive analysis of the characteristics of the spatiotemporal distribution and duration of ice-pellet precipitation,along with associated ground-level meteorological variables,was conducted using data from hourly or half-hourly surface observations and special observations of Chinese civil airports during the years 2011-2013.By matching the airport ground observations from airports with radiosonde data during the study period,the characteristics of the vertical atmospheric environment were analyzed.
It was found that latitude had a very important influence on the distribution of ice pellets.Ice pellets were mostly distributed in midlatitude areas,including the lower reaches of the Yellow River and the middle and lower reaches of the Yangtze River.There was no substantial correlation between the occurrence and duration of ice pellets.Events may last for a relatively long time where ice-pellet precipitation is rare.Ice-pellet precipitation occurred most often from January to February,and regional differences were found to exist.Ice pellets occurred frequently in January in southern and southwestern regions;and in February in midlatitudes.In the northeast,the peak month for ice pellets was April,while it was March in the north.
The duration of a single ice-pellet event was relatively short-mostly less than 2 hours.In the observation data,the number of single ice-pellet events that lasted less than 2 hours was 196,which was 87.50% of the total;Meanwhile,the number that lasted less than 1 hour was 152,which was 67.86% of the total.In addition,the number of single ice-pellet events that lasted more than 2 hours decreased exponentially:the number lasting more than 4 hours was 9 (less than 5% of the total);the number lasting more than 6 hours was only 2 (less than 2% of the total).
Ice pellets mostly occurred within the surface temperature range of -4 ℃ to 4 ℃.Therein,their occurrence was most common at 0-3 ℃ and within that range,most often at 1 ℃.Ice pellets often occurred at the dew-point temperature within the range of -5 ℃ to 2 ℃and most often at the dew-point temperature of 0 ℃.When the range of the depression of dew point dropped to 0-3 ℃,conditions were highly conducive to the occurrence of ice pellets;and when the depression was 1 ℃ they occurred most frequently.
Ice-pellet precipitation in China is often mixed with mist(45% in total),rain(34% in total),and seldom with snow(only 2% in total).However,freezing rain in China is often mixed with snow (17% of the total).The weather phenomenon of ice pellets in China is significantly different from that in the USA and Canada,in which the proportion of snow(37%) is significantly different.In China,ice-pellet precipitation is mostly caused by the melting mechanism and the warm-rain mechanism.Ice pellets can form if there is only partial melting of snow or ice pellets in the lower weak melting layer,allowing precipitation to eventually fall to the ground in the form of ice pellets.Overall,the melting parameter of ice pellets is less than that for freezing rain,while the freezing parameter of ice pellets is more than that for freezing rain.The temperature decreases,while pressure increases,before the occurrence of ice pellets.The wind speed changes were found to be small throughout ice-pellet events,and accompanied by nearly saturated conditions before and after the event.The evolution of precipitation types during ice-pellet events was found to be variable and complex.

Abstract:In winter 2012/2013,China's average temperature was -3.8 ℃,which was lower than the same period in a normal year by 0.4 ℃.The temperature of Northeast China,North China,Huang Huai,Jiang Huai and northern Xinjiang was lower than in normal years.Using monthly mean temperature data from 160 observation stations for the period 1951-2013,supplied by the National Climate Center,along with global SST data from the UK Hadley Center,NCEP/NCAR reanalysis data,and sea-ice satellite remote sensing data from the University of Bremen,Germany,we employed EOF analysis,regression analysis,composite analysis,and correlation analysis,to study the mid-high latitude atmospheric circulation anomalies in East Asia that resulted in the 2012/2013 winter temperature anomalies in China.The causes of the abnormal circulation were also analyzed,from the perspective of anomalies in the oceanic environment.
The results showed that the winter temperature in China has two modes:the first mode shows the change all over China is warmer or colder,and the second mode shows an adverse change between Northeast China,North China,northern Xinjiang and other areas of China.The 2012/2013 winter temperature anomaly distribution was very similar to the second mode,and the 500 hPa height anomaly field of the Northern Hemisphere in winter 2012/2013 was also similar to that of the second mode.Through regression analysis of the time coefficient of the second mode and 500 hPa height field of East Asia,the high latitudes of the Northern Hemisphere,form the North Atlantic subpolar along the waveguide,from west to east,showed a "+-+-" abnormal distribution of the wave train.The Atlantic area,Urals and Siberia was higher than normal,and the East Asian trough was significantly deeper.
The East Asian winter monsoon index and Pacific Decadal Oscillation(PDO) both showed characteristics of decadal changes,but their phases were opposite.The PDO in positive phase corresponds to a weak winter monsoon index,and vice versa.From 2002,the PDO entered into a negative phase,while the East Asian winter monsoon became stronger.A strong winter monsoon often causes low temperatures,especially in the north of China.Composite analysis showed that when the PDO is in its cold phase,the Aleutian low weakens,the Siberian high enhances,and the East Asian trough deepens in the winter season.The 500 hPa circulation over Easte Asia in winter 2012/2013 was similar to this case.Such a circulation configuration usually leads to cold air behind the trough moving towards the south from Siberia,resulting in a wide range of low temperatures in East China in winter.
Finally,analysis revealed that the Arctic sea-ice extent in early September in the autumn season may have implications for better prediction of late-winter Arctic Oscillation(AO) index.If the early September Arctic sea-ice extent is smaller,high pressure usually controls the high latitudes to the polar regions of the Northern Hemisphere,and the pressure in midlatitude areas is lower than in normal years..This kind of pressure distribution shows a typically negative AO phase.A negative phase of the AO indicates that high pressure is controlling the Arctic area,which is the source of cold air.The cold air of the polar regions is usually squeezed and breaks out to the south,leading to the emergence of cold air and causing low temperatures in the high latitudes of the Northern Hemisphere.In autumn 2012,the Arctic sea-ice extent was smaller than in normal years and the AO remained in its negative phase in late winter.Thus,the winter season in China demonstrated abnormally low temperature characteristics,particularly in Northeast China and northern Xinjiang.

Abstract:In recent years,a wide range of abnormal weather events have been occurring frequently in China,imposing considerable impacts on people's daily lives.For example,the severe winter in South China in 2008 and the strong cold air over North China in 2009.These abnormal events have generated great interest among experts and scholars.A large body of research shows that the evolution of the atmospheric low-frequency oscillation in the weather and climate plays an important role.Building upon this previous research,the present paper attempts to discuss the characteristics and regularity of continuous abnormal events in North China,as well as the relationship with atmospheric low-frequency oscillations.
Based on 1959-2009 NCEP/NCAR daily reanalysis data and daily observed temperature data in China,we begin by defining persistent abnormal low temperature.When the average air temperature is less than or equal to -10 ℃ for five to seven consecutive days or more,with only 1 day of discontinuity permitted,we argue that the region is subject to a persistent abnormal low temperature process.At the same time,the first day of the continuous low temperature process is defined as the start date,and similarly,the end day is the last day of the average temperature being less than -10 ℃.On the basis of this definition,the characteristics of winter persistent abnormal low temperature events in North China are studied.Then,the main relationships between winter persistent abnormal low temperature in North China and atmospheric low-frequency oscillation activities are discussed.
A regular pattern is found insofar as,during 1959-2008,persistent abnormal low temperature processes occurred 26 times in North China,featuring obvious interdecadal variation characteristics.During the 1960s to 1990s,persistent abnormal low temperature events were more frequent than at other times.However,there was a rising trend after 2000.Importantly,persistent abnormal low temperature events were focused in two periods,late December to early January and late January to early February,which could be key for extended-range forecasting.
Previous research has pointed out that atmospheric low-frequency oscillations bear a close relationship with abnormal events,playing an especially important role in periodic,continuous abnormal extreme events and high impact events.It provides the background field for such abnormal events,whilst at the same time,the occurrence of persistent abnormal low temperature events usually takes place through adjustment of the circulation field.By analyzing the processing of persistent abnormal low temperature events,we found that the structure from the upper troposphere to the lower troposphere is consistent,corresponding to the establishment of a ridge of high pressure in the Ural Mountains,followed by its development and demise,and the maintenance,deepening and weakening of the East Asian trough.
Meanwhile,persistent abnormal low temperature events in North China are closely related to the change in the atmospheric low-frequency circulation field.Though a series analysis,we find that both 10-20-day and 30-60-day low-frequency activities influence persistent abnormal low temperature events greatly.When persistent abnormal events happened,a 10-20-day low-frequency cyclone occurs in Northeast and North China,and an interim one in the central Siberian Plateau.Meanwhile,an anticyclone near the western Siberian Plateau and a cyclone near the Sea of Japan are the important 30-60-day low-frequency systems caused by persistent abnormal low temperature events.

Abstract:Synchronous sampling of particulate matter(PM)was conducted in urban and suburban sites in Nanjing to understand the characteristics and sources of PAHs within PM in each season(November 2009,autumn;January 2010,winter;April 2010,spring;July 2010,summer).PAHs associated with fine PM(PM_2.1)and coarse PM(PM_2.1-10)at the different sites and in the different seasons were comprehensively and comparatively analyzed.
The concentrations of PAHs in fine and coarse particles ranged from 19.11 to 131.31 ng·m^-3 and 17.77 to 134.85 ng·m^-3,respectively.Similarities between PAH profiles at the two sites were identified by the coefficient of divergence(CD),which is a self-normalizing parameter used to evaluate the degree of divergence between two sets of data.The CD value of the two sites was 0.13 and 0.14 for fine and coarse particles,respectively,which indicated that PAHs at the two sites displayed similar daily variation.The concentrations and profiles of 16 PAHs from the different sites were nearly the same,all of which meant that PAHs at the two sites had the same sources and pollution processes.The concentrations of PM_2.1-PAHs at the two sites followed the order winter>spring>autumn>summer,while PM_2.1-10-PAHs were ordered autumn>winter>spring>summer.Generally,PAHs in Nanjing were distributed more in fine than coarse particulates,and the mean proportion of PM_2.1/(PM_2.1+PM_2.1-10)was 55%.The proportion values in autumn,winter,spring and summer were 41%、6%、1%、d 50%,respectively.Different from other seasons,PAHs in autumn were more abundant in coarse particulates,which may be attributable to the distinctive source types and unique pollution form of local emissions in this season.Additionally,the proportion of coarse particles in autumn increased with the pollution level,while the proportion of fine particles in spring and winter increased with the pollution level.
The abundant PAH species in fine and coarse particles suggested that the main source of PAHs in Nanjing is vehicular exhaust,and fine particles could be more influenced by vehicular exhaust than coarse particles.Besides,coal/coke sources could influence coarse particles more than fine particles.The combined action of local emissions and regional transport led to the PAHs from different sites being characterized by the same sources and pollution processes.Regional transport of air masses contributed substantially to the PAH concentrations in Nanjing.In autumn,local emissions dominated the abundance of PAHs,and the air masses that influenced coarse particles were more local.The PAHs in summer were influenced by local sources as well as the dilution by clean air from the southwest;the pollution forms for fine and coarse particles were similar.In spring,the polluted air masses from east-northeast to south contributed to the accumulation of PAHs in fine and coarse particles,and the effect on fine particles was more serious than on coarse particles.In winter,the polluted air masses from north-northwest to northeast and local emissions contributed equally to the accumulation of PAHs,and regional transport had a greater impact on fine particles.
Source apportionment by PCA showed that different seasons had different source types.The leading sources of PAHs in Nanjing were vehicle exhaust,followed by coal/coke.The main sources for PM_2.1-PAHs in both spring and winter were vehicle exhaust and coal/coke,while for PM_2.1-10-PAHs in these two seasons another source-wood combustion-was apparent.In summer,there was only one source type-vehicle exhaust-for PM_2.1-PAHs:while for PM_2.1-10-PAHs there were two source types-vehicle exhaust and biomass burning.In autumn,the sources of PM_2.1-PAHs were vehicle exhaust,biomass burning and coal/coke.The primary source for PM_2.1-10-PAHs was a mixed source:biomass burning and coal/coke,while the secondary source was vehicle exhaust,whose contribution rate was smaller than for PM_2.1-PAHs.In particular,biomass burning contributed greatly to the PAHs in autumn,perhaps because of the unique source types and dominance of local emissions in autumn that made the distribution of PAHs in this season different from other seasons.

Abstract:Based on the daily meteorological data of 90 stations for the period 1971 to 2000 and daily 0.25°×0.25° gridded meteorological data under the A1B climate scenario(1951-2070) extracted from the regional climate model RegCM3 released by the National Climate Center,a temperature suitability and coefficient of variation(CV) model for the Huang-Huai-Hai region was built,combing with the growth demand of summer maize for temperature.The spatial and temporal variations of thermal resources,summer maize temperature suitability and its CV in the Huang-Huai-Hai region for the period 1951-2070 were analyzed.The Huang-Huai-Hai area has distinct dry and wet seasons.The heat resources are particularly important for the growth of summer maize.The analysis of this region in this paper,against the background of climate change,is aimed at improving the efficiency of the utilization of climate resources,and providing a scientific basis for summer maize planting.The results showed that:
(1)The accumulated temperature of 10 ℃ with a guaranteed rate of 80% in the Huang-Huai-Hai region showed a gradually increasing trend from north to south,increasing over time.(2)The first day of 10 ℃ with a guaranteed rate of 80% in the Huang-Huai-Hai region showed a gradually increasing trend from north to south,advancing over time.(3)In the stage of seeding to emergence,the temperature suitability showed a trend of rising firstly and then falling,with the CV falling firstly and then rising over time.In the stage of emergence to heading,a falling-rising-falling trend was apparent,with the CV showing a falling-rising-falling-rising trend over time.In the stage of heading to maturity,spatially,the temperature suitability was higher in the south than the north before 2010,but showed a future pattern of being higher in the center than the surroundings.Temporally,it was stable before 2010,but showed a falling followed by rising pattern for the future,which was opposite to the pattern for the CV.(4)The temperature suitability and CV fluctuated in positive phase with time from seeding to maturity.
To date,most research on summer maize suitability has mainly been based on regional climate model data,combined with physiological indexes of existing varieties,which mainly focus on the change in seeding time,growth period,yield,and the effect of crop planting structure by analyzing existing dates.Crucially,there remains a lack of systematic research on the variation of summer maize temperature suitability in the future.Therefore,combining field results with future projections,such as the present work in the Huang-Huai-Hai region,may be the most appropriate research direction moving forwards.This study of the spatiotemporal trends of summer maize temperature suitability and its variation under a future climate scenario in the Huang-Huai-Hai region should help to make full use of climate resources,which may also guide the production of summer maize in the region and provide important information for decision-makers.

Abstract:Meteorological satellites have become an irreplaceable weather and ocean observing tool in China.Recently,much progress has been made in direct assimilation of satellite radiance measurements in numerical weather prediction(NWP).The Microwave Atmospheric Humidity Sounder(MWHS),carried onboard the Chinese new generation of polar-orbiting weather satellites,the Feng-Yun(FY-3) series,provides passive measurements of the radiation emitted from Earth's surface and throughout the atmosphere.MWHS is similar to AMSU-B and the Microwave Humidity Sounder of NOAA,with a primary purpose of moisture sounding in cloudy regions,designed to obtain information on atmospheric humidity profiles,water vapor,rainfall,cloud liquid water,and so on.
Several operational NWP centers currently rely on a variational analysis system to define the initial state for their NWP models.From the point of view of variational assimilation,errors from observations and models should have normal and unbiased distributions.However,statistical errors of radiance between observation and prediction from the NWP model are usually not random but systemic.MWHS is a cross-track scanning microwave radiometer.A feature of a cross-track sounder is that the measurements vary with scan angle because of the change in the optical path length between Earth and the satellite.This feature is called the limb effect.Cross-track scan bias correction is a key part of an NWP assimilation system.In order to use radiances from MWHS,biases between the observed radiances and those simulated from the model first guess must be corrected.The bias of global FY-3A MWHS observed brightness temperature(T_O) and simulated brightness temperature(T_B) by the Community Radiative Transfer Model(CRTM) based on 6 h forecast fields of the NCEP GFS from 28 August to 6 September 2010 are calculated in this study.
The statistical features of observation increment(T_O minus T_B) in channels 3,4 and 5 of MWHS are analyzed.The scan angle bias of channels 3-5 varying along scan position reveal that the scan angle bias generally increases with the scan position far away from the nadir,but does not increase in a strictly progressive manner.Large positive scan biases are present at large scan angles at all latitudes for channels 3 and 4 on both sides of the scan lines.Relatively large negative scan biases for channel 5 are seen at most scan angles and are highly asymmetric on both sides of nadir.The closer to the surface the peak height of the channel weighting functions,the more serious the asymmetry.All of this further verifies the importance of scan angle bias correction.
Analysis of radiance data shows a significant residual scan bias that depends strongly on latitude for these channels.The scheme applies a latitudinally dependent scan correction to take this into account.In this study,the correction coefficients are calculated within every 5° latitudinal band for each scan position.Moreover,nadir biases are subtracted.These biases will be subtracted from T_O minus-values in the formulation of data assimilation.Therefore,a constant scan bias for each channel needs be removed before MWHS radiance assimilation.The statistical distribution of brightness temperature bias(the departures of T_O minus T_B) after correction locates mostly in the vicinity of zero,with a more Gaussian distribution.The bias and standard deviations of T_O minus T_B differences between observations and model simulations are reduced after bias correction.
The scan-angle and latitudinal-dependence of the observation increment for the MWHS channels 3 to 5 within 5° latitudinal bands are given quantitatively.This scan-bias correction coefficient can be used directly for MWHS data assimilation.This work can be extended to the FY-3 MWHS series.The methodology will be incorporated into the Global/Regional Assimilation and Prediction System,operational NWP data assimilation systems in China,or other NWP modeling systems.

Abstract:Owing to a lack of sufficient observational data to provide an accurate initial field in numerical modeling,the numerical prediction of severe convective weather systems is always difficult.With the rapid development of atmospheric detection technology,nonconventional observed data(e.g.,radar data)have been widely applied.Compared with conventional data,radar data-with their higher spatial and temporal resolution-can extract more useful information to improve the model's initial field,improve rainstorm mesoscale weather forecasting,and promote the simulation process capability.
In this paper,the impact of Doppler radar radial velocity on the prediction of a heavy rainfall event is examined.Based on the mesoscale nonhydrostatic Weather Research and Forecasting(WRF)model and its three dimensional variational assimilation system(WRF-3DVAR),a control experiment and three assimilation experiments were conducted for a heavy rainfall process that happened over the Huai-he River basin in July 2007.The model background fields were provided by NCEP data,and the Doppler radar radial velocity data were obtained from Fu-yang station,which houses a new generation of S-band Doppler Weather Radar(Model:CINRAD/SA).Because the effect of the radar data is related to the thinning method,this paper focuses on the influence of different thinning methods of radar data on assimilation results and rainstorm numerical simulations.To this end,a new radar data thinning method is introduced.Firstly,a horizontal polar coordinate plane with certain resolution is constructed;secondly,radar data on the elevation plane are projected onto the polar coordinate plane;then,the distances between the projected points and the polar coordinate plane grid points are calculated;and lastly,the nearest points are regarded as good points and the corresponding radar data are retained.In this method,the degree of radar data thinning depends on the density of the polar coordinate horizontal structured grid.
The numerical results showed:(1)By assimilating the Doppler radar radial velocity data,more sophisticated mesoscale information were retrieved in the initial wind fields,which was helpful in the simulation of the rainstorm process;(2)Through the assimilation of the Doppler weather radar radial velocity data,the circulation structure of the storm could be adjusted and the false precipitation in the control experiment could be reduced.Compared with the control experiment,both the rainfall intensity and the rainfall area in the assimilation experiments were improved greatly.Furthermore,it also made a positive contribution to further prediction of mesoscale heavy rainfall;(3)With more radar radial velocity data introduced into the model initial fields,the initial field and the simulation of precipitation could be improved more accurately.For different thinning methods,the assimilation of radar radial velocity data had different effects on the initial field,which also led to different results in the precipitation forecast.Compared with other tests,in the RV3 test(i.e.,radial polar coordinate grid resolution taken as 10 km),the pattern of precipitation and the storm center were the best.
It is important to note that the findings of this study are based on one heavy rain case;future research and more cases are needed to obtain more and deeper conclusions.

Abstract:K-theory is one of the most extensive turbulent closure revision schemes using weather patterns.However,because it cannot explain the counter-gradient transportation phenomenon,it must be corrected.There are three turbulent closure revision schemes representative of the convective boundary layer(CBL):the first was developed by Deardorff(1972),the second scheme by Holtslag and Moeng(1991),and the third by Liu Feng(2001).Because these schemes are based on different physical assumptions,they present different parameterizations and interpretations of counter-gradient transportation within the CBL.In the present work,using part of the published database obtained from the WL-ARPDD94 Experiment in Xianghe,the three schemes were tested and compared.The results showed that the first scheme systematically underestimates the heat flux within the entire CBL,and is inconsistent with the observations of the Xianghe CBL Experiment.The second scheme can reproduce inverse gradient transportation phenomena in most of the CBL,and can basically depict the vertical distribution of turbulent flux.However,it is not in agreement with observations in the lower and upper CBL.The third scheme's counter-gradient item is related to height,reaching a maximum in the central CBL,while the other two schemes' counter-gradient items remain constant with changes in height.The third scheme's results are not only consistent with the second scheme in most of the CBL,but can also reasonably describe the turbulent flux distribution within the entire CBL.Liu's parameterization exhibits good agreement with observations in the whole CBL.The analysis suggests that Liu's scheme,first used to determine heat flux based on field experiment data,is able to represent the heat flux profile for the CBL.On the basis of reviewing the physical interpretation of counter-gradient transport phenomena by the different closure schemes,a universal scheme for the planetary boundary layer,suitable for numerical weather forecasting models,is urgently needed.

Abstract:Rainstorms are a major category of meteorological disaster,and thus research on their spatiotemporal distributions and trends is important in reducing or even preventing their adverse impacts.In this study,precipitation data gathered from meteorological observation stations over seven counties in Longyan during a 54-year period from 1960 to 2013 were used to study the spatial distribution characteristics of rainstorms.Further analysis was made by dividing the seven counties of Longyan into southern and northern counties.The main analytical methods used were the Mann-Kendall (M-K) method and Morlet wavelet power spectrum analysis [for the change or long-term trends of precipitation,and multi-scale analysis of the temporal (annual,seasonal,monthly) distribution of precipitation,respectively].
The results showed that the annual precipitation duration at seven meteorological observation stations had an increasing tendency during the 54-year time period,but this tendency was not statistically significant.An obvious change-point occurred around 1975,after which the annual precipitation increased by 101.2 mm.Moreover,based on the Morlet wavelet power spectrum analysis,the southern and northern counties had different significant time-scale cycles,as well as variation in the strength of cycle over time.The precipitation amount at the seven observation stations was greatest in spring,accounting for around 38.2% of the annual precipitation,followed by summer and autumn.However,each of the four seasons demonstrated distinct changes,and change ranges,in different years.For example,spring precipitation changed significantly around 1999,according to analysis using the M-K test,decreasing by 7.1% after that year.
Combined with the spatial distribution of rainfall duration,the precipitation over the northern counties was greater than that in the southern counties in spring and winter,less than that over southern counties in autumn,and nearly the same in summer.At the same time,however,neither the northern counties or southern counties showed a significant change in seasonal precipitation under the 95% confidence level.
Through further data analysis,it was found that the monthly precipitation over the seven meteorological observation stations had an increasing trend in the time period from January to June,and a decreasing trend in the time period from August to December.Monthly precipitation was concentrated from March to June (being greatest in June),amounting to 17.3% of the total precipitation in a year.Comparing the monthly precipitation between the northern and southern counties,it was clear that-except for the period from July to September-monthly precipitation in the northern counties was greater than that in the southern counties.