Abstract:The South Asian high (SAH) in summer is a strong anticyclone over the Tibetan Plateau and adjacent areas.It is an important component of the Asian summer monsoon.The east-west oscillation of the SAH is an important characteristic and is closely related to the weather situation and climate change of Asia-especially the distribution of drought and flood.It is found that the east-west oscillation of the SAH is not only manifested as the zonal expansion of the area,but also the adjustment of different forms.The climatological mean center position of the SAH is usually located over the Tibetan Plateau,and the SAH has multiple centers in general.The different centers often appear over the Iranian Plateau,the Tibetan Plateau,eastern China,or the western Pacific.The SAH can be classified into different forms according to the number and location of these SAH centers.Identifying the circulation features and maintenance mechanisms of the different forms can help research the mechanism of the east-west oscillation of the SAH.In this paper,based on NCEP-NCAR monthly mean height and wind field reanalysis data from 1948 to 2013,the SAH is classified into several forms according to its center numbers and center location using composite analysis.In addition,the relationship between the circulation characteristics of different SAH forms and the atmospheric circulation in the Northern Hemisphere is discussed.The results obtained are as follows:
(1)The SAH can have between one and five centers,among which having two or three centers constitutes the majority,accounting for 82% of the total samples.Next,is the SAH with a single center,accounting for 14% of the total samples,and the remainder comprises SAHs with four or five centers,accounting only for 3% of the total samples.
(2)The SAH can be classified into different forms according to the number of centers,the meridional position and the circulation features.SAHs with only one center can be classified into Ⅰ1 form and I2 form,accounting for 44% and 56% of the total samples,respectively.SAHs with two centers can be classified into Ⅱ1 form,Ⅱ2 form and Ⅱ3 form,accounting for 66.7%,18.5% and 14.8% of the total samples,respectively.Ⅲ1 form is the only form with three centers considered,accounting for 67% of the total samples.
(3)The center of Ⅰ1 form SAHs is located over the Iranian Plateau,and the center of Ⅰ2 form SAHs is located over the Tibetan Plateau.The two centers of Ⅱ1 form SAHs are located over the Iranian Plateau and Tibetan Plateau,respectively.The centers of Ⅱ2 form SAHs are located over the Iranian Plateau and western Pacific-eastern China,respectively.The two centers of Ⅱ3 form SAHs are located over the Tibetan Plateau and western Pacific-eastern China,respectively.The three centers of Ⅲ1 form SAHs are located over the Iranian Plateau,the Tibetan Plateau and western Pacific-eastern China,respectively.
(4)The geopotential height fields and temperature fields in the upper-middle troposphere feature significant positive anomalies in those areas where the SAH is located,and the maintenance mechanisms of the temperature anomaly fields in different regions are also different.Therefore,the east-west oscillation of the SAH can also be expressed as the conversion of the different forms of the SAH,which is closely related to the temperature in the upper-middle troposphere.Moreover,the conversion of the different forms of the SAH affects the atmospheric circulation and the distribution of precipitation in Asia.

Abstract:Based on NCEP and GODAS monthly reanalysis data for the period 1982-2013,we explored the influence of atmospheric and oceanic processes on the SST anomaly over the equatorial Southeast Indian Ocean during Indian Ocean Dipole(IOD) events using regression analysis,composite analysis and a 2.5-layer dynamic upper-ocean model.Results show that the SST anomaly over the equatorial Southeast Indian Ocean,which plays a key role in the formation and maintenance of IOD events,has an advanced phase in comparison with that of the SST anomaly over the equatorial West Indian Ocean.The intensity of the SST anomaly over the equatorial Southeast Indian Ocean is stronger than that over the equatorial West Indian Ocean during the entire cycle of IOD events.The SST anomaly over the equatorial Southeast Indian Ocean matures in the fall,whereas over the equatorial West Indian Ocean it matures in winter.Strong moisture transport from the Arabian Sea,northeastern Indochina Peninsula,and southwestern Bay of Bengal,to the eastern Bay of Bengal,results in significantly increased rainfall over the eastern Bay of Bengal in early summer.Latent heat release because of the heavy rainfall anomaly over the eastern Bay of Bengal perhaps strengthens the local meridional circulation crossing the equatorial eastern Indian Ocean.The local meridional circulation crossing the equatorial eastern Indian Ocean may contribute to the southerly wind anomalies off the coast of Sumatra.The southerly wind anomalies off the coast of Sumatra may lead to a negative SST anomaly over the equatorial Southeast Indian Ocean through enhanced entrainment and zonal advection.Then,the rapid enhancement of southeast wind anomalies off the coast of Sumatra stimulated by the negative SST anomaly over the equatorial Southeast Indian Ocean and easterly wind anomalies in the central-eastern equatorial Indian Ocean,transport moisture from the equatorial Southeast Indian Ocean to the equatorial West Indian Ocean.This leads to less rainfall over the Bay of Bengal and equatorial Southeast Indian Ocean,and more rainfall over the West Indian Ocean.Westward-propagating warm Rossby waves south of the equator stimulated by anomalous anticyclones could lead to a warming SST anomaly over the Southwest Indian Ocean.Therefore,the southeast wind anomalies off the coast of Sumatra,because of the heavy rainfall anomaly over the eastern Bay of Bengal,through the local meridional circulation crossing the equatorial eastern Indian Ocean,leads to a negative SST anomaly over the equatorial Southeast Indian Ocean and contributes to the birth of an IOD event.

Abstract:The North Pacific Oscillation(NPO) is one of the most prominent large-scale patterns of atmospheric low-frequency variability in the northern extratropics.It plays an important role in modulating atmospheric circulation and climate over the East Asian region.Based on the ERA-Interim sea level pressure data,along with the observed precipitation data of 160 stations in China provided by the National Climate Center,spanning from January 1979 to December 2013,the interannual variation of the winter monthly(December,January and February) NPO and its association with simultaneous precipitation in China and atmospheric circulation over East Asia are investigated in this paper through use of correlation analysis,linear regression analysis and Morlet wavelet analysis.
The results show that the monthly NPO has a significant interannual variation in wintertime.The index of the monthly NPO has a 2-4 yr period.Importantly,however,the correlations among the interannual variation of the winter monthly NPO indices are weak.During 1979-2012,the correlation coefficients between the NPO index in December and that in January is 0.09,while between January and February it is only -0.003,without passing the reliability test at the 95% confidence level.
Additionally,it is shown that the interannual variation of the NPO impacts evidently upon the precipitation anomalies over East China.Significant positive correlation is found between the interannual variations of the NPO and the precipitation over the Huanghuai River valleys in December and January.However,the interannual variation of the NPO in February relates negatively to the precipitation over North China in February.The precipitation over the Huanghuai River valleys increases by about 50%(40%) compared with its climatology as the NPO index increases by one standard deviation in January(December).Meanwhile,when the NPO index increases by one standard deviation in February,the precipitation over North China decreases by about 30%.
Furthermore,the monthly NPO is closely associated with anomalous East Asian atmospheric circulation,which leads to anomalous precipitation over East China.When the NPO index is positive in December and January,the simultaneous sea level pressure and 500 hPa geopotential height anomalies are positive over East Asia.As a result,the precipitation over the Huanghuai River valleys increases in December and January.When the NPO index is negative in December and January,the simultaneous sea level pressure and 500 hPa geopotential height anomalies are negative over East Asia.Accordingly,the precipitation over the Huanghuai River valleys decreases in December and January.When the NPO index is positive in February,the sea level pressure anomalies are positive over northwestern China and Inner Mongolia and the 500 hPa geopotential height anomalies are negative over northeastern China,which leads to a decrease in precipitation over North China in February.Lastly,when the NPO index is negative in February,the sea level pressure anomalies are negative over northwestern China and Inner Mongolia and the 500 hPa geopotential height anomalies are positive over northeastern China,resulting in increased precipitation over North China in February.

Abstract:Using the daily data of NCEP/DOE Reanalysis II and the temperature data established by conventional observation stations of the National Meteorological Information Center,cold waves during the extreme event of regional averaged temperature in China in the winter of 2011/2012 and the characteristics of the low-frequency oscillation(LFO) of the mean temperature of 828 stations were analyzed.Then,the evolution of the low-frequency temperature field with phases was also analyzed,as well as the impact of the spatial configuration of the low-frequency circulation system in the mid-troposphere in the extratropical Northern Hemisphere on temperature changes by using the SVD method.The results showed that:
(1)The increased cumulated frequency of the cold waves and the declining-temperature periods from November 2011 to February 2012,accompanied by the wide temperature reduction,led to the extreme event of regional averaged temperature in China and an abnormally low temperature anomaly in North and Southeast China in the winter of 2011/2012.
(2)Cold-temperature anomalies were the result of overlapping of the strong 10-30-day oscillation of temperature,based on the seasonal temperature change trend.Low-frequency temperature in the western Tibetan Plateau and Yellow River basin and middle and lower reaches of the Yangtze River and the region to its south changed coherently,and two centers of strong oscillation were separately located in the Hetao area in the north and in southern China in the south.Whereas,the eastern Tibetan Plateau showed the opposite,with a decrease(increase) of the low-frequency temperature in Northeast Inner Mongolia and Northeast China lagging behind the large area.As for northwest north,the LFO of temperature was mostly consistent with both of the two former.
(3)The results of coupling spatial patterns and their temporal variations of the low-frequency height field at 500 hPa and the low-frequency temperature field of 2 days later by using the SVD diagnosis method indicated that,when the low-frequency high between the Urals and Lake Baikal was enhanced,and the low-frequency wave train in mid-low latitudes was coupled with that in the mid-high latitudes,these circulation systems led to strong cold air spells south along the easterly path.Furthermore,they caused the eastern area from the west of Inner Mongolia to southern China to undergo cold waves and declining temperature in winter's eve and in mid to late winter,with the two centers of severe declining temperature separately located in the east of the Hetao area in the north and in southern China in the south.However,the eastern Tibetan Plateau showed the opposite,with the low-frequency wave train along Kara-east of the Urals-Northwest China being the low-frequency circulation system that led to strong cold air spells in the south,which then dispersed along the westerly and northerly path before sequentially impacting Northwest and Northeast China during the cold waves in the latter half of winter.

Abstract:A comprehensive set of aircraft-based aerial observations of the physical structure of a low trough cold front stratiform cloud was organized on 25 September 2012 in Shanxi Province.Combined with satellite and other data,the main results were as follows:
The system was a mixed system with no interlayer.The cloud physical structure was uniform and stable.Rainfall was obvious on the ground.The detection area was mainly ahead of the trough at 500 hPa and 700 hPa,and behind the cold front on the ground.The height of the cloud top was 10-13 km.The temperature of the cloud top is -40 to -50℃.The height of the 0℃ layer was 4 000 m.
The cloud physical parameters obtained from satellite and radar changed little along with space and time.In cold cloud region,there is hardly any supercooled water,but mainly ice-phase particles,which grow lager by condensation process.The spectrum of cloud droplet probe(in short,CDP,range from 2-50 μm) detection showed a exponential distribution.The spectrum of cloud image probe(in short,CIP,range from 25-1 550 μm) detection showed a bimodal distribution.The spectrum of precipitation image probe(in short,PIP,range from 100-6 200 μm) detection showed a trimodal distribution.The particle spectrum type and concentration was uniform in different positions at the same height in the cold zone.The distribution of the microphysical parameters was uniform in the cold zone.Ice particles fell into the 0℃ layer and began to melt,and then the particle phase state shifted.The spectral width of CIP and PIP turned narrow in the warm zone,and their spectrum type turned unimodal.PIP was concentrated under 2 000 μm.The CDP spectrum was unimodal near 0℃.The concentration of CDP and CIP was largest near the 0℃ layer,and another high concentration area of these parameters occurred around the height of 1 500 m.The max concentration of PIP appeared at 6 300 m,The concentration is fewer,while the effective diameter is bigger with the reduced height,which is caused by cloud physical processes,such as coagulation.The phenomenon is consistent with the vertical radar echo structure.Calculating the radar echo on the aircraft flight path revealed that CIP and PIP were larger than their measured values.The vertical growth rate of the radar echo values from high to low was approximately 5 dBz·km^-1.
Based on the analysis,the microphysical structure of the cloud system was uniform and stable,and lacked supercooled water.In this kind of cloud,the potential for precipitation enhancement is small;rainfall on the ground is mainly caused by ice particles.This paper provides some evidence for the seeding index during precipitation enhancement operation.However,this is just a case study,and more statistics analysis should be supplement in the future.Additionally,the design of the flight path needs further consideration.

Abstract:The hierarchical ensemble filter(HEF) and sampling error correction(SEC) localization methods can minimize sampling error without giving definition of physical distance.To examine the advantages of the two methods and the possibility of applying them to storm-scale assimilation,experiments involving assimilating radar data are conducted using the ensemble Kalman filter(EnKF).Compared with the Gaspari-Cohn(GC) experiment,the influence of the localization methods on the assimilation effect is investigated.Results show that the analysis reflectivity coverage of all the experiments is smaller than the true reflectivity.The analysis reflectivity of the HEF experiment is bigger than that of the GC experiment in both the horizontal and vertical directions.The analysis error of most model variables decreases with time and becomes lower after analysis.This indicates that radar data assimilation can help to improve the quality of the forecast field.The RMSE of the HEF experiment is the smallest and the analysis error of the SEC experiment is smaller than the GC experiment.Compared with the GC experiment,the analysis error of the U,V and W of the HEF experiment decreases more sharply than the microphysical variables,including QR(cloud-water mixing ratio),QC(rainwater mixing ratio),QI(ice mixing ratio),QS(snow mixing ratio) and QG(graupel mixing ratio).For U,V and W,the analysis error decreases by 25% and,for microphysical variables,it decreases by 17%.The spread of the HEF experiment is largest and the spread of the SEC experiment is larger than that of the GC experiment.Compared with the GC experiment,the spread of the U,V and W of the HEF experiment increases by 45%,while that of the microphysical variables increases by 42%.In the convective region,the temperature is colder than the environment,which is called the cold pool.This is caused by the evaporation of the rainwater in the convective system.The strength and coverage of the cold pool of the GC experiment are stronger than the true field,while the HEF and SEC experiments are weaker and their areas are smaller.From 60 km to 120 km in the south-north direction,and from 0 km to 12 km in the vertical direction,the areas of vertical wind and Graupel mixing ratio are bigger,while their values are larger.So,they are closer to the wind and Graupel mixing ratio of the true field,respectively.Through simulation of the analysis fields,it is found that the northern branch of the convective system of the HEF experiment is stronger than that of the SEC and GC experiments,especially at 80 km in the south-north direction.The true field and HEF forecast result can reach about 50 dBz,which corresponds well with the assimilation results.The southern branch of the convective system of the SEC experiment is stronger than that of the HEF and GC experiments.The SEC experiment can simulate the new convective cell at(40 km,60 km).The cold pool of the HEF experiment is coldest,reaching as low as 299 K.Both the HEF and SEC experiments can simulate the center of the graupel mixing ratio.These results prove that the HEF and SEC localization methods can improve the performance of the EnKF based on GC localization method.The SEC localization method is inferior to the HEF method,but it can reduce the computational expense of the HEF method and its effect is better than the GC method.So,it could be a good choice when the NWP model is complicated.

Abstract:Five sets of regional ensemble forecasts with lead times of 36 h over two months from 24 June 2008 to 24 August 2008 from the Beijing 2008 Olympics Research and Development Project(B08RDP) are evaluated and analyzed.This is firstly done by means of standard probabilistic verification scores,including root-mean-square error(RMSE),ensemble spread,talagrand diagrams,reliability,and ROC(Relative Operating Characteristic) curves.Then,to improve the forecast quality,a combined decaying averaging bias correction scheme(BC) is applied to the ensemble forecasts of B08RDP to reduce the bias in the ensemble mean and to adjust the improper spread of ensembles with sufficient performance evaluation.The BC scheme is designed based on the original Kalman filter.It contains the first moment bias correction,mainly for correcting the bias in the ensemble mean to improve the reliability of the ensemble forecasts,and the second moment bias correction mainly for adjusting the ensemble spread to make the ensemble forecasts fully representative of the uncertainties in the observations.Lastly,the BC scheme's capacity is evaluated and discussed by means of the verification scores mentioned above.Temperatures at 850 hPa are corrected and verified in this study,wherein ECMWF reanalysis data are used as the reference for the verification.
The results show that,among the five sets of regional ensemble forecasts in B08RDP,the regional ensemble forecasts from NCEP possess the best forecast quality,with minimal bias,the most appropriate spread,and the best performance in terms of reliability,resolution and talagrand distributions.Meanwhile,the regional ensemble forecast from CAMS demonstrates the worst forecast quality,due to its largest forecast bias.On the whole,a relatively small spread is a common problem for several of the ensemble forecasts,except those from NCEP.In general,the combined bias correction scheme is proven to be efficient in reducing the RMSE of the ensemble mean,and in generating a more appropriate ensemble spread,for the five sets of ensemble forecasts,revealing its ability to improve the quality of ensemble forecasts,especially for ensemble forecasts of an already low quality.

Abstract:In order to promote the application of ATOVS microwave humidity sounder(MHS) radiance data in the Global/Regional Assimilation and Prediction System(GRAPES),this paper focuses on the bias correction problems of NOAA polar orbiting satellite MHS radiances and establishes a suitable bias correction system for the MHS data.The bias correction scheme used in this paper is the method of Harris and Kelly(2001) and considers the characteristics of MHS radiances.The bias correction contains scan bias and air-mass bias.Considering the features of water vapor,three schemes are designed for air-mass bias correction.The first scheme sets 1 000-300 hPa thickness and 200-50 hPa thickness as predictors;the second scheme sets 1 000-300 hPa thickness,200-50 hPa thickness,and the model first-guess total column water vapor as predictors;and the third scheme sets 1 000-300 hPa thickness,200-50 hPa thickness,the model first-guess total column water vapor,and the model first-guess surface skin temperature as predictors.After a number of experiments and statistical data analysis,the following results are found:Scan biases of MHS channels have different characteristics with latitude-dependent properties.The residual error fits the normalized distribution with zero mean after bias correction.The residual error after correction is reduced and stable over time.All of the three schemes have an obvious bias correction effect,with the effect of scheme 3 being the best.The first-guess total column water vapor has a positive effect on the bias correction of MHS radiance data.As a consequence,combining the four predictors of 1 000-300 hPa thickness,200-50 hPa thickness,the model first-guess total column water vapor,and the model first-guess surface skin temperature,is recommended in studies of the air-mass bias correction of microwave humidity radiance.This work lays a foundation for the assimilation and application of MHS radiance data.

Abstract:Considerable differences in the influence of urbanization on climate change are found owing to the different methods employed to classify urban and rural observation stations.In this study,based on DMSP/OLS(Defense Meteorological Satellite program/Operational Linescan System) night light data,MODIS land cover data and population data,three different methods are used to distinguish between urban and rural observation station,from which we try to identify a reliable method of classification and study the effects of the three methods in terms of the uncertainty in urbanization impact assessment.Specifically,we analyze the urban heat island effect on changes in maximum temperature,minimum temperature and average temperature over different regions and 12 city groups in China for the period 1961-2004.The data used in this paper are air temperature data,provided by the National Meteorological Information Center of China,based on approximately 740 stations.The results show that the different classification methods yield considerable differences in the urban heat island effect,and with different regional characteristics.The uncertainties of the urban heat island effect over the southeast,southwest and northeast are mainly characterized by the absolute numerical quantities,whereas over the northwest it is characterized by the change trend.The urban heat island effect has a more significant influence on minimum temperature warming than maximum temperature and average temperature.There is a significant contribution of the urban heat island effect over the southeast,whereas the effect over the northwest is relatively weak.There is no influence of the urban heat island effect over the northeast and southwest.The urban heat island effect on the seasonal variation in temperature shows large differences between the north and south of China.Specifically,it is more significant in spring and autumn over South China,but in winter and spring over North China.Meanwhile,the results of the 12 city groups in China are similar to these characteristics.Temperature changes over most of the city groups are contributed to greatly by the urban heat island effect,especially in terms of the regional and seasonal effect.The urban heat island effect on minimum temperature is strongest,and the effect is more obvious over Southeast China;the value of the urban heat island effect on minimum temperature is 0.089 1℃·(10 yr)^-1 and the contribution rate of warming is 34.11%.Meanwhile,the urban heat island effect on maximum temperature is weakest.Although the urban heat island effect is not obvious for some of the city groups,the influence is significant in terms of the seasonal change.Taking the Chengdu-Chongqing region in spring as an example,the urban heat island effect on maximum temperature can reach 0.036 4℃·(10 yr)^-1,and the effect on the seasonal change in maximum temperature is more significant than on minimum and average temperature.

Abstract:Accurate wind speed forecasts ensure the timely dispatch of power,thereby improving the economic effectiveness of wind power.The traditional methods of wind speed prediction focus on statistical models,but these are unable to satisfy requirements in terms of precision and time.Numerical models have become more prevalent in wind speed forecasting in recent years.Accordingly,in order to investigate simulation accuracy,error characteristics and time effectiveness for wind speed simulation of a numerical model over a complex underlying surface,one-month long wind speeds at the heights of 10 m,30 m,50 m and 70 m on a wind farm in Liuao (coastal area) and Jiucaiping (mountain area) are respectively simulated using the WRF model.The main results and discussion points are as follows:
(1)The comparison of simulated and observed wind speeds at different heights indicates that the WRF model performs well in simulating the wind speed over a complex underlying surface,the simulated wind speed trends are in good agreement with the observations in both coastal and mountain areas,and the synoptic-scale variations are also well reflected in the simulation.However,the fluctuation caused by the local circulation and turbulence is hard to capture in the wind speed simulation.Besides,statistical assessments using correlation coefficients,relative error,root-mean-square error(RMSE) and index of agreement show that the accuracy of wind speed simulation does not enhance with increased height in coastal areas,but improves significantly in mountain areas.
(2)The error characteristics between simulations and observations are different in coastal and mountain areas.Compared with the real landforms,the small island in coastal areas does not appear in the model's static terrestrial data.As a result,the frictional effect of the underlying island is neglected in the simulation,and the average simulated wind speeds are overestimated in coastal areas.Nevertheless,the elevation of the wind tower in mountain areas decreases in the static terrestrial data due to the weakening of the actual mountain slope,and thus the average simulated wind speeds are underestimated in mountain areas.
(3)The normalized RMSE of wind speeds is analyzed in different directions.The normalized RMSE increases significantly due to the relatively complex underlying surface in the case of land breezes,and decreases due to the homogeneous underlying surface in the case of sea breezes in coastal areas.Conversely,the normalized RMSE distribution is not obvious in mountain areas.The obvious error distribution characteristics provide a direction for further error correction of wind speed forecasting on wind farms in coastal areas.
(4)To forecast the wind speed on a scale of a few hundred kilometers surrounding the wind farm,parallel computation of the WRF model using a server with 12-core processors is sufficient to meet the time effectiveness of 48-h short-term forecasts.However,only increasing the grid resolution is not necessary to improve the accuracy of the simulation.Therefore,in the practical application of wind speed forecasting on a wind farm,it is important to set an appropriate grid resolution for the balance between simulation accuracy and time effectiveness.More accurate terrestrial data should be introduced to improve the precision.

Abstract:The net radiation at the top of the atmosphere(TOA) is one of the most important driving forces of the Earth's climate system,while the radiation budget of the climate system directly influences atmospheric and oceanic motion,as well as the atmospheric water cycle.In this paper,the performance of the regional climate model RegCM4 in simulating the radiation budget over eastern China is evaluated.A long-term simulation at a grid spacing of 25 km driven by ERA-Interim data for the period 1990-2010 is conducted.The East Asia domain of phase II of the international COordinated Regional climate Downscaling EXperiment(CORDEX) is used as the model domain.The simulation is compared with a satellite dataset and reanalysis over eastern China during 2001-10 in terms of surface net shortwave(SNS),surface net longwave(SNL),TOA net shortwave(TNS),and TOA net longwave(TNL) radiation.Results show that biases in shortwave fluxes are larger in summer,and biases in longwave fluxes are larger in winter.However,spatial distributions of the biases in summer and winter are similar.For surface fluxes,biases of SNS are positive(overestimation of net downward shortwave flux),with a regional average of nearly 50 W/m²,which is the maximum among these radiation flux biases.Biases of SNL are negative(overestimation of net upward longwave flux).For TOA fluxes,biases of TNS are negative in the north but positive in the south,and biases of TNL are overall positive.Attribution analysis on the biases in radiation fluxes is conducted by two methods-spatial correlation and linear regression.The biases in the cloud fraction,surface albedo,and surface temperature are considered.We find that biases in the radiation fluxes can be explained,to a large degree,by significant negative biases in cloud fraction.

Abstract:As the average global temperature increases,it is generally expected that the air near the surface should be drier,which should result in an increase in the rate of evaporation from terrestrial open water bodies.However,despite the observed increases in average temperature,observations from many regions show that the rate of evaporation from open pans of water has been steadily decreasing over the past 60 years.It is important to understand why pan evaporation has decreased despite the increases in average temperature in order to make more robust predictions about future changes in the hydrological cycle.One of the explanations is that the decrease in evaporation is caused by large and widespread decreases in sunlight resulting from increasing cloud coverage and aerosol concentration.Previous work demonstrated that,in non-humid environments,measured pan evaporation is not a good measure of potential evaporation(I_ETp);moreover,in many situations,decreasing pan evaporation actually provides a strong indication of increasing terrestrial actual evaporation(I_ETa).The key issue in research on the hydrological cycle is how to estimate I_ETa.As we know,it is difficult to obtain a sufficient volume of reliable instrumental I_ETa measurements,so scientists have made use of a range of theoretical,especially climatological,methods for this purpose.There are two main theories to estimate I_ETa from I_ETp.At the regional scale,the Penman hypothesis is a common approach to reducing I_ETp to I_ETa in response to the water stress,which is given by a function of soil water availability.This is often questioned by the Bouchet complementary relationship theory,in that the Penman hypothesis does not consider the complex surface-atmosphere interactions at the catchment scale.The discrepancy between the Penman and Bouchet hypotheses is especially highlighted in non-humid regions.
In this paper,we select the Pearl River basin of southern China as the study area,and the relationship between I_ETa and I_ETp is analyzed in depth.Firstly,the actual evapotranspiration(I_ETa) and potential evapotranspiration(I_ETp) are calculated,respectively based on the water balance model and the Penman formula,in seven sub-basins of the Pearl River Basin from 1961 to 2000.The relationship between I_ETa and I_ETp under the change in water supply conditions is quantified and compared among the seven sub-basins.The results show that:
(1)The annual I_ETa is much lower than the I_ETp,and the mean annual I_ETa values are less than 1/2 of the I_ETp in most of the sub-basins.The area-weighted average I_ETa of the seven sub-basins is 681.4 mm yr^-1,and the I_ETp is 1 560.8 mm yr^-1.The variability of the I_ETa is more significant than the variability of the I_ETp.
(2)I_ETa in five sub-basins(Dongjiang,Xijiang,Beijiang,Liujiang and Panjiang) is positively correlated with the precipitation(P),but in the other two sub-basins (Hanjiang River and Yujiang),the correlations between I_ETa and P are not so obvious.The I_ETp of all sub-basins shows a significant negative correlation with P.Given the condition of increasing P,the annual mean I_ETa of the seven sub-basins shows an obvious increasing trend,while the I_ETp presents a clear downward trend.
(3)A joint regression equation(P-I_ET) between I_ET(containing I_ETa and I_ETp) and precipitation is constructed for every sub-basin,and t-tests of all the regression coefficients are used to determine if the relationship between P and I_ETa or I_ETp belongs to the Bouchet complementary relationship theory or the Penman proportional hypothesis theory.The results confirm the applicability of the former theory in all of the seven sub-basins except Yujiang.In Hanjiang,Liujiang and Panjiang,the relationship between I_ETa and I_ETp fits the complementary relationship theory completely.Furthermore,in three sub-basins(Dongjiang,Xijiang and Beijiang),the relationship between I_ETa and I_ETp belongs to the "asymmetry complementary relationship".
(4)A number of previous studies generally lend support to the I_ETa formula based on the completely symmetric complementary relationship theory,but not the "asymmetry complementary relationship" theory.A schematic diagram of the "asymmetric complementary relationship" between I_ETa and I_ETp is given in the present paper.Based on strict logical inference,and at the same time considering the boundary conditions of extreme drought and extreme wet conditions,this paper gives the I_ETa model under the "asymmetry complementary relationship".

Abstract:In China,the Southwest Vortex(a special type of mesoscale convective system) is second only to that caused by tropical cyclones when it comes to the severity of heavy precipitation.During 11-12 July 2013,heavy rainfall(referred to as the "7.18 rainfall" hereafter) occurred over Sichuan Province in China,resulting in catastrophic flooding.Based on rain gauge data-including conventional meteorological observations and those of automatic weather stations-provided by the Meteorological Information Center of the China Meteorological Administration,and NCEP FNL(Final) Operational Global Analysis data with a horizontal resolution of 1°×1° and prepared operationally every six hours,synoptic diagnostic methods and mesoscale numerical modeling were used to study the 7.18 heavy rainfall with the Weather Research and Forecasting(WRF) model.Numerical experiments were performed to (1)test the capability of WRF in simulating nighttime precipitation over complex terrain,such as that of Sichuan Province;(2)examine the characteristics of the Southwest Vortex;and (3)elucidate the cause of the 7.18 heavy rainfall with respect to the large-scale precipitation conditions.The main results can be summarized as follows:
(1)The 7.18 heavy rainfall was influenced by a typical mesoscale vortex,and the period of the largest amount of precipitation was 0100-0200 Beijing standard time(BST) 18 July 2013.Accompanying the development and disappearance of the mesoscale vortex at 500 hPa,the intensity of precipitation gradually changed from strong to weak and,finally,stable,meaning the 7.18 heavy rainfall possessed obvious characteristics of nighttime rainfall.
(2)The main weather systems of influence were a westerly trough at 500 hPa(nearby at 0000 UTC) and a mesoscale vortex at 700 hPa over Sichuan Province.Meanwhile,meridionally,the western Pacific subtropical high(WPSH) extended towards the west and formed a typical "western trough-eastern high" pattern;and under the obstruction of the stable WPSH,the westerly trough at 500 hPa developed a low pressure vortex,before weakening gradually and ultimately disappearing.Sichuan Province suffered long-duration precipitation during 11-12 July 2013 because there was a westerly trough at 500 hPa and a mesoscale vortex at 700 hPa stagnated over Sichuan Province for a long period under the blocking of the WPSH.The typical "western trough-eastern high" pattern allowed warm and wet flow to arrive from the ocean to the south,and dry and cold flow from the north,which converged over Sichuan Province.In addition,Sichuan Province was influenced by strong atmospheric upward motion,and these conditions led to the occurrence of the 7.18 heavy rainfall.
(3)The low vortex at 700 hPa had a baroclinic feature similar to that of a frontal zone,and was under the influence of unusually steep potential pseudo-equivalent temperature(θ_se),meaning slantwise and unstable vorticity could develop gradually.As the stronger and higher value positive vorticity center would have been beneficial to the formation of small and mesoscale vortexes,the formation and development of such vortexes could have provided favorable dynamic conditions for the heavy rainfall.
(4)The simulation results from the WRF model showed that WRF was able to simulate the location of the rain belt near Ziyang well,but the location of the rain belt near Guangyuan was shifted to the north and east.Moreover,the intensity of the simulated precipitation was greater than observed.Regarding the temporal evolution of precipitation occurrence,the simulation results of WRF were better for nighttime than daytime,indicating that WRF needs to be further improved for simulating daytime precipitation over complex terrain like that of Sichuan Province.

Abstract:Natural disasters result from the complex relationships and interactions of the vulnerability of disaster-bearing bodies with the disaster-causing factors.The nature of natural disaster risk is described by the probability distribution which is associated with the magnitude and duration of the natural disaster.Evaluating a risk involves establishing a scientifically robust method to estimate the probability magnitude of a natural disaster risk.The mathematical theory of natural disaster risk assessment is essentially equivalent to an issue of probability and statistics,which can be described by the method of probability.The usual sample size required in probability-based statistical analyses is at least 30.However,in disaster risk assessment,especially when small areas are adopted as the evaluation unit,the data collection period is often short and statistics are incomplete.Therefore,it is difficult to reflect the variation in the risk of a disaster over certain study areas and big bias of computed results from observation often happen if we use traditional statistical methods to assess risk.
Drought is one of the most serious meteorological disaster and often causes considerable socioeconomic losses in the affected region.The Sichuan basin China is a very important agricultural production area.Researching and assessing the risk of agricultural drought in this region is helpful in making service decisions and carries huge social significance.However,risk assessment work on agricultural drought in the Sichuan basin has been minimal,and mainly focused at the city prefecture level.Agricultural disaster area is related to the disaster strength and scale,thus,the assessment of agricultural drought risk can be accomplished via a method‘disaster loss evaluation’.
Based on agricultural drought disaster data in Sichuan basin during 1984-2007 and information diffusion theory,the probability of agricultural drought,and its spatial distribution,are discussed under different risk levels.Accordingly,the risk of agricultural drought disaster in the Sichuan basin is separated(spatially) into a few of zones.Results show that the normal information diffusion method can provide a good fit for the agricultural drought disaster rate which is a proportion of the disaster area to the cultivated one.Further investigation shows that the difference in risk between Chongqing and Meishan,where the agricultural drought disaster rate is greater than or equal to 10% and 40%,respectively,increasing from the end of the 20th century to the beginning of the 21st century.An exceeding probability means an accumulated probability when the drought disaster rate is larger than a threshold,which is defined as 5% and 40% in this study,respectively.Cities such as Bazhong,Zhongjiang and Luxian are found to be high-risk regions.Low-risk regions are located in the western Sichuan basin,owing to its abundant precipitation.The research provides some useful decision-making information for those involved in disaster reduction and emergency management.
This study shows that small samples of disaster data can be applied in natural disaster risk assessment by using the information diffusion method.The accuracy and completeness of assessment data is probably the most crucial aspect in evaluating results.Due to the disaster data record being subjective and the sown area of the crop not completely matching the data in time,the result is not completely satisfactory.The method is a time-independent disaster risk assessment method that can be used to carry out statistical analysis of the disaster risk for a region where disaster events have occurred,and can also provide an indication of the natural disaster risk level of the region.Further research is necessary to help us make effective forecasts of long-term drought risk in the future.