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    2022,45(2):161-166, DOI: 10.13878/j.cnki.dqkxxb.20211011001
    In recent years, urban climate change has received great attention.This paper synthesizes IPCC AR6 WGI assessment on urbanization influence on extreme weather and climate events in context of global climate change.The new understanding are summarized as follows:Urbanization has exacerbated local warming, thus large cities are facing more severe heat waves;More extreme precipitation events are observed in many urban areas and their downwind direction, resulting in increased surface runoff;Coastal cities are affected by increasing compound flooding related to sea-level rise;Urban pollutant emissions and building structures with unfavorable ventilation have enhanced regional pollution and increased surface ozone concentration.In the future, extreme temperature, extreme precipitation and air pollution are projected to occur more frequently and intensified in cities, thus lead to increased risks of climate change.Considering the rapid progress of China in urbanization, it is necessary to further strengthen observation network, mechanism study and numerical simulation for urban extreme events under global warming, thus to improve our understanding and enhance response capabilities in coping with urban extreme events.
    2022,45(2):167-178, DOI: 10.13878/j.cnki.dqkxxb.20211113002
    This paper studies the relationship between summer sea ice concentration in the Barents Sea from July to August and autumn drought in Southwest China from September to November, and discusses the possible mechanisms.It is found that the correlation coefficient of interannual variation of autumn drought index in Southwest China and summer sea ice concentration in the Barents sea increases significantly to -0.69 (significant at 99% confidence level) during 1998—2019, whereas they are not well correlated during 1979—1997.When summer sea ice concentration in the Barents Sea increases, it is beneficial for autumn drought occurrence in Southwest China, and vice versa.Further results illustrate that, when there is positive summer sea ice concentration anomalies in the Barents Sea during 1998—2019, the anomalies can persist into autumn, leading to negative surface turbulent heat flux anomalies over the Barents Sea.Thus, the atmosphere in the area west of Novaya Zemlya becomes more stable, triggering anomalous descending motion there.It further induces anomalous ascending motion around the Mediterranean via the anomalous meridional circulation.The resultant anomalous divergent wind in the upper troposphere (300 hPa) of the northern Mediterranean triggers a Rossby wave.The wave train propagates eastwards along 55°N and then begins to spread southwards around the Baikal Lake to North and Southwest China, resulting in an anomalous high over Southwest China to East China.The anomalous high is conducive to the reduced precipitation and higher temperature over Southwest China, resulting in drought there.Additionally, compared with that in 1979—1997, the larger interannual variability of summer sea ice concentration in the Barents Sea during 1998—2019 may be an important reason for the strengthened relationship.
    2022,45(2):179-190, DOI: 10.13878/j.cnki.dqkxxb.20210731001
    Visibility is an important physical quantity that reflects the degree of atmospheric transparency, and is closely related to people's daily life and traffic travel.In this study, in order to make the estimation of visibility more flexible and efficient, three visibility estimation models are constructed and improved for different scenarios, and the respective applicability, advantages and disadvantages of the different models are analyzed.First, the visibility estimation is performed based on meteorological station observations, using correlation coefficient matrix and feature importance analysis to filter out the three variables of relative humidity, temperature and horizontal wind speed, and both day and night are considered to build a ternary cubic polynomial fitting model, which improves the overall fitting ability.Second, the deep learning model of visibility performs estimation based on images, and the scale invariant feature change method is used to extract the feature vector of key points of images, as the training of fully connected neural network model.Next, as the training data of the fully connected neural network model, the computational cost is reduced and the stability of the model is improved.Third, the inverse model of visibility estimation based on height highway images, according to the dark channel a priori theory and basic equation of visibility measurement, the atmospheric luminosity and transmittance are calculated, and the visibility of the monocular images is obtained based on the image distance information.The method does not require pre-set target and camera parameters, nor does it require training samples.The three visibility estimation models can be adapted to different scenarios, and can reduce the dependence on observation equipment.
    2022,45(2):191-202, DOI: 10.13878/j.cnki.dqkxxb.20210903001
    Against the background of global warming, summer extreme precipitation in Hunan has increased significantly.Therefore, improving the prediction accuracy of precipitation is of great practical significance for disaster prevention and mitigation in Hunan Province.Using the monthly precipitation data from meteorological stations in Hunan, the climate index sets from the National Climate Center (NCC) and the precipitation data from the hindcast experiments are performed using seasonal prediction models of NCC and NCEP (National Centers for Environmental Prediction).The recursive feature elimination (RFE) method is used to determine the key factors, and two statistical prediction schemes of summer precipitation in Hunan are established by three algorithms:multilayer feedforward neural network (FNN), support vector regression (SVR) and natural gradient boosting (NGBoost).The results show that the prediction model based on machine learning (ML) has superior ability to predict the distribution pattern of summer precipitation in Hunan.The respective average ACC skills of the two statistical schemes with lead times of 1 to 6 months are 0.15 and 0.19, which is a great improvement compared with the dynamic model.The respective average PS scores are 69.3 and 69.2, which are higher than the NCC model.The further analysis indicates that the preceding winter polar and mid-and high-latitude latitude circulation may be the main predictability sources of ML models with lead times of 1 to 3 months.Finally, the prediction skills of models with lead times of 4 to 6 months are likely derived from the precursory signal of sea surface temperature.
    2022,45(2):203-211, DOI: 10.13878/j.cnki.dqkxxb.20220104002
    Taking VGG16 as the benchmark model, integrating batch normalization, global average pooling and joint loss function, this paper proposed a highway fog visibility classification method based on the convolutional neural network.The experimental results show that the average recognition accuracy of the improved neural network model is 83.9%, which has higher accuracy and better convergence than other models.After the model is encapsulated into the business system for operational verification, the average recognition accuracy can reach 84.9%, and the recognition performance in the daytime is better than that at night.A dynamic generation and elimination process of agglomerate fog in Beijing-Shanghai Expressway on April 4, 2019 was monitored by the business system.The agglomerate fog process has the characteristics of fast movement, small range and short survival time.The application of the system can provide technical support for the traffic management department to deal with the intelligent management and control and decision-making scheduling when the fog occurs.
    2022,45(2):212-224, DOI: 10.13878/j.cnki.dqkxxb.20211124002
    The Yangtze River Basin(YZRB) has the highest concentration of precipitation in China.Against the background of climate warming, short-duration heavy rainfall (SDHR) tends to increase.In the main flood season (June, July and August) of 2020, there were several rounds of heavy precipitation in the YZRB, and the basin flood level was lower than only two years since the founding of the People’s Republic of China, namely 1954 and 1998.Based on the hourly precipitation data collected by the National Meteorological Information Center of China Meteorological Administration, this study analyzes the temporal and spatial distributions of SDHR and statistical characteristics of different type short-duration heavy rainfall events (SDHREs) in the upper YZRB (YR-A), middle YZRB (YR-B) and lower YZRB (YR-C).The results show the following:1) Due to the influence of terrain, the frequency and intensity of precipitation in the YZRB mountainous areas increase, while the terrain effect increases the frequency of SDHR in the mountainous areas, thereby enhancing the precipitation amount of SDHR in these areas.In addition, the spatial distribution of precipitation intensity in the YZRB depends on the spatial distribution of precipitation amount of SDHR.2) The diurnal variations of both precipitation amount and frequency of SDHR in the YR-A, YR-B and YR-C areas show a bimodal pattern, and the bimodal time tends to shift from night to day from west to east in the YZRB, which is related to the regional difference of diurnal variation of convective activity.Moreover, the precipitation amount and frequency of SDHR exhibit similar diurnal variations, indicating that the precipitation amount of SDHR mainly originates from the contribution of its precipitation frequency.3) Among the three types of SDHRE, the frequency of the growth type is the highest (~62.6%), followed by the burst type (~26.9%), with that of the continuous type being the lowest (~10.5%).However, the high incidence precipitation amount of the burst-type SDHRE is the smallest (~30 mm), while that of the continuous-type SDHRE is the largest (~90 mm), and the high incidence precipitation amount of the growth-type SDHRE is between the two (40—60 mm).4) The spatial distribution of precipitation amount of different types of SDHREs mainly depends on the spatial distribution of their precipitation frequency.Since the precipitation frequency of the growth-type SDHRE is generally higher than those of the burst-type and continuous-type SDHREs, its precipitation amount is also greater than those of the latter two types.Note that the Dabie Mountain area is a high incidence area of the continuous-type SDHRE, due to its terrain effect, while the burst-type SDHRE is more likely to form high precipitation intensity locally.
    2022,45(2):225-238, DOI: 10.13878/j.cnki.dqkxxb.20200430001
    In order to study the improvements of the numerical weather forecast model with radar data assimilation on precipitation forecast, in this paper, an experiment is performed to simulate the Meiyu Front precipitation event during the period of June 26—28, 2015 in the Jianghuai area.The precipitation features and synoptic situation of the event are described with emphasis on the evolution of mesoscale convective systems which contribute greatly to the rainfall.The WRF mode is applied to perform this simulation.After the control experiment, the 3DVAR radar data assimilation scheme is executed.After 15 h spin-up, the sensitivity experiments for len_scaling and var_scaling of background error covariance matrix are performed respectively.The optimal len_scaling is 0.5, and optimal var_scaling is 0.7.By setting the optimal len, var and assimilation time-step of 30 min and 1 h, experiments of assimilating reflectivity factor, radial velocity individually and simultaneously are implemented.The results from the analyses on the water vapor, dynamic and precipitation fields reveal the following:1) assimilating radar data can effectively improve precipitation forecast, 2) assimilating both radar reflectivity factor and radial velocity yields superior precipitation forecast, and 3) higher frequency of assimilating radar data yields superior precipitation forecast.
    2022,45(2):239-246, DOI: 10.13878/j.cnki.dqkxxb.20200601001
    In this paper, based on the comparison between Mid-Holocene (6 ka BP) experiment and the RCP8.5 experiment performed in CMIP5, the spatial pattern and causes of rainfall evolution in the East Asian summer monsoon region under different warming scenarios are studied.The study results show that there are significant differences in the spatial patterns of rainfall evolution in the East Asian summer monsoon against the two warming backgrounds.During the mid-Holocene warm period dominated by the enhancement of summer orbital radiation, the pattern of rainfall evolution in the East Asian summer monsoon region bore a meridional “tripole” structure.However, the future strong warming dominated by the increase of atmospheric CO2 concentration was dominated by the overall increasing pattern.In addition, the moisture budget decomposition of water vapor shows that the dynamic component of the rainfall change in the East Asian summer monsoon was dominated by the monsoon circulation, which is represented by the meridional “tripole” structure, while its thermodynamic component depends on the atmospheric specific humidity dominated by the temperature, which is represented as a spatial distribution consistent with the temperature change.The change of rainfall in the East Asian summer monsoon region was dominated by the change of dynamic component during the warm period of the Mid-Holocene, but later it was dominated by the change of thermodynamic component under strong warming.
    2022,45(2):247-256, DOI: 10.13878/j.cnki.dqkxxb.20211024001
    To obtain the distribution features of ice particle habits in the precipitation stratiform clouds of northern China, the ice particle image data recorded by the airborne cloud particle imager (OAP-CIP) in three stratiform precipitation events occurring during the 11th Five-Year National Key Technology Research and Development Program “Beijing Cloud Experiment (BCE)” were used to analyze the distribution characteristics of ice particle habits in different precipitation stages, along with temperature and diameter ranges.The following results were obtained:in the early stage of precipitation development, the habit distribution of ice crystal particles in clouds is dominated by graupel and line shape, and their respective occurrence frequencies exceed 20% and 40% with particle size of larger than 500 μm.The occurrence frequency of aggregate in the temperature area of 0 to -4 ℃ ranges between 10% and 20%;however, it is quite low in other temperature intervals, at less than 10%.The key microphysical processes affecting ice particles' growth in the early stage are sublimation and riming.In the mature stage of precipitation, graupel and aggregate particles are the two main particle habits, and the occurrence frequencies of both greater than 25%.The occurrence frequencies of linear particles at the temperature intervals of 0 to -4 ℃ and -4 to -8 ℃ are both between 10% and 20%.The occurrence frequency of hexagonal particles is between 5% and 15%.The occurrence frequency of irregular is greater than 10% at the size of larger than 125 μm, but less than 10% at other diameter size intervals, and decreases with the increase of statistical particle size.The key processes affecting the ice particles’ growth in this stage are riming and coalescence.
    2022,45(2):257-267, DOI: 10.13878/j.cnki.dqkxxb.20210407001
    This study explores the impact of the “topography height dependent horizontal localization scale scheme” in the GRAPES regional ensemble three-dimensional variational hybrid data assimilation system on the forecast performance of typhoons.Taking Typhoons Sudelor (2015) and Dujuan (2015) as examples, an application experiment of ensemble variational hybrid data assimilation system in these typhoons was carried out.Next, the forecast results of the typhoon track, intensity and precipitation caused by the typhoons were compared and analyzed by observing the “topography height dependent horizontal localization scale scheme” and the “non-topography height dependent horizontal localization scale scheme” of the ensemble variational hybrid data assimilation experiment.The results show that the typhoon track under the “topography height dependent horizontal localization scale scheme” is more similar to the actual situation, which can effectively reduce the track error of the typhoon, but the effect of the intensity is not obvious.In addition, compared with the “non-topography height dependent horizontal localization scale scheme, ” the “topography height dependent horizontal localization scale scheme” can reduce the underreporting phenomenon of typhoon precipitation forecast to a certain extent, and improve the TS score of each precipitation level.In general, the “topography height dependent horizontal localization scale scheme” can be used to improve typhoon precipitation forecasting skills and reduce typhoon track errors to a certain extent.
    2022,45(2):268-279, DOI: 10.13878/j.cnki.dqkxxb.20200908018
    The proper initial perturbation structure is the core of constructing ensemble prediction, and the quality of initial perturbation directly affects the quality and overall performance of ensemble forecasting.This study focuses on the uncertainty of the initial value, then analyzes and reveals its spatial physical structure and the spatiotemporal evolution characteristics of the initial disturbance in ensemble prediction.Therefore, this paper provides an objective basis for the rational construction of the initial disturbance in ensemble prediction.In this study, based on the prediction field of the ECMWF, the T639 global ensemble forecast system in China and the GRAPES regional ensemble forecast system, the physical structure and evolution characteristics of wind perturbation in the three ensemble forecasts are revealed by analyzing the initial disturbance component, structure of ensemble spread, and evolution of the perturbation energy.The analysis results show that most of the initial perturbation are located near the main weather systems, and the perturbation has the characteristics of flow-dependence.In addition, the ensemble spread and Total Perturbation Energy present a developing state over forecast hours.Meanwhile, the lower atmosphere is dominated by the Internal Perturbation Energy, while the higher atmosphere is dominated by the Kinetic Perturbation Energy, and the Kinetic Perturbation Energy is dominated in the evolution process.The evolution of the ensemble spread is also closely related to the evolution of the weather situation.This reflects the dependence of the perturbation structure on the flow pattern from another angle.The results confirm that the regional ensemble prediction can reflect more mesoscale and small-scale disturbance information than the global ensemble prediction.The perturbation structure of the ECMWF is more reasonable in the global ensemble prediction system, but the prediction products of T639 is more applicable for China.Compared with the ECMWF, the domestic ensemble prediction system has the drawback of insufficient high-level spread.
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    2014,37(5):642-652, DOI: 10.13878/j.cnki.dqkxxb.20121017006
    [Abstract] (2374) [HTML] (0) [PDF 12.46 M] (14603)
    In this paper,the Weather Research and Forecast Model(WRF) is coupled with Surface-Layer Scheme,Single-Layer Urban Canopy Model and Mingle-Layer Urban Canopy Model respectively to evaluate the simulation effect of various parameterizations on the weather conditions on 1 August 2007 in Nanjing.The best urban parameterization scheme is coupled into WRF to study the impact of land cover change on the Urban Heat Island(UHI) effect in Nanjing.Results show that the Mingle-Layer Urban Canopy Model shows the best simulation effect for surface temperature and 10m wind field.Urbanization makes surface air temperature increase over the region,especially at night and thus intensifies the UHI effect.After urbanization,the wind speed in the downtown area decreases obviously while the Urban Heat Circulation occurs more apparently.There also exists the downstream effect of UHI in Nanjing.
    2011(1):14-27, DOI:
    [Abstract] (2821) [HTML] (0) [PDF 15.30 M] (13662)
    Based on the multiple type observational data,this paper preliminarily analyses the meso scale convective systems(MCSs) and weather background producing an extremely heavy rain along the Mei yu front in Hubei and Anhui provinces during 29—30 June 2009,and investigates the multi scale structure features of the Mei yu frontal rainstorm system.Then the meso scale numerical model WRF with large domain and 9 km horizontal resolution is used to carry out a 3 domain nested fine simulation for the heavy rain process.Morlet wavelet transformation is carried out to do spatial band passing filter for the model outputs,and the meso 〖WTBX〗α, β〖WTB1〗 and 〖WTBX〗γ〖WTB1〗 scale systems are separated out,in such a way that the three dimensional spatial dynamic and thermodynamic characteristics of the meso scale systems with different scales are studied.The results are as follows.The extremely Mei yu frontal heavy rain is directly resulted from several MCSs with different scales,which are of different features on satellite cloud images and radar echoes.On meso 〖WTBX〗α, β〖WTB1〗 and 〖WTBX〗γ〖WTB1〗 scales,the Mei yu frontal heavy rain system has obvious different dynamic and thermodynamic structure features in horizontal and vertical directions.The meso 〖WTBX〗α〖WTB1〗 and 〖WTBX〗β〖WTB1〗 scale systems have obvious vertical circulation,while meso 〖WTBX〗γ〖WTB1〗 scale system has some features of inertial gravity waves and usually develops in meso 〖WTBX〗α〖WTB1〗 and 〖WTBX〗β〖WTB1〗 scale system.Lastly,a physic conceptual model is advanced for the typical Mei yu frontal rainstorm system.
    2019,42(4):631-640, DOI: 10.13878/j.cnki.dqkxxb.20170815015
    [Abstract] (645) [HTML] (0) [PDF 6.93 M] (13631)
    Imperative quality control methods for Doppler radar data,such as ground clutter elimination,range folding elimination and velocity dealiasing,should be adopted before being used for quantitative analyses,due to the serious impacts originating from certain non-meteorological factors.In this study,in order to precisely identify the ground clutter and precipitous echo,an automatic algorithm based on the Support Vector Machine(SVM) is performed,based on the observational CINRAD/SA Doppler weather radar data in the areas of Anqing and Changzhou from June to August,2013,and the results are compared with the recognition effect based on the Artificial Neural Networks(ANNs) method.Statistical learning theory(SLT) is favorable for small samples,which focuses on the statistical law and nature of small-sample learning.As a new machine learning based on SLT,the basic principle of the SVM is to possess an optimal separating hyperplane which is able to satisfy the requirement of the classification accuracy by introducing the largest classification intervals on either side of the hyperplane.In the first step,the dataset used in the experiment will be establised by empirically distinguishing the ground clutter and precipitous points at each bin.Next,several characteristic parameters,which are used to quantify the possibility affected by the ground clutter,such as reflectivity vertical variation (GDBZ),reflectivity horizontal texture (TDBZ),velocity regional average (MDVE),and spectrum regional average (MDSW),will be derived from the reflectivity,radaial velocity,spectrum width and spatial variance information of the ground clutter and precipitous echo.The statistical results of the above characteristic parameters show the following:a large portion of these parameters vary in terms of ground clutter and precipitous echo,which indicates that the seven parameters (GDBZ,TDBZ,SPIN,SIGN,MDVE,MDSW and SDVE) contribute to the identifiable recognition of the ground clutter and precipitous echo.Based on the above conclusions,seven parameters,which are regarded as the trigger (the training factor of SVM) to establish the SVM's training model,can be randomly extracted from the database.Finally,the training model is used to automatically recognize the ground clutter and precipitation using the random data from the database.The recognition effect of the SVM method will be examined by comparing the model output with the empirical identifications,and the examination of the ANNs algorithm is the same as that of the SVM method.The comparison of the recognition effect between the SVM and ANNs methods reveals the following:(1) The statistically identifiable recognition parameter for the sSVM and ANNs methods appears to be steady,despite the fact that the Doppler radar data vary in shape and position between Anqing and Changzhou;(2) An identifying threshold must be determined for the ANNs method before the ground clutter and precipitous echo are identified,which will lead to a differently identifiable accuracy with the unlike threshold;and (3) Overall,the SVM method works better than the ANNs method in terms of radar echo identification.Moreover,the identifiable recognition accuracy of the latter increases significantly with the increasing total number of training samples,while the identifiable recognition accuracy of the former performs at a highly accurate level,which remains relatively stable with the changes in the training samples.In terms of the identification accuracy of the total samples (ground clutter and precipitous echo) and identification accuracy of the ground clutter echo,the SVM method presents better results than the ANNs method.As for the precipitous echo erroneous recognition,the ANNs method performs slightly better than the SVM,but both methods control the erroneous recognition rate at a low level.
    2014,37(2):129-137, DOI:
    [Abstract] (2130) [HTML] (0) [PDF 13.30 M] (12314)
    Wind shear in the atmosphere is a serious threat to the safety of aircraft,especially the low-level wind shear which is an important factor affecting the aircraft taking off and landing.By using the Doppler radar velocity data to calculate the one-dimension tangential,one-dimensional radial and two-dimension composite shear,accurately judging the dangerous area of wind shear could provide timely warning for flight,taking off and landing.In this study,as the wind shear automatic identification product on the principal user processor(PUP) for Doppler radar applications has the shortcomings such as weak edge recognition and larger location errors,according to Doppler radar velocity distributions and taking advantage of least square fitting method,"fitting window" suitable for airborne radar parameters are chosen,and the several cases have been identified and analyzed.For the performance in wind shear's identification,location and edge discerning,the least square method could provide better reference of wind shear and warnings than PUP's identification products.
    2021,44(1):39-49, DOI: 10.13878/j.cnki.dqkxxb.20201113007
    [Abstract] (202) [HTML] (155) [PDF 37.05 M] (8813)
    The Arctic climate,an important component of the global climate system,has moved into a new state over the past 20 years.Scientific questions and possible consequences related to these changes are now front in the midst of many important issues that the world needs to deal with in the future.These changes,including prominent atmospheric and oceanic warming and sea ice melting have been largely attributed to a combined effect of anthropogenic forcing and internal variability of the climate system.This review highlights some findings from a number of studies conducted by my research group in the past few years.The studies collectively suggest that the high latitude atmospheric circulation that is sensitive to tropical SST forcing related to the interdecadal Pacific oscillation (IPO) plays a vital role in driving the interannual and interdecadal variability of Arctic sea ice by affecting the atmospheric temperature,moisture,clouds and radiative fluxes over sea ice.In particular,the teleconnection excited by a SST cooling over the tropical Pacific is suggested to cause an enhanced melting from 2007 to 2012.In addition,it suggests that a similar internal process may also play a role to cause strong sea ice melting in summer 2020.Furthermore,the model evaluation focusing on CMIP5 models finds that most climate models have a limitation to replicate this IPO-related teleconnection,raising awareness on an urgent need to investigate the cause of this bias in models.Thus,this review is meant to offer priorities for future Arctic research so that more efforts are targeted on critical scientific questions raised in this study.
    2015,38(1):27-36, DOI: 10.13878/j.cnki.dqkxxb.20130626001
    [Abstract] (1949) [HTML] (0) [PDF 20.93 M] (8364)
    The high-resolution numerical simulations of Hurricane Bonnie(1998) are used to analyze its intensity and structure changes in relation to its associated inertial stability under the influence of intense vertical wind shear during three different stages of its life cycle.Results show that Bonnie has high asymmetry and experiences an eyewall displacement cycle during its rapid intensifying stage.During its rapid structure change stage,the development of high inertial stability is consistent with the change in hurricane inner core size.The inertially stable region,which is usually present inside the eyewall,provides resistance to radial motions,and plays an important role in reducing the influence of vertical wind shear.The inertially stable region reduces the Rossby radius of deformation,and concentrates the latent heating,which is beneficial to the enhancing of the hurricane.This is an important factor in the development of inner core region of the hurricane.
    2014,37(5):653-664, DOI: 10.13878/j.cnki.dqkxxb.20111230001
    [Abstract] (2088) [HTML] (0) [PDF 33.55 M] (6331)
    Studies have shown that large-scale monsoon gyre activity is closely associated with tropical cyclogenesis over the western North Pacific.In this study,two cases of monsoon gyre activities in 2002 and 2009 were first examined.It was found that a monsoon gyre can be linked to the formation of one or more tropical cyclones,which usually occur near or to the east of the gyre center.Further analysis of the monsoon gyre activity during the period of 2000—2009 indicates that tropical cyclogenesis mainly occurs near or to the east of the gyre center,although the definition of a monsoon gyre depends on its duration and the circulation intensity.It is suggested that the tropical cyclogensis may be associated with the Rossby wave energy dispersion of monsoon gyres.
    2010(6):667-679, DOI:
    [Abstract] (2339) [HTML] (0) [PDF 2.74 M] (6139)
    利用IAEA\WMO\GNIP的降水稳定同位素资料,分析了中国降水稳定同位素的时空分布特征及其影响因素。结果表明,整体来看我国降水稳定同位素有明显的大陆效应和高度效应。各地大气降水线存在地域差异,内陆地区同一站点冬、夏半年也有明显差异,显示出水汽团特性的不同。不同地区降水稳定同位素(δ和过量氘)的季节变化特征明显不同,表明主要水汽来源存在季节性差异。通过对比长序列降水稳定同位素的年际变化与季风和ENSO指数的关系,发现ENSO与降水稳定同位素有显著的正相关,但不一定通过影响降水量来引起降水稳定同位素(stable isotope in precipitation, SIP)的变化。重点分析了我国降水量效应、温度效应的特点,指出沿海和西南等季风区主要受降水量的影响,北方非季风区温度效应起主要作用,交叉地带则两种效应都有影响。
    2011(2):251-256, DOI:
    [Abstract] (2233) [HTML] (0) [PDF 2.67 M] (6040)
    A new atmospheric correction algorithm based on dark object method and the look up table developed from MODTRAN model was introduced for Landsat images in the paper.The infomation of the satellite remote sensing images was used to support the atmospheric correction.The algorithm was applied to the Landsat ETM+imagery and comparisons show that the influence on Landsat imagery caused by molecules,water vapor,ozone,and aerosol particles in the atmosphere was effectively reduced after the correction.The surface reflectivity was more precisely,which is beneficial for remote sensing information extraction and thematic interpretation.
    2015,38(2):184-194, DOI: 10.13878/j.cnki.dqkxxb.20140508002
    [Abstract] (1890) [HTML] (0) [PDF 16.29 M] (5722)
    The observed SST data and CMIP5 data are used to analyze climate state and interdecadal variation of sea surface temperature(SST) over Northwest Pacific(20—60°N,120°E—120°W).Results indicate that the selected 22 models can simulate the climate state perfectly.More importantly,the selected models can simulate the annual and interdecadal variations of SST over Northwest Pacific.Total standard deviation of SST simulted by the models is the largest in Kuroshio extension region.The majority of models have an ability to simulate the first EOF mode of SST.The SST over Northwest Pacific has a significant interdecadal oscillation phenomenon.SSTs simulated by the 13/22 models have obvious interdecadal oscillations.Meanwhile,the simulated deviation of SST climate state has a great effect on the periodic oscillation of SST,especially in Kuroshio extension region.
    2010(6):738-744, DOI:
    [Abstract] (2229) [HTML] (0) [PDF 2.05 M] (5420)
    2010(5):593-599, DOI:
    [Abstract] (2093) [HTML] (0) [PDF 1.04 M] (5330)
    采用中国1951-2006年的气象观测资料,在运用度日分析法分析全国、各省及省会城市近50a的平均温度变化的基础上,系统分析全国的度日变化情况;研究了中国六大区省会城市热度日(Heating Degree day,HDD)和冷度日(Cooling Degree day,CDD)的变化情况;分析了典型城北京、上海、广州CDD的上升趋势和上升率,并求得相关方程。结果表明,北京、上海、广州CDD的长期变化都呈上升趋势,上升率分别为117℃/(10a)、104℃/(10a)、251℃/(10a)。
    2010(6):697-702, DOI:
    [Abstract] (2135) [HTML] (0) [PDF 1.61 M] (5214)
    2010(4):489-495, DOI:
    [Abstract] (2496) [HTML] (0) [PDF 1.91 M] (5106)
    2013(1):37-46, DOI:
    [Abstract] (3256) [HTML] (0) [PDF 4.97 M] (5097)
    Based on the hourly precipitation observed by automatic weather stations(AWS) in China and retrieved from CMORPH(CPC MORPHing technique) satellite data,the merged precipitation product at hourly/0.1°lat/0.1°lon temporal-spatial resolution in China is developed through the two-step merging algorithm of PDF(probability density function) and OI(optimal interpolation).In this paper,the quality of merged precipitation product is assessed from the points of temporal-spatial characteristics of error,accuracy at different precipitation rates and cumulative times,merging effect at three station network densities and monitoring capability of the heavy rainfall.Results indicate that:1)The merged precipitation product effectively uses the advantages of AWS observations and satellite product of CMORPH,so it is more reasonable both at the precipitation amount and spatial distribution;2)The regional mean bias and root-mean-square error of the merged precipitation product are decreased remarkably,and they have a little change with time;3)The relative bias of merged precipitation product is -1.675%,less than 15% and about 30% for the medium(1.0—2.5 mm/h),medium to large(1.0—8.0 mm/h) and heavy rainfall(≥8.0 mm/h),respectively,and the product quality is improved further with the cumulative time increases.The merged precipitation product can capture the precipitation process very well and have a definite advantage in the quantitatively rainfall monitoring.
    2010(4):385-394, DOI:
    [Abstract] (2274) [HTML] (0) [PDF 1.49 M] (5090)


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