Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract:Based on the sea surface temperature (SST) data from NOAA in USA, the asymmetric characteristics of interannual relationship between ENSO and Victoria mode (VM;EOF2 of North Pacific SST anomalies in winter (DJF)) were emphatically analyzed.Results show that the correlation between VM and ENSO is weak on the decadal scale, but strong on the interannual scale.VM has significant negative correlation with ENSO in the same year, and has strong positive correlation with ENSO in the following year.However, there is a certain asymmetry in the relationship between the positive/negative VM events and ENSO warm/cold phases on the interannual scale.The relationship between the positive VM events and the SST anomalies in the tropical central and eastern Pacific in the same winter is weak, but El Niño events often occur in the following year.In contrast, the negative VM events are usually accompanied by El Niño events in the same years, but there is no significant relationship between the negative VM events and the SST anomalies in the tropical central and eastern Pacific in the following winter and there are few ENSO events.It can be seen that the positive VM event seems to promote the occurrence and development of El Niño in the next year and can be used as one of the early prediction factors of ENSO, while the negative VM event cannot be used as the early prediction factor of ENSO.

Abstract:Global Positioning System Radio Occultation (GPS RO) measurements are particularly suitable for the study of tropopause characteristics, due to their high measurement accuracy at the tropopause height.In this study, COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) occultation data from 2007 to 2013 were used to calculate the tropopause heights over the Tibetan Plateau according to the WMO (1957) tropospheric height discriminant method, then radiosonde data were used to examine the results.In addition, the height characteristics of the troposphere over the Tibetan Plateau and the distribution of water vapor in the troposphere were analyzed.The results showed that there was a high linear correlation between the tropopause heights detected by the COSMIC occultation data and radiosonde data over the Tibetan Plateau.The correlation coefficient was as high as 0.976, average deviation was 0.448 km, and root mean square error was 0.672 km.Influenced by thermodynamic factors, the tropopause over the Tibet Plateau is highest in summer and lowest in winter and spring.From winter to summer, the position of the tropopause break area gradually moves northward.In spring, winter and autumn, affected by the equatorial heat source, the entropy surface from low to high latitude rises, with the water vapor mixing ratio decreasing gradually in the middle and lower troposphere.In summer, under the effect of the deep convection caused by the heat source and horizontal transport caused by the monsoon, a high value area of water vapor appears over the Qinghai Tibet Plateau.

Abstract:The WRF model was used to simulate a mesoscale convective complex (MCC) weather process in Southwest China in June 2009.Combined with HYSPLIT Lagrangian trajectory analysis, the characteristics and mechanism of troposphere-to-stratosphere transport (TST) dominated by the MCC were discussed.The conclusions are as follows:(1) There are two source regions for particles near the tropopause in the MCC.In a short time (within 6 h), most of them come from the lower troposphere over the southwest region, guided by the low-level southwesterly.With the increase of time (accumulated to more than 12 h), the particles from the middle and upper troposphere over the north region gradually increase, which are guided by the airflow behind the northern upper trough.(2) The 24.2% of particles in the boundary layer below the MCC are transported to the stratosphere, which are also controlled by other two large-scale weather systems around them respectively.Most of the particles that finally enter the stratosphere are transported vertically and quickly into the tropopause by the MCC, and then move westward into the stratosphere under the influence of the peripheral circulation on the south side of the South Asian High.A small parts of the particles that finally enter the stratosphere firstly escape from the MCC, and then are transported to the northeast with the southwest airflow, encounter the mid-latitude frontal system, transport eastward over Japan and also enter the stratosphere through the joint action of slow frontal climb and fast westerly jet.

Abstract:Using the WRF (Weather Research and Forecasting) model and the MWRT (Microwave Radiative Transfer) model, this paper simulated the cloud precipitation process of an ideal convective cell, and studied the influence of graupel spectrum parameters on the brightness temperature of high-frequency microwave radiation of strong convective precipitation cloud.Results show that the changes of graupel spectrum parameters have effects on the mass concentration distribution of ice phase hydrometeors and the high frequency microwave brightness temperature in convective cell cloud.Decreasing (increasing) of graupel density parameter will increase (decrease) the width of graupel spectrum, strengthen (weaken) the collision-coalescence growth efficiency of graupel, increase (decrease) the maximum mass concentration of graupel, and reduce (increase) the maximum mass concentration of ice crystal and snow, finally the minimum brightness temperature decreases (increases).Increasing (decreasing) of graupel shape parameter will increase (decrease) the width of graupel spectrum, increase (decrease) the maximum mass concentration of graupel, and decrease (increase) the maximum mass concentration of ice crystal and snow, finally the minimum brightness temperature decreases (increases) in the simulation area.In addition, the sensitivity of regional minimum brightness temperature to different graupel spectrum parameters or different changes of the same graupel spectrum parameters is different.