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Characteristics of wet potential vortex in two rainstorms at the eastern foothills of Helan Mountains Yong WANG,Yuying CHEN,Ting LI,Yang SU Journal of Meteorology and Environment    2023, 39 (6): 1-9.   DOI: 10.3969/j.issn.1673-503X.2023.06.001 Abstract （147）   HTML （22）    PDF （5326KB）（216）       Knowledge map    Based on hourly precipitation data from 512 automatic meteorological observation stations at the eastern foothills of Helan Mountains in Ningxia province, the ERA5 reanalysis data, and conventional meteorological detection data, the moist potential vortex characteristics of the two extreme rainstorm events occurred on July 22, 2018, and August 11, 2020, in this region were compared and analyzed.The occurrence and development mechanism of the two rainstorm events were explored.The results show that the two extreme rainstorm processes occur under the circulation situation of "high in the east and low in the west".The southerly flow on the west side of the western Pacific Subtropical High, the configuration of high and low air jets, and the typhoon provide favorable water vapor and dynamic conditions for the heavy rainfall processes.In the lower troposphere of 700~850 hPa, 3 ~ 6 h before the rainstorm, there is a dense isocontourt zone with the transition between the negative center of the positive pressure term of the moist potential vortex (MPV1) and the positive and negative center of the moist potential vortex baroclinic term (MPV2), and its movement development and duration correspond well to the occurrence and development of the rainstorm, which can indicate the rainstorm forecast.In the lower troposphere, the position where MPV1 negative region and MPV2 positive region are superposed is an area prone to heavy rainfall, and the stronger and longer the intensity and duration of MPV1 and MPV2 are, the stronger the precipitation will be.When MPV1 and MPV2 approach zero, the atmospheric stratification will be stable and the rainfall process will gradually end. Table and Figures | Reference | Related Articles | Metrics

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Diagnosis and analysis of the extreme blizzard in Liaoning province from 6 to 9, November, 2021 Tingting ZHAO,Xin MENG,Lingfeng GAO,Zewen ZHOU,Hailong LIU,Jing GAO Journal of Meteorology and Environment    2023, 39 (6): 10-17.   DOI: 10.3969/j.issn.1673-503X.2023.06.002 Abstract （143）   HTML （14）    PDF （4023KB）（248）       Knowledge map    Using the conventional meteorological observational data and 1°×1° reanalysis data from the NCEP (National Centers for Environmental Prediction), the weather situation and physical quantity diagnosis and analysis of the extreme blizzard process in Liaoning province from 6 to 9, November, 2021 were carried out.The results show that the extreme blizzard process is mainly affected by the Northeast cold vortex and strong cyclone, the maximum snowfall is 80.8 mm, and the maximum snow depth measured at 20 stations exceeds 30 cm.The main cause of extreme blizzard is the long duration of strong water vapor transport and water vapor convergence, with the maximum values of 18 g·hPa-1·s-1·cm-1 and -7×10-5 g·hPa-1·cm-2·s-1, respectively.The strong ascending motion produced by abnormally strong convergence at the low level and divergence at the high level, with a central value of -3.0 Pa·s-1, is indicative of an extreme blizzard forecast.The baroclinic forcing and strong horizontal frontogenesis at 850 hPa are important mechanisms for the occurrence and development of this extreme snowfall event.The configuration of the moist potential vortex, with MPV1>0 and MPV2 < 0 indicates that the increase of cyclonic vorticity and symmetric instability provides favorable conditions for the occurrence of the blizzard process. Table and Figures | Reference | Related Articles | Metrics

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Analysis of the characteristics and causes of explosive intensification of a persistent heavy fog event over Guanzhong Plain, Shaanxi in January 2019 Mian LIANG,Liujie PAN,Bei JIA,Wenlian YAN,Tianshu WANG,Xingxing GAO,Peirong LI Journal of Meteorology and Environment    2023, 39 (6): 18-27.   DOI: 10.3969/j.issn.1673-503X.2023.06.003 Abstract （105）   HTML （6）    PDF （4923KB）（111）       Knowledge map    Using 5 min dense observations from automatic meteorological stations, second-level sounding data, wind profile radar data, and ERA5 hourly reanalysis data from the European Centre, the circulation pattern, evolution characteristics, and causes of explosive intensification of a persistent heavy fog event in Guanzhong Plain, Shaanxi from January 10 to 12, 2019 were analyzed.The Results show that this heavy fog event has the characteristics of high intensity, long duration, and explosive enhancement in multiple locations.The highly humid environment after the rain provides favorable water vapor conditions for this heavy fog event.The stable and persisting strong inversion layer causes large amounts of moisture to accumulate near the surface and is difficult to diffuse, which provides favorable stratification conditions for the explosive intensification and persistence of this heavy fog.The convergence of the wind field formed by the special terrain of Guanzhong Plain makes the water vapor fully condense, which is conducive to the development of heavy fog.Triggering factors such as the sudden change of wind direction and the return of cold air near the surface, may have caused the short-term explosive intensification of heavy fog in multiple locations.The preemptive jump of the static stability index before the fog outbreak and the near-surface easterly backflow below 925 hPa under the static and stable weather background can be used as a reference index for the fog outbreak enhancement in this region. Table and Figures | Reference | Related Articles | Metrics

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Comparative analysis of heavy rain forecast in Sichuan province from two numerical models based on the object recognition method Jiajin WANG,Binyan WANG,Dixiang XIAO,Ke-ji LONG Journal of Meteorology and Environment    2023, 39 (6): 44-50.   DOI: 10.3969/j.issn.1673-503X.2023.06.006 Abstract （62）   HTML （3）    PDF （2235KB）（141）       Knowledge map    According to the deviation test of 31 heavy rain process forecasts in Sichuan province in 2021, 3 forecasting cases predicted by the ECMWF (European Centre for Medium-Range Weather Forecasts) model and the CMA-MESO (China Meteorological Administration Mesoscale Model) model were selected for comparisons.For these three cases, the rain bands predicted by the ECMWF model were westerly biased, and those produced by the CMA-MESO were better.Based on the object-oriented verification method, the characteristics and main reasons for the bias of the two models in the heavy precipitation falling area (≥25 mm) were compared from four aspects: location deviation, area deviation, rain band trend, and precipitation intensity.The results show that the falling region of the precipitation forecasted by the ECMWF model biases westward and northward, and the westward deviation distance (59.06~123.67 km) is significantly larger than the northerly deviation distance (8.23~53.59 km), while that forecasted by the CMA-MESO model is closer to the forecast.The precipitation areas forecasted by the ECMWF and CMA-MESO models both exceed the actual areas with the ECMWF model being over 7.0%~34.3% and CMA-MESO model being over 25.2%~45.9%, respectively.The deviation between the average precipitation forecast and the actual precipitation is -3.5%~20.0%, but the extreme precipitation forecast is larger than the actual precipitation deviation, with a deviation range of 50.1%~196.9%.The test analysis shows that the CMA-MESO model can provide a correction reference for the heavy rainfall process in Sichuan province, which occurs at the edge of subtropical high and is affected by the plateau vortex or the southwest vortex when the ECMWF model forecasts the heavy rainfall area (≥25 mm) to the west. Table and Figures | Reference | Related Articles | Metrics

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Simulation and projection of climate change in Central China based on CMIP6 multi-model ensemble Miao WANG,Pengcheng QIN,Chenxu SHE,Xiaofang ZHAO,Mingwei YANG Journal of Meteorology and Environment    2023, 39 (6): 51-60.   DOI: 10.3969/j.issn.1673-503X.2023.06.007 Abstract （88）   HTML （10）    PDF （3857KB）（154）       Knowledge map    Utilizing daily meteorological observation data from Central China from 1961-2014, along with downscaled and bias-corrected data from 12 CMIP6 models from 1961-2100, this study assesses the spatial and temporal distributions of temperature and precipitation simulations of the CMIP6 models for the region, using the selected temperatures from six models and the precipitation data from four models. Based on the ensemble mean of the selected model results, the change trends in temperature and precipitation for Central China during different periods from 2021 to 2100 under three future scenarios i.e. SSP1-2.6, SSP2-4.5, and SSP5-8.5 were analyzed. The results indicate that the ensemble mean provides better interannual variability in temperature simulations than those of precipitation, while the spatial simulation of precipitation is better than that of temperature. Under all three scenarios, both regional temperature and precipitation show increasing trends, with temperature rise rates of 0.13 ℃/decade, 0.30 ℃/decade, and 0.62 ℃/decade, and precipitation rise rates of 16.2 mm/decade, 12.3 mm/decade, and 19.3 mm/decade, respectively. For the future period from 2021 to 2100 under the three scenarios, precipitation in Central China is projected to decrease in the south and to increase in the north. Near-term and mid-term temperatures are expected to decrease in the west and to increase in the central and eastern parts, while the long-term trend indicates that temperature increases across the region and only decreases in the western mountainous area of Hubei. Table and Figures | Reference | Related Articles | Metrics

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Analysis of the applicability of CLDAS wind field data in Liaoning province in 2020 Weihua LIU,Wei JIN,Huipin WANG,Chunxiang SHI,Shulin QU,Guojing HAN,Miao YU Journal of Meteorology and Environment    2023, 39 (6): 61-68.   DOI: 10.3969/j.issn.1673-503X.2023.06.008 Abstract （57）   HTML （6）    PDF （1788KB）（63）       Knowledge map    Using the 10 m wind field data from 286 meteorological stations in Liaoning province in 2020 and the 10 m wind field data from the Land Data Assimilation System (CLDAS) of the China Meteorological Administration, the correlation coefficient (COR), mean bias (ME), root mean square error (RMSE) and mean absolute error (MAE) between the hourly wind speed data from CLDAS interpolated to the stations and the observed wind speed data at the stations were calculated to analyze and evaluate the applicability of the CLDAS wind field data in Liaoning province. The results show that the CLDAS gridded data with a 1 km resolution is closer to the observed data than those with a 5 km resolution, and the biases of the nearest neighbor interpolation method are smaller than those of the bilinear interpolation method. For the 286 stations in Liaoning province, the hourly CLDAS wind field data has a correlation coefficient below 0.95 with the observed data for only 1.7% of the total stations. The biases between the CLDAS and the observed wind speeds are larger in the coastal low-lying areas and northern Liaoning than in other inland areas. The mean biases between the CLDAS and the observed wind speeds are negative. Among the seasons, the mean bias is smallest in autumn, followed by summer and winter, and largest in spring. For the diurnal variation, the biases are smallest at night in summer and autumn, followed by winter, and largest in spring. During the daytime, the bias is smallest in winter, followed by summer and autumn, and largest in spring. Case studies of 3 strong wind events in Liaoning province all indicate that the CLDAS wind field data has good applicability. Table and Figures | Reference | Related Articles | Metrics

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Projected changes of extreme precipitation in Liaohe River Basin at global warming levels of 1.5 ℃ and 2.0 ℃ Xue AO,Qingfei ZHAI,Chunyu ZHAO,Yan CUI,Shujiang GENG,Yiqiu YU,Xiaoyu ZHOU,Jingwei LI Journal of Meteorology and Environment    2023, 39 (6): 69-79.   DOI: 10.3969/j.issn.1673-503X.2023.06.009 Abstract （49）   HTML （1）    PDF （4246KB）（84）       Knowledge map    Based on the estimated data of the Sixth Coupled Model Intercomparison Project (CMIP6) conducted by the median resolution model BCC-CSM2-MR from the National Climate Center, methods including bilinear interpolation, trend analysis, anomaly analysis, etc. are used to analyze the changes of extreme precipitation over the Liaohe River Basin under the global warming of 1.5 ℃ and 2.0 ℃. The results show that the anomalous percentage increase of the annual average precipitation over the Liaohe River Basin at the global warming of 1.5 ℃ rises with the increase of emission scenarios, reaching 5.82% under the SSP5-8.5 emission scenario. Under the global warming of 2.0 ℃, the annual and seasonal precipitations over the Liaohe River Basin all show increasing trends, especially for summer precipitation; under the SSP2-4.5 and SSP5-8.5 scenarios, the precipitation decreases from southwest to northeast, with a remarkable increase of over 15% in western Liaoning. Under different emission scenarios, the extreme precipitation indices over the Liaohe River Basin all show increasing trends, with significant growths in daily precipitation intensity, the number of heavy precipitation days, and the proportion of heavy precipitation. With the increase of emission scenarios, the growth rate of extreme precipitation indices rises and is two times more than under the SSP5-8.5 scenario compared to that under the SSP2-4.5 scenario. Under the SSP5-8.5 scenario, the precipitation intensity, the number of heavy precipitation days, the proportion of heavy precipitation, the threshold of heavy precipitation, the maximum number of consecutive wet days, and the maximum 10-day precipitation amount will reach 11.66 mm/d, 15.15 d, 59.08%, 32.94 mm, 9.69 d, 201.29 mm by the end of 21st century, increased by 5.58 mm/d, 5.15 d, 37.08%, 10.15 mm, 5.55 d, 102.86 mm compared to those in the baseline period. Under the global warming of 2.0 ℃, the increases of six extreme precipitation indices are more significant than those under 1.5 ℃ warming, and the extreme precipitation over the Liaohe River Basin shows a consistent increasing trend under the SSP3-7.0 and SSP5-8.5 scenarios. Table and Figures | Reference | Related Articles | Metrics

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Study on the relationship between the number of strong cold air days and the interannual variation of sea surface temperature anomalies from 1961 to 2019 in Beijing-Tianjin-Hebei region of China Guohong ZHANG,Xiaoqiong WANG,Yalin ZHANG Journal of Meteorology and Environment    2023, 39 (6): 80-86.   DOI: 10.3969/j.issn.1673-503X.2023.06.010 Abstract （70）   HTML （5）    PDF （3482KB）（130）       Knowledge map    Utilizing meteorological observatory data of daily minimum temperature from 1961 to 2019 in Beijing-Tianjin-Hebei region of China, along with NOAA′s monthly sea surface temperature and NCEP/NCAR′s monthly 500 hPa geopotential height field, this study employs physical statistical methods to analyze the variation characteristics of the number of strong cold air days during winter in the region and its relation to sea surface temperatures. This study also explains the mechanism behind the Pacific North American (PNA) teleconnection pattern influenced by sea temperatures in the Niño 3.4 region. The results indicate that the average annual number of strong cold air days in Beijing-Tianjin-Hebei region varies between 0.0 to 8.7 days, with a spatial distribution decreasing from northwest to southeast. Interannually, the number of strong cold air days during winter in Beijing-Tianjin-Hebei significantly correlating with the preceding summer, autumn, and concurrent winter sea temperatures are mainly in the central and eastern equatorial Pacific. Significant negative correlation areas in the westerly jet region and northeastern North Atlantic appear in the preceding autumn and concurrent winter. A pronounced positive correlation with the equatorial Indian Ocean is maintained concurrently. Anomalies in the winter strong cold air days in Beijing-Tianjin-Hebei region are influenced by variations of 500 hPa geopotential height field features such as the Ural Mountain high-pressure ridge, Baikal Lake low-pressure, the anomalous high-pressure over mid-low latitudes of East Asia, and the East Asian trough. Concurrently, sea temperature anomalies in the Niño 3.4 region affect the variation of height field through the PNA teleconnection pattern, indirectly influencing the number of strong cold air days in the region. Table and Figures | Reference | Related Articles | Metrics