Reanalysis on Hail Suppression Weather Prewarning of the "8.21" Rare Hail in Shenyang

[Objective]The research aimed to analyze hail weather during 18：30-19：30 on August 21,2011.[Method]Based on NCEP 6 h reanalysis data,Micaps data and FY-2 satellite cloud image,weather situation field,meteorological element field and satellite cloud image of the hail during 18：30-19：30 on August 21,2011 were reanalyzed.Weather causes of the hail and characteristics of the satellite cloud image were discussed.We summed up how to conduct prewarning analysis of the hail suppression weather from live weather data and numerical forecast products.[Result]In occurrence and development process of the hail weather,cold vortex at 500 hPa was background weather system.850 hPa warm tongue and ground wind shear were essential conditions for forming strong convective hail cloud.Early weather chart was analyzed.It could analyze occurrence reason of the weather from mechanism aspect of the weather system,and issue weather prewarning as early as possible.Numerical forecast products were used to analyze meteorological element field.It could further analyze and accurately predict probability,time and range of the hail occurrence.Infrared satellite cloud image was more accurate for monitoring strong convective hail cloud,which could intuitively predict occurrence of the hail weather.[Conclusion]The research offered some hail suppression prewarning experiences for the future similar hail weather.

Half-a-century(1971–2020)of glacier shrinkage and climatic variability in the Bhaga basin,western Himalaya

Glacier shrinkage is a globally occurring phenomena.High-resolution change detection based on frequent mapping and monitoring of high-altitude glaciers is necessary to precisely evaluate future water availability and to understand glacier evolution under different climatic scenarios in the Hindukush-Karakoram-Himalayan(HKH)region.This also holds true for the Bhaga basin of the western Himalaya.This study investigates glacier and glacier lake changes in the Bhaga basin,over the last five decades based on satellite imagery including Corona KH4(1971),Landsat 7 Enhanced Thematic Mapper Plus(ETM+;2000),Linear Imaging Self-Scanning Sensor(LISS Ⅳ;2013),and Sentinel 2(2020).Regional temperature and precipitation trends were evaluated from gridded climatic datasets(1900–2020).In the Bhaga basin 306 glaciers(>0.2 km^(2))were mapped with a total area of 360.3±4.0 km^(2),of which 55.7±0.6 km^(2)was covered with debris in 2013.The total glacier covered area decreased by∼8.2±1.5%(0.16±0.03%yr-1)during the entire observation period 1971–2020,with noticeable heterogeneity between tributary watersheds.In the past two decades(2000–2020),the deglaciation rate has increased significantly(0.25%yr-1)compared to the previous decades(1971–2000;0.12%yr-1).Glacier lake area increased by 0.6±0.1 km^(2)(0.012 km^(2)yr-1)between 1971 and 2020.The NCEP/NCAR climatic data reveals an increase of 0.63℃in temperature and a decrease of 6.39 mm in precipitation for the period 1948–2018.In comparison,APHRODITE data shows an increasing trend in temperature of 1.14℃between 1961 and 2015 and decreasing trend in precipitation of 31 mm between 1951 and 2007.Both NCEP/NCAR and APHRODITE data reveal significant temperature increase and precipitation decrease since the 1990s,which have probably augmented ice loss in the Bhaga basin during the early 21st century.

The Response of Geopotential Height Anomalies to El Niño and La Niña Conditions and Their Implications to Seasonal Rainfall Variability over the Horn of Africa

In this study, we unveil atmospheric circulation anomalies associated with the large-scale tropical teleconnections using National Center for Environmental Prediction (NCEP) reanalysis dataset. Composite analyses have been performed to know the impact of large-scale tropical circulations on the Horn of Africa. The composite analysis performed at the geopotential height of 850 Mb and 200 Mb, and precipitation rate (mm/day) during six strong El Niño and La Niña episodes revealed that the large-scale tropical variability induced climate anomalies in space and time. A substantial decrease in upper-level height (200 Mb) has been observed in the study area during El Niño composite years as compared to the La Niña years. During El Niño conditions, the upper-level divergence initiates low-level vertical motion, thereby enhancing convection, however, during La Niña composite years, nearly contrasting situations are noticed in Belg (February to May) season in Ethiopia. However, geopotential height anomalies at 850 Mb are above-normal during the strong El Niño years, suggesting suppressed convection due to vertical shrinking and enhancement of divergence at the lower level. Compared to the Belg (February to May), geopotential anomalies were generally positive during the Kiremt (June to September) season, thereby suppressing the rainfall, particularly in Southern Ethiopia and Northern Part of Kenya. In contrast, an increase in rainfall was observed during the Belg season (February to May).

Statistical Guidance on Seasonal Forecast of Korean Dust Days over South Korea in the Springtime

This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast （below normal, normal, above normal） which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years （1981-2010）. In this study, we used three kinds of monthly data： the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research （NCEP/NCAR） reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.

Reliability Analyses of Anomalies of NCEP/NCAR Reanalyzed Wind Speed and Surface Air Temperature in Climate Change Research in China

By means of varied statistical methods, such as normalized root mean square error （RMSE）, correlation analysis, empirical orthogonal function （EOF） decomposition, etc., the reliability of the varied seasonal anomalies of NCEP/NCAR reanalyzed wind speed and surface air temperature （SAT） data frequently used in the climate change research in China is studied. Results show that RMSEs of meteorological variables are smaller in eastern China than in western China, i.e., the reliability of NCEP/NCAR reanalysis in eastern China is better than that in western China. This could be due to effects of the topography in the reanalysis model and the disposition of ＂dense-in-eastern-and-sparse-in-western＂ of meteorological stations in China. The RMSE of anomalies of reanalyzed wind speeds decreases with increasing height, further confirming the possible impact of topography on reliability of reanalysis. Results of correlation analysis inversely correspond to those of RMSE analysis, i.e., if the RMSE is larger, the correlation between reanalyzed and observed data is worse, and vice versa. It is found from comparing the EOF eigenvectors of anomaly of reanalyzed and observed data that if a meteorological variable has smaller RMSE, the spatial patterns of corresponding EOF eigenvectors of anomaly of reanalyzed and observed data are similar and their time coefficients are significantly correlated, and vice versa. Therefore, the similarity of EOF modes and＂ the consistency of their time coefficients can be used to objectively assess the reliability of the reanalysis. On the whole, the reliability of the reanalyzed wind speed is better in spring, summer, and autumn, but worse in winter; and for the reanalyzed SAT, it is the best in winter and the worst in summer.