Study on Hail Weather Analysis and Forecast in Guilin

[Objective] The hail weather and forecast storm in Guilin were studied. [Method] In allusion to the occurrence of hailstorm in Guilin and considering the observation data of a new generation of Doppler weather radar in Guilin, the weather situation and radar echo characteristics in Guilin was summarized so as to explore the short time forecast method. [Result] There were one or two icy storms every year in Guilin. The occurrence of icy storm was distinctly influenced by terrain. A new generation of Doppler weather radar detection ice storm was very effective. The singular intensity of echo of icy storm in Guilin was above or equal to 50 dBz and the height of echo was above or equal to 10 km. The vertical liquid content was above or equal to 40 kg/m2, accompanied by mild cyclone. When there was strong icy storm, there were three flux characteristics. The forecast of icy storm was mainly short time forecast. [Conclusion] The study offered reference for the forecast of icy storm, artificial storm and disaster prevention and mitigation work.

Analysis of Weather Anomalies to Assess the 2021 Flood Events in Yaounde, Cameroon (Central Africa)

Extreme weather anomalies such as rainfall and its subsequent flood events are governed by complex weather systems and interactions between them. It is important to understand the drivers of such events as it helps prepare for and mitigate or respond to the related impacts. In line with the above statements, quarter-hourly data for the year 2021 recorded in the Yaounde meteorological station were synthesized to come out with daily and dekadal (10-day averaged) anomalies of six climate factors (rainfall, temperature, insolation, relative humidity, dew point and wind speed), in order to assess the occurrences and severity of floods to changing weather patterns in Yaounde. In addition, Precipitation Concentration Index (PCI) was computed to evaluate the distribution and analyse the frequency and intensity of precipitation. Coefficient of variation (CV) was used to estimate the seasonal and annual variation of rainfall patterns, while Mann-Kendall (MK) trend test was performed to detect weather anomalies (12-month period variation) in quarter-hourly rainfall data from January 1st to December 31st 2021. The Standard Precipitation Index (SPI) was also used to quantify the rainfall deficiency of the observed time scale. Results reveal that based on the historical data from 1979 to 2018 in the bimodal rainfall forest zone, maximum and minimum temperature averages recorded in Yaounde in 2021 were mostly above historical average values. Precipitations were rare during dry seasons, with range value of 0 - 13.6 mm for the great dry season and 0 - 21.4 mm for the small dry season. Whereas during small and great rainy seasons, rainfalls were regular with intensity varying between 0 and 50 mm, and between 0 and 90.4 mm, respectively. The MK trend test showed that there was a statistical significant increase in rainfall trend for the month of August at a 5% level of significance, while a significant decreasing trend was observed in July and December. There was a strong irregular rainfall distribution during the months of February, July and December 2021, with a weather being mildly wetted during all the dry seasons and extremely wetted in August. Recorded flooding days within the year of study matched with heavy rainy days including during dry seasons.

Analysis on an Easterly Wave Thunderstorm and Gale Weather during the Latter Flood Season of 2010

[Objective] The research aimed to analyze an easterly wave thunderstorm and gale weather during the latter flood season of 2010.[Method] Based on conventional observation data,data of automatic station,NCEP 1°×1° reanalysis data,Doppler radar reflectivity and radial velocity data,the easterly wave thunderstorm and gale weather process which happened during 4-5 August,2010 was analyzed.The circulation situation,wind field and dynamic & thermal structures of easterly wave,echo characteristics of Doppler radar when thunderstorm and gale happened were studied.[Result] The thunderstorm and gale weather happened in the northeaster zone in front of the deep thick easterly wave trough.When thunderstorm and gale weather happened,position of the subtropical high was by north(ridge line was at 35° N).Eastward movement of the north branch of trough compelled subtropical high splitting into east and west circles.Westward extension of the east subtropical high and saddle-type field circulation were favorable for generation and development of the easterly wave.As development and westward movement of the easterly wave,in the influence zone in front of the trough,upper easterly component transmitted downward.Then,low-level northeaster obviously strengthened,and thunderstorm and gale weather appeared.In the zone where thunderstorm and gale happened,airflow had cyclonic convergence at the middle and low layers and anti-cyclonic divergence near the ground layer.Subsidence movement was obvious.Moreover,thermal force structure that it tended to be dry and cold at the middle and high layers,warm and wet at the low layer existed.Supercell storm was at the developed stage on 4th.It had obvious mesocyclone and hooked echo characteristics(meso-and small-scale characteristics).Characteristics of the squall line,gale region and adverse wind region appeared in central west Guangdong on 5th.Doppler characteristics of the mesocyclone,hooked echo,squall line,gale region and adverse wind region had indication significance for short-imminent forecast of the thunderstorm and gale.[Conclusion] This research revealed some information which had significance for forecasting local easterly wave thunderstorm and gale weather.

Addressing the Challenge of Interpreting Microclimatic Weather Data Collected from Urban Sites

This paper presents some installation and data analysis issues from an ongoing urban air temperature and humidity measurement campaign in Hangzhou and Ningbo, China. The location of the measurement sites, the positioning of the sensors and the harsh conditions in an urban environment can result in missing values and observations that are unrepresentative of the local urban microclimate. Missing data and erroneous values in micro-scale weather time series can produce bias in the data analysis, false correlations and wrong conclusions when deriving the specific local weather patterns. A methodology is presented for the identification of values that could be false and for determining whether these are “noise”. Seven statistical methods were evaluated in their performance for replacing missing and erroneous values in urban weather time series. The two methods that proposed replacement with the mean values from sensors in locations with a Sky View Factor similar to that of the target sensor and the sensors closest to the target’s location performed well for all Day-Night and Cold-Warm days scenarios. However, during night time in warm weather the replacement with the mean values for air temperature of the nearest locations outperformed all other methods. The results give some initial evidence of the distinctive urban microclimate development in time and space under different regional weather forcings.

"Weather" transit is reliable? Using AVL data to explore tram performance in Melbourne,Australia

This paper uses automatic vehicle location （AVL） records to investigate the effect of weather conditions on the travel time reliability of on-road rail transit, through a case study of the Melbourne streetcar （tram） network. The datasets available were an extensive historica; AVL dataset as well as weather observations. The sample size used in the analysis included all trips made over a period of five years （2006-2010 inclusive）, during the morning peak （7 am-9 am） for fifteen randomly selected radial tram routes, all traveling to the Melbourne CBD create a linear model Ordinary least square （OLS） regression analysis was conducted to with tram travel time being the dependent variable. An alternative formulation of the model is also compared. Travel time was regressed on various weather effects including precipitation, air temperature, sea level pressure and wind speed; as well as indicator variables for weekends, public holidays and route numbers to investigate a correlation between weather condition and the on-time performance of the trams. The results indicate that only precipitation and air temperature are significant in their effect on tram travel time. The model demonstrates that on average, an additional millimeter of precipitation during the peak period adversely affects the average travel time during that period by approximately 8 s, that is, rainfall tends to increase the travel time. The effect of air temperature is less intuitive, with the model indicating that trams adhere more closely to schedule when the temperature is different in absolute terms to the mean operating conditions （taken as 15 ℃）.