Application of AIRS Soundings to Afternoon Convection Forecasting and Nowcasting at Airports

Abstract

In Taiwan, the frequency of afternoon convection increases in summer (July and August), and the peak hour of afternoon convection occurs at 1500–1600 local solar time (LST). Afternoon convection events are forecasted based on the atmospheric stability index, as computed from the 0800 LST radiosonde data. However, the temporal and spatial resolution and forecast precision are not satisfactory. This study used the observation data of Aqua satellite overpass near Taiwan around 1–3 h before the occurrence of afternoon convection. Its advantages are that it improves the prediction accuracy and increases the data coverage area, which means that more airports can use results of this research, especially those without radiosondes. In order to determine the availability of Atmospheric Infrared Sounder (AIRS) in Taiwan, 2010–2016 AIRS and radiosonde-sounding data were used to determine the accuracy of AIRS. This study also used 2017–2018 AIRS data to establish K index (KI) and total precipitable water (TPW) thresholds for the occurrence of afternoon convection of four airports in Taiwan. Finally, the KI and TPW were calculated using the independent AIRS atmospheric sounding (2019–2020) to forecast the occurrence of afternoon convection at each airport. The average predictive accuracy rate of the four airports is 84%. Case studies at Hualien Airport show the average predictive accuracy rate of this study is 81.8%, which is 9.1% higher than that of the traditional sounding forecast (72.7%) during the same period. Research results show that using AIRS data to predict afternoon convection in this study could not only increase data coverage area but also improve the accuracy of the prediction effectively.

Exploring the link between Atmospheric conditions and Acid rain prevalence: a 12-year study at Juanda International Airport, Sidoarjo, Indonesia.

“…The temperature and humidity data were meticulously gathered from different atmospheric layers: 850 hPa, 700 hPa, and 500 hPa, representing the low, middle, and high atmospheric layers respectively. This stratified approach offers a holistic overview of the atmospheric dynamics at different altitudes [12], [13]. Rainwater quality data was sourced from the Air Quality Database (DBKU) of the Meteorology, Climatology, and Geophysics Agency (BMKG).…”

“…These studies unravel the destructive potential of acid rain, which includes the degradation of the mechanical properties of asphalt and the corrosion of stainless steel rebars embedded in concrete both of which are crucial constituents of urban infrastructure. Adding to this, the crucial role of weather forecasting and nowcasting in alleviating the environmental pollution impacts on sectors like aviation is convincingly demonstrated by [5] and [12]. Advanced predictive methodologies, as advocated by these studies, can facilitate the anticipation of severe weather phenomena, including those exacerbated by pollution, thereby enabling efficient planning and response mechanisms.…”

Impact of Lidar Data Assimilation on Simulating Afternoon Thunderstorms near Pingtung Airport, Taiwan: A Case Study

“…Southern Taiwan covers the areas of Chiayi, Tainan, Kaohsiung, and Pingtung from north to south (Figure 1). The study area was located near Pingtung Airport (22.7 • N, 120.5 • E, Figure 1), which has a higher percentage of rainfall associated with ATs than airports in eastern [35] and northern Taiwan [36]. Another reason for choosing this airport was that it is one of the four airports in Taiwan equipped with a Doppler lidar wind profiler.…”

Spatiotemporal Variability of Convective Events in Romania Based on METAR Data

“…The main objective of this study is to evaluate the convective episodes based on METAR and SPECI data collected from 17 Romanian airports from 2012 to 2022. Extensive Although convective events have a great spatiotemporal variability, climatological studies can provide valuable information in respect to their spatial and temporal differences in a particular region, as well as providing trends on various time-scales [34,35]. Based on climatological scientific results, the user can anticipate important changes in local or regional weather, as well as severe weather associated with convection events [29].…”