Two Types of Diurnal Variations in Heavy Rainfall during July over Korea

This study examined the characteristics of the diurnal variations of heavy rainfall (⩾110 mm in 12 hours) in Korea and the related atmospheric circulation for July from 1980–2020. During the analysis period, two dominant pattens of diurnal variation of the heavy rainfall emerged: all-day heavy rainfall (AD) and morning only heavy rainfall (MO) types. For the AD-type, the heavy rainfall is caused by abundant moisture content in conjunction with active convection in the morning (0000–1200, LST; LST = UTC + 9) and the afternoon hours (1200–2400 LST). These systems are related to the enhanced moisture inflow and upward motion induced by the strengthening of the western North Pacific subtropical high and upper-tropospheric jet. For the MO-type, heavy rainfall occurs mostly in the morning hours; the associated atmospheric patterns are similar to the climatology. We find that the atmospheric pattern related to severe heavy rainfalls in 2020 corresponds to a typical AD-type and resembles the 1991 heavy-rainfall system in its overall synoptic/mesoscale circulations. The present results imply that extremely heavy rainfall episodes in Korea during the 2020 summer may occur again in the future associated with the recurring atmospheric phenomenon related to the heavy rainfall.

Forecasting of Debris Flow Using Machine Learning-Based Adjusted Rainfall Information and RAMMS Model

In recent years, climate change and extreme weather conditions have caused natural disasters of various sizes and forms across the world. The increase in the resulting flood damage and secondary damage has also inflicted massive social and economic harm. Korea is no exception, where debris flows created by typhoons and localized heavy rainfalls have caused human injuries and property damage in the Wumyeonsan Mountain in Seoul, Majeoksan Mountain in Chuncheon, Sinnam in Samcheok, Gokseong in Jeollanam-do, and Anseong in Gyeonggi-do. Disaster damage needs to be minimized by preparing for typhoons and heavy rainfalls that cause debris flow. To that end, we need accurate prediction of rainfall and flooding through simulations based on debris flow models. Most of the previous literature analyzed debris flows using rainfall events in the past before debris flow occurrence, rather than analyzing and predicting based on rainfall predictions. The main body of this study assesses the applicability of hydrological quantitative precipitation forecast (HQPF) generated through a machine learning method named the Random Forest (RF) method to debris flow analysis models. To that end, this study uses scatter plots to compare and analyze the precipitation observation data collected from the areas hit by debris flows in the past, and the quantitative precipitation forecast (QPF) and HQPF data from the Korea Meteorological Administration (KMA). Based on the verified HQPF data, runoff was calculated using the spatial runoff assessment tool (S-RAT) model, and the soil amount was calculated to simulate the debris flow damage with a two-dimensional rapid mass movements (RAMMS) model. The debris flow simulation based on the said data indicated varying degrees of flow depth, impact force, speed, and damage area depending on the precipitation. The correction of the HQPF was verified by measuring and comparing the spatial location accuracy by analyzing the Lee Sallee shape index (LSSI) of the damage areas. The findings confirm the correction of the HQPF based on machine learning and indicate its applicability to debris flow models.

Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin, China

Precipitable Water Vapor (PWV), as an important indicator of atmospheric water vapor, can be derived from Global Navigation Satellite System (GNSS) observations with the advantages of high precision and all-weather capacity. GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in meteorology, particularly for severe weather conditions, for water vapor is not well sampled in the current meteorological observing systems. In this study, an empirical atmospheric weighted mean temperature (Tm) model for Guilin is established using the radiosonde data from 2012 to 2017. Then, the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017. The results show that the new Tm model in Guilin has better performance with the mean bias and Root Mean Square (RMS) of − 0.51 and 2.12 K, respectively, compared with other widely used models. Moreover, the GNSS PWV estimates are validated with the data at Guilin radiosonde station. Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of − 0.9 and 3.53 mm, respectively. Finally, an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed. It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements, and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall. It also reveals the moisture variation in several regions of Guilin during a heavy rainfall, which is significant for the monitoring of rainfalls and weather forecast.

Deciding on Climate Change Adaptation Measures: A Living-Lab-Approach Profiting from VGI in an Interactive Mapping-Service

A great variety of local sectors, e. g. water management, urban planning, agriculture, forestry, regional development, soil protection, nature conservation, and others, is nowadays concerned with deciding on climate change adaptation measures. Sectoral departments perceive that it is necessary to build bridges between different administrational offices due to various dependences and interactions. Increasing heavy rainfalls, for instance, are an often-mentioned threat that is caused by climate change in certain regions. Heavy rainfalls lead to flooding on the one, and soil erosion on the other hand. Flooding, as well as erosion, cause damages for buildings, road networks, and other infrastructures. Both events can also have negative aftermaths for agriculture (loss of arable land) and settlements (landslides, accumulation of mud on roads or in gardens). To mitigate such threats, it is often desirable not to start single, sectoral actions, but to develop measures that take into account comprehensively the different perspectives from relevant sectors.Meanwhile, the BebeR-project, a collaborative network within which all relevant actors participate in the decision-making processes on climate change adaptation measures, was finished as a follow-up of the foregoing project KLIMPASS (https://klimpass.de/). Spatial data and web-map-services played a central supporting role to enable fair collaboration and decision making, as this paper will show.

Impact Assessment of Aeolus Winds on NOAA Global Forecast

<p>Recent efforts have focused on evaluation of the reprocessed Aeolus Level 2B (L2B) wind data with ESA M1 bias correction and its impact on NOAA global forecast. Aeolus wind quality especially the remaining biases vs NOAA global model background is examined. As a result, a revised bias correction taking account of noises in both Aeolus and GFS winds is implemented in the NOAA global data assimilation system to improve Aeolus wind assimilation.  In this study we will present impact from Aeolus wind on NOAA global forecast, focusing on synoptic and mesoscale scale events, e.g., tropical cyclones track and intensity in Eastern Pacific, and heavy rainfalls over the Western Coast of US.</p>

Study of Some Patterns for Severe Rainfalls Over Iraq

Study of rain received particularly great importance in the areas described as semi-arid, which is on the other hand are not well prepared for the drainage of rain that may turned into flash floods. The pressure systems, especially those passing through the country in the winter rainy season and spring also autumn have a role in determining the amount of rainfall falling in the region In addition to climate change and its effects in terms of climate cycles and climate extremes and thus required determine the size of rainfall Whether it is beneficial or harmful. In this study to determine of heavy rainfalls, two important cases of heavy rainfalls were studied in 24, Dec, 2016 and 24, Nov, 2018, which exceeded 50 mm on the Iraq, from one country to another in this account , rainfalls rate, divider from the World Meteorological Organization (WMO) in which the rain intensity is determined according to the schedule and limits (light precipitation I≤2 mm / hour), (moderate precipitation 2<I≤10 mm / Hour), (heavy precipitation 10 <I≤50 mm / hour), (torrential precipitation I> 50 mm / hour). Each case was Analyzed and visualized by using the data analysis and display system (GrADS) The data were obtained from Tropical Rainfall Measuring Mission (TRMM). Show maps results of the first case in (24 December, 2016) in the northeastern region, the central region and the western region of the country the abundant rain condition through maps of rainfall rates on these areas as well as by maps of mean sea level pressure and dense cloud cover, maps showed a decrease the temperature accompanying the low pressure also streamlines, geopotential height, relative vorticity show this. And show the vertical velocity (omega), relative humidity, geopotential height, relative vorticity, and show support of air decline in terms of streamlines, relative humidity, geopotential height and relative vorticity over the country. Maps 700 hPa the vertical velocity (omega), relative humidity, geopotential height and relative vorticity, maps 500 hPa, results of second case, (24 November, 2018) that occurred in the northeastern and eastern part and southeastern part of the country, also appear clear through maps of falling rainfall rates, as well as maps of sea level pressure and the dense cloud cover accompanying the heavy rain situation. maps 850 hPa it shows the low temperature accompanying the atmospheric decline, also streamlines, geopotential height and relative vorticity also maps 700 hPa and 500 hPa lik first case, in differential patterns all of this shows clear support for the atmospheric decline in terms of streamlines, relative humidity, geopotential height, and relative vorticity, and explain the causes of heavy rain situation over Iraq.