Evaluation of the CMORPH high-resolution precipitation product for hydrological applications over South Korea

2021 ◽  
pp. 105650
Author(s):  
Jungho Kim ◽  
Heechan Han
2020 ◽  
Vol 102 (sp1) ◽  
Author(s):  
Dong-Lim Choi ◽  
Dong-Hyeok Shin ◽  
Jae-Youll Jin ◽  
Yong-Kuk Lee ◽  
Byung-Cheol Kum

2019 ◽  
Vol 34 (5) ◽  
pp. 1277-1293 ◽  
Author(s):  
Hwan-Jin Song ◽  
Byunghwan Lim ◽  
Sangwon Joo

Abstract Heavy rainfall events account for most socioeconomic damages caused by natural disasters in South Korea. However, the microphysical understanding of heavy rain is still lacking, leading to uncertainties in quantitative rainfall prediction. This study is aimed at evaluating rainfall forecasts in the Local Data Assimilation and Prediction System (LDAPS), a high-resolution configuration of the Unified Model over the Korean Peninsula. The rainfall of LDAPS forecasts was evaluated with observations based on two types of heavy rain events classified from K-means clustering for the relationship between surface rainfall intensity and cloud-top height. LDAPS forecasts were characterized by more heavy rain cases with high cloud-top heights (cold-type heavy rain) in contrast to observations showing frequent moderate-intensity rain systems with relatively lower cloud-top heights (warm-type heavy rain) over South Korea. The observed cold-type and warm-type events accounted for 32.7% and 67.3% of total rainfall, whereas LDAPS forecasts accounted for 65.3% and 34.7%, respectively. This indicates severe overestimation and underestimation of total rainfall for the cold-type and warm-type forecast events, respectively. The overestimation of cold-type heavy rainfall was mainly due to its frequent occurrence, whereas the underestimation of warm-type heavy rainfall was affected by both its low occurrence and weak intensity. The rainfall forecast skill for the warm-type events was much lower than for the cold-type events, due to the lower rainfall intensity and smaller rain area of the warm-type. Therefore, cloud parameterizations for warm-type heavy rain should be improved to enhance rainfall forecasts over the Korean Peninsula.


2006 ◽  
Vol 7 (1) ◽  
pp. 61-80 ◽  
Author(s):  
B. Decharme ◽  
H. Douville ◽  
A. Boone ◽  
F. Habets ◽  
J. Noilhan

Abstract This study focuses on the influence of an exponential profile of saturated hydraulic conductivity, ksat, with soil depth on the water budget simulated by the Interaction Soil Biosphere Atmosphere (ISBA) land surface model over the French Rhône River basin. With this exponential profile, the saturated hydraulic conductivity at the surface increases by approximately a factor of 10, and its mean value increases in the root zone and decreases in the deeper region of the soil in comparison with the values given by Clapp and Hornberger. This new version of ISBA is compared to the original version in offline simulations using the Rhône-Aggregation high-resolution database. Low-resolution simulations, where all atmospheric data and surface parameters have been aggregated, are also performed to test the impact of the modified ksat profile at the typical scale of a climate model. The simulated discharges are compared to observations from a dense network consisting of 88 gauging stations. Results of the high-resolution experiments show that the exponential profile of ksat globally improves the simulated discharges and that the assumption of an increase in saturated hydraulic conductivity from the soil surface to a depth close to the rooting depth in comparison with values given by Clapp and Hornberger is reasonable. Results of the scaling experiments indicate that this parameterization is also suitable for large-scale hydrological applications. Nevertheless, low-resolution simulations with both model versions overestimate evapotranspiration (especially from the plant transpiration and the wet fraction of the canopy) to the detriment of total runoff, which emphasizes the need for implementing subgrid distribution of precipitation and land surface properties in large-scale hydrological applications.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Hossein Hashemi ◽  
Jessica Fayne ◽  
Venkat Lakshmi ◽  
George J. Huffman

2021 ◽  
Vol 13 (16) ◽  
pp. 8954
Author(s):  
Seoyeon Lee ◽  
Seung-Jae Lee ◽  
Jung-Hyuk Kang ◽  
Eun-Suk Jang

The spatiotemporal variations in the atmospheric ventilation index (AVI) with the particulate matter (PM) concentrations in South Korea were investigated using a regional grid model derived from the National Center for AgroMeteorology and PM10 concentration data obtained from AirKorea and the Korea Meteorological Administration. To construct a high-resolution AVI database with 1 h time intervals and a spatial resolution of approximately 2.4 km, a medium-range prediction was performed using a regional model twice a week from December 2018 to November 2019. The resultant dataset was used to explore the seasonal patterns of the areal distribution of a novel index: Ventilation Index coupled with PM (VIP), defined by the ratio of the AVI to PM. To determine the effects of geography on the VIP, diurnal variations of the VIP were examined at three major cities in South Korea. The emphasis of the investigation was on major cities that are planned to be developed into smart cities. This study reveals the specific spatiotemporal structure of the AVI in South Korea for the first time at a high resolution and introduced the potential usefulness of the VIP. The results provide insights that could aid decision making for determining favorable locations for clean or polluted cities on an annual basis and can enable the sustainable management of fine PM in and around the areas of interest.


Author(s):  
Ryan R Neely ◽  
Louise Parry ◽  
David Dufton ◽  
Lindsay Bennett ◽  
Chris Collier

AbstractThe Radar Applications in Northern Scotland (RAiNS) experiment took place from February to August 2016 near Inverness, Scotland. The campaign was motivated by the need to provide enhanced weather radar observations for hydrological applications for the Inverness region. Here we describe the campaign in detail and observations over the summer period of the campaign that show the improvements that high-resolution polarimetric radar observations may have on quantitative precipitation estimates in this region compared to concurrently generated operational radar quantitative precipitation estimates (QPE). We further provide suggestions of methods for generating QPE using dual-polarisation X-band radars in similar regions.


Author(s):  
K. M. Kim

Traditional field methods for measuring tree heights are often too costly and time consuming. An alternative remote sensing approach is to measure tree heights from digital stereo photographs which is more practical for forest managers and less expensive than LiDAR or synthetic aperture radar. This work proposes an estimation of stand height and forest volume(m<sup>3</sup>/ha) using normalized digital surface model (nDSM) from high resolution stereo photography (25cm resolution) and forest type map. The study area was located in Mt. Maehwa model forest in Hong Chun-Gun, South Korea. The forest type map has four attributes such as major species, age class, DBH class and crown density class by stand. Overlapping aerial photos were taken in September 2013 and digital surface model (DSM) was created by photogrammetric methods(aerial triangulation, digital image matching). Then, digital terrain model (DTM) was created by filtering DSM and subtracted DTM from DSM pixel by pixel, resulting in nDSM which represents object heights (buildings, trees, etc.). Two independent variables from nDSM were used to estimate forest stand volume: crown density (%) and stand height (m). First, crown density was calculated using canopy segmentation method considering live crown ratio. Next, stand height was produced by averaging individual tree heights in a stand using Esri’s ArcGIS and the USDA Forest Service’s FUSION software. Finally, stand volume was estimated and mapped using aerial photo stand volume equations by species which have two independent variables, crown density and stand height. South Korea has a historical imagery archive which can show forest change in 40 years of successful forest rehabilitation. For a future study, forest volume change map (1970s&ndash;present) will be produced using this stand volume estimation method and a historical imagery archive.


2018 ◽  
Author(s):  
Laurie Caillouet ◽  
Jean-Philippe Vidal ◽  
Eric Sauquet ◽  
Benjamin Graff ◽  
Jean-Michel Soubeyroux

Abstract. SCOPE Climate (Spatially COherent Probabilistic Extended Climate dataset) is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature and Penman-Monteith reference evapotranspiration over France, from 1 January 1871 to 29 December 2012. SCOPE Climate provides an ensemble of 25 spatially coherent gridded multivariate time series. It is derived from the statistical downscaling of the Twentieth Century Reanalysis (20CR) by the SCOPE method (Spatially COherent Probabilistic Extended method) which is based on the analogue approach. SCOPE Climate performs well in comparison to both dependent and independent data for precipitation and temperature. The ensemble aspect corresponds to the uncertainty related to the SCOPE method. SCOPE Climate is the first century-long gridded high-resolution homogeneous dataset available over France and thus paves the way for improving the knowledge on specific past meteorological events or for improving the knowledge on climate variability since the end of the 19th century. This dataset has also been designed as a forcing dataset for long-term hydrological applications and studies of the hydrological consequences of climate variability over France. SCOPE Climate is freely available for any non-commercial use, and can be downloaded as NetCDF files from http://doi.org/10.5281/zenodo.1299760 for precipitation, http://doi.org/10.5281/zenodo.1299712 for temperature, and http://doi.org/10.5281/zenodo.1251843 for reference evapotranspiration.


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