Hyun Il Choi

Regional Climate–Weather Research and Forecasting Model

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approac...

Surface Boundary Conditions for Mesoscale Regional Climate Models

Abstract This paper utilizes the best available quality data from multiple sources to develop consistent surface boundary conditions (SBCs) for mesoscale regional climate model (RCM) applications. The primary SBCs include 1) fields of soil characteristic (bedrock depth, and sand and clay fraction profiles), which for the first time have been consistently introduced to define 3D soil properties; 2) fields of vegetation characteristic fields (land-cover category, and static fractional vegetation cover and varying leaf-plus-stem-area indices) to represent spatial and temporal variations of vegetation with improved data coherence and physical realism; and 3) daily sea surface temperature variations based on the most appropriate data currently available or other value-added alternatives. For each field, multiple data sources are compared to quantify uncertainties for selecting the best one or merged to create a consistent and complete spatial and temporal coverage. The SBCs so developed can be readily incorpor...

Improved Terrestrial Hydrologic Representation in Mesoscale Land Surface Models

Abstract This study addresses several deficiencies in the existing formulations for terrestrial hydrologic processes in the Common Land Model (CLM) and presents improved solutions, focusing on runoff prediction. In particular, this paper has 1) incorporated a realistic geographic distribution of bedrock depth to improve estimates of the actual soil water capacity; 2) replaced an equilibrium approximation with a dynamic prediction of the water table to produce more reasonable variations of the saturated zone depth; 3) used an exponential decay function with soil depth for the saturated hydraulic conductivity to consider the effect of macropores near the ground surface; 4) formulated an effective hydraulic conductivity of the liquid part at the frozen soil interface and imposed a maximum surface infiltration limit to eliminate numerically generated negative or excessive soil moisture solution; and 5) examined an additional contribution to subsurface runoff from saturation lateral runoff or baseflow controll...

A Conjunctive Surface-Subsurface Flow Representation for Mesoscale Land Surface Models

AbstractMost current land surface models used in regional weather and climate studies capture soil-moisture transport in only the vertical direction and are therefore unable to capture the spatial variability of soil moisture and its lateral transport. They also implement simplistic surface runoff estimation from local soil water budget and ignore the role of surface flow depth on the infiltration rate, which may result in significant errors in the terrestrial hydrologic cycle. To address these issues, this study develops and describes a conjunctive surface–subsurface flow (CSSF) model that comprises a 1D diffusion wave model for surface (overland) flow fully interacted with a 3D volume-averaged soil-moisture transport model for subsurface flow. The proposed conjunctive flow model is targeted for mesoscale climate application at relatively large spatial scales and coarse computational grids as compared to the traditional coupled surface–subsurface flow scheme in a typical basin. The CSSF module is substit...

Assessment of Vulnerability to Extreme Flash Floods in Design Storms

There has been an increase in the occurrence of sudden local flooding of great volume and short duration caused by heavy or excessive rainfall intensity over a small area, which presents the greatest potential danger threat to the natural environment, human life, public health and property, etc. Such flash floods have rapid runoff and debris flow that rises quickly with little or no advance warning to prevent flood damage. This study develops a flash flood index through the average of the same scale relative severity factors quantifying characteristics of hydrographs generated from a rainfall-runoff model for the long-term observed rainfall data in a small ungauged study basin, and presents regression equations between rainfall characteristics and the flash flood index. The aim of this study is to develop flash flood index-duration-frequency relation curves by combining the rainfall intensity-duration-frequency relation and the flash flood index from probability rainfall data in order to evaluate vulnerability to extreme flash floods in design storms. This study is an initial effort to quantify the flash flood severity of design storms for both existing and planned flood control facilities to cope with residual flood risks due to extreme flash floods that have ocurred frequently in recent years.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface‐Subsurface Process (CSSP) land surface model

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol’ sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol’ sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture.

Estimation of the Relative Severity of Floods in Small Ungauged Catchments for Preliminary Observations on Flash Flood Preparedness: A Case Study in Korea

An increase in the occurrence of sudden local flooding of great volume and short duration has caused significant danger and loss of life and property in Korea as well as many other parts of the World. Since such floods usually accompanied by rapid runoff and debris flow rise quite quickly with little or no advance warning to prevent flood damage, this study presents a new flash flood indexing methodology to promptly provide preliminary observations regarding emergency preparedness and response to flash flood disasters in small ungauged catchments. Flood runoff hydrographs are generated from a rainfall-runoff model for the annual maximum rainfall series of long-term observed data in the two selected small ungauged catchments. The relative flood severity factors quantifying characteristics of flood runoff hydrographs are standardized by the highest recorded maximum value, and then averaged to obtain the flash flood index only for flash flood events in each study catchment. It is expected that the regression equations between the proposed flash flood index and rainfall characteristics can provide the basis database of the preliminary information for forecasting the local flood severity in order to facilitate flash flood preparedness in small ungauged catchments.

Application of a Land Surface Model Using Remote Sensing Data for High Resolution Simulations of Terrestrial Processes

Most current land surface models (LSMs) coupled to regional climate models (RCMs) have been implemented at the several tens of kilometer spatial scales. Modeling land surface processes in LSMs at a finer resolution is necessary for improvements in terrestrial water and energy predictions especially for small catchments. This study has therefore assessed the applicability of high-resolution simulations for terrestrial processes to a small study basin from the Common Land Model (CoLM) using 1-km surface boundary conditions (SBCs) based on remote sensing products. The performance of the CoLM simulations at finer (1-km) and coarser (30-km) resolutions are evaluated for daily runoff and land surface temperature results which have a significant influence on the terrestrial water and energy cycles. The daily stream water temperature is also estimated by a linear regression function of the 1-km daily land surface temperature prediction. The daily stream runoff and temperature results are compared with observations from a stream gauge station, and the daily land surface temperature prediction is compared with the 1-km remote sensing product. It is observed that the high-resolution CoLM results can reasonably capture seasonal variations in both daily runoff and temperatures crucial to the terrestrial water and energy budget.

A method of flood severity assessment for predicting local flood hazards in small ungauged catchments

A flash flood caused by heavy storm in a short period of time is now one of the common natural disasters worldwide. The aim of this paper is to develop a new flood hazard index for use in local flood severity predictions in small ungauged catchments through the regression analysis between the flood hazard index and rainfall features. The flood events with the peak flow above a threshold discharge are targeted to estimate the flood hazard index among the annual maximum flood runoff hydrographs generated from a rainfall–runoff model for the long-term-observed rainfall data. To quantify characteristics of flood runoff hydrographs simulated for ungauged catchments, the new flood hazard index is measured by the average of the three normalized relative severity factors, such as the flood magnitude ratio, the rising curve gradient, and the rising average runoff to the peak time. The proposed flood hazard index shows a high correlation with logarithm of the short-duration rainfall for the two selected small ungauged catchments in the Korean Peninsula. The best-fit regression equation between the flood hazard index and rainfall patterns can be used in predicting the relative flash flood severity for small ungauged catchments.

Parameterization of High Resolution Vegetation Characteristics using Remote Sensing Products for the Nakdong River Watershed, Korea

Mesoscale regional climate models (RCMs), the primary tool for climate predictions, have recently increased in sophistication and are being run at increasingly higher resolutions to be also used in climate impact studies on ecosystems, particularly in agricultural crops. As satellite remote sensing observations of the earth terrestrial surface become available for assimilation in RCMs, it is possible to incorporate complex land surface processes, such as dynamics of state variables for hydrologic, agricultural and ecologic systems at the smaller scales. This study focuses on parameterization of vegetation characteristics specifically designed for high resolution RCM applications using various remote sensing products, such as Advanced Very High Resolution Radiometer (AVHRR), Systeme Pour l’Observation de la Terre-VEGETATION (SPOT-VGT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The primary vegetative parameters, such as land surface characteristics (LCC), fractional vegetation cover (FVC), leaf area index (LAI) and surface albedo localization factors (SALF), are currently presented over the Nakdong River Watershed domain, Korea, based on 1-km remote sensing satellite data by using the Geographic Information System (GIS) software application tools. For future high resolution RCM modeling efforts on climate-crop interactions, this study has constructed the deriving parameters, such as FVC and SALF, following the existing methods and proposed the new interpolation methods to fill missing data with combining the regression equation and the time series trend function for time-variant parameters, such as LAI and NDVI data at 1-km scale.