• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.143-154
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• 2012

As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

• Atmosphere
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• v.28 no.2
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• pp.211-222
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• 2018

Cloud droplet activation process is well described by $K{\ddot{o}}hler$ theory and several parameterizations based on $K{\ddot{o}}hler$ theory are used in a wide range of models to represent this process. Here, we test the two different method of calculating the solute effect in the $K{\ddot{o}}hler$ equation, i.e., osmotic coefficient method (OSM) and ${\kappa}-K{\ddot{o}}hler$ method (KK). To do that, each method is implemented in the cloud droplet activation parameterization module of WRF-CHEM (Weather Research and Forecasting model coupled with Chemistry) model. It is assumed that aerosols are composed of five major components (i.e., sulfate, organic matter, black carbon, mineral dust, and sea salt). Both methods calculate similar representative hygroscopicity parameter values of 0.2~0.3 over the land, and 0.6~0.7 over the ocean, which are close to estimated values in previous studies. Simulated precipitation, and meteorological variables (i.e., specific heat and temperature) show good agreement with reanalysis. Spatial patterns of precipitation and liquid water path from model results and satellite data show similarity in general, but on regional scale spatial patterns and intensity show some discrepancy. However, meteorological variables, precipitation, and liquid water path do not show significant differences between OSM and KK simulations. So we suggest that the relatively simple KK method can be a good alternative to the OSM method that requires various information of density, molecular weight and dissociation number of each individual species in calculating the solute effect.

• Atmosphere
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• v.32 no.4
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• pp.381-394
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• 2022

The Korea Meteorological Administration (KMA) National Typhoon Center has been officially releasing reanalyzed best tracks for the previous year's northwest Pacific typhoons since 2015. However, while most typhoon researchers are aware of the data released by other institutions, such as the Joint Typhoon Warning Center (JTWC) and the Regional Specialized Meteorological Center (RSMC) Tokyo, they are often unfamiliar with the KMA products. In this technical note, we describe the best track data released by KMA, and the algorithms that are used to generate it. We hope that this will increase the usefulness of the data to typhoon researchers, and help raise awareness of the product. The best track reanalysis process is initiated when the necessary database of observations-which includes satellite, synoptic, ocean, and radar observations-has become complete for the required year. Three categories of best track information-position (track), intensity (maximum sustained winds and central pressure), and size (radii of high-wind areas)-are estimated based on scientific processes. These estimates are then examined by typhoon forecasters and other internal and external experts, and issued as an official product when final approval has been given.

• Journal of the Korean earth science society
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• v.24 no.6
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• pp.558-567
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• 2003

The regional dependency of cloud-radiative forcing at the top of atmosphere is studied using ERBE (Earth Radiation Budget Experiment), ISCCP (International Satellite Cloud Climatology Project) and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data for 60 months from January 1985 to December 1989 over tropical ocean. In the interannual time scale, the dependency of cloud-radiative forcing on the sea surface temperature over the equatorial eastern Pacific ocean is about 7.4Wm$^{-2}$K$^{-1}$ for longwave radiation and about -4.4Wm$^{-2}$K$^{-1}$ for shortwave radiation, respectively. This shows that the net cloud-radiative forcing due to the increase of sea surface temperature over the equatorial eastern Pacific ocean heats the atmosphere. But the dependency is reversed over tropical oceans with -3.4Wm$^{-2}$K$^{-1}$ for longwave and 1.9WmWm$^{-2}$K$^{-1}$ for shortwave radiation, indicating that the net cloud-radiative forcing cools the atmosphere over tropical oceans. In raw data including seasonal cycle, the dependency of cloud-radiative forcing over the equatorial eastern Pacific ocean is very similar to that in interannual time scale in both the magnitude and the sign. But the dependency of cloud-radiative forcing on the sea surface temperature over tropical oceans is about 0.2Wm$^{-2}$K$^{-1}$ for longwave and 2.7Wm$^{-2}$K$^{-1}$ for shortwave radiation, respectively. These results represent that the role of seasonal cycle on the cloud radiative forcing is gradually more important than role of interannual time scale as the ocean area is broadening from the tropical central Pacific to the tropical ocean.

• Journal of the Korean earth science society
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• v.21 no.5
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• pp.503-524
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• 2000

Intercomparisons between four kinds of data have been done to estimate the accuracy of satellite observations and model reanalysis for middle and lower tropospheric thermal state over regional oceans. The data include the Microwave Sounding Units (MSU) Channel 2 (Ch2) brightness temperatures of NOAA satellites and the vertically weighted corresponding temperature of ECMWF GCM (1980-93). The satellite data for midtropospheric temperatures are MSU2 (1980-98) in nadir direction and SC2 (1980-97) in multiple scans, and for lower tropospheric temperature SC2R (1980-97). MSU2 was derived in this study while SC2 and SC2R were described in Spencer and Christy (1992a, 1992b). Temporal correlations between the above data were high (r${\ge}$0.90) in the middle and high latitudes, but low(r${\sim}$0.65) over the low latitude and more convective regions. Their values with SC2R which included the noises due to hydrometeors and surface emission were conspicuously low. The reanalysis shows higher correlation with SC2 than with MSU2 partially because of the hydrometeors screening. SC2R in monthly climatological anomalies was more sensitive to surface thermal condition in northern hemisphere than MSU2 or SC2. The first EOF mode for the monthly mean data of MSU and ECMWF shows annual cycle over most regions except the tropics. The mode in MSU2 over the Pacific suggests the east-west dipole due to the Walker circulation, but this tendency is not clear in other data. In the first and second modes for the Ch2 anomalies over most regions, the MSU and ECMWF data commonly indicate interannual variability due to El Ni${\tilde{n}$o and La Ni${\tilde{n}$a. The substantial disagreement between observations and model reanalysis occurs over the equatorial upwelling region of the western Pacific, suggesting uncertainties in the model parameterization of atmosphere-ocean interaction.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.833-848
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• 2014

The assessment of the current and future climate change-induced potential wind energy is an important issue in the planning and operations of wind farm. Here, the authors analyze spatiotemporal characteristics and variabilities of wind energy over Korean Peninsula in the near future (2006-2040) using Representative Concentration Pathway(RCP) scenarios data. In this study, National Institute of Meteorological Research (NIMR) regional climate model HadGEM3-RA based RCP 2.6 and 8.5 scenarios are analyzed. The comparison between ERA-interim and HadGEM3-RA during the period of 1981-2005 indicates that the historical simulation of HadGEM3-RA slightly overestimates (underestimates) the wind energy over the land (ocean). It also shows that interannual and intraseasonal variability of hindcast data is generally larger than those of reanalysis data. The investigation of RCP scenarios based future wind energy presents that future wind energy density will increase over the land and decrease over the ocean. The increase in the wind energy and its variability is particularly significant over the mountains and coastal areas, such as Jeju island in future global warming. More detailed analysis presents that the changes in synoptic conditions over East Asia in future decades can influence on the predicted wind energy abovementioned. It is also suggested that the uncertainty of the predicted future wind energy may increase because of the increase of interannual and intra-annual variability. In conclusion, our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.