• Title/Summary/Keyword: global NWP system

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Application of Weakly Coupled Data Assimilation in Global NWP System (전지구 예보모델의 대기-해양 약한 결합자료동화 활용성에 대한 연구)

  • Yoon, Hyeon-Jin;Park, Hyei-Sun;Kim, Beom-Soo;Park, Jeong-Hyun;Lim, Jeong-Ock;Boo, Kyung-On;Kang, Hyun-Suk
    • Atmosphere
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    • v.29 no.2
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    • pp.219-226
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    • 2019
  • Generally, the weather forecast system has been run using prescribed ocean condition. As it is widely known that coupling between atmosphere and ocean process produces consistent initial condition at all-time scales to improve forecast skill, there are many trials on the application of data assimilation of coupled model. In this study, we implemented a weakly coupled data assimilation (short for WCDA) system in global NWP model with low horizontal resolution for coupled forecast with uncoupled initialization, following WCDA system at the Met Office. The experiment is carried out for a typhoon evolution forecast in 2017. Air-sea exchange process provides SST cooling and gives a substantial impact on tendency of central pressure changes in the decaying phase of the typhoon, except the underestimated central pressure. Coupled data assimilation is a challenging new area, requiring further work, but it would offer the potential for improving air-sea feedback process on NWP timescales and finally contributing forecast accuracy.

UNCERTAINTIES IN AMV ESTIMATION

  • Sohn, Eun-Ha;Cho, Hee-Je;Ou, Mi-Lim;Kim, Yoon-Jae
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.153-155
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    • 2007
  • Korea Meteorological Administration (KMA) has operationally produced Atmospheric Motion Vector (AMV) from the consecutive MTSAT-1R satellite image dataset. Comparing with radiosonde data, our current AMV scheme shows more than 10 m/s RMSE. Therefore we need to improve continuously its accuracy. Many AMV producers have stated that the bad performance of the Height Assignment (HA) algorithm is the main reason of degrading the accuracy of AMV. The uncertainties in AMV HA can occur in the algorithm itself, used NWP profiles, and the performance of Radiative Transfer Model (RTM) etc. This study introduces currently operated AMV HA schemes and the impacts of NWP profile data and RTM that these schemes use were investigated. Finally we analyzed the relationship between vectors by vector tracking and heights assigned to each vector by using collocated wind profile dataset with radiosonde data. This study is a preliminary work to improve the accuracy of AMV by removing or decreasing the uncertainties in AMV estimation.

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Sea Level Rise due to Global Warming in the Northwestern Pacific and Seas around the Korean Peninsula (지구온난화에 의한 북서태평양 및 한반도 근해의 해수면 상승)

  • Oh, Sang-Myeong;Kwon, Seok-Jae;Moon, Il-Ju;Lee, Eun-Il
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.23 no.3
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    • pp.236-247
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    • 2011
  • This study investigates sea level (SL) rise due to global warming in the Northwestern Pacific (NWP) and Seas around the Korean peninsula (KP) using outputs of IPCC AR4 climate models. Particularly, components of the SL rise induced by a local steric effect, which was not considered in most climate models, were computed using model-projected 3-dimensional temperature and salinity data. Analysis of the SL data shows that the ratio of the SL rise in the NWP and KP was about two times higher than that in global mean and particularly the ratio in the Kuroshio extension region was the highest. The SL rises over 100 years estimated from MPI_ECHAM5 and GFDL_CM2.1 model by A1B scenario considering the thermosteric effect were 24 cm and 28 cm for the NWP and 27 cm and 31 cm for the Seas around the KP, respectively. Statistical analysis reveals that these SL rises are caused by the weakening of the Siberian High in winter as well as variations of pressure system in the NWP and by the resultant change of water temperature. It also found that the highest SL rise in the Kuroshio extension region of the NWP was connected with the large increase of water temperature in this area.

Development of Mongolian Numerical Weather Prediction System (MNWPS) Based on Cluster System (클러스터 기반의 몽골기상청 수치예보시스템 개발)

  • Lee, Yong Hee;Chang, Dong-Eon;Cho, Chun-Ho;Ahn, Kwang-Deuk;Chung, Hyo-Sang;Gomboluudev, P.
    • Atmosphere
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    • v.15 no.1
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    • pp.35-46
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    • 2005
  • Today, the outreach of National Meteorological Service such as PC cluster based Numerical Weather Prediction (NWP) technique is vigorous in the world wide. In this regard, WMO (World Meteorological Organization) asked KMA (Korea Meteorological Administration) to formulate a regional project, which cover most of RA II members, using similar technical system with KMA's. In that sense, Meteorological Research Institute (METRI) in KMA developed Mongolian NWP System (MNWPS) based on PC cluster and transferred the technology to Weather Service Center in Mongolia. The hybrid parallel algorithm and channel bonding technique were adopted to cut cost and showed 41% faster performance than single MPI (Message Passing Interface) approach. The cluster technique of Beowulf type was also adopted for convenient management and saving resources. The Linux based free operating system provide very cost effective solution for operating multi-nodes. Additionally, the GNU software provide many tools, utilities and applications for construction and management of a cluster. A flash flood event happened in Mongolia (2 September 2003) was selected for test run, and MNWPS successfully simulated the event with initial and boundary condition from Global Data Assimilation and Prediction System (GDAPS) of KMA. Now, the cluster based NWP System in Mongolia has been operated for local prediction around the region and provided various auxiliary charts.

ANALYSIS ON GPS PWV EFFECTS AS AN INITIAL INPUT DATA OF NWP MODEL (수치예보모델 초기치로서 GPS 가강수량 영향 분석)

  • Lee, Jae-Won;Cho, Jung-Ho;Baek, Jeong-Ho;Park, Jong-Uk
    • Journal of Astronomy and Space Sciences
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    • v.24 no.4
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    • pp.285-296
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    • 2007
  • The Precipitable Water Vapor (PWV) from GPS with high resolution in terms of time and space might reduce the limitations of the numerical weather prediction (NWP) model for easily variable phenomena, such as precipitation and cloud. We have converted to PWV from Global Positioning System (GPS) data of Korea Astronomy and Space Science Institute (KASI) and Ministry of Maritime Affairs & Fisheries (MOMAF). First of all, we have selected the heavy rainfall case of having a predictability limitation in time and space due to small-scale motion. In order to evaluate the effect for GPS PWV, we have executed the sensitivity experiment with PWV from GPS data over Korean peninsula in the Weather Research & Forecasting 3-Dimensional Variational (WRF-3DVAR). We have also suggested the direction of further research for an improvement of the predictability of NWP model on the basis of this case.

The Impact of Satellite Observations on the UM-4DVar Analysis and Prediction System at KMA (위성자료가 기상청 전지구 통합 분석 예측 시스템에 미치는 효과)

  • Lee, Juwon;Lee, Seung-Woo;Han, Sang-Ok;Lee, Seung-Jae;Jang, Dong-Eon
    • Atmosphere
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    • v.21 no.1
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    • pp.85-93
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    • 2011
  • UK Met Office Unified Model (UM) is a grid model applicable for both global and regional model configurations. The Met Office has developed a 4D-Var data assimilation system, which was implemented in the global forecast system on 5 October 2004. In an effort to improve its Numerical Weather Prediction (NWP) system, Korea Meteorological Administration (KMA) has adopted the UM system since 2008. The aim of this study is to provide the basic information on the effects of satellite data assimilation on UM performance by conducting global satellite data denial experiments. Advanced Tiros Operational Vertical Sounder (ATOVS), Infrared Atmospheric Sounding Interferometer (IASI), Special Sensor Microwave Imager Sounder (SSMIS) data, Global Positioning System Radio Occultation (GPSRO) data, Air Craft (CRAFT) data, Atmospheric Infrared Sounder (AIRS) data were assimilated in the UM global system. The contributions of assimilation of each kind of satellite data to improvements in UM performance were evaluated using analysis data of basic variables; geopotential height at 500 hPa, wind speed and temperature at 850 hPa and mean sea level pressure. The statistical verification using Root Mean Square Error (RMSE) showed that most of the satellite data have positive impacts on UM global analysis and forecasts.

Comparative Analysis of Observation and NWP Data of Downslope Windstorm Cases during 3-Dimensional Meteorological Observation Project in Yeongdong Region of Gangwon province, South Korea in 2020 (2020 강원영동 공동 입체기상관측 기간 강풍 사례에 대한 관측자료와 수치모델 비교 분석)

  • Kwon, Soon-Beom;Park, Se-Taek
    • Atmosphere
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    • v.31 no.4
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    • pp.395-404
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    • 2021
  • In order to investigate downslope windstorm by using more detailed observation, we observed 6 cases at 3 sites - Inje, Yongpyeong, and Bukgangneung - during "3-D Meteorological Observation Project in Yeongdong region of Gangwon province, South Korea in 2020." The results from analysis of the project data were as follows. First, AWS data showed that a subsidence inversion layer appeared in 800~700 hPa on the windward side and 900~850 hPa on the leeward side. Second, before strong wind occurred, the inversion layer had descended to about 880~800 hPa. Third, with mountain wave breaking, downslope wind was intensified at the height of 2~3 km above sea level. After the downslope wind began to descend, the subsidence inversion layer developed. When the subsidence inversion layer got close to the ground, wind peak occurred. In general, UM (Unified Model) GDAPS (Global Data Assimilation Prediction System) have had negative bias in wind speed around peak area of Taebaek mountain range, and positive bias in that of East Sea coast area. The stronger wind blew, the larger the gap between observed and predicted wind speed by GDAPS became. GDAPS predicted strong p-velocity at 0600 LST 25 Apr 2020 (4th case) and weak p-velocity at 2100 LST 01 Jun 2020 (6th case) on the lee-side of Taebaek mountain range near Yangyang. As hydraulic jump theory was proved, which is known as a mechanism of downslope windstorm in Yeongdong region, it was confirmed that there is a relationship between p-velocity of lee-side and wind speed of eastern slope of Taebaek mountain range.

A Study of Static Bias Correction for Temperature of Aircraft based Observations in the Korean Integrated Model (한국형모델의 항공기 관측 온도의 정적 편차 보정 연구)

  • Choi, Dayoung;Ha, Ji-Hyun;Hwang, Yoon-Jeong;Kang, Jeon-ho;Lee, Yong Hee
    • Atmosphere
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    • v.30 no.4
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    • pp.319-333
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    • 2020
  • Aircraft observations constitute one of the major sources of temperature observations which provide three-dimensional information. But it is well known that the aircraft temperature data have warm bias against sonde observation data, and therefore, the correction of aircraft temperature bias is important to improve the model performance. In this study, the algorithm of the bias correction modified from operational KMA (Korea Meteorological Administration) global model is adopted in the preprocessing of aircraft observations, and the effect of the bias correction of aircraft temperature is investigated by conducting the two experiments. The assimilation with the bias correction showed better consistency in the analysis-forecast cycle in terms of the differences between observations (radiosonde and GPSRO (Global Positioning System Radio Occultation)) and 6h forecast. This resulted in an improved forecasting skill level of the mid-level temperature and geopotential height in terms of the root-mean-square error. It was noted that the benefits of the correction of aircraft temperature bias was the upper-level temperature in the midlatitudes, and this affected various parameters (winds, geopotential height) via the model dynamics.

A Monitoring System of Ensemble Forecast Sensitivity to Observation Based on the LETKF Framework Implemented to a Global NWP Model (앙상블 기반 관측 자료에 따른 예측 민감도 모니터링 시스템 구축 및 평가)

  • Lee, Youngsu;Shin, Seoleun;Kim, Junghan
    • Atmosphere
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    • v.30 no.2
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    • pp.103-113
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    • 2020
  • In this study, we analyzed and developed the monitoring system in order to confirm the effect of observations on forecast sensitivity on ensemble-based data assimilation. For this purpose, we developed the Ensemble Forecast Sensitivity to observation (EFSO) monitoring system based on Local Ensemble Transform Kalman Filter (LETKF) system coupled with Korean Integrated Model (KIM). We calculated 24 h error variance of each of observations and then classified as beneficial or detrimental effects. In details, the relative rankings were according to their magnitude and analyzed the forecast sensitivity by region for north, south hemisphere and tropics. We performed cycle experiment in order to confirm the EFSO result whether reliable or not. According to the evaluation of the EFSO monitoring, GPSRO was classified as detrimental observation during the specified period and reanalyzed by data-denial experiment. Data-denial experiment means that we detect detrimental observation using the EFSO and then repeat the analysis and forecast without using the detrimental observations. The accuracy of forecast in the denial of detrimental GPSRO observation is better than that in the default experiment using all of the GPSRO observation. It means that forecast skill score can be improved by not assimilating observation classified as detrimental one by the EFSO monitoring system.

Analyzing off-line Noah land surface model spin-up behavior for initialization of global numerical weather prediction model (전지구수치예측모델의 토양수분 초기화를 위한 오프라인 Noah 지면모델 스핀업 특성분석)

  • Jun, Sanghee;Park, Jeong-Hyun;Boo, Kyung-On;Kang, Hyun-Suk
    • Journal of Korea Water Resources Association
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    • v.53 no.3
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    • pp.181-191
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    • 2020
  • In order to produce accurate initial condition of soil moisture for global Numerical Weather Prediction (NWP), spin-up experiment is carried out using Noah Land Surface Model (LSM). The model is run repeatedly through 10 years, under the atmospheric forcing condition of 2008-2017 until climatological land surface state is achieved. Spin-up time for the equilibrium condition of soil moisture exhibited large variability across Koppen-Geiger climate classification zone and soil layer. Top soil layer took the longgest time to equilibrate in polar region. From the second layer to the fourth layer, arid region equilibrated slower (7 years) than other regions. This result means that LSM reached to equilibrium condition within 10 year loop. Also, spin-up time indicated inverse correlation with near surface temperature and precipitation amount. Initialized from the equilibrium state, LSM was spun up to obtain land surface state in 2018. After 6 months from restarted run, LSM simulates soil moisture, skin temperature and evaportranspiration being similar land surface state in 2018. Based on the results, proposed LSM spin-up system could be used to produce proper initial soil moisture condition despite updates of physics or ancillaries for LSM coupled with NWP.