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According to the 6th IPCC report, the concentration of greenhouse gases has increased about 20% since pre-industrial revolution, and 17% of them have increased over the last 10 years. The Korea Metoeorological Administration has analyzed satellite-based greenhouse gases to monitor climate change and support government’s achievement of net zero. The KMA has validated satellite-based greenhouse gases using CO2 observed in situ and retrieved TCCON in Anmyeon, the South Korea which is a GAW site. Both ground- and satellite-based CO2 showed a good agreement in their increasing trends with seasonal variations. However, satellite-based CO2 observed total column appear smaller than in situ observations affected by local sources due to observe near the surface, but agree well with TCCON observed the total column. The RMSD of GOSAT, and OCO2 with in situ and TCCON is estimated about 14.85, 16.93 and 2.81, 2.01 ppmv for a 1.0 degree × 1.0 degree spatial resolution on a daily time scale from January 2014 to December 2018. The results show that satellite-based products could be used greenhouse gases monitoring, but it needs to be verified more validation data. We will present the detailed methods and results in the conference.This work was funded by the Korea Meteorological Administration’s Research and Development Program “Technical Development on Weather Forecast Support and Convergence Service using Meteorological Satellites” under Grant (KMA2020-00120).

To quantify CH4 emissions at policy-relevant spatial scales, the Korea Meteorological Administration (KMA) started monitoring its atmospheric levels in 1999 at Anmyeondo (AMY) and expanded monitoring to Jeju Gosan Suwolbong (JGS) and Ulleungdo (ULD) in 2012. The monitoring system consists of a cavity ring-down spectrometer (CRDS) and a new cryogenic drying method, with a measurement uncertainty (68 % c.i. (confidence interval)) of ± 0.7–0.8 ppb. To determine the regional characteristics of CH4 at each KMA station, we assessed the CH4 level relative to local background (CH4xs), analyzed local surface winds and CH4 with bivariate polar plots, and investigated CH4 diurnal cycles. We also compared the CH4 levels measured at KMA stations with those measured at the Mt. Waliguan (WLG) station in China and Ryori (RYO) station in Japan. CH4xs followed the order AMY (55.3 ± 37.7 ppb) > JGS (24.1 ± 10.2 ppb) > ULD (7.4 ± 3.9 ppb). Although CH4 was observed in well-mixed air at AMY, it was higher than at other KMA stations, indicating that it was affected not only by local sources but also by distant air masses. Annual mean CH4 was highest at AMY among all East Asian stations, while its seasonal amplitude was smaller than at JGS, which was strongly affected in the summer by local biogenic activities. From the long-term records at AMY, we confirmed that growth rate increased by 3.3 ppb yr−1 during 2006/2010 and by 8.3 ppb yr−1 from 2016 to 2020, which is similar to the global trend. Studies indicated that the recent global accelerated CH4-growth rate was related to biogenic sources. However, δ13CH4 indicates that the CH4 trend in East Asia is derived from both biogenic and fossil fuel sources from 2006 to 2020. We confirmed that long-term high-quality data can help understand changes in CH4 emissions in East Asia.

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.

To understand the Korean Peninsula's carbon dioxide (CO2) emissions and sinks as well as those of the surrounding region, we used 70 flask-air samples collected during May 2014 to August 2016 at Anmyeondo (AMY; 36.53∘ N, 126.32∘ E; 46 m a.s.l.) World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) station, located on the west coast of South Korea, for analysis of observed 14C in atmospheric CO2 as a tracer of fossil fuel CO2 contribution (Cff). Observed 14C ∕ C ratios in CO2 (reported as Δ values) at AMY varied from −59.5 ‰ to 23.1 ‰, with a measurement uncertainty of ±1.8 ‰. The derived mean value Cff of (9.7±7.8) µmol mol−1 (1σ) is greater than that found in earlier observations from Tae-Ahn Peninsula (TAP; 36.73∘ N, 126.13∘ E; 20 m a.s.l., 28 km away from AMY) of (4.4±5.7) µmol mol−1 from 2004 to 2010. The enhancement above background mole fractions of sulfur hexafluoride (Δx(SF6)) and carbon monoxide (Δx(CO)) correlate strongly with Cff (r>0.7) and appear to be good proxies for fossil fuel CO2 at regional and continental scales. Samples originating from the Asian continent had greater Δx(CO) : Cff(RCO) values, (29±8) to (36±2) nmol µmol−1, than in Korean Peninsula local air ((8±2) nmol µmol−1). Air masses originating in China showed (1.6±0.4) to (2.0±0.1) times greater RCO than a bottom-up inventory, suggesting that China's CO emissions are underestimated in the inventory, while observed RSF6 values are 2–3 times greater than inventories for both China and South Korea. However, RCO values derived from both inventories and observations have decreased relative to previous studies, indicating that combustion efficiency is increasing in both China and South Korea. Since we confirmed the possibility to verify the bottom-up inventories using our measurement data, it will be presented the Korea IG3IS future plan in this presentation.

Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) has adopted KMA/NIMS Atmospheric Research Aircraft (NARA) since the beginning of 2018. NARA has performed year-round airborne measurement of Sea surface Wind Speed (SWS) using Stepped Frequency Microwave Radiometer (SFMR) during 2018-2019. Total 84 flights of SFMR SWS measurements during this period were analyzed by comparing to concurrent measurements of KMA marine buoy. SFMR SWS around the Korean peninsula during the same period was 6.34±4.95 m s-1. SFMR SWS was appeared to be 12.3% larger than those of KMA marine buoy and mean Bias Difference (BD) was 0.69 m s-1. However, SFMR SWS and KMA marine buoy were correlated well to each other (R2~0.80). The BD was decreased with increasing SWS, this agreed well with results of previous studies (Klotz et al., 2014), however, SFMR SWS measurement showed still reliable even in low SWS environment (< 15 m s-1). For more accurate measurement of SFMR SWS, parameters such as the flight altitude (swath area) and pre-input values (sea surface temperature, salinity) should also be considered. Also, this result can be a comparison reference for those of satellite-borne sensors, as well.

Airborne campaigns for the meteorological and environmental research have been conducted in regional and global scales. The aircraft is increasingly considered as one of the best platforms to get the atmospheric spatial information, especially over sea. National Institute of Meteorological Sciences (NIMS), Korea Meteorological Administration (KMA) has been utilizing an aircraft (Beechcraft King Air 350HW) equipped with 25 scientific mission instruments since 2018, in order to fill in observational gaps and observe the upper level of troposphere at higher temporal/spatial resolution and to test advanced observational and experimental techniques, resulting in enhancing meteorological technologies and research capabilities. Our airborne observation plans using the aircraft are designed over the Korean Peninsula; preceding observation of severe weather (e.g., tropical cyclone, heavy rainfall and snowfall), greenhouse gas monitoring, environmental meteorology monitoring (e.g., Asian dust), and cloud physics and cloud seeding. In particular, preceding observation of severe weather which mainly uses dropsondes focuses on characterizing generation/migration of severe weather phenomena and investigating meteorological precursors sensitive to severe weather and variations in its thermo-dynamical structures, and then improving predictability of numerical models with the data assimilation. Here, we discuss current status and future plan of our airborne measurement campaigns over the Korean Peninsula, with examples of data observed from the aircraft.

The 2018 Winter Olympic and Paralympic Games will be held in Pyeongchang, Korea, during February and March. We examined the near surface winds and wind gusts along the sloping surface at two outdoor venues in Pyeongchang during February and March using surface wind data. The outdoor venues are located in a complex, mountainous terrain, and hence the near-surface winds form intricate patterns due to the interplay between large-scale and locally forced winds. During February and March, the dominant wind at the ridge level is westerly; however, a significant wind direction change is observed along the sloping surface at the venues. The winds on the sloping surface are also influenced by thermal forcing, showing increased upslope flow during daytime. When neutral air flows over the hill, the windward and leeward flows show a significantly different behavior. A higher correlation of the wind speed between upper- and lower-level stations is shown in the windward region compared with the leeward region. The strong synoptic wind, small width of the ridge, and steep leeward ridge slope angle provide favorable conditions for flow separation at the leeward foot of the ridge. The gust factor increases with decreasing surface elevation and is larger during daytime than nighttime. A significantly large gust factor is also observed in the leeward region.

Understanding the temporal variability of atmospheric methane (CH4) and its potential drivers can advance the progress toward mitigating changes to the climate. To comprehend interannual variability and spatial characteristics of anomalous CH4 mole fractions and its drivers, we used integrated data from different platforms such as in situ measurements and satellites (TROPOspheric Monitoring Instrument (TROPOMI) and Greenhouse Gases Observing SATellite (GOSAT)) retrievals. A pronounced change of annual growth rate was detected at Anmyeondo (AMY), Republic of Korea, ranging from −16.8 to 31.3 ppb yr−1 as captured in situ through 2015–2020 and 3.9 to 16.4 ppb yr−1 detected by GOSAT through 2014–2019, respectively. High growth rates were discerned in 2016 (31.3 ppb yr−1 and 13.4 ppb yr−1 from in situ and GOSAT, respectively) and 2019 (27.4 ppb yr−1 and 16.4 ppb yr−1 from in situ and GOSAT, respectively). The high growth in 2016 was essentially explained by the strong El Niño event in 2015–2016, whereas the large growth rate in 2019 was not related to ENSO. We suggest that the growth rate that appeared in 2019 was related to soil temperature according to the Noah Land Surface Model. The stable isotopic composition of 13C/12C in CH4 (δ13-CH4) collected by flask-air sampling at AMY during 2014–2019 supported the soil methane hypothesis. The intercept of the Keeling plot for summer and autumn were found to be −53.3‰ and −52.9‰, respectively, which suggested isotopic signature of biogenic emissions. The isotopic values in 2019 exhibited the strongest depletion compared to other periods, which suggests even a stronger biogenic signal. Such changes in the biogenic signal were affected by the variations of soil temperature and soil moisture. We looked more closely at the variability of XCH4 and the relationship with soil properties. The result indicated a spatial distribution of interannual variability, as well as the captured elevated anomaly over the southwest of the domain in autumn 2019, up to 70 ppb, which was largely explained by the combined effect of soil temperature and soil moisture changes, indicating a pixel-wise correlation of XCH4 anomaly with those parameters in the range of 0.5–0.8 with a statistical significance (p < 0.05). This implies that the soil-associated drivers are able to exert a large-scale influence on the regional distribution of CH4 in Korea.

A new set of Infrared Atmospheric Sounding Interferometer (IASI) channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis (1D-Var) for the Unified Model (UM) data assimilation system at the Met Office, using the channel score index (CSI) as a figure of merit. Then, 200 channels were selected in order by counting each individual channel’s CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach. Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

BackgroundIt is important to quantify changes in CO2sources and sinks with land use and land cover change. In the last several decades, carbon sources and sinks in East Asia have been altered by intensive land cover changes due to rapid economic growth and related urbanization. To understand impact of urbanization on carbon cycle in the monsoon Asia, we analyze net CO2exchanges for various land cover types across an urbanization gradient in Korea covering high-rise high-density residential, suburban, cropland, and subtropical forest areas.ResultsOur analysis demonstrates that the urban residential and suburban areas are constant CO2sources throughout the year (2.75 and 1.02 kg C m−2 year−1at the urban and suburban sites), and the net CO2emission indicate impacts of urban vegetation that responds to the seasonal progression of the monsoon. However, the total random uncertainties of measurement are much larger in the urban and suburban areas than at the nonurban sites, which can make it challenging to obtain accurate urban flux measurements. The cropland and forest sites are strong carbon sinks because of a double-cropping system and favorable climate conditions during the study period, respectively (− 0.73 and − 0.60 kg C m−2 year−1at the cropland and forest sites, respectively). The urban area of high population density (15,000 persons km−2) shows a relatively weak CO2emission rate per capita (0.7 t CO2 year−1 person−1), especially in winter because of a district heating system and smaller traffic volume. The suburban area shows larger net CO2emissions per capita (4.9 t CO2 year−1 person−1) because of a high traffic volume, despite a smaller building fraction and population density (770 persons km−2).ConclusionsWe show that in situ flux observation is challenging because of its larger random uncertainty and this larger uncertainty should be carefully considered in urban studies. Our findings indicate the important role of urban vegetation in the carbon balance and its interaction with the monsoon activity in East Asia. Urban planning in the monsoon Asia must consider interaction on change in the monsoon activity and urban structure and function for sustainable city in a changing climate.

The Korea Meteorological Administration has operated the Automatic Weather Stations, of the average 13 km horizontal resolution, to observe rainfall. However, an additional RADAR network also has been operated in all-weather conditions, because AWS network could not observed rainfall over the sea. In general, the rainrate is obtained by estimating the relationship between the radar reflectivity (Z) and the rainfall (R). But thisempirical relationship needs to be optimized on the rainfall over the Korean peninsula. This study was car-ried out to optimize the Z-R relationship in the summer of 2014 using a parallel Micro Genetic Algorithm. The optimized Z-R relationship, Z=120R 1.56, using a micro genetic algorithm was different from the various Z-R relationships that have been previously used. However, the landscape of the fitness function found in this study looked like a flat plateau. So there was a limit to the fine estimation including the complexdevelopment and decay processes of precipitation between the ground and an altitude of 1.5km.Key Words : Micro genetic algorithm, Z-R relationship, Quantitative precipitation estimation, RADAR rain-rateReceived: Aug. 13, 2015Revised : Dec. 31, 2015Accepted: Jan. 4, 2016

Three compact microwave radiometers are developed for a lightweight solar-powered HALE UAV (High-Altitude, Long Endurance; Unmanned Aerial Vehicle) or pseudo-satellite. The platform aims to operate at UTLS, i.e. altitude of 16~20 km, where air becomes thin enough to prevent operation of a conventional fossil fuel engines. Despite atmospheric science community has long been attracted in its potential scientific and operational value as an observation platform, only limited opportunities were available. The payload aims to obtain vertical temperature profiles and column-averaged water vapour for entire troposphere where most weather system takes place. Given total weight (< 3 kg) and maximum power (< 50 W) constraints are not the only challenges for design of the CHAISR. It requires nominal operation in thermal range between −75 and +43 °C and from 1013 to 50 hPa. Along with optical cameras and in situ sensors in the CHASIR, three microwave radiometers with 16 channels from 18 to 60 GHz are to fit in 130 mm diameter and 290 mm length with total weight less than 1.5 kg for cross-track scan unit. Maximum power consumption of less than 15 W does not allow conventional internal blackbody calibration facility onboard, and alternative methods has been developed. This study represents calibration of miniature microwave radiometer followed by preliminary results of a series of test flights conducted in 2017. While CHAISR has reached 2/3 of its target altitude, data from test flight showed effective performance of tipping curve calibration with altitude as expected. On the contrary, pre-flight calibration with liquid nitrogen indicates there are rooms to improve method of lab-based characterisation of the CHAISR. The result suggests feasibility of in situ cold reference for microwave radiometer and better than 1°K of total RMSE can be achievable once accuracy of warm reference is available from noise diode or ambient temperature readings. Continuous improvement of quality of instrument is currently explored at the same time, researching way of improving current specification of microwave radiometer in CHAISR.

The role of observations in reducing 24-h forecast errors is evaluated using the adjoint-based forecast sensitivity to observations (FSO) method developed within the Met Office global numerical weather prediction (NWP) system. The impacts of various subsets of observations are compared, with emphasis on space-based observations, particularly those from instruments on board the European Organisation for the Exploitation of Meteorological Satellites Meteorological Operational-A (MetOp-A) platform. Satellite data are found to account for 64% of the short-range global forecast error reduction, with the remaining 36% coming from the assimilation of surface-based observation types. MetOp-A data are measured as having the largest impact of any individual satellite platform (about 25% of the total impact on global forecast error reduction). Their large impact, compared to that of NOAA satellites, is mainly due to MetOp's additional sensors [Infrared Atmospheric Sounding Interferometer (IASI), Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding (GRAS), and the Advanced Scatterometer (ASCAT)]. Microwave and hyperspectral infrared sounding techniques are found to give the largest total impacts. However, the GPS radio occultation technique is measured as having the largest mean impact per profile of observations among satellite types. This study demonstrates how the FSO technique can be used to assess the impact of individual satellite data types in NWP. The calculated impacts can be used to guide improvements in the use of currently available data and to contribute to discussions on the evolution of future observing systems.

Temperature and moisture profiles retrieved from Infrared Atmospheric Sounding Interferometer (IASI) were evaluated by using radiosonde observations and model forecasts over East Asia. We used the level 2 products provided by National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) for IASI retrievals. Numerical model outputs from Regional Data Assimilation and Prediction System (RDAPS), Korea Weather Research and Forecasting (KWRF), and UK Met Office model (UM) were also matched with the satellite and radiosonde profiles for examining the model performances, in comparison with satellite data. The statistics of temperature and water vapor profiles were calculated by using the collocated radiosonde measurements as a reference. Both of temperature and moisture retrievals from satellite showed degraded performances over land and in dry conditions. Moist bias of the lower-troposphere is significant in dry condition especially over land, whereas dry bias of the mid-troposphere is significant in moist condition both over land and ocean. Based on the validation results, we discuss which factors can contribute to the improvement of the retrieval results over East Asia.

Temperature and water vapor profiles from the Korea Meteorological Administration (KMA) and the United Kingdom Met Office (UKMO) Unified Model (UM) data assimilation systems and from reanalysis fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) were assessed using collocated radiosonde observations from the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) for January–December 2012. The motivation was to examine the overall performance of data assimilation outputs. The difference statistics of the collocated model outputs versus the radiosonde observations indicated a good agreement for the temperature, amongst datasets, while less agreement was found for the relative humidity. A comparison of the UM outputs from the UKMO and KMA revealed that they are similar to each other. The introduction of the new version of UM into the KMA in May 2012 resulted in an improved analysis performance, particularly for the moisture field. On the other hand, ECMWF reanalysis data showed slightly reduced performance for relative humidity compared with the UM, with a significant humid bias in the upper troposphere. ECMWF reanalysis temperature fields showed nearly the same performance as the two UM analyses. The root mean square differences (RMSDs) of the relative humidity for the three models were larger for more humid conditions, suggesting that humidity forecasts are less reliable under these conditions.