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Young J. Kim and Joe F. Boatman

Abstract

Distortion of the size spectra measured with a forward mattering spectrometer probe (FSSP) under different transit time modes—“inhibit”, “normal”, and “delayed”—was evaluated using the theoretical analyses by Baumgardner and Spowart and the results of the response time and beam intensity profile measurements of the NOAA FSSP. The Baumgardner and Spowart work is extended to correct the FSSP atmospheric aerosol data collected under the “inhibit” or “delayed” mode. A correction algorithm is developed using the non-negative least squares (NNLS) method to reconstruct the original size distribution from a distorted one measured with an FSSP under the inhibit or delayed mode. A lognormal fit to the corrected size spectra was able to successfully recover from the original size distributions from the distorted artificial ones obtained from the theoretical simulation of the FSSP performance. When the actual test flight data for atmospheric aerosols measured with the NOAA FSSP under the inhibit and delayed modes were corrected using the NNLS correction scheme, the two corrected size spectra converged, implying the measurement of the same sample of particles.

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Kuh Kim, Sang Jin Lyu, Young-Gyu Kim, Byung Ho Choi, Keisuke Taira, Henry T. Perkins, William J. Teague, and Jeffrey W. Book

Abstract

Voltage induced by the Tsushima Current on an abandoned submarine telephone cable between Pusan, Korea, and Hamada, Japan, has been measured since March 1998 in order to monitor the volume transport through the Korea Strait. Voltage has a good linear relationship with the transport measured by bottom-mounted acoustic Doppler current profilers (ADCPs) along a section spanning the Korea Strait. The linear conversion factor is estimated to be Λ0 = (8.06 ± 0.63) × 106 m3 s−1 V−1 with the reference voltage of V 0 = 0.48 ± 0.07 V. The voltage-derived transport reveals various temporal variations that have not been known previously. Measurement of the cable voltage provides a reliable means for continuous monitoring of the volume transport of the Tsushima Current, which determines the major surface circulation and hydrography in the East Sea.

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Nobuo Sugimoto, Tomoaki Nishizawa, Xingang Liu, Ichiro Matsui, Atsushi Shimizu, Yuanhang Zhang, Young J. Kim, Ruhao Li, and Jun Liu

Abstract

Continuous lidar observation was performed in Guangzhou, China, in the Pearl River Delta (PRD) observation campaign in July 2006 (PRD2006), using a two-wavelength Mie-scattering lidar (532 and 1064 nm) with a depolarization measurement channel at 532 nm. The profiles of the extinction coefficients at 532 nm were derived using the two-wavelength method. The planetary boundary layer (PBL) height and the cloud-base height were derived from the signals at 1064 nm. Two air pollution episodes occurred during the campaign, one on 10–12 July and the other on 22–24 July. Two events with a typhoon-driven flow of northern air occurred on 15 and 25 July. Elevated aerosol layers were observed at 1 km above ground level on 12 July and on 22 and 23 July. This layer was also observed by the lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) at 0200 LT 23 July 2006 near Guangzhou. The distribution observed by CALIPSO and trajectory analysis revealed that the layer was probably generated within the PRD region. The time–height indication of the ground-based lidar suggested that aerosols in the elevated layer were transported to the ground by convection when the PBL height reached the elevated layer. The surface concentration of elemental carbon also exhibited a corresponding increase. The air pollution index at Guangzhou, Shaoguan, Changsha, and other cities indicated temporal variations, implying the regional transport of air pollution in the typhoon episodes. Trajectory analysis indicated that an air mass from the north arrived after 24 July in the air pollution episode of 22–25 July 2006.

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Hui Wang, Lindsey Long, Arun Kumar, Wanqiu Wang, Jae-Kyung E. Schemm, Ming Zhao, Gabriel A. Vecchi, Timothy E. Larow, Young-Kwon Lim, Siegfried D. Schubert, Daniel A. Shaevitz, Suzana J. Camargo, Naomi Henderson, Daehyun Kim, Jeffrey A. Jonas, and Kevin J. E. Walsh

Abstract

The variability of Atlantic tropical cyclones (TCs) associated with El Niño–Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions during eastern Pacific (EP) and central Pacific (CP) El Niño events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Niño and stronger activity during La Niña. For CP El Niño, there is a slight increase in the number of TCs as compared with EP El Niño. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region during CP El Niño as in observations. The difference between the models and observations is likely due to the bias of the models in response to the shift of tropical heating associated with CP El Niño, as well as the model bias in the mean circulation.

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Jhoon Kim, Ukkyo Jeong, Myoung-Hwan Ahn, Jae H. Kim, Rokjin J. Park, Hanlim Lee, Chul Han Song, Yong-Sang Choi, Kwon-Ho Lee, Jung-Moon Yoo, Myeong-Jae Jeong, Seon Ki Park, Kwang-Mog Lee, Chang-Keun Song, Sang-Woo Kim, Young Joon Kim, Si-Wan Kim, Mijin Kim, Sujung Go, Xiong Liu, Kelly Chance, Christopher Chan Miller, Jay Al-Saadi, Ben Veihelmann, Pawan K. Bhartia, Omar Torres, Gonzalo González Abad, David P. Haffner, Dai Ho Ko, Seung Hoon Lee, Jung-Hun Woo, Heesung Chong, Sang Seo Park, Dennis Nicks, Won Jun Choi, Kyung-Jung Moon, Ara Cho, Jongmin Yoon, Sang-kyun Kim, Hyunkee Hong, Kyunghwa Lee, Hana Lee, Seoyoung Lee, Myungje Choi, Pepijn Veefkind, Pieternel F. Levelt, David P. Edwards, Mina Kang, Mijin Eo, Juseon Bak, Kanghyun Baek, Hyeong-Ahn Kwon, Jiwon Yang, Junsung Park, Kyung Man Han, Bo-Ram Kim, Hee-Woo Shin, Haklim Choi, Ebony Lee, Jihyo Chong, Yesol Cha, Ja-Ho Koo, Hitoshi Irie, Sachiko Hayashida, Yasko Kasai, Yugo Kanaya, Cheng Liu, Jintai Lin, James H. Crawford, Gregory R. Carmichael, Michael J. Newchurch, Barry L. Lefer, Jay R. Herman, Robert J. Swap, Alexis K. H. Lau, Thomas P. Kurosu, Glen Jaross, Berit Ahlers, Marcel Dobber, C. Thomas McElroy, and Yunsoo Choi

Abstract

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in February 2020 to monitor air quality (AQ) at an unprecedented spatial and temporal resolution from a geostationary Earth orbit (GEO) for the first time. With the development of UV–visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO, and aerosols) can be obtained. To date, all the UV–visible satellite missions monitoring air quality have been in low Earth orbit (LEO), allowing one to two observations per day. With UV–visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be on board the Geostationary Korea Multi-Purpose Satellite 2 (GEO-KOMPSAT-2) satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager 2 (GOCI-2). These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) and ESA’s Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS).

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