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Kyung-Sup Shin
,
Gerald R. North
,
Yoo-Shin Ahn
, and
Phillip A. Arkin

Abstract

A statistical analysis of time series of area-averaged rainfall over the oceans has been conducted around the diurnal time scale. The results of our analysis can be applied directly to the problem of establishing the magnitude of expected errors to be incurred in the estimation of monthly area-averaged rain rates from low orbiting satellites. Such statistics as the mean, standard deviation, integral time scale of background red noise and spectral analyses were performed oil time series of the GOES Precipitation Index (GPI) taken at 3-hour intervals during the period spanning 19 December 1987 to 31 March 1988 over the central and eastern tropical Pacific. The analyses have been conducted on 2.5°×2.5° and 5°×5° grid boxes, separately.

The ratio of standard deviation to mean for area-averaged rain rate in the Pacific ITCZ is very regular and similar to that in GATE. Analysis of the area-averaged rainfall in the SPCZ shows a longer autocorrelation time scale than that in the ITCZ. The SPCZ exhibits significant power at the diurnal and semidiurnal frequencies, but the ITCZ shows only a marginally significant diurnal cycle in our data. The rainfall characteristics in the Pacific ITCZ appear to be similar to those in the Atlantic ITCZ in both autocorrelation time scale and diurnal variation. The mechanism driving convection in the ITCZ is suggested to be different from that in the SPCZ. The study shows that rainfall measurements by a sun-synchroneous satellite visiting a spot twice per day will include a bias due to the existence of the semidiurnal cycle in the SPCZ ranging from 5 to 10 percentage points. The bias in the ITCZ may be of the order of 5 percentage points.

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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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