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Tae-Won Park, Chang-Hoi Ho, and Song Yang

Abstract

The present study reveals the changes in the characteristics of cold surges over East Asia associated with the Arctic Oscillation (AO). Based on circulation features, cold surges are grouped into two general types: wave train and blocking types. The blocking type of cold surge tends to occur during negative AO periods, that is, the AO-related polarity of the blocking type. However, the wave train type is observed during both positive and negative AO periods, although the wave train features associated with negative AO are relatively weaker. The cold surges during negative AO are stronger than those during positive AO in terms of both amplitude and duration. The cold surges during positive AO in which the extent of effect is confined to inland China passes through East Asia quickly because of weaker Siberian high and Aleutian low, leading to short duration of these cold surges. In contrast, the cold surge during negative AO, characterized by a well-organized anticyclone–cyclone couplet with high pressure over continental East Asia and low pressure over Japan, brings continuous cold air into the entire East Asian region for more than one week with long-lasting cold advection. It is also found that the tracks of the cold surges during negative AO tend to occur more frequently over Korea and Japan and less frequently over China, compared with those during positive AO. The tracks are related to a west–east dipole structure of the ratio of rain conversion to snow according to AO phase, resulting in freezing precipitation or snowfall events over inland China (Korea and Japan) are likely to occur more frequently during the positive (negative) AO periods.

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Chang-Kyun Park, Doo-Sun R. Park, Chang-Hoi Ho, Tae-Won Park, Jinwon Kim, Sujong Jeong, and Baek-Min Kim

Abstract

Because spring precipitation in East Asia is critical for recharging water resources after dry winters, its spatiotemporal variations and related mechanisms need in-depth research. This study analyzed a leading spatiotemporal variability of precipitation over East Asia for boreal spring (March–May) during 1979 to 2017. We found that a dipole mode dominates the anomalous spring precipitation between southern China and Southeast Asia with significant interannual and decadal variations. The interannual dipole mode is attributable to the eastern Pacific (EP)-type El Niño–Southern Oscillation (ENSO) while the decadal dipole mode is related to the decadal variation of the central Pacific (CP)-type ENSO. In the El Niño phases of both time scales, the anticyclonic anomaly over the South China Sea and Philippines causes moisture convergence (divergence) over southern China (Southeast Asia), resulting in positive (negative) precipitation anomalies therein; the opposite occurs in the La Niña phases. The ensemble experiments using the Community Atmosphere Model version 5.1 confirmed that the tropical sea surface temperature (SST) in the EP- and CP-type ENSO can be the major drivers of the interannual and decadal dipole modes, respectively. About half of 15 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) showed that the El Niño phase of dipole mode will become dominant in the future. The individual models’ future projections however considerably vary, implying that there is still large uncertainty.

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Jee-Hoon Jeong, Chang-Hoi Ho, Deliang Chen, and Tae-Won Park

Abstract

The impacts of initialized land surface conditions on the monthly prediction were investigated using ensemble simulations from the Community Atmosphere Model version 3 (CAM3). The land surface initialization was based on an offline calculation of Community Land Model version 3 driven by observation-based meteorological forcings from the Global Soil Wetness Project 2 (GSWP2). A simple but effective correction method was applied to the GSWP2 forcings prior to the offline calculation to reduce the discrepancies between the observation-forced land surface conditions and the modeling system, which can cause climate drift and initial shock problems. The climatological mean of GSWP2 forcings was adjusted to that of the target model (CAM3), while the monthly anomalies were scaled to the model statistics and high-frequency synoptic variabilities were included.

Ensemble hindcast experiments with and without land surface initialization were conducted for the boreal summer (May–September), for 1983–95. The initialization process is shown to prevent climate drift and to transfer the atmospheric anomalies to the land surface memory. Statistical analyses of the simulation results reveal that the land surface initialization increased the externally forced variance over most continental regions, which is translated to enhanced potential predictability, particularly for regions with strong land–atmosphere coupling.

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Won Chang, Michael L. Stein, Jiali Wang, V. Rao Kotamarthi, and Elisabeth J. Moyer

Abstract

Climate models robustly imply that some significant change in precipitation patterns will occur. Models consistently project that the intensity of individual precipitation events increases by approximately 6%–7% K−1, following the increase in atmospheric water content, but that total precipitation increases by a lesser amount (1%–2% K−1 in the global average in transient runs). Some other aspect of precipitation events must then change to compensate for this difference. The authors develop a new methodology for identifying individual rainstorms and studying their physical characteristics—including starting location, intensity, spatial extent, duration, and trajectory—that allows identifying that compensating mechanism. This technique is applied to precipitation over the contiguous United States from both radar-based data products and high-resolution model runs simulating 80 years of business-as-usual warming. In the model study the dominant compensating mechanism is a reduction of storm size. In summer, rainstorms become more intense but smaller; in winter, rainstorm shrinkage still dominates, but storms also become less numerous and shorter duration. These results imply that flood impacts from climate change will be less severe than would be expected from changes in precipitation intensity alone. However, these projected changes are smaller than model–observation biases, implying that the best means of incorporating them into impact assessments is via “data-driven simulations” that apply model-projected changes to observational data. The authors therefore develop a simulation algorithm that statistically describes model changes in precipitation characteristics and adjusts data accordingly, and they show that, especially for summertime precipitation, it outperforms simulation approaches that do not include spatial information.

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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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