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Jinwon Kim and Hyun-Suk Kang

Abstract

To understand the influence of the Sierra Nevada on the water cycle in California the authors have analyzed low-level winds and water vapor fluxes upstream of the mountain range in regional climate model simulations. In a low Froude number (Fr) regime, the upstream low-level wind disturbances are characterized by the rapid weakening of the crosswinds and the appearance of a stagnation point over the southwestern foothills. The weakening of the low-level inflow is accompanied by the development of along-ridge winds that take the form of a barrier jet over the western slope of the mountain range. Such upstream wind disturbances are either weak or nonexistent in a high-Fr case. A critical Fr (Frc) of 0.35 inferred in this study is within the range of those suggested in previous observational and numerical studies. The depth of the blocked layer estimated from the along-ridge wind profile upstream of the northern Sierra Nevada corresponds to Frc between 0.3 and 0.45 as well. Associated with these low-level wind disturbances are significant low-level southerly moisture fluxes over the western slope and foothills of the Sierra Nevada in the low-Fr case, which result in significant exports of moisture from the southern Sierra Nevada to the northern region. This along-ridge low-level water vapor transport by blocking-induced barrier jets in a low-Fr condition may result in a strong north–south precipitation gradient over the Sierra Nevada.

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Ji-Hyun Ha, Jeon-Ho Kang, and Suk-Jin Choi

Abstract

The sensitivity of GPS radio occultation (GPSRO) bending angle assimilation to vertical resolution was studied within a global three-dimensional variational data assimilation (3DVAR) system. The sensitivity experiments were performed using different vertical resolutions of GPSRO data at 2 km, 1 km, 500 m, and 200 m. The assimilation of the higher vertical resolution GPSRO data showed better consistency in the analysis–forecast cycle in terms of the differences between GPSRO bending angle data and 6-h forecasts (O-F). This resulted in an improved analysis of the temperature, geopotential height, and wind in the mid-/upper-level troposphere by the hydrostatic response and the related model dynamics. It should be noted that the highest vertical resolution of the GPSRO data (200 m in this study) improved the forecasting skill level in terms of the root-mean-square error (against the European Centre for Medium-Range Weather Forecasts analysis) and the anomaly correlation of the geopotential height forecasting at 500 and 200 hPa in both the Northern and Southern Hemispheres. The benefits of assimilating higher vertical resolution GPSRO data were more pronounced in the upper-level troposphere, which was in agreement with previous studies using real GPSRO observations.

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Hyun-Suk Kang, Yongkang Xue, and G. James Collatz

Abstract

This study assesses the impact of two different remote sensing–derived leaf area index (RSLAI) datasets retrieved from the same source (i.e., Advanced Very High Resolution Radiometer measurements) on a general circulation model’s (GCM) seasonal climate simulations as well as the mechanisms that lead to the improvement in simulations over several regions. Based on the analysis of these two RSLAI datasets for 17 yr from 1982 to 1998, their spatial distribution patterns and characteristics are discussed. Despite some disagreements in the RSLAI magnitudes and the temporal variability between these two datasets over some areas, their effects on the simulation of near-surface climate and the regions with significant impact are generally similar to each other. Major disagreements in the simulated climate appear in a few limited regions.

The GCM experiment using the RSLAI and other satellite-derived land surface products showed substantial improvements in the near-surface climate in the East Asian and West African summer monsoon areas and boreal forests of North America compared to the control experiment that used LAI extrapolated from limited ground surveys. For the East Asia and northwest U.S. regions, the major role of RSLAI changes is in partitioning the net radiative energy into latent and sensible heat fluxes, which results in discernable warming and decrease of precipitation due to the smaller RSLAI values compared to the control. Meanwhile, for the West African semiarid regions, where the LAI difference between RSLAI and control experiments is negligible, the decrease in surface albedo caused by the high vegetation cover fraction in the satellite-derived dataset plays an important role in altering local circulation that produces a positive feedback in land/atmosphere interaction.

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Hyerim Kim, Myong-In Lee, Daehyun Kim, Hyun-Suk Kang, and Yu-Kyung Hyun

Abstract

This study examines the representation of the Madden–Julian oscillation (MJO) and its teleconnection in boreal winter in the Global Seasonal Forecast System, version 5 (GloSea5), using 20 years (1991–2010) of hindcast data. The sensitivity of the performance to the polarity of El Niño–Southern Oscillation (ENSO) is also investigated. The real-time multivariate MJO index of Wheeler and Hendon is used to assess MJO prediction skill while intraseasonal 200-hPa streamfunction anomalies are used to evaluate the MJO teleconnection. GloSea5 exhibits significant MJO prediction skill up to 25 days of forecast lead time. MJO prediction skill in GloSea5 also depends on initial MJO phases, with relatively enhanced (degraded) performance when the initial MJO phase is 2 or 3 (8 or 1) during the first 2 weeks of the hindcast period. GloSea5 depicts the observed MJO teleconnection patterns in the extratropics realistically up to 2 weeks albeit weaker than the observed. The ENSO-associated basic-state changes in the tropics and in the midlatitudes are reasonably represented in GloSea5. MJO prediction skill during the first 2 weeks of the hindcast is slightly higher in neutral and La Niña years than in El Niño years, especially in the upper-level zonal wind anomalies. Presumably because of the better representation of MJO-related tropical heating anomalies, the Northern Hemispheric MJO teleconnection patterns in neutral and La Niña years are considerably better than those in El Niño years.

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Ahreum Lee, Byung-Ju Sohn, Ed Pavelin, Yoonjae Kim, Hyun-Suk Kang, Roger Saunders, and Young-Chan Noh

Abstract

The Unified Model (UM) data assimilation system incorporates a 1D-Var analysis of cloud variables for assimilating hyperspectral infrared radiances. For the Infrared Atmospheric Sounding Interferometer (IASI) radiance assimilation, a first guess of cloud top pressure (CTP) and cloud fraction (CF) is estimated using the minimum residual (MR) method, which simultaneously obtains CTP and CF by minimizing radiance difference between observation and model simulation. In this study, we examined how those MR-based cloud retrievals behave, using “optimum” CTP and CF that yield the best 1D-Var analysis results. It is noted that the MR method tends to overestimate cloud top height while underestimating cloud fraction, compared to the optimum results, necessitating an improved cloud retrieval. An artificial neural network (ANN) approach was taken to estimate CTP as close as possible to the optimum value, based on the hypothesis that CTP and CF closer to the optimum values will bring in better 1D-Var results. The ANN-based cloud retrievals indicated that CTP and CF biases shown in the MR method are much reduced, giving better 1D-Var analysis results. Furthermore, the computational time can be substantially reduced by the ANN method, compared to the MR method. The evaluation of the ANN method in a global weather forecasting system demonstrated that it helps to use more temperature channels in the assimilation, although its impact on UM forecasts was found to be near neutral. It is suggested that the neutral impact may be improved when error covariances for the cloudy sky are employed in the UM assimilation system.

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Hyeonjae Lee, Chun-Sil Jin, Dong-Hyun Cha, Minkyu Lee, Dong-Kyou Lee, Myoung-Seok Suh, Song-You Hong, and Hyun-Suk Kang

Abstract

Future changes in tropical cyclone (TC) activity over the western North Pacific (WNP) are analyzed using four regional climate models (RCMs) within the Coordinated Regional Climate Downscaling Experiment (CORDEX) for East Asia. All RCMs are forced by the HadGEM2-AO under the historical and representative concentration pathway (RCP) 8.5 scenarios, and are performed at about 50-km resolution over the CORDEX-East Asia domain. In the historical simulations (1980–2005), multi-RCM ensembles yield realistic climatology for TC tracks and genesis frequency during the TC season (June–November), although they show somewhat systematic biases in simulating TC activity. The future (2024–49) projections indicate an insignificant increase in the total number of TC genesis (+5%), but a significant increase in track density over East Asia coastal regions (+17%). The enhanced TC activity over the East Asia coastal regions is mainly related to vertical wind shear weakened by reduced meridional temperature gradient and increased sea surface temperature (SST) at midlatitudes. The future accumulated cyclone energy (ACE) of total TCs increases significantly (+19%) because individual TCs have a longer lifetime (+6.6%) and stronger maximum wind speed (+4.1%) compared to those in the historical run. In particular, the ACE of TCs passing through 25°N increases by 45.9% in the future climate, indicating that the destructiveness of TCs can be significantly enhanced in the midlatitudes despite the total number of TCs not changing greatly.

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Yongkang Xue, Jinjun Ji, Shufen Sun, Guoxiong Wu, K-M. Lau, Isabelle Poccard, Hyun-Suk Kang, Renhe Zhang, John C. Schaake, Jian Yun Zhang, and Yanjun Jiao

Abstract

This is an exploratory study to investigate the spatial and temporal characteristics of east China’s (EC) river runoff and their relationship with precipitation and sea surface temperature (SST) at the continental scale. Monthly mean data from 72 runoff stations and 160 precipitation stations in EC, covering a period between 1951 and 1983, are used for this study. The station river runoff data have been spatially interpolated onto 1° grid boxes as runoff depth based on an extracted drainage network. Comparing runoff depth with precipitation shows that seasonal variation in runoff is consistent with the development of the summer monsoon, including the delayed response of runoff in several subregions. The dominant spatial scales and temporal patterns of summer runoff and precipitation are studied with empirical orthogonal function (EOF) analysis and wavelet analyses. The analyses show interannual, biennial, and longer-term variations in the EOF modes. South–north dipole anomaly patterns for the first two runoff EOF’s spatial distributions have been identified. The first/second runoff principal components (PCs) are highly correlated with the second/first precipitation PCs, respectively. The summer runoff’s EOF PCs also show significant correlations with the multivariate El Niño–Southern Oscillation index (MEI) of the summer and winter months, while the summer precipitation PCs do not. Statistic analysis shows that EOF1 of runoff and EOF2 of precipitation are related to El Niño, while EOF2 of runoff and EOF1 of precipitation are related to a dipole SST anomaly over the northwestern Pacific. The interdecadal relationship between summer runoff, precipitation, and SST variability is further studied by singular value decomposition (SVD) analysis. Pronounced warming (SST) and drying (runoff) trends in first SVD PCs have been identified. These SVDs are used to reconstruct a decadal anomaly pattern, which produces flooding in part of the Chang Jiang River basin and dryness in the northern EC, consistent with observations.

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