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Chih-Chiang Wei, Gene Jiing-Yun You, Li Chen, Chien-Chang Chou, and Jinsheng Roan

Abstract

Rainfall is a fundamental process in the hydrologic cycle. This study investigated the cause–effect relationship in which precipitation at lower frequencies affects the amount of emitted radiation and at higher frequencies affects the amount of backscattered terrestrial radiation. Because the advantage of a probabilistic graphical model is its graphical representation, which allows easy causality interpretation using the arc directions, two Bayesian networks (BNs) were used, namely, a naïve Bayes classifier and a tree-augmented naïve Bayes model. To empirically evaluate and compare BN-based models, “black box”–based models, including nearest-neighbor searches and artificial neural network (ANN)-based multilayer perceptron and logistic regression, were used as benchmarks. For the two study regions—namely, the Tanshui River basin in northern Taiwan and Chianan Plain in southern Taiwan—rain occurrences during typhoon seasons were examined using passive microwave imagery recorded using the Special Sensor Microwave Imager/Sounder. The results show that although black box models exhibit excellent prediction ability, interpretation of their behavior is unsatisfactory. By contrast, probabilistic graphical models can explicitly reveal the causal relationship between brightness temperatures and nonrain/rain discrimination. For the Tanshui River basin, 19.35-, 22.23-, 37.0-, and 85.5-GHz vertically polarized brightness temperatures were found to diagnose rain occurrences. For the Chianan Plain, a more sensitive indicator of rain-scattering signals was obtained using 85-GHz measurements. The results demonstrate the potential use of BNs in identifying rain occurrences in regions with land features comprising various absorbing and scattering materials.

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Tae-Kwon Wee, Ying-Hwa Kuo, Dong-Kyou Lee, Zhiquan Liu, Wei Wang, and Shu-Ya Chen

Abstract

The authors have discovered two sizeable biases in the Weather Research and Forecasting (WRF) model: a negative bias in geopotential and a warm bias in temperature, appearing both in the initial condition and the forecast. The biases increase with height and thus manifest themselves at the upper part of the model domain. Both biases stem from a common root, which is that vertical structures of specific volume and potential temperature are convex functions. The geopotential bias is caused by the particular discrete hydrostatic equation used in WRF and is proportional to the square of the thickness of model layers. For the vertical levels used in this study, the bias far exceeds the gross 1-day forecast bias combining all other sources. The bias is fixed by revising the discrete hydrostatic equation. WRF interpolates potential temperature from the grids of an external dataset to the WRF grids in generating the initial condition. Associated with the Exner function, this leads to the marked bias in temperature. By interpolating temperature to the WRF grids and then computing potential temperature, the bias is removed. The bias corrections developed in this study are expected to reduce the disparity between the forecast and observations, and eventually to improve the quality of analysis and forecast in the subsequent data assimilation. The bias corrections might be especially beneficial to assimilating height-based observations (e.g., radio occultation data).

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Shuyi S. Chen, Wei Zhao, Mark A. Donelan, and Hendrik L. Tolman

Abstract

The extreme high winds, intense rainfall, large ocean waves, and copious sea spray in hurricanes push the surface-exchange parameters for temperature, water vapor, and momentum into untested regimes. The Coupled Boundary Layer Air–Sea Transfer (CBLAST)-Hurricane program is aimed at developing improved coupling parameterizations (using the observations collected during the CBLAST-Hurricane field program) for the next-generation hurricane research prediction models. Hurricane-induced surface waves that determine the surface stress are highly asymmetric, which can affect storm structure and intensity significantly. Much of the stress is supported by waves in the wavelength range of 0.1–10 m, which is the unresolved “spectral tail” in present wave models. A directional wind–wave coupling method is developed to include effects of directionality of the wind and waves in hurricanes. The surface stress vector is calculated using the two-dimensional wave spectra from a wave model with an added short-wave spectral tail. The wind and waves are coupled in a vector form rather than through the traditional roughness scalar. This new wind–wave coupling parameterization has been implemented in a fully coupled atmosphere–wave–ocean model with 1.67-km grid resolution in the atmospheric model, which can resolve finescale features in the extreme high-wind region of the hurricane eyewall. It has been tested in a number of storms including Hurricane Frances (2004), which is one of the best-observed storms during the CBLAST-Hurricane 2004 field program. This paper describes the new wind–wave coupling parameterization and examines the characteristics of the coupled model simulations of Hurricane Frances (2004). Observations of surface waves and winds are used to evaluate the coupled model results.

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George Tai-Jen Chen, Chung-Chieh Wang, and David Ta-Wei Lin

Abstract

The present study investigates the characteristics of low-level jets (LLJs) (≥12.5 m s−1) below 600 hPa over northern Taiwan in the mei-yu season and their relationship to heavy rainfall events (≥50 mm in 24 h) through the use of 12-h sounding data, weather maps at 850 and 700 hPa, and hourly rainfall data at six surface stations during the period of May–June 1985–94. All LLJs are classified based on their height, appearance (single jet or double jet), and movement (migratory and nonmigratory). The frequency, vertical structure, and spatial and temporal distribution of LLJs relative to the onset of heavy precipitation are discussed.

Results on the general characteristics of LLJs suggest that they occurred about 15% of the time in northern Taiwan, with a top speed below 40 m s−1. The level of maximum wind appeared mostly between 850 and 700 hPa, with highest frequency at 825–850 hPa. A single jet was observed more often (76%) than a double jet (24%), while in the latter case a barrier jet usually existed at 900–925 hPa as the lower branch.

Migratory and nonmigratory LLJs each constituted about half of all cases, and there existed no apparent relationship between their appearance and movement. Migratory LLJs tended to be larger in size, stronger over a thicker layer, more persistent, and were much more closely linked to heavy rainfall than nonmigratory jets. They often formed over southern China between 20° and 30°N and moved toward Taiwan presumably along with the mei-yu frontal system.

Before and near the onset of the more severe heavy rain events (≥100 mm in 24 h) in northern Taiwan, there was a 94% chance that an LLJ would be present over an adjacent region at 850 hPa, and 88% at 700 hPa, in agreement with earlier studies. Occurrence frequencies of LLJs for less severe events (50–100 mm in 24 h) were considerably lower, and the difference in accumulative rainfall amount was seemingly also affected by the morphology of the LLJs, including their strength, depth, elevation of maximum wind, persistence, proximity to northern Taiwan, source region of moisture, and their relative timing of arrival before rainfall. During the data period, about 40% of all migratory LLJs at 850 or 700 hPa passing over northern Taiwan were associated with heavy rainfall within the next 24 h. The figure, however, was much lower compared to earlier studies, and some possible reasons are offered to account for this deficit.

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Wei Chen, Michael L. Banner, Edward J. Walsh, Jorgen B. Jensen, and Sunhee Lee

Abstract

The Southern Ocean Waves Experiment (SOWEX) was an international collaborative air–sea interaction experiment in which a specially instrumented meteorological research aircraft simultaneously gathered marine boundary-layer atmospheric turbulence data and sea surface roughness data over the Southern Ocean, particularly for gale-force wind conditions. In this paper analysis and findings are presented on key aspects of the coupled variability of the wind field, the wind stress, and the underlying sea surface roughness. This study complements the overview, methodology, and mean results published in Part I.

Weakly unstable atmospheric stratification conditions prevailed during SOWEX, with wind speeds ranging from gale force to light and variable. Throughout the SOWEX observational period, the wind field was dominated by large-scale atmospheric roll-cell structures, whose height scale was comparable with the thickness of the marine atmospheric boundary layer (MABL). Well above the sea surface, these coherent structures provide the dominant contribution to the downward momentum flux toward the sea surface. Closer to the sea surface, these organized large-scale structures continued to make significant contributions to the downward momentum flux, even within a few tens of meters of the sea surface.

At the minimum aircraft height, typical cumulative stress cospectra indicated that 10-km averages along crosswind tracks appeared adequate to close the stress cospectrum. Nevertheless, a large-scale spatial inhomogeneity in the wind stress vector was observed using 10- and 20-km spatial averaging intervals on one of the strongest wind days when the mean wind field was close to being spatially uniform. This indicates a departure from the familiar drag coefficient relationship and implies large-scale transverse modulations in the MABL with an effective horizontal to vertical aspect ratio of around 20.

A high visual correlation was found between mean wind speed variations and collocated sea-surface mean square slope (mss) variations, averaged over 1.9 km. A comparable plot of the 10-km running average of the downward momentum flux, observed at heights from 30 to 90 m, showed appreciably lower visual correlation with the wind speed variations and mss variations. The 10–20 km averaging distance needed to determine the wind stress was larger than the local scale of variation of the mss roughness variations. It also exceeded the scale of the striations often observed in synthetic aperture radar imagery under unstable atmospheric conditions and strong wind forcing. This highlights an overlooked intrinsic difficulty in using the friction velocity as the wind parameter in models of the wind wave spectrum, especially for the short wind wave scales.

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Yanzhou Wei, Sarah T. Gille, Matthew R. Mazloff, Veronica Tamsitt, Sebastiaan Swart, Dake Chen, and Louise Newman

Abstract

Proposals from multiple nations to deploy air–sea flux moorings in the Southern Ocean have raised the question of how to optimize the placement of these moorings in order to maximize their utility, both as contributors to the network of observations assimilated in numerical weather prediction and also as a means to study a broad range of processes driving air–sea fluxes. This study, developed as a contribution to the Southern Ocean Observing System (SOOS), proposes criteria that can be used to determine mooring siting to obtain best estimates of net air–sea heat flux (Q net). Flux moorings are envisioned as one component of a multiplatform observing system, providing valuable in situ point time series measurements to be used alongside satellite data and observations from autonomous platforms and ships. Assimilating models (e.g., numerical weather prediction and reanalysis products) then offer the ability to synthesize the observing system and map properties between observations. This paper develops a framework for designing mooring array configurations to maximize the independence and utility of observations. As a test case, within the meridional band from 35° to 65°S we select eight mooring sites optimized to explain the largest fraction of the total variance (and thus to ensure the least variance of residual components) in the area south of 20°S. Results yield different optimal mooring sites for low-frequency interannual heat fluxes compared with higher-frequency subseasonal fluxes. With eight moorings, we could explain a maximum of 24.6% of high-frequency Q net variability or 44.7% of low-frequency Q net variability.

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Wanxin Zhang, Haishan Chen, Liming Zhou, Botao Zhou, Jie Zhang, and Jiangfeng Wei

Abstract

Previous studies detected significant negative correlations between the nonuniform land surface warming and the decadal weakened activities of the summer extratropical cyclones (ECs) over East Asia and the East Asian summer monsoon (EASM) after the early 1990s. Here such relationships are further examined and the possible mechanisms are explored via numerical sensitivity experiments with a regional climate model (RegCM4.5). The positive/negative sensible heat flux (SH) anomalies were added as a forcing to a key region near 50°N of East Asia in RegCM4.5 to simulate the observed ground surface temperature (GST) anomalies. The model results suggest that the nonuniform land surface warming over the Lake Baikal area (50°–60°N, 90°–120°E) can indeed cause the weakening of the extratropical cyclogenesis and affect the decadal weakening of the EASM. Warm (cold) GST forcing over the key GST region can lead to decreasing (increasing) atmospheric baroclinicity and related energy conversion of the EC activity over the key EC region (40°–50°N, 90°–120°E), resulting in an evidently weakening (enhancing) of the ECs over East Asia. Meanwhile, precipitation shows a dipole pattern with significantly suppressed (enhanced) precipitation in northern and northeastern China, and slightly enhanced (suppressed) rainfall south of 40°N of East Asia, mainly over the East China Sea. Lake Baikal and its adjacent areas are occupied by a strong anticyclonic (cyclonic) circulation while the southeast coastal areas of China have a relatively weak cyclonic (anticyclonic) circulation accompanied with an anomalous northeasterly (southwesterly) wind to the southeast of the anticyclonic circulation, which is opposite to (coincident with) the atmospheric circulation anomalies that are associated with the second mode of the EASM.

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Wenping Jiang, Gang Huang, Ping Huang, Renguang Wu, Kaiming Hu, and Wei Chen

Abstract

This study investigates the characteristics and maintaining mechanisms of the anomalous northwest Pacific anticyclone (NWPAC) following different El Niño decaying paces. In fast decaying El Niño summers, the positive SST anomalies in the tropical central-eastern Pacific (TCEP) have transformed to negative, and positive SST anomalies appear around the Maritime Continent (MC), whereas in slow decaying El Niño summers, positive SST anomalies are present in the TCEP and in the tropical Indian Ocean (TIO). During fast decaying El Niño summers, the cold Rossby wave in response to the negative TCEP SST anomalies has a primary contribution to maintaining the NWPAC anomalies. The warm Kelvin wave response and enhanced Hadley circulation anomalies forced by the positive MC SST anomalies also facilitate developing the NWPAC anomalies. During slow decaying El Niño summers, the warm Kelvin wave anchored over the TIO plays a crucial role in sustaining the NWPAC anomalies, while the warm Rossby wave triggered by the positive TCEP SST anomalies weakens the western part of the NWPAC anomalies. The southwesterly anomalies of the NWPAC anomalies during fast decaying El Niño summers can reach to higher latitudes than those during slow decaying El Niño summers. Correspondingly, positive rainfall anomalies appear in northern China and the Yangtze River basin in fast decaying El Niño summers but are only distributed in the Yangtze River basin in slow decaying El Niño summers. This study implies that the El Niño decaying pace is a key factor in East Asian summer climate.

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Chunpeng Wang, Zhengzhao Johnny Luo, Xiuhong Chen, Xiping Zeng, Wei-Kuo Tao, and Xianglei Huang

Abstract

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

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Shuyi S. Chen, James F. Price, Wei Zhao, Mark A. Donelan, and Edward J. Walsh
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