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Guoxing Chen and Wei-Chyung Wang

Abstract

Recently, Chen et al. used a combination of observations and WRF simulations to illustrate that the anthropogenic aerosol–cloud microphysics–radiation interactions over the southeast Pacific can potentially reduce the excessive shortwave radiation reaching the sea surface, a common bias identified in CMIP5 models. Here, with the aid of a mixed-layer ocean, the authors further study the implications of the shortwave radiation reduction to the underlying air–sea coupling, focusing on the SST sensitivity to the changes. Results show that responses of the air–sea coupling include two negative feedbacks (a large decrease in the latent heat flux and a small decrease in the sensible heat flux, both associated with the surface cooling) and a positive feedback (an increase in the cloud cover, caused by the increase in the relative humidity within the boundary layer, especially during the daytime). The 0.1°C (W m−2)−1 SST sensitivity is about half that documented in CMIP5 models. In addition, an effective daytime cloud fraction weighted with the solar diurnal cycle is proposed to facilitate diagnosing the intensity of cloud–radiation interactions in general circulation models.

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Wei Wang and Eric W. Gill

Abstract

The errors in the current radial velocity measurements are examined using Bartlett beamforming and Multiple Signal Classification (MUSIC) direction-finding algorithms with a linear phased array antenna system. A variety of radar and environmental parameters are examined. Suggestions for the optimal choice of operating parameters are proposed. The MUSIC algorithm has shown promising performance in current measurement when beamforming is used to first establish the maximum current velocity. Comparisons of radar field data and current meter measurements show RMS radial velocity differences in magnitude of 7.44 and 6.64 cm s−1 for the Bartlett beamforming and MUSIC–Bartlett algorithms, respectively. The results indicate that there are advantages to using a MUSIC–Bartlett approach in operational applications.

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Wei Wang and Thomas T. Warner

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The Penn State/NCAR mesoscale model has been used in a study of special static- and dynamic-initialization techniques that improve a very-short-range forecast of the heavy convective rainfall that occurred in Texas, Oklahoma and Kansas during 9–10 May 1979, the SESAME IV study period. In this study, the model is initialized during the precipitation event. Two types of four-dimensional data assimilation (FDDA) procedures are used in the dynamic-initialization experiments in order to incorporate data during a 12-hour preforecast period. With the first type, FDDA by Newtonian relaxation is used to incorporate sounding data during the preforecast period. With the second FDDA procedure, radar-based precipitation-rate estimates and hourly raingage data are used to define a three-dimensional latent-heating rate field that contributes to the diabatic heating term in the model's thermodynamic equation during the preforecast period. This latent-heating specification procedure is also employed in static-initialization experiments, where the observed rainfall rate and radar echo pattern near the initial time of the forecast are used to infer a latent-heating rate that is specified in the mesoscale model's thermodynamic equation during the early part of the actual forecast. The precipitation forecasts from these static- and dynamic-initialization experiments are compared with the forecast produced when only operational radiosonde data are used in a conventional static initialization.

The conventional (control) initialization procedure that used only operational radiosonde data produced a precipitation prediction for the first three to four hours of the forecast period that would have been inadequate in an operational setting. Whereas at the initial time of the forecast there was substantial convective precipitation observed in a band near the edge of an elevated mixed layer, the model did not initiate the heavy rainfall until about the fourth hour of the forecast.

The use of the experimental static initialization with prescribed latent heating during the first forecast hour produced greatly improved rainfall rates during the first three to four hours. The success of the technique was shown to be not especially sensitive to moderate variations in the duration, intensity and vertical distribution of the imposed heating. Applications of the Newtonian-relaxation procedure during the preforecast period, that relaxed the model solution toward the initial large-scale analysis, produced a better precipitation forecast than did the control, with a maximum in approximately the correct position, but the intensities were too small. Combined use of either the preforecast or in-forecast latent-heat forcing with the Newtonian relaxation produced an improved forecast of rainfall intensity compared to use of the Newtonian relaxation alone. Even though both the experimental static- and dynamic-initialization procedures produced considerably improved very-short-range precipitation forecasts, compared to the control, the experimental static-initialization procedure that used latent-heat forcing during the first forecast hour did slightly better for this case.

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Wei-Chyung Wang and Kerang Li

Abstract

In recent years the semiarid region of northern China, which has total annual precipitation between 200 and 500 mm, has shown signs of severe desertification. Intensive theoretical and observational studies are currently underway to examine the climate changes and other contributing factors. In this study, we used the 1951–86 monthly precipitation measurements in this region to study their fluctuations and relationship with the El Niño/Southern Oscillation. Three main features are identified: 1) a 2–3 year quasi-periodic fluctuation, 2) a tendency for rainfall deficiency for the whole region during ENSO years, and 3) a significant correlation between the precipitation fluctuation in the southern part of this region and Southern Oscillation index, with the former lagging the latter by 2–5 months. These features are also evident from analysis of the proxy data during the last hundred years. Discussions on the possible link between the precipitation fluctuation, the summer monsoon, the western Pacific subtropical high, and ENSO are also presented.

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Wei Wang and Nelson L. Seaman

Abstract

A comparison study of four cumulus parameterization schemes (CPSs), the Anthes–Kuo, Betts–Miller, Grell, and Kain–Fritsch schemes, is conducted using The Pennsylvania State University–National Center for Atmospheric Research mesoscale model. Performance of these CPSs is examined using six precipitation events over the continental United States for both cold and warm seasons. Grid resolutions of 36 and 12 km are chosen to represent current mesoscale research models and future operational models. The key parameters used to evaluate skill include precipitation, sea level pressure, wind, and temperature predictions. Precipitation is evaluated statistically using conventional skill scores (such as threat and bias scores) for different threshold values based on hourly rainfall observations. Rainfall and other mesoscale features are also evaluated by careful examination of analyzed and simulated fields, which are discussed in the context of timing, evolution, intensity, and structure of the precipitation systems.

It is found that the general 6-h precipitation forecast skill for these schemes is fairly good in predicting four out of six cases examined in this study, even for higher thresholds. The forecast skill is generally higher for cold-season events than for warm-season events. There is an increase in the forecast skill in the 12-km model, and the gain is most obvious in predicting heavier rainfall amounts. The model’s precipitation forecast skill is better in rainfall volume than in either the areal coverage or the peak amount. The scheme with the convective available potential energy–based closure assumption (Kain–Fritsch scheme) appears to perform better. Some systematic behaviors associated with various schemes are also noted wherever possible.

The partition of rainfall into subgrid scale and grid scale is sensitive to the particular parameterization scheme chosen, but relatively insensitive to either the model grid sizes or the convective environments.

The prediction of mesoscale surface features in warm-season cases, such as mesoscale pressure centers, wind-shift lines (gust fronts), and temperature fields, strongly suggests that the CPSs with moist downdrafts are able to predict these surface features more accurately.

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Wei Wang and Rui Xin Huang

Abstract

Wind energy input into the ocean is primarily produced through surface waves. The total rate of this energy source, integrated over the World Ocean, is estimated at 60 TW, based on empirical formulas and results from a numerical model of surface waves. Thus, surface wave energy input is about 50 times the energy input to the surface geostrophic current and 20 times the total tidal dissipation rate. Most of the energy input is concentrated within the Antarctic Circumpolar Current.

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Wei Wang and Rui Xin Huang

Abstract

Wind stress energy input through the surface ageostrophic currents is studied. The surface ageostrophic velocity is calculated using the classical formula of the Ekman spiral, with the Ekman depth determined from an empirical formula. The total amount of energy input over the global oceans for subinertial frequency is estimated as 2.4 TW averaged over a period from 1997 to 2002, or 2.3 TW averaged over a period from 1948 to 2002, based on daily wind stress data from NCEP–NCAR. Thus, in addition to the energy input to the near inertial waves of 0.5–0.7 TW reported by Alford and by Watanabe and Hibiya, the total energy input to the Ekman layer is estimated as 3 TW. This input is concentrated primarily over the Southern Ocean and the storm track in both the North Pacific and North Atlantic Oceans.

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Wei Tan, Xin Wang, Weiqiang Wang, Chunzai Wang, and Juncheng Zuo

Abstract

This study investigates variations of sea surface temperature (SST) anomalies in the South China Sea (SCS) during developing autumn of various El Niño events. The warm SST anomalies are observed in the SCS for canonical El Niño and El Niño Modoki I, whereas the cold SST anomalies are found for El Niño Modoki II. The ocean heat budget analyses show that the latent heat flux change induced by various types of El Niño events is a major contributor to the SCS SST variations. An anomalous anticyclone resides near the Philippine Sea for canonical El Niño and El Niño Modoki I, which induces the southerly wind anomalies over the SCS and thus weakens the climatological northeasterly in boreal autumn. The weakened surface wind speed reduces heat loss from the ocean, leading to a warmer state in the SCS. However, for El Niño Modoki II, the anomalous anticyclone shifts westward to the west of the SCS, and thus the northeasterly wind anomalies appear in the SCS. The northeasterly anomalies enhance the climatological northeasterly monsoon, increase the wind speed, and increase heat loss from the ocean, thus resulting in a cooling in the SCS. The anomalous anticyclone associated with El Niño events also increases shortwave radiation. The increases of the shortwave radiation can also contribute to the SCS warming for canonical El Niño and El Niño Modoki I in addition to the warm effect from the latent heat flux. Because the cooling effect from the latent heat flux is larger than that of the shortwave radiation for El Niño Modoki II, the SCS for El Niño Modoki II tends to be cool.

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Sergey Sokolovskiy, Ying-Hwa Kuo, and Wei Wang

Abstract

Assimilation into numerical weather models of the refractivity, Abel-retrieved from radio occultations, as the local refractivity at ray tangent point may result in large errors in the presence of strong horizontal gradients (atmospheric fronts, strong convection). To reduce these errors, other authors suggested modeling the Abel-retrieved refractivity as a nonlocal linear function of the 3D refractivity, which can be used as a linear observation operator for assimiliation. The authors of this study introduce their approach for the nonlocal linear observation operator, which consists of modeling the excess phase path, calculated along certain trajectories below the top of an atmospheric model. In this study (not aimed at development of an observation operator for any specific atmospheric model), both approaches are validated by assessing the accuracy of both linearized observation operators by numerical simulations with the high-resolution Weather Research and Forecasting (WRF) model and comparing them to the accuracy of interpretation of the Abel-retrieved refractivity as local. Improvement of the accuracy of about an order of magnitude is found with the nonlocal refractivity and further improvement is found with the excess phase path. The effect of horizontal resolution of an atmospheric model on the accuracy of modeling local and nonlocal linear observables is also investigated, and it is demonstrated that the nonlocal linear modeling of radio occultation observables is especially important for weather prediction models with sufficiently high horizontal resolution, grid size <100 km (mesoscale models).

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Yangyang Song, Guoxing Chen, and Wei-Chyung Wang

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The WRF-simulated changes in clouds and climate due to the increased anthropogenic aerosols for the summers of 2002–08 (vs the 1970s) over eastern China were used to offline calculate the radiative forcings associated with aerosol–radiation (AR) and aerosol–cloud–radiation (ACR) interactions, which subsequently facilitated the interpretation of surface temperature changes. During this period, the increases of aerosol optical depth (ΔAOD) averaged over eastern China range from 0.18 in 2004 to 0.26 in 2007 as compared to corresponding cases in the 1970s, and the multiyear means (standard deviations) of AR and ACR forcings at the surface are −6.7 (0.58) and −3.5 (0.63) W m−2, respectively, indicating the importance of cloud changes in affecting both the aerosol climate forcing and its interannual variation. The simulated mean surface cooling is 0.35°C, dominated by AR and ACR with a positive (cooling) feedback associated with changes in meteorology (~10%), and two negative (warming) feedbacks associated with decreases in latent (~70%) and sensible (~20%) heat fluxes. More detailed spatial characteristics were analyzed using ensemble simulations for the year 2008. Three regions—Jing-Jin-Ji (ΔAOD ~ 0.63), Sichuan basin (ΔAOD ~ 0.31), and middle Yangtze River valley (ΔAOD ~ 0.26)—at different climate regimes were selected to investigate the relative roles of AR and ACR. While the AR forcing is closely related to ΔAOD values, the ACR forcing presents different regional characteristics owing to cloud changes. In addition, the surface heat flux feedbacks are also different between regions. The study thus illustrates that ACR forcing is useful as a diagnostic parameter to unravel the complexity of climate change to aerosol forcing over eastern China.

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