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  • Author or Editor: Wei Wang x
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Wei-Chyung Wang

Abstract

A parameterization for the absorption of solar radiation as a function of the amount of water vapor in the earth's atmosphere is obtained. Absorption computations are based on the Goody band model and the near-infrared absorption band data of Ludwig et al. A two-parameter Curtis-Godson approximation is used to treat the inhomogeneous atmosphere. Heating rates based on a frequently used one-parameter pressure-scaling approximation are also discussed and compared with the present parameterization.

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Lijuan Wang, Hongchao Zuo, and Wei Wang

Abstract

Fengyun-4A (FY-4A) is a geostationary meteorological satellite with four advanced payloads, which can be used to quantitatively detect Earth’s atmospheric system with multispectral and high spatial and temporal resolution. However, the applicable model limits the application of the FY-4A satellite data. In this paper, the empirical statistical model developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is extended for FY-4A Advanced Geosynchronous Radiation Imager (AGRI), and it is applied to observed data to evaluate the applicability of the model for AGRI measurements. To improve the accuracy of radiation estimation, the artificially intelligent particle swarm optimization (PSO) algorithm was used for model optimizing. Results show that the estimated radiation has diurnal variation that is in accord with the characteristics of radiation variation. The estimated net surface shortwave radiation (Sn) and observed values show good correlation. However, large deviations from observations are found in the estimated values when the empirical model based on MODIS is directly used to process AGRI data. Thus, the empirical statistical model based on MODIS can be applied to AGRI data, but the empirical parameters need to be revised. Optimization of the empirical statistical model by the PSO algorithm can effectively improve the accuracy of the radiation estimate. The mean absolute percentage error (MAPE) of Sn estimated by optimized models is reduced to 15%. The MAPE of the net surface longwave radiation (Ln) estimated by optimized models is reduced to 31%, and the MAPE of the net radiation (Rn) estimated by optimized models is reduced to 27%. However, for the uncertainty caused by error accumulation effect, the influence of PSO optimization on Rn is not as obvious as that of Ln. However, the analysis of error distribution shows that PSO optimization does improve the estimation results of Rn. Based on AGRI data, the surface radiation can be estimated simply, and the regional or larger-scale surface radiation retrieval can quickly be realized by this method, which has large application potential and popularization value.

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Wei-Chyung Wang and Gerald A. Domoto

Abstract

A modified two-flux approximation is employed to compute the transfer of radiation in a finite, inhomogeneous, turbid atmosphere. A perturbation technique is developed to allow the treatment of non-gray gaseous absorption with multiple scattering. The perturbation method, which employs a backscatter factor as a parameter, can be used with anisotropic particle scattering as well as Rayleigh scattering.

This method is used to study the effect of aerosols on radiative solar heating and infrared cooling as well as the radiative-convective temperature distribution in the earth's atmosphere. It is found that the effect of aerosols in the infrared cannot be neglected; while in the visible, the effect can be the same order as that due to absorption by water vapor. For a high surface albedo (>0.30) heating of the earth-atmosphere system results due to the presence of aerosols. The aerosols also reduce the amount of convection needed to maintain a stable atmosphere. For the case of a dense haze a temperature inversion is found to exist close to the ground.

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Chuanfeng Zhao, Liping Liu, Qianqian Wang, Yanmei Qiu, Wei Wang, Yang Wang, and Tianyi Fan

Abstract

This study describes the microphysical properties of high ice clouds (with bases above 5 km) using ground-based millimeter cloud radar cirrus-mode observations over the Naqu site of the Tibetan Plateau (TP) during a short period from 6 to 31 July 2014. Empirical regression equations are applied for the cloud retrievals in which the parameters are given on the basis of a review of existing literature. The results show a unimodal distribution for the cloud ice effective radius r e and ice water content with maximum frequencies around 36 μm and 0.001 g m−3, respectively. Analysis shows that clouds with high ice r e are more likely to occur at times from late afternoon until nighttime. The clouds with large (small) r e mainly occur at low (high) heights and are likely orographic cumulus or stratocumulus (thin cirrus). Further analysis indicates that ice r e decreases with increasing height and shows strong positive relationships between ice r e (μm) and depth h (m), with a regression equation of r e = 35.45 + 0.0023h + (1.7 × 10−7)h 2. A good relationship between ice r e and temperature T (°C) is found, r e = 44.65 + 0.1438T, which could serve as a baseline for retrieval of characteristic ice r e properties over the TP.

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Meilin Zhu, Tandong Yao, Wei Yang, Baiqing Xu, and Xiaojun Wang

Abstract

Accurate evaluations of incoming longwave radiation (L in) parameterization have practical implications for glacier and river runoff changes in high-mountain regions of the Tibetan Plateau (TP). To identify potential means of accurately predicting spatiotemporal variations in L in, 13 clear-sky parameterizations combined with 10 cloud corrections for all-sky atmospheric emissivity were evaluated at five sites in high-mountain regions of the TP through temporal and spatial parameter transfer tests. Most locally calibrated parameterizations for clear-sky and all-sky conditions performed well when applied to the calibration site. The best parameterization at five sites is Dilley and O’Brien’s A model combined with Sicart et al.’s A for cloud-correction-incorporated relative humidity. The performance of parameter transferability in time is better than that in space for the same all-sky parameterizations. The performance of parameter transferability in space presents spatial discrepancies. In addition, all all-sky parameterizations show a decrease in performance with increasing altitude regardless of whether the parameters of all-sky parameterizations were recalibrated by local conditions or transferred from other study sites. This may be attributable to the difference between screen-level air temperature and the effective atmospheric boundary layer temperature and to different cloud-base heights. Nevertheless, such worse performance at higher altitudes is likely to change because of terrain, underlying surfaces, and wind systems, among other factors. The study also describes possible spatial characteristics of L in and its driving factors by reviewing the few studies about L in for the mountain regions of the TP.

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Wei-Yu Chang, Jothiram Vivekanandan, and Tai-Chi Chen Wang

Abstract

A variational algorithm for estimating measurement error covariance and the attenuation of X-band polarimetric radar measurements is described. It concurrently uses both the differential reflectivity Z DR and propagation phase ΦDP. The majority of the current attenuation estimation techniques use only ΦDP. A few of the ΦDP-based methods use Z DR as a constraint for verifying estimated attenuation. In this paper, a detailed observing system simulation experiment was used for evaluating the performance of the variational algorithm. The results were compared with a single-coefficient ΦDP-based method. Retrieved attenuation from the variational method is more accurate than the results from a single coefficient ΦDP-based method. Moreover, the variational method is less sensitive to measurement noise in radar observations. The variational method requires an accurate description of error covariance matrices. Relative weights between measurements and background values (i.e., mean value based on long-term DSD measurements in the variational method) are determined by their respective error covariances. Instead of using ad hoc values, error covariance matrices of background and radar measurement are statistically estimated and their spatial characteristics are studied. The estimated error covariance shows higher values in convective regions than in stratiform regions, as expected. The practical utility of the variational attenuation correction method is demonstrated using radar field measurements from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) during 2008’s Southwest Monsoon Experiment/Terrain-Influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX). The accuracy of attenuation-corrected X-band radar measurements is evaluated by comparing them with collocated S-band radar measurements.

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Yongwei Wang, Yaqi Gao, Hairun Qin, Jianping Huang, Cheng Liu, Cheng Hu, Wei Wang, Shoudong Liu, and Xuhui Lee

Abstract

Lake Taihu is a shallow lake located in the Yangtze River delta region in eastern China. Lake breezes and their interactions with urban heat islands are of great importance to air quality and weather forecasting. In this study, surface observations at a dense network and Wind Profile Radar measurements were utilized to characterize the lake breezes at Lake Taihu and assess the impact of geophysical factors on the development and intensity of the lake breezes. The lake breezes were characterized by a low occurrence frequency of 12%–17% (defined as the percentage of days with lake breezes in a given month), weak speed (annual mean ranging from 1.5 to 3.3 m s−1), late onset [average onset around 1110 local standard time (LST), with a range of 0900–1300 LST], short duration (annual mean 3.5 h), and low circulation depth (average depth of 400 m from 1200 to 1400 LST). The lake breezes were greatly suppressed when the geostrophic winds were higher than 4.1 m s−1. The low heat capacity of shallow water (mean depth 2.0 m) led to small temperature differences between the land and the lake, which was the main factor responsible for the low occurrence frequency along Lake Taihu. All of the characteristic parameters showed distinct seasonal variations. Increased frequencies, earlier onset times, and longer durations on the northern lakeshore were indicative of the impact of the urban heat island on the lake breezes.

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Jianqiong Zhan, Wenyuan Chang, Wei Li, Yanming Wang, Liqi Chen, and Jinpei Yan

Abstract

Fujian Province in southeastern coastal China is a relatively clean region with low emissions, as its high altitude isolates it from the rest of the country. However, the region experienced haze episodes on 3–14 December 2013. The authors performed simulations using the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) to examine the impacts of meteorological conditions, aerosol radiative feedbacks (ARFs; including aerosol direct and nearly first indirect effect), and internal and external emissions reduction scenarios on particulate matter smaller than 2.5 μm (PM2.5) concentrations. To the best of the authors’ knowledge, this is the first time the WRF-Chem model has been used to study air quality in this region. The model reasonably reproduced the meteorological conditions and PM2.5 concentrations. The analysis demonstrated that the highest-PM2.5 event was associated with a cold surge that promoted the impingement of northern pollutants on the region, and PM2.5 concentrations were sensitive to the emissions from the Yangtze River delta (16.6%) and the North China Plain (12.1%). This suggests that efforts toward coastal air quality improvement require regional cooperation to reduce emissions. Noticeably, ARFs were unlikely to increase PM2.5 concentrations in the coastal region, which was in contrast to the case in northern China. ARFs induced strong clean wind anomalies in the coastal region and also lowered the inland planetary boundary layer, which enhanced the blocking of northern pollutants crossing the high terrain in the north of Fujian Province. This indicates that ARFs tend to weaken the haze intensity in the southeastern coastal region.

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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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Bradfield Lyon, Michael A. Bell, Michael K. Tippett, Arun Kumar, Martin P. Hoerling, Xiao-Wei Quan, and Hui Wang

Abstract

The inherent persistence characteristics of various drought indicators are quantified to extract predictive information that can improve drought early warning. Predictive skill is evaluated as a function of the seasonal cycle for regions within North America. The study serves to establish a set of baseline probabilities for drought across multiple indicators amenable to direct comparison with drought indicator forecast probabilities obtained when incorporating dynamical climate model forecasts. The emphasis is on the standardized precipitation index (SPI), but the method can easily be applied to any other meteorological drought indicator, and some additional examples are provided. Monte Carlo resampling of observational data generates two sets of synthetic time series of monthly precipitation that include, and exclude, the annual cycle while removing serial correlation. For the case of no seasonality, the autocorrelation (AC) of the SPI (and seasonal precipitation percentiles, moving monthly averages of precipitation) decays linearly with increasing lag. It is shown that seasonality in the variance of accumulated precipitation serves to enhance or diminish the persistence characteristics (AC) of the SPI and related drought indicators, and the seasonal cycle can thereby provide an appreciable source of drought predictability at regional scales. The AC is used to obtain a parametric probability density function of the future state of the SPI that is based solely on its inherent persistence characteristics. In addition, a method is presented for determining the optimal persistence of the SPI for the case of no serial correlation in precipitation (again, the baseline case). The optimized, baseline probabilities are being incorporated into Internet-based tools for the display of current and forecast drought conditions in near–real time.

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