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Xiaomin Chen, Kun Zhao, Wen-Chau Lee, Ben Jong-Dao Jou, Ming Xue, and Paul R. Harasti

Abstract

The ground-based velocity track display (GBVTD) was developed to deduce a three-dimensional primary circulation of landfalling tropical cyclones from single-Doppler radar data. However, the cross-beam component of the mean wind cannot be resolved and is consequently aliased into the retrieved axisymmetric tangential wind . Recently, the development of the hurricane volume velocity processing method (HVVP) enabled the independent estimation of ; however, HVVP is potentially limited by the unknown accuracy of empirical assumptions used to deduce the modified Rankine-combined vortex exponent . By combing the GBVTD with HVVP techniques, this study proposes a modified GBVTD method (MGBVTD) to objectively deduce from the GBVTD technique and provide a more accurate estimation of and via an iterative procedure to reach converged and cross-beam component of solutions. MGBVTD retains the strength of both algorithms but avoids their weaknesses. The results from idealized experiments demonstrate that the MGBVTD-retrieved cross-beam component of is within 2 m s−1 of reality. MGBVTD was applied to Hurricane Bret (1999) whose inner core was captured simultaneously by two Weather Surveillance Radar-1988 Doppler (WSR-88D) instruments. The MGBVTD-retrieved cross-beam component of from single-Doppler radar data is very close to that from dual-Doppler radar synthesis using extended GBVTD (EGBVTD); their difference is less than 2 m s−1. The mean difference in the MGBVTD-retrieved from the two radars is ~2 m s−1, which is significantly smaller than that resolved in GBVTD retrievals (~5 m s−1).

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Xuefeng Cui, Hans-F. Graf, Baerbel Langmann, Wen Chen, and Ronghui Huang

Abstract

The hydrological impact of forest removal on the southeast Tibetan Plateau during the second half of the last century is investigated in this study using an atmospheric general circulation model. The effects of deforestation are investigated by examining the differences between the forest replacement and control experiments. Model results demonstrate that deforestation of the southeast Tibetan Plateau would influence the local and the remote climate as well. It would lead to decreased transpiration and increased summer precipitation in the deforested area and a wetter and warmer climate on the Tibetan Plateau in summer. This may produce more runoff into the rivers originating from the Tibetan Plateau and worsen flooding disasters in the downstream areas. The numerical experiments also show that deforestation would remotely impact Asian climate, and even global climate, although the statistical significance is small. A strong drought is found at middle and lower reaches of the Yellow River, where livelihoods and economics have suffered from recent droughts. Ecosystem research on the Tibetan Plateau is a relatively new topic and needs further interdisciplinary investigation.

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FengJiao Chen, ShaoXue Sheng, ZhengQing Bao, HuaYang Wen, LianSheng Hua, Ngarukiyimana Jean Paul, and YunFei Fu

Abstract

Utilizing the cloud parameters derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner and the near-surface rainfall detected by the TRMM Precipitation Radar, the differences of cloud parameters for precipitating clouds (PCs) and nonprecipitating clouds (NPCs) are examined in tropical cyclones (TCs) during daytime from June to September 1998–2010. A precipitation delineation scheme that is based on cloud parameter thresholds is proposed and validated using the independent TC datasets in 2011 and observational datasets from Terra/MODIS. Statistical analysis of these results shows that the differences in the effective radius of cloud particles R e are small for PCs and NPCs, while thick clouds with large cloud optical thickness (COT) and liquid water path (LWP) can be considered as candidates for PCs. The probability of precipitation increases rapidly as the LWP and COT increase, reaching ~90%, whereas the probability of precipitation reaches a peak value of only 30% as R e increases. The combined threshold of a brightness temperature at 10.8 μm (BT4) of 270 K and an LWP of 750 g m−2 shows the best performance for precipitation discrimination at the pixel levels, with the probability of detection (POD) reaching 68.2% and false-alarm ratio (FAR) reaching 31.54%. From MODIS observations, the composite scheme utilizing BT4 and LWP also proves to be a good index, with POD reaching 77.39% and FAR reaching 24.2%. The results from this study demonstrate a potential application of real-time precipitation monitoring in TCs utilizing cloud parameters from visible and infrared measurements on board geostationary weather satellites.

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Junpeng Wen, Ji Chen, Wenshi Lin, Baolin Jiang, Suishan Xu, and Jing Lan

Abstract

This study investigated heavy frontal rainfall that occurred on 13–14 October 2011 over the Pearl River Delta (PRD) in China. The frontal rainstorm was simulated using the WRF-ARW Model (version 3.3), which included its urban canopy model. Although the model-simulated convection occurred 2 h early and the second precipitation peak was underestimated, the model represented the formation, development, and extinction of the frontal rainfall and captured the distribution of the peak value. In addition, the averaged value of 49.7 W m−2 was taken as the anthropogenic heat flux (AHF) of the PRD, and two land-use datasets were adopted: one for 1992 and the other for 2011. The simulation revealed that AHF and urban land-use change (ULUC) increased the total rainfall over the PRD by 6.3% and 7.4% and increased the maximum hourly rainfall intensity by 24.6% and 21.2%, respectively. Furthermore, to elucidate the mechanism of AHF and ULUC influence, the rainstorm structure, low-level jet (LLJ), and CAPE of the rainfall event were analyzed. It was found that AHF and ULUC enhanced two strong southward LLJs located over the urban areas, which carried abundant water vapor to the PRD and generated additional upper-level CAPE. This not only sustained steady ascent of the air, but it also created conditions favorable for downward motion, resulting in large persistent convective clouds and heavy frontal rainfall.

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Hao Huang, Kun Zhao, Guifu Zhang, Qing Lin, Long Wen, Gang Chen, Zhengwei Yang, Mingjun Wang, and Dongming Hu

Abstract

Quantitative precipitation estimation (QPE) with polarimetric radar measurements suffers from different sources of uncertainty. The variational approach appears to be a promising way to optimize the radar QPE statistically. In this study a variational approach is developed to quantitatively estimate the rainfall rate (R) from the differential phase (ΦDP). A spline filter is utilized in the optimization procedures to eliminate the impact of the random errors in ΦDP, which can be a major source of error in the specific differential phase (K DP)-based QPE. In addition, R estimated from the horizontal reflectivity factor (Z H) is used in the a priori with the error covariance matrix statistically determined. The approach is evaluated by an idealized case and multiple real rainfall cases observed by an operational S-band polarimetric radar in southern China. The comparative results demonstrate that with a proper range filter, the proposed variational radar QPE with the a priori included agrees well with the rain gauge measurements and proves to have better performance than the other three approaches, that is, the proposed variational approach without the a priori included, the variational approach proposed by Hogan, and the conventional power-law estimator-based approach.

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Wei-Chyung Wang, Wei Gong, Wen-Shung Kau, Cheng-Ta Chen, Huang-Hsiung Hsu, and Chia-Hsiu Tu

Abstract

Observations indicate that the East Asian summer monsoon (EASM) exhibits distinctive characteristics of large cloud amounts with associated heavy and persistent rainfall, although short breaks for clear sky usually occur. Consequently, the effects of cloud–radiation interactions can play an important role in the general circulation of the atmosphere and, thus, the evolution of the EASM. In this note, as a first step toward studying the topic, the 5-yr (January 1985–December 1989) Earth Radiation Budget Experiment (ERBE) dataset is used to show the spatial and temporal patterns of both shortwave (SW) and longwave (LW) cloud radiative forcing (CRF) at the top of the atmosphere over east China, and to compare the observed features with Atmospheric Model Intercomparison Project-II (AMIP-II) simulations with the University at Albany, State University of New York (SUNYA) Community Climate Model 3 (CCM3) and the ECHAM4 general circulation models.

The observations indicate that the net CRF provides a cooling effect to the atmosphere–surface climate system, dominated by the SW CRF cooling (albedo effect) with partial compensation from the LW CRF warming (greenhouse effect). The SW CRF shows a strong seasonal cycle, and its peak magnitude is particularly large, ∼110 W m−2, for south China and the Yangtze–Huai River valley (YHRV) during May and June, while the LW CRF is about 50 W m−2 for the same months with a weak dependence on the latitudes and seasons. These characteristics are in sharp contrast to the Northern Hemispheric zonal means of the same latitude bands and seasons, thus implying a unique role for cloud–radiation interaction in east China. Both model simulations show similar observed characteristics, although biases exist. For example, in May, the ECHAM4 underestimates the SW CRF while the SUNYA CCM3 simulates a significantly larger value, both attributed to the respective biases in the simulated total cloud cover. Model-to-observation comparisons of the association between total cloud cover and SW CRF, and between high cloud cover and LW CRF, are also presented and their differences are discussed. Finally, the SUNYA CCM3 biases in the CRF and its relevance to the model cloud biases are discussed in the context of model cold and dry biases in climate simulations.

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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Xin Wang, Jun Wen, Martijn J. Booij, Arjen Y. Hoekstra, and Yingying Chen

Abstract

This is the second part of a study on the assessment of the Noah land surface model (LSM) in simulating surface water and energy budgets in the high-elevation source region of the Yellow River. Here, there is a focus on turbulent heat fluxes and heat transport through the soil column during the monsoon season, whereas the first part of this study deals with the soil water flow. Four augmentations are studied for mitigating the overestimation of turbulent heat flux and underestimation of soil temperature measurements: 1) the muting effect of vegetation on the thermal heat conductivity is removed from the transport of heat from the first to the second soil layer, 2) the exponential decay factor imposed on is calculated using the ratio of the leaf area index (LAI) over the green vegetation fraction (GVF), 3) Zilitinkevich’s empirical coefficient for turbulent heat transport is computed as a function of the momentum roughness length , and 4) the impact of organic matter is considered in the parameterization of the thermal heat properties. Although usage of organic matter for calculating improves the correspondence between the estimates and laboratory measurements of heat conductivities, it is shown to have a relatively small impact on the Noah LSM performance even for large organic matter contents. In contrast, the removal of the muting effect of vegetation on and the parameterization of greatly enhances the soil temperature profile simulations, whereas turbulent heat flux and surface temperature computations mostly benefit from the modified formulation. Further, the nighttime surface temperature overestimation is resolved from a coupled land–atmosphere perspective.

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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Xin Wang, Jun Wen, Martijn J. Booij, Arjen Y. Hoekstra, and Yingying Chen

Abstract

This is the first part of a study focusing on evaluating the performance of the Noah land surface model (LSM) in simulating surface water and energy budgets for the high-elevation source region of the Yellow River (SRYR). A comprehensive dataset is utilized that includes in situ micrometeorological and profile soil moisture and temperature measurements as well as laboratory soil property measurements of samples collected across the SRYR. Here, the simulation of soil water flow is investigated, while Part II concentrates on the surface heat flux and soil temperature simulations. Three augmentations are proposed: 1) to include the effect of organic matter on soil hydraulic parameterization via the additivity hypothesis, 2) to implement the saturated hydraulic conductivity as an exponentially decaying function with soil depth, and 3) to modify the vertical root distribution to represent the Tibetan conditions characterized by an abundance of roots in the topsoil. The diffusivity form of Richards’ equation is further revised to allow for the simulation of soil water flow across soil layers with different hydraulic properties. Usage of organic matter for calculating the porosity and soil suction improves the agreement between the estimates and laboratory measurements, and the exponential function together with the Kozeny–Carman equation best describes the in situ . Through implementation of the modified hydraulic parameterization alone, the soil moisture underestimation in the upper soil layer under wet conditions is resolved, while the soil moisture profile dynamics are better captured by also including the modified root distribution.

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Gang Chen, Kun Zhao, Guifu Zhang, Hao Huang, Su Liu, Long Wen, Zhonglin Yang, Zhengwei Yang, Lili Xu, and Wenjian Zhu

Abstract

In this study, the capability of using a C-band polarimetric Doppler radar and a two-dimensional video disdrometer (2DVD) to estimate monsoon-influenced summer rainfall during the Observation, Prediction and Analysis of Severe Convection of China (OPACC) field campaign in 2014 and 2015 in eastern China is investigated. Three different rainfall R estimators, for reflectivity at horizontal polarization [R(Z h)], for reflectivity at horizontal polarization and differential reflectivity factor [R(Z h, Z dr)], and for specific differential phase [R(K DP)], are derived from 2-yr 2DVD observations of summer precipitation systems. The radar-estimated rainfall is compared to gauge observations from eight rainfall episodes. Results show that the two polarimetric estimators, R(Z h, Z dr) and R(K DP), perform better than the traditional Z hR relation [i.e., R(Z h)]. The K DP-based estimator [i.e., R(K DP)] produces the best rainfall accumulations. The radar rainfall estimators perform differently across the three organized convective systems (mei-yu rainband, typhoon rainband, and squall line). Estimator R(Z h) overestimates rainfall in the mei-yu rainband and squall line, and R(Z h, Z dr) mitigates the overestimation in the mei-yu rainband but has a large bias in the squall line. QPE from R(K DP) is the most accurate among the three estimators, but it possesses a relatively large bias for the squall line compared to the mei-yu case. The high variability of drop size distribution (DSD) related to the precipitation microphysics in different types of rain is largely responsible for the case-dependent QPE performance using any single radar rainfall estimator. The squall line has a distinct ice-phase process with a large mean size of raindrops, while the mei-yu rainband and typhoon rainband are composed of smaller raindrops. Based on the statistical QPE error in the Z HZ DR space, a new composite rainfall estimator is constructed by combining R(Z h), R(Z h, Z dr), and R(K DP) and is proven to outperform any single rainfall estimator.

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Weixin Xu, Edward J. Zipser, Yi-Leng Chen, Chuntao Liu, Yu-Chieng Liou, Wen-Chau Lee, and Ben Jong-Dao Jou

Abstract

This study investigates a long-duration mesoscale system with extremely heavy rainfall over southwest Taiwan during the Terrain-influenced Monsoon Rainfall Experiment (TiMREX). This mesoscale convective system develops offshore and stays quasi-stationary over the upstream ocean and southwest coast of Taiwan. New convection keeps developing upstream offshore but decays or dies after moving into the island, dropping the heaviest rain over the upstream ocean and coastal regions. Warm, moist, unstable conditions and a low-level jet (LLJ) are found only over the upstream ocean, while the island of Taiwan is under the control of a weak cold pool. The LLJ is lifted upward at the boundary between the cold pool and LLJ. Most convective clusters supporting the long-lived rainy mesoscale system are initiated and develop along that boundary. The initiation and maintenance is thought to be a “back-building–quasi-stationary” process. The cold pool forms from previous persistent precipitation with a temperature depression of 2°–4°C in the lowest 500 m, while the high terrain in Taiwan is thought to trap the cold pool from spreading or moving. As a result, the orography of Taiwan is “extended” to the upstream ocean and plays an indirect effect on the long-duration mesoscale system.

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