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Yang Zhang, Xiu-Qun Yang, Yu Nie, and Gang Chen

Abstract

Eddy–zonal flow interactions in the annular modes are investigated in this study using a modified beta-plane multilayer quasigeostrophic (QG) channel model. This study shows the different response of high- and low-phase-speed (frequency) eddies to the zonal wind anomalies and suggests a baroclinic mechanism through which the two eddies work symbiotically maintaining the positive eddy feedback in the annular modes. Analysis also indicates that the different roles played by these two eddies in the annular modes are related to the differences in their critical line distributions. Eddies with higher phase speeds experience a low-level critical layer at the center of the jet. They drive the zonal wind anomalies associated with the annular mode but weaken the baroclinicity of the jet in the process. Lower-phase-speed eddies encounter low-level critical lines on the jet flanks. While their momentum fluxes are not as important for the jet shift, they play an important role by restoring the lower-level baroclinicity at the jet center, creating a positive feedback loop with the fast eddies that extends the persistence of the jet shift.

The importance of the lower-level baroclinicity restoration by the low-phase-speed eddies in the annular modes is further demonstrated in sensitivity runs, in which surface friction on eddies is increased to selectively damp the low-phase-speed eddies. For simulations in which the low-phase-speed eddies become inactive, the leading mode of the zonal wind variability shifts from the position fluctuation to a pulsing of the jet intensity. Further studies indicate that the response of the lower-level baroclinicity to the zonal wind anomalies caused by the low-phase-speed eddies can be crucial in maintaining the annular mode–like variations.

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Yongming Wang, Shanhong Gao, Gang Fu, Jilin Sun, and Suping Zhang

Abstract

An extended three-dimensional variational data assimilation (3DVAR) method based on the Weather Research and Forecasting Model (WRF) is developed to assimilate satellite-derived humidity from sea fog at its initial stage over the Yellow Sea. The sea fog properties, including its horizontal distribution and thickness, are retrieved empirically from the infrared and visible cloud imageries of the Multifunctional Transport Satellite (MTSAT). Assuming a relative humidity of 100% in fog, the MTSAT-derived humidity is assimilated by the extended 3DVAR assimilation method. Two sea fog cases, one spread widely over the Yellow Sea and the other spread narrowly along the coast, are first studied in detail with a suite of experiments. For the widespread-fog case, the assimilation of MTSAT-derived information significantly improves the forecast of the sea fog area, increasing the probability of detection and equitable threat scores by about 20% and 15%, respectively. The improvement is attributed to a more realistic representation of the marine boundary layer (MBL) and better descriptions of moisture and temperature profiles. For the narrowly spread coastal case, the model completely fails to reproduce the sea fog event without the assimilation of MTSAT-derived humidity. The extended 3DVAR assimilation method is then applied to 10 more sea fog cases to further evaluate its effect on the model simulations. The results reveal that the assimilation of MTSAT-derived humidity not only improves sea fog forecasts but also provides better moisture and temperature structure information in the MBL.

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Lei Zhang, Gang Wang, Matthew Newman, and Weiqing Han

Abstract

The Indian Ocean has received increasing attention for its large impacts on regional and global climate. However, sea surface temperature (SST) variability arising from Indian Ocean internal processes has not been well understood particularly on decadal and longer time scales, and the external influence from the tropical Pacific has not been quantified. This paper analyzes the interannual-to-decadal SST variability in the tropical Indian Ocean in observations and explores the external influence from the Pacific versus internal processes within the Indian Ocean using a linear inverse model (LIM). Coupling between Indian Ocean and tropical Pacific SST anomalies (SSTAs) is assessed both within the LIM dynamical operator and the unpredictable stochastic noise that forces the system. Results show that the observed Indian Ocean basin (IOB)-wide SSTA pattern is largely a response to the Pacific ENSO forcing, although it in turn has a damping effect on ENSO especially on annual and decadal time scales. On the other hand, the Indian Ocean dipole (IOD) is an Indian Ocean internal mode that can actively affect ENSO; ENSO also has a returning effect on the IOD, which is rather weak on decadal time scale. The third mode is partly associated with the subtropical Indian Ocean dipole (SIOD), and it is primarily generated by Indian Ocean internal processes, although a small component of it is coupled with ENSO. Overall, the amplitude of Indian Ocean internally generated SST variability is comparable to that forced by ENSO, and the Indian Ocean tends to actively influence the tropical Pacific. These results suggest that the Indian–Pacific Ocean interaction is a two-way process.

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Weixing Zhang, Yidong Lou, Jennifer S. Haase, Rui Zhang, Gang Zheng, Jinfang Huang, Chuang Shi, and Jingnan Liu

Abstract

Global positioning system (GPS) data from over 260 ground-based permanent stations in China covering the period from 1 March 1999 to 30 April 2015 were used to estimate precipitable water (PW) above each site with an accuracy of about 0.75 mm. Four types of radiosondes (referred to as GZZ2, GTS1, GTS1-1, and GTS1-2) were used in China during this period. Instrumentation type changes in radiosonde records were identified by comparing PW calculated from GPS and radiosonde data. Systematic errors in different radiosonde types introduced significant biases to the estimated PW trends at stations where more than one radiosonde type was used. Estimating PW trends from reanalysis products (ERA-Interim), which assimilate the unadjusted radiosonde humidity data, resulted in an artificial downward PW trend at almost all stations in China. The statistically significant GPS PW trends are predominantly positive, consistent in sign with the increase in moisture expected from the Clausius–Clapeyron relation due to a global temperature increase. The standard deviations of the differences between ERA-Interim and GPS PW in the summer were 3 times larger than the observational error of GPS PW, suggesting that potentially significant improvements to the reanalysis could be achieved by assimilating denser GPS PW observations over China. This work, based on an entirely independent GPS PW dataset, confirms previously reported significant differences in radiosonde PW trends when using corrected data. Furthermore, the dense geographical coverage of the all-weather GPS PW observations, especially in remote areas in western China, provides a valuable resource for calibrating regional trends in reanalysis products.

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Xiaoye Yang, Gang Zeng, Guwei Zhang, Jingwei Li, Zhongxian Li, and Zhixin Hao

Abstract

The summer heat waves (HWs) in Northeast China (NEC) during 1961–2016 can be classified into two types, namely, wave train HWs and blocking HWs based on the hierarchical clustering algorithm by using ERA-Interim daily datasets. Wave train HWs occurred accompanied by eastward-moving wave trains with a “− + − +” structure formed over Eurasia, while the blocking HWs occurred with blocking circulation anomalies over Eurasia. In general, the blocking HWs could cause the positive temperature anomalies in NEC to last longer than wave train HWs. During the period from 1961 to 2016, the wave train HWs experienced an interdecadal variation from less to more, while the blocking HWs experienced interdecadal variations of less–more–less. Regression analysis and information flow indicate that the interdecadal variation of the wave train HWs is associated with Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO), while the interdecadal variation of the blocking HWs is more likely associated with PDO. The positive phase of AMO (negative phase of PDO) could increase the wave train (blocking) HWs by strengthening the zonal wave train similar to the Silk Road pattern (the arched wave train like the polar–Eurasian pattern). The observed results are in agreement with the numerical experiments with the NCAR Community Atmosphere Model, version 5.3.

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Chao Li, Ying Sun, Francis Zwiers, Dongqian Wang, Xuebin Zhang, Gang Chen, and Hui Wu

Abstract

On the basis of a newly developed observational dataset and a suite of climate model simulations, we evaluate changes in summer mean wet bulb globe temperature (WBGT) in China from 1961 through 2080. We show that summer mean WBGT has increased almost everywhere across China since 1961 as a result of human-induced climate change. Consequently, hot summers as measured by summer mean WBGT are becoming more frequent and more conducive to heat stress. Hot summers like the hottest on record during 1961–2015 in western or eastern China are now expected occur once every 3–4 years. These hot WBGT summers have become more than 140 times as likely in eastern China in the present decade (2010s) as in the 1961–90 baseline period and more than 1000 times as likely in western China. The substantially larger influence in western China is associated with its stronger warming signal, which is likely due to the high Bowen ratio of sensible to latent heat fluxes of dry soils and increases in absorbed solar radiation from the decline in mountain snow cover extent. Observation-constrained projections of future summer mean WBGT under the RCP8.5 emissions scenario indicate that, by the 2040s, almost every summer in China will be at least as hot as the hottest summer in the historical record, and by the 2060s it will be common (on average, every other year) for summers to be as much as 3.0°C hotter than the historical record, pointing to potentially large increases in the likelihood of human heat stress and to a massive adaption challenge.

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Hao Huang, Guifu Zhang, Kun Zhao, Su Liu, Long Wen, Gang Chen, and Zhengwei Yang

Abstract

Drop size distribution (DSD) is a fundamental parameter in rain microphysics. Retrieving DSDs from polarimetric radar measurements extends the capabilities of rain microphysics research and quantitative precipitation estimation. In this study, issues in rain DSD retrieval were studied with simulated and measured data. It was found that a three-parameter gamma distribution model was not suitable for directly retrieving DSD from polarimetric radar measurements. A statistical constraint, such as the shape–slope relation used in the constrained-gamma (C-G) distribution model, helped to reduce the uncertainties and errors in the retrieval. The inclusion of specific differential phase (K DP) measurements resulted in more accurate DSD retrieval and rain physical parameter estimation if the measurement errors were properly characterized in the error minimization analysis (EMA), which was verified using two real precipitation events. The study demonstrated the potential of using full polarimetric radar measurements to improve rain DSD retrieval.

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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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Xiaoyan Zhang, Jianping Huang, Gang Li, Yongwei Wang, Cheng Liu, Kaihui Zhao, Xinyu Tao, Xiao-Ming Hu, and Xuhui Lee

Abstract

The Weather Research and Forecasting (WRF) Model is used in large-eddy simulation (LES) mode to investigate a lake-breeze case occurring on 12 June 2012 over the Lake Taihu region of China. Observational data from 15 locations, wind profiler radar, and the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to evaluate the WRF nested-LES performance in simulating lake breezes. Results indicate that the simulated temporal and spatial variations of the lake breeze by WRF nested LES are consistent with observations. The simulations with high-resolution grid spacing and the LES scheme have a high correlation coefficient and low mean bias when evaluated against 2-m temperature, 10-m wind, and horizontal and vertical lake-breeze circulations. The atmospheric boundary layer (ABL) remains stable over the lake throughout the lake-breeze event, and the stability becomes even stronger as the lake breeze reaches its mature stage. The improved ABL simulation with LES at a grid spacing of 150 m indicates that the non-LES planetary boundary layer parameterization scheme does not adequately represent subgrid-scale turbulent motions. Running WRF fully coupled to a lake model improves lake-surface temperature and consequently the lake-breeze simulations. Allowing for additional model spinup results in a positive impact on lake-surface temperature prediction but is a heavy computational burden. Refinement of a water-property parameter used in the Community Land Model, version 4.5, within WRF and constraining the lake-surface temperature with observational data would further improve lake-breeze representation.

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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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