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Maosi Chen, John Davis, and Wei Gao

Abstract

Cloud screening of direct-beam solar radiation is an essential step for in situ calibration and atmospheric properties retrieval. The internal cloud screening module of a Langley analysis program [Langley Analyzer (LA)] used by the U.S. Department of Agriculture (USDA) UV-B Monitoring and Research Program (UVMRP) is used for screening the uncalibrated direct-beam measurements and for deriving Langley offset voltages for calibration of the UV version of the Multifilter Rotating Shadowband Radiometer (UV-MFRSR). The current LA cloud screening module utilizes data from extended clear-sky periods and tends to ignore shorter periods that typify periods of broken cloudiness, and as a result, fewer values are generated for sites with higher frequencies of cloudy days (cloudy sites). A new cloud screening algorithm is presented that calculates the total optical depth (TOD) difference between a target point and pairs of points, and identifies the target as cloudy if the mean TOD difference exceeds a certain threshold. The screening is an iterative process that finishes when no new cloudy points are found. The result at a typical clear/sunny site shows that values from partly cloudy days are consistent with those from cloud-free days, when the new method is employed. The new cloud screening algorithm picks up significantly more values at cloudy sites. The larger decrease of the annual mean value of at cloudy sites than at relatively clear sites suggests the potential for improving calibration accuracy at cloudy sites. The results also show that the new cloud screening method is capable of detecting clear points in short clear windows and in transitional regions.

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Yanhong Gao, Fei Chen, and Yingsha Jiang

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Precipitation is a critical input to land surface and hydrology modeling and prediction. Dynamical downscale modeling has added value to representing precipitation, when compared with the performance of coarse-resolution reanalysis and global climate models, over the Tibetan Plateau (TP). Convection-permitting modeling (CPM) may even outperform dynamical downscale models (DDMs). In this study, 4-km CPM results were compared to 28-km DDM results for a snow season (1 October 2013–31 May 2014) over the TP. The CPM- and DDM-simulated precipitation, as well as three merged gridded precipitation datasets, were evaluated against in situ observations below 4800 m. The five precipitation datasets (CPM, DDM, CMFD, COPRPH, and TRMM) showed large differences over the TP with underestimation of TRMM and overestimation of CPM and DDM compared to observations. The most significant difference occurred in the Brahmaputra Grand Canyon. Given the substantial uncertainty in observed precipitation at high mountains, snow cover simulated by a high-resolution land data assimilation system was used to indirectly evaluate the above precipitation data using MODIS observations. Simulated snow-cover fraction was greatly underestimated using all the merged precipitation datasets. However, simulations using the DDM- and CPM-generated precipitation as input outperformed those using other gridded precipitation data, showing lower biases, higher pattern correlations, and closer probability distribution functions than runs driven by the merged precipitation. The findings of this study generally support the assumption that high-resolution CPM-produced precipitation has an added value for use in land surface and hydrology simulations in high-mountain regions without reliable in situ precipitation observations.

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Si Gao, Zhifan Chen, and Wei Zhang

Abstract

This study examines the impacts of tropical North Atlantic (TNA) sea surface temperature anomaly (SSTA) on western North Pacific (WNP) landfalling tropical cyclones (TCs). The authors find that TNA SSTA has significant negative correlations with the frequency of TCs making landfall in China, Vietnam, the Korean Peninsula and Japan, and the entirety of East Asia. TNA SSTA influences the frequency of TC landfalls in these regions by regulating TC genesis location and frequency associated with modulated environmental conditions. During cold TNA SST years, larger low-level relative vorticity and weaker vertical wind shear lead to more TC formations over the South China Sea (SCS) and western Philippine Sea (WPS), and larger low-level relative vorticity, higher midlevel relative humidity, and weaker vertical wind shear result in more TC formations over the eastern part of WNP (EWNP). More TCs forming over different regions are important for more TC landfalls in Vietnam (mainly forming over the SCS and WPS), south China (predominantly forming over the SCS), Taiwan (mostly forming over the WPS), and the Korean Peninsula and Japan (forming over the WPS and EWNP). Tracks of these landfalling TCs basically follow the mean steering flow in spite of different directions of steering flow anomalies in the vicinity. The modulation of large-scale environments by TNA SSTA may be through two possible pathways proposed in previous studies: the Indian Ocean relaying effect and the subtropical eastern Pacific relaying effect. The results of this study suggest that TNA SSTA is a potential predictor for the frequency of TCs making landfall in China, Vietnam, the Korean Peninsula and Japan, and the entirety of East Asia.

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Dong Chen, Ya Gao, and Huijun Wang

Abstract

Previous studies have noted that a strong El Niño event occurring in the preceding winter will result in westward stretching of the western North Pacific subtropical high (WPSH) in the following summer, causing anomalously high precipitation in the Yangtze–Huaihe River basin and anomalously low precipitation in southern China. The winters preceding the summers of 1998 and 2016 featured strong El Niño events, which, along with the El Niño event of 1982, represented the strongest El Niño events since 1950. Under these similar El Niño event backgrounds, the July precipitation anomaly in 2016 was similar to that in 1998, but the August precipitation anomalies in the two years featured opposite distributions. According to the atmospheric circulation analysis, we found that an anomalous ascending motion appeared over the Indian Ocean, while an anomalous descending motion appeared over the Pacific Ocean in August 1998. In addition, the WPSH stretched westward over southern China. However, the atmospheric circulation distribution in August 2016 was the opposite of that in 1998, and the WPSH was divided into eastern and western parts by the anomalous western Pacific cyclone. Further analysis showed that the number of tropical cyclones and typhoons over the western Pacific Ocean increased significantly in August 2016, and their activities were concentrated in the South China Sea (SCS)–southern China region and the western Pacific Ocean, resulting in the division of the WPSH. Therefore, the numbers, tracks, and strengths of tropical cyclones and typhoons were responsible for the differences in the anomalous precipitation distributions over the East Asia–Pacific Ocean region between August 2016 and August 1998.

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Yanhong Gao, Jianwei Xu, and Deliang Chen

Abstract

To develop a finescale dataset for the purpose of analyzing historical climatic change over the Tibet Plateau (TP), a high-resolution regional climate simulation for 1979–2011 was conducted using the Weather Research and Forecasting (WRF) Model driven by the ERA-Interim (ERA-Int). This work evaluates the high-resolution (30 km) WRF simulation in terms of annual variation, spatial structure, and 33-yr temporal trends of surface air temperature (Tair) and precipitation (Prec) over the TP, with reference to station observations. Another focus is on the examination of the height–temperature relationship. Inheriting from its forcing, the WRF simulation presents an apparent cold bias in the TP. The cold bias is largely reduced by a lapse rate correction of the simulated surface air temperature with help of the station and model elevations. ERA-Int presents the same sign of Tair and Prec trends as the observations, but with smaller magnitude, especially in the dry season. Compared to its forcing, the WRF simulation improves the simulation of the annual cycles and temporal trends of Tair and Prec in the wet season. In the dry season, however, there is hardly any improvement. The observed Tair presents a downward linear trend in the lapse rate. This feature is examined in the WRF simulation in comparison to ERA-Int. The WRF simulation captures the observed lapse rate and its temporal trend better than ERA-Int. The decreasing lapse rate over time confirms that Tair change in the TP is elevation dependent.

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Ya Gao, Huijun Wang, and Dong Chen

Abstract

The predictability of the dominant modes of summer (June–September) precipitation in the pan-Asian monsoon region is evaluated based on 1-month-lead retrospective forecasts in five state-of-the-art coupled models from the ENSEMBLES project for the period 1979–2005. The results show that the models and their multimodel ensemble mean (MME) perform well in reproducing the interannual variability of the climatology and the spatiotemporal distribution of the first mode of summer precipitation in the pan-Asian monsoon region. The associated oceanic and atmospheric circulation indicators are also well captured, such as the spatiotemporal structures of the simultaneous El Niño–Southern Oscillation (ENSO) and Antarctic Oscillation in the Pacific Ocean (AAOSP). Moreover, the interannual variation of the preceding AAOSP can also be captured by some of the coupled models. For individual models, the ECMWF, Météo-France, and Met Office models exhibit better skill with respect to the first mode of summer precipitation in the pan-Asian monsoon region, which displays a tripole pattern from north to south over 80°–140°E. In addition, these models can successfully predict the intensity and location of the associated ENSO, as well as the simultaneous summer AAOSP distributions. By contrast, the prediction capabilities of the Leibniz Institute of Marine Sciences (IFM-GEOMAR) and Euro-Mediterranean Center for Climate Change (CMCC-INGV) models are relatively weaker. Furthermore, the predictions of the second mode of the summer precipitation in the pan-Asian monsoon region are investigated. Some of the ENSEMBLES models show good capability in predicting the spatiotemporal distribution of the second mode, owing to the successful prediction of the atmospheric convection activities over the tropical Indian Ocean.

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Lu Gao, Jie Huang, Xingwei Chen, Ying Chen, and Meibing Liu

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This study analyzes the variation and risk changes of extreme precipitation under nonstationarity conditions using the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) and the Mann–Kendall (MK) test. The extreme precipitation series is extracted from the observations during the second flood season (July–September) from 1960 to 2012 derived from 86 meteorological stations in the southeastern coastal region of China. The trend of mean (Mn) and variance (Var) of extreme precipitation is detected by MK. Ten large-scale circulation variables and four greenhouse gases are selected to construct a climate change index and a human activity index, which are based on principal component analysis. The recurrence risk of extreme precipitation is calculated by GAMLSS while considering climate changes and human activities. The results demonstrate that the nonstationarity characteristic of extreme precipitation is widespread in this region. A significant increasing trend of Mn is found in Shanghai, eastern Zhejiang, and northern and southern Fujian. An enhanced Var is found in eastern Guangdong. A significant positive correlation exists between climate changes/human activities and Mn/Var, especially in Zhejiang and Fujian. Generally, the contribution of climate changes and human activities to Mn is greater than it is to Var. In this region, the precipitation amount of high-frequency (2-yr return period) and low-frequency (100-yr return period) events increases from inland to coastal and from north to south. The government should pay careful attention to these trends because the intensity of extreme precipitation events and their secondary disasters could result in serious losses.

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Bingcheng Wan, Zhiqiu Gao, Fei Chen, and Chungu Lu

Abstract

This paper combines observations, climatic analysis, and numerical modeling to investigate the Tibetan Plateau’s (TP) surface heating conditions’ influence on extreme persistent precipitation events (PEPEs) in southeastern China. Observations indicated an increase of TP surface air temperature 3–4 days prior to extreme persistent precipitation events in southeastern China. NCEP reanalysis data revealed a significant low pressure anomaly in southern China and a high pressure anomaly in northern China during extreme persistent precipitation event periods. Using correlation analysis and random resampling nonparametric statistics, a typical PEPE event from 17 to 25 June 2010 was selected for numerical simulation. The Weather Research and Forecasting (WRF) Model was used to investigate the impact of the TP’s surface heating on the evolution of this event. Three contrasting WRF experiments were conducted with different surface heating strengths by changing initial soil moisture over the TP. Different soil conditions generate different intensities of surface sensible heat fluxes and boundary layer structures over the TP resulting in two main effects on downstream convective rainfall: modulating large-scale atmospheric circulations and modifying the water vapor transport at southern China. Increased surface heating in the TP strengthens a high pressure system over the Yangtze Plain, thereby blocking the northward movement of precipitation. It also enhances the water vapor transport from the South China Sea to southern China. The combined effects substantially increase precipitation over most of the southeastern China region.

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Si Gao, Langfeng Zhu, Wei Zhang, and Zhifan Chen

Abstract

This study finds a significant positive correlation between the Pacific meridional mode (PMM) index and the frequency of intense tropical cyclones (TCs) over the western North Pacific (WNP) during the peak TC season (June–November). The PMM influences the occurrence of intense TCs mainly by modulating large-scale dynamical conditions over the main development region. During the positive PMM phase, anomalous off-equatorial heating in the eastern Pacific induces anomalous low-level westerlies (and cyclonic flow) and upper-level easterlies (and anticyclonic flow) over a large portion of the main development region through a Matsuno–Gill-type Rossby wave response. The resulting weaker vertical wind shear and larger low-level relative vorticity favor the genesis of intense TCs over the southeastern part of the WNP and their subsequent intensification over the main development region. The PMM index would therefore be a valuable predictor for the frequency of intense TCs over the WNP.

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Lei Liu, Xuejin Sun, Feng Chen, Shijun Zhao, and Taichang Gao

Abstract

Some cloud structure features that can be extracted from infrared images of the sky are suggested for cloud classification. Both the features and the classifier are developed over zenithal images taken by the whole-sky infrared cloud-measuring system (WSIRCMS), which is placed in Nanjing, China. Before feature extraction, the original infrared image was smoothed to suppress noise. Then, the image was enhanced using top-hat transformation and a high-pass filtering. Edges are detected from the enhanced image after adaptive optimization threshold segmentation and morphological edge detection. Several structural features are extracted from the segment image and edge image, such as cloud gray mean value (ME), cloud fraction (ECF), edge sharpness (ES), and cloud mass and gap distribution parameters, including very small-sized cloud mass and gaps (SMG), middle-sized cloud gaps (MG), medium–small-sized cloud gaps (MSG), and main cloud mass (MM). It is found that these features are useful for distinguishing cirriform, cumuliform, and waveform clouds. A simple but efficient supervised classifier called the rectangle method is used to do cloud classification. The performance of the classifier is assessed with an a priori classification carried out by visual inspection of 277 images. The index of agreement is 90.97%.

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