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Wenguang Wei, Zhongwei Yan, and P. D. Jones

Abstract

The potential predictability of seasonal extreme precipitation accumulation (SEPA) across mainland China is evaluated, based on daily precipitation observations during 1960–2013 at 675 stations. The potential predictability value (PPV) of SEPA is calculated for each station by decomposing the observed SEPA variance into a part associated with stochastic daily rainfall variability and another part associated with longer-time-scale climate processes. A Markov chain model is constructed for each station and a Monte Carlo simulation is applied to estimate the stochastic part of the variance. The results suggest that there are more potentially predictable regions for summer than for the other seasons, especially over southern China, the Yangtze River valley, the north China plain, and northwestern China. There are also regions of large PPVs in southern China for autumn and winter and in northwestern China for spring. The SEPA series for the regions of large PPVs are deemed not entirely stochastic, either with long-term trends (e.g., increasing trends in inland northwestern China) or significant correlation with well-known large-scale climate processes (e.g., East Asian winter monsoon for southern China in winter and El Niño for the Yangtze River valley in summer). This fact not only verifies the claim that the regions have potential predictability but also facilitates predictive studies of the regional extreme precipitation associated with large-scale climate processes.

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Qing Yan, Ting Wei, and Zhongshi Zhang

Abstract

Simulations of past warm climate provide an opportunity to better understand how the climate system may respond to increased greenhouse gas emissions. Using the ~25-km-resolution Community Atmosphere Model, version 4 (CAM4), we examine climate change over China in the Late Pliocene warm period (3.264–3.025 Ma) and further explore the influences of different sea surface temperature (SST) forcings and model horizontal resolutions. Initial evaluation shows that the high-resolution CAM4 performs well in capturing the climatological distribution of present-day temperature, precipitation, and low-level monsoon circulations over China. Based on the standard Pliocene Research, Interpretation and Synoptic Mapping (version 4; PRISM4) boundary conditions, CAM4 predicts an increase of annual mean temperature by ~0.5°C over China in the Late Pliocene relative to the preindustrial era, with the greatest warming in northwest China but cooling in southwest China. Enhanced annual mean precipitation is observed in the Late Pliocene over most of China except for northwest China where precipitation is decreased. The East Asian summer (winter) monsoon is intensified (weakened) in the Late Pliocene as suggested by geological evidence, which is attributed to the enhanced (reduced) land–sea thermal contrast. The East Asian monsoon domain exhibits a northwestward expansion in the Late Pliocene, especially over the Tibetan Plateau. Additionally, our results indicate that the modeled climate change is sensitive to the Late Pliocene SST forcings and model resolution. Particularly, different SST forcings [PRISM4-based vs Pliocene Model Intercomparison Project (PlioMIP)-based SSTs] affect the modeled phase change of summer monsoon and the associated precipitation change, while model resolution (~25 vs 400 km) mainly impacts precipitation change.

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Rui Wang, Xin Yan, Zhenguo Niu, and Wei Chen

Abstract

Water surface temperature is a direct indication of climate change. However, it is not clear how China’s inland waters have responded to climate change in the past using a consistent method on a national scale. In this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2015 to study the temporal and spatial variation characteristics of water surface temperature in China using the wavelet transform method. The results showed the following: 1) the freezing date of China inland water has shown a significant delaying trend during the past 16 years with an average rate of −1.5 days yr−1; 2) the shift of the 0°C isotherm position of surface water across China has clear seasonal changes, which first moved eastward about 25° and northward about 15°, and then gradually moved back after the year 2009; 3) during the past 16 years, the 0°C isotherm of China’s surface water has gradually moved north by about 0.09° in the latitude direction and east by about 1° in the longitude direction; and 4) the interannual variation of water surface temperature in 17 lakes of China showed a similar fluctuation trend that increased before 2010, and then decreased. The El Niño and La Niña around 2010 could have impacts on the turning point of the annual variation of water surface temperature. This study validated the response of China’s inland surface water to global climate change and improved the understanding of the wetland environment’s response to climate change.

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Hongbo Zhang, Fan Zhang, Tao Che, Wei Yan, and Ming Ye

Abstract

Though the use of reanalysis datasets to analyze snow changes is increasingly popular, the snow depth variability in China simulated by multiple reanalysis datasets has not been well evaluated. Also, the extent of regional snow depth variability and its driving mechanisms are still unknown. In this study, monthly snow depth observations from 325 stations during the period of 1981–2018 were taken to evaluate the ability of five reanalysis datasets (JRA55, MERRA2, GLDAS2, ERA5, and ERA5L) to simulate the spatial and temporal variability of snow depth in China. The evaluation results indicate that MERRA2 has the lowest root-mean-square deviation of snow depth and a high spatial correlation coefficient with observations. This may be partly related to the high accuracy of precipitation and temperature in MERRA2. Also, the 31 combinations of the five reanalysis datasets do not yield better accuracy in snow depth than MERRA2 alone. This is because the other four datasets have larger uncertainty. Based on MERRA2, four hotspot regions with significant snow depth changes from 1981–2018 were identified, including the central Xinjiang (XJ-C), the southern part of the Northeastern Plain and Mountain (NPM-S), and the southwestern (TP-SW) and southeastern (TP-SE) of the Tibetan Plateau. Snow depth changes mostly occurred in spring in TP-SW and winter in XJ-C, NPM-S, and TP-SE. The snow depth increase in XJ-C, NPM-S, and TP-SW is mainly caused by increased seasonal precipitation, while the snow depth decrease in TP-SE is attributed to the combined effects of decreased precipitation and warming temperature in winter.

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Di Tian, Wenjie Dong, Xiaodong Yan, Jieming Chou, Shili Yang, Ting Wei, Han Zhang, Yan Guo, Xiaohang Wen, and Zhiyong Yang

Abstract

Global warming as quantified by surface air temperature has been shown to be approximately linearly related to cumulative emissions of CO2. Here, a coupled state-of-the-art Earth system model with an interactive carbon cycle (BNU-ESM) was used to investigate whether this proportionality extends to the complex Earth system model and to examine the climate system responses to different emission pathways with a common emission budget of man-made CO2. These new simulations show that, relative to the lower emissions earlier and higher emissions later (LH) scenario, the amount of carbon sequestration by the land and the ocean will be larger and Earth will experience earlier warming of climate under the higher emissions earlier and lower emissions later (HL) scenario. The processes within the atmosphere, land, and cryosphere, which are highly sensitive to climate, show a relatively linear relationship to cumulative CO2 emissions and will attain similar states under both scenarios, mainly because of the negative feedback between the radiative forcing and ocean heat uptake. However, the processes with larger internal inertias depend on both the CO2 emissions scenarios and the emission budget, such as ocean warming and sea level rise.

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Yue Wu, Xiao-Tong Zheng, Qi-Wei Sun, Yu Zhang, Yan Du, and Lin Liu

Abstract

Ocean salinity plays a crucial role in the upper-ocean stratification and local marine ecosystem. This study reveals that ocean salinity presents notable decadal variability in upper 200 m over the southeast Indian Ocean (SEIO). Previous studies linked this salinity variability with precipitation anomalies over the Indo-Pacific region modulated by the tropical Pacific decadal variability. Here we conduct a quantitative salinity budget analysis and show that, in contrast, oceanic advection, especially the anomalous meridional advection, plays a dominant role in modulating the SEIO salinity on the decadal time scale. The anomalous meridional advection is mainly associated with a zonal dipole pattern of sea level anomaly (SLA) in the south Indian Ocean (SIO). Specifically, positive and negative SLAs in the east and west of the SIO correspond to anomalous southward oceanic current, which transports much fresher seawater from the warm pool into the SEIO and thereby decreases the local upper-ocean salinity, and vice versa. Further investigation reveals that the local anomalous wind stress curl associated with tropical Pacific forcing is responsible for generating the sea level dipole pattern via oceanic Rossby wave adjustment on decadal time scale. This study highlights that the local ocean–atmosphere dynamical adjustment is critical for the decadal salinity variability in the SEIO.

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Shensen Hu, Shuo Ma, Wei Yan, Neil P. Hindley, Kai Xu, and Jun Jiang

Abstract

Atmospheric gravity waves are a kind of mesoscale disturbance, commonly found in the atmospheric system, that plays a key role in a series of mesospheric dynamic processes. When propagating to the upper atmosphere, the gravity waves will disturb the local temperature and density, and then modulate the intensity of the surrounding airglow radiation. As a result, the presence of gravity waves on a moonless night can usually cause the airglow to reveal ripple features in low-light images. In this paper we have applied a two-dimensional Stockwell transform technique (2DST) to airglow measurements from nighttime low-light images of the day–night band on the Suomi National Polar-Orbiting Partnership. To our knowledge this study is the first to measure localized mesospheric gravity wave brightness amplitudes, horizontal wavelengths, and propagation directions using such a method and data. We find that the method can characterize the general shape and amplitude of concentric gravity wave patterns, capturing the dominant features and directions with a good degree of accuracy. The key strength of our 2DST application is that our approach could be tuned and then automated in the future to process tens of thousands of low-light images, globally characterizing gravity wave parameters in this historically poorly studied layer of the atmosphere.

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Lingsheng Meng, Wei Zhuang, Weiwei Zhang, Angela Ditri, and Xiao-Hai Yan

Abstract

Sea level changes within wide temporal–spatial scales have great influence on oceanic and atmospheric circulations. Efforts have been made to identify long-term sea level trend and regional sea level variations on different time scales. A nonuniform sea level rise in the tropical Pacific and the strengthening of the easterly trade winds from 1993 to 2012 have been widely reported. It is well documented that sea level in the tropical Pacific is associated with the typical climate modes. However, sea level change on interannual and decadal time scales still requires more research. In this study, the Pacific sea level anomaly (SLA) was decomposed into interannual and decadal time scales via an ensemble empirical mode decomposition (EEMD) method. The temporal–spatial features of the SLA variability in the Pacific were examined and were closely associated with climate variability modes. Moreover, decadal SLA oscillations in the Pacific Ocean were identified during 1993–2016, with the phase reversals around 2000, 2004, and 2012. In the tropical Pacific, large sea level variations in the western and central basin were a result of changes in the equatorial wind stress. Moreover, coherent decadal changes could also be seen in wind stress, sea surface temperature (SST), subtropical cells (STCs), and thermocline depth. Our work provided a new way to illustrate the interannual and decadal sea level variations in the Pacific Ocean and suggested a coupled atmosphere–ocean variability on a decadal time scale in the tropical region with two cycles from 1993 to 2016.

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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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Jun Jiang, Wei Yan, Shuo Ma, Yangyang Jie, Xiarong Zhang, Shensen Hu, Lei Fan, and Linyu Xia

Abstract

The day–night band (DNB) low-light-level visible sensor, mounted on the Suomi–National Polar-Orbiting Partnership (SNPP) satellite, can measure visible radiances from the earth and atmosphere (solar/lunar reflection, and natural/anthropogenic nighttime light emissions) during both day and night and can achieve unprecedented nighttime low-light-level imaging with its accurate radiometric calibration and fine spatiotemporal resolution. Based on the good characteristics of DNB, a multichannel threshold (MCT) algorithm combining DNB with other Visible–Infrared Imager–Radiometer Suite (VIIRS) channels is proposed to monitor nighttime fog/low stratus. Through a gradual separation of the underlying surface (land, vegetation, water bodies, and city lights), snow, and high/medium clouds, a fog/low-stratus region can ultimately be extracted by the algorithm. Then, the algorithmic feasibility is verified by three typical cases of heavy fog/low stratus in China. The experimental results demonstrate that the outcomes of the MCT algorithm approximately coincide with the ground-measured results. Furthermore, the MCT algorithm shows promise for nighttime fog/low-stratus detection in some example cases with about a 0.84 average probability of detection (POD), a 0.73 average critical success index (CSI), and a 0.15 average false alarm ratio (FAR), which reveals some improvement over the conventional dual-channel difference (DCD) algorithm.

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