Processes of intraseasonal snow cover variations over the eastern China during boreal winter

This study reveals that the dominant time scale of intraseasonal snow cover variation over the eastern China is within 30 days by using the latest satellite snow cover data from the moderate resolution imaging spectroradiometer (MODIS)/Terra product. The leading empirical orthogonal function (EOF) mode of 10–30‐day snow cover variation during boreal winter from 2004 to 2018 over the eastern China has two centers: northwest part of the eastern China and north of the Yangtze River. Composite analysis based on 25 snow events identified from normalized leading principal time series (PC1) indicates that the southeastward intrusion of surface anticyclonic anomalies and accompanying low temperature anomalies provide the temperature condition for snow events. Negative Arctic Oscillation induces mid‐latitude wave train and leads to the development of surface anticyclonic anomalies and upper‐level cyclonic anomalies over East Asia. The cyclonic anomalies induce ascending motion and anomalous convergence of water vapor fluxes over the eastern China, which supplies moisture for snowfall.(a) Time evolution of composite NAO index (pink curve), AO index (blue curve), regional mean surface air temperature anomalies (°C) (black curve) and snow cover anomalies (%) (red curve) in the region of 20–40°N, 105–120°E. (b) Time evolution of composite anomalies of regional mean snow cover tendency (%/day) (black curve), vertical velocity (Pa/s) (blue curve), and divergence of water vapor flux integral from 1,000 to 100‐hPa (*10−6 kg/(m2*s)) (pink curve) in the region of 20–40°N, 105–120°E. Dots on the curves indicate anomalies significant at the 95% confidence level.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149343/1/asl2901_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149343/2/asl2901.pd

Time-frequency analysis framework for understanding non-stationary and multi-scale characteristics of sea-level dynamics

Rising sea level caused by global climate change may increase extreme sea level events, flood low-lying coastal areas, change the ecological and hydrological environment of coastal areas, and bring severe challenges to the survival and development of coastal cities. Hong Kong is a typical economically and socially developed coastal area. However, in such an important coastal city, the mechanisms of local sea-level dynamics and their relationship with climate teleconnections are not well explained. In this paper, Hong Kong tide gauge data spanning 68 years was documented to study the historical sea-level dynamics. Through the analysis framework based on Wavelet Transform and Hilbert Huang Transform, non-stationary and multi-scale features in sea-level dynamics in Hong Kong are revealed. The results show that the relative sea level (RSL) in Hong Kong has experienced roughly 2.5 cycles of high-to-low sea-level transition in the past half-century. The periodic amplitude variation of tides is related to Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO). RSL rise and fall in eastern Hong Kong often occur in La Niña and El Niño years, respectively. The response of RSL to the PDO and ENSO displays a time lag and spatial heterogeneity in Hong Kong. Hong Kong's eastern coastal waters are more strongly affected by the Pacific climate and current systems than the west. This study dissects the non-stationary and multi-scale characteristics of relative sea-level change and helps to better understand the response of RSL to the global climate system

Modulation of the Westerly and Easterly Quasi-Biennial Oscillation Phases on the Connection between the Madden–Julian Oscillation and the Arctic Oscillation

Previous studies have revealed the relationship between the Madden–Julian oscillation (MJO) and the Arctic Oscillation (AO). The MJO phase 2/3 is followed by the positive AO phase, and the MJO phase 6/7 is followed by the negative AO phase. This study reveals that the MJO phase 6/7–AO connection is modulated by the Quasi-Biennial Oscillation (QBO) through both tropospheric and stratospheric pathways during boreal winter. The MJO 2/3 phase and AO relationship is favored in both QBO easterly (QBOE) and westerly (QBOW) years because of the MJO-triggered tropospheric Rossby wave train from the tropics toward the polar region. The AO following the MJO 6/7 phase shifts to negative in QBOW years, but the MJO–AO connection diminishes in QBOE years. In QBOW years, the Asian-Pacific jet is enhanced, leading to more evident poleward propagation of tropospheric Rossby wave train, which contributes to the tropospheric pathway of the AO–MJO 6/7 connection. Besides, the enhanced Asian-Pacific jet in QBOW years is favorable for vertical propagation of planetary waves into the stratosphere in MJO phase 6/7, leading to negative AO, which indicates the stratospheric pathway of the AO–MJO 6/7 connection

Two Distinctive Processes for Abnormal Spring to Summer Transition over the South China Sea

The period from April to June signifies the transition from spring to summer over the South China Sea (SCS). The present study documents two distinct processes for abnormal spring to summer transition over the SCS. One process is related to large-scale sea surface temperature (SST) anomalies in the tropical Indo-Pacific region. During spring of La Nina decaying years, negative SST anomalies in the equatorial central Pacific (ECP) and the southwestern tropical Indian Ocean (TIO) coexist with positive SST anomalies in the tropical western North Pacific. Negative ECP SST anomalies force an anomalous Walker circulation, negative southwestern TIO SST anomalies induce anomalous cross-equatorial flows from there, and positive tropical western North Pacific SST anomalies produce a Rossby wave-type response to the west. Together, they contribute to enhanced convection and an anomalous lower-level cyclone over the SCS, leading to an advanced transition to summer there. The other process is related to regional air-sea interactions around the Maritime Continent. Preceding positive ECP SST anomalies induce anomalous descent around the Maritime Continent, leading to SST increase in the SCS and southeast TIO. An enhanced convection region moves eastward over the south TIO during spring and reaches the area northwest of Australia in May. This enhances descent over the SCS via an anomalous cross-equatorial overturning circulation and contributes to further warming in the SCS. The SST warming in turn induces convection over the SCS, leading to an accelerated transition to summer. Analysis shows that the above two processes are equally important during 1979-2015

Roles of Indian and Pacific Ocean air–sea coupling in tropical atmospheric variability

Sea surface temperature (SST) variations include negative feedbacks from the atmosphere, whereas SST anomalies are specified in stand-alone atmospheric general circulation simulations. Is the SST forced response the same as the coupled response? In this study, the importance of air–sea coupling in the Indian and Pacific Oceans for tropical atmospheric variability is investigated through numerical experiments with a coupled atmosphere-ocean general circulation model. The local and remote impacts of the Indian and Pacific Ocean coupling are obtained by comparing a coupled simulation with an experiment in which the SST forcing from the coupled simulation is specified in either the Indian or the Pacific Ocean. It is found that the Indian Ocean coupling is critical for atmospheric variability over the Pacific Ocean. Without the Indian Ocean coupling, the rainfall and SST variations are completely different throughout most of the Pacific Ocean basin. Without the Pacific Ocean coupling, part of the rainfall and SST variations in the Indian Ocean are reproduced in the forced run. In regions of large mean rainfall where the atmospheric negative feedback is strong, such as the North Indian Ocean and the western North Pacific in boreal summer, the atmospheric variability is significantly enhanced when air–sea coupling is replaced by specified SST forcing. This enhancement is due to the lack of the negative feedback in the forced SST simulation. In these regions, erroneous atmospheric anomalies could be induced by specified SST anomalies derived from the coupled model. The ENSO variability is reduced by about 20% when the Indian Ocean air–sea coupling is replaced by specified SST forcing. This change is attributed to the interfering roles of the Indian Ocean SST and Indian monsoon in western and central equatorial Pacific surface wind variations