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Wei Gu, Lin Wang, Zeng-Zhen Hu, Kaiming Hu, and Yong Li

Abstract

The first rainy season (FRS), also known as the presummer rainy season, is the first standing stage of the East Asian summer monsoon when over 40% of the annual precipitation is received over South China. Based on the start and end dates of the FRS defined by the China Meteorological Administration, this study investigates the interannual variations of the FRS precipitation over South China and its mechanism with daily mean data. The length and start/end date of the FRS vary year to year, and the average length of the FRS is 90 days, spanning from 6 April to 4 July. Composite analyses reveal that the years with abundant FRS precipitation over South China feature weakened anticyclonic wind shear over the Indochina Peninsula in the upper troposphere, southwestward shift of the western Pacific subtropical high, and anticyclonic wind anomalies over the South China Sea in the lower troposphere. The lower-tropospheric southwesterly wind anomalies are especially important because they help to enhance warm advection and water vapor transport toward South China, increase the lower tropospheric convective instability, and shape the pattern of the anomalous ascent over South China. It is further proposed that a local positive feedback between circulation and precipitation exists in this process. The variability of the FRS precipitation can be well explained by a zonal sea surface temperature (SST) dipole in the tropical Pacific and the associated Matsuno–Gill-type Rossby wave response over the western North Pacific. The interannual variability of both the SST dipole and the FRS precipitation over South China is weakened after the year 2000.

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Chao Wang, Liguang Wu, Jun Lu, Qingyuan Liu, Haikun Zhao, Wei Tian, and Jian Cao

Abstract

Understanding variations in tropical cyclone (TC) translation speed (TCS) is of great importance for islands and coastal regions since it is an important factor in determining TC-induced local damages. Investigating the long-term change in TCS was usually subject to substantial limitations in the quality of historical TC records, but here we investigated the interannual variability in TCS over the western North Pacific (WNP) Ocean by using reliable satellite TC records. It was found that both temporal changes in large-scale steering flow and TC track greatly contributed to interannual variability in the WNP TCS. In the peak season (July–September), TCS changes were closely related to temporal variations in large-scale steering flow, which was linked to the intensity of the western North Pacific subtropical high. However, for the late season (October–December), changes in TC track played a vital role in interannual variability in TCS while the impacts of temporal variations in large-scale steering were weak. The changes in TC track were mainly contributed by the El Niño–Southern Oscillation (ENSO)-induced zonal migrations in TC genesis locations, which make more or fewer TCs move to the subtropical WNP, thus leading to notable changes in the basinwide TCS because of the much greater large-scale steering in the subtropical WNP. The increased influence of TC track change on TCS in the late season was linked to the greater contrast between the subtropical and the tropical large-scale steering in the late season. These results have important implications for understanding current and future variations in TCS.

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Thomas R. Karl, Wei-Chyung Wang, Michael E. Schlesinger, Richard W. Knight, and David Portman

Abstract

Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.

We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.

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Hainan Gong, Lin Wang, Wen Chen, Renguang Wu, Ke Wei, and Xuefeng Cui

Abstract

In this paper the model outputs from the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) are used to examine the climatology and interannual variability of the East Asian winter monsoon (EAWM). The multimodel ensemble (MME) is able to reproduce reasonably well the circulation features of the EAWM. The simulated surface air temperature still suffers from a cold bias over East Asia, but this bias is reduced compared with CMIP phase 3 models. The intermodel spread is relatively small for the large-scale circulations, but is large for the lower-tropospheric meridional wind and precipitation along the East Asian coast. The interannual variability of the EAWM-related circulations can be captured by most of the models. A general bias is that the simulated variability is slightly weaker than in the observations. Based on a selected dynamic EAWM index, the patterns of the EAWM-related anomalies are well reproduced in MME although the simulated anomalies are slightly weaker than the observations. One general bias is that the northeasterly anomalies over East Asia cannot be captured to the south of 30°N. This bias may arise both from the inadequacies of the EAWM index and from the ability of models to capture the EAWM-related tropical–extratropical interactions. The ENSO–EAWM relationship is then evaluated and about half of the models can successfully capture the observed ENSO–EAWM relationship, including the significant negative correlation between Niño-3.4 and EAWM indices and the anomalous anticyclone (or cyclone) over the northwestern Pacific. The success of these models is attributed to the reasonable simulation of both ENSO’s spatial structure and its strength of interannual variability.

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Fuyao Wang, Yan Yu, Michael Notaro, Jiafu Mao, Xiaoying Shi, and Yaxing Wei

Abstract

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.

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Guoxing Chen, Wei-Chyung Wang, Chao-Tzuen Cheng, and Huang-Hsiung Hsu

Abstract

Winter extreme snowstorm events along the coast of the northeast United States have significant impacts on social and economic activities, and their potential changes under global warming are of great concern. Here, we adopted the pseudo–global warming approach to investigate the responses of 93 events identified in our previous observational analysis. The study was conducted by contrasting two sets of WRF simulations for each event: the first set driven by the ERA-Interim reanalysis and the second set by that data superimposed with mean-climate changes simulated from HiRAM historical (1980–2004) and future (2075–99; RCP8.5) runs. Results reveal that the warming together with increased moisture tends to decrease the snowfall along the coast but increase the rainfall throughout the region. For example, the number of events having daily snow water equivalent larger than 10 mm day−1 at Boston, Massachusetts; New York City, New York; Philadelphia, Pennsylvania; and Washington, D.C., is decreased by 47%, 46%, 30%, and 33%, respectively. The compensating changes in snowfall and rainfall lead to a total-precipitation increase in the three more-southern cities but a decrease in Boston. In addition, the southwestward shift of regional precipitation distribution is coherent with the enhancement (reduction) of upward vertical motion in the south (north) and the movement of cyclone centers (westward in 58% of events and southward in 72%). Finally, perhaps more adversely, because of the northward retreat of the 0°C line and the expansion of the near-freezing zone, the number of events with mixed rain and snow and freezing precipitation in the north (especially the inland area) is increased.

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Wei Zhao, Shangfeng Chen, Hengde Zhang, Jikang Wang, Wen Chen, Renguang Wu, Wanqiu Xing, Zhibiao Wang, Peng Hu, Jinling Piao, and Tianjiao Ma

Abstract

The Beijing-Tianjin-Hebei (BTH) region has encountered increasingly severe and frequent haze pollution during recent decades. This study reveals that the El Niño–Southern Oscillation (ENSO) has distinctive impacts on interannual variations of haze pollution over BTH in early and late winters. The impact of ENSO on the haze pollution over the BTH is strong in early winter, but weak in late winter. In early winter, ENSO-related sea surface temperature anomalies generate double-cell Walker circulation anomalies, with upward motion anomalies over the tropical central-eastern Pacific and tropical Indian Ocean, and downward motion anomalies over tropical western Pacific. The ascending motion and enhanced atmospheric heating anomalies over the tropical Indian Ocean trigger atmospheric teleconnection propagating from North Indian Ocean to East Asia, and result in generation of an anticyclonic anomaly over northeast Asia. The associated southerly anomalies to the west side lead to more serious haze pollution via reducing surface wind speed and increasing low-level humidity and thermal inversion. Strong contribution of the Indian Ocean heating anomalies to the formation of the anticyclonic anomaly over northeast Asia in early winter can be confirmed by atmospheric model numerical experiments. In late winter, vertical motion and precipitation anomalies are weak over tropical Indian Ocean related to ENSO. As such, ENSO cannot induce clear anticyclonic anomaly over northeast Asia via atmospheric teleconnection, and thus has a weak impact on the haze pollution over BTH. Further analysis shows that stronger ENSO-induced atmospheric heating anomalies over tropical Indian Ocean in early winter is partially due to higher mean SST and precipitation there.

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Wei Zhao, Shangfeng Chen, Hengde Zhang, Jikang Wang, Wen Chen, Renguang Wu, Wanqiu Xing, Zhibiao Wang, Peng Hu, Jinling Piao, and Tianjiao Ma

Abstract

The Beijing–Tianjin–Hebei (BTH) region has encountered increasingly severe and frequent haze pollution during recent decades. This study reveals that El Niño–Southern Oscillation (ENSO) has distinctive impacts on interannual variations of haze pollution over BTH in early and late winters. The impact of ENSO on the haze pollution over the BTH is strong in early winter, but weak in late winter. In early winter, ENSO-related sea surface temperature anomalies generate double-cell Walker circulation anomalies, with upward motion anomalies over the tropical central-eastern Pacific and tropical Indian Ocean, and downward motion anomalies over the tropical western Pacific. The ascending motion and enhanced atmospheric heating anomalies over the tropical Indian Ocean trigger atmospheric teleconnection propagating from the north Indian Ocean to East Asia, and result in the generation of an anticyclonic anomaly over Northeast Asia. The associated southerly anomalies to the west side lead to more serious haze pollution via reducing surface wind speed and increasing low-level humidity and the thermal inversion. The strong contribution of the Indian Ocean heating anomalies to the formation of the anticyclonic anomaly over Northeast Asia in early winter can be confirmed by atmospheric model numerical experiments. In late winter, vertical motion and precipitation anomalies are weak over the tropical Indian Ocean related to ENSO. As such, ENSO cannot induce a clear anticyclonic anomaly over Northeast Asia via atmospheric teleconnection, and thus has a weak impact on the haze pollution over BTH. Further analysis shows that stronger ENSO-induced atmospheric heating anomalies over the tropical Indian Ocean in early winter are partially due to higher mean SST and precipitation there.

Significance Statement

There exist large discrepancies regarding the contribution of El Niño–Southern Oscillation (ENSO) events to the wintertime haze pollution over North China. Several studies have indicated that ENSO has a weak impact on the haze pollution over North China. However, some studies have argued that ENSO events can exert impacts on the occurrence of haze pollution over North China. In this study, we present evidence to demonstrate that ENSO has distinctive impacts on interannual variations of the haze pollution over the Beijing–Tianjin–Hebei (BTH) region in North China in early and late winters. Specifically, ENSO has a strong impact on the haze pollution over BTH in early winter, whereas the impact of ENSO on the haze pollution over BTH is fairly weak in late winter. Results of this study could reconcile the discrepancy of previous studies about the impact of ENSO on the haze pollution over North China.

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Guoxing Chen, Wei-Chyung Wang, Lijun Tao, Huang-Hsiung Hsu, Chia-Ying Tu, and Chao-Tzuen Cheng

Abstract

This study used both observations and global climate model simulations to investigate the characteristics of winter extreme snowfall events along the coast (the Interstate 95 corridor) of the northeast United States where several mega-cities are located. Observational analyses indicate that, during 1980–2015, 110 events occurred when four coastal cities—Boston, New York City, Philadelphia, and Washington, D.C.—had either individually or collectively experienced daily snowfall exceeding the local 95th percentile thresholds. Boston had the most events, with a total of 69, followed by 40, 36, and 30 (moving southward) in the other three cities. The associated circulations at 200 and 850 hPa were categorized via K-means clustering. The resulting three composite circulations are characterized by the strength and location of the jet at 200 hPa and the coupled low pressure system at 850 hPa: a strong jet overlying the cities coupled with an inland trough, a weak and slightly southward shifted jet coupled with a cyclone at the coast, and a weak jet stream situated to the south of the cities coupled with a cyclone over the coastal oceans. Comparative analyses were also conducted using the GFDL High Resolution Atmospheric Model (HiRAM) simulation of the same period. Although the simulated extreme events do not provide one-to-one correspondence with observations, the characteristics nevertheless show consistency notably in total number of occurrences, intraseasonal and multiple-year variations, snow spatial coverage, and the associated circulation patterns. Possible future change in extreme snow events was also explored utilizing the HiRAM RCP8.5 (2075–2100) simulation. The analyses suggest that a warming global climate tends to decrease the extreme snowfall events but increase extreme rainfall events.

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