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

Abstract

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated here using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.

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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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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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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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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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