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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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Liqi Chen, Wei Li, Jianqiong Zhan, Jianjun Wang, Yuanhui Zhang, and Xulin Yang

Abstract

To investigate the concentrations, sources, and temporal variations of atmospheric black carbon (BC) in the summer Arctic, routine ground-level observations of BC by optical absorption were made in the summer from 2005 to 2008 at the Chinese Arctic “Yellow River” Station (78°55′N, 11°56′E) at Ny-Ålesund on the island of Spitsbergen in the Svalbard Archipelago. Methods of the ensemble empirical-mode decomposition analysis and back-trajectory analysis were employed to assess temporal variation embedded in the BC datasets and airmass transport patterns. The 10th-percentile and median values of BC concentrations were 7.2 and 14.6 ng m−3, respectively, and hourly average BC concentrations ranged from 2.5 to 54.6 ng m−3. A gradual increase was found by 4 ng m−3 a−1. This increase was not seen in the Zeppelin Station and it seemed to contrast with the prevalent conception of generally decreasing BC concentration since 1989 in the Arctic. Factors responsible for this increase such as changes in emissions and atmospheric transport were taken into consideration. The result indicated that BC from local emissions was mostly responsible for the observed increase from 2005 to 2008. BC temporal variation in the summer was controlled by the atmospheric circulation, which presented a significant 6–14-day variation and coherent with 1–3- and 2–5-day and longer cycle variation. Although the atmospheric circulation changes from 2005 to 2008, there was not a marked trend in long-range transportation of BC. This study suggested that local emissions might have significant implication for the regional radiative energy balance at Ny-Ålesund.

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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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Wei-Chyung Wang, William B. Rossow, Mao-Sung Yao, and Marilyn Wolfson

Abstract

We illustrate the potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included by studying the behavior of a one-dimensional radiative–convective model with two types of cloud variation: 1) variable cloud cover with constant optical thickness and 2) variable optical thickness with constant cloud cover. The variable parameter is calculated assuming a correlation between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, we examine the sensitivity of the results to two different critical lapse rates, a constant 6.5 K km−1 lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are examined using two cases: a 2% increase in the solar constant and a doubling of the atmospheric carbon dioxide concentration. The model results show that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover. Further the variety and complexity of the feedbacks exhibited even by this simple model suggest that proper determination of cloud feedbacks must include the effects of varying vertical distribution.

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Christopher A. Davis, David A. Ahijevych, Wei Wang, and William C. Skamarock

Abstract

An evaluation of medium-range forecasts of tropical cyclones (TCs) is performed, covering the eastern North Pacific basin during the period 1 August–3 November 2014. Real-time forecasts from the Model for Prediction Across Scales (MPAS) and operational forecasts from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) are evaluated. A new TC-verification method is introduced that treats TC tracks as objects. The method identifies matching pairs of forecast and observed tracks, missed and false alarm tracks, and derives statistics using a multicategory contingency table methodology. The formalism includes track, intensity, and genesis.

Two configurations of MPAS, a uniform 15-km mesh and a variable-resolution mesh transitioning from 60 km globally to 15 km over the eastern Pacific, are compared with each other and with the operational GFS. The two configurations of MPAS reveal highly similar forecast skill and biases through at least day 7. This result supports the effectiveness of TC prediction using variable resolution.

Both MPAS and the GFS suffer from biases in predictions of genesis at longer time ranges; MPAS produces too many storms whereas the GFS produces too few. MPAS better discriminates hurricanes than does the GFS, but the false alarms in MPAS lower overall forecast skill in the medium range relative to GFS. The biases in MPAS forecasts are traced to errors in the parameterization of shallow convection south of the equator and the resulting erroneous invigoration of the ITCZ over the eastern North Pacific.

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Xiaodong Huang, Zhaoyun Wang, Zhiwei Zhang, Yunchao Yang, Chun Zhou, Qingxuan Yang, Wei Zhao, and Jiwei Tian

Abstract

The role of mesoscale eddies in modulating the semidiurnal internal tide (SIT) in the northern South China Sea (SCS) is examined using the data from a cross-shaped mooring array. From November 2013 to January 2014, an anticyclonic eddy (AE) and cyclonic eddy (CE) pair crossed the westward SIT beam originating in Luzon Strait. Observations showed that, because of the current and stratification modulations by the eddy pair, the propagation speed of the mode-1 SIT sped up (slowed down) by up to 0.7 m s−1 (0.4 m s−1) within the AE’s (CE’s) southern portion. As a result of the spatially varying phase speed, the mode-1 SIT wave crest was clockwise rotated (counterclockwise rotated) within the AE (CE) core, while it exhibited convex and concave (concave and convex) patterns on the southern and northern peripheries of the AE (CE), respectively. In mid-to-late November, most of the mode-1 SIT energy was refracted by the AE away from Dongsha Island toward the north part of the northern SCS, which resulted in enhanced internal solitary waves (ISWs) there. Corresponding to the energy refraction, responses of the depth-integrated mode-1 SIT energy to the eddies were generally in phase at the along-beam-direction moorings but out of phase in the south and north parts of the northern SCS at the cross-beam-direction moorings. From late December to early January, intensified mode-2 SIT was observed, whose energy was likely transferred from the mode-1 SIT through eddy–wave interactions. The observation results reported here are helpful to improve the capability to predict internal tides and ISWs in the northern SCS.

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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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