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Xin-Zhong Liang, Wei-Chyung Wang, and Michael P. Dudek

Abstract

Observed and general circulation climate model (GCM) simulated interannual teleconnection patterns in the Northern Hemisphere are compared on a monthly basis. The study was based on 1946–1991 observations and two separate 100-year simulations corresponding to the present climate and a greenhouse warming climate. The teleconnection patterns are characterized by action centers and composite extreme anomaly (CEA) distributions. The definition and comparison of observed and simulated patterns include examination of time persistence, spatial coherence as well as consistent signatures between 500-mb height, sea level pressure, and surface air temperature.

For the present climate simulation, the GCM reproduces observed spatial and temporal variations of the action centers of four principal teleconnection patterns: the North Atlantic oscillation, the North Pacific oscillation, the Pacific/North American pattern, and the Eurasian pattern. Substantial model biases exist in the magnitude, regional structure as well as monthly transition of anomalies. The CEA regional characteristics are better simulated over land than over the oceans. For example, the model most accurately simulates the Eurasian pattern, which has its dominant action centers over Eurasia. In addition, all three climate variables exhibit substantial anomalies for each land-based action center. In contrast, over the oceans, the model systematically underestimates sea level pressure and 500-mb height CEAs, while it produces small surface temperature responses. It is suggested that atmospheric dynamics associated with flow instability is likely to be the dominant mechanism that generates these teleconnections, while the lack of interactive ocean dynamics may be responsible for small responses over the oceans.

In the greenhouse warming climate, the GCM continues to simulate the four interannual teleconnection patterns. Systematic changes, however, are found for the Pacific/North American and Eurasian patterns in winter, where the action centers shift to the east and the CEAs weaken over land. These results must be considered to be exploratory because of the use of a mixed layer ocean that does not include oceanic dynamics.

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David A. Portman, Wei-Chyung Wang, and Thomas R. Karl

Abstract

Validation of general circulation model (GCM) current climate simulations is important for further GCM development and application to climate change studies. So far, studies that compare GCM output with observations have focused primarily on large-scale spatial averages of the surface climate variables. Here we discuss two approaches to compare output of individual GCM grid boxes with local station observations near the surface and in the free troposphere. The first approach, proposed by Chervin, involves the application of standard parametric statistical analysis and hypothesis testing procedures. The second approach is nonparametric in the sense that no ideal distributions are postulated a priori to ascertain significance of the difference of mean temperature or the ratio of the temperature variance between model grid boxes and local stations. Instead, station observations are first subjected to a bootstrap technique and then used to define a unique set of distributions and confidence limits for each GCM grid box.

To demonstrate the usefulness of the two approaches, we compare daily and seasonal gridbox temperatures simulated by the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM1) with station temperatures at the surface, 850-mb, 500-mb, and 300-mb levels for three different areas in the United States. We find that although CCM1 gridbox temperatures are mostly cooler than station temperatures, they are equally variable. For all grid boxes, gridbox-to-station differences decrease with height and vary with time of year. We conclude that the techniques presented here can provide useful comparisons of GCM regional and local observed temperatures. Application to other variables and GCMs is also discussed.

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Wei Mei, Shang-Ping Xie, Ming Zhao, and Yuqing Wang

Abstract

Forced interannual-to-decadal variability of annual tropical cyclone (TC) track density in the western North Pacific between 1979 and 2008 is studied using TC tracks from observations and simulations by a 25-km-resolution version of the GFDL High-Resolution Atmospheric Model (HiRAM) that is forced by observed sea surface temperatures (SSTs). Two modes dominate the decadal variability: a nearly basinwide mode, and a dipole mode between the subtropics and lower latitudes. The former mode links to variations in TC number and is forced by SST variations over the off-equatorial tropical central North Pacific, whereas the latter might be associated with the Atlantic multidecadal oscillation. The interannual variability is also controlled by two modes: a basinwide mode driven by SST anomalies of opposite signs located in the tropical central Pacific and eastern Indian Ocean, and a southeast–northwest dipole mode connected to the conventional eastern Pacific ENSO. The seasonal evolution of the ENSO effect on TC activity is further explored via a joint empirical orthogonal function analysis using TC track density of consecutive seasons, and the analysis reveals that two types of ENSO are at work. Internal variability in TC track density is then examined using ensemble simulations from both HiRAM and a regional atmospheric model. It exhibits prominent spatial and seasonal patterns, and it is particularly strong in the South China Sea and along the coast of East Asia. This makes an accurate prediction and projection of TC landfall extremely challenging in these regions. In contrast, basin-integrated metrics (e.g., total TC counts and TC days) are more predictable.

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Jiandong Li, Wei-Chyung Wang, Jiangyu Mao, Ziqian Wang, Gang Zeng, and Guoxing Chen

Abstract

Clouds strongly modulate regional radiation balance and their evolution is profoundly influenced by circulations. This study uses 2001–16 satellite and reanalysis data together with regional model simulations to investigate the spring shortwave cloud radiative effect (SWCRE) and the associated circulations over southeastern China (SEC). Strong SWCRE, up to −110 W m−2, persists throughout springtime in this region and its spring mean is the largest among the same latitudes of the Northern Hemisphere. SWCRE exhibits pronounced subseasonal variation and is closely associated with persistent regional ascending motion and moisture convergence, which favor large amounts of cloud liquid water and resultant strong SWCRE. Around pentad 12 (late February), SWCRE abruptly increases and afterward remains stable between 22° and 32°N. The thermal and dynamic effects of Tibetan Plateau and westerly jet provide appropriate settings for the maintenance of ascending motion, while water vapor, as cloud water supply, stably comes from the southern flank of the Tibetan Plateau and South China Sea. During pentads 25–36 (early May to late June), SWCRE is further enhanced by the increased water vapor transport caused by the march of East Asian monsoon systems, particularly after the onset of the South China Sea monsoon. After pentad 36, these circulations quickly weaken and the SWCRE decreases accordingly. Individual years with spring strong and weak rainfall are chosen to highlight the importance of the strength of the ascending motion. The simulation broadly reproduced the observed results, although biases exist. Finally, the model biases in SWCRE–circulation associations are discussed.

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Wei-Chyung Wang, Wei Gong, Wen-Shung Kau, Cheng-Ta Chen, Huang-Hsiung Hsu, and Chia-Hsiu Tu

Abstract

Observations indicate that the East Asian summer monsoon (EASM) exhibits distinctive characteristics of large cloud amounts with associated heavy and persistent rainfall, although short breaks for clear sky usually occur. Consequently, the effects of cloud–radiation interactions can play an important role in the general circulation of the atmosphere and, thus, the evolution of the EASM. In this note, as a first step toward studying the topic, the 5-yr (January 1985–December 1989) Earth Radiation Budget Experiment (ERBE) dataset is used to show the spatial and temporal patterns of both shortwave (SW) and longwave (LW) cloud radiative forcing (CRF) at the top of the atmosphere over east China, and to compare the observed features with Atmospheric Model Intercomparison Project-II (AMIP-II) simulations with the University at Albany, State University of New York (SUNYA) Community Climate Model 3 (CCM3) and the ECHAM4 general circulation models.

The observations indicate that the net CRF provides a cooling effect to the atmosphere–surface climate system, dominated by the SW CRF cooling (albedo effect) with partial compensation from the LW CRF warming (greenhouse effect). The SW CRF shows a strong seasonal cycle, and its peak magnitude is particularly large, ∼110 W m−2, for south China and the Yangtze–Huai River valley (YHRV) during May and June, while the LW CRF is about 50 W m−2 for the same months with a weak dependence on the latitudes and seasons. These characteristics are in sharp contrast to the Northern Hemispheric zonal means of the same latitude bands and seasons, thus implying a unique role for cloud–radiation interaction in east China. Both model simulations show similar observed characteristics, although biases exist. For example, in May, the ECHAM4 underestimates the SW CRF while the SUNYA CCM3 simulates a significantly larger value, both attributed to the respective biases in the simulated total cloud cover. Model-to-observation comparisons of the association between total cloud cover and SW CRF, and between high cloud cover and LW CRF, are also presented and their differences are discussed. Finally, the SUNYA CCM3 biases in the CRF and its relevance to the model cloud biases are discussed in the context of model cold and dry biases in climate simulations.

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Wei-Chyung Wang, Qing-Yun Zhang, David R. Easterling, and Thomas R. Karl

Abstract

Two aspects of Beijing cloudiness are studied: its relationship to other climate parameters during the period 1951–1990 and the reconstruction of proxy values between 1875 and 1950. For the recent period, cloudiness varies with no apparent trend and is highly correlated with the total number of rain days (r=0.77) and total sunshine duration (r=0.72). Good correlation is also found with maximum surface air temperature, surface relative humidity, and total precipitation. While the correlation between cloudiness and solar radiation was large prior to 1976, the coefficient for the period 1976–1990 is much smaller. This decrease can be attributed to a negative trend in solar radiation, which is consistent with an observed decrease in visibility. Variations in Beijing cloudiness are closely related to those found over most of northern China, while little similarity is found with locations south of 35°N.

The large correlation between annual cloudiness and the total number of rain days between 1951 and 1990 was used in conjunction with the observed rain day record for the period 1875–1950 to construct a proxy cloudiness record for Beijing for the period 1875–1950. Comparisons between proxy cloudiness and available observations of surface air temperature and relative humidity reveal that the relationships are consistent with those found when observed cloudiness is compared with observed temperature and humidity data. On the century time scale, there is no clear trend in percent cloudiness. However, on the decadal time scale, there is a negative trend in cloudiness during the period 1880–1930 followed by a period of relatively constant values between 1940 and 1975.

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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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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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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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