Search Results

You are looking at 1 - 10 of 14 items for

  • Author or Editor: X. Zeng x
  • All content x
Clear All Modify Search
Zhen Zeng and X. Zou

Abstract

A principal component analysis (PCA) method is applied to Challenging Minisatellite Payload (CHAMP) level-2 radio occultation (RO) observations and the corresponding global analyses from the National Centers for Environmental Prediction (NCEP) in March 2004. The PCA is performed on a square symmetric vertical correlation matrix of observed or modeled RO profiles. By decomposing the matrix into pairs of loadings (EOFs) and associated principal components (PCs), outliers are identified and important modes that explain most variances of the vertical variability of the atmosphere as represented by the GPS RO data and the NCEP analyses are extracted and compared. Specifically, a quality control of RO data based on Hotelling’s T2 index is applied first, which removes 255 RO profiles from 4884 total profiles (about 5%) and smoothes the distributions of PC modes, making the remaining GPS RO dataset much more meaningful. The leading PC mode for global refractivity explains 60% of the total variance and is associated with a symmetric zonal pattern, with positive anomalies in the Tropics and negative anomalies at the two poles. The second PC mode explains an additional 16% of the total variance and shows a dipole pattern with positive anomalies in the North Pole and negative anomalies in the South Pole. Three significant positive anomalies are also found in the second and third PC modes over three predominant convective areas in the western Pacific, South America, and Africa in the Tropics. The first leading PC mode calculated from global NCEP analyses compared favorably with that from CHAMP observations, which proves that NCEP analyses are capable of representing most of the variance of the atmospheric profiles. However, disagreements between CHAMP observations and NCEP analyses are noticed in the second EOF over the Tropics and the Southern Hemisphere (SH). It is also found that the NCEP analyses describe CHAMP-observed larger vertical scale features better than smaller-scale features, captures features of more leading EOF modes in the Northern Hemisphere than in the SH and the Tropics, and does not capture the vertical structures revealed by the EOFs in CHAMP observations near and above the tropopause in the Tropics.

Full access
X. Zeng, R. A. Pielke, and R. Eykholt

Abstract

The fractal dimension, Lyapunov-exponent spectrum, Kolmogorov entropy, and predictability are analyzed for chaotic attractors in the atmosphere by analyzing the time series of daily surface temperature and pressure over several regions of the United States and the North Atlantic Ocean with different climatic signal-to-noise ratios. Though the total number of data points (from about 13 800 to about 36 500) is larger than those used in previous studies, it is still too small to obtain a reliable estimate of the Grassberger–Procaccia correlation dimension because of the limitations discussed by Ruelle. However, it can be shown that this dimension is greater than 8. Also, it is pointed out that most, if not all, of the previous estimates of low fractal dimensions in the atmosphere are spurious. These results lead us to claim that there probably exist no low-dimensional strange attractors in the atmosphere. Because the fractal dimension has not yet been saturated, the Kolmogorov entropy and the error-doubling time obtained by the method of Grassberger and Procaccia are sensitive to the selection of the time delay and are thus unreliable. Geographic variability of the fractal dimension is suggested, but further verification is needed.

A practical and more reliable method for estimating the Kolmogorov entropy and error-doubling time involves the computation of the Lyapunov-exponent spectrum using the algorithm of Zeng et al. Using this method, it is found that the error-doubling time is about 2–3 days in Fort Collins, Colorado, about 4–5 days in Los Angeles, California, and about 5–8 days in the North Atlantic Ocean. The predictability time is longer over regions with a higher climatic signal-to-noise ratio (e.g., Los Angeles), and the predictability time of summer and/or winter data is longer than for the entire year. The difference between these estimates of error-doubling time and estimates based on general circulation models (GCMs) is discussed. It is also mentioned that the computation of the Lyapunov exponents is slightly sensitive to the selection of the time delay, possibly because the fractal dimension is very high in the atmosphere. Such sensitivity has not been mentioned in previous similar studies.

Full access
G. A. Dalu, R. A. Pielke, M. Baldi, and X. Zeng

Abstract

The authors Present an analytical evaluation of the vertical heat and momentum fluxes associated with mesoscale flow generated by periodic and isolated thermal inhomogeneities within the convective boundary layer (CBL). The influence of larger-scale wind flow is also included.

The results show that, with little or no synoptic wind, the vertical velocity is in phase with the diabatic temperature perturbations and that the mesoscale heat flux is positive and of the same order as the diabatic heat flux within the CBL. Above the CBL, the heat flux is negative and penetrates into the free atmosphere through a depth comparable to the depth of the CBL. In the presence of synoptic flow, the mesoscale perturbation is in the form of propagating waves that penetrate deeply into the free atmosphere. As a result, there is a net downward flux of momentum, which is dissipated within the CBL by turbulence. Furthermore, mixing with the environment of the air particles displaced by the waves results in a net negative mesoscale heat flux, which contributes to the weakening of the stability of the free atmosphere.

Strong synoptic advection can significantly weaken the horizontal temperature gradients in the CBL, thereby weakening the intensity of the mesoscale flow. Turbulent diffusion also weakens the temperature gradients and the intensity of the mesoscale flow at large wavenumbers when the wavelength is comparable to the CBL depth. Finally, when the, synoptic wind is very strong, the mesoscale perturbation is very weak and vertically trapped.

Full access
Vasubandhu Misra, L. Marx, M. Brunke, and X. Zeng

Abstract

A set of multidecadal coupled ocean–atmosphere model integrations are conducted with different time steps for coupling between the atmosphere and the ocean. It is shown that the mean state of the equatorial Pacific does not change in a statistically significant manner when the coupling interval between the atmospheric general circulation model (AGCM) and the ocean general circulation model (OGCM) is changed from 1 day to 2 or even 3 days. It is argued that because the coarse resolution of the AGCM precludes resolving realistic “weather” events, changing the coupling interval from 1 day to 2 or 3 days has very little impact on the mean coupled climate.

On the other hand, reducing the coupling interval to 3 h had a much stronger impact on the mean state of the equatorial Pacific and the concomitant general circulation. A novel experiment that incorporates a (pseudo) interaction of the atmosphere with SST at every time step of the AGCM was also conducted. In this unique coupled model experiment, the AGCM at every time step mutually interacts with the skin SST. This skin SST is anchored to the bulk SST, which is updated from the OGCM once a day. Both of these experiments reduced the cold tongue bias moderately over the equatorial Pacific Ocean with a corresponding reduction in the easterly wind stress bias relative to the control integration. It is stressed from the results of these model experiments that the impact of high-frequency air–sea coupling is significant on the cold tongue bias.

The interannual variation of the equatorial Pacific was less sensitive to the coupling time step between the AGCM and the OGCM. Increasing (reducing) the coupling interval of the air–sea interaction had the effect of weakening (marginally strengthening) the interannual variations of the equatorial Pacific Ocean.

It is argued that the low-frequency response of the upper ocean, including the cold tongue bias, is modulated by the atmospheric stochastic forcing on the coupled ocean–atmosphere system. This effect of the atmospheric stochastic forcing is affected by the frequency of the air–sea coupling and is found to be stronger than the rectification effect of the diurnal variations of the air–sea interaction on the low frequency. This may be a result of a limitation in the coupled model used in this study in which the OGCM has an inadequate vertical resolution in the mixed layer to sustain diurnal variations in the upper ocean.

Full access
Z. Wang, X. Zeng, M. Barlage, R. E. Dickinson, F. Gao, and C. B. Schaaf

Abstract

The land surface albedo in the NCAR Community Climate System Model (CCSM2) is calculated based on a two-stream approximation, which does not include the effect of three-dimensional vegetation structure on radiative transfer. The model albedo (including monthly averaged albedo, direct albedo at local noon, and the solar zenith angle dependence of albedo) is evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) and albedo data acquired during July 2001–July 2002. The model monthly averaged albedos in February and July are close to the MODIS white-sky albedos (within 0.02 or statistically insignificant) over about 40% of the global land between 60°S and 70°N. However, CCSM2 significantly underestimates albedo by 0.05 or more over deserts (e.g., the Sahara Desert) and some semiarid regions (e.g., parts of Australia). The difference between the model direct albedo at local noon and the MODIS black-sky albedo for the near-infrared (NIR) band (with wavelength > 0.7 μm) is larger than the difference for the visible band (with wavelength < 0.7 μm) for most snow-free regions. For eleven model grid cells with different dominant plant functional types, the model diffuse NIR albedo is higher by 0.05 or more than the MODIS white-sky albedo in five of these cells. Direct albedos from the model and MODIS (as computed using the BRDF parameters) increase with solar zenith angles, but model albedo increases faster than the MODIS data. These analyses and the MODIS BRDF and albedo data provide a starting point toward developing a BRDF-based treatment of radiative transfer through a canopy for land surface models that can realistically simulate the mean albedo and the solar zenith angle dependence of albedo.

Full access
R. Rosolem, W. J. Shuttleworth, M. Zreda, T. E. Franz, X. Zeng, and S. A. Kurc

Abstract

The cosmic-ray method for measuring soil moisture, used in the Cosmic-Ray Soil Moisture Observing System (COSMOS), relies on the exceptional ability of hydrogen to moderate fast neutrons. Sources of hydrogen near the ground, other than soil moisture, affect the neutron measurement and therefore must be quantified. This study investigates the effect of atmospheric water vapor on the cosmic-ray probe signal and evaluates the fast neutron response in realistic atmospheric conditions using the neutron transport code Monte Carlo N-Particle eXtended (MCNPX). The vertical height of influence of the sensor in the atmosphere varies between 412 and 265 m in dry and wet atmospheres, respectively. Model results show that atmospheric water vapor near the surface affects the neutron intensity signal by up to 12%, corresponding to soil moisture differences on the order of 0.10 m3 m−3. A simple correction is defined to identify the true signal associated with integrated soil moisture that rescales the measured neutron intensity to that which would have been observed in the atmospheric conditions prevailing on the day of sensor calibration. Use of this approach is investigated with in situ observations at two sites characterized by strong seasonality in water vapor where standard meteorological measurements are readily available.

Restricted access
Zhenzhong Zeng, Shilong Piao, Laurent Z. X. Li, Tao Wang, Philippe Ciais, Xu Lian, Yuting Yang, Jiafu Mao, Xiaoying Shi, and Ranga B. Myneni

Abstract

Leaf area index (LAI) is increasing throughout the globe, implying Earth greening. Global modeling studies support this contention, yet satellite observations and model simulations have never been directly compared. Here, for the first time, a coupled land–climate model was used to quantify the potential impact of the satellite-observed Earth greening over the past 30 years on the terrestrial water cycle. The global LAI enhancement of 8% between the early 1980s and the early 2010s is modeled to have caused increases of 12.0 ± 2.4 mm yr−1 in evapotranspiration and 12.1 ± 2.7 mm yr−1 in precipitation—about 55% ± 25% and 28% ± 6% of the observed increases in land evapotranspiration and precipitation, respectively. In wet regions, the greening did not significantly decrease runoff and soil moisture because it intensified moisture recycling through a coincident increase of evapotranspiration and precipitation. But in dry regions, including the Sahel, west Asia, northern India, the western United States, and the Mediterranean coast, the greening was modeled to significantly decrease soil moisture through its coupling with the atmospheric water cycle. This modeled soil moisture response, however, might have biases resulting from the precipitation biases in the model. For example, the model dry bias might have underestimated the soil moisture response in the observed dry area (e.g., the Sahel and northern India) given that the modeled soil moisture is near the wilting point. Thus, an accurate representation of precipitation and its feedbacks in Earth system models is essential for simulations and predictions of how soil moisture responds to LAI changes, and therefore how the terrestrial water cycle responds to climate change.

Full access
Xin-Min Zeng, B. Wang, Y. Zhang, Y. Zheng, N. Wang, M. Wang, X. Yi, C. Chen, Z. Zhou, and H. Liu

Abstract

To quantify and explain effects of different land surface schemes (LSSs) on simulated geopotential height (GPH) fields, we performed simulations over China for the summer of 2003 using 12-member ensembles with the Weather Research and Forecasting (WRF) Model, version 3. The results show that while the model can generally simulate the seasonal and monthly mean GPH patterns, the effects of the LSS choice on simulated GPH fields are substantial, with the LSS-induced differences exceeding 10 gpm over a large area (especially the northwest) of China, which is very large compared with climate anomalies and forecast errors. In terms of the assessment measures for the four LSS ensembles [namely, the five-layer thermal diffusion scheme (SLAB), the Noah LSS (NOAH), the Rapid Update Cycle LSS (RUC), and the Pleim–Xiu LSS (PLEX)] in the WRF, the PLEX ensemble is the best, followed by the NOAH, RUC, and SLAB ensembles. The sensitivity of the simulated 850-hPa GPH is more significant than that of the 500-hPa GPH, with the 500-hPa GPH difference fields generally characterized by two large areas with opposite signs due to the smoothly varying nature of GPHs. LSS-induced GPH sensitivity is found to be higher than the GPH sensitivity induced by atmospheric boundary layer schemes. Moreover, theoretical analyses show that the LSS-induced GPH sensitivity is mainly caused by changes in surface fluxes (in particular, sensible heat flux), which further modify atmospheric temperature and pressure fields. The temperature and pressure fields generally have opposite contributions to changes in the GPH. This study emphasizes the importance of choosing and improving LSSs for simulating seasonal and monthly GPHs using regional climate models.

Full access
M. Chong, J.-F. Georgis, O. Bousquet, S. R. Brodzik, C. Burghart, S. Cosma, U. Germann, V. Gouget, R. A. Houze Jr., C. N. James, S. Prieur, R. Rotunno, F. Roux, J. Vivekanandan, and Z.-X. Zeng

A real-time and automated multiple-Doppler analysis method for ground-based radar data, with an emphasis on observations conducted over complex terrain, is presented. It is the result of a joint effort of the radar groups of Centre National de Recherches Météorologiques and Laboratoire d'Aérologie with a view to converging toward a common optimized procedure to retrieve mass-conserved three-dimensional wind fields in the presence of complex topography. The multiple-Doppler synthesis and continuity adjustment technique initially proposed for airborne Doppler radar data, then extended to ground-based Doppler radars and nonflat orography, is combined with a variational approach aimed at improving the vertical velocity calculation over mountainous regions. This procedure was successfully applied in real time during the Mesoscale Alpine Programme Special Observing Period. The real-time processing and display of Doppler radar data were intended to assist nowcast and aircraft missions, and involved efforts of the United Sates, France, and Switzerland.

Full access
Rym Msadek, T. L. Delworth, A. Rosati, W. Anderson, G. Vecchi, Y.-S. Chang, K. Dixon, R. G. Gudgel, W. Stern, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang

Abstract

Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.

Full access