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Yaru Guo, Yuanlong Li, Fan Wang, Yuntao Wei, and Zengrui Rong

Abstract

A high-resolution (3–8 km) regional oceanic general circulation model is utilized to understand the sea surface temperature (SST) variability of Ningaloo Niño in the southeast Indian Ocean (SEIO). The model reproduces eight Ningaloo Niño events with good fidelity and reveals complicated spatial structures. Mesoscale noises are seen in the warming signature and confirmed by satellite microwave SST data. Model experiments are carried out to quantitatively evaluate the effects of key processes. The results reveal that the surface turbulent heat flux (primarily latent heat flux) is the most important process (contribution > 68%) in driving and damping the SST warming for most events, while the roles of the Indonesian Throughflow (~15%) and local wind forcing are secondary. A suitable air temperature warming is essential to reproducing the reduced surface latent heat loss during the growth of SST warming (~66%), whereas the effect of the increased air humidity is negligibly small (1%). The established SST warming in the mature phase causes increased latent heat loss that initiates the decay of warming. A 20-member ensemble simulation is performed for the 2010/11 super Ningaloo Niño, which confirms the strong influence of ocean internal processes in the redistribution of SST warming signatures. Oceanic eddies can dramatically modulate the magnitudes of local SST warming, particularly in offshore areas where the “signal-to-noise” ratio is low, raising a caution for evaluating the predictability of Ningaloo Niño and its environmental consequences.

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Xin-Zhong Liang, Arthur N. Samel, and Wei-Chyung Wang

Abstract

China's rainfall interannual predictability is generally believed to depend upon the accurate representation of its annual cycle as well as teleconnections with planetary surface anomalies, including tropical east Pacific sea surface temperature and Eurasian snow and soil moisture. A suite of general circulation model (GCM) simulations is used to ascertain the existence of these relationships. First, a comparison of thirty 1980–88 Atmospheric Model Intercomparison Project (AMIP) GCM simulations shows no clear correspondence between model skill to reproduce observed rainfall annual cycle and interannual variability. Thus, accurate representation of either component does not ensure the realistic simulation of the other. Second, diagnosis of the 1903–94 and 1950–97 National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3), ensemble integrations indicates the existence of teleconnections in which spring planetary surface anomalies lead China's summer rainfall variations. These teleconnections, however, are sensitive to initial conditions, which define distinct dynamic regimes during the integration period. In addition, analysis of the NCAR Climate System Model (CSM) 300-yr equilibrium simulation reveals that the teleconnections display decadal variations. These results cast doubt on the traditional physical mechanisms that explain China's rainfall teleconnections and, hence, emphasize the need to incorporate interactions between planetary surface anomalies and specific dynamic regimes.

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Ling Ling Liu, Wei Wang, and Rui Xin Huang

Abstract

Wind stress and tidal dissipation are the most important sources of mechanical energy for maintaining the oceanic general circulation. The contribution of mechanical energy due to tropical cyclones can be a vitally important factor in regulating the oceanic general circulation and its variability. However, previous estimates of wind stress energy input were based on low-resolution wind stress data in which strong nonlinear events, such as tropical cyclones, were smoothed out.

Using a hurricane–ocean coupled model constructed from an axisymmetric hurricane model and a three-layer ocean model, the rate of energy input to the world’s oceans induced by tropical cyclones over the period from 1984 to 2003 was estimated. The energy input is estimated as follows: 1.62 TW to the surface waves and 0.10 TW to the surface currents (including 0.03 TW to the near-inertial motions). The rate of gravitational potential energy increase due to tropical cyclones is 0.05 TW. Both the energy input from tropical cyclones and the increase of gravitational potential energy of the ocean show strong interannual and decadal variability with an increasing rate of 16% over the past 20 years. The annual mean diapycnal upwelling induced by tropical cyclones over the past 20 years is estimated as 39 Sv (Sv ≡ 106 m3 s−1). Owing to tropical cyclones, diapycnal mixing in the upper ocean (below the mixed layer) is greatly enhanced. Within the regimes of strong activity of tropical cyclones, the increase of diapycnal diffusivity is on the order of (1 − 6) × 10−4 m2 s−1. The tropical cyclone–related energy input and diapycnal mixing may play an important role in climate variability, ecology, fishery, and environments.

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Wei Li, Yuanfu Xie, Shiow-Ming Deng, and Qi Wang

Abstract

In recent years, the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) has developed a space and time mesoscale analysis system (STMAS), which is currently a sequential three-dimensional variational data assimilation (3DVAR) system and is developing into a sequential 4DVAR in the near future. It is implemented by using a multigrid method based on a variational approach to generate grid analyses. This study is to test how STMAS deals with 2D Doppler radar radial velocity and to what degree the 2D Doppler radar radial velocity can improve the conventional (in situ) observation analysis. Two idealized experiments and one experiment with real Doppler radar radial velocity data, handled by STMAS, demonstrated significant improvement of the conventional observation analysis. Because the radar radial wind data can provide additional wind information (even it is incomplete: e.g., missing tangential wind vector), the analyses by assimilating both radial wind data and conventional data showed better results than those by assimilating only conventional data. Especially in the case of sparse conventional data, radar radial wind data can provide significant information and improve the analyses considerably.

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Chia-Chi Wang, Wei-Liang Lee, and Chia Chou

ABSTRACT

Aerosols are one of the key factors influencing the hydrological cycle and radiation balance of the climate system. Although most aerosols deposit near their sources, the induced cooling effect is on a global scale and can influence the tropical atmosphere through slow processes, such as air–sea interactions. This study analyzes several simulations of fully coupled atmosphere–ocean climate models under the influence of anthropogenic aerosols, with the concentrations of greenhouse gases kept constant. In the cooling simulations, precipitation is reduced in deep convective areas but increased around the edges of convective areas, which is opposite to the “rich-get-richer” phenomenon in global warming scenarios in the first-order approximation. Tropical convection is intensified with a shallower depth, and tropical circulations are enhanced. The anomalous gross moist stability (M′) mechanism and the upped-ante mechanism can be used to explain the dynamic and thermodynamic processes in the changes in tropical precipitation and convection. There is a northward cross-equatorial energy transport due to the cooler Northern Hemisphere in most of the simulations, together with the southward shift of the intertropical convergence zone (ITCZ) and the enhancement of the Hadley circulation. The enhancement of the Hadley circulation is more consistent between models than the changes of the Walker circulation. The change in the Hadley circulation is not as negligible as in the warming cases in previous studies, which supports the consistency of the ITCZ shift in cooling simulations.

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Christopher Davis, Wei Wang, Jimy Dudhia, and Ryan Torn

Abstract

The representation of tropical cyclone track, intensity, and structure in a set of 69 parallel forecasts performed at each of two horizontal grid increments with the Advanced Research Hurricane (AHW) component of the Weather and Research and Forecasting Model (WRF) is evaluated. These forecasts covered 10 Atlantic tropical cyclones: 6 from the 2005 season and 4 from 2007. The forecasts were integrated from identical initial conditions produced by a cycling ensemble Kalman filter. The high-resolution forecasts used moving, storm-centered nests of 4- and 1.33-km grid spacing. The coarse-resolution forecasts consisted of a single 12-km domain (which was identical to the outer domain in the forecasts with nests). Forecasts were evaluated out to 120 h. Novel verification techniques were developed to evaluate forecasts of wind radii and the degree of storm asymmetry. Intensity (maximum wind) and rapid intensification, as well as wind radii, were all predicted more accurately with increased horizontal resolution. These results were deemed to be statistically significant based on the application of bootstrap confidence intervals. No statistically significant differences emerged regarding storm position errors between the two forecasts. Coarse-resolution forecasts tended to overpredict the extent of winds compared to high-resolution forecasts. The asymmetry of gale-force winds was better predicted in the coarser-resolution simulation, but asymmetry of hurricane-force winds was predicted better at high resolution. The skill of the wind radii forecasts decayed gradually over 120 h, suggesting a synoptic-scale control of the predictability of outer winds.

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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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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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Bin Deng, Shoudong Liu, Wei Xiao, Wei Wang, Jiming Jin, and Xuhui Lee

Abstract

Models of lake physical processes provide the lower flux boundary conditions for numerical predictions of weather and climate in lake basins. So far, there have been few studies on evaluating lake model performance at the diurnal time scale and against flux observations. The goal of this paper is to evaluate the National Center for Atmospheric Research Community Land Model version 4–Lake, Ice, Snow and Sediment Simulator using the eddy covariance and water temperature data obtained at a subtropical freshwater lake, Lake Taihu, in China. Both observations and model simulations reveal that convective overturning was commonplace at night and timed when water switched from being statically stable to being unstable. By reducing the water thermal diffusivity to 2% of the value calculated with the Henderson–Sellers parameterization, the model was able to reproduce the observed diurnal variations in water surface temperature and in sensible and latent heat fluxes. The small diffusivity suggests that the drag force of the sediment layer in this large (2500 km2) and shallow (2-m depth) lake may be strong, preventing unresolved vertical motions and suppressing wind-induced turbulence. Model results show that a large fraction of the incoming solar radiation energy was stored in the water during the daytime, and the stored energy was diffused upward at night to sustain sensible and latent heat fluxes to the atmosphere. Such a lake–atmosphere energy exchange modulated the local climate at the daily scale in this shallow lake, which is not seen in deep lakes where dominant lake–atmosphere interactions often occur at the seasonal scale.

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