Fuqing Zhang

Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model

Abstract Accurate depiction of meteorological conditions, especially within the planetary boundary layer (PBL), is important for air pollution modeling, and PBL parameterization schemes play a critical role in simulating the boundary layer. This study examines the sensitivity of the performance of the Weather Research and Forecast (WRF) model to the use of three different PBL schemes [Mellor–Yamada–Janjic (MYJ), Yonsei University (YSU), and the asymmetric convective model, version 2 (ACM2)]. Comparison of surface and boundary layer observations with 92 sets of daily, 36-h high-resolution WRF simulations with different schemes over Texas in July–September 2005 shows that the simulations with the YSU and ACM2 schemes give much less bias than with the MYJ scheme. Simulations with the MYJ scheme, the only local closure scheme of the three, produced the coldest and moistest biases in the PBL. The differences among the schemes are found to be due predominantly to differences in vertical mixing strength and entr...

Assimilation of Simulated Doppler Radar Observations with an Ensemble Kalman Filter

Assimilation of Doppler radar data into cloud models is an important obstacle to routine numerical weather prediction for convective-scale motions; the difficulty lies in initializing fields of wind, temperature, moisture, and condensate given only observations of radial velocity and reflectivity from the radar. This paper investigates the potential of the ensemble Kalman filter (EnKF), which estimates the covariances between observed variables and the state through an ensemble of forecasts, to assimilate radar observations at convective scales. In the basic experiment, simulated observations are extracted from a reference simulation of a splitting supercell and assimilated using the EnKF and the same numerical model that produced the reference simulation. The EnKF produces accurate analyses, including the unobserved variables, after roughly 30 min (or six scans) of radial velocity observations. Additional experiments, in which forecasts are made from the ensemble-mean analysis, reveal that forecast errors grow significantly in this simple system, so that the ability of the EnKF to track the reference solution is not simply because of stable system dynamics. It is also found that the covariances between radial velocity and temperature, moisture, and condensate are important to the quality of the analyses, as is the initialization chosen for the ensemble members prior to assimilating the first observations. These results are promising, especially given the ease of implementing the EnKF. A number of important issues remain, however, including the initialization of the ensemble prior to the first observation, the treatment of uncertainty in the environmental sounding, the role of error in the forecast model (particularly the microphysical parameterizations), and the treatment of lateral boundary conditions.

Impacts of Initial Estimate and Observation Availability on Convective-Scale Data Assimilation with an Ensemble Kalman Filter

The ensemble Kalman filter (EnKF) uses an ensemble of short-range forecasts to estimate the flow-dependent background error covariances required in data assimilation. The feasibility of the EnKF for convective-scale data assimilation has been previously demonstrated in perfect-model experiments using simulated observations of radial velocity from a supercell storm. The present study further explores the potential and behavior of the EnKF at convective scales by considering more realistic initial analyses and variations in the availability and quality of the radar observations. Assimilation of simulated radial-velocity observations every 5 min where there is significant reflectivity using 20 ensemble members proves to be successful in most realistic observational scenarios for simulated supercell thunderstorms, although the same degree of success may not be readily expected with real observations and an imperfect model, at least with the present EnKF implementation. Even though the filter converges toward the truth simulation faster from a better initial estimate, an experiment with the initial estimate of the supercell displaced by 10 km still yields an accurate estimate of the storm for both observed and unobserved variables within 40 min. Similarly, radial-velocity observations below 2 km are certainly beneficial to capturing the storm (especially the detailed cold pool structure), but in their absence the assimilation scheme can still achieve a comparably accurate estimate of the state of the storm given a slightly longer assimilation period. An experiment with radar observations only above 4 km fails to assimilate the storm properly, but, with the addition of a hypothetical surface mesonet taking wind and temperature observations, the EnKF can again provide a good estimate of the storm. The supercell can also be successfully assimilated in the case of radar observations only below 4 km (such as those from the ground-based mobile radars). More frequent observations can help the storm assimilation initially, but the benefit diminishes after half an hour. Results presented here indicate that the vertical resolution and the uncertainty of observations, for the typical range of most of the observational radars, would have little impact on the overall performance of the EnKF in assimilating the storm.

Cloud-Resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter

Abstract This study explores the assimilation of Doppler radar radial velocity observations for cloud-resolving hurricane analysis, initialization, and prediction with an ensemble Kalman filter (EnKF). The case studied is Hurricane Humberto (2007), the first landfalling hurricane in the United States since the end of the 2005 hurricane season and the most rapidly intensifying near-landfall storm in U.S. history. The storm caused extensive damage along the southeast Texas coast but was poorly predicted by operational models and forecasters. It is found that the EnKF analysis, after assimilating radial velocity observations from three Weather Surveillance Radars-1988 Doppler (WSR-88Ds) along the Gulf coast, closely represents the best-track position and intensity of Humberto. Deterministic forecasts initialized from the EnKF analysis, despite displaying considerable variability with different lead times, are also capable of predicting the rapid formation and intensification of the hurricane. These forecasts...

Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments

Abstract The feasibility of using an ensemble Kalman filter (EnKF) to retrieve the wind and temperature fields in an isolated convective storm has been tested by applying the technique to observations of the 17 May 1981 Arcadia, Oklahoma, tornadic supercell. Radial-velocity and reflectivity observations from a single radar were assimilated into a nonhydrostatic, anelastic numerical model initialized with an idealized (horizontally homogeneous) base state. The assimilation results were compared to observations from another Doppler radar, the results of dual-Doppler wind syntheses, and in situ measurements from an instrumented tower. Observation errors make it more difficult to assess EnKF performance than in previous storm-scale EnKF experiments that employed synthetic observations and a perfect model; nevertheless, the comparisons in this case indicate that the locations of the main updraft and mesocyclone in the Arcadia storm were determined rather accurately, especially at midlevels. The magnitudes of v...

Effects of Moist Convection on Mesoscale Predictability

In a previous study by the authors, it was shown that the problematic numerical prediction of the 24‐25 January 2000 snowstorm along the east coast of the United States was in some measure due to rapid error growth at scales below 500 km. In particular they found that moist processes were responsible for this strong initial-condition sensitivity of the 1‐2-day prediction of mesoscale forecast aspects. In the present study they take a more systematic look at the processes by which small initial differences (‘‘errors’’) grow in those numerical forecasts. For initial errors restricted to scales below 100 km, results show that errors first grow as small-scale differences associated with moist convection, then spread upscale as their growth begins to slow. In the context of mesoscale numerical predictions with 30-km resolution, the initial growth is associated with nonlinearities in the convective parameterization (or in the explicit microphysical parameterizations, if no convective parameterization is used) and proceeds at a rate that increases as the initial error amplitude decreases. In higherresolution (3.3 km) simulations, errors first grow as differences in the timing and position of individual convective cells. Amplification at that stage occurs on a timescale on the order of 1 h, comparable to that of moist convection. The errors in the convective-scale motions subsequently influence the development of meso- and larger-scale forecast aspects such as the position of the surface low and the distribution of precipitation, thus providing evidence that growth of initial errors from convective scales places an intrinsic limit on the predictability of larger scales.

Generation of Mesoscale Gravity Waves in Upper-Tropospheric Jet–Front Systems

Abstract Multiply nested mesoscale numerical simulations with horizontal resolution up to 3.3 km are performed to study the generation of mesoscale gravity waves during the life cycle of idealized baroclinic jet–front systems. Long-lived vertically propagating mesoscale gravity waves with horizontal wavelengths ∼100–200 km are simulated originating from the exit region of the upper-tropospheric jet streak, in a manner consistent with past observational studies. The residual of the nonlinear balance equation is found to be a useful index in diagnosing flow imbalance and predicting wave generation. The imbalance diagnosis and model simulations suggest that balance adjustment, as a generalization of geostrophic adjustment, is likely responsible for generating these mesoscale gravity waves. It is hypothesized that, through balance adjustment, the continuous generation of flow imbalance from the developing baroclinic wave will lead to the continuous radiation of gravity waves.

Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part I: Perfect model experiments

Abstract Through observing system simulation experiments, this two-part study exploits the potential of using the ensemble Kalman filter (EnKF) for mesoscale and regional-scale data assimilation. Part I focuses on the performance of the EnKF under the perfect model assumption in which the truth simulation is produced with the same model and same initial uncertainties as those of the ensemble, while Part II explores the impacts of model error and ensemble initiation on the filter performance. In this first part, the EnKF is implemented in a nonhydrostatic mesoscale model [the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)] to assimilate simulated sounding and surface observations derived from simulations of the “surprise” snowstorm of January 2000. This is an explosive East Coast cyclogenesis event with strong error growth at all scales as a result of interactions between convective-, meso-, and subsynoptic-scale dynamics. It is found that the EnKF is very effective in keeping th...

Internal gravity waves from atmospheric jets and fronts

For several decades, jets and fronts have been known from observations to be significant sources of internal gravity waves in the atmosphere. Motivations to investigate these waves have included their impact on tropospheric convection, their contribution to local mixing and turbulence in the upper troposphere, their vertical propagation into the middle atmosphere, and the forcing of its global circulation. While many different studies have consistently highlighted jet exit regions as a favored locus for intense gravity waves, the mechanisms responsible for their emission had long remained elusive: one reason is the complexity of the environment in which the waves appear; another reason is that the waves constitute small deviations from the balanced dynamics of the flow generating them; i.e., they arise beyond our fundamental understanding of jets and fronts based on approximations that filter out gravity waves. Over the past two decades, the pressing need for improving parameterizations of nonorographic gravity waves in climate models that include a stratosphere has stimulated renewed investigations. The purpose of this review is to present current knowledge and understanding on gravity waves near jets and fronts from observations, theory, and modeling, and to discuss challenges for progress in coming years.

Astronomical calibration of loess-paleosol deposits at Luochuan, central Chinese Loess Plateau

Abstract The 140 m loess–paleosol profile at Luochuan in the central Chinese Loess Plateau was sampled at 5-cm intervals in loess units and at 3 cm in paleosol units, in order to obtain a high resolution climatic record covering the past 2.5 million years. All samples were measured for magnetic susceptibility, which is regarded as a good proxy index of the East Asian summer monsoon strength. On the basis of the astronomical theory of Pleistocene climatic change, an age model of the Luochuan loess–paleosol sequence was developed by tuning the magnetic susceptibility record to time-series of insolation changes. The results show that the ages of the boundaries between the Malan and Lishi, and Lishi and Wucheng loess formations are 71 and 1320 kyr BP, respectively. The onset of loess accumulation is at 2470 kyr BP. Our age model was tested by comparing the orbitally derived ages with absolute age determinations of magnetic reversals, and cross-spectrum analyzing with solar radiation variations for summer at 65°N. These indicate that the calibration provides a reliable time scale for the Luochuan loess–paleosol deposit.