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Adel F. Hanna, Duane E. Stevens, and Elmar R. Reiter

Abstract

A two-level, global, spectral model is used to study the response of the atmosphere to sea surface temperature anomalies. Two sea surface temperature anomaly patterns are investigated. The first, called the El Niño pattern (Experiment 1), represents a warm anomaly in the equatorial Pacific, whereas the second pattern (Experiment 2) represents coupled midlatitude (cold)/ equatorial (warm) sea surface temperature anomalies in the pacific Ocean.

The results demonstrate that both of these sea surface temperature anomaly patterns produce statistically significant midtropospheric geopotential responses in middle latitudes. However, the geopotential response forced by the coupled sea surface temperature anomaly is qualitatively more similar to the geopotential height pattern which is observed in association with the negative phase of the Southern Oscillation (Horel and Wallace). Analysis of the differences (anomaly minus control) of the meridional transports of momentum. sensible heat and latent heat indicates that the coupled pattern tends to largely enhance the northward transports of momentum and sensible heat, especially for the transient and stationary eddy components. The maximum difference in the total (transient, stationary eddies and mean meridional circulation) transport of momentum is nearly double that revealed by the El Niño experiment.

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Kiran Alapaty, Donald T. Olerud Jr., Kenneth L. Schere, and Adel F. Hanna

Abstract

Objective analysis and diagnostic methods are used to provide hourly meteorological fields to many air quality simulation models. The viability of using predictions from the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model version 4 (MM4) together with four-dimensional data assimilation, technique to provide meteorological information to the U.S. EPA Regional Oxidant Model (ROM) was studied. Two numerical simulations were performed for eight days using the ROM for a domain covering the eastern United States. In the first case, diagnostically analyzed data were used to provide meteorological conditions, while in the second case the MM4's prognostic data were used. Comparisons of processed diagnostic and prognostic meteorological data indicated differences in dynamical, thermodynamical, and other derived variables. Uncertainties and forecast errors present in the predicted vertical temperature profiles led to estimation of lower mixed-layer heights (∼ 30%–50%) and a smaller diurnal range of atmospheric temperatures (∼ 2 K) compared with those obtained from the diagnostic data. Comparison of area-averaged horizontal winds for four subdomains indicated minor differences (∼ 1–2 m s−1). These differences systematically affected the estimation of other derived meteorological parameters, such as friction velocity and sensible heat flux. Processed emission data also showed some differences (∼ 1–5 ppb h−1) that resulted from the differing characteristics of the diagnostic and prognostic meteorological data.

Comparison of predicted concentrations of primary (emitted) chemical species such as NOx and reactive organic gases in the two numerical simulations indicated higher values (1–5 and 1–25 ppb, respectively) when the prognostic meteorological data were used. This result was consistent with the lower estimated values of the ROM's layer 1 and layer 2 heights (planetary boundary layer) with the prognostic meteorology. However, comparison of predicted ozone concentrations did not indicate similar features. Area averages of predicted concentrations of ozone for four subdomains indicated both increases and decreases (+1 5 to −10 ppb) over the area averages predicted by the ROM using diagnostic meteorological data. These results indicate that the prediction of trace gas concentrations and the nonlinearity in the model's chemistry are sensitive to the type of meteorological input used.

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Kiran Alapaty, Nelson L. Seaman, Devdutta S. Niyogi, and Adel F. Hanna

Abstract

Large errors in atmospheric boundary layer (ABL) simulations can be caused by inaccuracies in the specification of surface characteristics in addition to assumptions and simplifications made in boundary layer formulations or other model deficiencies. For certain applications, such as air quality studies, these errors can have significant effects. To reduce such errors, a continuous surface data assimilation technique is developed. In this technique, surface-layer temperature and water vapor mixing ratio are directly assimilated by using the analyzed surface data. Then, the difference between the observations and model results is used to calculate adjustments to the surface fluxes of sensible and latent heat. These adjustments are then used to calculate a new estimate of the ground temperature, thereby affecting the simulated surface fluxes on the subsequent time step. This indirect data assimilation is applied simultaneously with the direct assimilation of surface data in the model's lowest layer, thereby maintaining greater consistency between the ground temperature and the surface-layer mass-field variables. A one-dimensional model was used to study the improvements that result from applying this technique for ABL simulations in two cases. It was found that application of the new technique led to significant reductions in ABL modeling errors.

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