The objective of this work is to suggest a new warm-fog visibility parameterization scheme for numerical weather prediction (NWP) models. In situ observations collected during the Radiation and Aerosol Cloud Experiment, representing boundary layer low-level clouds, were used to develop a parameterization scheme between visibility and a combined parameter as a function of both droplet number concentration N d and liquid water content (LWC). The current NWP models usually use relationships between extinction coefficient and LWC. A newly developed parameterization scheme for visibility, Vis ϭ f (LWC, N d ), is applied to the NOAA Nonhydrostatic Mesoscale Model. In this model, the microphysics of fog was adapted from the 1D Parameterized Fog (PAFOG) model and then was used in the lower 1.5 km of the atmosphere. Simulations for testing the new parameterization scheme are performed in a 50-km innermost-nested simulation domain using a horizontal grid spacing of 1 km centered on Zurich Unique Airport in Switzerland. The simulations over a 10-h time period showed that visibility differences between old and new parameterization schemes can be more than 50%. It is concluded that accurate visibility estimates require skillful LWC as well as N d estimates from forecasts. Therefore, the current models can significantly over-/ underestimate Vis (with more than 50% uncertainty) depending on environmental conditions. Inclusion of N d as a prognostic (or parameterized) variable in parameterizations would significantly improve the operational forecast models.

The Operational Multiscale Environment Model with Grid Adaptivity (OMEGA) and its embedded Atmospheric Dispersion Model is a new atmospheric simulation system for real-time hazard prediction, conceived out of a need to advance the state of the art in numerical weather prediction in order to improve the capability to predict the transport and diffusion of hazardous releases. OMEGA is based upon an unstructured grid that makes possible a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from a few tens of meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning because its unstructured grid permits the addition of grid elements at any point in space and time. In particular, unstructured grid cells in the horizontal dimension can increase local resolution to better capture topography or the important physical features of the atmospheric circulation and cloud dynamics. This means that OMEGA can readily adapt its grid to stationary surface or terrain features, or to dynamic features in the evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first model to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and hence real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with data.

Fully nonlinear mesoscale model simulations are used to investigate the momentum fluxes of gravity waves that emerge at a “far-field” height of 6 km from steady unsheared flow over both an axisymmetric and elliptical obstacle for nondimensional mountain heights ĥm = Fr−1 in the range 0.1–5, where Fr is the surface Froude number. Fourier- and Hilbert-transform diagnostics of model output yield local estimates of phase-averaged momentum flux, while area integrals of momentum flux quantify the amount of surface pressure drag that translates into far-field gravity waves, referred to here as the “wave drag” component. Estimates of surface and wave drag are compared to parameterization predictions and theory. Surface dynamics transition from linear to high-drag (wave breaking) states at critical inverse Froude numbers Frc−1 predicted to within 10% by transform relations. Wave drag peaks at Frc−1 < ĥm ≲ 2, where for the elliptical obstacle both surface and wave drag vacillate owing to cyclical buildup and breakdown of waves. For the axisymmetric obstacle, this occurs only at ĥm = 1.2. At ĥm ≳ 2–3 vacillation abates and normalized pressure drag assumes a common normalized form for both obstacles that varies approximately as ĥm−1.3. Wave drag in this range asymptotes to a constant absolute value that, despite its theoretical shortcomings, is predicted to within 10%–40% by an analytical relation based on linear clipped-obstacle drag for a Sheppard-based prediction of dividing streamline height. Constant wave drag at ĥm ∼ 2–5 arises despite large variations with ĥm in the three-dimensional morphology of the local wave momentum fluxes. Specific implications of these results for the parameterization of subgrid-scale orographic drag in global climate and weather models are discussed.

In this study, the role of the Saharan air layer (SAL) is investigated in the development and intensification of tropical cyclones (TCs) via modifying environmental stability and moisture, using multisensor satellite data, long-term TC track and intensity records, dust data, and numerical simulations with a state-of-the-art Weather Research and Forecasting model (WRF). The long-term relationship between dust and Atlantic TC activity shows that dust aerosols are negatively associated with hurricane activity in the Atlantic basin, especially with the major hurricanes in the western Atlantic region. Numerical simulations with the WRF for specific cases during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) experiment show that, when vertical temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS) were assimilated into the model, detailed features of the warm and dry SAL, including the entrainment of dry air wrapping around the developing vortex, are well simulated. Active tropical disturbances are found along the southern edge of the SAL. The simulations show an example where the dry and warm air of the SAL intruded into the core of a developing cyclone, suppressing convection and causing a spin down of the vortical circulation. The cyclone eventually weakened.To separate the contributions from the warm temperature and dry air associated with the SAL, two additional simulations were performed, one assimilating only AIRS temperature information (AIRST) and one assimilating only AIRS humidity information (AIRSH) while keeping all other conditions the same. The AIRST experiments show almost the same simulations as the full AIRS assimilation experiments, whereas the AIRSH is close to the non-AIRS simulation. This is likely due to the thermal structure of the SAL leading to low-level temperature inversion and increased stability and vertical wind shear. These analyses suggest that dry air entrainment and the enhanced vertical wind shear may play the direct roles in leading to the TC suppression. On the other hand, the warm SAL temperature may play the indirect effects by enhancing vertical wind shear; increasing evaporative cooling; and initiating mesoscale downdrafts, which bring dry air from the upper troposphere to the lower levels.

The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is an atmospheric simulation system that links the latest methods in computational fluid dynamics and high-resolution gridding technologies with numerical weather prediction. In the fall of 1999, OMEGA was used for the first time to examine the structure and evolution of a hurricane (Floyd, 1999). The first simulation of Floyd was conducted in an operational forecast mode; additional simulations exploiting both the static as well as the dynamic grid adaptation options in OMEGA were performed later as part of a sensitivity-capability study. While a horizontal grid resolution ranging from about 120 km down to about 40 km was employed in the operational run, resolutions down to about 15 km were used in the sensitivity study to explicitly model the structure of the inner core. All the simulations produced very similar storm tracks and reproduced the salient features of the observed storm such as the recurvature off the Florida coast with an average 48-h position error of 65 km. In addition, OMEGA predicted the landfall near Cape Fear, North Carolina, with an accuracy of less than 100 km up to 96 h in advance. It was found that a higher resolution in the eyewall region of the hurricane, provided by dynamic adaptation, was capable of generating better-organized cloud and flow fields and a well-defined eye with a central pressure lower than the environment by roughly 50 mb. Since that time, forecasts were performed for a number of other storms including Georges (1998) and six 2000 storms (Tropical Storms Beryl and Chris, Hurricanes Debby and Florence, Tropical Storm Helene, and Typhoon Xangsane). The OMEGA mean track error for all of these forecasts of 101, 140, and 298 km at 24, 48, and 72 h, respectively, represents a significant improvement over the National Hurricane Center (NHC) 1998 average of 156, 268, and 374 km, respectively. In a direct comparison with the GFDL model, OMEGA started with a considerably larger position error yet came within 5% of the GFDL 72-h track error. This paper details the simulations produced and documents the results, including a comparison of the OMEGA forecasts against satellite data, observed tracks, reported pressure lows and maximum wind speed, and the rainfall distribution over land.