Abstract

A regionally enhanced global (REG) data assimilation (DA) method is proposed. The technique blends high-resolution model information from a single or multiple limited-area model domains with global model and observational information to create a regionally enhanced analysis of the global atmospheric state. This single analysis provides initial conditions for both the global and limited-area model forecasts. The potential benefits of the approach for operational data assimilation are (i) reduced development cost, (ii) reduced overall computational cost, (iii) improved limited-area forecast performance from the use of global information about the atmospheric flow, and (iv) improved global forecast performance from the use of more accurate model information in the limited-area domains. The method is tested by an implementation on the U.S. Navy’s four-dimensional variational global data assimilation system and global and limited-area numerical weather prediction models. The results of the monthlong forecast experiments suggest that the REG DA approach has the potential to deliver the desired benefits.

Abstract

Dust storms are a significant weather phenomenon in the Iraq region in winter and spring. Real-time dust forecasting using the U.S. Navy’s Coupled Ocean–Atmospheric Mesoscale Prediction System (COAMPS) with an in-line dust aerosol model was conducted for Operation Iraqi Freedom (OIF) in March and April 2003. Daily forecasts of dust mass concentration, visibility, and optical depth were produced out to 72 h on nested grids of 9-, 27-, and 81-km resolution in two-way nest interaction. In this paper, the model is described, as are examples of its application during OIF. The model performance is evaluated using ground weather reports, visibility observations, and enhanced satellite retrievals. The comparison of the model forecasts with observations for the severe dust storms of OIF shows that COAMPS predicted the arrival and retreat of the major dust events within 2 h. In most cases, COAMPS predicted the intensity (reduction in visibility) of storms with an error of less than 1 km. The forecasts of the spatial distribution of dust fronts and dust plumes were consistent with those seen in the satellite images and the corresponding cold front observations. A statistical analysis of dust-related visibility for the OIF period reveals that COAMPS generates higher bias, rms, and relative errors at the stations having high frequencies of dust storms and near the source areas. The calculation of forecast accuracy shows that COAMPS achieved a probability of dust detection of 50%–90% and a threat score of 0.3–0.55 at the stations with frequent dust storms. Overall, the model predicted more than 85% of the observed dust and nondust weather events at the stations used in the verification for the OIF period. Comparisons of the forecast rates and statistical errors for the forecasts of different lengths (12–72 h) for both dust and dynamics fields during the strong dust storm of 26 March revealed little dependence of model accuracy on forecast length, implying that the successive COAMPS forecasts were consistent for the severest OIF dust event.

Abstract

The Trident Warrior observational field campaign conducted off the U.S. mid-Atlantic coast in July 2013 included the deployment of an unmanned aerial system (UAS) with several payloads on board for atmospheric and oceanic observation. These UAS observations, spanning seven flights over 5 days in the lowest 1550 m above mean sea level, were assimilated into a three-dimensional variational data assimilation (DA) system [the Naval Research Laboratory Atmospheric Variational Data Assimilation System (NAVDAS)] used to generate analyses for a numerical weather prediction model [the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)] with a coupled ocean model [the Naval Research Laboratory Navy Coastal Ocean Model (NCOM)]. The impact of the assimilated UAS observations on short-term atmospheric prediction performance is evaluated and quantified. Observations collected from 50 radiosonde launches during the campaign adjacent to the UAS flight paths serve as model forecast verification. Experiments reveal a substantial reduction of model bias in forecast temperature and moisture profiles consistently throughout the campaign period due to the assimilation of UAS observations. The model error reduction is most substantial in the vicinity of the inversion at the top of the model-estimated boundary layer. Investigations reveal a consistent improvement to prediction of the vertical position, strength, and depth of the boundary layer inversion. The relative impact of UAS observations is explored further with experiments of systematic denial of data streams from the NAVDAS DA system and removal of individual measurement sources on the UAS platform.

Abstract

The impact of ice phase cloud microphysical processes on prediction of tropical cyclone environment is examined for two microphysical parameterizations using the Coupled Ocean–Atmosphere Mesoscale Prediction System–Tropical Cyclone (COAMPS-TC) model. An older version of microphysical parameterization is a relatively typical single-moment scheme with five hydrometeor species: cloud water and ice, rain, snow, and graupel. An alternative newer method uses a hybrid approach of double moment in cloud ice and rain and single moment in the other three species. Basin-scale synoptic flow simulations point to important differences between these two schemes. The upper-level cloud ice concentrations produced by the older scheme are up to two orders of magnitude greater than the newer scheme, primarily due to differing assumptions concerning the ice nucleation parameterization. Significant (1°–2°C) warm biases near the 300-hPa level in the control experiments are not present using the newer scheme. The warm bias in the control simulations is associated with the longwave radiative heating near the base of the cloud ice layer. The two schemes produced different track and intensity forecasts for 15 Atlantic storms. Rightward cross-track bias and positive intensity bias in the control forecasts are significantly reduced using the newer scheme. Synthetic satellite imagery of Hurricane Igor (2010) shows more realistic brightness temperatures from the simulations using the newer scheme, in which the inner core structure is clearly discernible. Applying the synthetic satellite imagery in both quantitative and qualitative analyses helped to pinpoint the issue of excessive upper-level cloud ice in the older scheme.

Coastally trapped wind reversals along the U.S. west coast, which are often accompanied by a northward surge of fog or stratus, are an important warm-season forecast problem due to their impact on coastal maritime activities and airport operations. Previous studies identified several possible dynamic mechanisms that could be responsible for producing these events, yet observational and modeling limitations at the time left these competing interpretations open for debate. In an effort to improve our physical understanding, and ultimately the prediction, of these events, the Office of Naval Research sponsored an Accelerated Research Initiative in Coastal Meteorology during the years 1993–98 to study these and other related coastal meteorological phenomena. This effort included two field programs to study coastally trapped disturbances as well as numerous modeling studies to explore key dynamic mechanisms. This paper describes the various efforts that occurred under this program to provide an advancement in our understanding of these disturbances. While not all issues have been solved, the synoptic and mesoscale aspects of these events are considerably better understood.

Some of the highlights of an experiment designed to study coastal atmospheric phenomena along the California coast (Coastal Waves 1996 experiment) are described. This study was designed to address several problems, including the cross-shore variability and turbulent structure of the marine boundary layer, the influence of the coast on the development of the marine layer and clouds, the ageostrophy of the flow, the dynamics of trapped events, the parameterization of surface fluxes, and the supercriticality of the marine layer.

Based in Monterey, California, the National Center for Atmospheric Research (NCAR) C-130 Hercules and the University of North Carolina Piper Seneca obtained a comprehensive set of measurements on the structure of the marine layer. The study focused on the effects of prominent topographic features on the wind. Downstream of capes and points, narrow bands of high winds are frequently encountered. The NCAR-designed Scanning Aerosol Backscatter Lidar (SABL) provided a unique opportunity to connect changes in the depth of the boundary layer with specific features in the dynamics of the flow field.

An integral part of the experiment was the use of numerical models as forecast and diagnostic tools. The Naval Research Laboratory's Coupled Ocean Atmosphere Model System (COAMPS) provided high-resolution forecasts of the wind field in the vicinity of capes and points, which aided the deployment of the aircraft. Subsequently, this model and the MIUU (University of Uppsala) numerical model were used to support the analysis of the field data.

These are some of the most comprehensive measurements of the topographically forced marine layer that have been collected. SABL proved to be an exceptionally useful tool to resolve the small-scale structure of the boundary layer and, combined with in situ turbulence measurements, provides new insight into the structure of the marine atmosphere. Measurements were made sufficiently far offshore to distinguish between the coastal and open ocean effects. COAMPS proved to be an excellent forecast tool and both it and the MIUU model are integral parts of the ongoing analysis. The results highlight the large spatial variability that occurs directly in response to topographic effects. Routine measurements are insufficient to resolve this variability. Numerical weather prediction model boundary conditions cannot properly define the forecast system and often underestimate the wind speed and surface wave conditions in the nearshore region.

This study was a collaborative effort between the National Science Foundation, the Office of Naval Research, the Naval Research Laboratory, and the National Oceanographic and Atmospheric Administration.

Abstract

Three-dimensional simulations of the daytime thermally induced valley wind system for an idealized valley–plain configuration, obtained from nine nonhydrostatic mesoscale models, are compared with special emphasis on the evolution of the along-valley wind. The models use the same initial and lateral boundary conditions, and standard parameterizations for turbulence, radiation, and land surface processes. The evolution of the mean along-valley wind (averaged over the valley cross section) is similar for all models, except for a time shift between individual models of up to 2 h and slight differences in the speed of the evolution. The analysis suggests that these differences are primarily due to differences in the simulated surface energy balance such as the dependence of the sensible heat flux on surface wind speed. Additional sensitivity experiments indicate that the evolution of the mean along-valley flow is largely independent of the choice of the dynamical core and of the turbulence parameterization scheme. The latter does, however, have a significant influence on the vertical structure of the boundary layer and of the along-valley wind. Thus, this ideal case may be useful for testing and evaluation of mesoscale numerical models with respect to land surface–atmosphere interactions and turbulence parameterizations.

Abstract

The Coupled Air–Sea Processes and Electromagnetic Ducting Research (CASPER) project aims to better quantify atmospheric effects on the propagation of radar and communication signals in the marine environment. Such effects are associated with vertical gradients of temperature and water vapor in the marine atmospheric surface layer (MASL) and in the capping inversion of the marine atmospheric boundary layer (MABL), as well as the horizontal variations of these vertical gradients. CASPER field measurements emphasized simultaneous characterization of electromagnetic (EM) wave propagation, the propagation environment, and the physical processes that gave rise to the measured refractivity conditions. CASPER modeling efforts utilized state-of-the-art large-eddy simulations (LESs) with a dynamically coupled MASL and phase-resolved ocean surface waves. CASPER-East was the first of two planned field campaigns, conducted in October and November 2015 offshore of Duck, North Carolina. This article highlights the scientific motivations and objectives of CASPER and provides an overview of the CASPER-East field campaign. The CASPER-East sampling strategy enabled us to obtain EM wave propagation loss as well as concurrent environmental refractive conditions along the propagation path. This article highlights the initial results from this sampling strategy showing the range-dependent propagation loss, the atmospheric and upper-oceanic variability along the propagation range, and the MASL thermodynamic profiles measured during CASPER-East.