Abstract

The Naval Research Laboratory’s limited-area numerical prediction system, a version of Navy Operational Regional Atmospheric Prediction System, was used to investigate the interaction between Hurricane Florence (1988) and its upper-tropospheric environment. The model was initialized with the National Meteorological Center (now the National Centers for Environmental Prediction)/Regional Analysis and Forecasting Systems 2.5° analysis at 0000 UTC 9 September 1988, enhanced by a set of Omega dropwindsonde data through a three-pass nested-grid objective analysis.

Diagnosis of the 200-mb level structure of the 12-h forecast valid for 1200 UTC 9 September 1988 showed that the outflow layer was highly asymmetric with an outflow jet originating at approximately 3° north of the storm. In agreement with the result of an idealized simulation (), there was a thermally direct, circum-jet secondary circulation in the jet entrance region and a thermally indirect one in a reversed direction in the jet exit region. In several previous studies, it was postulated that an approaching westerly jet had modulated the convection and intensity variations of Florence. In a variational numerical experiment in this study, the approaching westerly jet was flattened out by repeatedly setting the jet-level meridional wind component and zonal temperature perturbations to zero in the normal mode initialization procedure. Compared with the control experiment, the variational experiment showed that the sudden burst of Florence’s inner core convection was highly correlated with the approaching upper-tropospheric westerly jet. These experiments also suggested that the approaching upper-tropospheric westerly jet was crucial to the intensification of Florence’s inner core convection between 1000 and 1500 UTC 9 September, which occurred prior to the deepening of the minimum sea level pressure (from 997 to 987 mb) between 1200 UTC 9 September and 0000 UTC 10 September.

Many earlier studies have attempted an explanation for the effect on tropical cyclones of upper-tropospheric forcings from the eddy angular momentum approach. The result of this study provides an alternative but complementary mechanism of the interaction between an upper-level westerly trough and a tropical cyclone.

Abstract

Extensive sensitivity experiments with an axisymmetric tropical cyclone model that includes the Bets convective parameterization scheme are carded out. The sensitivity of the model storm evolution to the convective adjustment parameters is studied. These results show that the model storm leads to earlier development as the adjustment time scale becomes small and the stability weight on the moist adiabat in the lower atmosphere is increased. The model storm evolution is very sensitive to variations in the saturation pressure departure at the lowermost model integer level and the storm at mature stage has a lower central pressure as the magnitude of the saturation pressure departure is increased. The adjustment parameters affect the grid-scale precipitation as well as the convective precipitation and the precipitation is especially sensitive to changes in the saturation pressure departure.

Sensitivity of the model to variations in the sea surface temperature, latitude, initial vortex amplitude, initial moisture distribution, and radiation is also investigated. The results of the numerical simulations are similar to previous studies. Sensitivity studies with various horizontal resolutions show that the subgrid-scale heating becomes a larger fraction of the total heating as the horizontal grid size is increased.

Abstract

The structure and dynamics of the outflow layer of tropical cyclones are studied using a three-dimensional numerical model. Weak and strong tropical cyclones are produced by the numerical model when starting from idealized initial vortices embedded in mean hurricane soundings. The quasi-steady state outflow layers of both the weak and strong tropical cyclones have similar characteristics 1) the circulations are mainly anticyclonic (except for a small region of cyclonic flow near the center) and highly asymmetric about the center, 2) the outflow layer is dominated by a narrow but elongated outflow jet, which contributes up to 50% of the angular momentum transport and 3) the air particles in the outflow jet mostly originate from the lower level, following “in-up-and-out” trajectories.

We found that there are secondary circulations around the outflow jet, very much like those associated with midlatitude westerly jet streaks. In the jet entrance region, the secondary circulation is thermally direct. That is, the ascending motion is located on the anticyclonic shear side of the jet, and the descending motion on the cyclonic shear side. There is a radially outward (perpendicular to the jet) flow above the jet and inflow below it. In the jet exit region, the secondary circulation is weaker and reversed in its direction (thermally indirect). The secondary circulations leave pronounced signatures on the relative humidity, potential vorticity, and tropopause height fields. The secondary circulation is more intense in the stronger tropical cyclone (with a stronger outflow jet) than in the weaker tropical cyclone.

The sensitivities to upper-tropospheric forcing of the outflow are tested in numerical experiments with prescribed forcings. It is found that the simulated tropical cyclone intensifies when its upper levels within a radius of approximately 500 km are accelerated and forced to be more divergent. Convection plays a key role in transforming the upper level divergence into low level convergence. In another experiment, additional regions of convection are initiated in the ascending branches of the circum-jet secondary circulations away from the inner region when the outflow jet between the radii of 500 and 1000 km is accelerated. These regions of convection become competitive with the inner core convection and eventually weaken the tropical cyclone. In both experiments, cumulus convection is the major link between the upper-level forcing and tropical cyclone's response.

Abstract

Data from the Special Sensor Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) spacecraft have been used to study the precipitation patterns associated with Hurricane Hugo (1989). Results indicate the intensification of Hugo was associated with increases in SSM/I-derived total latent heat release and increases in heavier rainfall rates near the storm center. This study also shows that SSM/I rainfall rates prior to the landfall of Hugo at Charleston, South Carolina, compared favorably with raingage observations. Additionally, data from the 85-GHz channel was used to monitor the extent of convection near the storm's center. As Hugo intensified, the areal coverage of deep convection increased. Furthermore, the 85-GHz brightness-temperature imagery was useful in determining the location of Hugo's low-level center. These results indicate the potential of using SSM/I data in the analysis and prediction of tropical cyclones in an operational environment.

Abstract

The National Weather Service's Cooperative Observer Program (COOP) is a valuable climate data resource that provides manually observed information on temperature and precipitation across the nation. These data are part of the climate dataset and continue to be used in evaluating weather and climate models. Increasingly, weather and climate information is also available from automated weather stations. A comparison between these two observing methods is performed in North Carolina, where 13 of these stations are collocated. Results indicate that, without correcting the data for differing observation times, daily temperature observations are generally in good agreement (0.96 Pearson product–moment correlation for minimum temperature, 0.89 for maximum temperature). Daily rainfall values recorded by the two different systems correlate poorly (0.44), but the correlations are improved (to 0.91) when corrections are made for the differences in observation times between the COOP and automated stations. Daily rainfall correlations especially improve with rainfall amounts less than 50 mm day⁻¹. Temperature and rainfall have high correlation (nearly 1.00 for maximum and minimum temperatures, 0.97 for rainfall) when monthly averages are used. Differences of the data between the two platforms consistently indicate that COOP instruments may be recording warmer maximum temperatures, cooler minimum temperatures, and larger amounts of rainfall, especially with higher rainfall rates. Root-mean-square errors are reduced by up to 71% with the day-shift and hourly corrections.

This study shows that COOP and automated data [such as from the North Carolina Environment and Climate Observing Network (NCECONet)] can, with simple corrections, be used in conjunction for various climate analysis applications such as climate change and site-to-site comparisons. This allows a higher spatial density of data and a larger density of environmental parameters, thus potentially improving the accuracy of the data that are relayed to the public and used in climate studies.

Normal temperatures, which are calculated by the National Climatic Data Center for locations across the country, are quality-controlled, smoothed 30-yr-average temperatures. They are used in many facets of media, industry, and meteorology, and a given day's normal maximum and minimum temperatures are often used synonymously with what the observed temperature extremes “should be.” However, allowing some leeway to account for natural daily and seasonal variations can more accurately reflect the ranges of temperature that we can expect on a particular day—a “normal range.” Providing such a range, especially to the public, presents a more accurate perspective on what the temperature “usually” is on any particular day of the year. One way of doing this is presented in this study for several locations across North Carolina. The results yield expected higher variances in the cooler months and seem to well represent the varied weather that locations in North Carolina tend to experience. Day-to-day variations in the normal range are larger than expected, but are retained rather than smoothed. The method is simple and applicable to any location with a complete 30-yr record and with a temperature variance time series that follows a bell curve. The normal-range product has many potential applications.

Abstract

Midlatitude cyclones develop off the Carolinas during winters and move north producing gale-force winds, ice, and heavy snow. It is believed that boundary-layer and air-sea interaction processes are very important during the development stages of these East Coast storms. The marine boundary layer (MBL) off the mid- Atlantic coastline is highly baroclinic due to the proximity of the Gulf Stream just offshore.

Typical horizontal distances between the Wilmington coastline and the western edge of the Gulf Stream vary between 90 and 250 km annually, and this distance can deviate by over 30 km within a single week. While similar weekly Gulf Stream position standard deviations also exist at Cape Hatteras, the average annual distance to the Gulf Stream frontal zone is much smaller off Cape Hatteras, normally ranging between 30 and 100 km.

This research investigates the low-level baroclinic conditions present prior to observed storm events. The examination of nine years of data on the Gulf Stream position and East Coast winter storms seems to indicate that the degree of low-level baroclinicity and modification existing prior to a cyclonic event may significantly affect the rate of cyclonic deepening off the mid-Atlantic coastline. Statistical analyses linking the observed surface-pressure decrease with both the Gulf Stream frontal location and the prestorm coastal baroclinic conditions are presented. These results quantitatively indicate that Gulf Stream-induced wintertime baroclinicity may significantly affect the regional intensification of East Coast winter cyclones.

Abstract

Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.

Abstract

A satellite–model coupled procedure for assimilating geostationary satellite sounder data was adapted to a mesoscale analysis and forecast system jointly developed by the Naval Research Laboratory and the Air Force Research Laboratory. The coupled procedure involves the use of the model output fields as the first guess for the thermodynamic retrievals. Atmospheric thermodynamic profiles and ground temperatures were retrieved from observed radiances of the VISSR Atmospheric Sounder (VAS) on board the Geostationary Operational Environmental Satellite. The successive corrections objective analysis scheme in the mesoscale analysis and forecast system was modified to consider the horizontal spatial correlation of the satellite data. The procedure was tested using a wintertime case from the 1986 Genesis of Atlantic Lows Experiment project. The retrievals generated by the coupled method were modestly improved relative to independent stand-alone retrievals. Coupled analyses and forecasts of temperature and moisture fields compared favorably to forecasts from a control run without the VAS assimilation.

Abstract

The successive correction scheme of Bratseth, which converges to optimum interpolation, is applied for the numerical analysis of data collected during the Genesis of Atlantic Lows Experiment. A first guess for the analysis is provided by a 12-h forecast produced by integrating a limited-area model from a prior coarse operational analysis. Initially, univariate analyses of the mass and wind fields are produced. To achieve the coupling of the mass and wind fields, additional iterations on the geopotential are performed by extrapolating the geopotential to grid points, using improving estimates of the geostrophic wind. This improved geostrophic wind is then used to update the geostrophic component of the initial univariate wind analysis. Use of a background forecast produces much improved mesoscale structures in the analysis. Enhanced gradients of the geopotential and larger wind shears are the result of the coupling of the mass and wind fields, particularly in regions of lower data density. Application of the vertical mode initialization scheme of Bourke and McGregor is used to diagnose the divergent component of the mesoscale circulations produced with the analysis scheme.