Ananthakrishna Sarma

An Operational Multiscale Hurricane Forecasting System

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.

A Godunov-type Finite-Volume Scheme for Flows on the Meso- and Micro-scales

§A Godunov-type finite volume scheme based on unstructured adaptive grids is described for simulating flows on the meso-, micro- and urban-scales. The higher-order spatial accuracy is achieved via gradient reconstruction techniques after van Leer and the total variation diminishing condition is enforced with the help of slope-limiters. A multi-stage explicit Runge-Kutta time marching scheme is implemented for higher-order accuracy in time. The scheme is conservative and exhibits minimal numerical dispersion and diffusion. The sub-grid scale diffusion in the model is parameterized via the Smagorinsky-Lilly turbulence closure. Different benchmark and idealized test cases are simulated for the validation of the numerical scheme.

Optimization of Airship Routes for Weather

Airships have in the past proven to be reliable airborne platforms for a variety of activities ranging from passenger transport to wartime surveillance and reconnaissance. However, they fell out of favor due to two reasons – 1) hydrogen was predominantly used to provide buoyancy and this proved to be disastrous as evidenced by the Hindenburg disaster; and 2) weather provided serious challenges to airship operations and was the cause of the majority of airship related accidents. In the face of these challenges the aircraft technology was able to dominate the aviation field. However, airships still can provide useful service in cargo and passenger transport as they can operate from and to remote regions with very little infrastructure requirements. In fact, several groups have begun the task of designing and building the next-generation airships. The first danger cited above is avoided, as helium is the gas of choice in modern airships. Still weather provides the most serious challenge to an airship pilot or operator. Airships in general fly at altitudes of a few thousands of feet. At these altitudes, they encounter significant wind variations due to large-scale systems as well as smaller local scale storms. Automatically locating regions of favorable weather conditions from forecasted weather can lead to significant savings in resources as well as reduction in risk to the airship and crew. With this in mind, a route planning algorithm has been designed by SAIC, which takes into account the four-dimensional weather and the performance parameters of the airship to come up with an optimal route between two given points. The paper will discuss the design and testing of this algorithm, as well as its application in a climatological sense to derive the projected fuel savings over a year of operations. A trans-Pacific route was chosen for testing of the algorithm. The algorithm was tested incrementally with increasingly complex scenarios. The algorithm used typical fuel burn rate formulae in determining total fuel usage. The results indicate that an average of 24% savings in fuel can be achieved over the route tested. 1 Senior Research Scientist 2 LTA Engineer 3 Meteorologist Introduction Airships have in the past proven to be reliable airborne platforms for a variety of activities ranging from passenger transport to wartime surveillance and reconnaissance. However, they fell out of favor due to two reasons – 1) hydrogen was predominantly used to provide buoyancy and this proved to be disastrous as evidenced by the Hindenburg disaster; and 2) weather provided serious challenges to airship operations and was the cause of the majority of airship related accidents. In the face of these challenges the aircraft technology was able to dominate the aviation field. However, airships still can provide useful service in cargo and passenger transport as they can operate from and to remote regions with very little infrastructure requirements. In fact, several groups have begun the task of designing and building the next-generation airships. The first danger cited above is avoided, as helium is the gas of choice in modern airships. Still weather provides the most serious challenge to an airship pilot or operator. Weather poses the following significant challenges to an airship. 1. High wind speeds can seriously impede the progress of an airship. The modern airships are expected to operate at air speeds ranging from 40 to 80 knots and at altitudes up to 10000 feet. But, winds in this atmospheric layer can be of comparable magnitude. Encountering head winds of speed equal to or higher than the airship results in wastage of fuel. 2. High winds are also detrimental to launch and landing operations. The airship is especially vulnerable during these times as it is close to the ground. 3. Severe weather, such as heavy precipitation also affects the performance of the airship. Heavy 7th AIAA Aviation Technology, Integration and Operations Conference (ATIO) 2nd Centre of E 18 20 September 2007, Belfast, Northern Ireland AIAA 2007-7880 Copyright

Simulation of Flows with Large Gradients using Adaptive Mesh Refinement

The Euler equations are solved for non-hydrostatic atmospheric flow problems in two dimensions using the Conservation Laws Package (CLAWPACK) with adaptive mesh refinement (AMR). The CLAWPACK software uses high-resolution wave propagation methods (LeVeque 2002) for solving hyperbolic conservation laws. In the current study, the Riemann problem is solved using flux-based wave decomposition (Bale et al. 2002; LeVeque 2002; Ahmad and Lindeman 2007). The computational efficiency achieved by using adaptive mesh refinement is demonstrated. The methodology shows promise for simulating multi-scale, time-critical and computationally intensive flow problems and flows which are dominated by large gradients of velocities and other thermodynamic quantities. A decrease in computational resources while maintaining the accuracy of the solution has obvious benefits in responding to emergency-response scenarios, such as dispersion of hazardous materials in the atmosphere.

Simulation of the Santa Ana Winds (Vientos de Satán)

*† ‡ § The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is used to simulate an episode of the Santa Ana winds over Southern California. The OMEGA model is based on an unstructured adaptive grid. The use of an unstructured gird allows the model to resolve complex terrain features with a good degree of accuracy and is ideally suited to simulate atmospheric flows which develop due to topographic forcing. This paper describes in detail simulations using the OMEGA model for an episode of the Santa Ana winds during October 2007. The wind and turbulence fields obtained from OMEGA were used to drive the Atmospheric Dispersion Model (ADM). The results of the ADM simulation of the Santa Ana fires are also reported.

Airship Transport Operational Management in Northern Latitudes

Many recent calls for operation of transport airships are predicated on the initial missions being conducted in regions far north of the contiguous US states. The northern latitudes offer a unique set of operational challenges that transport airship operators must be able to quickly master if they hope to establish safe and profitable transport services. This paper identifies the issues and factors that will collectively govern these far northern airship operations. A computer based methodology will also be offered for managing the diverse components that make up and influence airship transport operations.

Acoustic Ray-Tracing on Unstructured Adaptive Grids

*† ‡ § ** †† A computationally efficient acoustic ray-tracing code based on unstructured adaptive grids is described in detail. The use of unstructured grids allows wave propagation simulations on complex computational domains. Detailed surface layer physics is included to take into account the atmospheric variability under different stability conditions and landuse inhomogeneities. The ray-tracing model has been coupled with meso- and microscale atmospheric flow models. The method shows promise in simulating long-range acoustic wave propagation in the atmosphere over complex terrain.