A11G-01 INVITED
The promise and the challenges of the coming age of cloud resolving tropical cyclone prediction
Over the last two decades cloud resolving tropical cyclone models have evolved from an ambitious research project to the realm of real time numerical TC prediction systems. The increase in resolution has resulted in the ability to simulate internal storm features such as multiple and asymmetric eye wall systems, rain bands, outflow structures, variable sea states and so on. However, although model resolution has dramatically increased, model physics and initialization techniques have evolved much less. In early generations TC prediction models, numerous aspects of model physics such as the evolving sea state, microphysics processes and radiative processes could be treated less precisely because they coupled only weakly with imprecise model dynamics. These couplings become more significant in cloud resolving applications and result in the need for improvements both in the physics representations and the ability to provide observations of new key variables such as liquid, ice and aerosol structures and concentrations, initial sea state and so on. Perhaps most critical, is the serious and unprecedented (in numerical weather prediction) data gap between the space-time scales of the controlling internal features represented numerically and the capability of all current and perhaps all projected observation systems to provide information to initialize and correct through assimilation a deterministic prediction of these features. The data gap also reduces the ability to verify the structures simulated. The limits of deterministic predictability depend directly on the space-time scales of the features in question while the potential for deterministic analysis depends on the space-time fidelity of the data collection system. As deterministic predictability vanishes at small space-time thresholds, the cloud resolving prediction becomes probabilistic. Just as climate models place no significance in the space time location of a single transient cold front in a 500 year prediction, the new high resolution TC models may have limited or no skill predicting the timing and location of certain small scale features such as a convective plume. Predictability will depend on the time since critical data input was available to define these features independently from the model prediction as well as their dependence on more predictable features of the simulation, such as topographical interactions. The application of high resolution cloud resolving TC models to the intensity prediction problem has the potential to result in a significant period of deterministic prediction capability at meso-beta and meso-gamma scales, which can be quite useful, particularly as the TC makes landfall. These issues of probabilistic analysis and prediction and the data and physics required to maximize deterministic outcomes in the new age of cloud resolving TC prediction will be discussed.
A11G-02 INVITED
Real-time and Retrospective Hurricane Simulations using the Advanced Hurricane WRF Model
Beginning in 2003, real-time and retrospective simulations of Atlantic hurricanes have been conducted using the Advanced Hurricane WRF model (AHW), a version of the Advanced Research WRF model (ARW). The emphasis has been on storm-following nests to reach a grid spacing as fine as 1.33 km covering the inner core, thereby resolving the eye wall. In this talk, the performance of the model will be evaluated collectively over many cases. In addition the structural aspects of individual cases such as Katrina (2005), Wilma (2005), Ophelia (2005), Helene (2006) and Dean (2007) will be examined to show how the model realistically produces asymmetries in wind and rainfall in mature hurricanes and instances of extratropical transition. Sensitivities to variations in model physical processes and initialization methods will also be examined. In particular, the effect of differing treatments of the air-sea interface, including the upper-ocean feedback, and changes in cloud microphysics on storm intensity will be shown. Initialization with a three-dimensional variational assimilation (3D-Var) and an ensemble Kalman filter (EnKF) technique will be compared to the default initialization from the GFDL model for storms occurring during the 2007 season. Shortcomings of current forecasts and related plans for further model improvements will also be discussed. http://www.wrf- model.org/plots/realtime_main.php
A11G-03
Advanced Numerical Prediction and Modeling of Tropical Cyclones Using WRF-NMM modeling system
Dramatic improvement in tropical cyclone track forecasts have occurred through advancements in high quality observations, high speed computers and improvements in dynamical models. Similar advancements now need to be made for tropical cyclone intensity, structure and rainfall prediction. The Weather Research Forecasting Model (WRF) is a general purpose, multi-institutional mesoscale modeling system. A version of the WRF model called the HWRF/WRF-NMM modeling system, developed at the National Center for Environmental Protection (NCEP) was recently adopted for hurricane forecasting (Gopalakrishnan et al, 2006) by the National Hurricane Center (NHC). At the Hurricane Research Division (HRD/AOML/OAR) we are developing and further advancing a research version of this modeling system. This work is done in collaboration with the Developmental Test bed Center (DTC), Boulder, CO, Global Systems division (GSD/ESRL/OAR), Boulder, CO, The Air Resources Laboratory (ARL/OAR), Washington, D.C., the U.S. university community, the Indian Institute of Technology, IIT.Delhi, India, and the India Meteorological Department, New Delhi, India Our modeling effort includes advancing the WRF system for Ensemble Hurricane Forecasting, advancing our understanding of Ensemble-vs- High Resolution Forecasting of Hurricanes, advancing WRF/WRF-NMM with better analysis techniques (e.g. Four Dimensional Data Assimilation) for improving forecasts and above all, advancing our understanding of hurricane processes using a high resolution numerical modeling approach. Examples of some of these applications will be shown here. Reference: NCEP's Two-way-Interactive-Moving-Nest NMM-WRF modeling system for Hurricane Forecasting, S.G. Gopalakrishnan, N. Surgi, R. Tuleya, and Z. Janjic 27th Conference on Hurricanes and Tropical Meteorology, 24- 28 April 2006, Monterey, California.
A11G-04
Inner Core Structures and Intensity Change Simulated With the Advanced Hurricane WRF Model
The Advanced Hurricane WRF (AHW) has been used for real-time prediction and retrospective research simulations of Atlantic basin tropical cyclones since 2003. Verification of the intensity and track errors of the AHW forecasts has shown that 12 km and 4 km simulations perform as well as, and occasionally superior to, the National Hurricane Center official forecasts and other operational forecast systems. Verification of the inner core structure of the simulated storms, examined with a finest mesh of 1.33 km, has proven less successful. Realistic eye, eyewall and inner spiral rainband structures are simulated, but the eye is generally too small and the eyewall convection too wide. Outside of the eyewall, the azimuthal location of convective bands and asymmetries in the wind field agree well with reconnaissance observations and concentric eyewall cycles are simulated on realistic time and spatial scales. Closer to the core, the eyewall potential vorticity maximum provided steep gradients on which copious vortex Rossby waves and mesovortices were noted to propagate in accord with theory. The amplitude of these asymmetries and their dominant wavenumbers however, are inconsistent with observations. Possible explanations for the high Rossby wave activity, the effects of these asymmetries on storm intensity and sensitivity experiments undertaken to reduce the spurious wave activity will be the focus of this presentation.
A11G-05
Spatial and Temporal Variability of Precipitation Morphology During the Intensification of Hurricane Dennis (2005)
It is well-known that diabatic heating plays a crucial role in governing tropical cyclone (TC) genesis, intensity change, and structure. The role this heating plays is dependent on several factors, including its magnitude, longevity, horizontal and vertical distribution, and the characteristics of the vortex. The morphology of the precipitation, e.g., magnitude and horizontal and vertical distribution of diabatic heating and vertical motion, mode of organization (i.e., convective vs. stratiform), determines the impact of this precipitation on the intensity, structure, and rainfall of the vortex. Observational, theoretical, and numerical modeling studies have shown the importance of deep convection in tropical cyclone genesis and intensification. Multiple theories have been advanced to explain how these bursts of precipitation, often occurring episodically, facilitate genesis (e.g., vortical hot towers in the convective cores, midlevel mesoscale convective vortices in the stratiform regions), and intensification (primarily through bursts of deep convection and their associated stratiform precipitation). While the importance of these episodic bursts of precipitation has been documented, what has not been thoroughly documented is the morphology of the precipitation associated with these episodes, how this morphology may vary as a function of the lifecycle stage of the TC and location within the developing storm, the importance of any such variations in TC intensity change, and whether numerical models can reproduce these variations if they exist. This research addresses these issues, focusing on the intensification phase by investigating whether precipitation morphology, as measured by the statistical properties of various microphysical fields, varies as a function of TC lifecycle stage and location within the storm. A combination of a high-resolution simulation and airborne observations during the intensifying stage of Hurricane Dennis (2005) are analyzed here. This work may shed some light on the importance of convective and stratiform processes in an intensifying tropical cyclone.
A11G-06
Ensemble-based data assimilation for convective-resolvimg hurricane predictions: Impacts of assimilating ground-based and airborne radar observations during RAINEX
The ensemble-based data assimilation, commonly known as ensemble-Kalman filter or EnKF, has recently been demonstrated to be an effective and maturing assimilation technique with simulated and real observations for NWP across a range of scales. The current study examines the impacts of assimilating both ground-based and airborne Doppler radar observations as well as other convential data in the initiation and prediction of Hurricane Katrina (2005) with an WRF-based EnKF with model grid spacing down to 1.5 km. Despite some sensitivities to the number of observations to be assimilated (after quality control and data thinning) and the radius of influence of a given observation, assimilation of both the ground-based and airborne radar observations from RAINEX is very beneficial for initializing the hurricane near its observed intensity with realistic asymmetry and for subsequent ensemble forecast (or forecast from ensemble mean analysis). For example, forecast from a mean EnKF analysis that assimilates both the KMAX and KBYX Doppler radar observations at 00Z on 26 August 2005 tracks the observed hurricane position very closely and brings the hurricane directly to New Orleans in 96 h. Moreover, assimilation of raw airborne Doppler wind observations from 15 to 18Z 27 August ensure the hot-start of a Category 3 hurricane in near observed intensity without commonly used bogussing or surgical relocation techniques. We are currently exploring the best configurations and formulations with the EnKF framework for cloud-resolving hurricane initiation and prediction thorugh assimilating both synthetic and real observations. Ultimately, we plan to explore the structure, dynamics and predictability of hurricanes through assimilating all available observations during RAINEX and to determine minimum sufficient observations for monitoring and predicting tropical cyclones before diminishing returns.
A11G-07
Analysis of the 7 Easterly Waves Observed During the NAMMA Experiment
The 2006 NAMMA (NASA African Monsoon Multidisciplinary Analyses) Experiment was staged from the Cape Verde Islands during August and September 2006. The primary goals of the experiment were to distinguish the essential differences between developing and non-developing African easterly waves, and the effects of the Saharan Air Layer (SAL) on cloud microphysics and on the waves. The NASA DC-8 aircraft, enhanced soundings from the islands and mainland Africa, and ground-based research radars and mobile research stations produced a uniquely valuable database. During the campaign, 7 easterly waves were observed. 2 waves quickly became tropical cyclones near Africa (Debby, Helene), 2 waves did not develop, while 3 others had some role in the development of Ernesto, Florence, and Gordon that requires additional research to clarify. The focus of this study is to use the data from the NASA DC-8 and its dropsondes, serial soundings from Praia and Dakar, along with the NCEP GDAS (Global Data Assimilation System) analyses, to describe these 7 waves with a detail never before possible in this region. Careful analysis of the dropsonde data from the DC-8 often reveals significant differences from the GDAS analyses at 925 and 700 hPa, as well as humidity differences, which are quantified. LASE (Lidar Atmospheric Sensing Experiment) data on water vapor and aerosol structure is used to map the SAL from the DC-8, supplementing satellite data on clouds and aerosols. There is an important distinction between tracking the (large-scale) wave and tracking the vorticity centers within the waves. A principal finding is that there are often multiple vorticity centers within the wave, sometimes with short lifetimes, and that tropical cyclone development may depend upon their collocation with convective systems, a transient event more difficult to sample than the large-scale wave itself.
A11G-08
Tropical-Cyclone Intensification and Predictability in Three Dimensions
We present numerical model experiments to investigate the dynamics of tropical-cyclone amplification and its predictability in three dimensions. For the prototype amplification problem beginning with a weak tropical storm strength vortex, the emergent flow becomes highly asymmetric and dominated by deep convective vortex structures, even though the problem as posed is essentially axisymmetric. The asymmetries that develop are highly sensitive to the surface moisture distribution. When a small random moisture perturbation is added in the boundary layer at the initial time, the pattern of evolution of the flow asymmetries is dramatically changed and a non-negligible spread in the local and azimuthally-averaged intensity results. We conclude that: 1) the flow on the convective scales is not deterministic and only those asymmetric features that survive in an ensemble average of many realizations can be regarded as robust; 2) there is an intrinsic uncertainty in the prediction of maximum intensity using either maximum wind or minimum surface pressure metrics. There are clear implications for the possibility of deterministic forecasts of the mesoscale structure of tropical cyclones, which may have a large impact on the intensity and on rapid intensity changes. Other aspects of vortex structure are addressed also including the analogous problem on a beta-plane, a prototype problem for tropical-cyclone motion. The results provide deeper insight into the dynamics of the intensification process and suggest limitations of deterministic prediction for the mesoscale structure. Larger-scale characteristics are found to be less variable than their mesoscale counterparts.