Directorate

• Contents
• EXECUTIVE SUMMARY
• 1. SCOPE OF THE PROGRAM
• 2. IMPROVING OUR UNDERSTANDING OF EARTH-SYSTEM PROCESSES
• 2.1 Scale Interactions Associated with Precipitating Convective Systems
• 2.2 Understanding the Dynamics and Predictability of Weather Systems on Time Scales of 0-48 h
• 2.3 Fundamental Research on Precipitation Processes, with an Emphasis on their Improved Representation in Numerical Models
• 2.4 Understanding the Dynamics, Physics and Chemistry of Multi-Scale Atmospheric Chemical Constituent and Particulate Transport, Dispersion and Transformations
• 2.5 Fundamental Research in Boundary Layers and their Interfacial Interactions
• 3. ADVANCING THE SCIENCE OF ATMOSPHERIC PREDICTION
• 3.1 Advancing Short-Range Weather Prediction
• 3.2Advancing Data Assimilation Research
• 3.3 Improving Forecasting of Pollutants and Hazardous Materials
• 4. ADVANCED COMMUNITY RESEARCH TOOLS
• 4.1 WRF Community Model
• 4.2 Community Data Assimilation Techniques
• 4.3 Nested Community Climate Model
• 5. SUMMARY
• Acronym List
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Mesoscale & Microscale Meteorology Division Science Plan:

2.2 Understanding the Dynamics and Predictability of Weather Systems on Time Scales of 0-48 h

Goal: To investigate the dynamics of weather systems with the aim of improving their prediction, estimating their limits of predictability, identifying the key physical processes that limit forecast skill, and developing improved quantitative methods of determining forecast skill at the mesoscale.

Accurate and comprehensive estimates of predictability limits and improvements in prediction are critically dependent on improved understanding of weather system dynamics, together with identification of the important elements that govern these systems. Here we define weather systems as those occurring at, or being directly influenced by mesoscale processes (such as mesoscale convective systems, squalls, tropical cyclones and aspects of the Madden Julian Oscillation). This understanding is being developed from several complementary approaches,

• Testing hypotheses on observations;
• Examining model properties over many events and varied conditions; and,
• Assessing model sensitivity to initial conditions and moist processes.

Analysis of observations will be utilized to test and advance our dynamics hypotheses. A special emphasis is being given to targeted field data augmented by the background remote sensing (satellite and earth based) and in situ observation network. Both traditional and evolving model-based analysis systems will be employed.

A hierarchical modeling approach also is being adopted to elucidate basic physics. These models range from analytic or highly idealized models to full NWP models. Aspects of this research fall within the THORPEX Science Plan and this work will benefit from planned THORPEX field tests of targeted data strategies, such as the proposed THORPEX Pacific Regional Campaign in 2008. In turn, this research will provide a firm theoretical ground, along with ongoing research at other institutions in providing guidance to THORPEX on the design of these field studies.
We shall be using extended integrations of models over a range of weather systems and conditions to examine statistical properties over many events (e.g., convective systems, diurnal cycles, etc.). These simulations will help distinguish among different modeling-system error sources. Crucial to this analysis will be studies of the life cycle of organized convection, covering convective initiation, system maturation, dissipation, and the degree of coherence between discrete systems.

The highly nonlinear nature of moist precipitating systems renders them to be the most difficult challenge to mesoscale prediction. Mesoscale weather systems are typically embedded within synoptic-scale flows but also contain a variety of smaller-scale motions and forcing such as moist convection, interactions with the underlying surface, symmetric instabilities, gravity waves, and frontal and boundary layer circulations. Since many of these motions are unique to the mesoscale, studies of mesoscale predictability with models in which these mesoscale motions are parameterized are of limited utility. Moreover, the fact that these motions are highly intermittent and localized casts doubt on predictability results based on turbulence closures, which assume the turbulence to be homogeneous and isotropic. These facts suggest that further progress in understanding mesoscale predictability hinges on knowing how mesoscale forecasts are influenced by uncertainty in both smaller and larger scales.

These issues are being addressed by examining the growth of small differences (or "errors") in the initial conditions for forecasts of interest. These experiments, which focus on the evolution of the scale and amplitude of the initial error, employ local horizontal resolution of a few kilometers in order to minimize spurious effects of parameterized physics and limited resolution. Our work to date in this area indicates that moist processes exert a controlling influence on the error growth.

To gain further understanding of how mesoscale forecast errors evolve in the presence of moisture, idealized numerical simulations are continuing to examine both the up-scale organization of moist convection in simple environments and the interaction of synoptic-scale flows with embedded precipitation systems. Simulations of convection initiation and organization will assess the sensitivity of initiation, cell evolution and up-scale organization to perturbations of initial conditions. The simulations of synoptic-scale flows will begin with simulations of idealized baroclinic waves and fronts to assess the up- as well as down-scale processes. We shall particularly consider the degree to which uncertainties in the forcing at synoptic scales can alter the predictability of meso- and convective-scale flows. Conversely, we shall also examine the influence of variability at sub-100 km scales on larger scales.

In addition to these general investigations, we will be examining several specific aspects of mesoscale processes that are of particular importance:

• Understanding and quantification of the key physics needed for accurate diurnal cycle representation in weather prediction models, emphasizing rainfall andtopographically induced flows, which complements work under way in TIMES;
• Study of landfalling tropical cyclones, including the dynamics responsible for intensity change, inner core evolution, rainbands and severe weather; and,
• Understanding and quantification of the interaction of gravity waves and balanced flows. This includes the emission of waves from convection and jets and the adjustment of unbalanced moist, turbulent flows.

The use of newly developed approaches for model verification (Sec. 3.1) will quantify the relative increase in prediction skill likely to result from the above research. These will be used in tandem with estimates of predictability limits to prioritize activities to those processes, which, if properly included in models, would result in the largest increase in prediction skill and resulting societal benefits.
Through these and other sensitivity studies, guidance will be provided for the development of the model forecast systems by identifying those physical processes most crucial for mesoscale forecast accuracy.

Next section: Fundamental Research on Precipitation Processes, with an Emphasis on their Improved Representation in Numerical Models

 

 

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