Modeling and Analyzing Multiscale Phenomena in Earth and Geospace Systems
Presiding: A S Sharma, University of Maryland at College Park; J B Rundle, University of California, Davis
NG44A-01 INVITED 15:30h
Time Domain Identification of Nonlinear Systems: From the Measurements to Continuous Differential Equations
In nearly all of the geophysical studies, nonlinearities are unavoidable. and in many cases it is very difficult to derive a mathematical model of a nonlinear geophysical system or process from the first principles. Here we show how NARMAX based approach can be used to derive directly from data continuous equations that govern the evolution of nonlinear dynamical system. This approach is applicable to many various geophysical systems. We are presenting results of its application to space plasma turbulence and to the global dynamics of magnetosphere.
NG44A-02 15:45h
Intermittent Turbulence and SOC Dynamics in a 2-D Driven Current-Sheet Model
Borovsky et al. [Phys Plasma, 1997] have shown that Earth's magnetotail plasma sheet is strongly turbulent. More recently, Borovsky and Funsten [JGR, 2003] have shown that eddy turbulence dominates and have suggested that the eddy turbulence is driven by fast flows that act as jets in the plasma. Through basic considerations of energy and magnetic flux conservation, these fast flows are thought to be localized to small portions of the total plasma sheet and to be generated by magnetic flux reconnection that is similarly localized. Angelopoulos et al. [Phys Plasma, 1999], using single spacecraft Geotail data, have shown that the plasma sheet turbulence exhibits signs of intermittence and Weygand et al. [JGR, 2005], using four spacecraft Cluster data, have confirmed and expanded on this conclusion. Uritsky et al. [JGR, 2002; GRL, 2003], using Polar UVI image data, have shown that the evolution of bright, night-side, UV auroral emission regions is consistent with many of the properties of systems in self-organized criticality (SOC). Klimas et al. [JGR, 2000; 2004] have suggested that the auroral dynamics is a reflection of the dynamics of the fast flows in the plasma sheet. Their hypothesis is that the transport of magnetic flux/energy through the magnetotail is enabled by scale-free avalanches of localized reconnection whose SOC dynamics are reflected in the auroral UV emission dynamics. A corollary of this hypothesis is that the strong, intermittent, eddy turbulence of the plasma sheet is closely related to its critical dynamics. The question then arises: Can in situ evidence for the SOC dynamics be found in the properties of the plasma sheet turbulence? A 2-dimensional numerical driven current-sheet model of the central plasma sheet has been developed that incorporates an idealized current-driven instability with a resistive MHD system. It has been shown that the model can evolve into SOC in a physically relevant parameter regime. Initial results from a study of intermittent turbulence in this model and the relationship of this turbulence to the model's known SOC dynamics will be discussed.
NG44A-03 INVITED 16:00h
Modeling Systems Involving Interactions Between Scales
When we think of numerical models, `simulation modeling' often comes to mind: The modeler strives to include as many of the processes operating in the system of interest, and in as much detail, as is practical. The goal is typically to make accurate quantitative predictions. However, numerical models can also play an explanatory role. The goal of explaining a poorly understood phenomenon is often best pursued with an `exploratory' model (Murray 2002, 2003), in which a modeler minimizes the processes included and the level of detail, to try to determine what mechanisms-and what aspects of those mechanisms-are essential. These strategies are closely associated with different approaches to modeling processes across temporal and spatial scales. Simulation models often involve `explicit numerical reductionism'-the direct representation of interactions at scales as small as possible. Parameterizing sub-grid-scale processes is often seen as an unfortunate necessity, to be avoided if possible. On the other hand, when devising an exploratory model, a top-down strategy is often employed; an effort is made to represent only the effects that much smaller-scale processes have on the scale of interest. This approach allows investigation of the interactions between the emergent variables and structures that most directly explain many complex behaviors. As a caricature, we don't investigate water-wave phenomena by simulating molecular collisions. In addition, basing a model on processes at much smaller scales than those of the phenomena of interest leads to the concern that model imperfections may propagate up through the scales; that if the small-scale processes are not treated very accurately, the key interactions that emerge at larger scales may not occur as they do in the natural system. However, this risk can be bypassed by basing a model directly on larger-scale interactions, and examining which of these interactions might cause a phenomenon. For this reason, it has been suggested recently that a top-down approach leads to models that are better able to make practically useful predictions. The strategies described here represent end members of modeling continua, and what blend of approaches leads to predictions most useful to science or society likely varies from case to case.
NG44A-04 16:15h
Multiscale Variability of the Monsoon Climate
The reliability of weather forecasts is limited to a few days and is mainly determined by the synoptic scale features of the atmosphere. The predictability of weather models depends on the error growth determined by nonlinear terms representing advection. Smaller scale features, such as convection, may also influence the predictability of the synoptic scale forecasts. While the prediction of instantaneous states of the system may be impossible on longer time scale, there is optimism for medium-range and long-range forecasts of time-averaged features of the climate system. Such optimism is based on the observation that slowly-varying boundary forces such as sea surface temperature, soil moisture and snow influence the variability of the atmosphere on a longer time scale, especially in the tropical region. This study discusses the variability of such a tropical climate system, the monsoon, and shows that its variability consists of a combination of large-scale persistent seasonal mean component and intraseasonal variability of different time scales. The spatial variability of these components is also found to consist of different scales. By performing multi-channel singular spectrum analysis of daily rainfall, low-pressure systems, outgoing long-wave radiation and winds, two oscillatory modes with periods of about 45 and 20 days have been identified and shown to correspond to the active and break phases of the monsoon. These two intraseasonal modes, however, do not contribute much to the seasonal mean rainfall. Three other components of the MSSA are identified as the contributors to the seasonal mean rainfall, possibly arising from the influence of slowly-varying boundary forces. The prospect for making accurate long-range forecasts of the monsoon depends on the relative magnitudes of the large-scale seasonally persistent component and the intraseasonal component and on climate model experiments to establish a relation between the two components.