STORM FAQ AND TROUBLESHOOTING

The StoRM service is a storage resource manager for generic disk based storage systems separating the data management layer from the underlying storage system

STORM: FUNCTIONAL DESCRIPTION

The StoRM service is a storage resource manager for generic disk based storage systems separating the data management layer from the underlying storage system

Downstream Self-Destruction of Storm Tracks

The Northern Hemisphere storm tracks have maximum intensity over the Pacific and Atlantic basins; their intensity is reduced over the continents downstream. Here, simulations with an idealized aquaplanet general circulation model are used to demonstrate that even without continents, storm tracks have a self-determined longitudinal length scale. Their length is controlled primarily by the planetary rotation rate and is similar to that of Earth’s storm tracks for Earth’s rotation rate. Downstream, storm tracks self-destruct: the downstream eddy kinetic energy is lower than it would be without the zonal asymmetries that cause localized storm tracks. Likely involved in the downstream self-destruction of storm tracks are the energy fluxes associated with them. The zonal asymmetries that cause localized storm tracks enhance the energy transport through the generation of stationary eddies, and this leads to a reduced baroclinicity that persists far downstream of the eddy kinetic energy maxima

A quantitative assessment of empirical magnetic field models at geosynchronous orbit during magnetic storms

[1] We evaluate the performance of recent empirical magnetic field models (Tsyganenko, 1996, 2002a, 2002b; Tsyganenko and Sitnov, 2005, hereafter referred to as T96, T02 and TS05, respectively) during magnetic storm times including both pre- and post-storm intervals. The model outputs are compared with GOES observations of the magnetic field at geosynchronous orbit. In the case of a major magnetic storm, the T96 and T02 models predict anomalously strong negative Bz at geostationary orbit on the nightside due to input values exceeding the model limits, whereas a comprehensive magnetic field data survey using GOES does not support that prediction. On the basis of additional comparisons using 52 storm events, we discuss the strengths and limitations of each model. Furthermore, we quantify the performance of individual models at predicting geostationary magnetic fields as a function of local time, Dst, and storm phase. Compared to the earlier models (T96 and T02), the most recent storm-time model (TS05) has the best overall performance across the entire range of local times, storm levels, and storm phases at geostationary orbit. The field residuals between TS05 and GOES are small (≤3 nT) compared to the intrinsic short time-scale magnetic variability of the geostationary environment even during non-storm conditions (∼24 nT). Finally, we demonstrate how field model errors may affect radiation belt studies when estimating electron phase space density

Rain storm models and the relationship between their parameters

Rainfall interstation correlation functions can be obtained with the aid of analytic rainfall or storm models. Since alternative storm models have different mathematical formulas, comparison should be based on equallity of parameters like storm diameter, mean rainfall amount, storm maximum or total storm volume