Pressure Dependence of Wall Relaxation in Polarized 3^3He Gaseous Cells

We have observed a linear pressure dependence of longitudinal relaxation time ($T_1$) at 4.2 K and 295 K in gaseous $^3$He cells made of either bare pyrex glass or Cs/Rb-coated pyrex due to paramagnetic sites in the cell wall. The paramagnetic wall relaxation is previously thought to be independent of $^3$He pressure. We develop a model to interpret the observed wall relaxation by taking into account the diffusion process, and our model gives a good description of the data

Pore-scale dynamics and the multiphase Darcy law

Synchrotron x-ray microtomography combined with sensitive pressure differential measurements were used to study flow during steady-state injection of equal volume fractions of two immiscible fluids of similar viscosity through a 57-mm-long porous sandstone sample for a wide range of flow rates. We found three flow regimes. (1) At low capillary numbers, Ca, representing the balance of viscous to capillary forces, the pressure gradient, ∇ P , across the sample was stable and proportional to the flow rate (total Darcy flux) q t (and hence capillary number), confirming the traditional conceptual picture of fixed multiphase flow pathways in porous media. (2) Beyond Ca ∗ ≈ 10 − 6 , pressure fluctuations were observed, while retaining a linear dependence between flow rate and pressure gradient for the same fractional flow. (3) Above a critical value Ca > Ca i ≈ 10 − 5 we observed a power-law dependence with ∇ P ∼ q a t with a ≈ 0.6 associated with rapid fluctuations of the pressure differential of a magnitude equal to the capillary pressure. At the pore scale a transient or intermittent occupancy of portions of the pore space was captured, where locally flow paths were opened to increase the conductivity of the phases. We quantify the amount of this intermittent flow and identify the onset of rapid pore-space rearrangements as the point when the Darcy law becomes nonlinear. We suggest an empirical form of the multiphase Darcy law applicable for all flow rates, consistent with the experimental results

Investigate the impacts of assimilating satellite rainfall estimates on rainstorm forecast over southwest United States

Using the MM5-4DVAR system, a monsoon rainstorm case over southern Arizona (5-6 August 2002) was investigated for the influence of assimilating satellite rainfall estimates on precipitation forecasts. A set of numerical experiments was conducted with multiple configurations including using 20-km or 30-km grid distances and none or 3-h or 6-h assimilation time windows. Results show that satellite rainfall assimilation can improve the rainstorm-forecasting pattern and amount to some extent. The minimization procedure of 4DVAR is sensitive to model spatial resolution and the assimilation time window. The 3-h assimilation window with hourly rainfall data works well for the 6-h forecast, and for 12-h or longer forecasts, a 6-h assimilation window will be requested. Copyright 2004 by the American Geophysical Union

Impact of assimilating rainfall derived from radar and satellites on rainstorm forecasts over the Southwestern United States

The impact of assimilating rainfall derived from radar and satellites on rainstorm forecasts over the Southwestern United States is discussed. The major advantage of 4DVAR is the use of full model dynamics and physics to assimilate multiple-time-level observation data. Rainfall assimilation via 4DVAR is used to improve the moisture distributions in model IC. It is found that by using 4DVAR to generate model IC, the precipitation intensity and patterns can be improved substantially over the mid-latitude plain regions

Multimodel combination techniques for analysis of hydrological simulations: Application to distributed model intercomparison project results

This paper examines several multimodel combination techniques that are used for streamflow forecasting: the simple model average (SMA), the multimodel superensemble (MMSE), modified multimodel superensemble (M3SE), and the weighted average method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multimodel combination results were obtained using uncalibrated DMIP model simulations and were compared against the best-uncalibrated as well as the best-calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the accuracy levels of the multimodel simulations. This study revealed that the multimodel simulations obtained from uncalibrated single-model simulations are generally better than any single-member model simulations, even the best-calibrated single-model simulations. Furthermore, more sophisticated multimodel combination techniques that incorporated bias correction step work better than simple multimodel average simulations or multimodel simulations without bias correction. © 2006 American Meteorological Society