With the deployment of the WSR-88D weather radar, the National Weather Service will provide improved estimates of hourly precipitation accumulations for most of the United States on roughly a 4 by 4 km grid. This information will be used as input to operational hydrologic models to improve streamflow prediction for flood forecasting and water resources management. A critical issue that hydrolog...

With the three-dimensional field of velocity predicted by numerical methods it is possible to predict the moisture distribution and hence the occurrence of large-scale saturation. A three-parameter model was used to predict the 12-hour precipitation for the early stages of the storms of November 24, 1950 and November 5, 1953, neglecting cloud storage, supersaturation, a possible lack of condens...

Precipitation is important factor affecting vegetation and controlling key ecological processes. In order to quantify spatial patterns of precipitation in Chongqing tobacco planting region, China, under ArcGIS platform, three multivariate geostatistical methods including cokriging, small grid and regression kriging, coupled with auxiliary topographic factors extracted from a 1:100000 DEM were a...

Precipitation-type forecasting is the determination of when and where particular types of precipitation (e.g., snow, rain, ice pellets, freezing rain) will occur during a forecast period. Although much is already known about the physical processes that determine the type of precipitation that reaches the ground, these forecasts are very challenging for most forecasters because of inadequate atm...

In recent decades artificial neural networks (ANNs) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. This paper presents the application of artificial neural networks to predict drought in Yazd meteorological station. In this research, different archite...

Individually, ground-based, in situ observations, remote sensing, and regional climate modeling cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrains. Data assimilation techniques can be used to bridge the gap between observations and models by assimilating ground observations and remote sensing products into models to improve ...

The accuracy of rainfall predictions in the EPA’s BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The objectives of this study were improvement of using the entropy theory to supplement the precipitation data are significant when the watershed’s meteorological station is either far...

Drought is one of the most serious natural disasters in China. Drought disasters occur frequently and caused huge economic loss in recently. In this paper, a drought prediction model based on weighted Markov Chain is put forward. An application is demonstrated by Anhui province of Huaihe River in China. Based on the precipitation data during 1958-2006 at monthly scale, the different time scales...

We have seen in a recent paper (Surcel et al., 2009) that the diurnal cycle of precipitation over the continental US exhibits some seasonal variability. This is a consequence of the fact that during the summer, precipitation is strongly forced by the diurnal cycle of solar heating and it usually initiates as small scales, while during spring, precipitation occurs at larger scales, being synopti...