Search Results

You are looking at 1 - 10 of 45,827 items for :

  • Precipitation x
  • Refine by Access: All Content x
Clear All
Roy M. Rasmussen, John Hallett, Rick Purcell, Scott D. Landolt, and Jeff Cole

precipitation resulting from the small cross-sectional area represented by such crystals. Such a misleading condition was found to occur during five of the major deicing accidents ( Rasmussen et al. 2000 ). To overcome this problem, real-time estimates of the liquid-equivalent snowfall rate updated once every minute are needed. For this reason, aviation real-time nowcasting systems, such as the Weather Support to Deicing Decision Making (WSDDM) system ( Rasmussen et al. 2001 ), include real-time snowfall

Full access
Amir AghaKouchak, Nasrin Nasrollahi, Jingjing Li, Bisher Imam, and Soroosh Sorooshian

1. Introduction Spatial patterns in precipitation fields are fundamental to hydrologic modeling and streamflow analysis. Many studies highlight the importance of precipitation space–time variability ( Fiener and Auerswald 2009 ; Haile et al. 2009 ; Corradini and Singh 1985 ), which has been proven to affect the quality of runoff predictions ( Goodrich et al. 1995 ; Schuurmans and Bierkens 2007 ). Historically, most studies focus on temporal patterns in precipitation data (see Grayson and

Full access
Michael G. Bosilovich, Junye Chen, Franklin R. Robertson, and Robert F. Adler

physics provides data not easily observed, but is consistent with the analyzed observed data. So, while the data are guided by the observations, model physics and uncertainties still lead to uncertainty in the resultant data products. Betts et al. (2006) summarize strengths, weaknesses, and the utility of reanalyses, especially regarding hydroclimate studies. Precipitation is one of the critical components of the water and energy cycles, but is also largely related to modeled physical

Full access
Jianzhi Dong, Wade T. Crow, and Rolf Reichle

1. Introduction Precipitation detection skill (i.e., the ability to accurately detect precipitation occurrence) is a key metric for quantifying the accuracy of precipitation products ( Dinku et al. 2010 ; Hamada and Takayabu 2016 ). As demonstrated in gauge-based analyses ( Tong et al. 2014 ; Yang and Luo 2014 ), biases in remote sensing precipitation are often attributable to their tendency to falsely detect and/or miss precipitation events. Such detection errors are unavoidably propagated

Free access
Qiang Zhang, Xihui Gu, Jianfeng Li, Peijun Shi, and Vijay P. Singh

1. Introduction Tropical cyclones (TCs) and TC-induced storm surge, heavy precipitation, and flooding caused enormous losses of life and economic damage worldwide ( Lin et al. 2015 ; Yan et al. 2016 ). In the backdrop of warming climate, the intensity of nonextreme TCs and the frequency of the most intense TCs are expected to increase, based on the results of theoretical analyses and mathematical models (e.g., Knutson et al. 2010 ; Bindoff et al. 2013 ; Christensen et al. 2013

Full access
Nathalie Voisin, Andrew W. Wood, and Dennis P. Lettenmaier

. Among these are the Variable Infiltration Capacity (VIC) model of Liang et al. (1994) , and the University of Waterloo hydrologic model (WATflood; Snelgrove et al. 2005) . As the spatial scales of interest for the application of hydrologic models have increased, so has the need to explore alternative sources for the primary hydrologic forcing variable (i.e., precipitation). Although gridded station data [e.g., the continental U.S. dataset of Maurer et al. (2002) and the global dataset of Adam

Full access
Steven M. Martinaitis, Andrew P. Osborne, Micheal J. Simpson, Jian Zhang, Kenneth W. Howard, Stephen B. Cocks, Ami Arthur, Carrie Langston, and Brian T. Kaney

1. Introduction Accurate, high spatiotemporal resolution quantitative precipitation estimates (QPEs) are crucial for flood and flash flood operations, hydrologic forecasting, long-term climatological evaluations, and water resource management. One common source of measuring precipitation are rain gauges, which provide direct surface measurements; however, a single gauge observation based on an orifice of 80–325 cm 2 typically covers a region spanning many square kilometers. Large distances

Free access
Nathan M. Hitchens, Michael E. Baldwin, and Robert J. Trapp

1. Introduction Each year inland flash flooding in the United States poses a significant threat to life, property, and agriculture. Such flooding is often attributed to “extreme precipitation,” which herein will refer to rainfall occurring in 1 h, in amounts exceeding a statistically based threshold. For example, Hitchens et al. (2010) examined rain gauge data in the midwestern United States, and defined extreme precipitation events as uninterrupted 6-h periods that surpass the 10-yr return

Full access
Thomas M. Hamill and Jeffrey S. Whitaker

1. Introduction Despite much recent progress in numerical weather prediction, weather forecasts are still subject to error, both as a result of the growth of initial-condition errors and model errors. Near-surface forecasts and forecasts of hydrologic variables such as precipitation or cloud properties are particularly error prone, in part because these physical processes often occur at scales below those resolved by the model. These effects must be parameterized, and developing accurate

Full access
Eirik J. Førland, Ketil Isaksen, Julia Lutz, Inger Hanssen-Bauer, Thomas Vikhamar Schuler, Andreas Dobler, Herdis M. Gjelten, and Dagrun Vikhamar-Schuler

1. Introduction Precipitation in the Arctic affects the ocean and terrestrial freshwater budgets, the surface albedo and energy budget, as well as the mass balance of ice sheets, glaciers, and sea ice ( AMAP 2017 ). During recent decades, tropospheric water vapor ( Serreze et al. 2012 ) and precipitation ( Hartmann et al. 2013 ; Willett et al. 2013 ; Hanssen-Bauer et al. 2019 ) have generally increased in the Arctic. The increased precipitation is linked to the general warming, partly driven

Open access