North American Regional Reanalysis

Mesinger, Fedor; DiMego, Geoff; Kalnay, Eugenia; Mitchell, Kenneth E.; Shafran, P.; Ebisuzaki, Wesley; Jović, Danica; Woollen, Jack; Rogers, Eric; Berbery, Ernesto Hugo; Ek, Michael; Fan, Yun; Grumbine, Robert; Higgins, W.; Li, Hong; Ying, Lin; Manikin, Geoffrey S.; Parrish, David; Shi, Wei

doi:10.1175/bams-87-3-343

Cited by 3,058 publications

(2,484 citation statements)

References 22 publications

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“…To assess the impact of winds on the hydrographic and velocity structure in our domain, we used the North American Regional Reanalysis (NARR) 10-m wind field (Mesinger et al, 2006), which has a spatial and temporal resolution of 32 km and 6 hours, respectively.…”

Section: Surface Windsmentioning

confidence: 99%

The Chukchi slope current

Corlett

Pickart

2017

Progress in Oceanography

149

224

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Section: Surface Windsmentioning

confidence: 99%

The Chukchi slope current

Corlett

Pickart

2017

Progress in Oceanography

149

224

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“…Koizumi et al (2005) used the JMA 4D-Var system to assimilate 1-h radar-based precipitation data at a spatial resolution of 20 km and found improved precipitation forecasts up to 18 h ahead. Mesinger et al (2006) assimilated hourly precipitation observations into the North American Regional Reanalysis system, which provides 32-km spatial resolution products every 3 h, and demonstrated improvements in the precipitation analysis compared to the reference monthly observations. Furthermore, Lopez (2011) and Lopez and Bauer (2007) assimilated the National Centers for Environmental Prediction (NCEP) stage IV gauge-corrected radar precipitation into the global Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF) and found substantial improvement in the short-term (i.e., up to 12 h) precipitation forecasts.…”

Section: Introductionmentioning

confidence: 99%

Dynamical Precipitation Downscaling for Hydrologic Applications Using WRF 4D-Var Data Assimilation: Implications for GPM Era

Lin

Ebtehaj

Bras

et al. 2015

Journal of Hydrometeorology

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The objective of this study is to develop a framework for dynamically downscaling spaceborne precipitation products using the Weather Research and Forecasting (WRF) Model with four-dimensional variational data assimilation (4D-Var). Numerical experiments have been conducted to 1) understand the sensitivity of precipitation downscaling through point-scale precipitation data assimilation and 2) investigate the impact of seasonality and associated changes in precipitation-generating mechanisms on the quality of spatiotemporal downscaling of precipitation. The point-scale experiment suggests that assimilating precipitation can significantly affect the precipitation analysis, forecast, and downscaling. Because of occasional overestimation or underestimation of small-scale summertime precipitation extremes, the numerical experiments presented here demonstrate that the wintertime assimilation produces downscaled precipitation estimates that are in closer agreement with the reference National Centers for Environmental Prediction stage IV dataset than similar summertime experiments. This study concludes that the WRF 4D-Var system is able to effectively downscale a 6-h precipitation product with a spatial resolution of 20 km to hourly precipitation with a spatial resolution of less than 10 km in grid spacingrelevant to finescale hydrologic applications for the era of the Global Precipitation Measurement mission.

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“…We used the North American Regional Reanalysis data (NARR, Mesinger et al, 2004), a long-term, gridded (0.33°latitude/longitude) climate dataset to estimate patterns in abiotic drivers of mosquito activity over space and time in northern Alaska. NARR surface air temperature and wind speed data were used to estimate potential mosquito activity within the summer ranges of four caribou herds: Western Arctic herd (WAH), Teshekpuk caribou herd (TCH), Central Arctic herd (CAH), and Porcupine caribou herd (PCH).…”

Section: Methodsmentioning

confidence: 99%