Validation of a thirty year wave hindcast using the Climate Forecast System Reanalysis winds

2013 ◽  
Vol 70 ◽  
pp. 189-206 ◽  
Author(s):  
Arun Chawla ◽  
Deanna M. Spindler ◽  
Hendrik L. Tolman
Keyword(s):  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Wave Hindcast

scholarly journals Thirty-four years of Hawaii wave hindcast from downscaling of climate forecast system reanalysis

2016 ◽  
Vol 100 ◽  
pp. 78-95 ◽  
Author(s):  
Ning Li ◽  
Kwok Fai Cheung ◽  
Justin E. Stopa ◽  
Feng Hsiao ◽  
Yi-Leng Chen ◽  
...  
Keyword(s):  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Wave Hindcast

Climatic characteristics of drift ice in the northern Barents Sea

2019 ◽  
Vol 11 (3) ◽  
pp. 800-811
Author(s):  
Chenglin Duan ◽  
Sheng Dong ◽  
Zhifeng Wang ◽  
Zhenkun Liao
Keyword(s):  
Barents Sea ◽  
Ice Thickness ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Ice Velocity ◽  
Environmental Prediction ◽  
Climatic Characteristics

Abstract In this paper, a preliminary climatic description of the long-term offshore drift ice characteristics in the northern Barents Sea has been investigated from 1987 to 2016 based on the satellite ice motion datasets from National Snow and Ice Data Center (NSIDC) and reanalysis ice thickness datasets from National Centers for Environmental Prediction (NCEP)-Climate Forecast System Reanalysis (CFSR) and Climate Forecast System Version 2 (CFSv2). Both the ice velocity and thickness conditions have been studied at the three fixed locations from west to east. Annual and monthly drift ice roses indicate that the directions from WSW to SE are primarily prevailing, particularly in winter months. Besides, the annual ice speed extremums exceeding 40 cm s–1 mostly occur in the southerly directions from November to April. For the ice thickness, results reveal that it is prominently distributed in a thicker interval between 70 and 120 cm, and a thinner interval between 20 and 70 cm. The annual thickness maxima approximately range from 90 to 170 cm, primarily occurring from May to June, and demonstrate a light decreasing trend.

scholarly journals Evaluation of the Climate Forecast System Reanalysis weather data for the hydrological model in the Arctic watershed Målselv

2021 ◽  
Author(s):  
Minh Tuan Bui ◽  
Jinmei Lu ◽  
Linmei Nie
Keyword(s):  
High Resolution ◽  
Hydrological Model ◽  
The Arctic ◽  
Annual Rainfall ◽  
Climate Forecast ◽  
Hydrological Models ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis

Abstract The high-resolution Climate Forecast System Reanalysis (CFSR) data have recently become an alternative input for hydrological models in data-sparse regions. However, the quality of CFSR data for running hydrological models in the Arctic is not well studied yet. This paper aims to compare the quality of CFSR data with ground-based data for hydrological modeling in an Arctic watershed, Målselv. The QSWAT model, a coupling of the hydrological model SWAT (soil and water assessment tool) and the QGIS, was applied in this study. The model ran from 1995 to 2012 with a 3-year warm-up period (1995–1997). Calibration (1998–2007), validation (2008–2012), and uncertainty analyses were conducted by the model for each dataset at five hydro-gauging stations within the watershed. The objective function Nash–Sutcliffe coefficient of efficiency for calibration is 0.65–0.82 with CFSR data and 0.55–0.74 with ground-based data, which indicate higher performance of the high-resolution CFSR data than the existing scattered ground-based data. The CFSR weather grid points showed higher variation in precipitation than the ground-based weather stations across the whole watershed. The calculated average annual rainfall by CFSR data for the whole watershed is approximately 24% higher than that by ground-based data, which results in some higher water balance components. The CFSR data also demonstrate its high capacities to replicate the streamflow hydrograph, in terms of timing and magnitude of peak and low flow. Through examination of the uncertainty coefficients P-factors (≥0.7) and R-factors (≤1.5), this study concludes that CFSR data are a reliable source for running hydrological models in the Arctic watershed Målselv.

scholarly journals The Land Surface Analysis in the NCEP Climate Forecast System Reanalysis

2012 ◽  
Vol 13 (5) ◽  
pp. 1621-1630 ◽  
Author(s):  
Jesse Meng ◽  
Rongqian Yang ◽  
Helin Wei ◽  
Michael Ek ◽  
George Gayno ◽  
...  
Keyword(s):  
Surface Energy ◽  
Surface Analysis ◽  
Land Surface ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Data Assimilation System ◽  
Ncep Climate Forecast System ◽  
Assimilation System

Abstract The NCEP Climate Forecast System Reanalysis (CFSR) uses the NASA Land Information System (LIS) to create its land surface analysis: the NCEP Global Land Data Assimilation System (GLDAS). Comparing to the previous two generations of NCEP global reanalyses, this is the first time a coupled land–atmosphere data assimilation system is included in a global reanalysis. Global observed precipitation is used as direct forcing to drive the land surface analysis, rather than the typical reanalysis approach of using precipitation assimilating from a background atmospheric model simulation. Global observed snow cover and snow depth fields are used to constrain the simulated snow variables. This paper describes 1) the design and implementation of GLDAS/LIS in CFSR, 2) the forcing of the observed global precipitation and snow fields, and 3) preliminary results of global and regional soil moisture content and land surface energy and water budgets closure. With special attention made during the design of CFSR GLDAS/LIS, all the source and sink terms in the CFSR land surface energy and water budgets can be assessed and the total budgets are balanced. This is one of many aspects indicating improvements in CFSR from the previous NCEP reanalyses.

Patterns and cycles in the Climate Forecast System Reanalysis wind and wave data

2013 ◽  
Vol 70 ◽  
pp. 207-220 ◽  
Author(s):  
Justin E. Stopa ◽  
Kwok Fai Cheung ◽  
Hendrik L. Tolman ◽  
Arun Chawla
Keyword(s):  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Wave Data

scholarly journals Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis

2015 ◽  
Vol 28 (3) ◽  
pp. 1166-1183 ◽  
Author(s):  
Lejiang Yu ◽  
Shiyuan Zhong ◽  
Xindi Bian ◽  
Warren E. Heilman
Keyword(s):  
United States ◽  
Spatial Variability ◽  
El Niño ◽  
El Nino ◽  
The United States ◽  
Total Variance ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis

Abstract This study examines the spatial and temporal variability of wind speed at 80 m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the winter (summer), and higher (lower) speeds over much of the Midwest and U.S. Northeast (U.S. West and Southeast). Trends are also variable spatially, with more upward trends in areas of the Great Plains and Intermountain West of the United States and more downward trends elsewhere. The leading EOF mode, which accounts for 20% (summer) to 33% (winter) of the total variance and represents in-phase variations across the United States, responds mainly to the North Atlantic Oscillation (NAO) in summer and El Niño–Southern Oscillation (ENSO) in the other seasons. The dominant variation pattern can be explained by a southerly/southwesterly (westerly) anomaly over the U.S. East (U.S. West) as a result of the anomalous mean sea level pressure (MSLP) pattern. The second EOF mode, which explains about 15% of the total variance and shows a seesaw pattern, is mainly related to the springtime Arctic Oscillation (AO), the summertime recurrent circumglobal teleconnection (CGT), the autumn Pacific decadal oscillation (PDO), and the winter El Niño Modoki. The anomalous jet stream and MSLP patterns associated with these indices are responsible for the wind variation.

scholarly journals A 10-yr Climatology of Tibetan Plateau Vortices with NCEP Climate Forecast System Reanalysis

2014 ◽  
Vol 53 (1) ◽  
pp. 34-46 ◽  
Author(s):  
Xinyuan Feng ◽  
Changhai Liu ◽  
Roy Rasmussen ◽  
Guangzhou Fan
Keyword(s):  
Tibetan Plateau ◽  
Effective Diameter ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Average Life Span ◽  
Near Surface ◽  
Late Night ◽  
Ncep Climate Forecast System

AbstractA plateau vortex refers to a shallow meso-α-scale cyclonic vortex that is usually confined to near-surface levels (500 hPa) over the Tibetan Plateau during warm seasons. It is the major precipitation-producing weather system over the plateau, but the knowledge of its climatology and understanding of generation mechanisms are limited because of the lack of adequate observations in this harsh mountainous region. In this study, the high-resolution NCEP Climate Forecast System Reanalysis data have been used to perform a statistical survey of these vortices over 10 warm seasons (April–October of 2000–09). The purpose is to document their climatological features, including genesis, size, life cycle, propagation, and diurnal variation.Results show that ~103 plateau vortices occur on average every year. Most are detected from May through August, with the maximum monthly count in July. The primary area of origin exhibits a west–east orientation in correspondence with a large-scale confluence zone, and the most concentrated source lies in the area of 33°–36°N, 84°–90°E in the high elevated central and western plateau. Significant diurnal variations are observed, characteristic of a preferential genesis during late afternoon to evening hours and a late night dissipation peak. The vortex events have an average life span of ~15 h and an average horizontal dimension (effective diameter) of ~280 km. In accordance with the steering environmental flow, an overwhelming majority travel eastward with a mean translation speed of ~10 m s−1. A small fraction of systems (approximately nine cases annually) move off the plateau, predominantly from the eastern edge.

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