Selecting representative days for more efficient dynamical climate downscaling: Application to wind energy

Journal of Applied Meteorology and Climatology

Volumn 52, Issue 1, 2013, Pages 47-63

  Rife, Daran L ^a   Vanvyve, Emilie ^a   Pinto, James O ^a   Monaghan, Andrew J ^a   Davis, Christopher A ^a   Poulos, Gregory S ^b  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^b V Bar LLC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONALLY EFFICIENT; COMPUTING RESOURCE; LONG TERM RECORDS; METEOROLOGICAL RECORDS; REGIONAL CLIMATE MODELS; REPRESENTATIVE DAYS; SAMPLING METHOD; WIND ENERGY INDUSTRY;

CLIMATOLOGY; MONTE CARLO METHODS; PROBABILITY DENSITY FUNCTION; WIND;

WIND POWER;

ACCURACY ASSESSMENT; BOUNDARY CONDITION; CLIMATE MODELING; COMPUTER SIMULATION; DOWNSCALING; METHODOLOGY; MONTE CARLO ANALYSIS; NUMERICAL MODEL; PROBABILITY; REGIONAL CLIMATE;

UNITED STATES;

EID: 84875036827     PISSN: 15588424     EISSN: 15588432     Source Type: Journal    
DOI: 10.1175/JAMC-D-12-016.1     Document Type: Article

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