Raghavendra Krishnamurthy

Author

Pacific Northwest National Laboratory ORCID

Also Known As

BNL, Krishnamurthy, Raghavendra, Krishnamurthy, Raghu, R Krishnamurthy, R. KRISHNAMURTHY, R. Krishnamurthy, Raghavendra (Raghu) Krishnamurthy, Raghavendra Krishnamurthy, Raghu Krishnamurthy, Virendra Ghate

233

Publications

1.8K

Citations

H-Index

Concepts

All Affiliations

Pacific Northwest National Laboratory University of Notre Dame University of Colorado Boulder National Renewable Energy Laboratory Cooperative Institute for Research in Environmental Sciences

About

Raghavendra Krishnamurthy is an author at Pacific Northwest National Laboratory specializing in meteorology, engineering, and earth science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	19	27	971
2	Data Science	6	6	222
3	Civil Engineering	4	4	142
4	Climate Sciences	1	1	90
5	Computer Science	1	1	42

Raghavendra Krishnamurthy

Publications

1.4K

Citations

H-Index

Page 1

	Year	Citations
The Perdigão: Peering into Microscale Details of Mountain Winds Harindra J. S. Fernando, Jakob Mann, J. M. L. M. Palma, Bulletin of the American Meteorological Society	2018	198
The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign James M. Wilczak, Mark T. Stoelinga, Larry K. Berg, Bulletin of the American Meteorological Society EngineeringObservational Field CampaignWeather ForecastingClimate ModelingEarth System Science	2019	124
C-FOG: Life of Coastal Fog Harindra J. S. Fernando, Ismail Gültepe, Clive E. Dorman, Bulletin of the American Meteorological Society EngineeringClimate ModelingCoastal WaterOceanographyEarth Science	2020	90
Coherent Doppler lidar for wind farm characterization Raghavendra Krishnamurthy, Aditya Choukulkar, R. Calhoun, Wind Energy Vector Retrieval MethodsEngineeringWind EngineeringEarth ScienceAtmospheric Science	2012	87
On the estimation of boundary layer heights: a machine learning approach Raghavendra Krishnamurthy, Rob Newsom, Larry K. Berg, Atmospheric measurement techniques EngineeringMachine LearningMachine Learning ApproachWeather ForecastingDoppler Lidars	2021	66
Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting Daniel Vassallo, Raghavendra Krishnamurthy, Thomas Sherman, Energies Forecasting MethodologyHydrological PredictionEngineeringForestryWeather Forecasting	2020	58
Spatial and temporal variability of turbulence dissipation rate in complex terrain Nicola Bodini, Julie K. Lundquist, Raghavendra Krishnamurthy, Atmospheric chemistry and physics Complex TerrainEngineeringTurbulenceTurbulence Dissipation RateDoppler Lidars	2019	56
Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin Yelena L. Pichugina, Robert M. Banta, Timothy A. Bonin, Journal of Applied Meteorology and Climatology EngineeringSpatial UncertaintyDoppler LidarsWind EngineeringEarth Science	2019	47
3D Wind and Turbulence Characteristics of the Atmospheric Boundary Layer R. J. Barthelmie, Paola Crippa, Craig M. Smith, Bulletin of the American Meteorological Society	2013	46
Decreasing wind speed extrapolation error via domain-specific feature extraction and selection Daniel Vassallo, Raghavendra Krishnamurthy, Harindra J. S. Fernando Wind energy science EngineeringMachine LearningWeather ForecastingAnn Extrapolation AccuracyWind Engineering	2020	42

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