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Impact Of Surface State Analysis On Estimates Of Long Term Variability Of A Wind Resource. Dr. Jim McCaa jmccaa@3tiergroup.com. 3TIER Group Established 1999 Offices in North and Latin America Focused on the weather driven renewable energy sector (wind-hydro-solar) Forecasting for over:
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Impact Of Surface State Analysis On Estimates Of Long Term Variability Of A Wind Resource Dr. Jim McCaa jmccaa@3tiergroup.com
3TIER Group • Established 1999 • Offices in North and Latin America • Focused on the weather driven renewable energy sector (wind-hydro-solar) • Forecasting for over: • 2,000 MW wind energy (18 projects) • 2,000 MW hydro (6 projects)
Month Ahead Forecasts & Resource Assessment Requires a full understanding of project output and climate variability
Long term forecasting issues • Does wind have dependable capacity on seasonal/monthly time scales? • What is the probability of several above/below average years in a row? • Is production linked to predictable climate indices? • Can probabilistic forecasts contribute to dependable capacity?
Resource Related Risk Analysis: R-cubed Time-evolving Moisture Availability INPUTS METHOD PRODUCTS Hourly 3-dimensional meteorological data Numerical Weather Simulation Model Global Weather Archive 1948-present Spatial Maps of Wind Resource Hourly spatial meteorological data Multi year hourly time series Accurate Variability Estimate & Month Ahead Forecast Capability High Resolution Terrain, Soil and Vegetation Data Dynamics Statistics Accurate Dependable Capacity Estimates On-Site Observations
Strengths and Weaknesses of Modeled Record Extension • Demonstrated skill at downscaling large scale flows and generating internal thermally-driven circulations • Models generally underpredict natural variability • Strong dependence on lower and lateral boundary conditions
Limitations of reanalysis dataset • Useful for capturing large-scale flow in the upper atmosphere • Not suitable for use at a single point • Can not represent small-scale/thermally driven flow • Too coarse for proper surface initialization
Case study: Northern California • Long-term met tower near Altamont • Flow dominated by thermal circulation driven by heating in the San Joaquin Valley • Pathological case for reanalysis forcing
Interannual Variability by Season Winter (DJF) Mean Winds Summer (JJA) Mean Winds
Introduction of better surface initialization • Re-initialize surface moisture every 3 days from an 1/8 degree hydrology model • Hydrology simulation provided by Ed Maurer of the University of Washington • Hydrology model was driven by surface observations from 1950 to 2000 • Only addresses one part of the surface initialization problem
VIC hydrology model • The Variability Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington.
Old and new moisture availability Reanalysis 6/1/1993 VIC 6/1/1993 (red is 0.1, blue is 0.5)
Improved Interannual Variability Winter (DJF) Mean Winds Summer (JJA) Mean Winds
75% 30 Years of below average or average wind 10 Years of above average wind 17% Large variability in capacity factor from month to month
PDO Positive PDO Negative
Winter Wind Every month forecast below average Summer Wind Near Average El Nino Conditions: Annual Capacity Factor decreases from 43% to 39%
Summary • NCEP/NCAR reanalysis can be used (when appropriately downscaled!) to reconstruct synoptically-driven flow • Mesoscale model representation of thermally-driven circulations is reasonable, but may show insufficient interannual variability • Improvements to mesoscale model surface initialization translate to better reconstructed winds
3TIER Environmental Forecast Group www.3tiergroup.com info@3tiergroup.com (206) 325-1573