downscaling global reanalyses with wrf for wind energy resource assessment

DownscalingGlobal Reanalyses with WRF

for Wind Energy Resource Assessment

Mark Stoelinga,Matthew Hendrickson, and Pascal Storck

3TIER, Inc.

Wind Resource Assessment

What is the long-term average wind resource at each turbine location within a proposed wind farm?

Wind Resource Assessment

Install “met towers” for a period of ≥ 1 year.

60 m

Wind Resource Assessment

Need to extend the observed information, both • spatially (around proposed windfarm) and• temporally (to estimate long-term mean from 1 year of measurements)

Estimating Temporal Variabilityof Wind Resource

How can we extend the short (1-year) record into a long-term mean? 1. Conventional approach

Identify a nearby, long-term, routine 10m wind observation (“reference station”) that correlates well with the 1-year tower measurement. Use linear regression to craft a relationship between reference site and tower, and then predict long-term mean at tower -> MCP

Estimating Temporal Variabilityof Wind Resource

2. First-Generation Reanalysis Data Sets(NCAR/NCEP “R1”, ERA-40): Can potentially provide a “synthetic long-term reference station”, but with potential pitfalls1. Coarse resolution of underlying model (1.5-2.5

deg)2. Flaws/limitations in DA method3. Changes in observations over 50 years4. Grids available only every 6 h (hourly is

preferred)

Estimating Temporal Variabilityof Wind Resource

3. Downscaling of Reanalysis Data Sets with a Mesoscale Model• Foundation: a mesoscale model can produce good climatology of local surface wind if provided with appropriate large-scale flow conditions.

• Model can “fill in” at hourly frequency• Model can also provide multiple predictors to inform a statistical relationship between observations and the synthetic long-term reference (e.g., MOS)

2nd-Generation Reanalyses(CFSR, ERA-Interim, MERRA)

• 33-year record, entirely during satellite era• high-resolution (~0.5 degrees)• modern DA methodologies (4DVAR, or much better 3DVAR)

• Direct assimilation of satellite radiances

2nd-Generation Reanalyses(CFSR, ERA-Interim, MERRA)

Questions:• Do these new reanalysis data sets result in more accurate downscaled retrospective simulations?

• Are the reanalyses so good that we don’t need to downscale?

Will look at:• global maps• validation of regional runs at individual met towers

Global 80-m long-term meanwind maps

• NCAR/NCEP “R1” Reanalysis• R1 w/ WRF downscaling

• 3TIER “FirstLook” data set• Completed 2008, 5-km / 10-year global land coverage, WRF 2.2, YSU PBL, simple land surface

• CFSR• ERA-Interim• MERRA

80-m Mean Wind Speed (m s-1)

R1

8

0

80-m Mean Wind Speed (m s-1)

CFSR

8

0

80-m Mean Wind Speed (m s-1)

ERA-Interim

8

0

80-m Mean Wind Speed (m s-1)

MERRA

8

0

80-m Mean Wind Speed (m s-1)

R1

8

0

80-m Mean Wind Speed (m s-1)

R1 downscaled

8

0

80-m Mean Wind Speed (m s-1)

R1 downscaled

8

0

80-m Mean Wind Speed (m s-1)

ERA-Interim

8

0

Regional Runs at Tower Sites• 4.5-km WRF runs, V3.0• PBL: YSU or MYJ; LSM: simple or Noah; grid nudging• 3-day runs strung together continuously for multiple years

9

2

1

1

16 9 4

Regional Runs at Tower Sites• Towers provide hourly data for periods ranging

from 1 – 8 years.• Wind speed error metrics R2 and MAE were

calculated for WRF time series at the tower sites at hourly, daily, monthly, and yearly time scales

Wind Speed R2 fordownscaled CFSR vs. NCAR/NCEP “R1”

Daily Monthly

R1 R2 R1 R2

CFS

R R

2

CFS

R R

2

N. AmerS.AmerEuropeAfricaIndiaAustr.

Wind Speed R2 fordownscaled ERA-Int vs. NCAR/NCEP “R1”

Daily Monthly

R1 R2 R1 R2

ERA

-Int R

2

ERA

-Int R

2

N. AmerS.AmerEuropeAfricaIndiaAustr.

Wind Speed R2 fordownscaled CFSR vs. raw CFSR

Daily Monthly

Raw CFSR R2 Raw CFSR R2

Dow

nsca

led

CFS

R R

2

Dow

nsca

led

CFS

R R

2

N. AmerS.AmerEuropeAfricaIndiaAustr.

Conclusions• Several new 33+ -year reanalysis data sets

with ~0.5° resolution have recently become available for general use

• New reanalyses show improved performance when used to drive downscaled WRF retrospective simulations for wind energy assessment

• Although resolution and DA have been improved compared to 1st-generation reanalyses, considerable value is still added with WRF downscaling

Caveats about new reanalyses• ERA-Interim and MERRA lag real time by a

few months• Mostly “WRF-ready”, though MERRA requires

some work (HDF4 file format)• Freely available• CFSR not consistently produced after Jan

2011