Trends in Surface Wind Speed over the Last 30

Years

Trends in Surface Wind Speed over the Last 30

YearsGene Takle

Analyses done primarily by Sara Pryor, University of Indiana

Additional analyses by Theresa Andersen

Gene Takle

Analyses done primarily by Sara Pryor, University of Indiana

Additional analyses by Theresa AndersenBased on manuscript submitted to Journal of Geophysical Research:

Pryor, S. C., R. J. Barthelmie, D. T. Young, E. S. Takle, R. W. Arritt, D. Flory, W. J. Gutowski, Jr., and A. Nunes, 2008: Wind speed trends over the contiguous USA

Atmospheric Science Seminar SeriesIowa State University28 November 2008

OutlineOutline

Why should we care? Emerging importance of

wind power Trends in US wind speed

- observations Trends in US wind speed

- modeling studies Trends in winds

elsewhere Role of wind in the

global energy balance Future studies

Why should we care? Emerging importance of

wind power Trends in US wind speed

- observations Trends in US wind speed

- modeling studies Trends in winds

elsewhere Role of wind in the

global energy balance Future studies

Trends in Surface Wind Speeds:

Why should we care?

Trends in Surface Wind Speeds:

Why should we care?Surface winds drive ocean

circulationSurface winds regulate

exchanges of heat and moisture with the surface

Surface winds transport pollen, seeds, insects, etc.

Surface winds can be harnessed for wind power

Surface winds drive ocean circulation

Surface winds regulate exchanges of heat and moisture with the surface

Surface winds transport pollen, seeds, insects, etc.

Surface winds can be harnessed for wind power

Note: I am not considering storm-scale winds

Wind PowerWind Power

Wind is a clean (i.e., carbon-free, pollution-free) source of renewable energy

The US Department of Energy has a goal of producing 20% of our energy supply from wind by 2030.

This will require 300 GW by 2030 (US installed capacity as of Sept 2008 was 20 GW)

Wind is a clean (i.e., carbon-free, pollution-free) source of renewable energy

The US Department of Energy has a goal of producing 20% of our energy supply from wind by 2030.

This will require 300 GW by 2030 (US installed capacity as of Sept 2008 was 20 GW)

Wind power, P ~ V3

Iowa’s ContributionIowa’s Contribution

Iowa ranks third among all states in wind generation with 1.375 GW of operating capacity

An additional 1.586 GW of capacity is under construction and will be available in 18 months, according to the American Wind Energy Association. (DM Register, 24 October 2008).

Iowa ranks third among all states in wind generation with 1.375 GW of operating capacity

An additional 1.586 GW of capacity is under construction and will be available in 18 months, according to the American Wind Energy Association. (DM Register, 24 October 2008).

“Given that a 1% error in wind speed estimates for a 100 MW wind generation facility can lead to losses approaching $12,000,000 over the lifetime of that plant, a better understanding of the physical and dynamic processes across the range of scales that create a particular wind climate is needed.”Draft recommendations, DOE Workshop on Research Needs for Wind Resource Characterization, 14-16 Jan 2008, Broomfield, CO

Iowa will have 3,000 MW installed by 2010, so a 1% error is $360 million over its lifetime.

Need Better Estimates of Wind Speed for Forecasting Wind Power

Two Datasets of Observed Wind

Two Datasets of Observed Wind

Subset of NCDC-6421 dataset, homogenized to 10-m height, 800+ stations, 1973-2000 (Groisman, 2000)

Subset of NCDC DS3505 dataset, homogenized to 10-m height, 193 stations, 1973-2005

Only data from 00 and 12 UTC are used

Subset of NCDC-6421 dataset, homogenized to 10-m height, 800+ stations, 1973-2000 (Groisman, 2000)

Subset of NCDC DS3505 dataset, homogenized to 10-m height, 193 stations, 1973-2005

Only data from 00 and 12 UTC are used

Problems with Observations

Problems with Observations

Changes in instrumentation

Station movesChanges in land-use

around the stationMissing dataData resolution for

computing robust temporal trends

Changes in instrumentation

Station movesChanges in land-use

around the stationMissing dataData resolution for

computing robust temporal trends

Mean Wind Speeds as Representedin Observations, Reanalyses, and Regional Climate Models

Analysis MethodAnalysis Method

Focus on 50th and 95th percentiles of wind speed distribution (annual time scale)

Analyzed for trends using linear regression and bootstrapping techniques

Interannual variability computed from a 7-year window for annual means of each station, with value assigned to the central year (for assessing trends in interannual variability)

Focus on 50th and 95th percentiles of wind speed distribution (annual time scale)

Analyzed for trends using linear regression and bootstrapping techniques

Interannual variability computed from a 7-year window for annual means of each station, with value assigned to the central year (for assessing trends in interannual variability)

Trends is Surface Winds - Observations

Transition to ASOSwind speed change of -0.2 (-0.65 to +0.15) m/s)

Observed Wind Speeds

Trends in Observed Surface Winds (% per year)

00 UTC

Trends in Observed Surface Winds (% per year)

12 UTC

Modeled Trends in Surface Winds

Modeled Trends in Surface Winds

NCEP/NCAR Reanalysis 1NCEP/DOE Reanalysis 2ERA-40 ReanalysisNorth American Regional

Reanalysis (NARR)MM5RSM

NCEP/NCAR Reanalysis 1NCEP/DOE Reanalysis 2ERA-40 ReanalysisNorth American Regional

Reanalysis (NARR)MM5RSM

Trends in Reanalysis Surface Winds (% per year)NCEP/NCAR R 1 and NCEP/DOE R 2

00 UTC

Trends in Reanalysis Surface Winds (% per year)NCEP/NCAR R 1 (truncated to NCDC periods)

00 and 12 UTC combined

Trends in Reanalysis Surface Winds (% per year)ERA-40 and NARR

00 UTC

Trends in Regional Climate Models Surface Winds (% per year)

MM5 and RSM00 UTC

Trends in Regional Climate Models Surface Winds (% per year)

NARR

00 UTC

12 UTC

Trends in Regional Climate Models Surface Winds (% per year)

MM5

12 UTC

00 UTC

Trends in Regional Climate Models Surface Winds (% per year)

RSM

00 UTC

12 UTC

Summary of Analysis of Observed and Modeled Surface

Wind Speeds

Summary of Analysis of Observed and Modeled Surface

Wind Speeds Observed winds show substantial decreasing trends (up

to 1%/yr at many stations) NCEP-1 (but not NCEP-2) Reanal show increasing trend

over much of the US, especially the Midwest ERA-40 has regions in the western US that are evenly

divided between increases and decreases. Not much change in eastern US

NARR show little change in eastern US but conflicting changes (increases at 50th and decreases at 90th percentile; decreases at 00 UTC and increases at 12 UTC)

Period of observation is important in assessing trends MM5 shows decreasing trend RSM shows increasing trend (larger trends at 00 UTC)

Observed winds show substantial decreasing trends (up to 1%/yr at many stations)

NCEP-1 (but not NCEP-2) Reanal show increasing trend over much of the US, especially the Midwest

ERA-40 has regions in the western US that are evenly divided between increases and decreases. Not much change in eastern US

NARR show little change in eastern US but conflicting changes (increases at 50th and decreases at 90th percentile; decreases at 00 UTC and increases at 12 UTC)

Period of observation is important in assessing trends MM5 shows decreasing trend RSM shows increasing trend (larger trends at 00 UTC)

Statistically Significant Changes in Mean and Variability of Wind Speed: Observations

mean

mean & IV

IV

Statistically Significant Changes in Mean and Variability of Wind Speed: NCEP-1 and NCEP -2

Statistically Significant Changes in Mean and Variability of Wind Speed: ERA-40 and NARR

Statistically Significant Changes in Mean and Variability of Wind Speed: MM5 and RSM

Wind Speed (m/s) departures from monthly means from 70-m tall towers in MinnesotaKlink, K., 2007: J. Appl. Meteor. Clim. 46, 446

Seasonal and Interannual Variability of Wind Speeds

Wind Speed (m/s) departures from monthly means from 70-m tall towers in MinnesotaKlink, K., 2007: J. Appl. Meteor. Clim. 46, 446

Seasonal and Interannual Variability of Wind Speeds

Seasonal and Interannual Variability of Wind Speeds

Seasonal and Interannual Variability of Wind Speeds

Seasonal and Interannual Variability of Wind Speeds

Does MM5 recognize an SOI signal in the Upper Midwest from Jan 79 – May 04?

Does MM5 recognize an NAO signal in the Upper Midwest from Jan 79 – May 04?

Wind Speed Trends Elsewhere

Wind Speed Trends Elsewhere

China: “From 1969-2000, the annual mean wind speed over China has decreased steadily by 28%, and the prevalence of windy days (daily mean wind speed > 5 m/s) has decreased by 58%”. (Xu et. al., JGR 111, 2006)

Australia: “Recent observations of near-surface wind speed trends measured by terrestrial anemometers have shown declines between -0.004 m/s per year to -0.017 m/s per year over the last 30-50 years in Australia, China, Europe, North America, and Tibet.” McVicar et al., GRL 35, 2008)

China: “From 1969-2000, the annual mean wind speed over China has decreased steadily by 28%, and the prevalence of windy days (daily mean wind speed > 5 m/s) has decreased by 58%”. (Xu et. al., JGR 111, 2006)

Australia: “Recent observations of near-surface wind speed trends measured by terrestrial anemometers have shown declines between -0.004 m/s per year to -0.017 m/s per year over the last 30-50 years in Australia, China, Europe, North America, and Tibet.” McVicar et al., GRL 35, 2008)

McVicar et al., 2008: GRL 35.

“…the Australian-averaged u-trend for 1975-2006 was -0.009 m/s per year …over 88% of the land surface.”

Impact on Pan Evaporation

Roderick et al., 2007:GRL 34

SummarySummary

Evidence seems to be growing that wind speeds globally are declining

Observing and analysis challenges (NOA, SOI) make it difficult to define trends, however

Reanalyses and regional climate models are not consistent in simulating trends

Impacts of trends on wind power production demands better answers

Evidence seems to be growing that wind speeds globally are declining

Observing and analysis challenges (NOA, SOI) make it difficult to define trends, however

Reanalyses and regional climate models are not consistent in simulating trends

Impacts of trends on wind power production demands better answers