National Center for Atmospheric Research
Cloud and Solar Radiation Prediction
Although there has been a substantial, long-term effort by
the weather research community to improve precipitation
prediction, little attention has been paid to the prediction
of clouds and insolation. The need for accurate insolation
prediction is growing as the energy industry increases the
percentage of distributed and concentrated solar energy. In
addition, smart grid initiatives are expanding and the need for
accurate forecasts of insolation (and temperature) is growing
in parallel. NCAR’s Joint Numerical Testbed (JNT) has a
mission to test and verify the accuracy of weather models
for NOAA and the research community. It is well positioned
to assess the accuracy of operational and research models
in predicting clouds and solar radiation. The results would
highlight model skill and would provide valuable feedback to
modelers on accuracy deficiencies. The results would be used
to improve the models providing better information in the
future to solar energy decision makers.
research applications laboratory
Wind and Solar Energy Prediction
Background
Renewable energy decision makers are required to make
critical judgments on a daily basis with regard to energy
generation, distribution, demand, storage, and integration.
Accurate knowledge of the present and future state of the
atmosphere is vital in making these decisions.
The need for accurate insolation prediction is growing
as the energy industry increases the percentage of distributed
and concentrated solar energy.
Turbine Icing
For more than 20 years, NCAR, with funding from the FAA
and NASA, has led the nation in aircraft icing analysis and
prediction. NCAR’s aircraft icing products are disseminated
to the aviation industry through NOAA’s Aviation Weather
Center. There are many similarities between aircraft icing
and structural (wind turbine blade) icing because icing
on wind turbines can dramatically affect their efficiency.
Improved understanding of turbine icing is critical for the
accurate prediction of wind energy. NCAR would welcome an
opportunity to apply its icing expertise to the wind turbineicing problem.
Wind and solar energy are among the most difficult weather
variables to forecast. Topography, surface roughness, ground
cover, temperature inversions, foliage, gravity waves, lowlevel jets, clouds, and aerosols, all affect wind and solar
energy prediction skill.
As wind and solar energy portfolios expand, this forecast
problem is taking on new urgency because wind and solar
energy forecast inaccuracies frequently lead to substantial
economic losses and constrain the national expansion of
renewable energy.
NCAR scientists are already actively
engaged with industry decision makers on
how best to foresee and respond to shortand long-term changes in atmospheric
conditions to mitigate risks associated with
weather, particularly wind and solar energy
prediction.
The renewable energy industry expressed requirements for:
• Improved wind and solar energy forecast accuracy
• Improved resolution of forecast information and diagnostic
data in time and space (e.g., hourly and shorter term wind
and solar predictions)
NCAR has a long history of developing and maintaining
strong collaborations with universities; the private
sector; professional associations including the American
Meteorological Society, American Wind Energy Association,
Utility Wind Integration Group, American Geophysical Union,
National Business Aviation Association, and the Intelligent
Transportation Society of America; and with a host of federal
agencies such as DOE, NOAA, DOD, DHS, NASA, USDOT,
and NTSB. NCAR’s ability to perform research, develop realworld solutions, and work with industry to bring the solutions
to the marketplace to benefit the public make it an ideally
suited to contribute to the advancement of renewable energy
both nationally and internationally.
Icing on wind turbines can dramatically affect their efficiency.
Improved weather prediction and precise spatial analysis of
small-scale weather events are crucial for energy management,
as is the need to further develop and implement advanced
technologies. The National Center for Atmospheric Research
(NCAR), a leader in atmospheric research, development and
technology transfer for the past 50 years, is uniquely qualified
to support the renewable energy industry in these endeavors.
NCAR scientists are already actively engaged with industry
decision makers on how best to foresee and respond to shortand long-term changes in atmospheric conditions to mitigate
risks associated with weather, particularly wind and solar
energy prediction.
Industry Requirements
NCAR Collaborations
For More Information, Contact:
Sue Haupt, PhD
National Center for Atmospheric Research (NCAR)
Research Applications Laboratory
PO Box 3000 Boulder CO 80307-3000
303-497-2763
303-497-8401 fax
haupt@ucar.eduwww.ral.ucar.edu
Opportunity
• Better understanding of the uncertainty that is inherent in
the forecasts
• Additional weather observations at strategic locations for
energy nowcasting
Improved weather prediction and precise spatial analysis of smallscale weather events are crucial for energy management.
• Improved decision support products focused on:
• Load forecasting
• Increased efficiency in pricing for hourly
and bulk markets
• Precision management of demand in the local
distribution system
• Analysis of potential environmental and societal
impacts related to both short- and long-term
supply strategies
• Improved anticipatory response management planning
for high impact weather
• Improved air quality and greenhouse gas
management strategies
• Renewable energy planning, development,
and operations
Data Assimilation
NCAR leads a large effort on data assimilation and has
developed the WRF 3-Dimensional Variational Data
Assimilation (3DVAR) system and a continuous Real-Time
Four-Dimensional Data Assimilation (RTFDDA) system.
NCAR has ported its RTFDDA assimilation technique to
the WRF model, which is considered the best method
of incorporating local observations into high-resolution
models, such as those required for wind energy nowcasting
and forecasting. The WRF RTFDDA allows for smooth and
uninterrupted assimilation of new observations between
forecast cycles (i.e., with no cold-starts that incur model
spin-up effects in the first 6-12 hours of each forecast).
The RTFDDA technology is part of the operational suite of
weather systems NCAR has implemented for the U.S. Army’s
Test and Evaluation Command.
A 300-megawatt wind farm in Colorado will make enough electricity to power about 90,000 homes.
Relevant Experience
NCAR is a world-renowned atmospheric scientific research,
development and technology transfer center which works
to advance weather capabilities for mission agencies and
the public and private sectors. NCAR is operated by the
University Corporation for Atmospheric Research (UCAR),
a non-profit organization established in 1960 to oversee a
wide range of programs and facilities that support its 100+
university affiliates, as well as the national and international
scientific community. As a national center, NCAR is able
to utilize advancements developed not only at NCAR, but
at research centers, institutes, universities, and national
laboratories worldwide. NCAR is well-positioned to apply its
expertise and technologies to support the renewable energy
community and, through its technology transfer programs, to
ensure that advancements are quickly adopted and utilized by
industry. Below we highlight specific contributions NCAR can
make to improving wind and solar energy prediction.
Weather Prediction Modeling
and Data Assimilation
NCAR is one of the lead organizations developing the
Weather Research and Forecasting (WRF) model, as well as
testing and distributing the code to the weather research and
operational communities. WRF features multiple dynamical
cores, a growing suite of data assimilation systems, and a
software architecture allowing for computational parallelism
and system extensibility. WRF is suitable for a broad
spectrum of applications across scales ranging from meters
to thousands of kilometers. NCAR’s Joint Numerical Testbed
(JNT) tests and evaluates numerical weather prediction
systems to provide meaningful information about forecast
performance to operational decision makers and to provide
the research and development community (including NOAA
and AFWA) with support in their development of these systems.
Wind Energy Nowcasting
UCAR has spent more than 15 years developing and
operationally deploying a robust very short-term nowcasting
system called the Auto-Nowcaster (image below). This system
ingests available observational datasets (radar, surface
station, satellite, lidar, met tower, and rawinsonde) in realtime, analyzes the atmosphere using a physical model,
combines observational data with weather model output,
and generates nowcasts out to 2 hours every 6-10 minutes.
Although initially designed to predict thunderstorm initiation,
growth and decay, the methods and techniques used within
this system are focused on the analysis and prediction of
the lower boundary layer, and in particular, the local wind
fields that are critical for wind energy nowcasting. These
capabilities are uniquely suited for wind ramp and solar
energy nowcasting.
Quantifying interannual wind variability between El Niño and La Niña years - January winds at 0600 UTC (2300 MST)
UCAR has spent more than 15 years
developing and operationally deploying
a robust very short-term nowcasting
system called the Auto-Nowcaster. These
capabilities are uniquely suited for wind
ramp and solar energy nowcasting.
Boundary Layer Research
NCAR has extensive expertise in planetary boundary
layer (PBL) meteorology and modeling. NCAR research
includes three-dimensional, time-dependent, PBL turbulence
using turbulence-resolving numerical simulations and in
particular Large-Eddy Simulation (LES) for a wide variety
of geophysical flows. LES explicitly captures large turbulent
eddies, which contain most of the turbulent kinetic energy
and carry most of turbulent transport, and approximates
the effects of small turbulent eddies in its subgrid-scale
model. This technique was first developed at NCAR in the
late 1960s, and is now widely used as a major tool for
investigations of turbulence in engineering and geophysical
fields. LES techniques are well suited for investigations of
wind flow characterization, which is critical for the proper
design and operation of wind turbines.
NCAR's Auto-Nowcaster display showing approaching wind surge.
Modeled fine-scale wind flow over a wooded area.
Evaluation of Global Wind
and Solar Resources
NCAR’s climate modeling and downscaling technologies are
well positioned to support the development of wind and solar
resource assessment datasets. In particular, the Climate Four
Dimensional Data Assimilation System (CFDDA) has been
used to create 25 years of global hourly climatologies with
a 60 km grid size increment. This unique and large dataset
was generated by NCAR with support by the Defense Threat
Reduction Agenda (DTRA) and can be downscaled further
to generate high-resolution physically balanced datasets
that would provide critical information on the historical
characteristics of the wind field at various wind generator
hub heights. The global nature of these data makes them
particularly useful for assessing the character of onshore and
offshore wind resources.
Future Climate Impacts on Wind
and Solar Resources
NCAR is a world leader in climate research and modeling
and has been intimately involved in the work of the
Intergovernmental Panel on Climate Change (IPCC). NCAR
is also a key contributor to the North American Regional
Climate Change Assessment Program (NARCCAP), which
produces high-resolution climate change simulations in order
to investigate uncertainties in regional scale projections of
future climate and generate climate change scenarios for use
in impacts research. This program has generated a full suite
of regional climate projections at multiple scales that have
been used to create climate change scenarios by end-users.
These future climate data sets can be refined and reapplied
to investigate future wind and solar energy resources across
the nation.