scholarly journals Improving Wind Predictions in the Marine Atmospheric Boundary Layer through Parameter Estimation in a Single-Column Model

2016 ◽  
Vol 145 (1) ◽  
pp. 5-24 ◽  
Author(s):  
Jared A. Lee ◽  
Joshua P. Hacker ◽  
Luca Delle Monache ◽  
Branko Kosović ◽  
Andrew Clifton ◽  
...  

Abstract A current barrier to greater deployment of offshore wind turbines is the poor quality of numerical weather prediction model wind and turbulence forecasts over open ocean. The bulk of development for atmospheric boundary layer (ABL) parameterization schemes has focused on land, partly because of a scarcity of observations over ocean. The 100-m FINO1 tower in the North Sea is one of the few sources worldwide of atmospheric profile observations from the sea surface to turbine hub height. These observations are crucial to developing a better understanding and modeling of physical processes in the marine ABL. In this study the WRF single-column model (SCM) is coupled with an ensemble Kalman filter from the Data Assimilation Research Testbed (DART) to create 100-member ensembles at the FINO1 location. The goal of this study is to determine the extent to which model parameter estimation can improve offshore wind forecasts. Combining two datasets that provide lateral forcing for the SCM and two methods for determining , the time-varying sea surface roughness length, four WRF-SCM/DART experiments are conducted during the October–December 2006 period. The two methods for determining are the default Fairall-adjusted Charnock formulation in WRF and use of the parameter estimation techniques to estimate in DART. Using DART to estimate is found to reduce 1-h forecast errors of wind speed over the Charnock–Fairall ensembles by 4%–22%. However, parameter estimation of does not simultaneously reduce turbulent flux forecast errors, indicating limitations of this approach and the need for new marine ABL parameterizations.

2005 ◽  
Vol 118 (2) ◽  
pp. 273-303 ◽  
Author(s):  
J. Cuxart ◽  
A. A. M. Holtslag ◽  
R. J. Beare ◽  
E. Bazile ◽  
A. Beljaars ◽  
...  

2007 ◽  
Vol 112 (D24) ◽  
Author(s):  
Matthew C. Wyant ◽  
Christopher S. Bretherton ◽  
Andreas Chlond ◽  
Brian M. Griffin ◽  
Hiroto Kitagawa ◽  
...  

2014 ◽  
Vol 11 (1) ◽  
pp. 83-88 ◽  
Author(s):  
H. Breuer ◽  
F. Ács ◽  
Á. Horváth ◽  
P. Németh ◽  
K. Rajkai

Abstract. Weather Research and Forecasting (WRF) single-column model simulations were performed in the late summer of 2012 in order to analyse the diurnal changes of the planetary boundary layer (PBL). Five PBL schemes were tested with the WRF. From the radiometer and wind-profiler measurements at one station, derived PBL heights were also compared to the simulations. The weather conditions during the measurement period proved to be dry; the soil moisture was below wilting point 85 percent of the time. Results show that (1) simulation-based PBL heights are overestimated by about 500–1000 m with respect to the observation-based PBL heights, and (2) PBL height deviations between different observation-based methods (around 700 m in the midday) are comparable with PBL height deviations between different model schemes used in the WRF single-column model. The causes of the deviations are also discussed. It is shown that in the estimation of the PBL height the relevance of the atmospheric profiles could be as important as the relevance of the estimation principles.


2020 ◽  
Author(s):  
Ligia Bernardet ◽  
Grant Firl ◽  
Dom Heinzeller ◽  
Laurie Carson ◽  
Xia Sun ◽  
...  

<p>Contributions from the community (national laboratories, universities, and private companies) have the potential to improve operational numerical models and translate to better forecasts. However, researchers often have difficulty learning about the most pressing forecast biases that need to be addressed, running operational models, and funneling their developments onto the research-to-operations process. Common impediments are lack of access to current and portable model code, insufficient documentation and support, difficulty in finding information about forecast shortcomings and systematic errors, and unclear processes to contribute code back to operational centers. </p><p>The U.S. Developmental Testbed Center (DTC) has the mission of connecting the research and operational Numerical Weather Prediction (NWP) communities. Specifically in the field of model physics, the DTC works on several fronts to foster the engagement of community developers with the Unified Forecast System (UFS) employed by the U.S. National Oceanic and Atmospheric Administration (NOAA).  As a foundational step, the UFS’ operational and developmental physical parameterizations and suites are now publicly distributed through the Common Community Physics Package (CCPP), a library of physics schemes and associated framework that enables their use with various models. The CCPP can be used for physics experimentation and development in a hierarchical fashion, with hosts ranging in complexity from a single-column model driven by experimental case studies to fully coupled Earth system models. This hierarchical capability facilitates the isolation of non-linear processes prior to their integration in complex systems. </p><p>The first public release of a NOAA Unified Forecast System (UFS) application is expected for February 2020, with a focus on the Medium-Range Weather Application. This global configuration uses the CCPP and will be documented and supported to the community. To accompany future public releases, the DTC is creating a catalog of case studies to exemplify the most prominent model biases identified by the US National Weather Service. The case studies will be made available to the community, who will be able to rerun the cases, to test their innovations and document model improvements. </p><p>In this poster we will summarize how we are using the UFS public release, the single-column model, the CCPP, and the incipient catalog of code studies to create stronger connections among the groups that diagnose, develop, and produce predictions using physics suites.</p>


2000 ◽  
Vol 128 (9) ◽  
pp. 3187-3199 ◽  
Author(s):  
A. P. Lock ◽  
A. R. Brown ◽  
M. R. Bush ◽  
G. M. Martin ◽  
R. N. B. Smith

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