Wednesday, 28 September 2016
14:30 - 16:00 Meso-scale modelling and the model chain
Resource assessment  
          

Numerical weather prediction models are increasingly being used for the estimation of wind resources over large regions. The large-scale wind resource maps resulting from such models are useful to identify favourable regions for wind energy deployment in the prospection phase. Often reanalysis data is used as the input for these models and one these datasets, MERRA from NASA, has recently been replaced by MERRA2. We will discuss the consequences of this change along with using micro-scale models to downscale. Speakers will also address the important subject of modelling storms using a coupled numerical weather model a spectral wave model.

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Learning objectives

• An understanding of how to model winds and waves during a major storm;
• New techniques for using a microscale model to downscale from Weather Research and Forecasting (WRF);
• Improved guidelines for numerical modelling, turbulence analysis and wind engineering applications;
• Attendees will be introduced to MERRA2, a new Reanalysis database that will replace MERRA products;
• A map of changes in MERRA2 accuracy and how it affects representation of long-term wind variability will be provided for all target regions of the wind power industry.

Co-chair(s):

Pep Moreno Vortex, Spain
Co-authors:
Gil Lizcano (1) ^F
(1) Vortex, Barcelona, Spain

Half step forward towards new reanalysis generation: introducing MERRA2 and what it brings to the wind power industry

Introduction

A new interim NASA Reanalysis, MERRA2, has been released in February 2016. At the same time, original MERRA production has been discontinued with the completion of analyses for the same month. Interruption of MERRA was due to operational aspects and to the limitation of MERRA radiative transfer model to assimilate most of the currently active satellites.
The deployment of the new NASA Reanalysis and the interruption of the previous project implies an abrupt transition between sources. Analyses and studies are then required now to consolidate the new reanalysis product by the wind industry community.
What MERRA2 brings new and which is its impact on the quality of long-term wind data are questions that we are addressing through this work.

Approach

The analysis presented in this work is based on a comprehensive validation exercise of MERRA2 and derived WRF downscaled times series. Multiyear modeled times series are verified against wind mast data for about 100 sites across the world. Analysis of the accuracy of the modeled time series to capture climate variability and seasonality of wind regime is presented, including main correlation metrics and consistency tracks.
Comparison between MERRA2 and MERRA time series are also carried out as part of the analysis. As outcome, an identification of the regions where the transition between both NASA reanalysis products is more critical is obtained.

Main body of abstract

MERRA2 is an interim project which comes with new developments such as a better tracking of the chemistry of atmosphere, including aerosols and anthropogenic sources, providing more accurate answers to primary main objective of the Reanalysis projects: understanding contemporary climates and how are modulate by the global change trend.
MERRA2 also incoporates a new generation of satellite derived irradiance as part of the data assimilation system, which include all NOAA-18 onwards and MEtOp satellites. In what refers near surface wind regime, a cube sphere grid replaced the traditional regular latitude-longitude grid while MERRA horizontal resolution was preserved.

Preliminary results show changes in the quality of the reanalysis. MERRA2 has resolved some known issues with the exceed of low level drag and deficit in wind intensity over ocean. We also have identified stronger pressure gradients and winds around fronts and tropical cyclones than in MERRA.

The present work shows results from the verification exercise and the time consistency analysis. A map accuracy and quality changes in MERRA2 products from the wind industry end-user perspective will be provided.

Conclusion

Interrogating MERRA2 on its capability to portrait wind regime variability is crucial to consolidate MERRA2 usage within the wind industry. Wind industry demands that any modeled time series source meets the requirements to ensure necessary quality in representing seasonal and interannual variability and time consistency clearance.
Moreover, mitigating transition between different reanalysis products is important for the users community and requires to conduct analysis as the proposed in this work. We also foreseen transition challenges for ECWMF new reanalysis generation, ERA5, to be available in 2017, therefore the experience gained with MERRA to MERRA2 change will be very valuable.


Learning objectives
1. Attendees will be introduced to MERRA2, a new Reanalysis database that will replace MERRA products
2. A map of changes in MERRA2 accuracy and how it affects representation of long-term wind variability will be provided for all wind industry target regions
3. Audience will get guidelines on how to face next updates in different Reanalysis products