Evaluation of the impacts of assimilating the TAMDAR data on 12/4 km grid WRF-based RTFDDA simulations over the CONUS

An analysis of the impacts of assimilating the Tropospheric Airborne Meteorological Data Report (TAMDAR) data with the Weather Research and Forecasting-(WRF-) real-time four-dimensional data assimilation (RTFDDA) and forecasting system over the Contiguous US (CONUS) is presented. The impacts of the horizontal resolution increase from 12 km to 4 km on the WRF-RTFDDA simulations are also examined in conjunction with the TAMDAR data impacts. The assimilation of the TAMDAR data reduces the rootmean squared error of the moisture field predictions and increases the correlation between the predictions and the observations for both domains with 12 km and 4 km grid spacings. The TAMDAR data reduce the model dry biases in the middle and lower levels by adding moisture at those levels. Assimilating the TAMDAR data improves temperature predictions at middle to high levels and wind speed predictions at all levels especially for the 12 km domain. Increasing the horizontal resolution from 12 km to 4 km results in significantly larger impacts on surface variables than assimilating the TAMDAR data.

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Copyright Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 License.


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Author Zhang, Yongxin
Liu, Yubao
Nipen, Thomas
Publisher UCAR/NCAR - Library
Publication Date 2016-01-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:11:44.910363
Metadata Record Identifier edu.ucar.opensky::articles:18829
Metadata Language eng; USA
Suggested Citation Zhang, Yongxin, Liu, Yubao, Nipen, Thomas. (2016). Evaluation of the impacts of assimilating the TAMDAR data on 12/4 km grid WRF-based RTFDDA simulations over the CONUS. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7nv9kzn. Accessed 06 February 2025.

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