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An evaluation of a two-decade CONUS and Northern Hemispheric timeseries of retrospective WRF simulations
Citation:
Gilliam, R., K. Foley, J. Bash, R. Mathur, N. Possiel, C. Misenis, B. Henderson, G. Sarwar, Keith Wyat Appel, AND G. Pouliot. An evaluation of a two-decade CONUS and Northern Hemispheric timeseries of retrospective WRF simulations. 20th CMAS Conference, Virtual, NC, November 01 - 04, 2021.
Impact/Purpose:
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Description:
The US EPA’s Air QUAlity TimE Series (EQUATES) Project has developed a consistent set of modeled meteorology and emissions that are being used to produce multidecadal timeseries (2002-2017) of air quality model output using the Community Multiscale Air Quality (CMAQ) model. This CMAQ dataset will be leveraged for a diverse set of research and air quality management applications. To support this collective dataset that will be available for broad distribution, we present an evaluation of the nearly twenty years of meteorology that was produced using version 4.1.1 of the Weather, Research and Forecasting (WRFv4.1.1) model. WRFv4.1.1 was ran over the contiguous United States and the Northern Hemisphere for the 2002-2020 period using a horizontal grid-resolution of 12 km and 108 km, respectively, although the air quality was a few years shorter. We examine the simulated meteorology using a broad range of observations including upper-air and near-surface temperature, moisture and winds. We also use shortwave radiation observations to examine the model’s ability to represent clouds. And finally, the US-based PRISM (Parameter-elevation Regressions on Independent Slopes Model) precipitation dataset is leveraged to understand how well the model characterizes seasonal and annual precipitation. Results of the evaluation show that the model output is suitable in terms of driving air quality models as error levels are within expected bounds of recent retrospective simulations that use data assimilation. As expected, the 12 km scale simulations reduce the level of error when compared to the coarser 108 km hemispheric domain. As such, the distribution and use of these meteorological modeling datasets can help air quality modelers by providing a robust and lengthly set of inputs for air quality applications.