Model Simulation and Projection of Temperature, Precipitation in Present-Day and Future Climates in WRF driven by CCSM4 over North America

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Monday, 5 January 2015
Jiali Wang, ANL, Lemont, IL; and V. R. Kotamarthi

This work will present an overview of changes in climatology and extreme events that are likely to affect North America in the middle and by the end of the twenty first century. A variety of diagnostic approaches are used to determine how climatology and extreme events change between present (1995-2004) and future (2045-2055, 2085-2094) climate under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5). The simulations are conducted using the WRF driven by CCSM4.0. The simulation domain is centered at 52.24N and 105.5W and has dimensions of 600 * 516 horizontal grid points in the west-east and south-north directions with grid spacing of 12 km, covering most of North America. To our best knowledge, this is probably the first run at 12 km covering such a big domain over decadal timescales. The model setup/configurations, model bias, and the dominant causes for the bias have been investigated by running the WRF driven by NCEP-R2. For more details, see Wang and Kotamarthi (2014). This presentation work will focus on two parts, one is the evaluations of the historical simulation (summarized in point 1), and the other is the predictions of future climate (summarized in points 2-5). A summary of the main results so far follows. 1. The WRF adds value to the driving data in terms of spatial variations and local features based on monthly and daily total precipitation, especially over western US. The WRF captures the annual cycle of temperature and precipitation very well except showing some wet biases for precipitation over Mountain West and Desert (see Bukovsky 2011 for ten super subregions over the land). 2. There is a significant warm signal for the mean temperature for all the seasons over most of US, especially for summer mean temperature, showing signal-to-noise ratio >2 (the noise here defined as the interannual variability). 3. Changes in extreme temperature are investigated by defining different indices (Expert Team on Climate Change Detection and Indices (ETCCDI), Zhang et al. 2011). There is a robust increase in summer days, tropical nights, annual minimum daily minimum temperature, and annual maximum daily maximum temperature over most of North America. In contrast, there is a robust decrease in frost days. Interannual variability is considered in investigating the signal. 4. There is a dry signal for winter and spring precipitation over the southwestern US, and a wet signal for spring precipitation over the eastern US and all-season precipitation over Canada and Alaska. However, the dry/wet signal is not as strong as that for precipitation and is even weaker than the interannaul variability. 5. The extremes in precipitation are found to be increasing over most of subregions, except over Desert and Pacific Southwest. The days with 1-10mm/day and 20-40 mm/day are decreasing over Desert region. The annual maximum 1-day and 5-consecutive-day precipitation amount is also decreasing over the Desert region. References: Wang, J., and V. R. Kotamarthi (2014), Downscaling with a Nested Regional Climate Model in Near-Surface Fields over the Contiguous United States, J. Geophys. Res. Atmos., 119, DOI: 10.1002/2014JD021696. Bukovsky, M. S. (2011), Masks for the Bukovsky regionalization of North America, Regional Integrated Sciences Collective, Institute for Mathematics Applied to Geosciences, National Center for Atmospheric Research, Boulder, CO. Downloaded 2014-07-29. Zhang, X., L. Alexander, G. C. Hegerl, P. Jones, A. K. Tank, T. C. Peterson, B. Trewin, and F. W. Zwiers (2011), Indices for monitoring changes in extremes based on daily temperature and precipitation data, WIREs Clim. Chang., 2, 851-870, doi:10.1002/wcc.147.