A Performance Evaluation of Dynamical Downscaling of Precipitation over Northern California
AbstractIt is important to assess the reliability of high-resolution climate variables used as input to hydrologic models. High-resolution climate data is often obtained through the downscaling of Global Climate Models and/or historical reanalysis, depending on the application. In this study, the performance of dynamically downscaled precipitation from the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) reanalysis data (NCEP/NCAR reanalysis I) was evaluated at point scale, watershed scale, and regional scale against corresponding in situ rain gauges and gridded observations, with a focus on Northern California. Also, the spatial characteristics of the simulated precipitation and wind fields, with respect to various grid sizes, were investigated in order to gain insight to the topographic effect on the atmospheric state variables. To this end, dynamical downscaling was performed using the mesoscale atmospheric model MM5, and the synoptic scale reanalysis data were downscaled to a 3 km grid spacing with hourly temporal resolution. The results of comparisons at point scale and watershed scale over a 50-year time period showed that the MM5-simulated precipitation generally produced the timing and magnitude of the observed precipitation in Northern California. The spatial distributions of MM5-simulated precipitation matched the corresponding observed precipitation reasonably well. Furthermore, the statistical goodness of fit tests of the MM5-simulated precipitation against the corresponding observed precipitation showed the reliability and capability of MM5 simulations for downscaling precipitation. A comparison of the spatial characteristics of the results with respect to various grid sizes indicated that precipitation and wind fields are significantly affected by the local topography. In particular, the banded structures and orographic effects on precipitation and wind fields can be well described by a mesoscale model at 3 km and 9 km grid resolutions while 27 km and 81 km grid model simulation may not be sufficient for watershed-scale or sub-watershed-scale studies. View Full-Text
Share & Cite This Article
Jang, S.; Kavvas, M.L.; Ishida, K.; Trinh, T.; Ohara, N.; Kure, S.; Chen, Z.Q.; Anderson, M.L.; Matanga, G.; Carr, K.J. A Performance Evaluation of Dynamical Downscaling of Precipitation over Northern California. Sustainability 2017, 9, 1457.
Jang S, Kavvas ML, Ishida K, Trinh T, Ohara N, Kure S, Chen ZQ, Anderson ML, Matanga G, Carr KJ. A Performance Evaluation of Dynamical Downscaling of Precipitation over Northern California. Sustainability. 2017; 9(8):1457.Chicago/Turabian Style
Jang, Suhyung; Kavvas, M. L.; Ishida, Kei; Trinh, Toan; Ohara, Noriaki; Kure, Shuichi; Chen, Z. Q.; Anderson, Michael L.; Matanga, G.; Carr, Kara J. 2017. "A Performance Evaluation of Dynamical Downscaling of Precipitation over Northern California." Sustainability 9, no. 8: 1457.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.