A Performance Evaluation of Dynamical Downscaling of Precipitation over Northern California

Suhyung Jang, M. Levent Kavvas, Kei Ishida, Toan Trinh, Noriaki Ohara, Shuichi Kure, Z. Q. Chen, Michael L. Anderson, G. Matanga and Kara J. Carr
Additional contact information
Suhyung Jang: Water Resources Research Center, K-Water Institute, Daejeon 34045, Korea
M. Levent Kavvas: Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA
Kei Ishida: Department of Civil and Environmental Engineering, Kumamoto University, Kumamoto 860-8555, Japan
Toan Trinh: Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA
Noriaki Ohara: Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY 82071, USA
Shuichi Kure: Department of Environmental Engineering, Toyama Prefectural University, Toyama 939-0398, Japan
Z. Q. Chen: California Department of Water Resources, Sacramento, CA 95814, USA
Michael L. Anderson: California Department of Water Resources, Sacramento, CA 95821, USA
G. Matanga: US Bureau of Reclamation, Sacramento, CA 95825, USA
Kara J. Carr: Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, USA

Sustainability, 2017, vol. 9, issue 8, 1-17

Abstract: It 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.

Keywords: precipitation; regional climate model (RCM); watershed scale; reanalysis data; orographic effect; California (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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