Downscaling over Vietnam using the stretched-grid CCAM: verification of the mean and interannual variability of rainfall

• Published in: Climate dynamics 2014-08, Vol.43 (3-4), p.861-879
• Main Authors: Nguyen, Kim C, Katzfey, Jack J, McGregor, John L
• Format: Article
• Language: English
• Subjects: Analysis; Climate models; Climatology; data collection; Demographic aspects; Dry season; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; El Nino; Environmental aspects; Exact sciences and technology; External geophysics; Geophysics. Techniques, methods, instrumentation and models; Geophysics/Geodesy; Influence; Meteorology; Oceanography; Oceans; Precipitation variability; rain; Rain and rainfall; Rainfall; Rainfall measurement; sea level; Sea surface temperature; Southern Oscillation; statistical analysis; Statistical methods; surface temperature; Tidal waves; Water in the atmosphere (humidity, clouds, evaporation, precipitation); Water resources; Wind
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-013-1976-5

Rainfall over Vietnam is highly variable from north to south, due to the interaction of the monsoonal winds with the terrain. There is high rainfall from April to September, and little rainfall from October to March (except along the central Vietnam coast). In order to study the ability of the Commonwealth Scientific and Industrial Research Organisation stretched-grid Conformal Cubic Atmospheric Model (CCAM) to capture the climatic and interannual variability of rainfall, downscaled simulations at approximately 20 km horizontal resolution over the region were produced for the period 1979–2001. A scale-selective digital filter was used to force the winds, temperature and sea-level pressure from the ERA-Interim reanalysis for length scales greater than about 700 km. For wind and temperature, the forcing is applied for pressure-sigma levels above about 0.9. ERA-Interim sea surface temperatures were used over the oceans. The simulations were primarily validated against the gridded Asian Precipitation Highly Resolved Observational Data Integration Toward Evaluation of the Water Resources rainfall dataset and station observations using standard statistical methods. It was found that CCAM reproduces well the amount and spatial variability of rainfall, with an area-averaged bias for the entire study domain of less than 1 mm day⁻¹; CCAM is also able to capture the rainfall pattern under different El Niño Southern Oscillation phases reasonably well for the dry season. For interannual variability, the simulation generally performed better for North and Central Vietnam than for South Vietnam, where rainfall variability was overestimated.