Statistical‐dynamical downscaling of precipitation for Vietnam: methodology and evaluation for the recent climate. (23rd April 2017)

• Record Type: Journal Article
• Authors: Schubert, David; van der Linden, Roderick; Reyers, Mark; Fink, Andreas H.; Massmeyer, Klaus; Pinto, Joaquim G.
• Is Part Of: International journal of climatology. Volume 37:Number 11(2017)
• Page Start: 4211
• Page End: 4228
• Publication Date: 2017-04-23
• Subjects: precipitation -- Southeast Asia -- Vietnam -- k‐means -- statistical‐dynamical downscaling -- recent climate -- COSMO‐CLM; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.5062
• Languages: English
• ISSNs: 0899-8418

Abstract

ABSTRACT: Precipitation over Southeast Asia is primarily controlled by the Southeast Asian monsoon system. This area features complex orography and morphology, and has limited surface precipitation observations. In this study, a statistical‐dynamical downscaling approach that combines weather typing and dynamical downscaling is developed to obtain a high‐resolution precipitation climatology for tropical Southeast Asia. A transient simulation with the regional climate model COSMO‐CLM (COnsortium for Small Scale MOdelling‐Climate Limited‐area Modelling Community) driven by ERA‐Interim (1979–2008) is performed for the study region. Focussing on Vietnam, six weather types (WTs) are selected for the Indochina Peninsula during the wet season (April to October) using a k‐means cluster approach on daily 850 and 200 hPa zonal wind components from ERA‐Interim reanalysis. The six WTs can be physically interpreted as different stages of the seasonal progression of the planetary‐scale monsoon circulation. For each WT, selected representatives from the COSMO‐CLM run are dynamically downscaled to a resolution of 0.0625° × 0.0625° (∼7 km). Using the present‐day WT frequencies, the simulated COSMO‐CLM representatives at 7 km are recombined to a high‐resolution rainfall climatology for the recent decades. The resulting high‐resolution precipitation climatology is generally able to capture the present‐day precipitation estimates derived from APHRODITE (Asian Precipitation – Highly Resolved Observational Data Integration Towards Evaluation of Water Resources) and station data. In spite of systematic biases our approach provides a valuable tool to obtain more robust regional climate change projections for the study area.