The Interannual Variability as a Test Ground for Regional Climate Simulations over Japan

Abstract

The validation of regional climate models is usually based on the intercomparison of the model's mean climate with the observed climatology. Albeit a prerequisite for the use of the model in a predictive mode, a successful validation of this type does not strictly test the model's ability to simulate anomalous conditions as might be associated with anthropogenic climate change. Here, we explore an alternate strategy, whereby the model's ability to reproduce the observed interannual variability is tested. The model utilized is an operational numerical weather prediction model of the German Weather Service, and it is tested for its use over East Asia and Japan in a series of 5 month-long January simulations. The model is used in a domain of 5100x5100km2, has a horizontal resolution of 56km, and 20 levels in the vertical. It is driven at its boundaries by the European Center for Medium-Range Weather Forecast (ECMWF) analysis.In validating the integrations, particular emphasis is put on the precipitation fields. For validation we use three different observational data sets: a terrestrial analysis from rain gauges, including the Automated Meteorological Data Acquisition System (AMeDAS) data of the Japan Meteorological Agency, the gridded data set of the Global Precipitation Climatology Project (GPCP), which over sea is largely based upon satellite information, and the ECMWF Re-Analysis (ERA) data set, which is produced by a model in an assimilation mode.It is demonstrated that the synoptic-scale evolution of individual low-pressure systems within the modeling domain is deterministically controlled by the lateral boundary conditions. Precipitation -spatially averaged over selected subdomains -compares remarkably well with the observations, both in terms of the monthly amounts and of the temporal evolution throughout the integration period. Using the strategy of a previous study, we analyze the year-to-year variations of the model results, both for the dynamical and precipitation fields. It is found that the modeling error is substantially smaller than the typical year-to-year fluctuations of the interannual variability. Implications of this result, concerning the model's use as a tool for down-scaling climate change, are also discussed.

The precipitation climate of Central Asia—intercomparison of observational and numerical data sources in a remote semiarid region

“…The model we use is the Climate High Resolution Model (CHRM) described in section 2.4. While different versions of this model have been tested thoroughly for their ability to represent climate variability in European and Asian domains (Lüthi et al, 1996;Fukutome et al, 1999;Vidale et al, 2003;Vidale et al, 2007) it is applied here in a semiarid and continental region. It is well-established methodology to use a climate model's ability to represent interannual variability as a surrogate for its ability to simulate climate change.…”

Predictability and uncertainty in a regional climate model

“…The RCM is driven at its lateral boundaries by the observed synoptic‐scale variability, and the model is evaluated for its ability to reproduce climatic fluctuations on monthly and seasonal timescales, within predictability bounds derived from an ensemble experiment. A previous version of this methodology has been used in month‐long integrations [ Lüthi et al , 1996; Fukutome et al , 1999], and more recently in Giorgi and Shields [1999], Small et al [1999] and Dutton and Barron [2000].…”

Mesoscale precipitation variability in the region of the European Alps during the 20th century

“…Airey and Hulme, 1995;Murphy, 1999;Widmann and Bretherton, 2000), and regional climate models (RCMs) (e.g. Jones et al, 1995, Lüthi et al, 1996Fukutome et al, 1997;Murphy, 1999); the use for ecosystem and hydrological impact modelling; and the construction of regional climate-change scenarios by statistical downscaling techniques (e.g. Cubasch et al, 1996;Wanner et al, 1997;Wilby et al, 1998;Zorita and von Storch, 1999;Widmann and Bretherton, 2000).…”