Validating Basic Surface Variables in the Australian Bureau of Meteorology Model with CEOP EOP3 In-situ Data

Abstract

The Coordinated Enhanced Observing Period (CEOP) Project has initiated the collection of model output location time series (MOLTS) data from numerical weather prediction and assimilation centers, including the Australian Bureau of Meteorology. These were designed to complement the collection of insitu observational data sets at the same 41 locations. This study is a preliminary attempt to assess the differences and similarities between the MOLTS and time series of the in-situ data. The MOLTS from the Bureau's global model for a number of atmospheric surface variables are compared with in-situ data for 6 locations for the entire year of EOP3 (October 2002 to September 2003. Using surface pressure as a prototype a number of preliminary comparisons of different properties of the two types of data are performed. The model fields from the 6 hour assimilation forecast series and from the concatenated 12 to 36 hour forecasts are first compared with hourly in-situ observations in simple gross terms; simple statistics and scatter plots have been obtained to identify areas for further investigation. Global wavelet power spectra are compared to show the behavior of the dominant modes of variability and the average annual diurnal variations of the variables are derived. Some case studies with other variables with increasing sensitivity to sub-grid scales and increasing dependency on surface properties are then documented. The model and in-situ time series show similar behavior for surface pressure with greater differences for the other variables. Precipitation shows the greatest differences.

A Multimodel Analysis for the Coordinated Enhanced Observing Period (CEOP)

“…In general, comparisons of the analyses from the NWPCs have primarily been through the single-point Model Output Location Time Series (MOLTS) collocated with CEOP reference sites or through considering only one model system (Yang et al 2007;Chou et al 2007;Rikus 2007;Milton and Earnshaw 2007;Hirai et al 2007;Meinke et al 2007;Kato et al 2007;Bosilovich et al 2007). To get at the comparison of global grids, an ensemble of the analyses was developed for several purposes.…”

Evaluating CEOP model performance in semi-arid region of China

“…Comparison between CEOP MOLTS (Model Output Location Time Series) and the in situ observations has been conducted with the goal of improving representations of the key physical processes in the model [4][5][6][7]. Studies have shown that most climate models underestimate the variation of daily temperature and have poor ability in simulating precipitation (namely, with high systematic biases), and that model simulation biases change with the underlying surface, with the largest bias in the tropical oceans [8][9][10][11]. As for the dry period at the Rondonia CEOP reference site in Brazil, the CPTEC (Centro de Previsão de Tempo e Estudos Climáticos) model always overestimates precipitation, while the meso-scale Eta Model always overestimates near-surface temperature [12].…”