Poster Session P1.2 Validation by a new gauge-based daily grid precipitation dataset of daily precipitation climatology over Monsoon Asia simulated by MRI/JMA 20-km-mesh AGCM

Monday, 28 August 2006
Ballroom North (La Fonda on the Plaza)
Akiyo Yatagai, Research Institute for Humanity and Nature, Kyoto, Japan; and P. Xie and A. Kitoh

Handout (1.7 MB)

Using new gauge-based gridded daily precipitation climatology over monsoon Asia (5–60ºN, 65–155ºE) with a grid resolution of 0.05º, we validate the precipitation climatology simulated by a global 20-km resolution atmospheric model of the Meteorological Research Institute of Japan Meteorological Agency. The new gauge-based precipitation climatology explicitly expresses orographic precipitation over the East Asia. The model has the highest resolution of all atmospheric general circulation models currently in use to study global warming. It successfully simulates orographically enhanced precipitation patterns presented in the East Asia climatology (hereafter, EA clim). The model overestimates precipitation averaged over land areas of monsoon Asia, and bias is larger over India and central China. Difference in annual precipitation between the model and EA clim exceeds those between other well-known grid precipitation climatological datasets. EA clim can be used to validate seasonal changes in monsoon precipitation over the domain, including mountainous regions. The 20-km resolution model reproduces seasonal cycles in precipitation over northern China and the Himalayas. However, large biases and seasonal cycle differences occur over India and central and southern China. As the model resolution improves, gridded daily precipitation datasets based on dense rain-gauge networks should be prepared to validate the model results. Some satellite-derived product, for example, TRMM/PR can represent the characteristics of orographic rainfall. However, we still need to validate them before verify model precipitation quantitatively. We have compared area averaged TRMM/PR monthly product (3A25) by using this East Asia analysis dataset, and found that PR3A25 systematically underestimate summertime precipitation.
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