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Chee-Kiat Teo and Tieh-Yong Koh

Abstract

A statistical method to correct for the limb effect in off-nadir Atmospheric Infrared Sounder (AIRS) channel radiances is described, using the channel radiance itself and principal components (PCs) of the other channel radiances to account for the multicollinearity. A method of selecting an optimal set of predictors is proposed and demonstrated for one- and two-PC predictors. Validation results with a subset of AIRS channels in the spectral region 649–2664 cm−1 show that the mean nadir-corrected brightness temperature (BT) is largely independent of scan angle. More than 66% of the channels have a root-mean-square (rms) bias less than 0.10 K after nadir correction. Limb effect on the standard deviation (SD) of BT is discernible at larger scan angles, mainly for the atmospheric windows and the water vapor channels around 6.7 μm. After nadir correction, nearly all atmospheric window channels unaffected by solar glint and more than 76% of water vapor channels examined have BT SDs brought closer to nadir values. For the window channels affected by solar glint (wavenumber > 2490 cm−1), BT SDs at the scan angles with the strongest impact from solar reflection were improved on average by more than 0.6 K after nadir correction.

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Tieh-Yong Koh and Chee-Kiat Teo

The current weather observation network in Southeast Asia is unable to support the accurate monitoring and prediction of the region's predominantly convective weather. Establishing a multisensor mesoscale observation network comprising automated in situ instruments and atmospheric remote sensors (including weather radar) over land and exploiting weather satellite data especially over the sea would significantly improve the quantity and quality of data and benefit numerical weather prediction and tropical atmospheric science research. Several technical and organizational challenges need to be overcome in order to attain this goal. It is hoped that this article would motivate closer regional coordination in plans for developing infrastructure for atmospheric observations for weather research and forecasts in Southeast Asia.

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Chee-Kiat Teo, Tieh-Yong Koh, Jeff Chun-Fung Lo, and Bhuwan Chandra Bhatt

Abstract

Principal component analysis (PCA) is able to diagnose the diurnal rain cycle in the Maritime Continent into two modes that explain most of the diurnal variability in the region. The first mode results from the differential variation in potential instability forced by surface heat flux, insolation, and longwave radiative cooling on land and sea. The second mode is associated with intrinsic mesoscale dynamics of convective systems and its interactions with gravity waves, density currents, and local circulations in coastal regions or mountainous terrain. The spatial phase relation between the two modes determines whether a diurnal signal is propagating or stationary. Thus, validating model simulations of diurnal rainfall using PCA provides insights on the representation of dynamics and physics. In this paper, the main modes of diurnal rain variability in the Maritime Continent from satellite observations are studied and are compared with those from Weather Research and Forecasting (WRF) model simulations. Hovmoeller analyses of the reconstructed rainfall from the first two PCA modes clarify the impact of coastlines and mountains as sources of propagating signals. Wave cavities are identified in the Straits of Malacca, Malay Peninsula, and north Sumatra where stationary signals are produced. WRF reproduces the first two modes but each with a phase lead of about 1–2 h or longer, depending on the satellite rainfall product used for comparison. The basic diurnal forcing in the model seems to be too strong and the model responds too strongly to small islands and small-scale topography. The phase speed of propagating signals over open sea is correctly modeled but that over land is too slow.

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