Abstract. Much research and speculation exists about the meteorological and climatological impacts of biomass burning in the Maritime Continent (MC) of Indonesia and Malaysia, particularly during El Nino events. However, the MC hosts some of the world's most complicated meteorology, and we wish to understand how tropical phenomena at a range of scales influence observed burning activity. Using Moderate Resolution Imaging Spectroradiometer (MODIS) derived active fire hotspot patterns coupled with aerosol data assimilation products, satellite based precipitation, and meteorological indices, the meteorological context of observed fire prevalence and smoke optical depth in the MC are examined. Relationships of burning and smoke transport to such meteorological and climatic factors as the interannual El Nino-Southern Oscillation (ENSO), El Nino Modoki, Indian Ocean Dipole (IOD), the seasonal migration of the Intertropical Convergence Zone, the 30–90 day Madden Julian Oscillation (MJO), tropical waves, tropical cyclone activity, and diurnal convection were investigated. A conceptual model of how all of the differing meteorological scales affect fire activity is presented. Each island and its internal geography have different sensitivities to these factors which are likely relatable to precipitation patterns and land use practices. At the broadest scales as previously reported, we corroborate ENSO is indeed the largest factor. However, burning is also enhanced by periods of El Nino Modoki. Conversely, IOD influences are unclear. While interannual phenomena correlate to total seasonal burning, the MJO largely controls when visible burning occurs. High frequency phenomena which are poorly constrained in models such as diurnal convection and tropical cyclone activity also have an impact which cannot be ignored. Finally, we emphasize that these phenomena not only influence burning, but also the observability of burning, further complicating our ability to assign reasonable emissions.

Contrary to what is often reported in the literature, tropical cyclone intensity forecast models have improved over the past two decades at a rate that is statistically significant.

2015: Evaluating environmental impacts on tropical cyclone rapid intensification AMERICAN METEOROLOGICAL SOCIETY predictability utilizing statistical models. Wea. Forecasting.

The current version of the Statistical Typhoon Intensity Prediction Scheme (STIPS) used operationally at the Joint Typhoon Warning Center (JTWC) to provide 12-hourly tropical cyclone intensity guidance through day 5 is documented. STIPS is a multiple linear regression model. It was developed using a "perfect prog" assumption and has a statistical-dynamical framework, which utilizes environmental information obtained from Navy Operational Global Analysis and Prediction System (NOGAPS) analyses and the JTWC historical best track for development. NOGAPS forecast fields are used in real time. A separate version of the model (decay-STIPS) is produced that accounts for the effects of landfall by using an empirical inland decay model. Despite their simplicity, STIPS and decay-STIPS produce skillful intensity forecasts through 4 days, based on a 48-storm verification (July 2003-October 2004. Details of this model's development and operational performance are presented.

No abstract