Multispectral satellite training for inexperienced Navy forecasters

Recent advancements of meteorology and oceanography (METOC) satellite products has resulted from a surge in computing resources and expanded communications via the Internet. Greater tactical demands in military operations are placed on Navy and Marine METOC personnel to provide better atmospheric depictions and forecasts in support of helicopter, fighter jet and ground troop operations, as was experienced in Operation Enduring Freedom and Operation Iraqi Freedom. Unfortunately, US military weather forecasters are often limited in their abilities to provide state of the art products and forecasts. One reason for these inefficiencies are that oftentimes, daily forecasting tasks are left to non-commissioned personnel (e.g., AG’s and ET’s) who receive little or no classroom training in this area, nor are there continuing education/training available. METOC forecast centers vary greatly and might not have access to the appropriate information base to answer ongoing questions. Additionally, the typical tour of duty at a particular forecast center is 2 years, resulting in a stressful environment to bring new forecasters up to speed in demanding forecast operations. The result is that the user is often confined to image looping and basic image enhancements to convey the general environmental conditions over the region of interest. To facilitate the learning process, the Naval Research Laboratory and the Naval Postgraduate School have developed a 3 day intensive laboratory and lecture course in satellite remote sensing, focusing on topics vital to military operations such as smoke and fire detection, coastal maritime layer analysis, snow, fog, haze, tropical cyclones, hazardous wind conditions, etc. A wealth of satellite data is provided from MODIS, AVHRR, DMSP and Geostationary satellite data. Background satellite remote sensing topics such as radiative transfer theory is also presented. This report presents a sample of the material used within the training.