The Need for the Essential Coastal In-Situ Environmental Monitoring System

The state of the mathematical architecture and numerical modeling of coastal environmental systems has advanced greatly over the past decade and is expected to advance even more rapidly in the future. As air, land and water are interactively coupled in the real world, interactively coupled, atmospheric, ocean, coastal ocean and land based models will improve existing environmental forecasts. NOAA, NASA and DOD remote observing systems, are collecting and are expected to collect more, more types, and better data, to be used to improve diagnostic and prognostic modeling. Given these advances, federal agencies, such as NOAA, who provide environmental services to the public should be the direct beneficiary of the expanded remotely sensed data and the improved numerical model output, to improve its' forecasts and expand its' product and service suite. There are compelling, national, regional and local reasons for the most reliable forecasts in and over the Atlantic and Pacific Oceans, the Gulfs of Mexico, Maine and Alaska, the Great Lakes, and in and over the coastal ocean, estuaries and harbor regions of the Nation. The most reliable forecasts are those that take advantage of modern, advanced numerical modeling, observing system data, and data assimilation (DA). It is now possible to predict all environmental state variables in the coastal areas of the Nation. However, the availability and use of global ocean data sets are much farther along in maturity than are the equivalent in-situ observational resources for the coastal oceans and estuaries, in general, with coverage deemed to be marginal according to several prior studies and thus it was determined there is insufficient data to validate let alone drive models and to document climate (Spriggs and Bosart, NRC, 1997; Rotunno and Pietrafesa, BAMS, 1998). Because modeling and observations are dependent on one another to maximize their joint forecast utility, coordinated programs of observations and models are required regionally and locally. Objective analyses could be conducted to determine if these systems are under-sampled and thus, whether or not additional in-situ data would improve forecasts. Needed are DA numerical modeling experiments (retrospectives, hindcasts, observing system simulation experiments, diagnostic modeling) to determine where additional data might be needed to improve forecasts and information product suites. NOAA produces forecasts of phenomena in these areas but lack critical observations for validation and improved forecasting. Additionally, couplings to hydrologic systems, both atmospheric and land-based, are necessary both from monitoring and modeling perspectives. These are all feasible. However, an expanded observing network, in keeping with the Network of Networks NRC Report, is needed. This discussion will present a proposed national framework based on the existing national in-situ network and a proposed way forward.