6.5 High-Resolution Weather Observations for Improved Mesoscale Predictions

Wednesday, 9 January 2013: 11:30 AM
Room 15 (Austin Convention Center)
David A. Robinson, Rutgers University, Piscataway, NJ; and D. J. Leathers

The offices of the New Jersey and Delaware state climatologists operate mesonet weather networks that generate real-time, high-quality spatial and temporal data and value-added weather and climate related products. This information regarding atmospheric and surface conditions is valuable to the weather forecasting community, as well as to many other constituents in our states. Recently, our two offices have unified a number of our mesonet operations into a “Mid Atlantic Mesonet Consortium”, and through the Consortium we are actively contributing to the national "MesoUS" effort supported by the National Weather Service through Global Science and Technology, Inc.

The Delaware Environmental Observation System and the New Jersey Weather and Climate Network are state-of-the-art environmental observing systems dedicated to providing immediate information about environmental conditions and to archive data for historical environmental studies and research. Among the variables observed at five-minute increments from approximately 100 automated stations operated by our offices are air temperature, precipitation, humidity, wind speed and direction, barometric pressure, incoming solar radiation, soil moisture and temperature and snowfall (note, not all variables are observed at every station). Generated products include evapotranspiration, wind chill, heat index, and various growing, cooling and heating degree day indices.

It has become increasingly recognized that the availability of high-density, quality weather information is critical to generating accurate weather forecasts. This is certainly the case in our region with its diverse coastal, estuarine, agricultural, forested, suburban and urban landscapes, often closely located or co-located. Accurate forecasts in this densely populated region can save lives and protect and manage critical utilities and infrastructure during episodes of heat, flooding and air pollution. In this presentation we will provide examples of the highly varying weather conditions that are critical to recognize and interpret when making informed decisions and forecasts. This includes localized heavy rainfall, sea breeze fronts (including in urban locations), sharp snowfall gradients, and urban heat characteristics, to name a few. Specialized analysis systems made possible by the networks will also be discussed such as operational irrigation scheduling and coastal flood monitoring systems. This will include demonstrating the added value of having a dense network of observations compared to more sparsely distributed spatial and temporal coverages.

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