Mesonet

In meteorology (and climatology), a mesonet, portmanteau of mesoscale network, is a network of (typically) automated weather and environmental monitoring stations designed to observe mesoscale meteorological phenomena. Dry lines, squall lines, and sea breezes are examples of phenomena that can be observed by mesonets. Due to the space and time scales associated with mesoscale phenomena, weather stations comprising a mesonet will be spaced closer together and report more frequently than synoptic scale observing networks, such as ASOS. The term mesonet refers to the collective group of these weather stations, and are typically owned and operated by a common entity. Mesonets usually record in situ surface weather observations but some involve other observation platforms, particularly vertical profiles of the planetary boundary layer (PBL). In meteorology (and climatology), a mesonet, portmanteau of mesoscale network, is a network of (typically) automated weather and environmental monitoring stations designed to observe mesoscale meteorological phenomena. Dry lines, squall lines, and sea breezes are examples of phenomena that can be observed by mesonets. Due to the space and time scales associated with mesoscale phenomena, weather stations comprising a mesonet will be spaced closer together and report more frequently than synoptic scale observing networks, such as ASOS. The term mesonet refers to the collective group of these weather stations, and are typically owned and operated by a common entity. Mesonets usually record in situ surface weather observations but some involve other observation platforms, particularly vertical profiles of the planetary boundary layer (PBL). The distinguishing features that classify a network of weather stations as a mesonet are station density and temporal resolution. Depending upon the phenomena meant to be observed, mesonet stations utilize a spatial spacing of 1 to 40 kilometres (0.62 to 24.85 mi) and report conditions every 1 to 15 minutes. Micronets (see microscale and storm scale), such as in metropolitan areas such as Oklahoma City, St. Louis, and Birmingham UK, may be even denser in spatial resolution. Thunderstorms, squall lines, drylines, sea and land breezes, mountain breeze and valley breezes, mountain waves, mesolows and mesohighs, wake lows, mesoscale convective vortices (MCVs), tropical cyclone and extratropical cyclone rainbands, macrobursts, gust fronts and outflow boundaries, heat bursts, urban heat islands, and other mesoscale phenomena can cause weather conditions in a localized area to be significantly different from that dictated by the ambient large-scale conditions. As such, meteorologists need to understand these phenomena in order to improve forecast skill. Observations are critical to understanding the processes by which these phenomena form, evolve, and dissipate. The long-term observing networks (ASOS, AWOS, Coop), however, are too sparse and report too infrequently for mesoscale research. ASOS and AWOS stations are typically spaced 50 to 100 kilometres (31 to 62 mi) apart and report only hourly at many sites. The Cooperative Observer Program (COOP) database consists of only daily reports. 'Mesoscale' weather phenomena occur on spatial scales of tens to hundreds of kilometers and temporal (time) scales of minutes to hours. Thus, an observing network with finer temporal and spatial scales is needed for mesoscale research. This need led to the development of the mesonet. Mesonet data is directly used by humans for decision making, but also boosts the skill of numerical weather prediction and is especially beneficial for short-range mesoscale models. Mesonets, along with remote sensing solutions (data assimilation of weather radar, weather satellites, wind profilers), allow for much greater temporal and spatial resolution in a forecast model. As the atmosphere is a chaotic nonlinear dynamical system (i.e. Butterfly effect), this increase in data increases understanding of initial conditions and boosts model performance. In addition to meteorology and climatology users, transportation departments, energy producers and distributors, other utility interests, and agricultural entities also have a need for fine scale weather information. These organizations operate dozens of mesonets within the US and globally. Environmental, emergency management and public safety, and insurance interests also are heavy users of mesonet information. In many cases, mesonet stations may (by necessity) be located in positions where accurate measurements may be compromised; for instance, this is especially true of the stations built for WeatherBug's network, many of which were located on school buildings. The potential bias that these locations may cause must be accounted for when entering the data into a model, lest the phenomenon of 'garbage in, garbage out' occur. Mesonets were born out of the need to conduct mesoscale research. The nature of this research is such that mesonets, like the phenomena they are meant to observe, are short-lived. Long term research projects and non-research groups, however, have been able to maintain a mesonet for many years. For example, the U.S. Army Dugway Proving Ground in Utah has maintained a mesonet for many decades. The research-based origin of mesonets has led to the characteristic that mesonet stations tend to be modular and portable, able to be moved from one field program to another. Whether the mesonet is temporary or semi-permanent, each weather station is typically independent, drawing power from a battery and solar panels. An on-board computer takes readings from several instruments measuring temperature, humidity, wind speed & direction, and atmospheric pressure, as well as soil temperature and moisture, and other environmental variable deemed important to the mission of the mesonet, solar irradiance being a common non-meteorological parameter. The computer periodically saves these data to memory and transmits the observations to a base station via radio, telephone (wireless or landline), or satellite transmission. Advancements in computer technology and wireless communications in recent decades made possible the collection of mesonet data in real-time. The availability of mesonet data in real-time can be extremely valuable to operational forecasters as they can monitor weather conditions from many points in their forecast area.