Mesoscale in situ meteorological observations are essential for better understanding and forecasting the weather and climate and to aid in decision-making by a myriad of stakeholder communities. They include, for example, state environmental and emergency management agencies, the commercial sector, media, agriculture, and the general public. Over the last three decades, a number of mesoscale weather and climate observation networks have become operational. These networks are known as mesonets. Most are operated by universities and receive different levels of funding. It is important to communicate the current status and critical roles the mesonets play. Most mesonets collect standard meteorological data and in many cases ancillary near-surface data within both soil and water bodies. Observations are made by a relatively spatially dense array of stations, mostly at subhourly time scales. Data are relayed via various means of communication to mesonet offices, with derived products typically distributed in tabular, graph, and map formats in near–real time via the World Wide Web. Observed data and detailed metadata are also carefully archived. To ensure the highest-quality data, mesonets conduct regular testing and calibration of instruments and field technicians make site visits based on “maintenance tickets” and prescheduled frequencies. Most mesonets have developed close partnerships with a variety of local, state, and federal-level entities. The overall goal is to continue to maintain these networks for high-quality meteorological and climatological data collection, distribution, and decision-support tool development for the public good, education, and research.

While sharing many common qualities in design and operation, mesonets across the United States were established independently and organically over the last several decades. In numerous instances, the unique ways each network matured and developed new protocols has led to important lessons learned. These experiences have been shared in informal ways amongst various network operators over the years to promote reliable operation. As existing networks begin to introduce new sensors and technologies, and as new networks come online, there is a common need for guidance on best practices. This paper aims to formally provide recommendations to improve and harmonize the various aspects of operating a mesonet, including siting, sensors, maintenance, quality assurance, and data processing.

An enhanced knowledge of the feedbacks from land surface changes on regional climates is of great importance in the attribution of climate change. To explore the effects of deforestation on a midlatitude climate regime, two sets of two five-member ensembles of 28-day simulations were conducted using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) coupled to the "Noah" land surface model. The four ensembles represented conditions in summer (August) and winter (February) across the northern mid-Atlantic United States before and after extensive late-nineteenth-century logging of hardwood forests in central and northern Pennsylvania. Prelogging ensembles prescribed a vegetative cover of an evergreen needleleaf forest; postlogging ensembles prescribed sparse vegetation and bare soil to simulate clear-cut deforestation. The results of the MM5 experiments showed a decided seasonality in the response of the land surface-atmosphere system to deforestation, with much stronger effects arising in summer. In August, deforestation caused a repartitioning of the surface energy budget, beginning with a decrease in the latent heat flux of more than 60 W m Ϫ2 across the land cover-forcing area, representing almost one-half of the latent heat flux under prelogging land cover. Concomitant with this decrease in evapotranspiration, mean 2-m air temperatures warmed by at least 1.5°C. Increases in sensible heat flux led to a 150-m mean increase in the height of the atmospheric boundary layer over the deforested area. Low-level atmospheric mixing ratios and total precipitation decreased under clear-cut conditions. Mean soil moisture increased in all model levels to 150 cm because of a decrease in vegetative uptake of water, except at the 5-cm level at which such decreases were effectively balanced by greater soil evaporation and less precipitation. A strong diurnal variation in the response to deforestation of ground and lower-atmosphere temperatures and heat fluxes was also identified for the summer season. The February simulations showed the effects of deforestation during low-insolation months to be small and variable. The strong response of the summer land surface-atmosphere system to deforestation shown here suggests that land cover changes can appreciably affect regional climates. Thus, the role of human-induced and naturally occurring land cover variability should not be ignored in the attribution of climate change.

Extreme precipitation events are arguably one of the most important natural hazards in many areas of the globe, impacting nearly every societal sector. In the Northeastern United States, extreme precipitation events have been shown to be increasing with several recent events garnering national attention (i.e., Ellicott City Maryland 2018; Tropical Storm Lee 2011). The NOAA Atlas 14 product is the nation's standard for estimating the magnitude and frequency of site‐specific extreme precipitation events, containing both precipitation frequency estimates, as well as associated confidence intervals. The Atlas uses surface stations, primarily from the National Weather Service Cooperative Observer Program, and statistical methodologies to provide point‐based precipitation exceedance probability estimates for several durations and potential recurrence intervals. Unfortunately, the number and quality of Cooperative Observer sites varies greatly over space and time. This research compares observed precipitation extremes from a high‐resolution statewide mesonet to those estimated by the Atlas 14 product for a 10‐year recurrence interval at several precipitation durations. Results of the analysis indicate that Atlas 14 underestimates the number and magnitude of extreme precipitation events across the state of Delaware at longer event durations (360‐ to 1,440‐min). At shorter durations (5‐ to 240‐min) the Atlas 14 estimates are more closely aligned with the observations from the high‐resolution precipitation network. These results suggest that caution should be exercised when using Atlas 14 estimates for engineering standards and hydrologic studies, especially for longer duration events. Therefore, a more rapid update cycle for revision of the Atlas 14 product should be considered, as a changing climate regime may be responsible for the differences identified in this research.

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