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Accurate, timely, and accessible meteorological and soil moisture measurements are essential for a number of applications including weather forecasting, agricultural decision-making, and flood and drought prediction. Such data are becoming increasingly available globally, but the large number of networks and various data reporting formats often make utilization of such data difficult. The TexMesonet is a "network of networks" developed within the state of Texas to collect, process, and make public data collected from more than 1700 monitoring stations throughout the state. This paper describes the TexMesonet, with special attention paid to monitoring sites installed and managed by the Texas Water Development Board. It also provides a case study exemplifying how these data may be used and gives recommendations for future data applications. [ABSTRACT FROM AUTHOR]

Carbon flux phenology is widely used to understand carbon flux dynamics and surface exchange processes. Vegetation phenology has been widely evaluated by remote sensors; however, very few studies have evaluated the use of vegetation phenology for identifying carbon flux phenology. Currently available techniques to derive net ecosystem exchange (NEE) from a satellite image use a single generic modeling subgroup for agricultural crops. But, carbon flux phenological processes vary highly with crop types and land management practices; this paper reexamines this assumption. presented here are an evaluation of ground-truth remotely sensed vegetation indices with in situ NEE measurements and an identification of vegetation indices for estimating carbon flux phenology metrics by crop type. Results show that the performance of different vegetation indices as an indicator of phenology varies with crop type, particularly when identifying the start of a season and the peak of a season. Maize fields require vegetation indices that make use of the near-infrared and red reflectance bands, while soybean fields require those making use of the shortwave infrared (IR) and near-IR bands. In summary, the study identifies how to best utilize remote sensing technology as a crop-specific measurement tool. [ABSTRACT FROM AUTHOR]

Established as a social companion to the Oklahoma Mesonet, the Oklahoma Meso-Scale Integrated Socio-Geographic Network (M-SISNet) is a network of approximately 1500 'social monitoring stations' (geolocated households) across the state of Oklahoma that provide data on household perceptions and responses to signals that are sent from agricultural, hydrological, and meteorological systems. This paper outlines the purpose and nature of the M-SISNet, with specific focus on the sample frame, protocols for recruitment, retention, and survey implementation. It concludes with example survey questions, analyses, and directions for accessing the data. [ABSTRACT FROM AUTHOR]

A wide range of environmental applications would benefit from a dense network of air temperature observations. However, with limitations of costs, existing siting guidelines, and risk of damage, new methods are required to gain a high-resolution understanding of spatiotemporal patterns of temperature for agricultural and urban meteorological phenomena such as the urban heat island. With the launch of a new generation of low-cost sensors, it is possible to deploy a network to monitor air temperature at finer spatial resolutions. This study investigates the Aginova Sentinel Micro (ASM) sensor with a custom radiation shield (together less than USD$150) that can provide secure near-real-time air temperature data to a server utilizing existing (or user deployed) Wi-Fi networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors <±0.22°C between −25° and 30°C, with a time constant in ambient air of 110 ±15 s. Subsequent field tests also showed the ASM (in the custom shield) had excellent performance (RMSE = 0.13°C) over a range of meteorological conditions relative to a traceable operational Met Office platinum resistance thermometer. These results indicate that the ASM and radiation shield are more than fit for purpose for dense network deployment in environmental monitoring applications at relatively low cost compared to existing observation techniques. [ABSTRACT FROM AUTHOR]

Surface soil moisture plays an important role in the dynamics of land–atmosphere interactions and many current and upcoming models and satellite sensors. In situ data will be required to provide calibration and validation datasets. Therefore, there is a need for sensor networks at a variety of scales that provide near-real-time soil moisture and temperature data combined with other climate information for use in natural resource planning, drought assessment, water resource management, and resource inventory. The U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS)–National Water and Climate Center has established a continental-scale network to address this need, called the Soil Climate Analysis Network (SCAN). This ever-growing network has more than 116 stations located in 39 states, most of which have been installed since 1999. The stations are remotely located and collect hourly atmospheric, soil moisture, and soil temperature data that are available to the public online in near–real time. New stations are located on benchmark soils when possible. Future plans for the network include increasing the number of stations, improving on user-friendly data summaries, increasing data quality, and scaling the stations to the surrounding region. [ABSTRACT FROM AUTHOR]

Because Atlanta, Georgia, is a model of rapid transition from forest/agriculture land use to urbanization, NASA and other agencies have initiated programs to identify and understand how urban heat islands (UHIs) impact the environment in terms of land use, air quality, health, climate, and other factors. Atlanta's UHI may also impact the regional water cycle by inadvertent forcing of precipitating cloud systems. Yet, a focused assessment of the role of urban-induced rainfall in Atlanta has not been a primary focus of past efforts. Several observational and climatological studies have theorized that UHIs can have a significant influence on mesoscale circulations and resulting convection. Using spaceborne rain radar and a limited network of irregularly spaced, ground-based rain gauges, evidence that the Atlanta and Houston, Dallas, and San Antonio, Texas, urban areas may modify cloud and precipitation development was recently found. To validate these recent satellite-based findings, it was determined that a higher density of rainfall gauges would be required for future work. The NASA-sponsored Study of Precipitation Anomalies from Widespread Urban Landuse (SPRAWL) seeks to further address the impact of urban Atlanta on precipitation variability by implementing a dense rain gauge network to validate spaceborne rainfall estimates. To optimize gauge location to a given set of criteria, a geographical information system (GIS) aided by a spatial decision support system (DSS) has been developed. A multicriteria decision analysis (MCDA) technique was developed to locate optimal sites in accordance to the guidelines defined by the World Meteorological Organization (WMO). A multicriteria analysis model for the optimization of prospective sites was applied to identify prime locations for the tipping-bucket rain gauges. The MCDA design required development of a spatial model by applying a series of linear programming methods, with the aid of spatial analytical techniques, in order to identify land sites that meet a particular set of criteria. [ABSTRACT FROM AUTHOR]