Abstract

Since the Oklahoma Mesonet (the state’s automated mesoscale weather station network) was established in 1994, it has served a number of diverse groups and provided public services to foster weather preparedness, education, and public safety, while also supporting decision-making in agricultural production and wildland fire management.

With 121 monitoring stations across the state, the Oklahoma Mesonet has developed an array of technologies to observe a variety of atmospheric and soil variables in 5- to 30-min intervals. These consistent observations have been especially critical for predicting and preparing for extreme weather events like droughts, floods, ice storms, and severe convective storms as well as for development of value-added tools. The tools, outreach programs, and mesoscale data have been widely utilized by the general public, state decision-makers, public safety officials, K–12 community, agricultural sector, and researchers, thus generating wide societal and economic benefits to many groups.

Based on practical application examples of weather information provided by the Oklahoma Mesonet, this paper analyzes both benefits generated by Oklahoma Mesonet information to the public and decision-makers and ripple effects (spreading amplified outcomes/implications) of those benefits in the short and long term. The paper further details ongoing and anticipated Oklahoma Mesonet innovations as a response to changing needs for weather-related information over time, especially as a result of technological developments and weather variability.

1. Introduction: Importance of weather monitoring for decision-making and education

Weather knowledge and monitoring has always been a critical factor for human survival and resource (water, food, energy) security. In recent history, hurricanes, tornadoes, dust storms (e.g., the Dust Bowl in the U.S. Great Plains in the 1930s), and extreme and exceptional droughts considerably impacted social and economic welfare in many U.S. regions. Accordingly, weather predictions, preparedness, and emergency management became tightly connected to weather monitoring in the twentieth century. The paradigm of weather information use has also changed over time. In the past, weather monitoring was mainly utilized to better and more accurately inform about current and anticipated weather conditions and anomalies to prevent weather-related losses. More recently, its use has been expanded and integrated into many diverse sectors.

More importantly, timely availability of precise, accurate, and updated mesoscale weather information is critical for decision-making and business operations in agriculture, event management, thunderstorm prediction, establishment of early warning systems, and weather forecasting for aviation, marine, and wildland fire management (Mueller et al. 1993; Rao et al. 2011). Mesoscale weather monitoring has been documented to provide critical information in various sectors including public safety (Piercefield et al. 2011; Morris et al. 2002), public utilities (Kim et al. 2012), transportation [National Research Council (NRC) 2004], aviation services and military operations (Ghirardelli and Glahn 2010), wildfire risk and agricultural production (Reid et al. 2010; Johansson et al. 2015; Lin et al. 2013), engineering (Liu et al. 2007), human health (Kunkel et al. 1999), and air quality (Morris et al. 2001). These previous studies constitute only a selection of sectors relying on weather information for a wide range of decision-making processes impacting economic growth and human well-being. Over the past decades, the need for accurate and timely information has become increasingly important and is anticipated to increase even more in the future, especially in times of extreme weather events.

In response to the growing demand for reliable weather observations, the first automated weather monitoring technologies were developed as early as the 1970s (Brock and Govind 1977; Brock et al. 1986) and set the stage for the establishment of regional and statewide mesoscale networks like the Oklahoma Mesonet discussed in this paper.

As of 2016, the Oklahoma Mesonet (hereinafter referred to as Mesonet) consisted of 121 stations (Fig. 1) collecting data on air temperature, relative humidity, pressure, wind speed, and solar radiation every 5 min as well as soil temperature every 15 min and soil moisture measurements every 30 min.

The data collected at each weather station are transferred to the Mesonet operations center at the National Weather Center (NWC) via radio frequency (RF) and cellular (Fig. 2).

The uniqueness of the Mesonet is evidenced by its high data accuracy and quality, wide scope and range of weather variables collected, and data consistency and completeness. The Mesonet maintains near-complete records (>99.5%) of data collected (Fiebrich et al. 2006b). The accuracy and reliability of Mesonet data stem from the fact that the collected data are characterized by 1) high temporal resolution (5 min) and 2) high spatial resolution (~30 km) of observations over a large area. The high data accuracy has also been validated by three micronets1 operated by the Mesonet (Basara et al. 2011; McPherson et al. 2007; Brock et al. 1995). Moreover, the Mesonet stations collect different types of variables (e.g., atmospheric, hydrologic, agricultural), allowing for accurate comparisons of data without a need for interpolations or assumptions, which would otherwise be needed. Furthermore, the data are collected at industry standard heights/depths, requiring no vertical interpolation of the variables. Additionally, past datasets are continually analyzed for potential issues (e.g., sensor drift), thus ensuring a constant validation of high data quality (Shafer et al. 2000).

While the importance of weather monitoring in general and the weather information provided by the Mesonet has been emphasized in many studies (Gu et al. 2008; Swenson et al. 2008; Brotzge and Crawford 2000), a comprehensive analysis is still missing that delineates benefits and beneficiary groups of the Mesonet from the macroeconomic perspective. This paper aims to fill this gap. While this study does not necessarily quantify those benefits, it provides a discussion on 1) the variety of products and tools developed by the Mesonet, 2) direct and indirect benefits generated by the network at the state, national, and international scales, 3) beneficiary groups, and 4) ripple effects of those benefits in the short and long term.

Ripple effects are defined in this paper as constantly occurring and spreading outcomes/implications of the benefits generated by Mesonet weather information and value-added products that are amplified on the temporal scale and across different beneficiary groups. Ripple effects can occur on the economic, environmental, and social level, while they can also induce each other, thus creating further indirect ripple effects in the mid- and long term. While some ripple effects can be easily classified and distinguished, in many cases economic and social ripple effects may overlap in terms of their impacts. This paper aims at identifying and specifying ripple effects resulting from the Mesonet weather information and decision-support tools. However, it does not intend to distinctly discuss direct and indirect ripple effects, unless their boundaries are straightforward and clearly identifiable.

This research and a holistic perspective on economic and societal benefits of weather information provided by the Mesonet will help create a scientific basis for future quantitative evaluations of the respective Mesonet tools and products developed for individual users, decision-makers, and stakeholder groups.

2. History of the Mesonet in the national context

From the late seventeenth century through the mid-twentieth century, weather observations across the United States were largely collected by human observers (Fiebrich 2009). With the introduction of microprocessors in the 1970s, the development and use of automated weather stations across the country increased rapidly. As of 2016, at least 28 U.S. states maintained either regional or statewide networks of automated weather stations (Mahmood et al. 2017).

The development of the Mesonet was triggered by several factors, with the disastrous 1984 Memorial Day flood in Tulsa as a pivotal point in this process. This single event caused the death of 14 people and damage of $184 million (Meo et al. 2004). The late Kenneth Crawford, meteorologist in charge of the National Weather Service (NWS) for Oklahoma at the time, pinpointed the lack of real-time, county-level observations across Oklahoma, which hindered the forecasting process. By the late 1980s, only 14 weather stations existed across Oklahoma that reported mainly on an hourly basis. In 1989, Crawford became the director of the Oklahoma Climatological Survey (OCS) at the University of Oklahoma and joined forces with Ronald Elliott, a leading agricultural engineer from Oklahoma State University, to continue the pursuit of a statewide mesoscale network that could serve both weather and agricultural needs. Based on experiences of mesoscale networks in California, Nevada, Arizona, Nebraska, and Minnesota, in 1991, Crawford and Elliott acquired funding from the state of Oklahoma for the development of a statewide weather network. The Mesonet was implemented during the years 1992–93 and commissioned in 1994. In a January 2009 report by the NRC, the Mesonet was acknowledged as the “gold standard” for statewide mesoscale surface networks in the country due to its high precision in data collection as well as high geographical and temporal data resolution (NRC 2009). Because of its accuracy and consistency over decades of weather data collection, monitoring, and analyses, the Mesonet has served as a model network for the establishment of other weather monitoring networks across the United States and abroad (Crawford et al. 2005; Schroeder et al. 2005; Mahmood and Foster 2008).

3. Information and services provided by Mesonet as a changing technological paradigm

When the Mesonet first began, its main goal was to deliver near-real-time data from weather stations across Oklahoma. Over time, the process of data collection and delivery has changed significantly. Currently, the Mesonet delivers 5-min data in addition to a wide and diverse range of weather maps, graphs, and value-added products as well as visualization software. The value-added products include specialized decision tools for agriculture, fire and emergency responders, educational purposes, and the general public and are generated by combining two or more data sources to create new products (Fig. 3). The added value of the Mesonet is generated through inclusion of 20+ years of historical and statistical data in many weather products. Examples of historical data include seasonal statistics of days above 37.8°C (100°F) or below freezing, total rainfall for the past 1 h to 365 days, and highest wind gust on a particular day. All data undergo rigorous quality assurance procedures before being archived (Fiebrich et al. 2006a). The Mesonet also stores weather data from many external sources, such as the National Oceanic and Atmospheric Administration (NOAA; Doppler radar, radiosonde data, Cooperative Observer data, and NWS forecasts and advisories) and National Aeronautics and Space Administration (NASA; satellite data), and uses those external datasets to generate new value-added products. With those products, the Mesonet further enhances other agency datasets (e.g., support for NASA satellite measurement ground truthing calibration, NWS forecasts, radar rainfall estimates, and NWS advisories). In recent years, the Mesonet expanded its data presentation and delivery in the face of advancing technological developments, for instance through creation of multidimensional models to visualize annual rainfall totals (Fig. 4).

Real-time data and products are available to the public through the web (www.mesonet.org) and mobile applications (Android and iPhone). Automated data transfer services are available to agencies and for-profit businesses through fee-based subscriptions. Scientists can access and download Mesonet data files for research purposes through online tools or, in the case of funded grants, through special data requests handled by Mesonet staff. Metadata, including latitude, longitude, elevation, seasonal site photos, and quality assurance reports, are also publically available through the Mesonet website.

4. Benefits, beneficiary groups, and ripple effects of Mesonet information

The Mesonet provides tools and products used by a number of groups in the state and beyond. Figure 5 displays a graphical overview of those products, generated benefits (economic, environmental, and social), beneficiary groups, and ripple effects resulting from the application of Mesonet information and data. There is a continuous information exchange and cooperation between Mesonet users and the Mesonet team to provide information to the users in a timely manner, while also collecting feedback about needs from those groups.

a. Farmers, ranchers, and agricultural sector

Since 1890, many farmers and ranchers have been directly involved in the Cooperative Observer Program by collecting and providing weather observations to the NWS on a voluntary basis (NOAA 2014). Since the launch of the Mesonet, agricultural users were among the first customers of the weather information to optimize crop and livestock production, commercial horticulture, food and ornamental crop production, and forestry operations. The agriculture-focused weather information and tools provided by the Mesonet have expanded over time. Currently, they include a wide variety of unique farm and ranch decision-support products in addition to general weather data (Fig. 6).

The Mesonet currently has seven main agricultural decision-support products: 1) a cattle comfort advisor to monitor stress levels of livestock (Mader et al. 2010) and advise producers how to adjust handling, feeding, watering, and wind/sun exposure; 2) degree-day heat unit calculators to help track crop progress through the growing season; 3) a drift risk advisor to indicate ideal times for fertilizer/pesticide applications in order to minimize unnecessary drifts away from the targeted crop; 4) irrigation planners to allow farmers to track water losses from evapotranspiration and monitor soil plant water availability; 5) plant disease pest advisors to allow for more accurate timing of fungicide applications to improve disease control while minimizing environmental impacts; 6) plant insect pest advisors to indicate the need for scouting insect activity risk; and 7) a wheat first hollow stem advisor to monitor the progression and likelihood of reaching first hollow stem in hard red winter wheat. Several of these tools target Oklahoma agriculture commodities with high economic importance including cattle, wheat, corn, and cotton [U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) 2016].

Weather information and decision-support products provided by the Mesonet have been widely utilized by farmers and ranchers through multiple media approaches. In 2016 alone (which can serve as a typical benchmark year), 74 039 Mesonet.org agriculture section visits were recorded, 48 weekly television segments (also uploaded to YouTube) logged 1056 views, while 15 blog articles recorded 4186 reads, in addition to social media posts via Facebook and Twitter. Moreover, the Mesonet organized 16 trade show exhibits with more than 6500 attendees, 15 educational presentations with an estimated audience of 750, and a 2-day extension educator in-service training.

According to Oklahoma Department of Agriculture, Food and Forestry (ODAFF; ODAFF 2015), Oklahoma agriculture generated $40 billion in total economic impact in 2015. With 78 000 farms, Oklahoma agriculture provided 208 974 jobs in 2013. The total output2 in 2013 amounted to $30.1 billion, while the total added value3 equaled $9.5 billion. Given the fact that agriculture is an important sector in Oklahoma’s economy, providing food security and maintaining social well-being, changes in agricultural markets create ripple effects on the sector itself (direct effects), other economic sectors (indirect effects), and human spending behavior and welfare (induced effects). Those changes and implications are magnified by high seasonal and regional weather variability in Oklahoma as well as diversity of agricultural production in the state. Accordingly, in regard to crop production, meteorological drought can induce hydrological and agricultural drought, causing severe reduction in the harvested crop areas, and/or impaired and low-quality yields, which will ultimately reduce the total market supply of agricultural crops. The same effects occur with regard to livestock production through compromised animal health and production output. Given unchanged demand for crops and meat products (and assuming no significant changes to imported quantities), food and feed prices on regional and national markets will consequently rise (Al-Kaisi et al. 2013; Leister et al. 2015). This price increase will affect not only farmers and their production in the years to come, but also a wide range of consumer groups, their welfare, and cost of living (Low et al. 2013). Thus, providing farmers and ranchers with accurate weather information has been useful not only to mitigate negative impacts of weather at the farm/ranch level, but also to prevent unwanted ripple effects on other sectors in the regional and national economy.

b. Drought monitoring

Drought is often considered an unexpected weather hazard based in the climate time scale of weeks to months. Drought monitoring is of vital importance to economic interests of Oklahoma, particularly in the agricultural and wildfire sectors. For instance, droughts of a climatic temporal scale, especially if they occur across at least one crop cycle of wheat, can inflict damages of millions to billions of dollars in value depending on drought duration and severity. The Mesonet provides a unique capability for drought assessment and prediction.

Drought monitoring at the Mesonet began during the short but intense drought of 1995–96 that caused more than $1 billion in damage to crops, livestock, rangelands, and forests as well as to other sectors. This event instigated the formation of the state’s 1997 drought contingency plan and emphasized the importance of updated weather monitoring at the state level (Oklahoma Mesonet 2016). In addition, to respond to public needs on climate monitoring, an online drought monitoring tool was developed by the Mesonet. The tool provided rainfall statistics, such as departure from normal and percentage of normal as well as a number of specific drought indices in real-time and historical context.

The next significant step in drought monitoring occurred in 1999 with the advent of the U.S. Drought Monitor (USDM)—a weekly map of drought conditions produced jointly by NOAA, USDA, and the National Drought Mitigation Center (NDMC) at the University of Nebraska–Lincoln. The USDM is based on multiple indicators combined with local impacts and expert judgments to assess which indicators (often conflicting) are driving the system locally. It is in this role as the “local expert” in which the Mesonet has become crucial to the accurate evaluation of drought across Oklahoma. Mesonet personnel, which are considered the primary state contacts and contributors to the weekly Drought Monitor process, assess local trouble areas through the use of Mesonet data. The data are supported by local impacts from agricultural producers and county-level officials. In a next step, a finalized drought picture for the state is provided to the national Drought Monitor author.

The Drought Monitor assessments have had specific economic benefits. For instance, the USDA’s Farm Service Agency used the Drought Monitor to distribute an estimated $1.64 billion through the Livestock Forage Disaster (LFD) program from 2008 to 2011, $50 million through the Livestock Assistance grant program in 2007, and additional funds through the Nonfat Dry Milk program in 2003 and 2004 (U.S. Drought Monitor 2016). The Internal Revenue Service also uses the Drought Monitor to determine the replacement period for livestock sold because of drought. As part of its response to the 2012 drought, the USDA streamlined the process for secretarial disaster declarations to drought stricken areas, making declarations nearly automatic for a county shown in “severe drought” on the Drought Monitor map for eight consecutive weeks and in “exceptional drought” areas for four weeks.

Similarly, Mesonet data have been an integral part of diagnosing Oklahoma’s drought picture since the beginning of the Drought Monitor effort. It became even more important during the disastrous drought of 2010–15, declared as the worst drought in the state since the 1950s (Fig. 7). Between 2011 and 2014, the LFD program distributed over $833 million to Oklahoma livestock producers (B. Rippey 2014, personal communication). Thus, the Mesonet weather data were once more a critical factor for securing financial aid to agricultural producers in the state.

The direct benefits of drought monitoring provided by the Mesonet for agricultural and ranching operations have been emphasized by the Oklahoma Department of Emergency Management (ODEM) and Oklahoma Water Resources Board [OWRB; ODEM/OWRB 1997]. While drought reduces crop, rangeland, and forest productivity and increases livestock and wildlife mortality rates in the short term, it has economic ripple effects causing reduced income for farmers and agribusiness, increased consumer prices for food and timber, and increased unemployment in the agricultural sector and other sectors delivering production factors to the agricultural sector (Ziolkowska 2016; Combs 2012; Kirby et al. 2014). Furthermore, reduced water supplies for municipal/industrial, agricultural, and power uses could cause a decline in the number and quality of products and services provided by those sectors, causing societal implications and impacting human well-being (Ding et al. 2011). Additional economic ripple effects on the state economy include reduced tax revenues due to curtailed consumer and sectoral expenditures and foreclosures on bank loans to farmers and businesses (Landon-Lane et al. 2009; Wilhite et al. 2007). Environmental ripple effects as a result of drought include increased wildfire hazard as well as damage to fish and wildlife habitats, thus affecting ecosystem services (Banerjee et al. 2013; Van Dijk et al. 2013; Schwantes et al. 2016). Societal ripple effects include reduced tourism and recreational activities (Thomas et al. 2013, 2006), while it needs to be emphasized that there is no sharp boundary between economic and social benefits and ripple effects as they tend to overlap (and are sometimes difficult to separate). The application of Mesonet drought monitoring and prediction allows for mitigating those negative impacts in the short and long term at both the state and local levels.

c. Climate monitoring

For over 100 years, the NOAA Cooperative Observer Program (COOP) has monitored the nation’s climate, relying on human volunteers to manually record daily air temperature and precipitation observations. As the number of COOP observers across the nation decreased from 14 000 in 1958 [U.S. Department of Commerce (DOC) 1960] to 5000–6000 in the 1990s (NRC 1998), long-term Mesonet data became increasingly valuable (Fiebrich and Crawford 2009). As of 2016, the NWS has established ~70 Mesonet stations as part of the official COOP network. This trend shows the expanding utility and benefits of Mesonet data in climate research and in calculations of climate normals (Arguez and Vose 2011). The Mesonet delivers normals at different temporal resolutions, thus providing more precise information compared to other studies (IPCC 2007; Milly et al. 2008).

Climate variability can significantly impact, among others, agricultural production (i.e., selection of cultivated crops and livestock breeding) and energy demands for industrial and household use as well as exacerbate current water scarcity problems (Shadman et al. 2016; Bakker 2012). Those changes in resource allocation and use (especially in the long term) could consequently impact end consumers through increased food and utility prices and thus negatively affect social welfare (Wilhite et al. 2007) and potentially compromise economic growth in the state. Through climate monitoring, the Mesonet provides an essential service and benefit of observing and precisely detecting anthropogenic impacts on the environment and ecosystems both at the geospatial and temporal scale in Oklahoma. Archived Mesonet data and current observations provide consistent and high-quality information for decision-makers and researchers, information that can be utilized for development of research and prediction models, improving understanding of climate variability, advancing public climate education, and supporting development of mitigation and/or adaptation measures for local communities.

d. Public safety

Since 1996, the Mesonet has developed weather data products and tools specifically for Oklahoma’s public safety community through its Oklahoma’s First-Response Information Resource System using Telecommunications (OK-First) program (Morris et al. 2001, 2002). Recognized with the prestigious Harvard University Innovations in American Government Award in 2001, OK-First provides free classes to public safety officials on the use of Mesonet-developed products and tools in emergency preparedness and response. Beneficiaries of the training include, but are not limited to, 1) local, municipal, state, regional, tribal, or federal government agencies; 2) schools (K–12 and universities); and 3) nonprofit disaster relief agencies. Since 1997, more than 260 classes have been offered by the Mesonet at 49 different locations with more than 1250 public safety officials successfully completing OK-First certification or assistant certification training.

The Mesonet provides two primary information tools for public safety officials, including 1) a decision-support web page (Fig. 8) for use during a variety of natural disasters (tornado outbreaks, ice storms, wildfires, flooding, etc.) as well as manmade disasters (the Oklahoma City bombing in 1995, the I-40 bridge collapse in 2002, etc.) and 2) a software package called RadarFirst, which was developed as a value-added tool to address users’ need for reliable, fast, and simple radar visualization (Fig. 9). The direct benefits provided by OK-First through tools and classes create ripple effects by increasing the safety of local communities, raising public awareness, and most importantly saving lives (Morris et al. 2002).

e. Wildland fire management

A number of various fire weather, fire danger, and smoke management tools and models have been developed since the launch of the Mesonet. The Mesonet’s decision-support system dedicated to wildland fire management, formally known as OK-FIRE, was introduced in 2006.

The OK-FIRE program allows fire managers to assess past and current conditions in addition to predictions based on an 84-h numerical forecast model (Joint Fire Science Program 2011). It features important fire weather variables (e.g., relative humidity, wind speed and direction) as well as fire danger variables (e.g., burning index, spread rates) and critical dead fuel moisture conditions (Carlson and Burgan 2003; Carlson et al. 2007). In addition, smoke dispersion conditions are calculated via a dispersion model (Carlson and Arndt 2008).

OK-FIRE benefits fire managers through providing access to a comprehensive suite of real-time products (Fig. 10) as well as training and customer support. Applications include wildfire suppression, prescribed burning, and smoke management. Current users comprise a variety of federal agencies (U.S. Forest Service, Bureau of Indian Affairs, U.S. Fish and Wildlife Service, National Park Service, U.S. Army Corps of Engineers, and Natural Resources Conservation Service), Oklahoma Forestry Services, Oklahoma Department of Wildlife Conservation, The Nature Conservancy, fire departments, emergency managers, cooperative extension educators, and private landowners. To date, the Mesonet’s OK-FIRE program has trained over 1000 users through formal workshops.

The relevance of the Mesonet’s value-added fire products is substantiated by the fact that more than half of Oklahoma’s land consists of wildlands. About 2 million acres of wildlands are typically burned in Oklahoma every year: 10% by wildfire and 90% by prescribed fire (Carlson and Bidwell 2008). During severe fire seasons, however, wildfires can consume many more acres, causing property, animal, and human loss, such as during the November 2005 through September 2006 period when over 16 000 wildfires burned almost 1.5 million acres (Carlson and Bidwell 2008).

While the benefits provided by the Mesonet’s fire products are rather straightforward in the short term, the ripple effects might be generational in scale and extent. Through increased use of prescribed fire, agricultural and other use areas and forests are sustainably managed, which supports biodiversity maintenance in those ecosystems (Yoder et al. 2004; Russell et al. 1999). An additional ripple effect is that wildfires can cause significant long-term losses to forest habitats, thus reducing the forest’s natural absorbing capacity (Hurteau and North 2009). As a result, industrial and manmade greenhouse gas emissions can increase pollution and generate negative externalities, ultimately impacting human well-being (Engel 2013; Butry and Donovan 2008). Thus, through fostering prescribed fire and aiding in wildfire suppression, OK-FIRE creates benefits to prevent economic losses in natural ecosystems, while also contributing to social well-being and welfare.

f. Nowcasting

Because of the climatological maxima for significant tornados, large hail, and damaging winds, Oklahoma presents significant challenges to weather forecasters. Given the life-threatening nature of convective storms in the region, situational awareness regarding the expected location of convective initiation can provide decision-makers with the ability to implement emergency plans proactively.

The Mesonet has served as the primary tool to provide support in this area through nowcasting: accurate and timely weather predictions based on current weather conditions. Mesonet data are queried to identify the surface ingredients necessary and the likely location for storms to occur. The NOAA Storm Prediction Center (SPC), which is charged with forecasting storms and providing a continuum of products from convective outlooks to mesoscale discussions to severe thunderstorm and tornado watches, utilizes Mesonet data directly.

The Mesonet creates a myriad of products that serve as critical tools in the assessment of weather risks. Mesonet data and products help identify regions of moisture convergence and the potential for convective storms, evaluate equivalent potential temperature, determine wind gusts, among others, all of which enhance forecasters’ ability to provide accurate guidance for decision-makers statewide.

Nowcasting users include the NWS forecast offices in Amarillo, Texas; Norman, Oklahoma; Shreveport, Louisiana; and Tulsa, Oklahoma; as well as firms belonging to the nation’s private weather enterprise charged with forecasting for customers with customized needs (wind energy, public utilities, water resources and management, agriculture, public safety, venue and athletic events, outdoor carnivals and fairs, transportation, etc.). Ripple effects of nowcasting include improved public safety, emergency preparedness for outdoor activities, optimized resource use in the process of wind and conventional energy generation, protection of agricultural plantations and livestock, which all help avoid or minimize social and economic weather-related losses (Liu et al. 1996).

Figure 11 depicts a surface mesoscale weather analysis using Mesonet data at 1600 UTC 20 May 2013. The gradient of equivalent potential temperature (°K) and wind speed vectors is plotted. A dryline bulge (Schaefer 1986a,b; Hane et al. 1997) is clearly evident in southwest Oklahoma. On this day, forecasters at the NWS forecast office in Norman used Mesonet data to identify this feature and produced the graphicast shown in Fig. 12. The information provided to forecasters from the Mesonet, combined with other information, allowed for the severe weather threat to be communicated to Oklahoma decision-makers and the public nearly 4 h before tornadic storms developed along and ahead of this feature. Hane et al. (1997) noted that forecasting the location of thunderstorm development along the dryline is very difficult using traditional synoptic-scale surface analysis tools. In their study of severe convection on 26 May 1991, the authors accurately hypothesized that “the current Oklahoma Mesonetwork (Brock et al. 1995) likely would have resolved it had it occurred over Oklahoma” (Hane et al. 1997, p. 250).

g. State and federal agencies

Representatives from several state and federal agencies were part of the planning of the Mesonet in the early 1990s (Shafer et al. 2000). Accordingly, state and federal users of the data have been a core constituency of the Mesonet data consumer base. The primary state agency beneficiaries include the transportation sector and water resource entities, aside from the public safety agencies described in section 4d. The primary federal agency beneficiaries include the National Weather Service, the Army Corps of Engineers, the National Aeronautics and Space Administration, the U.S. Department of Agriculture, and the Department of Energy.

Specific applications of Mesonet observations by state agencies include road treatment decisions for snow and ice (by analyzing Mesonet air temperature data), predictions of vehicle stability danger (by monitoring Mesonet wind speed data), and road maintenance and management procedures. Mesonet reporting of high rain rates can indicate poor visibility for drivers, loss of pavement friction, and potential flooded roadways. Given that 1 258 978 weather-related crashes were reported by the Federal Highway Administration during the 2005–14 period [U.S. Department of Transportation (DOT) 2015], mesoscale weather information can have an invaluable importance in state and federal decisions, saving human lives. Also, the OWRB partnered with the Mesonet to install two additional hydrologic measurements: stream height and groundwater depth in addition to the Mesonet’s soil moisture data. To supplement the Mesonet’s standard observations, Mesonet staff installed a network of stream gauges in some of Oklahoma’s most flood-prone streams in 1995. Additionally, nine Mesonet sites were supplemented with sensors that track real-time groundwater levels, and thus determine the effects of climatic variability on groundwater recharge and storage.

Furthermore, the Mesonet provides a direct feed of data to the NWS offices across the state, including both the River Forecast Center and the local forecast offices. Mesonet rainfall observations are used as input into hydrologic forecast models and decision-making systems for various hydrology monitoring purposes, including river forecasting and flood warning (Kitzmiller et al. 2013). Radar estimates of rainfall have been corrected in many instances using the Mesonet gauge data (Zhang et al. 2011). For instance, the Arkansas Red-Basin River Forecast Center ingests the Mesonet’s rainfall observations into their Multisensor Precipitation Estimator to adjust radar estimates of rainfall. The Norman NWS found that nearly one-third of all storm data severe wind reports archived between September 2012 and September 2015 were recorded by Mesonet stations (Andra 2016). Thus, a ripple benefit of the Mesonet observations is that they have improved the archives of severe weather conditions.

h. Residential and public users

Mesonet data are distributed to the public and residential users via television, the Mesonet’s public website, social media, and newspapers on a daily basis. All major television networks in Oklahoma City and Tulsa subscribe to the Mesonet data feed, and through their subscription have the right to redistribute the data to their viewing audience. Additionally, since 2008, the Mesonet has filmed a segment on the weekly television show SUNUP (http://sunup.okstate.edu/) that focuses on the past week’s Mesonet observations and the upcoming week’s forecasts. The Mesonet also publishes event-driven and monthly press releases, resulting in Mesonet data appearing in the state’s two largest newspapers over 100 times each quarter.

The primary benefits to residential and public users of Mesonet data are in accessing local observations to answer questions about daily rainfall, wind conditions, and temperature. According to Nielsen data (Nielsen 2013), the Oklahoma City television market reached 730 020 homes in 2014 and 526 580 homes in Tulsa. According to Google Analytics data, the Mesonet’s public website recorded over 685 000 users during the calendar year 2015. The average number of monthly users accessing the website was 57 000, while it peaked at 160 000 during statewide severe weather (storms and flooding) in May 2015. The Mesonet also supports a mobile website, an iOS application, and an Android application to deliver data to the general public. Downloads of the two smartphone applications currently exceed 90 000, which shows the degree of public interest in timely, reliable, and accurate weather information.

Social media and print media have also been important avenues for the public and residential users to access the Mesonet data and information. As of 2016, the Mesonet regularly reached 5000–10 000 people through Facebook posts. On occasion, the Mesonet’s Facebook reach exceeds 400 000 readers during significant weather events.

Direct benefits and ripple effects of Mesonet information for the public include increased awareness about upcoming weather events, which can also result in enhanced public safety and improved individual weather decision-making (Golden and Adams 2000; Riebsame et al. 1986), which further leads to amplified social welfare.

i. Energy users

Mesonet observations benefit the energy industry in three distinct ways, as they help to 1) predict electrical load (based on local, real-time weather observations), 2) predict potential for wind and solar energy production, and 3) identify locations where transmission lines may be impacted by freezing rain. Tribble (2003) documented the significance of Mesonet data for determining the relationships between weather and electric load demand as well as for evaluating the impact of local weather on the consumption of electricity by different customers. The author found local temperatures to be the best predictor of load consumption. Moreover, observations of Mesonet solar radiation revealed strong correlations with power load during the fall season for residential consumers.

Furthermore, Hughes et al. (2002) documented the application and use of the Mesonet wind dataset to develop a wind energy resource assessment. The high spatial resolution of Mesonet data enabled the creation of a high-resolution map as well as the estimation of wind power density at many locations across the state (Fig. 13).

Mesonet observations of solar radiation can allow similar assessments for solar energy potential across Oklahoma. The mesoscale observations of solar radiation can be used to describe the spatial and temporal distribution and variation of irradiation across the state, which are essential for the design, site selection, and performance efficiency of solar power systems. Residential solar installers often use the Mesonet’s daily solar radiation maps to inform their customers how many kilowatt-hours of solar potential are available for their location on any given day.

The majority of Oklahoma’s electric transmission lines are above ground and susceptible to ice loading during freezing rain. Mesonet observations of temperature and rainfall are used to identify areas of the state where icing may occur. Once icing occurs, Mesonet wind observations are used to pinpoint locations most likely to suffer damage to overhead utility systems (McManus et al. 2008).

Ripple effects of Mesonet observations for energy users include public preparedness for blackouts, which might be critical for survival of the infirm at homes or in hospitals (Yan et al. 2016; Prezant et al. 2005). As renewables become more integrated in the state energy portfolio (as well as across the United States), Mesonet information can help improve efficiency of energy generation (Sharma et al. 2011; Yang et al. 2003). This ultimately contributes to an improved resource allocation and economic growth in the long term.

j. Education and STEM outreach

Mesonet data have provided a unique resource to the K–12 community across Oklahoma. As such, the Mesonet has actively led training and educational Science, Technology, Engineering, and Mathematics (STEM) outreach through a series of teacher workshops, science fairs, and student camps. The Mesonet teacher workshops originated in 1992 with a National Science Foundation (NSF)-supported EarthStorm workshop (1992–2011) offered to middle school science (and other discipline) teachers with the aim to provide computer-supported meteorology training (McPherson and Crawford 1996). In addition to the EarthStorm workshops, many new STEM-focused workshops were offered by the Mesonet, where 398 teachers and 59 emergency managers from across 28 states participated in professional development and became strong advocates for the Mesonet system in Oklahoma.

In addition to workshops, the Mesonet hosted science fairs between 1993 and 2009, which showcased 1007 projects from 1401 students from 55 schools. The Mesonet Weather Camp was held between 2011 and 2015 for sixth to eighth graders across the United States, with 111 students from 21 states and 59 students from Oklahoma participating in this week-long event. Similarly, the Oklahoma Regents for Higher Education sponsored the Mesonet’s Summer Academy in 2013–16 for 114 high school students from Oklahoma. In total, nine camps were organized within 6 years, with 217 student participants. In addition to educating the younger generation, the Mesonet has provided seminars for the Osher Lifelong Learning Institutes at the University of Oklahoma and Oklahoma State University for audiences in the age group of 55 years and older.

Knowledge generated by the Mesonet has both short- and long-term ripple effects on the entire society. While it helps with increasing awareness about weather events and public safety issues in the short and midterm, it also adds a primary intellectual value and educational benefits for the younger generation. A further ripple benefit is noted by the fact that seven teachers that were part of the Mesonet’s EarthStorm training won Presidential Awards for Excellence in Science Teaching, two teachers received the National Weather Association Education Award, and several teachers acquired new grants based on the weather programs they developed utilizing their skills from the Mesonet workshops.

k. Research applications

In addition to weather data and tools for specific field applications, the consistency, accuracy, and completeness of the Mesonet dataset has generated significant benefits to the scientific community to answer urgent research questions in Oklahoma and beyond state boundaries. Mesonet data have also been widely used to verify and validate other studies addressing soil moisture mapping, satellite ground truthing, and model output verification.

Through 2016, the Mesonet had been utilized and documented in over 700 research studies and peer-reviewed publications and nearly 200 theses and dissertations (Martens et al. 2017). Research studies utilizing Mesonet data cover a wide range of disciplines, including meteorology, agriculture, biology, public health, wildland fire, engineering, and political science. For instance, Haugland and Crawford (2005) and McPherson and Stensrud (2005) used Mesonet data to analyze the impact of Oklahoma’s winter wheat belt on the overlying atmosphere (Lee et al. 2013). Illston et al. (2004) quantified soil moisture variability across Oklahoma at a variety of temporal scales, while Shellberg (1994) and Brotzge and Richardson (2003) investigated the temporal correlation of atmospheric and soil variables. Basara and Crawford (2002) used Mesonet data to quantify the relationship between soil moisture and atmospheric variables throughout the planetary boundary layer. Brotzge (2004) studied the differences in the energy and water budgets across Oklahoma, while Illston and Basara (2003) examined the relationship between short-term droughts and soil moisture conditions in Oklahoma (Swenson et al. 2008).

Mesonet data have also been applied to develop or enhance new technologies and products to validate and improve land surface models used in numerical weather prediction (Sridhar et al. 2002; Marshall et al. 2003; Robock et al. 2003; Nemunaitis et al. 2004), satellite technologies and products (Czajkowski et al. 2000; Anderson et al. 2004; Sun et al. 2004), and radar-derived products (Lu et al. 1996; Pereira Fo. et al. 1998; Young et al. 2000). In addition, studies utilizing Mesonet data helped improve fire prediction capabilities (Carlson et al. 2002, 2007; Krueger et al. 2016) and the characterization of downwelling longwave radiation (Sridhar and Elliott 2002).

Furthermore, Mesonet observations have been used for international field campaigns including Global Energy and Water Exchanges project (GEWEX), Southern Great Plains (SGP)/Soil Moisture Experiments Project (SMEX), the Fall Water Vapor Intensive Observation Period sponsored by the Department of Energy (Richardson et al. 2000), the SGP experiments of 1997 and 1999 sponsored by NASA (Jackson et al. 1999), the International H2O Project sponsored by the National Science Foundation (Weckwerth et al. 2004), the Soil Moisture Experiment of 2003 sponsored by NASA (Cosh et al. 2003), the Joint Urban 2003 sponsored by the Departments of Defense and Homeland Security (Allwine et al. 2004), the Plains Elevated Convection at Night (PECAN) field project (Geerts et al. 2017), and NASA’s Soil Moisture Active-Passive (SMAP) satellite (Piepmeier et al. 2017). The entire archive of Mesonet data has also served research programs of the U.S. Department of Energy and USDA.

Benefits of the Mesonet for research purposes provide an intrinsic contribution and value to improved intellectual property of the entire society. New developments and inventions based on Mesonet data can thus support a broader regional and national societal growth and welfare.

5. Current limitations and future extensions

For years, the Mesonet has been evolving with its products in research, teaching, and outreach to better serve society in the face of increasing weather variability and severity of weather events. Limitations faced by the Mesonet throughout the life span of its operation have been identified based on feedback provided by Mesonet data users and resulted, for the most part, in technological developments. Moreover, generational transition and an emerging need for access to advanced and user-friendly interfaces have determined the approach taken to address the existing limitations. While the Mesonet currently supports a mobile website and two applications for mobile devices, it will increasingly support mobile website design and data delivery. Other anticipated advancements include mirroring data centers and delivery of data and processing into the cloud that will increase uptime and reliability. Also, social media will be utilized to a greater extent to provide younger users with updated weather information and to educate them about the importance of weather monitoring for their personal welfare as well as the economic growth in Oklahoma.

Mesonet weather products will be embedded with georeference in the future, thus allowing for geo-oriented weather representation on all Mesonet applications and all other geocomputer appliances. This will allow users to follow weather changes and patterns in their specific locations, while the Mesonet weather data can be incorporated into existing software and hardware that supports geolocated data, such as mapping software, geographic information systems, and GPS micro devices. Those services will likely be autointegrated into common devices in our homes and cars with functions to provide visual and auditory queues when weather becomes severe.

One of the current limitations of Mesonet’s observations is that they extend only up to 10 m above the ground surface. To mitigate this limitation, in the future Mesonet will expand its measurements into the lower atmosphere, likely through the use of unmanned aerial systems (UAS). UAS have the potential to provide observations of the planetary boundary layer (PBL) up to heights of several kilometers. The NRC (2009) reported that the lack of PBL measurements is a major source of uncertainty in current forecast models. Thus, these new measurements have the potential to impact every sector that benefits from improved weather forecasts.

Furthermore, the application of virtual reality for weather data will become more pronounced in the future, as it is already in use for analyzing radar data. Future advancements in this field will help end users better understand complex weather systems by using 3D interactive visuals.

6. Conclusions

Since 1994, the Mesonet has provided timely and updated weather data and products to support many sectors across the state. This paper delineated products and tools provided by the Mesonet, while it also identified the beneficiaries of this information and the resulting ripple effects for each group as well as the state economy. By means of applied examples, this paper outlined economic, social, and environmental benefits of weather information provided by the Mesonet. It highlighted the contribution of the Mesonet to filling the information gap identified by Thomson et al. (2011) in which stakeholders oftentimes struggle to access the weather data they need for research and decision-making activities.

The availability of timely and high-quality data provided by the Mesonet also creates opportunities for educated and effective decision-making processes and policy design. The application of early warning systems based on information from the Mesonet offers policy makers a cost-effective and efficient means to identify potential risks in advance and enables them to take critical steps to reduce impacts related to severe weather. The identification of high-risk areas enables resources to be mobilized in advance with the aim to mitigate negative impacts and bolster response efforts in the event an impact occurs (Ceccato et al. 2014). While there are many beneficiaries of weather information and products delivered by the Mesonet, the extent of the benefits cannot always be measured with purely economic values, especially with regard to social benefits (e.g., number of lives saved by early warning systems).

The information provided in this paper can be used for future quantitative studies of economic, environmental, and social benefits resulting from application of Mesonet data in the identified sectors and groups discussed here.

Acknowledgments

This material is based on work supported by the National Science Foundation under Grant OIA-1301789. Continued funding for operation of the Oklahoma Mesonet is provided by the taxpayers of the state of Oklahoma. The authors thank Kyle Davis, Michael Klatt, and Ada Shih for their assistance in creating several of the figures in this manuscript.

REFERENCES

REFERENCES
Al-Kaisi
,
M. M.
, and Coauthors
,
2013
:
Drought impact on crop production and the soil environment: 2012 experiences from Iowa
.
J. Soil Water Conserv.
,
68
,
19A
24A
, doi:.
Allwine
,
K. J.
,
M. J.
Leach
,
L. W.
Stockham
,
J. S.
Shinn
,
R. P.
Hosker
,
J. F.
Bowers
, and
J. C.
Pace
,
2004
: Overview of Joint Urban 2003—An atmospheric dispersion study in Oklahoma City. Preprints, Symp. on Planning, Nowcasting, and Forecasting in the Urban Zone, Seattle, WA, Amer. Meteor. Soc., J7.1. [Available online at https://ams.confex.com/ams/84Annual/techprogram/paper_74349.htm.]
Anderson
,
M. C.
,
J. R.
Mecikalski
,
R. D.
Torn
,
J. M.
Norman
,
W. L.
Kustas
, and
J. B.
Basara
,
2004
:
Disaggregation of regional flux estimates using Landsat thermal and visible band imagery
.
J. Hydrometeor.
,
5
,
343
363
, doi:.
Andra
,
D. L.
,
2016
: The role of the Oklahoma Mesonet in decision support services for a weather-ready nation. Preprints, 22nd Conf. on Applied Climatology, Amer. Meteor. Soc., New Orleans, LA, Amer. Meteor. Soc., 3.6. [Available online at https://ams.confex.com/ams/96Annual/webprogram/Paper285750.html.]
Arguez
,
A.
, and
R. S.
Vose
,
2011
:
The definition of the standard WMO climate normal: The key to deriving alternative climate normal
.
Bull. Amer. Meteor. Soc.
,
92
,
699
704
, doi:.
Bakker
,
K.
,
2012
:
Water security: Research challenges and opportunities
.
Science
,
337
,
914
915
, doi:.
Banerjee
,
O.
,
R.
Bark
,
J.
Connor
, and
D.
Neville
,
2013
:
Crossman. An ecosystem services approach to estimating economic losses associated with drought
.
Ecol. Econ.
,
91
,
19
27
, doi:.
Basara
,
J. B.
, and
K. C.
Crawford
,
2002
:
Linear relationships between root-zone soil moisture and atmospheric processes in the planetary boundary layer
.
J. Geophys. Res.
,
107
, doi:.
Basara
,
J. B.
, and Coauthors
,
2011
:
The Oklahoma City micronet
.
Meteor. Appl.
,
18
,
252
261
, doi:.
Brock
,
F. V.
, and
P. K.
Govind
,
1977
:
Portable automated Mesonet in operation
.
J. Appl. Meteor.
,
16
,
299
310
, doi:.
Brock
,
F. V.
,
G. H.
Saum
, and
S. R.
Semmer
,
1986
:
Portable automated Mesonet II
.
J. Atmos. Oceanic Technol.
,
3
,
573
583
, doi:.
Brock
,
F. V.
,
K. C.
Crawford
,
R. L.
Elliott
,
G. W.
Cuperus
,
S. J.
Stadler
,
H. L.
Johnson
, and
M. D.
Eilts
,
1995
:
The Oklahoma Mesonet: A technical overview
.
J. Atmos. Oceanic Technol.
,
12
,
5
19
, doi:.
Brotzge
,
J. A.
,
2004
:
A two-year comparison of the surface energy and water budgets between two OASIS sites 900 km apart
.
J. Hydrometeor.
,
5
,
311
326
, doi:.
Brotzge
,
J. A.
, and
K. C.
Crawford
,
2000
:
Estimating sensible heat flux from the Oklahoma Mesonet
.
J. Appl. Meteor.
,
39
,
102
116
, doi:.
Brotzge
,
J. A.
, and
S. J.
Richardson
,
2003
:
Spatial and temporal correlation among Oklahoma Mesonet and OASIS surface-layer measurements
.
J. Appl. Meteor.
,
42
,
5
19
, doi:.
Butry
,
D.
, and
G.
Donovan
,
2008
:
Protect thy neighbor: Investigating the spatial externalities of community wildfire hazard mitigation
.
For. Sci.
,
54
,
417
428
. [Available online at https://www.treesearch.fs.fed.us/pubs/33131.]
Carlson
,
J. D.
, and
R. E.
Burgan
,
2003
:
Review of user needs in operational fire danger estimation: The Oklahoma example
.
Int. J. Remote Sens.
,
24
,
1601
1620
, doi:.
Carlson
,
J. D.
, and
D. S.
Arndt
,
2008
:
The Oklahoma Dispersion Model: Using the Gaussian plume model as an operational management tool for determining near-surface dispersion conditions across Oklahoma
.
J. Appl. Meteor. Climatol.
,
47
,
462
474
, doi:.
Carlson
,
J. D.
, and
T. G.
Bidwell
,
2008
: OK-FIRE: A new weather-based decision support system for wildland fire managers. OSU Cooperative Extension Service, Leaflet L-326.
Carlson
,
J. D.
,
R. E.
Burgan
,
D. M.
Engle
, and
J. R.
Greenfield
,
2002
:
The Oklahoma Fire Danger Model: An operational tool for mesoscale fire danger rating in Oklahoma
.
Int. J. Wildland Fire
,
11
,
183
191
, doi:.
Carlson
,
J. D.
,
L. S.
Bradshaw
,
R. M.
Nelson
Jr.
,
R. R.
Bensch
, and
R.
Jabrzemski
,
2007
:
Application of the Nelson model to four timelag fuel classes using Oklahoma field observations: Model evaluation and comparison with National Fire Danger Rating System algorithms
.
Int. J. Wildland Fire
,
16
,
204
216
, doi:.
Ceccato
,
P.
,
K.
Fernandes
,
D.
Ruiz
, and
E.
Allis
,
2014
:
Climate and environmental monitoring for decision making
.
Earth Perspect.
,
1
,
16
, doi:.
Combs
,
S.
,
2012
: The impact of the 2011 drought and beyond. Texas Comptroller of Public Accounts Publication 96-1704, 16 pp. [Available online at https://texashistory.unt.edu/ark:/67531/metapth542095/m2/1/high_res_d/txcs-0790.pdf.]
Cosh
,
M. H.
,
T. J.
Jackson
,
P. J.
Starks
,
G. C.
Heathman
, and
R.
Bindlish
,
2003
:
Satellite soil moisture validation using in-situ point sources in the Southern Great Plains during SMEX03
.
Eos, Trans. Amer. Geophys. Union
,
84
,
618
.
Crawford
,
K. C.
,
S.
Pritchett
,
T.
Ross
, and
G.
Essenberg
,
2005
: COOP Modernization: Building NOAA’s environmental real-time observation network. Preprints, 13th Symp. on Meteorological Observations and Instrumentation, Savannah, GA, Amer. Meteor. Soc., KS1.2. [Available online at https://ams.confex.com/ams/15AppClimate/techprogram/paper_94167.htm.]
Czajkowski
,
K. P.
,
S. N.
Goward
,
S. J.
Stadler
, and
A.
Walz
,
2000
:
Thermal remote sensing of near surface environmental variables: Application over the Oklahoma Mesonet
.
Prof. Geogr.
,
52
,
345
357
, doi:.
Ding
,
Y.
,
M.
Hayes
, and
M.
Widhalm
,
2011
:
Measuring economic impacts of drought: A review and discussion
.
Disaster Prev. Manage.
,
20
,
434
446
, doi:.
Engel
,
K. H.
,
2013
:
Perverse incentives: The case of wildfire smoke regulation
.
Ecol. Law Quart.
,
623
,
623
672
, doi:.
Fiebrich
,
C. A.
,
2009
:
History of surface weather observations in the United States
.
Earth Sci. Rev.
,
93
,
77
84
, doi:.
Fiebrich
,
C. A.
, and
K. C.
Crawford
,
2009
:
Automation: A step toward improving the quality of daily temperature data produced by climate observing networks
.
J. Atmos. Oceanic Technol.
,
26
,
1246
1260
, doi:.
Fiebrich
,
C. A.
,
D. L.
Grimsley
,
R. A.
McPherson
, and
K. A.
Kesler
,
2006a
:
The value of routine site visits in managing and maintaining quality data from the Oklahoma Mesonet
.
J. Atmos. Oceanic Technol.
,
23
,
406
416
, doi:.
Fiebrich
,
C. A.
,
D. L.
Grimsley
,
R. A.
McPherson
,
K. A.
Kesler
, and
G. R.
Essenberg
,
2006b
:
The value of routine site visits in managing and maintaining quality data from the Oklahoma Mesonet
.
J. Atmos. Oceanic Technol.
,
23
,
406
416
, doi:.
Geerts
,
B.
, and Coauthors
,
2017
:
The 2015 Plains Elevated Convection At Night field project
.
Bull. Amer. Meteor. Soc.
,
98
,
767
786
, doi:.
Ghirardelli
,
J. D.
, and
B.
Glahn
,
2010
:
The meteorological development laboratory’s aviation weather prediction system
.
Wea. Forecasting
,
25
,
1027
1051
, doi:.
Golden
,
J.
, and
C. R.
Adams
,
2000
:
The tornado problem: Forecast, warning, and response
.
Nat. Hazards Rev.
,
1
,
107
118
, doi:.
Gu
,
Y.
,
E.
Hunt
,
B.
Wardlow
,
J. B.
Basara
,
J. F.
Brown
, and
J. P.
Verdin
,
2008
:
Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data
.
Geophys. Res. Lett.
,
35
,
L22401
, doi:.
Hane
,
C. E.
,
H. B.
Bluestein
,
T. M.
Crawford
,
M. E.
Baldwin
, and
R. M.
Rabin
,
1997
:
Severe thunderstorm development in relation to along-dryline variability: A case study
.
Mon. Wea. Rev.
,
125
,
231
251
, doi:.
Haugland
,
M. J.
, and
K. C.
Crawford
,
2005
:
The diurnal cycle of land–atmosphere interactions across Oklahoma’s winter wheat belt
.
Mon. Wea. Rev.
,
133
,
120
130
, doi:.
Hughes
,
T. W.
,
M.
Shafer
,
T.
Simonsen
,
J.
Traurig
,
N.
Mirsky
,
S. J.
Stadler
, and
P. G.
Earls
,
2002
: Using environmental data to attract development: The Oklahoma Wind Power Assessment Initiative. Preprints, Third Symp. on Environmental Applications, Orlando, FL, Amer. Meteor. Soc., 5.5. [Available online at https://ams.confex.com/ams/annual2002/techprogram/paper_28627.htm.]
Hurteau
,
M.
, and
M.
North
,
2009
:
Fuel treatment effects on tree-based forest carbon storage and emissions under modeled wildfire scenarios
.
Front. Ecol. Environ.
,
7
,
409
414
, doi:.
Illston
,
B. G.
, and
J. B.
Basara
,
2003
:
Analysis of short-term droughts in Oklahoma
.
Eos, Trans. Amer. Geophys. Union
,
84
,
157
161
, doi:.
Illston
,
B. G.
,
J. B.
Basara
, and
K. C.
Crawford
,
2004
:
Seasonal to interannual variations of soil moisture measured in Oklahoma
.
Int. J. Climatol.
,
24
,
1883
1896
, doi:.
IPCC
,
2007
: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.
Jackson
,
T. J.
,
D. M.
Le Vine
,
A. Y.
Hsu
,
A.
Oldak
,
P. J.
Starks
,
C. T.
Swift
,
J. D.
Isham
, and
M.
Haken
,
1999
:
Soil moisture mapping at regional scales using microwave radiometry: The Southern Great Plains Hydrology Experiment
.
IEEE Trans. Geosci. Remote Sens.
,
37
,
2136
2151
, doi:.
Johansson
,
R.
,
E.
Luebehusen
,
B.
Morris
,
H.
Shannon
, and
S.
Meyer
,
2015
:
Monitoring the impacts of weather and climate extremes on global agricultural production
.
Wea. Climate Extremes
,
10
,
65
71
, doi:.
Joint Fire Science Program
,
2011
: OK-FIRE: Weather-based decision support for wildland fire management. Fire Science Brief, No. 127, Joint Fire Science Program, 1–6. [Available online at https://www.firescience.gov/projects/briefs/05-2-1-81_FSBrief127.pdf.]
Kim
,
T.
,
P.
Kenkel
, and
B. W.
Brorsen
,
2012
:
Forecasting hourly peak call volume for a rural electric cooperative call center
.
J. Forecasting
,
31
,
314
329
, doi:.
Kirby
,
M.
,
R.
Bark
,
J.
Connor
,
M. E.
Qureshi
, and
S.
Keyworth
,
2014
:
Sustainable irrigation: How did irrigated agriculture in Australia’s Murray–Darling Basin adapt in the Millennium Drought?
Agric. Water Manage.
,
145
,
154
162
, doi:.
Kitzmiller
,
D.
,
D.
Miller
,
R.
Fulton
, and
F.
Ding
,
2013
:
Radar and multisensory precipitation estimation techniques in National Weather Service hydrologic operations
.
J. Hydrol. Eng.
,
18
,
133
142
, doi:.
Krueger
,
E. S.
,
T. E.
Ochsner
,
J. D.
Carlson
,
D. M.
Engle
,
D.
Twidwell
, and
S. D.
Fuhlendorf
,
2016
:
Concurrent and antecedent soil moisture relate positively or negatively to probability of large wildfires depending on season
.
Int. J. Wildland Fire
,
25
,
657
668
, doi:.
Kunkel
,
K. E.
,
R. A.
Pielke
, and
S. A.
Changnon
,
1999
:
Temporal fluctuations in weather and climate extremes that cause economic and human health impacts: A review
.
Bull. Amer. Meteor. Soc.
,
80
,
1077
1098
, doi:.
Landon-Lane
,
J.
,
H.
Rockoff
, and
R. H.
Steckel
,
2009
: Droughts, floods and financial distress in the United States. NBER Working Paper 15596, 49 pp.
Lee
,
B. H.
,
P.
Kenkel
, and
B.
Wade Brorsen
,
2013
:
Pre-harvest forecasting of county wheat yield and wheat quality using weather information
.
Agric. For. Meteor.
,
168
,
26
35
, doi:.
Leister
,
A.
,
P. L.
Paarlberg
, and
J. G.
Lee
,
2015
:
Dynamic effects of drought on U.S. crop and livestock sectors
.
J. Agric. Appl. Econ.
,
47
,
261
284
, doi:.
Lin
,
B.
,
P.
Stackhouse
,
W.
Sun
,
Y.
Hu
,
Z.
Liu
, and
T. F.
Fan
,
2013
:
Is Oklahoma getting drier?
J. Quant. Spectrosc. Radiat. Transfer
,
122
,
208
213
, doi:.
Liu
,
S.
,
L. E.
Quenemoen
,
J.
Malilay
,
E.
Noji
,
T.
Sinks
, and
J.
Mendlein
,
1996
:
Assessment of a severe-weather warning system and disaster preparedness, Calhoun County, Alabama, 1994
.
Amer. J. Public Health
,
86
,
87
89
, doi:.
Liu
,
X.
,
S. J.
Rees
, and
J. D.
Spitle
,
2007
:
Modeling snow melting on heated pavement surfaces. Part II: Experimental validation
.
Appl. Therm. Eng.
,
27
,
1125
1131
, doi:.
Low
,
P. S.
, and Coauthors
, Eds.,
2013
: White paper I: Economic and social impacts of desertification, land degradation and drought. UNCCD Second Scientific Conference 2013 Rep., 62 pp. [Available online at http://2sc.unccd.int/fileadmin/unccd/upload/documents/WhitePapers/White_Paper_1.pdf.]
Lu
,
Y. Y.
,
R. J.
Doviak
, and
C.
Crisp
,
1996
:
Estimating large-scale vorticity using VAD products and reflectivity
.
J. Atmos. Oceanic Technol.
,
13
,
1129
1138
, doi:.
Mader
,
T. L.
,
L. J.
Johnson
, and
J. B.
Gaughan
,
2010
:
A comprehensive index for assessing environmental stress in animals. 2010
.
J. Anim. Sci.
,
88
,
2153
2165
, doi:.
Mahmood
,
R.
, and
S. A.
Foster
,
2008
:
Mesoscale weather and climate observations in Kentucky for societal benefit
.
Focus Geogr.
,
50
,
32
36
, doi:.
Mahmood
,
R.
, and Coauthors
,
2017
:
Mesonets: Mesoscale weather and climate observations for the United States
.
Bull. Amer. Meteor. Soc.
, doi:, in press.
Marshall
,
C. H.
,
K.
Crawford
,
K.
Mitchell
, and
D.
Stensrud
,
2003
:
The impact of the land surface physics in the operational NCEP Eta model on simulating the diurnal cycle: Evaluation and testing using Oklahoma Mesonet data
.
Wea. Forecasting
,
18
,
748
768
, doi:.
Martens
,
B. V.
,
B. G.
Illston
, and
C. A.
Fiebrich
,
2017
:
The Oklahoma Mesonet: A case study of the diverse state of environmental sensor data citations
.
Data Sci. J.
, in press.
McManus
,
G. D.
, and Coauthors
,
2008
: Development and testing of an ice accumulation algorithm. Preprints, 17th Conf. on Applied Climatology, Whistler, BC, Canada, Amer. Meteor. Soc., 9.5. [Available online at https://ams.confex.com/ams/13MontMet17AP/webprogram/Paper141246.html.]
McPherson
,
R. A.
, and
K. C.
Crawford
,
1996
:
The EARTHSTORM project: Encouraging the use of real-time data from the Oklahoma Mesonet in K-12 classrooms
.
Bull. Amer. Meteor. Soc.
,
77
,
749
761
, doi:.
McPherson
,
R. A.
, and
D. J.
Stensrud
,
2005
:
Influences of a winter wheat belt on the evolution of the boundary layer
.
Mon. Wea. Rev.
,
133
,
2178
2199
, doi:.
McPherson
,
R. A.
, and Coauthors
,
2007
:
Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet
.
J. Atmos. Oceanic Technol.
,
24
,
301
321
, doi:.
Meo
,
M.
,
B.
Ziebro
, and
A.
Patton
,
2004
:
Tulsa turnaround: From disaster to sustainability
.
Nat. Hazards Rev.
,
5
,
1
9
, doi:.
Milly
,
P. C. D.
,
J.
Betancourt
,
M.
Falkenmark
,
R. M.
Hirsch
,
Z. W.
Kundzewicz
,
D. P.
Lettenmaier
, and
R. J.
Stouffer
,
2008
:
Stationarity is dead: Whither water management?
Science
,
319
,
573
574
, doi:.
Morris
,
D. A.
,
K. C.
Crawford
,
K. A.
Kloesel
, and
J. M.
Wolfinbarger
,
2001
:
OK-FIRST: A meteorological information system for public safety
.
Bull. Amer. Meteor. Soc.
,
82
,
1911
1923
, doi:.
Morris
,
D. A.
,
K. C.
Crawford
,
K. A.
Kloesel
, and
G.
Kitch
,
2002
:
OK-FIRST: An example of successful collaboration between the meteorological and emergency response communities on 3 May 1999
.
Wea. Forecasting
,
17
,
567
576
, doi:.
Mueller
,
C. K.
,
J. W.
Wilson
, and
N. A.
Crook
,
1993
:
The utility of sounding and Mesonet data to nowcast thunderstorm initiation
.
Wea. Forecasting
,
8
,
132
146
, doi:.
Nemunaitis
,
K. L.
,
J. B.
Basara
,
B. A.
Cosgrove
,
D.
Lohmann
,
K. E.
Mitchell
, and
P. R.
Houser
,
2004
: Validation of the North American Land Data Assimilation System (NLDAS) using data from Oklahoma Mesonet OASIS sites. Preprints, 18th Conf. on Hydrology, Seattle, WA, Amer. Meteor. Soc., 2.2. [Available online at https://ams.confex.com/ams/84Annual/techprogram/paper_72207.htm.]
Nielsen
,
2013
: Local television market universe estimates. Accessed 11 October 2016. [Available online at http://www.nielsen.com/content/dam/corporate/us/en/docs/solutions/measurement/television/2013-2014-DMA-Ranks.pdf.]
NOAA
,
2014
: What is the Coop program? Accessed 19 September 2016. [Available online at http://www.nws.noaa.gov/om/coop/what-is-coop.html.]
NRC
,
1998
: Future of the National Weather Service Cooperative Observer Network. National Academy Press, 65 pp.
NRC
,
2004
: Where the Weather Meets the Road: A Research Agenda for Improving Road Weather Services. National Academies Press, 174 pp. [Available online at http://www.nap.edu/openbook.php?record_id=10893.]
NRC
,
2009
: Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. National Academy Press, 234 pp.
ODAFF
,
2015
: Oklahoma Agriculture Statistics 2015: Pocket facts. ODAFF, USDA-NASS, OSU Rep., 31 pp. [Available online at https://www.nass.usda.gov/Statistics_by_State/Oklahoma/Publications/Annual_Statistical_Bulletin/ok_pocket_facts_2015.pdf.]
ODEM/OWRB
,
1997
: Oklahoma drought contingency plan. Accessed 30 September 2016. [Available online at http://bradley-ok.us/Water/drought.html.]
Oklahoma Mesonet
,
2016
: Rainfall summaries by climate division. Accessed 30 September 2016. [Available online at http://climate.ok.gov/index.php/drought/last_30_days/drought_wildfire.]
Pereira Fo
,
F.
,
K. C.
Crawford
, and
C. L.
Hartzell
,
1998
:
Improving WSR-88D hourly rainfall estimates
.
Wea. Forecasting
,
13
,
1016
1028
, doi:.
Piercefield
,
E.
,
T.
Wendling
,
P.
Archer
, and
S.
Mallonee
,
2011
:
Winter storm-related injuries in Oklahoma, January 2007
.
J. Saf. Res.
,
42
,
27
32
, doi:.
Piepmeier
,
J. R.
, and Coauthors
,
2017
:
SMAP L-band microwave radiometer: Instrument design and first year on orbit
.
IEEE Trans. Geosci. Remote Sens.
,
55
,
1954
1966
, doi:.
Prezant
,
D. J.
, and Coauthors
,
2005
:
Effects of the August 2003 blackout on the New York City healthcare delivery system: A lesson for disaster preparedness
.
Crit. Care Med.
,
33
,
S96
S101
, doi:.
Rao
,
K. G.
,
G.
Ramakrishna
, and
N. N.
Reddy
,
2011
:
Impact of meso-net observations on short-term prediction of intense weather systems during PRWONAM: Part I—On wind variations
.
J. Atmos. Sol. Terr. Phys.
,
73
,
965
985
, doi:.
Reid
,
A. M.
,
S. D.
Fuhlendorf
, and
J. R.
Weir
,
2010
:
Weather variables affecting Oklahoma wildfires
.
Rangeland Ecol. Manag.
,
63
,
599
603
, doi:.
Richardson
,
S. J.
,
M. E.
Splitt
, and
B. M.
Lesht
,
2000
:
Enhancement of ARM surface meteorological observations during the fall 1996 water vapor intensive observation period
.
J. Atmos. Oceanic Technol.
,
17
,
312
322
, doi:.
Riebsame
,
W. E.
,
M.
Price
,
H. F.
Diaz
, and
T.
Moses
,
1986
:
The social burden of weather and climate hazards
.
Bull. Amer. Meteor. Soc.
,
67
,
1378
1388
, doi:.
Robock
,
A.
, and Coauthors
,
2003
:
Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season
.
J. Geophys. Res.
,
108
,
1
14
, doi:.
Russell
,
K. R.
,
D. H.
Van Lear
, and
D. C.
Guynn
Jr.
,
1999
:
Prescribed fire effects on herpetofauna: Review and management implications
.
Wildl. Soc. Bull.
,
27
,
374
384
. [Available online at http://www.jstor.org/stable/3783904.]
Schaefer
,
J. T.
,
1986a
: The dryline. Mesoscale Meteorology and Forecasting, P. S. Ray, Ed., Amer. Meteor. Soc., 549–572.
Schaefer
,
J. T.
,
1986b
:
Severe thunderstorm forecasting: A historical perspective
.
Wea. Forecasting
,
1
,
164
189
, doi:.
Schroeder
,
J. L.
,
W. S.
Burgett
,
K. B.
Haynie
,
I.
Sonmez
,
D.
Skwira
,
A. L.
Doggett
, and
J. W.
Lipe
,
2005
:
The West Texas Mesonet: A technical overview
.
J. Atmos. Oceanic Technol.
,
22
,
211
222
, doi:.
Schwantes
,
A. M.
,
J. J.
Swenson
, and
R. B.
Jackson
,
2016
:
Quantifying drought-induced tree mortality in the open canopy woodlands of central Texas
.
Remote Sens. Environ.
,
181
,
54
64
, doi:.
Shadman
,
F.
,
S.
Sadeghipour
,
M.
Moghavvemi
, and
R.
Saidur
,
2016
:
Drought and energy security in key ASEAN countries
.
Renewable Sustainable Energy Rev.
,
53
,
50
58
, doi:.
Shafer
,
M. A.
,
C. A.
Fiebrich
,
D.
Arndt
,
S. E.
Fredrickson
, and
T. W.
Hughes
,
2000
:
Quality assurance procedures in the Oklahoma Mesonetwork
.
J. Atmos. Oceanic Technol.
,
17
,
474
494
, doi:.
Sharma
,
N.
,
P.
Sharma
,
D.
Irwin
, and
P.
Shenoy
,
2011
: Predicting solar generation from weather forecasts using machine learning. IEEE SmartGridComm: Second IEEE Int. Conf. on Smart Grid Communications, Brussels, Belgium, IEEE, 528–533.
Shellberg
,
D. J.
,
1994
: Spatial and temporal variation of the earth/atmosphere system across Oklahoma from October 1993 through January 1994. M.S. thesis, School of Meteorology, University of Oklahoma, 77 pp.
Sridhar
,
V.
, and
R. L.
Elliott
,
2002
:
On the development of a simple downwelling longwave radiation scheme
.
Agric. For. Meteor.
,
112
,
237
243
, doi:.
Sridhar
,
V.
,
R. L.
Elliott
,
F.
Chen
, and
J. A.
Brotzge
,
2002
:
Validation of the NOAH-OSU land surface model using surface flux measurements in Oklahoma
.
J. Geophys. Res.
,
107
,
4418
, doi:.
Sun
,
D.
,
R.
Pinker
, and
J. B.
Basara
,
2004
:
Land surface temperature estimation from the next generation Geostationary Operational Environmental Satellite GOES M–Q
.
J. Appl. Meteor.
,
43
,
363
372
, doi:.
Swenson
,
S.
,
J.
Famiglietti
,
J.
Basara
, and
J.
Wahr
,
2008
:
Estimating profile soil moisture and groundwater variations using GRACE and Oklahoma Mesonet soil moisture data
.
Water Resour. Res.
,
44
,
W01413
, doi:.
Thomas
,
D. S. K.
,
O. V.
Wilhelmi
, and
M. J.
Hayes
,
2006
: Disaster reduction, drought, and the mountain resort community. Mountain Resort Planning and Development in an Era of Globalization, T. Clark, T., A. Gill, and R. Hartmann, Eds., Cognizant Communication Corporation, 221–233.
Thomas
,
D. S. K.
,
O. V.
Wilhelmi
,
T. N.
Finnessey
, and
V.
Deheza
,
2013
:
A comprehensive framework for tourism and recreation drought vulnerability reduction
.
Environ. Res. Lett.
,
8
,
044004
, doi:.
Thomson
,
M. C.
,
S. J.
Connor
,
S. E.
Zebiak
, and
M.
Jancloes
,
2011
:
Africa needs climate data to fight disease
.
Nature
,
471
,
440
443
, doi:.
Tribble
,
A.
,
2003
: The relationship between weather variables and electricity demand to improve short-term load forecasting. Ph.D. dissertation, University of Oklahoma, 221 pp.
USDA NASS
,
2016
: USDA’s national agricultural statistics service: Oklahoma Field Office. Accessed 15 December 2016. [Available online at https://www.nass.usda.gov/ok.]
U.S. DOC
,
1960
: The cooperative weather observer. Key to Meteorological Records Doc. 1.11, U.S. Government Printing Office, 116 pp.
U.S. DOT
,
2015
: How do weather events impact roads? Road Weather Management Program, accessed 1 October 2016. [Available online at http://www.ops.fhwa.dot.gov/weather/q1_roadimpact.htm.]
U.S. Drought Monitor
,
2016
: U.S. Drought Monitor background. Accessed 1 October 2016. [Available online at http://droughtmonitor.unl.edu/AboutUSDM/Background.aspx.]
Van Dijk
,
A. I. J. M.
,
H. E.
Beck
,
R. S.
Crosbie
,
R. A. M.
De Jeu
,
Y. Y.
Liu
,
G. M.
Podger
,
B.
Timbal
, and
N. R.
Viney
,
2013
:
The Millennium Drought in southeast Australia (2001–2009): Natural and human causes and implications for water resources, ecosystems, economy, and society
.
Water Resour. Res.
,
49
,
1040
1057
, doi:.
Weckwerth
,
T. M.
, and Coauthors
,
2004
:
An overview of the International H2O Project (IHOP_2002) and some preliminary highlights
.
Bull. Amer. Meteor. Soc.
,
85
,
253
277
, doi:.
Wilhite
,
D. A.
,
M. D.
Svoboda
, and
M. J.
Hayes
,
2007
:
Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness
.
Water Resour. Manage.
,
21
,
763
774
, doi:.
Yan
,
Q.
,
T.
Dokic
, and
M.
Kezunovic
,
2016
: Predicting impact of weather caused blackouts on electricity customers based on risk assessment. Proc. Power and Energy Society General Meeting (PESGM), Boston, MA, IEEE, 1–5, doi:.
Yang
,
H. X.
,
L.
Lu
, and
J.
Burnett
,
2003
:
Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong
.
Renewable Energy
,
28
,
1813
1824
, doi:.
Yoder
,
J.
,
D.
Engle
, and
S.
Fuhlendorf
,
2004
:
Liability, incentives, and prescribed fire for ecosystem management
.
Front. Ecol. Environ
,
2
,
361
366
, doi:.
Young
,
C. B.
,
A. A.
Bradley
,
W. F.
Krajewski
,
A.
Kruger
, and
M. L.
Morrissey
,
2000
:
Evaluating NEXRAD multisensory precipitation estimates for operational hydrologic forecasting
.
J. Hydrometeor.
,
1
,
241
254
, doi:.
Zhang
,
Y.
,
S.
Reed
, and
D.
Kitzmiller
,
2011
:
Effects of retrospective gauge-based readjustment of multisensory precipitation estimates on hydrologic simulations
.
J. Hydrometeor.
,
12
,
429
443
, doi:.
Ziolkowska
,
J. R.
,
2016
:
Socio-economic implications of drought in the agricultural sector and the state economy
.
Economies
,
4
,
19
, doi:.

Footnotes

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

1

Micronet is a mesogamma to microscale network of weather stations spaced closer than a mesoscale network.

2

Output: Market value of goods and services produced.

3

Added value: Residual value after subtracting purchased inputs from the market value of goods/services sold.