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The WxChallenge, a project developed at the University of Oklahoma, brings a state-of-the-art, fun, and exciting forecast contest to participants at colleges and universities across North America. The challenge is to forecast the maximum and minimum temperatures, precipitation, and maximum wind speeds for select locations across the United States over a 24-h prediction period. The WxChallenge is open to all undergraduate and graduate students, as well as higher-education faculty, staff, and alumni. Through the use of World Wide Web interfaces accessible by personal computers, tablet computer, and smartphones, the WxChallenge provides a state-of-the-art portal to aid participants in submitting forecasts and alleviate many of the administrative issues (e.g., tracking and scoring) faced by local managers and professors.
Since its inception in 2006, 110 universities have participated in the contest and it has been utilized as part of the curricula for 140 classroom courses at various institutions. The inherently challenging nature of the WxChallenge has encouraged its adoption as an educational tool. As its popularity has grown, professors have seen the utility of the Wx-Challenge as a teaching aid and it has become an instructional resource of many meteorological classes at institutions for higher learning. In addition to evidence of educational impacts, the competition has already begun to leave a cultural and social mark on the meteorological learning experience.
The WxChallenge, a project developed at the University of Oklahoma, brings a state-of-the-art, fun, and exciting forecast contest to participants at colleges and universities across North America. The challenge is to forecast the maximum and minimum temperatures, precipitation, and maximum wind speeds for select locations across the United States over a 24-h prediction period. The WxChallenge is open to all undergraduate and graduate students, as well as higher-education faculty, staff, and alumni. Through the use of World Wide Web interfaces accessible by personal computers, tablet computer, and smartphones, the WxChallenge provides a state-of-the-art portal to aid participants in submitting forecasts and alleviate many of the administrative issues (e.g., tracking and scoring) faced by local managers and professors.
Since its inception in 2006, 110 universities have participated in the contest and it has been utilized as part of the curricula for 140 classroom courses at various institutions. The inherently challenging nature of the WxChallenge has encouraged its adoption as an educational tool. As its popularity has grown, professors have seen the utility of the Wx-Challenge as a teaching aid and it has become an instructional resource of many meteorological classes at institutions for higher learning. In addition to evidence of educational impacts, the competition has already begun to leave a cultural and social mark on the meteorological learning experience.
Abstract
The May 2015 record rainfall that occurred across Oklahoma was the result of a large number of high-intensity rain events. A unique set of observations from gauges in the Oklahoma Mesonet, the NWS Cooperative Observer (COOP) network, the Community Collaborative Rain, Hail and Snow (CoCoRaHS) network, an experimental pit gauge system, and NWS radar was available that covered an area in and around Norman, Oklahoma. This paper documents the performance of the various gauges throughout the course of the month. Key findings are 1) observations from all methods significantly exceeded the 200-yr return interval; 2) a weighing-bucket gauge at ground level recorded amounts up to 4.5% higher than a similarly located ground-level tipping-bucket gauge and up to 8.2% higher than a nearby aboveground tipping-bucket gauge; 3) a manual COOP gauge recorded nearly identical (within 1.2%) observations as compared to an automated tipping-bucket gauge at a collocated Mesonet station; and 4) observations from 26 CoCoRaHS gauges yielded an average rainfall within 1% of the aerially averaged radar rainfall derived from the Multisensor Precipitation Estimator.
Abstract
The May 2015 record rainfall that occurred across Oklahoma was the result of a large number of high-intensity rain events. A unique set of observations from gauges in the Oklahoma Mesonet, the NWS Cooperative Observer (COOP) network, the Community Collaborative Rain, Hail and Snow (CoCoRaHS) network, an experimental pit gauge system, and NWS radar was available that covered an area in and around Norman, Oklahoma. This paper documents the performance of the various gauges throughout the course of the month. Key findings are 1) observations from all methods significantly exceeded the 200-yr return interval; 2) a weighing-bucket gauge at ground level recorded amounts up to 4.5% higher than a similarly located ground-level tipping-bucket gauge and up to 8.2% higher than a nearby aboveground tipping-bucket gauge; 3) a manual COOP gauge recorded nearly identical (within 1.2%) observations as compared to an automated tipping-bucket gauge at a collocated Mesonet station; and 4) observations from 26 CoCoRaHS gauges yielded an average rainfall within 1% of the aerially averaged radar rainfall derived from the Multisensor Precipitation Estimator.
Abstract
Many studies have investigated urban heat island (UHI) intensity for cities around the world, which is normally quantified as the temperature difference between urban location(s) and rural location(s). A few open questions still remain regarding the UHI, such as the spatial distribution of UHI intensity, temporal (including diurnal and seasonal) variation of UHI intensity, and the UHI formation mechanism. A dense network of atmospheric monitoring sites, known as the Oklahoma City (OKC) Micronet (OKCNET), was deployed in 2008 across the OKC metropolitan area. This study analyzes data from OKCNET in 2009 and 2010 to investigate OKC UHI at a subcity spatial scale for the first time. The UHI intensity exhibited large spatial variations over OKC. During both daytime and nighttime, the strongest UHI intensity is mostly confined around the central business district where land surface roughness is the highest in the OKC metropolitan area. These results do not support the roughness warming theory to explain the air temperature UHI in OKC. The UHI intensity of OKC increased prominently around the early evening transition (EET) and stayed at a fairly constant level throughout the night. The physical processes during the EET play a critical role in determining the nocturnal UHI intensity. The near-surface rural temperature inversion strength was a good indicator for nocturnal UHI intensity. As a consequence of the relatively weak near-surface rural inversion, the strongest nocturnal UHI in OKC was less likely to occur in summer. Other meteorological factors (e.g., wind speed and cloud) can affect the stability/depth of the nighttime boundary layer and can thus modulate nocturnal UHI intensity.
Abstract
Many studies have investigated urban heat island (UHI) intensity for cities around the world, which is normally quantified as the temperature difference between urban location(s) and rural location(s). A few open questions still remain regarding the UHI, such as the spatial distribution of UHI intensity, temporal (including diurnal and seasonal) variation of UHI intensity, and the UHI formation mechanism. A dense network of atmospheric monitoring sites, known as the Oklahoma City (OKC) Micronet (OKCNET), was deployed in 2008 across the OKC metropolitan area. This study analyzes data from OKCNET in 2009 and 2010 to investigate OKC UHI at a subcity spatial scale for the first time. The UHI intensity exhibited large spatial variations over OKC. During both daytime and nighttime, the strongest UHI intensity is mostly confined around the central business district where land surface roughness is the highest in the OKC metropolitan area. These results do not support the roughness warming theory to explain the air temperature UHI in OKC. The UHI intensity of OKC increased prominently around the early evening transition (EET) and stayed at a fairly constant level throughout the night. The physical processes during the EET play a critical role in determining the nocturnal UHI intensity. The near-surface rural temperature inversion strength was a good indicator for nocturnal UHI intensity. As a consequence of the relatively weak near-surface rural inversion, the strongest nocturnal UHI in OKC was less likely to occur in summer. Other meteorological factors (e.g., wind speed and cloud) can affect the stability/depth of the nighttime boundary layer and can thus modulate nocturnal UHI intensity.
Abstract
Soil moisture data from the Oklahoma Mesonet are widely used in research efforts spanning many disciplines within Earth sciences. These soil moisture estimates are derived by translating measurements of matric potential into volumetric water content through site- and depth-specific water retention curves. The objective of this research was to increase the accuracy of the Oklahoma Mesonet soil moisture data through improved estimates of the water retention curve parameters. A comprehensive field sampling and laboratory measurement effort was conducted that resulted in new measurements of the percent of sand, silt, and clay; bulk density; and volumetric water content at −33 and −1500 kPa. These inputs were provided to the Rosetta pedotransfer function, and parameters for the water retention curve and hydraulic conductivity functions were obtained. The resulting soil property database, MesoSoil, includes 13 soil physical properties for 545 individual soil layers across 117 Oklahoma Mesonet sites. The root-mean-square difference (RMSD) between the resulting soil moisture estimates and those obtained by direct sampling was reduced from 0.078 to 0.053 cm3 cm−3 by use of the new water retention curve parameters, a 32% improvement. A >0.15 cm3 cm−3 high bias on the dry end was also largely eliminated by using the new parameters. Reanalysis of prior studies that used Oklahoma Mesonet soil moisture data may be warranted given these improvements. No other large-scale soil moisture monitoring network has a comparable published soil property database or has undergone such comprehensive in situ validation.
Abstract
Soil moisture data from the Oklahoma Mesonet are widely used in research efforts spanning many disciplines within Earth sciences. These soil moisture estimates are derived by translating measurements of matric potential into volumetric water content through site- and depth-specific water retention curves. The objective of this research was to increase the accuracy of the Oklahoma Mesonet soil moisture data through improved estimates of the water retention curve parameters. A comprehensive field sampling and laboratory measurement effort was conducted that resulted in new measurements of the percent of sand, silt, and clay; bulk density; and volumetric water content at −33 and −1500 kPa. These inputs were provided to the Rosetta pedotransfer function, and parameters for the water retention curve and hydraulic conductivity functions were obtained. The resulting soil property database, MesoSoil, includes 13 soil physical properties for 545 individual soil layers across 117 Oklahoma Mesonet sites. The root-mean-square difference (RMSD) between the resulting soil moisture estimates and those obtained by direct sampling was reduced from 0.078 to 0.053 cm3 cm−3 by use of the new water retention curve parameters, a 32% improvement. A >0.15 cm3 cm−3 high bias on the dry end was also largely eliminated by using the new parameters. Reanalysis of prior studies that used Oklahoma Mesonet soil moisture data may be warranted given these improvements. No other large-scale soil moisture monitoring network has a comparable published soil property database or has undergone such comprehensive in situ validation.
Atlantic Tropical Depression Five (2007) briefly strengthened into Tropical Storm Erin over the western Gulf of Mexico shortly before making landfall as a tropical depression near Corpus Christi, Texas, on the morning of 16 August 2007. During the overnight hours of 18–19 August 2007, nearly 3 days after landfall, Erin's remnant circulation strengthened over western Oklahoma, where sustained winds near the circulation's center exceeded 18 m s−1 for more than 3 h—the strongest reported during Erin's entire life cycle. Likewise, station pressure values reduced to sea level were lower at several measurement sites on 19 August than those recorded while Erin was classified by the National Hurricane Center as a tropical cyclone. During this period of lowest pressure, Erin developed an eye, an eyewall structure, and spiral bands, as observed by radar.
The reintensification occurred within the domain of multiple observing networks and platforms, which provided rich detail on the near-surface behavior of Erin and embedded processes. Erin's reintensification was not only unique in its magnitude, but also in the breadth of related available observations. This manuscript describes the intensification of Erin over western Oklahoma as observed by the Oklahoma Mesonet (1-min resolution), the Fort Cobb and Little Washita micronets of the U.S. Department of Agriculture Agricultural Research Service Grazinglands Research Laboratory, and the National Weather Service's upper-air, Doppler radar, and surface observing networks.
Atlantic Tropical Depression Five (2007) briefly strengthened into Tropical Storm Erin over the western Gulf of Mexico shortly before making landfall as a tropical depression near Corpus Christi, Texas, on the morning of 16 August 2007. During the overnight hours of 18–19 August 2007, nearly 3 days after landfall, Erin's remnant circulation strengthened over western Oklahoma, where sustained winds near the circulation's center exceeded 18 m s−1 for more than 3 h—the strongest reported during Erin's entire life cycle. Likewise, station pressure values reduced to sea level were lower at several measurement sites on 19 August than those recorded while Erin was classified by the National Hurricane Center as a tropical cyclone. During this period of lowest pressure, Erin developed an eye, an eyewall structure, and spiral bands, as observed by radar.
The reintensification occurred within the domain of multiple observing networks and platforms, which provided rich detail on the near-surface behavior of Erin and embedded processes. Erin's reintensification was not only unique in its magnitude, but also in the breadth of related available observations. This manuscript describes the intensification of Erin over western Oklahoma as observed by the Oklahoma Mesonet (1-min resolution), the Fort Cobb and Little Washita micronets of the U.S. Department of Agriculture Agricultural Research Service Grazinglands Research Laboratory, and the National Weather Service's upper-air, Doppler radar, and surface observing networks.
Abstract
Global “hot spots” for land–atmosphere coupling have been identified through various modeling studies—both local and global in scope. One hot spot that is common to many of these analyses is the U.S. southern Great Plains (SGP). In this study, we perform a mesoscale analysis, enabled by the Oklahoma Mesonet, that bridges the spatial and temporal gaps between preceding local and global analyses of coupling. We focus primarily on east–west variations in seasonal coupling in the context of interannual variability over the period spanning 2000–15. Using North American Regional Reanalysis (NARR)-derived standardized anomalies of convective triggering potential (CTP) and the low-level humidity index (HI), we investigate changes in the covariance of soil moisture and the atmospheric low-level thermodynamic profile during seasonal hydrometeorological extremes. Daily CTP and HI z scores, dependent upon climatology at individual NARR grid points, were computed and compared to in situ soil moisture observations at the nearest mesonet station to provide nearly collocated annual composites over dry and wet soils. Extreme dry and wet year CTP and HI z-score distributions are shown to deviate significantly from climatology and therefore may constitute atmospheric precursors to extreme events. The most extreme rainfall years differ from climatology but also from one another, indicating variability in the strength of land–atmosphere coupling during these years. Overall, the covariance between soil moisture and CTP/HI is much greater during drought years, and coupling appears more consistent. For example, propagation of drought during 2011 occurred under antecedent CTP and HI conditions that were identified by this study as being conducive to positive dry feedbacks demonstrating potential utility of this framework in forecasting regional drought propagation.
Abstract
Global “hot spots” for land–atmosphere coupling have been identified through various modeling studies—both local and global in scope. One hot spot that is common to many of these analyses is the U.S. southern Great Plains (SGP). In this study, we perform a mesoscale analysis, enabled by the Oklahoma Mesonet, that bridges the spatial and temporal gaps between preceding local and global analyses of coupling. We focus primarily on east–west variations in seasonal coupling in the context of interannual variability over the period spanning 2000–15. Using North American Regional Reanalysis (NARR)-derived standardized anomalies of convective triggering potential (CTP) and the low-level humidity index (HI), we investigate changes in the covariance of soil moisture and the atmospheric low-level thermodynamic profile during seasonal hydrometeorological extremes. Daily CTP and HI z scores, dependent upon climatology at individual NARR grid points, were computed and compared to in situ soil moisture observations at the nearest mesonet station to provide nearly collocated annual composites over dry and wet soils. Extreme dry and wet year CTP and HI z-score distributions are shown to deviate significantly from climatology and therefore may constitute atmospheric precursors to extreme events. The most extreme rainfall years differ from climatology but also from one another, indicating variability in the strength of land–atmosphere coupling during these years. Overall, the covariance between soil moisture and CTP/HI is much greater during drought years, and coupling appears more consistent. For example, propagation of drought during 2011 occurred under antecedent CTP and HI conditions that were identified by this study as being conducive to positive dry feedbacks demonstrating potential utility of this framework in forecasting regional drought propagation.
Abstract
Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Understanding the spatial and temporal nature of soil moisture on the mesoscale is vital to determine the influence that land surface processes have on the atmosphere. Recognizing the need for improved in situ soil moisture measurements, the Oklahoma Mesonet, an automated network of 116 remote meteorological stations across Oklahoma, installed Campbell Scientific 229-L devices to measure soil moisture conditions. Herein, background information on the soil moisture measurements, the technical design of the soil moisture network embedded within the Oklahoma Mesonet, and the quality assurance (QA) techniques applied to the observations are provided. This project also demonstrated the importance of operational QA regarding the data collected, whereby the percentage of observations that passed the QA procedures increased significantly once daily QA was applied.
Abstract
Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Understanding the spatial and temporal nature of soil moisture on the mesoscale is vital to determine the influence that land surface processes have on the atmosphere. Recognizing the need for improved in situ soil moisture measurements, the Oklahoma Mesonet, an automated network of 116 remote meteorological stations across Oklahoma, installed Campbell Scientific 229-L devices to measure soil moisture conditions. Herein, background information on the soil moisture measurements, the technical design of the soil moisture network embedded within the Oklahoma Mesonet, and the quality assurance (QA) techniques applied to the observations are provided. This project also demonstrated the importance of operational QA regarding the data collected, whereby the percentage of observations that passed the QA procedures increased significantly once daily QA was applied.
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.
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.
Abstract
Established as a multipurpose network, the Oklahoma Mesonet operates more than 110 surface observing stations that send data every 5 min to an operations center for data quality assurance, product generation, and dissemination. Quality-assured data are available within 5 min of the observation time. Since 1994, the Oklahoma Mesonet has collected 3.5 billion weather and soil observations and produced millions of decision-making products for its customers.
Abstract
Established as a multipurpose network, the Oklahoma Mesonet operates more than 110 surface observing stations that send data every 5 min to an operations center for data quality assurance, product generation, and dissemination. Quality-assured data are available within 5 min of the observation time. Since 1994, the Oklahoma Mesonet has collected 3.5 billion weather and soil observations and produced millions of decision-making products for its customers.
