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Jerald A. Brotzge

Abstract

Few surface-observation networks exist that provide comprehensive multiyear, multiseason observations of surface energy fluxes and subsurface soil moisture and temperature, combined with near-surface atmospheric data. More such networks are needed to validate, improve, and calibrate current global weather and climate models, including those used as the backbone or background models in global reanalysis. One such measurement system is the Oklahoma Mesonet–Oklahoma Atmospheric Surface-layer Instrumentation System (OASIS), which provides atmospheric, surface, and soil data in real time. This study compares 2 yr of surface energy and water budget data from two OASIS sites located in two distinct climate zones with NCEP–NCAR global reanalysis (GR) estimates. The intraseasonal hydrological and thermodynamic cycles are discussed. Results show generally good agreement between most reanalysis values and observations. Incoming and reflected shortwave radiation are largely overestimated by the GR, and incoming longwave radiation is slightly underestimated by the GR when compared to OASIS observations. The GR significantly overestimates latent heat (LE) at the Idabel, Oklahoma (IDAB) site. Furthermore, the GR likely underestimates entrainment of drier air from above the PBL and mixes the turbulent fluxes over too shallow of a layer. Both the reanalysis and observations find a positive water residual for the easternmost site (IDAB) but estimate a negative near-surface water residual for the western site [Boise City, Oklahoma (BOIS)]. Overall, surface fluxes and thermodynamic properties were well analyzed by the reanalysis at capturing the unique features associated with each OASIS site.

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Jerald A. Brotzge and Kenneth C. Crawford

Abstract

A reliable method for monitoring the surface energy budget is critical to the development and validation of numerical models and remote sensing algorithms. Unfortunately, closure of the energy budget remains difficult to achieve among measurement systems. Reasons for nonclosure still are not clearly understood, and, until recently, few long-term datasets were available to address this issue of nonclosure. This contribution examined 108 days of a year dataset collected from collocated eddy correlation (EC) and Bowen ratio (BR) systems. Differences between systems were examined across seasonal and diurnal cycles to better understand nonclosure of the energy budget. Closure by the EC system was observed to vary with season and with time of day, primarily as a function of latent heat flux. Furthermore, the EC and BR methods partitioned energy differently, with the EC system favoring latent heat flux and the BR system favoring sensible heat flux.

Instrument error, surface heterogeneity, and the theoretical assumptions behind the EC and BR methods are discussed to explain observed patterns in closure and the differences between measurement systems. Sensor error and variability in net radiation and soil moisture data increased uncertainty in measurements of net radiation and ground heat flux. Significant differences in soil temperature and flux between sites appear to be caused by the heterogeneity of vegetation and soil type. Finally, several assumptions of the BR method are examined to explain observed differences in sensible and latent heat flux between systems. Recommendations for future observational studies are proposed.

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Jerald A. Brotzge and Scott J. Richardson

Abstract

A major challenge in meteorology is determining the manner and scale at which the land surface interacts with the atmosphere. A majority of field programs, designed to address this issue, have been limited in space and time and thus have been unable to span the seasonal cycle across a regional to a statewide area. In an effort to address this problem, data for one year were collected and archived from 89 sites during 2000 from the Oklahoma Mesonet and Oklahoma Atmospheric Surface-Layer Instrumentation System (OASIS). Mean and variance estimates of radiation, air and skin temperature, relative humidity, surface fluxes, and soil moisture were investigated. Site-to-site correlation coefficients of these variables also were examined. Furthermore, Hovmoeller diagrams of atmospheric and surface variables were plotted and were discussed in relation to statewide patterns of rainfall, vegetation, and topography. The data revealed complex interactions among the more slowly varying parameters, such as soil wetness and vegetation greenness, and the more rapidly changing variables, such as atmospheric temperature and moisture.

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Jerald A. Brotzge and Kenneth C. Crawford

Abstract

The challenges of using the Oklahoma Mesonet for calculations of sensible heat flux are discussed. The mesonet is an integrated network of 115 remote and automated meteorological stations across Oklahoma that provides the spatial density to observe synoptic and mesoscale features. Temperature and wind speed are measured at two levels at 48 mesonet sites, from which heat flux may be estimated using a gradient approach. A series of field experiments was conducted that quantified the problems and limitations of estimating heat fluxes from the mesonet sites. Four specific problems were identified, and solutions to these limitations are discussed. These problems include 1) differences in instrumentation, 2) an apparent “offset” between thermistors, 3) radiative heating error, and 4) fetch limitations. As an independent verification, mesonet flux values were compared directly with eddy correlation estimates.

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Vivek N. Mahale, Jerald A. Brotzge, and Howard B. Bluestein

Abstract

Adding a mix of X- or C-band radars to the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network could address several limitations of the network, including improvements to spatial gaps in low-level coverage and temporal sampling of volume scans. These limitations can result in missing critical information in highly dynamic events, such as tornadoes and severe straight-line wind episodes. To evaluate the potential value of a mixed-band radar network for severe weather operations, a case study is examined using data from X- and S-band radars. On 13 May 2009, a thunderstorm complex associated with a cold front moved southward into southwest Oklahoma. A tornado rapidly developed from an embedded supercell within the complex. The life cycle of the tornado and subsequent wind event was sampled by the experimental Collaborative Adaptive Sensing of the Atmosphere (CASA) radar testbed of four X-band radars as well as two operational WSR-88Ds. In this study, the advantages of a mixed-band radar network are demonstrated through a chronological analysis of the event. The two radar networks provided enhanced overall situational awareness. Data from the WSR-88Ds provided 1) clear-air sensitivity, 2) a broad overview of the storm complex, 3) a large maximum unambiguous range, and 4) upper-level scans up to 19.5°. Data from the CASA radars provided 1) high-temporal, 1-min updates; 2) overlapping coverage for dual-Doppler analysis; and 3) dense low-level coverage. The combined system allowed for detailed, dual- and single-Doppler observations of a wind surge, a mesocyclone contraction, and a downburst.

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Vivek N. Mahale, Jerald A. Brotzge, and Howard B. Bluestein

Abstract

On 2 April 2010, a developing quasi-linear convective system (QLCS) moved rapidly northeastward through central Oklahoma spawning at least three intense, mesoscale vortices. At least two of these vortices caused damage rated as category 0 to 1 on the enhanced Fujita scale (EF0–EF1) in and near the town of Rush Springs. Two radar networks—the National Weather Service Weather Surveillance Radar-1988 Doppler network (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network—collected high spatial and temporal resolution data of the event. This study is an in-depth polarimetric analysis of mesovortices within a QLCS. In this case study, the storm development and evolution of the QLCS mesovortices are examined. Significant findings include the following: 1) The damage in Rush Springs was caused by a combination of the fast translation speed and the embedded circulations associated with QLCS vortices. The vortices’ relative winds nearly negated the storm motion to the left of the vortex, but doubled the ground-relative wind to the right of the vortex. 2) A significant differential reflectivity (Z DR) arc developed along the forward flank of the first vortex. The Z DR arc propagated northeastward along the QLCS with the development of each new vortex. 3) A minimum in the copolar correlation coefficient (ρ hv) in the center of the strongest vortex was observed, indicating the likely existence of a polarimetric tornado debris signature (TDS). A secondary ρ hv minimum also was found just to the right of the vortex center, possibly associated with lofted debris from straight-line winds.

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Christopher A. Fiebrich, Janet E. Martinez, Jerald A. Brotzge, and Jeffrey B. Basara

Abstract

In 1999, the Oklahoma Mesonet deployed infrared temperature (IRT) sensors at 89 of its environmental monitoring stations. A 3-yr dataset collected since that time provides a unique opportunity to analyze longer-term, continuous, mesoscale observations of skin temperature across a large area. Several limitations of the sensor have been identified and include 1) failure of the calibration equation during the cold season, 2) difficulty in keeping the sensor's lens clean at remote sites, and 3) limited representativeness of local conditions due to the sensor's narrow field of view. Despite these limitations, the Oklahoma Mesonet's skin temperature network provides a wealth of information that can be used to better understand many land–atmosphere interactions. Not only can the observations be used to estimate the partitioning of latent and sensible heat flux, they also provide beneficial “ground truth” estimates to validate remotely sensed estimates of skin temperature. This manuscript describes the IRT sensor, evaluates its performance, and provides analysis of time series data and observed spatial variability across Oklahoma.

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Jerald A. Brotzge, Steven E. Nelson, Richard L. Thompson, and Bryan T. Smith

Abstract

The ability to provide advanced warning on tornadoes can be impacted by variations in storm mode. This research evaluates 2 yr of National Weather Service (NWS) tornado warnings, verification reports, and radar-derived convective modes to appraise the ability of the NWS to warn across a variety of convective modes and environmental conditions. Several specific hypotheses are considered: (i) supercell morphologies are the easiest convective modes to warn for tornadoes and yield the greatest lead times, while tornadoes from more linear, nonsupercell convective modes, such as quasi-linear convective systems, are more difficult to warn for; (ii) parameters such as tornado distance from radar, population density, and tornado intensity (F scale) introduce significant and complex variability into warning statistics as a function of storm mode; and (iii) tornadoes from stronger storms, as measured by their mesocyclone strength (when present), convective available potential energy (CAPE), vertical wind shear, and significant tornado parameter (STP) are easier to warn for than tornadoes from weaker systems. Results confirmed these hypotheses. Supercell morphologies caused 97% of tornado fatalities, 96% of injuries, and 92% of damage during the study period. Tornado warnings for supercells had a statistically higher probability of detection (POD) and lead time than tornado warnings for nonsupercells; among supercell storms, tornadoes from supercells in lines were slightly more difficult to warn for than tornadoes from discrete or clusters of supercells. F-scale intensity and distance from radar had some impact on POD, with less impact on lead times. Higher mesocyclone strength (when applicable), CAPE, wind shear, and STP values were associated with greater tornado POD and lead times.

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Jerald A. Brotzge, J. Wang, C. D. Thorncroft, E. Joseph, N. Bain, N. Bassill, N. Farruggio, J. M. Freedman, K. Hemker Jr., D. Johnston, E. Kane, S. McKim, S. D. Miller, J. R. Minder, P. Naple, S. Perez, James J. Schwab, M. J. Schwab, and J. Sicker

Abstract

The New York State Mesonet (NYSM) is a network of 126 standard environmental monitoring stations deployed statewide with an average spacing of 27 km. The primary goal of the NYSM is to provide high-quality weather data at high spatial and temporal scales to improve atmospheric monitoring and prediction, especially for extreme weather events. As compared with other statewide networks, the NYSM faced considerable deployment obstacles with New York’s complex terrain, forests, and very rural and urban areas; its wide range of weather extremes; and its harsh winter conditions. To overcome these challenges, the NYSM adopted a number of innovations unique among statewide monitoring systems, including 1) strict adherence to international siting standards and metadata documentation; 2) a hardened system design to facilitate continued operations during extreme, high-impact weather; 3) a station design optimized to monitor winter weather conditions; and 4) a camera installed at every site to aid situational awareness. The network was completed in spring of 2018 and provides data and products to a variety of sectors including weather monitoring and forecasting, emergency management, agriculture, transportation, utilities, and education. This paper focuses on the standard network of the NYSM and reviews the network siting, site configuration, sensors, site communications and power, network operations and maintenance, data quality control, and dissemination. A few example analyses are shown that highlight the benefits of the NYSM.

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