Kenneth C. Crawford

The Oklahoma Mesonet: A Technical Overview

Abstract The Oklahoma mesonet is a joint project of Oklahoma State University and the University of Oklahoma. It is an automated network of 108 stations covering the state of Oklahoma. Each station measures air temperature, humidity, barometric pressure, wind speed and direction, rainfall, solar radiation, and soil temperatures. Each station transmits a data message every 15 min via a radio link to the nearest terminal of the Oklahoma Law Enforcement Telecommunications System that relays it to a central site in Norman, Oklahoma. The data message comprises three 5-min averages of most data (and one 15-min average of soil temperatures). The central site ingests the data, runs some quality assurance tests, archives the data, and disseminates it in real time to a broad community of users, primarily through a computerized bulletin board system. This manuscript provides a technical description of the Oklahoma mesonet including a complete description of the instrumentation. Sensor inaccuracy, resolution, height ...

Statewide Monitoring of the Mesoscale Environment: A Technical Update on the Oklahoma Mesonet

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.

Mesoscale Monitoring of Soil Moisture across a Statewide Network

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.

The Impact of Oklahoma's Winter Wheat Belt on the Mesoscale Environment

Abstract Oklahoma Mesonet data were used to measure the impact of Oklahomas winter wheat belt on the mesoscale environment from 1994 to 2001. Statistical analyses of monthly means of near-surface air temperatures demonstrated that 1) a well-defined cool anomaly existed across the wheat belt during November, December, January, February, and April, and 2) a well-defined warm anomaly existed across the wheat belt during June, July, and August. Data from crop year 2000 indicated a slight moist anomaly over the growing wheat from November 1999 through April 2000. In addition, based upon 21 000 daily statistics over eight unique years, statistical computations indicated less than a 0.1% chance that the moist anomaly during March resulted from random chance. During the period from 1999 to 2001, about 50 days between 15 March and 1 May showed evidence of heightened values of daily maximum dewpoint over Oklahomas winter wheat belt as compared to adjacent grasslands. On more than half of these days, the dewpoint ...

The Impact of the Urban Heat Island during an Intense Heat Wave in Oklahoma City

During late July and early August 2008, an intense heat wave occurred in Oklahoma City. To quantify the impact of the urban heat island (UHI) in Oklahoma City on observed and apparent temperature conditions during the heat wave event, this study used observations from 46 locations in and around Oklahoma City. The methodology utilized composite values of atmospheric conditions for three primary categories defined by population and general land use: rural, suburban, and urban. The results of the analyses demonstrated that a consistent UHI existed during the study period whereby the composite temperature values within the urban core were approximately 0.5∘C warmer during the day than the rural areas and over 2∘C warmer at night. Further, when the warmer temperatures were combined with ambient humidity conditions, the composite values consistently revealed even warmer heat-related variables within the urban environment as compared with the rural zone.

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

Abstract On 31 January 1996, the National Centers for Environmental Prediction/Environmental Modeling Center (NCEP/EMC) implemented a state-of-the-art land surface parameterization in the operational Eta Model. The purpose of this study is to evaluate and test its performance and demonstrate its impacts on the diurnal cycle of the modeled planetary boundary layer (PBL). Operational Eta Model output from summer 1997 are evaluated against the unique observations of near-surface and subsurface fields provided by the Oklahoma Mesonet. The evaluation is partially extended to July 1998 to examine the effects of significant changes that were made to the operational model configuration during the intervening time. Results indicate a severe positive bias in top-layer soil moisture, which was significantly reduced in 1998 by a change in the initialization technique. Net radiation was overestimated, largely because of a positive bias in the downward shortwave component. Also, the ground heat flux was severely undere...

Explicit Cloud-Scale Models for Operational Forecasts: A Note of Caution

Abstract As computational capacity has increased, cloud-scale numerical models are slowly being modified from pure research tools to forecast tools. Previous studies that used cloud-scale models as explicit forecast tools, in much the same way as a mesoscale model might be used, have met with limited success. Results presented in this paper suggest that this is due, at least in part, to the nature of cloud-scale models themselves. Results from over 700 cloud-scale model runs indicate that, in some cases, differences in the initial soundings that are smaller than can be measured by the current observing system result in unexpected differences in storm longevity. In other cases, easily measurable differences in the initial soundings do not result in significant differences in storm longevity. There unfortunately appears to be no set of parameters that can be used to determine whether the initial sounding is near some part of the cloud-model parameter space that displays this sensitivity. Because different c...

Mesoscale Precipitation Fields. Part II: Hydrometeorologic Modeling

A hydrometeorologic forecast system (HFS) has been developed that takes advantage of new high-resolution rainfall datasets from the WSR-88D radar system, the Oklahoma Mesonet, and Oklahoma Local Analysis and Prediction System (OLAPS). New schemes to analyze precipitation and to adjust radar rainfall rates have been proposed to improve the quantitative precipitation forecast (QPF) for hydrologic purposes. Adjusted WSR-88D rainfall rates were advected by the 700-mb wind field from OLAPS to produce an extrapolation QPF. Several experiments were conducted to evaluate the effect of the rainfall adjustment and wind field upon the extrapolation QPF. In addition, mesoscale model‐produced QPFs were generated using The Pennsylvania State University‐ National Center for Atmospheric Research Mesoscale Model. Control and rainfall assimilation experiments were performed using both Kuo and Kain‐Fritsch cumulus parameterization schemes for three rainfall events from April 1994. All model runs were integrated forward 12 h and then verified against the analyzed precipitation field. Both the extrapolation and model-produced QPFs were used to produce hydrologic forecasts for the Dry Creek watershed in north-central Oklahoma. Results indicate that extrapolation QPFs degrade exponentially with time and become inferior to the QPF from a mesoscale model after 2 h. When the extrapolated rainfall estimates were input into a hydrologic model, an underestimate of the peak flow occurred since the time evolution of precipitating systems is not handled by extrapolation. Due to the lag time between the peak in precipitation and the peak in streamflow, the greatest impact upon the accuracy of hydrologic forecasts resulted from improvements in the analyzed precipitation field. On the other hand, mesoscale forecast simulations revealed that the assimilation of analyzed rainfall had a limited impact upon the evolution of model-produced precipitation forecasts out to 4 h. However, model-produced QPFs improved after 8 h into the integration. While the Kuo scheme produced less dispersion error, the Kain‐ Fritsch scheme created less amplitude error. The assimilation of analyzed rainfall through the convergence factor of the Kuo scheme had a greater impact upon the performance of the mesoscale model than did the Kain‐Fritsch rainfall assimilation through the adjustment of its precipitation efficiency factor. Therefore, a new generation HFS has been developed to take advantage of new technology and new scientific methods in an attempt to mitigate the age-old issue of devastating floods that occur without warning. Each component has been tested and evaluated. The results of testing and evaluating each component of the proposed HFS are presented in this paper.

Ensemble Cloud Model Applications to Forecasting Thunderstorms

Abstract A cloud model ensemble forecasting approach is developed to create forecasts that describe the range and distribution of thunderstorm lifetimes that may be expected to occur on a particular day. Such forecasts are crucial for anticipating severe weather, because long-lasting storms tend to produce more significant weather and have a greater impact on public safety than do storms with brief lifetimes. Eighteen days distributed over two warm seasons with 1481 observed thunderstorms are used to assess the ensemble approach. Forecast soundings valid at 1800, 2100, and 0000 UTC provided by the 0300 UTC run of the operational Meso Eta Model from the National Centers for Environmental Prediction are used to provide horizontally homogeneous initial conditions for a cloud model ensemble made up from separate runs of the fully three-dimensional Collaborative Model for Mesoscale Atmospheric Simulation. These soundings are acquired from a 160 km × 160 km square centered over the location of interest; they ar...

OK-FIRST: A Meteorological Information System for Public Safety

The Oklahoma Climatological Survey has supported local public safety agencies (fire departments, law enforcement agencies, and emergency management) through its OK-FIRST program since 1996. OK-FIRST provides real-time use of weather data to help public safety agencies fulfill their respective operational missions. Users are taught how to interpret and apply weather data in their operations. The OK-FIRST system has been applied during a wide variety of weather events, including severe weather, floods, wildfires, and hazardous materials incidents.