Renee A. McPherson

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.

A review of vegetation—atmosphere interactions and their influences on mesoscale phenomena

Vegetation strongly influences exchanges of energy and moisture between land and atmosphere through (1) the vegetations response to incoming radiation and its emission of longwave radiation (2) the vegetations physical presence, and (3) the plants transpiration. These processes affect the diurnal temperature range, processes in the atmospheric boundary layer, cloud cover, rainfall, differential heating, and atmospheric circulations. This paper overviews how vegetation interacts with surface energy and moisture budgets and reviews both observational and modelling studies that examine how vegetation affects weather and climate on the mesoscale (ie, phenomena 10s to 100s of kilometres in horizontal size).

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 ...

OBSERVATIONS OF THE OVERLAND REINTENSIFICATION OF TROPICAL STORM ERIN (2007)

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, Erins remnant circulation strengthened over western Oklahoma, where sustained winds near the circulations center exceeded 18 m s−1 for more than 3 h—the strongest reported during Erins 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 ...

Quality assurance procedures for mesoscale meteorological data.

Abstract Mesoscale meteorological data present their own challenges and advantages during the quality assurance (QA) process because of their variability in both space and time. To ensure data quality, it is important to perform quality control at many different stages (e.g., sensor calibrations, automated tests, and manual assessment). As part of an ongoing refinement of quality assurance procedures, meteorologists with the Oklahoma Mesonet continually review advancements and techniques employed by other networks. This article’s aim is to share those reviews and resources with scientists beginning or enhancing their own QA program. General QA considerations, general automated tests, and variable-specific tests and methods are discussed.

The Value of Routine Site Visits in Managing and Maintaining Quality Data from the Oklahoma Mesonet

Abstract The Oklahoma Mesonet, jointly operated by the University of Oklahoma and Oklahoma State University, is a network of 116 environmental monitoring stations across Oklahoma. Technicians at the Oklahoma Mesonet perform three seasonal (i.e., spring, summer, and fall) maintenance passes annually. During each 3-month-long pass, a technician visits every Mesonet site. The Mesonet employs four technicians who each maintain the stations in a given quadrant of the state. The purpose of a maintenance pass is to 1) provide proactive vegetation maintenance, 2) perform sensor rotations, 3) clean and inspect sensors, 4) test the performance of sensors in the field, 5) standardize maintenance procedures at each site, 6) document the site characteristics with digital photographs, and 7) inspect the station’s hardware. The Oklahoma Mesonet has learned that routine and standardized station maintenance has two unique benefits: 1) it allows personnel the ability to manage a large network efficiently, and 2) it provide...

Influences of a Winter Wheat Belt on the Evolution of the Boundary Layer

Abstract Evidence exists that a large-scale alteration of land use by humans can cause changes in the climatology of the region. The largest-scale transformation is the substitution of native landscape by agricultural cropland. This modeling study examines the impact of a direct substitution of one type of grassland for another—in this case, the replacement of tallgrass prairie with winter wheat. The primary difference between these grasses is their growing season: native prairie grasses of the U.S. Great Plains are warm-season grasses whereas winter wheat is a cool-season grass. Case study simulations were conducted for 27 March 2000 and 5 April 2000—days analyzed in previous observational studies. The simulations provided additional insight into the physical processes involved and changes that occurred throughout the depth of the planetary boundary layer. Results indicate the following: 1) with the proper adjustment of vegetation parameters, land-use type, fractional vegetation coverage, and soil moistu...

New Multisite Cascading Calibration Approach for Hydrological Models: Case Study in the Red River Basin Using the VIC Model

AbstractA novel multisite cascading calibration (MSCC) approach using the shuffled complex evolution–University of Arizona (SCE-UA) optimization method, developed at the University of Arizona, was employed to calibrate the variable infiltration capacity (VIC) model in the Red River Basin. Model simulations were conducted at 35 nested gauging stations. Compared with simulated results using a priori parameters, single-site calibration can improve VIC model performance at specific calibration sites; however, improvement is still limited in upstream locations. The newly developed MSCC approach overcomes this limitation. Simulations using MSCC not only utilize all of the available streamflow observations but also better represent spatial heterogeneities in the model parameters. Results indicate that MSCC largely improves model performance by decreasing the number of stations with negative Nash-Sutcliffe coefficient of efficiency (NSCE) values from 69% (66%) for a priori parameters to 37% (34%) for single-site ...

An evaluation of dynamical downscaling of Central Plains summer precipitation using a WRF‐based regional climate model at a convection‐permitting 4 km resolution

A significant challenge with dynamical downscaling of climate simulations is the ability to accurately represent convection and precipitation. The use of convection-permitting resolutions avoids cumulus parameterization, which is known to be a large source of uncertainty. A regional climate model (RCM) based on the Weather Research and Forecasting model is configured with a 4 km grid spacing and applied to the U.S. Great Plains, a region characterized by many forms of weather and climate extremes. The 4 km RCM is evaluated by running it in a hindcast mode over the central U.S. region for a 10 year period, forced at the boundary by the 32 km North America Regional Reanalysis. The model is also run at a 25 km grid spacing, but with cumulus parameterization turned on for comparison. The 4 km run more successfully reproduces certain observed features of the Great Plains May-through-August precipitation. In particular, the magnitude of extreme precipitation and the diurnal cycle of precipitation over the Great Plains are better simulated. The 4 km run more realistically simulates the low-level jet and related atmospheric circulations that transport and redistribute moisture from Gulf of Mexico. The convection-permitting RCM may therefore produce better dynamical downscaling of future climate when nested within global model climate projections, especially for extreme precipitation magnitudes. The 4 km and 25 km simulations do share similar precipitation biases, including low biases over the central Great Plains and high biases over the Rockies. These biases appear linked to circulation biases in the simulations, but determining of the exact causes will require extensive, separate studies.

On the Economic Nature of Crop Production Decisions Using the Oklahoma Mesonet

Abstract Because of the sensitivity of agricultural production to both short-term weather and long-range climatic patterns, the availability of reliable and relevant meteorological data and climate products can potentially affect the entire production process. This study focuses on the use of information from a dense meteorological network—the Oklahoma Mesonet—and its AgWeather program in support of agricultural production decisions. Production decisions that are particularly dependent on information from the Mesonet are identified. Producers in Oklahoma are influenced by Mesonet data at several levels, including agricultural policy, production choices, and risk management. Additionally, producers use the Mesonet to attain their financial goals, through such measures as cost saving and maximization of quality and quantity, in addition to others. Potential savings from Mesonet data for the state’s agricultural sector are also estimated.