Jeffrey B. Basara

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.

Description and Evaluation of the Characteristics of the NCAR High-Resolution Land Data Assimilation System

Abstract This paper describes important characteristics of an uncoupled high-resolution land data assimilation system (HRLDAS) and presents a systematic evaluation of 18-month-long HRLDAS numerical experiments, conducted in two nested domains (with 12- and 4-km grid spacing) for the period from 1 January 2001 to 30 June 2002, in the context of the International H2O Project (IHOP_2002). HRLDAS was developed at the National Center for Atmospheric Research (NCAR) to initialize land-state variables of the coupled Weather Research and Forecasting (WRF)–land surface model (LSM) for high-resolution applications. Both uncoupled HRDLAS and coupled WRF are executed on the same grid, sharing the same LSM, land use, soil texture, terrain height, time-varying vegetation fields, and LSM parameters to ensure the same soil moisture climatological description between the two modeling systems so that HRLDAS soil state variables can be used to initialize WRF–LSM without conversion and interpolation. If HRLDAS is initialized...

A Multiscale Remote Sensing Model for Disaggregating Regional Fluxes to Micrometeorological Scales

Abstract Disaggregation of regional-scale (103 m) flux estimates to micrometeorological scales (101–102 m) facilitates direct comparison between land surface models and ground-based observations. Inversely, it also provides a means for upscaling flux-tower information into a regional context. The utility of the Atmosphere–Land Exchange Inverse (ALEXI) model and associated disaggregation technique (DisALEXI) in effecting regional to local downscaling is demonstrated in an application to thermal imagery collected with the Geostationary Operational Environmental Satellite (GOES) (5-km resolution) and Landsat (60-m resolution) over the state of Oklahoma on 4 days during 2000–01. A related algorithm (DisTrad) sharpens thermal imagery to resolutions associated with visible–near-infrared bands (30 m on Landsat), extending the range in scales achievable through disaggregation. The accuracy and utility of this combined multiscale modeling system is evaluated quantitatively in comparison with measurements made with...

Verification of a Mesoscale Data-Assimilation and Forecasting System for the Oklahoma City Area during the Joint Urban 2003 Field Project

Abstract The National Center for Atmospheric Research (NCAR) and the U.S. Army Test and Evaluation Command have developed a multiscale, rapid-cycling, real-time, four-dimensional data-assimilation and forecasting system that has been in operational use at five Army test ranges since 2001. This system was employed to provide operational modeling support for the Joint Urban 2003 (JU2003) Dispersion Experiment, conducted in Oklahoma City, Oklahoma, during July 2003. To better support this mission, modifications were made to the nonlocal boundary layer (BL) parameterization (known as the Medium Range Forecast scheme) of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model, in order to improve BL forecasts. The NCEP–Oregon State University–Air Force–Hydrologic Research Laboratory land surface model was also improved to better represent urban forcing. Verification of the operational model runs and retrospectively simulated cases show 1) a significantly reduced low bias in the forecast surface...

Using ENVISAT ASAR Global Mode Data for Surface Soil Moisture Retrieval Over Oklahoma, USA

The Advanced Synthetic Aperture Radar (ASAR) onboard of the satellite ENVISAT can be operated in global monitoring (GM) mode. ASAR GM mode has delivered the first global multiyear C-band backscatter data set in HH polarization at a spatial resolution of 1 km. This paper investigates if ASAR GM can be used for retrieving soil moisture using a change detection approach over large regions. A method previously developed for the European Remote Sensing (ERS) scatterometer is adapted for use with ASAR GM and tested over Oklahoma, USA. The ASAR-GM-derived relative soil moisture index is compared to 50-km ERS soil moisture data and pointlike in situ measurements from the Oklahoma MESONET. Even though the scale gap from ASAR GM to the in situ measurements is less pronounced than in the case of the ERS scatterometer, the correlation for ASAR against the in situ measurements is, in general, somewhat weaker than for the ERS scatterometer. The analysis suggests that this is mainly due to the much higher noise level of ASAR GM compared to the ERS scatterometer. Therefore, some spatial averaging to 3-10 km is recommended to reduce the noise of the ASAR GM soil moisture images. Nevertheless, the study demonstrates that ASAR GM allows resolving spatial details in the soil moisture patterns not observable in the ERS scatterometer measurements while still retaining the basic capability of the ERS scatterometer to capture temporal trends over large areas.

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 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.

Examining Rapid Onset Drought Development Using the Thermal Infrared–Based Evaporative Stress Index

AbstractReliable indicators of rapid drought onset can help to improve the effectiveness of drought early warning systems. In this study, the evaporative stress index (ESI), which uses remotely sensed thermal infrared imagery to estimate evapotranspiration (ET), is compared to drought classifications in the U.S. Drought Monitor (USDM) and standard precipitation-based drought indicators for several cases of rapid drought development that have occurred across the United States in recent years. Analysis of meteorological time series from the North American Regional Reanalysis indicates that these events are typically characterized by warm air temperature and low cloud cover anomalies, often with high winds and dewpoint depressions that serve to hasten evaporative depletion of soil moisture reserves. Standardized change anomalies depicting the rate at which various multiweek ESI composites changed over different time intervals are computed to more easily identify areas experiencing rapid changes in ET. Overal...

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 ...

Improved Installation Procedures for Deep-Layer Soil Moisture Measurements

Abstract The Oklahoma Mesonet, an automated network of 115 meteorological observing stations, includes soil moisture monitoring devices at 60 locations. The Campbell Scientific model 229-L matric potential (water potential) sensor was chosen for operational use based on its capability to perform as a fully automated soil water measuring device. Extensive laboratory calibrations were performed on each sensor to ensure the quality of the matric potential measurements. Examination of the data from the Norman site during July 1997 revealed significant inconsistencies between near-surface (5 and 25 cm) measurements of soil moisture and deep-layer (60 and 75 cm) measurements of soil moisture. In particular, a heavy precipitation event was followed by only a small increase in near-surface soil water potential values, while a much larger increase occurred in the deep-layer values. It is theorized that an installation flaw is the cause for these inconsistencies. A solution is proposed in the hope that future effor...