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Kenneth W. Johnson

Abstract

Development of a methodology for the optimal placement of multivariate sensors as an aid in the design of geophysical field experiments is shown. The optimal placement methodology relies on spatial correlation estimates, interpolation error estimates as provided by a multivariate optimal interpolation scheme, and optimization techniques using nonlinear programming. Atmospheric fields and their associated statistics are simulated by analytic functions to demonstrate the capabilities of the methodology. These include the ability to design new networks, to add sensors optimally to existing networks, and to place restrictions on the region in which sensors can be located by introducing physical and economical constraints on the nonlinear programming problem. It is demonstrated that the mean and variance of the interpolation error for all fields is generally smaller for analyses whose input is derived from optimal sampling locations rather than from subjectively chosen locations.

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Kenneth S. Johnson, Joshua N. Plant, Stephen C. Riser, and Denis Gilbert

Abstract

Aanderaa optode sensors for dissolved oxygen show remarkable stability when deployed on profiling floats, but these sensors suffer from poor calibration because of an apparent drift during storage (storage drift). It has been suggested that measurement of oxygen in air, during the period when a profiling float is on the surface, can be used to improve sensor calibration and to determine the magnitude of sensor drift while deployed in the ocean. The effect of air calibration on oxygen measurement quality with 47 profiling floats that were equipped with Aanderaa oxygen optode sensors is assessed. Recalibrated oxygen concentration measurements were compared to Winkler oxygen titrations that were made at the float deployment stations and to the World Ocean Atlas 2009 oxygen climatology. Recalibration of the sensor using air oxygen reduces the sensor error, defined as the difference from Winkler oxygen titrations in the mixed layer near the time of deployment, by about tenfold when compared to errors obtained with the factory calibration. The relative error of recalibrated sensors is <1% in surface waters. A total of 29 floats were deployed for time periods in excess of one year in ice-free waters. Linear changes in the percent of atmospheric oxygen reported by the sensor, relative to the oxygen partial pressure expected from the NCEP air pressure, range from −0.9% to +1.3% yr−1 with a mean of 0.2% ± 0.5% yr−1. Given that storage drift for optode sensors is only negative, it is concluded that there is no evidence for sensor drift after they are deployed and that other processes are responsible for the linear changes.

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Pavlos Kollias, Bruce A. Albrecht, Eugene E. Clothiaux, Mark A. Miller, Karen L. Johnson, and Kenneth P. Moran

Abstract

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurements (ARM) program operates millimeter-wavelength cloud radars (MMCRs) in several specific locations within different climatological regimes. These vertically pointing cloud profiling radars supply the three most important Doppler spectrum moment estimates, which are the radar reflectivity (or zero moment), the mean Doppler velocity (or first moment), and the Doppler spectrum width (or second moment), as a function of time and height. The ARM MMCR Doppler moment estimates form the basis of a number of algorithms for retrieving cloud microphysical and radiative properties. The retrieval algorithms are highly sensitive to the quality and accuracy of the MMCR Doppler moment estimates. The significance of these sensitivities should not be underestimated, because the inherent physical variability of clouds, instrument-induced noise, and sampling strategy limitations all potentially introduce errors into the Doppler moment estimates. In this article, the accuracies of the first three Doppler moment estimates from the ARM MMCRs are evaluated for a set of typical cloud conditions from the three DOE ARM program sites. Results of the analysis suggest that significant errors in the Doppler moment estimates are possible in the current configurations of the ARM MMCRs. In particular, weakly reflecting clouds with low signal-to-noise ratios (SNRs), as well as turbulent clouds with nonzero updraft and downdraft velocities that are coupled with high SNR, are shown to produce degraded Doppler moment estimates in the current ARM MMCR operational mode processing strategies. Analysis of the Doppler moment estimates and MMCR receiver noise characteristics suggests that the introduction of a set of quality control criteria is necessary for identifying periods of degraded receiver performance that leads to larger uncertainties in the Doppler moment estimates. Moreover, the temporal sampling of the ARM MMCRs was found to be insufficient for representing the actual dynamical states in many types of clouds, especially boundary layer clouds. New digital signal processors (DSPs) are currently being developed for the ARM MMCRs. The findings presented in this study will be used in the design of a new set of operational strategies for the ARM MMCRs once they have been upgraded with the new DSPs.

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Kenneth S. Johnson, Luke J. Coletti, Hans W. Jannasch, Carole M. Sakamoto, Dana D. Swift, and Stephen C. Riser

Abstract

Reagent-free optical nitrate sensors [in situ ultraviolet spectrophotometer (ISUS)] can be used to detect nitrate throughout most of the ocean. Although the sensor is a relatively high-power device when operated continuously (7.5 W typical), the instrument can be operated in a low-power mode, where individual nitrate measurements require only a few seconds of instrument time and the system consumes only 45 J of energy per nitrate measurement. Operation in this mode has enabled the integration of ISUS sensors with Teledyne Webb Research's Autonomous Profiling Explorer (APEX) profiling floats with a capability to operate to 2000 m. The energy consumed with each nitrate measurement is low enough to allow 60 nitrate observations on each vertical profile to 1000 m. Vertical resolution varies from 5 m near the surface to 50 m near 1000 m, and every 100 m below that. Primary lithium batteries allow more than 300 vertical profiles from a depth of 1000 m to be made, which corresponds to an endurance near four years at a 5-day cycle time. This study details the experience in integrating ISUS sensors into Teledyne Webb Research's APEX profiling floats and the results that have been obtained throughout the ocean for periods up to three years.

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Kenneth J. Voss, Howard R. Gordon, Stephanie Flora, B. Carol Johnson, Mark Yarbrough, Michael Feinholz, and Terrence Houlihan

Abstract

The upwelling radiance attenuation coefficient K Lu in the upper 10 m of the water column can be significantly influenced by inelastic scattering processes and thus will vary even with homogeneous water properties. The Marine Optical Buoy (MOBY), the primary vicarious calibration site for many ocean color sensors, makes measurements of the upwelling radiance L u at 1, 5, and 9 m, and uses these values to determine K Lu and to propagate the upwelling radiance directed toward the zenith, L u, at 1 m to and through the surface. Inelastic scattering causes the K Lu derived from the measurements to be an underestimate of the true K Lu from 1 m to the surface at wavelengths greater than 575 nm; thus, the derived water-leaving radiance is underestimated at wavelengths longer than 575 nm. A method to correct this K Lu, based on a model of the upwelling radiance including Raman scattering and chlorophyll fluorescence, has been developed that corrects this bias. The model has been experimentally validated, and this technique can be applied to the MOBY dataset to provide new, more accurate products at these wavelengths. When applied to a 4-month MOBY deployment, the corrected water-leaving radiance L w can increase by 5% (600 nm), 10% (650 nm), and 50% (700 nm). This method will be used to provide additional and more accurate products in the MOBY dataset.

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Kenneth J. Voss, Scott McLean, Marlon Lewis, Carol Johnson, Stephanie Flora, Michael Feinholz, Mark Yarbrough, Charles Trees, Mike Twardowski, and Dennis Clark

Abstract

Vicarious calibration of ocean color satellites involves the use of accurate surface measurements of water-leaving radiance to update and improve the system calibration of ocean color satellite sensors. An experiment was performed to compare a free-fall technique with the established Marine Optical Buoy (MOBY) measurement. It was found in the laboratory that the radiance and irradiance instruments compared well within their estimated uncertainties for various spectral sources. The spectrally averaged differences between the National Institute of Standards and Technology (NIST) values for the sources and the instruments were <2.5% for the radiance sensors and <1.5% for the irradiance sensors. In the field, the sensors measuring the above-surface downwelling irradiance performed nearly as well as they had in the laboratory, with an average difference of <2%. While the water-leaving radiance Lw calculated from each instrument agreed in almost all cases within the combined instrument uncertainties (approximately 7%), there was a relative bias between the two instrument classes/techniques that varied spectrally. The spectrally averaged (400–600 nm) difference between the two instrument classes/techniques was 3.1%. However, the spectral variation resulted in the free-fall instruments being 0.2% lower at 450 nm and 5.9% higher at 550 nm. Based on the analysis of one matchup, the bias in Lw was similar to that observed for Lu(1 m) with both systems, indicating the difference did not come from propagating Lu(1 m) to Lw.

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Fred V. Brock, Kenneth C. Crawford, Ronald L. Elliott, Gerrit W. Cuperus, Steven J. Stadler, Howard L. Johnson, and Michael D. Eilts

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 with respect to ground level, and method of exposure are discussed.

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Pavlos Kollias, Mark A. Miller, Edward P. Luke, Karen L. Johnson, Eugene E. Clothiaux, Kenneth P. Moran, Kevin B. Widener, and Bruce A. Albrecht

Abstract

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates millimeter-wavelength cloud radars in several climatologically distinct regions. The digital signal processors for these radars were recently upgraded and allow for enhancements in the operational parameters running on them. Recent evaluations of millimeter-wavelength cloud radar signal processing performance relative to the range of cloud dynamical and microphysical conditions encountered at the ARM Program sites have indicated that improvements are necessary, including significant improvement in temporal resolution (i.e., less than 1 s for dwell and 2 s for dwell and processing), wider Nyquist velocities, operational dealiasing of the recorded spectra, removal of pulse compression while sampling the boundary layer, and continuous recording of Doppler spectra. A new set of millimeter-wavelength cloud radar operational modes that incorporate these enhancements is presented. A significant change in radar sampling is the introduction of an uneven mode sequence with 50% of the sampling time dedicated to the lower atmosphere, allowing for detailed characterization of boundary layer clouds. The changes in the operational modes have a substantial impact on the postprocessing algorithms that are used to extract cloud information from the radar data. New methods for postprocessing of recorded Doppler spectra are presented that result in more accurate identification of radar clutter (e.g., insects) and extraction of turbulence and microphysical information. Results of recent studies on the error characteristics of derived Doppler moments are included so that uncertainty estimates are now included with the moments. The microscale data product based on the increased temporal resolution of the millimeter-wavelength cloud radars is described. It contains the number of local maxima in each Doppler spectrum, the Doppler moments of the primary peak, uncertainty estimates for the Doppler moments of the primary peak, Doppler moment shape parameters (e.g., skewness and kurtosis), and clear-air clutter flags.

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Yuichiro Takeshita, Brent D. Jones, Kenneth S. Johnson, Francisco P. Chavez, Daniel L. Rudnick, Marguerite Blum, Kyle Conner, Scott Jensen, Jacqueline S. Long, Thom Maughan, Keaton L. Mertz, Jeffrey T. Sherman, and Joseph K. Warren

Abstract

The California Current System is thought to be particularly vulnerable to ocean acidification, yet pH remains chronically undersampled along this coast, limiting our ability to assess the impacts of ocean acidification. To address this observational gap, we integrated the Deep-Sea-DuraFET, a solid-state pH sensor, onto a Spray underwater glider. Over the course of a year starting in April 2019, we conducted seven missions in central California that spanned 161 glider days and >1600 dives to a maximum depth of 1000 m. The sensor accuracy was estimated to be ± 0.01 based on comparisons to discrete samples taken alongside the glider (n = 105), and the precision was ±0.0016. CO2 partial pressure, dissolved inorganic carbon, and aragonite saturation state could be estimated from the pH data with uncertainty better than ± 2.5%, ± 8 μmol kg−1, and ± 2%, respectively. The sensor was stable to ±0.01 for the first 9 months but exhibited a drift of 0.015 during the last mission. The drift was correctable using a piecewise linear regression based on a reference pH field at 450 m estimated from published global empirical algorithms. These algorithms require accurate O2 as inputs; thus, protocols for a simple predeployment air calibration that achieved accuracy of better than 1% were implemented. The glider observations revealed upwelling of undersaturated waters with respect to aragonite to within 5 m below the surface near Monterey Bay. These observations highlight the importance of persistent observations through autonomous platforms in highly dynamic coastal environments.

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