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- Author or Editor: Christopher W. Fairall x
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Estimation of Rain Rate from Airborne Doppler W-Band Radar in CalWater-2ABSTRACT
The NOAA W-band radar was deployed on a P-3 aircraft during a study of storm fronts off the U.S. West Coast in 2015 in the second CalWater (CalWater-2) field program. This paper presents an analysis of measured equivalent radar reflectivity factor Z em profiles to estimate the path-averaged precipitation rate and profiles of precipitation microphysics. Several approaches are explored using information derived from attenuation of Z em as a result of absorption and scattering by raindrops. The first approach uses the observed decrease of Z em with range below the aircraft to estimate column mean precipitation rates. A hybrid approach that combines Z em in light rain and attenuation in stronger rain performed best. The second approach estimates path-integrated attenuation (PIA) via the difference in measured and calculated normalized radar cross sections (NRCS m and NRCS c , respectively) retrieved from the ocean surface. The retrieved rain rates are compared to estimates from two other systems on the P-3: a Stepped Frequency Microwave Radiometer (SFMR) and a Wide-Swath Radar Altimeter (WSRA). The W-band radar gives reasonable values for rain rates in the range 0–10 mm h−1 with an uncertainty on the order of 1 mm h−1. Mean profiles of Z em, raindrop Doppler velocity, attenuation, and precipitation rate in bins of rain rate are also computed. A method for correcting measured profiles of Z em for attenuation to estimate profiles of nonattenuated profiles of Z e is examined. Good results are obtained by referencing the surface boundary condition to the NRCS values of PIA. Limitations of the methods are discussed.
ABSTRACT
The NOAA W-band radar was deployed on a P-3 aircraft during a study of storm fronts off the U.S. West Coast in 2015 in the second CalWater (CalWater-2) field program. This paper presents an analysis of measured equivalent radar reflectivity factor Z em profiles to estimate the path-averaged precipitation rate and profiles of precipitation microphysics. Several approaches are explored using information derived from attenuation of Z em as a result of absorption and scattering by raindrops. The first approach uses the observed decrease of Z em with range below the aircraft to estimate column mean precipitation rates. A hybrid approach that combines Z em in light rain and attenuation in stronger rain performed best. The second approach estimates path-integrated attenuation (PIA) via the difference in measured and calculated normalized radar cross sections (NRCS m and NRCS c , respectively) retrieved from the ocean surface. The retrieved rain rates are compared to estimates from two other systems on the P-3: a Stepped Frequency Microwave Radiometer (SFMR) and a Wide-Swath Radar Altimeter (WSRA). The W-band radar gives reasonable values for rain rates in the range 0–10 mm h−1 with an uncertainty on the order of 1 mm h−1. Mean profiles of Z em, raindrop Doppler velocity, attenuation, and precipitation rate in bins of rain rate are also computed. A method for correcting measured profiles of Z em for attenuation to estimate profiles of nonattenuated profiles of Z e is examined. Good results are obtained by referencing the surface boundary condition to the NRCS values of PIA. Limitations of the methods are discussed.
An Evaluation of HIRS Near-Surface Air Temperature Product in the Arctic with SHEBA DataAbstract
The accuracy of cloud-screened 2-m air temperatures derived from the intersatellite-calibrated brightness temperatures based on the High Resolution Infrared Radiation Sounder (HIRS) measurements on board the National Oceanic and Atmospheric Administration (NOAA) Polar-Orbiting Operational Environmental Satellite (POES) series is evaluated by comparing HIRS air temperatures to 1-yr quality-controlled measurements collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) project (October 1997–September 1998). The mean error between collocated HIRS and SHEBA 2-m air temperature is found to be on the order of 1°C, with a slight sensitivity to spatial and temporal radii for collocation. The HIRS temperatures capture well the temporal variability of SHEBA temperatures, with cross-correlation coefficients higher than 0.93, all significant at the 99.9% confidence level. More than 87% of SHEBA temperature variance can be explained by linear regression of collocated HIRS temperatures. The analysis found a strong dependency of mean temperature errors on cloud conditions observed during SHEBA, indicating that availability of an accurate cloud mask in the region is essential to further improve the quality of HIRS near-surface air temperature products. This evaluation establishes a baseline of accuracy of HIRS temperature retrievals, providing users with information on uncertainty sources and estimates. It is a first step toward development of a new long-term 2-m air temperature product in the Arctic that utilizes intersatellite-calibrated remote sensing data from the HIRS instrument.
Abstract
The accuracy of cloud-screened 2-m air temperatures derived from the intersatellite-calibrated brightness temperatures based on the High Resolution Infrared Radiation Sounder (HIRS) measurements on board the National Oceanic and Atmospheric Administration (NOAA) Polar-Orbiting Operational Environmental Satellite (POES) series is evaluated by comparing HIRS air temperatures to 1-yr quality-controlled measurements collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) project (October 1997–September 1998). The mean error between collocated HIRS and SHEBA 2-m air temperature is found to be on the order of 1°C, with a slight sensitivity to spatial and temporal radii for collocation. The HIRS temperatures capture well the temporal variability of SHEBA temperatures, with cross-correlation coefficients higher than 0.93, all significant at the 99.9% confidence level. More than 87% of SHEBA temperature variance can be explained by linear regression of collocated HIRS temperatures. The analysis found a strong dependency of mean temperature errors on cloud conditions observed during SHEBA, indicating that availability of an accurate cloud mask in the region is essential to further improve the quality of HIRS near-surface air temperature products. This evaluation establishes a baseline of accuracy of HIRS temperature retrievals, providing users with information on uncertainty sources and estimates. It is a first step toward development of a new long-term 2-m air temperature product in the Arctic that utilizes intersatellite-calibrated remote sensing data from the HIRS instrument.
Assessing Surface Heat Flux Products with In Situ Observations over the Australian Sector of the Southern OceanAbstract
Given the large uncertainties in surface heat fluxes over the Southern Ocean, an assessment of fluxes obtained by European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) product, the Australian Integrated Marine Observing System (IMOS) routine observations, and the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project hybrid dataset is performed. The surface fluxes are calculated using the COARE 3.5 bulk algorithm with in situ data obtained from the NOAA Physical Sciences Division flux system during the Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment on board the R/V Investigator during a voyage (March–April 2016) in the Australian sector of the Southern Ocean (43°–53°S). ERA-Interim and OAFlux data are further compared with the Southern Ocean Flux Station (SOFS) air–sea flux moored surface float deployed for a year (March 2015–April 2016) at ~46.7°S, 142°E. The results indicate that ERA-Interim (3 hourly at 0.25°) and OAFlux (daily at 1°) estimate sensible heat flux H s accurately to within ±5 W m−2 and latent heat flux H l to within ±10 W m−2. ERA-Interim gives a positive bias in H s at low latitudes (<47°S) and in H l at high latitudes (>47°S), and OAFlux displays consistently positive bias in H l at all latitudes. No systematic bias with respect to wind or rain conditions was observed. Although some differences in the bulk flux algorithms are noted, these biases can be largely attributed to the uncertainties in the observations used to derive the flux products.
Abstract
Given the large uncertainties in surface heat fluxes over the Southern Ocean, an assessment of fluxes obtained by European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) product, the Australian Integrated Marine Observing System (IMOS) routine observations, and the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project hybrid dataset is performed. The surface fluxes are calculated using the COARE 3.5 bulk algorithm with in situ data obtained from the NOAA Physical Sciences Division flux system during the Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment on board the R/V Investigator during a voyage (March–April 2016) in the Australian sector of the Southern Ocean (43°–53°S). ERA-Interim and OAFlux data are further compared with the Southern Ocean Flux Station (SOFS) air–sea flux moored surface float deployed for a year (March 2015–April 2016) at ~46.7°S, 142°E. The results indicate that ERA-Interim (3 hourly at 0.25°) and OAFlux (daily at 1°) estimate sensible heat flux H s accurately to within ±5 W m−2 and latent heat flux H l to within ±10 W m−2. ERA-Interim gives a positive bias in H s at low latitudes (<47°S) and in H l at high latitudes (>47°S), and OAFlux displays consistently positive bias in H l at all latitudes. No systematic bias with respect to wind or rain conditions was observed. Although some differences in the bulk flux algorithms are noted, these biases can be largely attributed to the uncertainties in the observations used to derive the flux products.
Saildrone Direct Covariance Wind Stress in Various Wind and Current Regimes of the Tropical PacificAbstract
High-frequency wind measurements from Saildrone autonomous surface vehicles are used to calculate wind stress in the tropical east Pacific. Comparison between direct covariance (DC) and bulk wind stress estimates demonstrates very good agreement. Building on previous work that showed the bulk input data were reliable, our results lend credibility to the DC estimates. Wind flow distortion by Saildrones is comparable to or smaller than other platforms. Motion correction results in realistic wind spectra, albeit with signatures of swell-coherent wind fluctuations that may be unrealistically strong. Fractional differences between DC and bulk wind stress magnitude are largest at wind speeds below 4 m s−1. The size of this effect, however, depends on choice of stress direction assumptions. Past work has shown the importance of using current-relative (instead of Earth-relative) winds to achieve accurate wind stress magnitude. We show that it is also important for wind stress direction.
Significance Statement
We use data from Saildrone uncrewed oceanographic research vehicles to investigate the horizontal forces applied to the surface of the ocean by the action of the wind. We compare two methods to calculate the forces: one uses several simplifying assumptions, and the other makes fewer assumptions but is error prone if the data are incorrectly processed. The two methods agree well, suggesting that Saildrone vehicles are suitable for both methods and that the data processing methods work. Our results show that it is important to consider ocean currents, as well as winds, in order to achieve accurate magnitude and direction of the surface forces.
Abstract
High-frequency wind measurements from Saildrone autonomous surface vehicles are used to calculate wind stress in the tropical east Pacific. Comparison between direct covariance (DC) and bulk wind stress estimates demonstrates very good agreement. Building on previous work that showed the bulk input data were reliable, our results lend credibility to the DC estimates. Wind flow distortion by Saildrones is comparable to or smaller than other platforms. Motion correction results in realistic wind spectra, albeit with signatures of swell-coherent wind fluctuations that may be unrealistically strong. Fractional differences between DC and bulk wind stress magnitude are largest at wind speeds below 4 m s−1. The size of this effect, however, depends on choice of stress direction assumptions. Past work has shown the importance of using current-relative (instead of Earth-relative) winds to achieve accurate wind stress magnitude. We show that it is also important for wind stress direction.
Significance Statement
We use data from Saildrone uncrewed oceanographic research vehicles to investigate the horizontal forces applied to the surface of the ocean by the action of the wind. We compare two methods to calculate the forces: one uses several simplifying assumptions, and the other makes fewer assumptions but is error prone if the data are incorrectly processed. The two methods agree well, suggesting that Saildrone vehicles are suitable for both methods and that the data processing methods work. Our results show that it is important to consider ocean currents, as well as winds, in order to achieve accurate magnitude and direction of the surface forces.
Abstract
Several methods are examined for correction of turbulence and eddy fluxes in the atmospheric boundary layer, two of them based on a potential-flow approach initiated by Wyngaard. If the distorting object is cylindrical or if the distance to the sensor is much greater than the size of the body, the undisturbed wind stress can be calculated solely from measurements made by the sensor itself; no auxiliary measurements or lengthy model calculations are needed. A more general potential-flow correction has been developed in which distorting objects of complex shape are represented as a number of ellipsoidal elements.
These models are applied to data from three turbulence anemometers with differing amounts of flow distortion, operated simultaneously in the Humidity Exchange over the Sea (HEXOS) Main Experiment. The results are compared with wind-stress estimates by the inertial-dissipation technique; these are much less sensitive to local flow distortion and are consistent with the corrected eddy correlation results. From these comparisons it is concluded that the commonly used “tilt correction” is not sufficient to correct eddy wind stress for distortion by nearby objects, such as probe supports and neighboring sensors.
Neither potential-flow method is applicable to distortion by larger bodies of a scale comparable to the measuring height, such as the superstructure of the Meetpost Noordwijk (MPN) platform used in HEXOS. Flow distortion has been measured around a model of MPN in a wind tunnel study. The results were used to correct mean winds, but simulation of distortion effects on turbulence levels and wind stress turned out not to be feasible.
Abstract
Several methods are examined for correction of turbulence and eddy fluxes in the atmospheric boundary layer, two of them based on a potential-flow approach initiated by Wyngaard. If the distorting object is cylindrical or if the distance to the sensor is much greater than the size of the body, the undisturbed wind stress can be calculated solely from measurements made by the sensor itself; no auxiliary measurements or lengthy model calculations are needed. A more general potential-flow correction has been developed in which distorting objects of complex shape are represented as a number of ellipsoidal elements.
These models are applied to data from three turbulence anemometers with differing amounts of flow distortion, operated simultaneously in the Humidity Exchange over the Sea (HEXOS) Main Experiment. The results are compared with wind-stress estimates by the inertial-dissipation technique; these are much less sensitive to local flow distortion and are consistent with the corrected eddy correlation results. From these comparisons it is concluded that the commonly used “tilt correction” is not sufficient to correct eddy wind stress for distortion by nearby objects, such as probe supports and neighboring sensors.
Neither potential-flow method is applicable to distortion by larger bodies of a scale comparable to the measuring height, such as the superstructure of the Meetpost Noordwijk (MPN) platform used in HEXOS. Flow distortion has been measured around a model of MPN in a wind tunnel study. The results were used to correct mean winds, but simulation of distortion effects on turbulence levels and wind stress turned out not to be feasible.
