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Sean Celona, Sophia T. Merrifield, Tony de Paolo, Nate Kaslan, Tom Cook, Eric J. Terrill, and John A. Colosi

Abstract

A method based on machine learning and image processing techniques has been developed to track the surface expression of internal waves in near-real time. X-Band radar scans are first preprocessed and averaged to suppress surface wave clutter and enhance the signal to noise ratio of persistent backscatter features driven by gradients in surface currents. A machine learning algorithm utilizing a support vector machine (SVM) model is then used to classify whether or not the image contains an internal solitary wave (ISW) or internal tide bore (bore). The use of machine learning is found to allow rapid assessment of the large data set, and provides insight on characterizing optimal environmental conditions to allow for radar illumination and detection of ISWs and bores. Radon transforms and local maxima detections are used to locate these features within images that are determined to contain an ISWor bore. The resulting time series of locations is used to create a map of propagation speed and direction that captures the spatiotemporal variability of the ISW or bore in the coastal environment. This technique is applied to 2 months of data collected near Point Sal, California and captures ISW and bore propagation speed and direction information that currently cannot be measured with instruments such as moorings and synthetic aperture radar (SAR).

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Biao Zhang, Yiru Lu, William Perrie, Guosheng Zhang, and Alexis Mouche

Abstract

We have developed C-band compact polarimetry geophysical model functions for RADARSAT Constellation Mission ocean surface wind speed retrieval. A total of 1594 RADARSAT-2 images acquired in quad-polarization SAR imaging mode were collocated with in situ buoy observations. This data set is first used to simulate compact polarimetric data and to examine their dependencies on radar incidence angle and wind vectors. We find that RR-pol radar backscatters are less sensitive to incidence angles and wind directions but are more dependent on wind speeds, compared to RH-, RV-, and RL-pol. Subsequently, the matchup data pairs are used to derive the coefficients of the transfer functions for the proposed compact polarimetric geophysical model functions, and to validate the associated wind speed retrieval accuracy. Statistical comparisons show that the retrieved wind speeds from CMODRH, CMODRV, CMODRL, CMODRR are in good agreement with buoy measurements, with root mean square errors of 1.38, 1.51, 1.47, 1.25 m/s, respectively. The results suggest that compact polarimetry is a good alternative to linear polarization for wind speed retrieval. CMODRR is more appropriate to retrieve high wind speeds than CMODRH, CMODRV or CMODRL.

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Laurence C. Breaker and Dustin Carroll

Abstract

The purpose of this study is to extract more information about the scaling exponents we obtain from sea surface temperature (SST) because their information content is limited to a single value. We examine the application of Empirical Mode Decomposition (EMD) to power law scaling using sea surface temperature (SST) from Scripps Pier, California. The daily observations we employ extend from 1920 to 2009, a period of 90 years. The annual cycle and the long-term trend were first removed. The decomposition produced a total of 15 modes. The scaling exponents were then calculated separately for each mode from the EMD decomposition. We have examined the distribution of scaling exponents with respect to the ensemble, and then with respect to the individual modes for the oceanic processes that we may infer from them. The first three modes are anti-persisitent and contain about a quarter of the total variance. The pattern of modes that was obtained is continuous and relatively smooth beyond mode 3 with increasing values up to mode 8 and generally decreasing values thereafter. The pattern exhibits intramodal correlation, as expected, and intermodal correlation as well. Intermodal correlation is likely due, for the most part, to Long-range Persistence (LRP). Finally, the annual cycle in SST at Scripps Pier is a dominant feature in the record and contains almost 70% of the variance. A method for removing the annual cycle that is not based on removing the mean value is introduced and recommended for future use.

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Daosheng Wang, Haidong Pan, Lin Mu, Xianqing Lv, Bing Yan, and Hua Yang

Abstract

The coastal ocean sea level (SL) variations result from multiscale processes and are dominated by SL changes due to meteorological forcing. In this study, a new methodology, which combines inverted barometer correction and regression analysis (IBR), is developed to estimate the coastal ocean response to meteorological forcing in shallow water. The response is taken as the combination of the static ocean response calculated using the inverted barometer formula and the dynamic ocean response estimated using the multivariable linear regression involving atmospheric pressure and the wind component in the dominant wind orientation. IBR was implemented to estimate the coastal ocean response at two stations, E1 and E2, in Bohai Bay, China. The analyzed results indicate that at both stations, the adjusted SLs are related more to the regional wind, which is the averaged value of ERA-Interim data in Bohai Bay, than to the local wind. The estimated response using IBR with the regional meteorological forcing is much closer to the observed values than other methods, including the classical inverted barometer correction, the dynamic atmospheric correction, the multivariable linear regression, and the IBR with local forcing. The deviations between the observed values and the estimated values using IBR with regional meteorological forcing can be primarily attributed to remote wind. This case study indicates that IBR is a feasible and relatively effective method to estimate the coastal ocean response to meteorological forcing in shallow water.

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Haruhiko Kashiwase, Kay I. Ohshima, Kazuki Nakata, and Takeshi Tamura

Abstract

Long-term quantification of sea ice production in coastal polynyas (thin sea ice areas) is an important issue to understand the global overturning circulation and its changes. The Special Sensor Microwave/Imager (SSM/I), which has nearly 30 years of observation, is a powerful tool for that purpose owing to its ability to detect thin ice areas. However, previous SSM/I thin ice thickness algorithms differ between regions, probably due to the difference in dominant type of thin sea ice in each region. In this study, we developed an SSM/I thin ice thickness algorithm that accounts for three types of thin sea ice (active frazil, thin solid ice, and a mixture of two types), using the polarization and gradient ratios. The algorithm is based on comparison with the ice thickness derived from the MODerate resolution Imaging Spectroradiometer (MODIS) for 22 polynya events off the Ross Ice Shelf, off Cape Darnley, and off the Ronne Ice Shelf in the Southern Ocean. The algorithm can properly discriminate the ice type in coastal polynyas and estimate the thickness of thin sea ice (≤20 cm) with an error range of less than 6 cm. We also confirmed that the algorithm can be applied to other passive microwave radiometers with higher spatial resolution to obtain more accurate and detailed distributions of ice type and thickness. The validation of this algorithm in the Arctic Ocean, suggests its applicability to the global oceans.

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Brian E. Sheppard, Merhala Thurai, Peter Rodriguez, Patrick C. Kennedy, and David R. Hudak

Abstract

The Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar that measures the Doppler velocity spectra from precipitation falling in a small volume near the sensor. The sensor records a 2-D frequency of occurrence matrix of the velocity and power at the mode of each spectrum measured during one minute. The centroid of the distribution of these modes, along with other spectral parameters, defines a data vector input to a Multiple Discriminant Analysis (MDA) for classification of the precipitation type. This requires the a priori determination of a training set for different types, particle size distributions (PSDs), and wind speed conditions. A software model combines POSS system parameters, particle scattering cross section, and terminal velocity models, to simulate the real time Doppler signal measured by the system for different PSDs and wind speeds. This is processed in the same manner as the system hardware to produce bootstrap samples of the modal centroid distributions for the MDA training set. MDA results are compared to images from the Multi-Angle-Snowflake-Camera (MASC) at the MASCRAD site near Easton, Colorado, and to the CSU-CHILL X-Band observations from Greeley, Colorado. In the four case studies presented, POSS successfully identified precipitation transitions through a range of types (rain, graupel, rimed dendrites, aggregates, unrimed dendrites). Also two separate events of hail were reported and confirmed by the images.

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Mohar Chattopadhyay, Will McCarty, and Isaac Moradi

Abstract

Microwave temperature sounders provide key observations in data assimilation, both in the current and historical global observing systems, as they provide the largest amount of horizontal and vertical temperature information due to their insensitivity to clouds. In the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), microwave sounder radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) are assimilated beginning with NOAA-15 and continuing through the current period. The time series of observation minus background statistics for AMSU-A channels sensitive to upper stratosphere and lower mesosphere show variabilities due to changes in AMSU-A constellation in the early AMSU-A period. Noted discrepancies are seen at the onset and exit of AMSU-A observations on the NOAA-15, NOAA-16, NOAA-17, and NASA EOS Aqua satellites. This effort characterizes the sensitivity, both in terms of the observations and the MERRA-2 analysis. Furthermore, it explores the use of reprocessed and inter-calibrated datasets to evaluate whether these homogenized observations can reduce the disparity due to change in instrumental biases against the model background. The results indicate that the AMSU-A radiances used in MERRA-2 are the fundamental cause of this inter-platform sensitivity which can be mitigated by using reprocessed data. The results explore the importance of the reprocessing of the AMSU-A radiances as well as their inter-calibration.

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F. Tornow, C. Domenech, J. N. S. Cole, N. Madenach, and J. Fischer

Abstract

Top-of-atmosphere (TOA) shortwave (SW) angular distribution models (ADMs) approximate – per angular direction of an imagined upward hemisphere – the intensity of sunlight scattered back from a specific Earth-atmosphere scene. ADMs are, thus, critical when converting satellite-borne broadband radiometry into estimated radiative fluxes. This paper applies a set of newly developed ADMs with a more refined scene definition and demonstrates tenable changes in estimated fluxes compared to currently operational ADMs. Newly developed ADMs use a semi-physical framework to consider cloud-top effective radius, R¯e, and above-cloud water vapor, ACWV, in addition to accounting for surface wind speed and clouds’ phase, fraction, and optical depth. In effect, instantaneous TOA SWfluxes for marine liquid-phase clouds had the largest flux differences (of up to 25 W m−2) for lower solar zenith angles and cloud optical depth greater than 10 due to extremes in R¯e or ACWV. In regions where clouds had persistently extreme levels of R¯e (here mostly for R¯e<7μm and R¯e>15μm) or ACWV, instantaneous fluxes estimated from Aqua, Terra, and Meteosat 8 and 9 satellites using the two ADMs differed systematically, resulting in significant deviations in daily mean fluxes (up to ±10 W m−2) and monthly mean fluxes (up to ±5 W m−2). Flux estimates using newly developed, semi-physical ADMs may contribute to a better understanding of solar fluxes over low-level clouds. It remains to be seen whether aerosol indirect effects are impacted by these updates.

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Arnaud Le Boyer, Matthew H. Alford, Nicole Couto, Michael Goldin, Sean Lastuka, Sara Goheen, San Nguyen, Andrew J. Lucas, and Tyler D. Hennon

Abstract

The Epsilometer (“epsi”) is a small (7cm diameter × 30cm long), low-power (0.15 W) and extremely modular microstructure package measuring thermal and kinetic energy dissipation rates, χ and ε. Both the shear probes and FP07 temperature sensors are fabricated in house following techniques developed by Michael Gregg at the Applied Physics Laboratory / University of Washington (APL/UW). Sampling 8 channels (2 shear, 2 temperature, 3-axis accelerometer and a spare for future sensors) at 24 bit precision and 325 Hz, the system can be deployed in standalone mode (battery power and recording to microSD cards) for deployment on autonomous vehicles, wave powered profilers, or it can be used with dropping body termed the “epsi-fish” for profiling from boats, autonomous surface craft or ships with electric fishing reels or other simple winches. The epsi-fish can also be used in real-time mode with the Scripps “fast CTD” winch for fully streaming, altimeter-equipped, line-powered rapid-repeating near-bottom shipboard profiles to 2200 m. Because this winch has a 25ft boom deployable outboard from the ship, contamination by ship wake is reduced 1-2 orders of magnitude in the upper 10-15 m. The noise floor of ε profiles from the epsi-fish is ~ 10−10 W kg−1. This paper describes the fabrication, electronics and characteristics of the system, and documents its performance compared to its predecessor, the APL/UW Modular Microstructure Profiler (MMP).

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Sergey Y. Matrosov

Abstract

Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (Z DR) specific differential phase shift (K DP) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, K DP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.

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