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Yingkai Sha, David John Gagne II, Gregory West, and Roland Stull

Abstract

We present a novel approach for the automated quality control (QC) of precipitation for a sparse station observation network within the complex terrain of British Columbia, Canada. Our QC approach uses convolutional neural networks (CNNs) to classify bad observation values, incorporating a multiclassifier ensemble to achieve better QC performance. We train CNNs using human QC’d labels from 2016 to 2017 with gridded precipitation and elevation analyses as inputs. Based on the classification evaluation metrics, our QC approach shows reliable and robust performance across different geographical environments (e.g., coastal and inland mountains), with 0.927 area under curve (AUC) and type I/type II error lower than 15%. Based on the saliency-map-based interpretation studies, we explain the success of CNN-based QC by showing that it can capture the precipitation patterns around, and upstream of the station locations. This automated QC approach is an option for eliminating bad observations for various applications, including the preprocessing of training datasets for machine learning. It can be used in conjunction with human QC to improve upon what could be accomplished with either method alone.

Open access
Xingru Feng, Junchuan Sun, Dezhou Yang, Baoshu Yin, Guandong Gao, and Weiqi Wan

Abstract

Reasonable parameterization of air–sea momentum flux is important for the accuracy of ocean and atmosphere simulations, and in the numerical model, the parameterization of the air–sea momentum flux becomes a problem of parameterization of the sea surface wind stress drag coefficient (C d). In this study, five kinds of typical C d parameterization methods were assessed in the simulation of two typhoon cases, one of which was a supertyphoon and another was a common severe typhoon, based on an atmosphere–wave–ocean coupled model. Based on the two case studies, it was found that the typhoon path and minimum sea level pressure were not very sensitive to C d parameterizations, though the spatial distribution of C d and its variation with wind speed were all very different across the parameterization methods. However, C d has a significant effect on the wind speed, and at high wind speed, the simulated maximum wind speed compared better with the observation in the experiment that adopted the C d calculation method considering the effects of sea spray. Also, C d plays an important role in the feedback processes between atmosphere and ocean during the typhoon process, through its effect on the air–sea heat and momentum flux, SST, ocean mixed layer depth, ocean currents, etc. The results of this study answered the question of how the C d affects the atmosphere and ocean during the typhoon process, and to what extent they are affected, which can help to explain or even further improve the simulation results.

Open access
Michael O’Malley, Adam M. Sykulski, Romuald Laso-Jadart, and Mohammed-Amin Madoui

Abstract

We provide a novel method for computing the most likely path taken by drifters between arbitrary fixed locations in the ocean. We also provide an estimate of the travel time associated with this path. Lagrangian pathways and travel times are of practical value not just in understanding surface velocities, but also in modeling the transport of oceanborne species such as planktonic organisms and floating debris such as plastics. In particular, the estimated travel time can be used to compute an estimated Lagrangian distance, which is often more informative than Euclidean distance in understanding connectivity between locations. Our method is purely data driven and requires no simulations of drifter trajectories, in contrast to existing approaches. Our method scales globally and can simultaneously handle multiple locations in the ocean. Furthermore, we provide estimates of the error and uncertainty associated with both the most likely path and the associated travel time.

Open access
Simon P. de Szoeke

Abstract

A small integrated oceanographic thermometer with a nominal response time of 1 s was affixed to a floating hose “sea snake” towed near the bow of a research vessel. The sensor measured the near-surface ocean temperature accurately and in agreement with other platforms. The effect of conduction and evaporation is modeled for a sensor impulsively alternated between water and air. Large thermal mass makes most sea snake thermometers insensitive to temperature impulses. The smaller 1-s thermometer cooled by evaporation, but the sensor never reached the wet-bulb temperature. The cooling was less than 6% of the (~2.7°C) difference between the ocean temperature and the wet-bulb temperature in 99% of 2-s−1 samples. Filtering outliers, such as with a median, effectively removes the evaporative cooling effect from 1- or 10-min average temperatures.

Open access
Matthew L. Walker McLinden, Lihua Li, Gerald M. Heymsfield, Michael Coon, and Amber Emory

Abstract

The NASA Goddard Space Flight Center’s (GSFC’s) W-band (94 GHz) Cloud Radar System (CRS) has been comprehensively updated to modern solid-state and digital technology. This W-band (94 GHz) radar flies in nadir-pointing mode on the NASA ER-2 high-altitude aircraft, providing polarimetric reflectivity and Doppler measurements of clouds and precipitation. This paper describes the design and signal processing of the upgraded CRS. It includes details on the hardware upgrades [solid-state power amplifier (SSPA) transmitter, antenna, and digital receiver] including a new reflectarray antenna and solid-state transmitter. It also includes algorithms, including internal loop-back calibration, external calibration using a direct relationship between volume reflectivity and the range-integrated backscatter of the ocean, and a modified staggered–pulse repetition frequency (PRF) Doppler algorithm that is highly resistant to unfolding errors. Data samples obtained by upgraded CRS through recent NASA airborne science missions are provided.

Restricted access
Minjie Xu, Yuzhe Wang, Shuya Wang, Xianqing Lv, and Xu Chen

Abstract

Sufficient and accurate tide data are essential for analyzing physical processes in the ocean. A method is developed to spatially fit the tidal amplitude and phase lag data along satellite altimeter tracks near Hawaii and construct reliable cotidal charts by using the Chebyshev polynomials. The method is completely dependent on satellite altimeter data. By using the cross-validation method, the optimal orders of Chebyshev polynomials are determined and the polynomial coefficients are calculated by the least squares method. The tidal amplitudes and phase lags obtained by the method are compared with those from the Finite Element Solutions 2014 (FES2014), National Astronomical Observatory 99b (NAO.99b), and TPXO9 models. Results indicate that the method yields accurate results as its fitting results are consistent with the harmonic constants of the three models. The feasibility of this method is also validated by the harmonic constants from tidal gauges near Hawaii.

Restricted access
I. A. Houghton, P. B. Smit, D. Clark, C. Dunning, A. Fisher, N. J. Nidzieko, P. Chamberlain, and T. T. Janssen

Abstract

A distributed sensor network of over 100 free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019. The Spotter buoys used in the network represent a next-generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature. Large distributed sensor networks like these provide much needed long-dwell sensing capabilities in open-ocean regions. Despite the demand for better weather forecasts and climate data in the oceans, direct in situ measurements of marine surface weather (waves, winds, currents) remain exceedingly sparse in the open oceans. Because of the large expanse of Earth’s oceans, distributed paradigms are necessary to create sufficient data density at global scale, similar to advances in sensing on land and in space. Here we discuss initial findings from this long-dwell open-ocean distributed sensor network. Through triple-collocation analysis, we determine errors in collocated satellite-derived observations and model estimates. The correlation analysis shows that the Spotter network provides wave height data with lower errors than both satellites and models. The wave spectrum was also further used to infer wind speed. Buoy drift dynamics are similar to established drogued drifters, particularly when accounting for windage. We find a windage correction factor for the Spotter buoy of approximately 1%, which is in agreement with theoretical estimates. Altogether, we present a completely new open-ocean weather dataset and characterize the data quality against other observations and models to demonstrate the broad value for ocean monitoring and forecasting that can be achieved using large-scale distributed sensor networks in the oceans.

Open access
Amy K. Huff, Shobha Kondragunta, Hai Zhang, Istvan Laszlo, Mi Zhou, Vanessa Caicedo, Ruben Delgado, and Robert Levy

Abstract

Aerosol optical depth (AOD) retrieved from the GOES-16 Advanced Baseline Imager (ABI) was used to track a smoke plume from a prescribed fire in northeastern Virginia on 8 March 2020. Weather and atmospheric conditions created a favorable environment to transport the plume through the Washington, D.C., and Baltimore, Maryland, metro areas in the afternoon and concentrate smoke near the surface, degrading air quality for several hours. ABI AOD with 5-min temporal resolution and 2-km spatial resolution definitively identified the timing and geographic extent of the plume during daylight hours. Comparison to AERONET AOD indicates that ABI AOD captured the relative change in AOD due to passage of the smoke, with a mean absolute error of 0.047. Ground-based measurements of fine particulate matter (PM2.5) confirm deteriorations in air quality coincident with the progression of the smoke. Ceilometer aerosol backscatter profiles verify plume transport timing and indicate that smoke aerosols were well mixed in a shallow boundary layer. This event illustrates the advantages of using multiple datasets to analyze the impacts of aerosols on ambient air quality. Given the quickly evolving nature of the event over several hours, ABI AOD provided information for the public and decision-makers that was not available from any other source, including polar-orbiting satellite sensors. This study suggests that PM2.5 concentrations estimated from ABI AOD can be used to fill in the gaps in nationwide regulatory PM2.5 monitor networks and may be a valuable addition to EPA’s PM2.5 NowCast of current air quality conditions.

Restricted access
Ganesh Gopalakrishnan, Bruce D. Cornuelle, Matthew R. Mazloff, Peter F. Worcester, and Matthew A. Dzieciuch

Abstract

A strongly nonlinear eddy field is present in and around the Subtropical Countercurrent in the Northern Philippine Sea (NPS). A regional implementation of the Massachusetts Institute of Technology general circulation model–Estimating the Circulation and Climate of the Ocean four-dimensional variational (MITgcm-ECCO 4DVAR) assimilation system is found to be able to produce a series of two-month-long dynamically-consistent optimized state estimates between April 2010 and April 2011 for the eddy-rich NPS region. The assimilation provides a stringent dynamical test of the model, showing that a free run of the model forced using adjusted controls remains consistent with the observations for two months. The 4DVAR iterative optimization reduced the total cost function for the observations and controls by 40–50% from the reference solution, initialized using the Hybrid Coordinate Ocean Model 1/12° global daily analysis, achieving residuals approximately equal to the assumed uncertainties for the assimilated observations. The state estimates are assessed by comparing with assimilated and withheld observations and also by comparing one-month model forecasts with future data. The state estimates and forecasts were more skillful than model persistence and the reference solutions. Finally, the continuous state estimates were used to detect and track the eddies, analyze their structure, and quantify their vertically-integrated meridional heat and salt transports.

Restricted access
Giuseppe Zibordi, Brent N. Holben, Marco Talone, Davide D’Alimonte, Ilya Slutsker, David M. Giles, and Mikhail G. Sorokin

Abstract

The Ocean Color Component of the Aerosol Robotic Network (AERONET-OC) supports activities related to ocean color such as validation of satellite data products, assessment of atmospheric correction schemes, and evaluation of bio-optical models through globally distributed standardized measurements of water-leaving radiance and aerosol optical depth. In view of duly assisting the AERONET-OC data user community, this work (i) summarizes the latest investigations on a number of scientific issues related to above-water radiometry, (ii) emphasizes the network expansion that from 2002 until the end of 2020 integrated 31 effective measurement sites, (iii) shows the equivalence of data product accuracy across sites and time for measurements performed with different instrument series, (iv) illustrates the variety of water types represented by the network sites ensuring validation activities across a diversity of observation conditions, and (v) documents the availability of water-leaving radiance data corrected for bidirectional effects by applying a method specifically developed for chlorophyll-a-dominated waters and an alternative one that is likely suitable for any water type.

Open access