Journal of Atmospheric and Oceanic Technology

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-404masthead

Bertossa, Cameron; L’Ecuyer, Tristan; Merrelli, Aronne; Huang, Xianglei; Chen, Xiuhong

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0023.1

AbstractThe Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) will fill a gap in our understanding of polar processes and the polar climate by offering widespread, spectrally resolved measurements through the far-infrared (FIR) with two identical CubeSat spacecraft. While the polar regions are typically difficult for skillful cloud identification due to cold surface temperatures, the reflection by bright surfaces, and frequent temperature inversions, the inclusion of the FIR may offer increased spectral sensitivity, allowing for the detection of even thin ice clouds. This study assesses the potential skill, as well as limitations, of a neural network (NN)-based cloud mask using simulated spectra mimicking what the PREFIRE mission will capture. Analysis focuses on the polar regions. Clouds are found to be detected approximately 90% of time using the derived neural network. The NN’s assigned confidence for whether a scene is “clear” or “cloudy” proves to be a skillful way in which quality flags can be attached to predictions. Clouds with higher cloud-top heights are typically more easily detected. Low-altitude clouds over polar surfaces, which are the most difficult for the NN to detect, are still detected over 80% of the time. The FIR portion of the spectrum is found to increase the detection of clear scenes and increase mid- to high-altitude cloud detection. Cloud detection skill improves through the use of the overlapping fields of view produced by the PREFIRE instrument’s sampling strategy. Overlapping fields of view increase accuracy relative to the baseline NN while simultaneously predicting on a sub-FOV scale.Significance StatementClouds play an important role in defining the Arctic and Antarctic climates. The purpose of this study is to explore the potential of never-before systematically measured radiative properties of the atmosphere to aid in the detection of polar clouds, which are traditionally difficult to detect. Satellite measurements of emitted radiation at wavelengths longer than 15 μm, combined with complex machine learning methods, may allow us to better understand the occurrence of various cloud types at both poles. The occurrence of these clouds can determine whether the surface warms or cools, influencing surface temperatures and the rate at which ice melts or refreezes. Understanding the frequencies of these various clouds is increasingly important within the context of our rapidly changing climate.

Lv, Kaiyun; Yang, Weifeng; Chen, Zhiping; Xia, Pengfei; He, Xiaoxing; Chen, Zhigao; Lu, Tieding

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0111.1

AbstractZenith hydrostatic delay (ZHD) is a crucial parameter in Global Navigation Satellite System (GNSS) navigation and positioning and GNSS meteorology. Since the Saastamoinen ZHD model has a larger error in China, it is significant to improve the Saastamoinen ZHD model. This work first estimated the Saastamoinen model using the integrated ZHD as reference values obtained from radiosonde data collected at 73 stations in China from 2012 to 2016. Then, the residuals between the reference values and the Saastamoinen modeled ZHDs were calculated, and the correlations between the residuals and meteorological parameters were explored. The continuous wavelet transform method was used to recognize the annual and semiannual characteristics of the residuals. Because of the nonlinear variation characteristics of residuals, the nonlinear least squares estimation method was introduced to establish an improved ZHD model—China Revised Zenith Hydrostatic Delay (CRZHD)—adapted for China. The accuracy of the CRZHD model was assessed using radiosonde data and International GNSS Service (IGS) data in 2017; the radiosonde data results show that the CRZHD model is superior to the Saastamoinen model with a 69.6% improvement. The three IGS stations with continuous meteorological data present that the BIAS and RMSE are decreased by 2.7 and 1.5 (URUM), 5.9 and 5.3 (BJFS), and 9.6 and 8.8 mm (TCMS), respectively. The performance of the CRZHD model retrieving PWV was discussed using radiosonde data in 2017. It is shown that the CRZHD model retrieving PWV (CRZHD-PWV) outperforms the Saastamoinen model (SAAS-PWV), in which the precision is improved by 44.4%. The BIAS ranged from −1 to 1 mm and RMSE ranged from 0 to 2 mm in CRZHD-PWV account for 89.0% and 95.9%, while SAAS-PWV account for 46.6% and 58.9%.Significance StatementZenith hydrostatic delay (ZHD) is one of the most important parameters in Global Navigation Satellite System (GNSS) navigation and positioning and GNSS meteorology, which can be derived from a precise ZHD model due to its stability. This research established an improved ZHD model for China to obtain accurate ZHD, which is a prerequisite for pinpoint precipitable water vapor (PWV) retrieval. And the PWV value is beneficial to analyze the change in precipitation in some regions, forecast the short-term rainfall, and monitor the climate.

Cazzaniga, Ilaria; Zibordi, Giuseppe

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0061.1

AbstractThe Ocean Color Component of the Aerosol Robotic Network (AERONET-OC) aims at supporting the assessment of satellite ocean color radiometric products with in situ reference data derived from automated above-water measurements. This study, applying metrology principles and taking advantage of recent technology and science advances, revisits the uncertainty estimates formerly provided for AERONET-OC normalized water-leaving radiances LWN. The new uncertainty values are quantified for a number of AERONET-OC sites located in marine regions representative of chlorophyll-a-dominated waters (i.e., Case 1) and a variety of optically complex waters. Results show uncertainties typically increasing with the optical complexity of water and wind speed. Relative and absolute uncertainty values are provided for the various sites together with contributions from each source of uncertainty affecting measurements. In view of supporting AERONET-OC data users, the study also suggests practical solutions to quantify uncertainties for LWN from its spectral values. Additionally, results from an evaluation of the temporal variability characterizing LWN at various AERONET-OC sites are presented to address the impact of temporal mismatches between in situ and satellite data in matchup analysis.

Cropper, Thomas E.; Berry, David I.; Cornes, Richard C.; Kent, Elizabeth C.

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0080.1

AbstractMarine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the vessels. This makes unadjusted daytime observations unsuitable for many applications including for the monitoring of long-term temperature change over the oceans. In this paper a physics-based approach is used to estimate this heating bias in ship observations from ICOADS. Under this approach, empirically determined coefficients represent the energy transfer terms of a heat budget model that quantifies the heating bias and is applied as a function of cloud cover and the relative wind speed over individual ships. The coefficients for each ship are derived from the anomalous diurnal heating relative to nighttime air temperature. Model coefficients, cloud cover, and relative wind speed are then used to estimate the heating bias ship by ship and generate nighttime-equivalent time series. A variety of methodological approaches were tested. Application of this method enables the inclusion of some daytime observations in climate records based on marine air temperatures, allowing an earlier start date and giving an increase in spatial coverage compared to existing records that exclude daytime observations.Significance StatementCurrently, the longest available record of air temperature over the oceans starts in 1880. We present an approach that enables observations of air temperatures over the oceans to be used in the creation of long-term climate records that are presently excluded. We do this by estimating the biases inherent in daytime temperature reports from ships, and adjust for these biases by implementing a numerical heat-budget model. The adjustment can be applied to the variety of ship types present in observational archives. The resulting adjusted temperatures can be used to create a more spatially complete record over the oceans, that extends further back in time, potentially into the late eighteenth century.

Fitzgerald, Brian J.; Broccolo, J.; Garrett, K.

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0054.1

AbstractThe Mount Washington Observatory Regional Mesonet (MWRM) is a network of 18 remote meteorological monitoring stations (as of 2022), including the Auto Road Vertical Profile (ARVP), located across the White Mountains of northern New Hampshire. Each station measures temperature and relative humidity, with additional variables at many locations. All stations need to withstand the frequent combination of intense cold, high precipitation amounts, icing, and hurricane-force winds in a mountain environment. Due to these challenges, the MWRM employs rugged instrumentation, an innovative radio-communications relay approach, and carefully selected sites that balance ideal measuring environments with station survivability. Data collected from the MWRM are used operationally by forecasters (including Mount Washington Observatory and National Weather Service staff) to validate model guidance, by alpine and climate scientists, by recreationalists accessing conditions in the backcountry, by groups operating on the mountain (Cog Railway, toll Auto Road), and by search and rescue organizations. This paper provides a detailed description of the network, with emphasis on how the challenging climate and terrain of this mountain region impacts sensor selection, site maintenance, and overall operation.Significance StatementThe mountain environment is a heterogeneous landscape, and interactions between the atmosphere and terrain can cause a wide variety of conditions across time and space. Our network of remote stations at different elevations across the White Mountains allows data users to understand how the weather varies spatially across the mountain range where conditions on higher peaks can be drastically, and dangerously, different. Sharing information about the MWRM can help other groups establish networks in similar challenging environments, and broaden our understanding of weather and climate in mountainous regions.

Huang, Boyin; Yin, Xungang; Carton, James A.; Chen, Ligang; Graham, Garrett; Liu, Chunying; Smith, Thomas; Zhang, Huai-Min

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0081.1

AbstractOur study shows that the intercomparison among sea surface temperature (SST) products is influenced by the choice of SST reference, and the interpolation of SST products. The influence of reference SST depends on whether the reference SSTs are averaged to a grid or in pointwise in situ locations, including buoy or Argo observations, and filtered by first-guess or climatology quality control (QC) algorithms. The influence of the interpolation depends on whether SST products are in their original grids or preprocessed into common coarse grids. The impacts of these factors are demonstrated in our assessments of eight widely used SST products (DOISST, MUR25, MGDSST, GAMSSA, OSTIA, GPB, CCI, CMC) relative to buoy observations: (i) when the reference SSTs are averaged onto 0.25° × 0.25° grid boxes, the magnitude of biases is lower in DOISST and MGDSST (<0.03°C), and magnitude of root-mean-square differences (RMSDs) is lower in DOISST (0.38°C) and OSTIA (0.43°C); (ii) when the same reference SSTs are evaluated at pointwise in situ locations, the standard deviations (SDs) are smaller in DOISST (0.38°C) and OSTIA (0.39°C) on 0.25° × 0.25° grids; but the SDs become smaller in OSTIA (0.34°C) and CMC (0.37°C) on products’ original grids, showing the advantage of those high-resolution analyses for resolving finer-scale SSTs; (iii) when a loose QC algorithm is applied to the reference buoy observations, SDs increase; and vice versa; however, the relative performance of products remains the same; and (iv) when the drifting-buoy or Argo observations are used as the reference, the magnitude of RMSDs and SDs become smaller, potentially due to changes in observing intervals. These results suggest that high-resolution SST analyses may take advantage in intercomparisons.Significance StatementIntercomparisons of gridded SST products be affected by how the products are compared with in situ observations: whether the products are in coarse (0.25°) or original (0.05°–0.10°) grids, whether the in situ SSTs are in their reported locations or gridded and how they are quality controlled, and whether the biases of satellite SSTs are corrected by localized matchups or large-scale patterns. By taking all these factors into account, our analyses indicate that the NOAA DOISST is among the best SST products for the long period (1981–present) and relatively coarse (0.25°) resolution that it was designed for.

Harrison, Trevor W.; Clemett, Nate; Polagye, Brian; Thomson, Jim

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0034.1

AbstractTidal currents, particularly in narrow channels, can be challenging to characterize due to high current speeds (>1 m s−1), strong spatial gradients, and relatively short synoptic windows. To assess tidal currents in Agate Pass, Washington, we cross evaluated data products from an array of acoustically tracked underwater floats and from acoustic Doppler current profilers (ADCPs) in both station-keeping and drifting modes. While increasingly used in basin-scale science, underwater floats have seen limited use in coastal environments. This study presents the first application of a float array toward small-scale (<1 km), high-resolution (<5 m) measurements of mean currents in energetic tidal channel and utilizes a new prototype float, the μFloat, designed specifically for sampling in dynamic coastal waters. We show that a float array (20 floats) can provide data with similar quality to ADCPs, with measurements of horizontal velocity differing by less than 10% of nominal velocity, except during periods of low flow (0.1 m s−1). Additionally, floats provided measurements of the three-dimensional temperature field, demonstrating their unique ability to simultaneously resolve in situ properties that cannot be remotely observed.Significance StatementThe purpose of this research was to validate measurements of tidal currents in a fast-flowing tidal channel using a prototype technology composed of 20 drifting underwater sensors called μFloats (“microFloats”) and five surface buoys against standard devices (acoustic Doppler current profilers). Float measurements matched those from the standard devices within 10% of the mean water speed and simultaneously provided three-dimensional mapping of temperature in the test region. Results demonstrate how moderate numbers of simultaneously deployed μFloats can provide high-resolution sensing capacity that will improve our understanding of physical, chemical, and biological processes in coastal waters.

Zhang, Yibo; Jiao, Shengyi; Wang, Yuzhe; Wang, Yonggang; Lv, Xianqing

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0052.1

AbstractThe Chebyshev polynomial fitting (CPF) method has been proved to be effective to construct reliable cotidal charts for the eight major tidal constituents (M2, S2, K1, O1, N2, K2, P1, and Q1) and six minor tidal constituents (2N2, J1, L2, Mu2, Nu2, and T2) near Hawaii in Part I and Part II, respectively. In this paper, this method is extended to estimate the harmonic constants of four long-period tidal constituents (Mf, Mm, Sa, and Ssa). The harmonic constants obtained by this method were compared with those from the TPXO9, Finite Element Solutions 2014 (FES2014), and Empirical Ocean Tide 20 (EOT20) models, using benchmark data from satellite altimeters and eight tide gauges. The accuracies of the Mf and Mm constituents derived from the CPF method are comparable to those from the models, but the accuracies of the Sa and Ssa constituents are significantly higher than those from the FES2014 and EOT20 models. The results indicate that the CPF method is also effective for estimating harmonic constants of long-period tidal constituents. Furthermore, since the CPF method relies only on satellite altimeter data, it is an easier-to-use method than these ocean tide models.

Reeves Eyre, J. E. Jack; Cronin, Meghan F.; Zhang, Dongxiao; Thompson, Elizabeth J.; Fairall, Christopher W.; Edson, James B.

2023 Journal of Atmospheric and Oceanic Technology

doi: 10.1175/jtech-d-22-0077.1

AbstractHigh-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 StatementWe 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.