A New Algorithm for Simultaneous Retrieval of Aerosols and Marine Parameters

We present an algorithm for simultaneous retrieval of aerosol and marine parameters in coastal waters. The algorithm is based on a radiative transfer forward model for a coupled atmosphere-ocean system, which is used to train a radial basis function neural network (RBF-NN) to obtain a fast and accurate method to compute radiances at the top of the atmosphere (TOA) for given aerosol and marine input parameters. The inverse modelling algorithm employs multidimensional unconstrained non-linear optimization to retrieve three marine parameters (concentrations of chlorophyll and mineral particles, as well as absorption by coloured dissolved organic matter (CDOM)), and two aerosol parameters (aerosol fine-mode fraction and aerosol volume fraction). We validated the retrieval algorithm using synthetic data and found it, for both low and high sun, to predict each of the five parameters accurately, both with and without white noise added to the top of the atmosphere (TOA) radiances. When varying the solar zenith angle (SZA) and retraining the RBF-NN without noise added to the TOA radiance, we found the algorithm to predict the CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction with correlation coefficients greater than 0.72, 0.73, 0.93, 0.67, and 0.87, respectively, for 45∘≤ SZA ≤ 75∘. By adding white Gaussian noise to the TOA radiances with varying values of the signal-to-noise-ratio (SNR), we found the retrieval algorithm to predict CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction well with correlation coefficients greater than 0.77, 0.75, 0.91, 0.81, and 0.86, respectively, for high sun and SNR ≥ 95.

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IAP-AACM v1.0： Global to regional evaluation of the atmospheric chemistry model in CAS-ESM

10.5194/acp-2018-1007 ◽

2018 ◽

Author(s):

Ying Wei ◽

Xueshun Chen ◽

Huansheng Chen ◽

Jie Li ◽

Zifa Wang ◽

...

Keyword(s):

East Asia ◽

Spatial Variation ◽

Atmospheric Chemistry ◽

Comprehensive Evaluation ◽

Correlation Coefficients ◽

Full Description ◽

Atmospheric Physics ◽

Temporal And Spatial Variability ◽

Fine Mode ◽

Aerosol Effects

Abstract. In this study, a full description and comprehensive evaluation of a global-regional nested model, the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics (IAP-AACM), is presented for the first time. Not only the global budgets and distribution, but also a comparison of nested simulation over China against multi-datasets are investigated, benefiting from the access of air quality monitoring data in China since 2013 and the Model Inter-Comparison Study for Asia project. The model results and analysis can greatly help reduce uncertainties and understand model diversity in assessing global and regional aerosol effects, especially over East Asia and areas affected by East Asia. The 1-year simulation for 2014 shows that the IAP-AACM is within the range of other models, and well reproduces both spatial distribution and seasonal variation of trace gases and aerosols over major continents and oceans (mostly within the factor of two). The model nicely captures spatial variation for carbon monoxide except an underestimation over the ocean that also shown in other models, which suggests the need for more accurate emission rate of ocean source. For aerosols, the simulation of fine-mode particulate matter (PM2.5) matches observation well and it has a better simulating ability on primary aerosols than secondary aerosols. This calls for more investigation on aerosol chemistry. Furthermore, IAP-AACM shows the superiority of global model, compared with regional model, on performing regional transportation for the nested simulation over East Asia. For the city evaluation over China, the model reproduces variation of sulfur dioxide (SO2), nitrogen dioxide (NO2) and PM2.5 accurately in most cities, with correlation coefficients above 0.5. Compared to the global simulation, the nested simulation exhibits an improved ability to capture the high temporal and spatial variability over China. In particular, the correlation coefficients for PM2.5, SO2 and NO2 are raised by ~ 0.25, ~ 0.15 and ~ 0.2 respectively in the nested grid. The summary provides constructive information for the application of chemical transport models. In future, we recommend the model's ability to capture high spatial variation of PM2.5 is yet to be improved.

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A Robust Dual-Frequency Radar Profiling Algorithm

Journal of Applied Meteorology and Climatology ◽

10.1175/2011jamc2655.1 ◽

2011 ◽

Vol 50 (7) ◽

pp. 1543-1557 ◽

Cited By ~ 25

Author(s):

Mircea Grecu ◽

Lin Tian ◽

William S. Olson ◽

Simone Tanelli

Keyword(s):

Synthetic Data ◽

Optimization Procedure ◽

Correction Method ◽

Single Frequency ◽

Retrieval Algorithm ◽

Dual Frequency ◽

Ka Band ◽

Radar Observations ◽

Distribution Shape ◽

Ku Band

AbstractIn this study, an algorithm to retrieve precipitation from spaceborne dual-frequency (13.8 and 35.6 GHz, or Ku/Ka band) radar observations is formulated and investigated. Such algorithms will be of paramount importance in deriving radar-based and combined radar–radiometer precipitation estimates from observations provided by the forthcoming NASA Global Precipitation Measurement (GPM) mission. In GPM, dual-frequency Ku-/Ka-band radar observations will be available only within a narrow swath (approximately one-half of the width of the Ku-band radar swath) over the earth’s surface. Therefore, a particular challenge is to develop a flexible radar retrieval algorithm that can be used to derive physically consistent precipitation profile estimates across the radar swath irrespective of the availability of Ka-band radar observations at any specific location inside that swath, in other words, an algorithm capable of exploiting the information provided by dual-frequency measurements but robust in the absence of Ka-band channel. In the present study, a unified, robust precipitation retrieval algorithm able to interpret either Ku-only or dual-frequency Ku-/Ka-band radar observations in a manner consistent with the information content of the observations is formulated. The formulation is based on 1) a generalized Hitschfeld–Bordan attenuation correction method that yields generic Ku-only precipitation profile estimates and 2) an optimization procedure that adjusts the Ku-band estimates to be physically consistent with coincident Ka-band reflectivity observations and surface reference technique–based path-integrated attenuation estimates at both Ku and Ka bands. The algorithm is investigated using synthetic and actual airborne radar observations collected in the NASA Tropical Composition, Cloud, and Climate Coupling (TC4) campaign. In the synthetic data investigation, the dual-frequency algorithm performed significantly better than a single-frequency algorithm; dual-frequency estimates, however, are still sensitive to various assumptions such as the particle size distribution shape, vertical and cloud water distributions, and scattering properties of the ice-phase precipitation.

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Assessing the Skills of a Seasonal Forecast of Chlorophyll in the Global Pelagic Oceans

Remote Sensing ◽

10.3390/rs13061051 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1051

Author(s):

Cecile S. Rousseaux ◽

Watson W. Gregg ◽

Lesley Ott

Keyword(s):

Ocean Circulation ◽

North Atlantic ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Chlorophyll Concentration ◽

Correlation Coefficients ◽

Global Scale ◽

Seasonal Forecasts ◽

Mean Square Errors ◽

Satellite Chlorophyll

While forecasts of atmospheric variables, and to a lesser degree ocean circulation, are relatively common, the forecast of biogeochemical conditions is still in its infancy. Using a dynamical ocean biogeochemical forecast forced by seasonal forecasts of atmospheric and physical ocean variables, we produce seasonal predictions of chlorophyll concentration at the global scale. Results show significant Anomaly Correlation Coefficients (ACCs) for the majority of regions (11 out of the 12 regions for the 1-month lead forecast). Root mean square errors are smaller (<0.05 µg chlorophyll (chl) L−1) in the Equatorial regions compared to the higher latitudes (range from 0.05 up to 0.13 µg chl L−1). The forecast for all regions except three (North Atlantic, South Pacific and North Indian) are within the Semi-Interquartile Range of the satellite chlorophyll concentration (Suomi-National Polar-orbiting Partnership (NPP), 27.9%). This suggests the potential for skillful global biogeochemical forecasts on seasonal timescales of chlorophyll, primary production and harmful algal blooms that could support fisheries management and other applications.

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Estimating cloud optical thickness and associated surface UV irradiance from SEVIRI by implementing a semi-analytical cloud retrieval algorithm

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-7961-2012 ◽

2012 ◽

Vol 12 (17) ◽

pp. 7961-7975 ◽

Cited By ~ 7

Author(s):

P. Pandey ◽

K. De Ridder ◽

D. Gillotay ◽

N. P. M. van Lipzig

Keyword(s):

Optical Thickness ◽

Correlation Coefficients ◽

Retrieval Algorithm ◽

Satellite Mission ◽

Spectral Bands ◽

Uv Irradiance ◽

Intercomparison Exercises ◽

Cloud Optical Thickness ◽

Mean Square Difference ◽

Good Agreement

Abstract. In this paper, we describe the implementation of the Semi-Analytical Cloud Retrieval Algorithm (SACURA), to obtain scaled cloud optical thickness (SCOT) from satellite imagery acquired with the SEVIRI instrument and surface UV irradiance levels. In estimation of SCOT particular care is given to the proper specification of the background (i.e. cloud-free) spectral albedo and the retrieval of the cloud water phase from reflectance ratios in SEVIRI's 0.6 μm and 1.6 μm spectral bands. The SACURA scheme is then applied to daytime SEVIRI imagery over Europe, for the month of June 2006, at 15-min time increments. The resulting SCOT fields are compared with values obtained by the CloudSat experimental satellite mission, yielding a negligible bias, correlation coefficients ranging from 0.51 to 0.78, and a root mean square difference of 1 to 2 SCOT increments. These findings compare favourably to results from similar intercomparison exercises reported in the literature. Based on the retrieved SCOT from SEVIRI and radiative transfer modelling approach, simple parameterisations are proposed to estimate the surface UV-A and UV-B irradiance. The validation of the modelled UV-A and UV-B irradiance against the measurements over two Belgian stations, Redu and Ostend, indicate good agreement with the high correlation, index of agreement and low bias. The SCOT fields estimated by implementing SACURA on imagery from geostationary satellite are reliable and its impact on surface UV irradiance levels is well produced.

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Its What’s on the Inside That Counts: An Effective, Efficient, and Streamlined Method for Quantification of Octocoral Symbiodiniaceae and Chlorophyll

Frontiers in Marine Science ◽

10.3389/fmars.2021.710730 ◽

2021 ◽

Vol 8 ◽

Author(s):

Rosemary Kate Steinberg ◽

Emma L. Johnston ◽

Teresa Bednarek ◽

Katherine A. Dafforn ◽

Tracy D. Ainsworth

Keyword(s):

Protein Content ◽

Surface Area ◽

Water Movement ◽

Chlorophyll Concentration ◽

Dry Weight ◽

Accurate Method ◽

Host Protein ◽

Biomass Composition ◽

Wet Weight ◽

Chlorophyll Concentrations

Ocean warming driven bleaching is one of the greatest threats to zooxanthellate cnidarians in the Anthropocene. Bleaching is the loss of Symbiodiniaceae, chlorophyll, or both from zooxanthellate animals. To quantify bleaching and recovery, standardised methods for quantification of Symbiodiniaceae and chlorophyll concentrations have been developed for reef-building scleractinian corals, but no such standard method has been developed for octocorals. For stony corals, quantification of Symbiodiniaceae and chlorophyll concentrations often relies on normalisation to skeletal surface area or unit of biomass [i.e., protein, ash-free dry weight (AFDW)]. Stiff octocorals do not change their volume, as such studies have used volume and surface area to standardise densities, but soft-bodied octocorals can alter their size using water movement within the animal; therefore, Symbiodiniaceae and chlorophyll cannot accurately be measured per unit of surface area and are instead measured in units of Symbiodiniaceae and chlorophyll per μg of host protein or AFDW. Though AFDW is more representative of the full biomass composition than host protein, AFDW is more time and resource intensive. Here, we provide a streamlined methodology to quantify Symbiodiniaceae density, chlorophyll concentration, and protein content in soft-bodied octocorals. This technique uses minimal equipment, does not require freeze-drying or burning samples to obtain ash weight, and is effective for down to 0.2 g wet tissue. Bulk samples can be centrifuged, the Symbiodiniaceae pellet washed, and the supernatant saved for protein analysis. This efficient technique allows for clean, easy to count samples of Symbiodiniaceae with minimal animal protein contamination. Chlorophyll a and c2 extractions occurs at different rates, with chlorophyll a taking 24 h to extract completely at 4°C and chlorophyll c2 taking 48 h. Finally, we found that where necessary, wet weight may be used as a proxy for protein content, but the correlation of protein and wet weight varies by species and protein should be used when possible. Overall, we have created a rapid and accurate method for quantification of bleaching markers in octocorals.

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High-resolution seismic velocity analysis by sign-based weighted semblance

Geophysics ◽

10.1190/geo2021-0173.1 ◽

2021 ◽

pp. 1-35

Author(s):

M. Javad Khoshnavaz

Keyword(s):

Seismic Velocity ◽

Resolution Enhancement ◽

Synthetic Data ◽

Correlation Coefficients ◽

Velocity Model ◽

Seismic Attenuation ◽

Velocity Analysis ◽

Velocity Models ◽

Amplitude Versus Offset ◽

Amplitude Versus

Building an accurate velocity model plays a vital role in routine seismic imaging workflows. Normal-moveout-based seismic velocity analysis is a popular method to make the velocity models. However, traditional velocity analysis methodologies are not generally capable of handling amplitude variations across moveout curves, specifically polarity reversals caused by amplitude-versus-offset anomalies. I present a normal-moveout-based velocity analysis approach that circumvents this shortcoming by modifying the conventional semblance function to include polarity and amplitude correction terms computed using correlation coefficients of seismic traces in the velocity analysis scanning window with a reference trace. Thus, the proposed workflow is suitable for any class of amplitude-versus-offset effects. The approach is demonstrated to four synthetic data examples of different conditions and a field data consisting a common-midpoint gather. Lateral resolution enhancement using the proposed workflow is evaluated by comparison between the results from the workflow and the results obtained by the application of conventional semblance and three semblance-based velocity analysis algorithms developed to circumvent the challenges associated with amplitude variations across moveout curves, caused by seismic attenuation and class II amplitude-versus-offset anomalies. According to the obtained results, the proposed workflow is superior to all the presented workflows in handling such anomalies.

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Description of a formaldehyde retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS)

Atmospheric Measurement Techniques ◽

10.5194/amt-12-3551-2019 ◽

2019 ◽

Vol 12 (7) ◽

pp. 3551-3571 ◽

Cited By ~ 2

Author(s):

Hyeong-Ahn Kwon ◽

Rokjin J. Park ◽

Gonzalo González Abad ◽

Kelly Chance ◽

Thomas P. Kurosu ◽

...

Keyword(s):

Optical Absorption ◽

Absorption Spectroscopy ◽

Cross Sections ◽

Correlation Coefficients ◽

Optical Absorption Spectroscopy ◽

Retrieval Algorithm ◽

Environment Monitoring ◽

Ozone Monitoring Instrument ◽

Nonlinear Fitting ◽

Regression Slopes

Abstract. We describe a formaldehyde (HCHO) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) that will be launched by the Korean Ministry of Environment in 2019. The algorithm comprises three steps: preprocesses, radiance fitting, and postprocesses. The preprocesses include a wavelength calibration, as well as interpolation and convolution of absorption cross sections; radiance fitting is conducted using a nonlinear fitting method referred to as basic optical absorption spectroscopy (BOAS); and postprocesses include air mass factor calculations and bias corrections. In this study, several sensitivity tests are conducted to examine the retrieval uncertainties using the GEMS HCHO algorithm. We evaluate the algorithm with the Ozone Monitoring Instrument (OMI) Level 1B irradiance/radiance data by comparing our retrieved HCHO column densities with OMI HCHO products of the Smithsonian Astrophysical Observatory (OMHCHO) and of the Quality Assurance for Essential Climate Variables project (OMI QA4ECV). Results show that OMI HCHO slant columns retrieved using the GEMS algorithm are in good agreement with OMHCHO, with correlation coefficients of 0.77–0.91 and regression slopes of 0.94–1.04 for March, June, September, and December 2005. Spatial distributions of HCHO slant columns from the GEMS algorithm are consistent with the OMI QA4ECV products, but relatively poorer correlation coefficients of 0.52–0.76 are found compared to those against the OMHCHO products. Also, we compare the satellite results with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. OMI GEMS HCHO vertical columns are 9 %–25 % lower than those of MAX-DOAS at Haute-Provence Observatory (OHP) in France, Bremen in Germany, and Xianghe in China. We find that the OMI GEMS retrievals have less bias than the OMHCHO and OMI QA4ECV products at OHP and Bremen in comparison with MAX-DOAS.

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Verification of CFD tool for simulation of cavitating flows in hydraulic systems

Journal of Hydroinformatics ◽

10.2166/hydro.2017.004 ◽

2017 ◽

Vol 19 (5) ◽

pp. 653-665 ◽

Cited By ~ 8

Author(s):

Agnieszka Niedźwiedzka ◽

Seweryn Lipiński ◽

Sebastian Kornet

Keyword(s):

Statistical Analysis ◽

Volume Fraction ◽

Correlation Coefficients ◽

Hydraulic Systems ◽

Computer Methods ◽

Main Challenge ◽

Cavitation Intensity ◽

History Of ◽

Fluent Software ◽

Verification Process

Cavitation is an undesirable phenomenon in hydraulic systems, as it causes erosion and noise. The main difficulty in cavitation prediction when using Fluent software is lack of an openly accessible tool for implementation of a freely chosen homogeneous cavitation model. In this paper the main challenge is to make such a tool, user defined function (UDF). The second challenge is to use a qualitative method in the assessment of the results of verification process. Three cavitation models are verified in Fluent 14.5: Singhal et al., Schnerr & Sauer and Zwart et al. The verification is based on the benchmark example from the Cavitation Modeling tutorial. Three methods of the algorithms verification are used: analysis of the convergence history of volume fraction, comparison of vapour volume fractions and statistical analysis of these data. The original achievements are not only the verified codes but also statistical analysis based on the computer methods of image analysis performed using two correlation coefficients: the first based on the cavitation intensity, and the second based on the changes of the cloud shape. The results of the analyses do not give any reasons to reject the UDFs. The appendix contains the analysed codes (available with the online version of this paper).

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Structure-Function Correlative Microscopy of Peritubular and Intertubular Dentine

Materials ◽

10.3390/ma11091493 ◽

2018 ◽

Vol 11 (9) ◽

pp. 1493 ◽

Cited By ~ 4

Author(s):

Tan Sui ◽

Jiří Dluhoš ◽

Tao Li ◽

Kaiyang Zeng ◽

Adrian Cernescu ◽

...

Keyword(s):

Focused Ion Beam ◽

Volume Fraction ◽

Ion Beam ◽

Near Field ◽

Structural Difference ◽

Correlative Microscopy ◽

Mineral Concentration ◽

Force Microscopy ◽

Atomic Force ◽

Backscattered Electron

Peritubular dentine (PTD) and intertubular dentine (ITD) were investigated by 3D correlative Focused Ion Beam (FIB)-Scanning Electron Microscopy (SEM)-Energy Dispersive Spectroscopy (EDS) tomography, tapping mode Atomic Force Microscopy (AFM) and scattering-type Scanning Near-Field Optical Microscopy (s-SNOM) mapping. The brighter appearance of PTD in 3D SEM-Backscattered-Electron (BSE) imaging mode and the corresponding higher grey value indicate a greater mineral concentration in PTD (~160) compared to ITD (~152). However, the 3D FIB-SEM-EDS reconstruction and high resolution, quantitative 2D map of the Ca/P ratio (~1.8) fail to distinguish between PTD and ITD. This has been further confirmed using nanoscale 2D AFM map, which clearly visualised biopolymers and hydroxyapatite (HAp) crystallites with larger mean crystallite size in ITD (32 ± 8 nm) than that in PTD (22 ± 3 nm). Correlative microscopy reveals that the principal difference between PTD and ITD arises primarily from the nanoscale packing density of the crystallites bonded together by thin biopolymer, with moderate contribution from the chemical composition difference. The structural difference results in the mechanical properties variation that is described by the parabolic stiffness-volume fraction correlation function introduced here. The obtained results benefit a microstructure-based mechano-chemical model to simulate the chemical etching process that can occur in human dental caries and some of its treatments.

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Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm

Atmospheric Measurement Techniques ◽

10.5194/amt-13-553-2020 ◽

2020 ◽

Vol 13 (2) ◽

pp. 553-573 ◽

Cited By ~ 3

Author(s):

Guangliang Fu ◽

Otto Hasekamp ◽

Jeroen Rietjens ◽

Martijn Smit ◽

Antonio Di Noia ◽

...

Keyword(s):

Central Valley ◽

Absolute Error ◽

The United States ◽

High Spectral Resolution ◽

Retrieval Algorithm ◽

Smoke Plume ◽

Aerosol Retrieval ◽

Fine Mode ◽

High Spectral Resolution Lidar ◽

532 Nm

Abstract. In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON – the Netherlands Institute for Space Research. The campaign took place in October–November 2017 over the western part of the United States. During ACEPOL six different instruments were deployed on the NASA ER-2 high-altitude aircraft, including four multi-angle polarimeters (MAPs): SPEX airborne, the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), and the Research Scanning Polarimeter (RSP). Also, two lidars participated: the High Spectral Resolution Lidar-2 (HSRL-2) and the Cloud Physics Lidar (CPL). Flights were conducted mainly for scenes with low aerosol load over land, but some cases with higher AOD were also observed. We perform aerosol retrievals from SPEX airborne, RSP (410–865 nm range only), and AirMSPI using the SRON aerosol retrieval algorithm and compare the results against AERONET (AErosol RObotic NETwork) and HSRL-2 measurements (for SPEX airborne and RSP). All three MAPs compare well against AERONET for the aerosol optical depth (AOD), with a mean absolute error (MAE) between 0.014 and 0.024 at 440 nm. For the fine-mode effective radius the MAE ranges between 0.021 and 0.028 µm. For the comparison with HSRL-2 we focus on a day with low AOD (0.02–0.14 at 532 nm) over the California Central Valley, Arizona, and Nevada (26 October) as well as a flight with high AOD (including measurements with AOD>1.0 at 532 nm) over a prescribed forest fire in Arizona (9 November). For the day with low AOD the MAEs in AOD (at 532 nm) with HSRL-2 are 0.014 and 0.022 for SPEX and RSP, respectively, showing the capability of MAPs to provide accurate AOD retrievals for the challenging case of low AOD over land. For the retrievals over the smoke plume a reasonable agreement in AOD between the MAPs and HSRL-2 was also found (MAE 0.088 and 0.079 for SPEX and RSP, respectively), despite the fact that the comparison is hampered by large spatial variability in AOD throughout the smoke plume. A good comparison is also found between the MAPs and HSRL-2 for the aerosol depolarization ratio (a measure of particle sphericity), with an MAE of 0.023 and 0.016 for SPEX and RSP, respectively. Finally, SPEX and RSP agree very well for the retrieved microphysical and optical properties of the smoke plume.

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