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.publishedVersio

CDOM absorption properties of natural water bodies along extreme environmental gradients

We present absorption properties of colored dissolved organic matter (CDOM) sampled in six different water bodies along extreme altitudinal, latitudinal, and trophic state gradients. Three sites are in Norway: the mesotrophic Lysefjord (LF), Samnangerfjord (SF), and Røst Coastal Water (RCW); two sites are in China: the oligotrophic Lake Namtso (LN) and the eutrophic Bohai Sea (BS); and one site is in Uganda: the eutrophic Lake Victoria (LV). The site locations ranged from equatorial to subarctic regions, and they included water types from oligotrophic to eutrophic and altitudes from 0 m to 4700 m. The mean CDOM absorption coefficients at 440 nm [ a CDOM (440) aCDOM(440) ] and 320 nm [ a CDOM (320) aCDOM(320) ] varied in the ranges 0.063–0.35 m −1 −1 and 0.34–2.28 m −1 −1 , respectively, with highest values in LV, Uganda and the lowest in the high-altitude LN, Tibet. The mean spectral slopes S 280−500 S280−500 and S 350−500 S350−500 were found to vary in the ranges of 0.017–0.032 nm −1 −1 and 0.013–0.015 nm −1 −1 , respectively. The highest mean value for S 280−500 S280−500 as well as the lowest mean value for S 350−500 S350−500 were found in LN. Scatter plots of S 280−500 S280−500 versus a CDOM (440) aCDOM(440) and a CDOM (320) aCDOM(320) values ranges revealed a close connection between RCW, LF, and SF on one side, and BS and LV on the other side. CDOM seems to originate from terrestrial sources in LF, SF, BS, and LV, while RCW is characterized by autochthonous-oceanic CDOM, and LN by autochthonous CDOM. Photobleaching of CDOM is prominent in LN, demonstrated by absorption towards lower wavelengths in the UV spectrum. We conclude that high altitudes, implying high levels of UV radiation and oligotrophic water conditions are most important for making a significant change in CDOM absorption properties.publishedVersio

Validation of OMI erythemal doses with multi-sensor ground-based measurements in Thessaloniki, Greece

The aim of this study is to validate the Ozone Monitoring Instrument (OMI) erythemal dose rates using ground-based measurements in Thessaloniki, Greece. In the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki, a Yankee Environmental System UVB-1 radiometer measures the erythemal dose rates every minute, and a Norsk Institutt for Luftforskning (NILU) multi-filter radiometer provides multi-filter based irradiances that were used to derive erythemal dose rates for the period 2005–2014. Both these datasets were independently validated against collocated UV irradiance spectra from a Brewer MkIII spectrophotometer. Cloud detection was performed based on measurements of the global horizontal radiation from a Kipp & Zonen pyranometer and from NILU measurements in the visible range. The satellite versus ground observation validation was performed taking into account the effect of temporal averaging, limitations related to OMI quality control criteria, cloud conditions, the solar zenith angle and atmospheric aerosol loading. Aerosol optical depth was also retrieved using a collocated CIMEL sunphotometer in order to assess its impact on the comparisons. The effect of total ozone columns satellite versus ground-based differences on the erythemal dose comparisons was also investigated. Since most of the public awareness alerts are based on UV Index (UVI) classifications, an analysis and assessment of OMI capability for retrieving UVIs was also performed. An overestimation of the OMI erythemal product by 3–6% and 4–8% with respect to ground measurements is observed when examining overpass and noontime estimates respectively. The comparisons revealed a relatively small solar zenith angle dependence, with the OMI data showing a slight dependence on aerosol load, especially at high aerosol optical depth values. A mean underestimation of 2% in OMI total ozone columns under cloud-free conditions was found to lead to an overestimation in OMI erythemal doses of 1–5%.While OMI overestimated the erythemal dose rates over the range of cloudiness conditions examined, its UVIs were found to be reliable for the purpose of characterising the ambient UV radiation impact

Ground-based and Satellite Remote Sensing of Atmospheric Aerosols and Ultraviolet Solar Radiation

Satellite remote sensed data have been used to determine the aerosol climatology and to investigate the influence of the aerosol index (AI) on the ultraviolet (UV) index in coastal land areas in Serrekunda (13.28◦ N, 16.34◦ W, 17 m), The Gambia, and Dar-es- Salaam (6.8◦ S, 39.26◦ E, 24 m), Tanzania, as well as in inland areas in Kampala (0.31◦ N, 32.58◦ E, 1200 m), Uganda. Over three decades of satellite data (1979–1994 and 1996–2012) from total ozone mapping spectrometer (TOMS) and ozone monitoring instrument (OMI), which have provided measurements of backscattered radiances in the wavelength range from 331 to 380 nm, have been used. We found a high correlation coefficient between UV index and AI of 0.82 for Serrekunda, but poor correlation for Kampala and Dar-es-Salaam. The average AI for Serrekunda was found to be about three times higher than that for Kampala or Dar-es-Salaam, and a positive trend with time of the AI was found for Kampala and Dar-es-Salaam, whereas a negative trend was found for Serrekunda. The OMI overpass UV indices were validated against the ground-based UV indices derived from NILU-UV irradiance measurements in Kampala, Uganda for the period between 2005 and 2014. It was found that the UV index values follow a seasonal pattern with maximum values in March and October. Under all-sky conditions, the OMI retrieval algorithm was found to overestimate the UV index values with a mean bias of about 28%. But under cloud/aerosol-free sky conditions, the mean bias reduced to values less than 10%. The overestimation of the UV index by the OMI retrieval algorithm was found to be mainly due to clouds and aerosols. An excessive use of old cars, which would imply a high loading of absorbing aerosols, could have been the reason for the increase with time in the AI for Kampala. Direct solar radiances measured at a ground-based station in Bergen, Norway be- tween February 2012 and April 2014, have been analyzed. It was found that the spectral aerosol optical thickness (AOT) and precipitable water vapor column (PWVC) retrieved from these measurements have a seasonal variation with highest values in summer and lowest values in winter. The highest value of the monthly median AOT at 440 nm of about 0.16 was measured in July and the lowest of about 0.04 was measured in Decem- ber. The highest value of the monthly median PWVC of about 2.0 cm was measured in July and the lowest of about 0.4 cm was measured in December. The Ångström expo- nent was derived and used to deduce aerosol particle size distributions. We found that coarse-mode aerosol particles dominated most of the time during the measurement pe- riod, but fine-mode aerosol particles dominated during the winter seasons. The derived Ångström exponent values suggested that aerosols containing sea salt could have been dominating at this station during the measurement period. In a comparison study conducted on aerosol data from AERONET (Aerosol Robotic Network) sites in Northern Norway and Svalbard, at Andenes (69.28◦ N, 16.01◦ E, 379 m) and Hornsund (77.00◦ N, 15.56◦ E, 10 m) for the period between 2008 and 2013, it was found that the five/six-year annual mean values of the AOT at 500 nm at Andenes and Hornsund were both 0.09. Less variation of the monthly mean value of the AOT at 500 nm was found at Hornsund than at Andenes. The annual mean values of the Ångström exponent of about 1.29 and 1.34 were respectively measured at Andenes and Hornsund. An Ångström exponent value of larger than 1.1 was respectively found in 68% and 84% of the observations at Andenes and Hornsund, which implies that fine- mode particles were dominating at both sites during the observation period. Despite the differences in their geographical locations with Hornsund in the arctic and Andenes in sub-arctic, both sites had a similar aerosol size distribution during summer

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