Estimation of photolysis frequencies from TOMS satellite measurements and routine meteorological observations

A study on the estimation of J(O<sup>1</sup>D) and J(NO<sub>2</sub>) photolysis frequencies when limited ground based measurements (or even no measurements at all), are available is presented in this work. Photolysis frequencies can be directly measured by chemical actinometry and filter radiometry or can be calculated from actinic flux measurements. In several meteorological stations, none of the methods above are applicable due to the absence of sophisticated instruments such as actinometers, radiometers or spectroradiometers. In this case, it is possible to calculate photolysis frequencies with reasonable uncertainty using either a) standard meteorological observations, such as ozone, cloud coverage and horizontal visibility, available in various ground based stations, as input for a radiative transfer model or b) satellite observations of solar global irradiance available worldwide, in combination with an empirical method for the conversion of irradiance in photolysis frequencies. Both methods can provide photolysis frequencies with a standard deviation between 20% and 30%. The absolute level of agreement of the retrieved frequencies to those calculated from actual actinic flux measurements, for data from all meteorological conditions, is within ±5% for J(O<sup>1</sup>D) and less than 1% for J(NO<sub>2</sub>) for the first method, while for the second method it rises up to 25% for the case of J(O<sup>1</sup>D) and 12% for J(NO<sub>2</sub>), reflecting the overestimation of TOMS satellite irradiance when compared to ground based measurements of irradiance for the respective spectral regions. Due to the universality of the methods they can be practically applied to almost any station, thus overcoming problems concerning the availability of instruments measuring photolysis frequencies

Multi-modal analysis of aerosol robotic network size distributions for remote sensing applications: dominant aerosol type cases

To date, size distributions obtained from the aerosol robotic network (AERONET) have been fit with bi-lognormals defined by six secondary microphysical parameters: the volume concentration, effective radius, and the variance of fine and coarse particle modes. However, since the total integrated volume concentration is easily calculated and can be used as an accurate constraint, the problem of fitting the size distribution can be reduced to that of deducing a single free parameter – the mode separation point. We present a method for determining the mode separation point for equivalent-volume bi-lognormal distributions based on optimization of the root mean squared error and the coefficient of determination. The extracted secondary parameters are compared with those provided by AERONET’s Level 2.0 Version 2 inversion algorithm for a set of benchmark dominant aerosol types, including desert dust, biomass burning aerosol, urban sulphate and sea salt. The total volume concentration constraint is then also lifted by performing multimodal fits to the size distribution using nested Gaussian mixture models, and a method is presented for automating the selection of the optimal number of modes using a stopping condition based on Fisher statistics and via the application of statistical hypothesis testing. It is found that the method for optimizing the location of the mode separation point is independent of the shape of the aerosol volume size distribution (AVSD), does not require the existence of a local minimum in the size interval 0.439 µm ≤ r ≤ 0.992 µm, and shows some potential for optimizing the bi-lognormal fitting procedure used by AERONET particularly in the case of desert dust aerosol. The AVSD of impure marine aerosol is found to require three modes. In this particular case, bi-lognormals fail to recover key features of the AVSD. Fitting the AVSD more generally with multi-modal models allows automatic detection of a statistically significant number of aerosol modes, is applicable to a very diverse range of aerosol types, and gives access to the secondary microphysical parameters of additional modes currently not available from bi-lognormal fitting methods

Optical and geometrical characteristics of cirrus clouds over a Southern European lidar station

Optical and geometrical characteristics of cirrus clouds over Thessaloniki, Greece (40.6° N, 22.9° E) have been determined from the analysis of lidar and radiosonde measurements performed during the period from 2000 to 2006. Cirrus clouds are generally observed in a mid-altitude region ranging from 8.6 to 13 km, with mid-cloud temperatures in the range from −65° to −38°C. The cloud thickness generally ranges from 1 to 5 km and 38{%} of the cases studied have thickness between 2 and 3 km. The retrieval of optical depth and lidar ratio of cirrus clouds is performed using three different methods, taking into account multiple scattering effect. The mean optical depth is found to be 0.31±0.24 and the corresponding mean lidar ratio is 30±17 sr following the scheme of Klett-Fernald method. Sub-visual, thin and opaque cirrus clouds are observed at 3%, 57% and 40% of the measured cases, respectively. A comparison of the results obtained between the three methods shows good agreement. The multiple scattering errors of the measured effective extinction coefficients range from 20 to 60%, depending on cloud optical depth. The temperature and thickness dependencies on optical properties have also been studied in detail. A maximum mid-cloud depth of ~3.5 km is found at temperatures around ~−47.5°C, while there is an indication that optical depth and mean extinction coefficient increases with increasing mid-cloud temperature. A correlation between optical depth and thickness was also found. However, no clear dependence of the lidar ratio values on the cloud temperature and thickness was found

Optical and geometrical characteristics of cirrus clouds over a mid-latitude lidar station

International audienceOptical and geometrical characteristics of cirrus clouds over Thessaloniki, Greece (40.6°, 22.9°) have been determined from the analysis of lidar and radiosonde measurements performed during the period from 2000 to 2006. Cirrus clouds are generally observed in a mid altitude region ranging from 7 to 12 km, with mid-cloud temperatures in the range from ?65° to ?25°C. A seasonality of cirrus geometrical and temperature properties is found. The cloud thickness ranges from 0.85 to 5 km and 37% of our cases have thickness between 2 and 3 km. The retrieval of cloud's optical depth and lidar ratio is performed using three different methods, taking into account multiple scattering effects. The mean optical depth is found to be 0.3±0.24 and the corresponding mean lidar ratio is 28±17 sr. Sub-visual, thin and opaque cirrus clouds are observed at 7.5%, 51% and 42.5% of the measured cases respectively. The multiple scattering errors of the measured effective extinction coefficients range from 20% to 60% depending on cloud optical depth. A comparison of the results between the three methods shows good agreement. In addition we present the advantages and limitations of each method applied. The temperature and thickness dependencies on optical properties have also been studied in detail. A maximum mid-cloud depth of ~3 km is found at temperatures around ~?45°C while there is an indication that optical depth increases with increasing thickness and mid-cloud temperature. No clear dependence of the lidar ratio values on the cloud temperature and thickness was found

Inferring Absorbing Organic Carbon Content from AERONET Data

Black carbon, light-absorbing organic carbon (often called brown carbon) and mineral dust are the major light-absorbing aerosols. Currently the sources and formation of brown carbon aerosol in particular are not well understood. In this study we estimated globally the amount of light absorbing organic carbon and black carbon from AERONET measurements. We find that the columnar absorbing organic carbon (brown carbon) levels in biomass burning regions of South-America and Africa are relatively high (about 15-20 magnesium per square meters during biomass burning season), while the concentrations are significantly lower in urban areas in US and Europe. However, we estimated significant absorbing organic carbon amounts from the data of megacities of newly industrialized countries, particularly in India and China, showing also clear seasonality with peak values up to 30-35 magnesium per square meters during the coldest season, likely caused by the coal and biofuel burning used for heating. We also compared our retrievals with the modeled organic carbon by global Oslo CTM for several sites. Model values are higher in biomass burning regions than AERONET-based retrievals, while opposite is true in urban areas in India and China

Satellite retrieval of aerosol microphysical and optical parameters using neural networks: a new methodology applied to the Sahara desert dust peak

In order to exploit the full-earth viewing potential of satellite instruments to globally characterise aerosols, new algorithms are required to deduce key microphysical parameters like the particle size distribution and optical parameters associated with scattering and absorption from space remote sensing data. Here, a methodology based on neural networks is developed to retrieve such parameters from satellite inputs and to validate them with ground-based remote sensing data. For key combinations of input variables available from the MODerate resolution Imaging Spectro-radiometer (MODIS) and the Ozone Measuring Instrument (OMI) Level 3 data sets, a grid of 100 feed-forward neural network architectures is produced, each having a different number of neurons and training proportion. The networks are trained with principal components accounting for 98% of the variance of the inputs together with principal components formed from 38 AErosol RObotic NETwork (AERONET) Level 2.0 (Version 2) retrieved parameters as outputs. Daily averaged, co-located and synchronous data drawn from a cluster of AERONET sites centred on the peak of dust extinction in Northern Africa is used for network training and validation, and the optimal network architecture for each input parameter combination is identified with reference to the lowest mean squared error. The trained networks are then fed with unseen data at the coastal dust site Dakar to test their simulation performance. A neural network (NN), trained with co-located and synchronous satellite inputs comprising three aerosol optical depth measurements at 470, 550 and 660 nm, plus the columnar water vapour (from MODIS) and the modelled absorption aerosol optical depth at 500 nm (from OMI), was able to simultaneously retrieve the daily averaged size distribution, the coarse mode volume, the imaginary part of the complex refractive index, and the spectral single scattering albedo – with moderate precision: correlation coefficients in the range 0.368 ≤ R ≤ 0.514. The network failed to recover the spectral behaviour of the real part of the complex refractive index. This new methodological approach appears to offer some potential for moderately accurate daily retrieval of the total volume concentration of the coarse mode of aerosol at the Saharan dust peak in the area of Northern Africa

Monitoring of UV spectral irradiance at Thessaloniki (1990?2005): data re-evaluation and quality control

International audienceWe present a re-evaluation and quality control of spectral ultraviolet irradiance measurements from two Brewer spectroradiometers operating regularly at Thessaloniki, Greece. The calibration history of the two instruments was re-examined and data flaws were identified by comparing quasi synchronous measurements. Analysis of the sensitivity of both instruments to variations of their internal temperature revealed that they have temperature coefficients of different sign. These coefficients exhibit small variability during the 15-year period. Using averaged temperature coefficients, we corrected both datasets. Corrections were applied for the angular response error using two different approaches depending on the availability of required ancillary data. The uncertainties associated with the measurements have been estimated and presented. Finally, the two datasets are compared using ratios of irradiance integrals at various bands in the UV, in order to assess any dependencies on the internal instrument temperature, solar zenith angle and wavelength

Assessment of surface solar irradiance derived from real-time modelling techniques and verification with ground-based measurements

This study focuses on the assessment of surface solar radiation (SSR) based on operational neural network (NN) and multi-regression function (MRF) modelling techniques that produce instantaneous (in less than 1 min) outputs. Using real-time cloud and aerosol optical properties inputs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (MSG) satellite and the Copernicus Atmosphere Monitoring Service (CAMS), respectively, these models are capable of calculating SSR in high resolution (1 nm, 0.05 degree, 15 min) that can be used for spectrally integrated irradiance maps, databases and various applications related to energy exploitation. The real-time models are validated against ground-based measurements of the Baseline Surface Radiation Network (BSRN) in a temporal range varying from 15 min to monthly means, while a sensitivity analysis of the cloud and aerosol effects on SSR is performed to ensure reliability under different sky and climatological conditions. The simulated outputs, compared to their common training dataset created by the radiative transfer model (RTM) libRadtran, showed median error values in the range −15 to +15 % for the NN that produces spectral irradiances (NNS), 5–6 % underestimation for the integrated NN and close to zero errors for the MRF technique. The verification against BSRN revealed that the real-time calculation uncertainty ranges from −100 to +40 and −20 to +20 W/m^2, for the 15 min and monthly mean global horizontal irradiance (GHI) averages, respectively, while the accuracy of the input parameters, in terms of aerosol and cloud optical thickness (AOD and COT), and their impact on GHI, was of the order of 10 % as compared to the ground-based measurements. The proposed system aims to be utilized through studies and real-time applications which are related to solar energy production planning and use

Effects of total solar eclipse of 29 March 2006 on surface radiation

International audienceSolar irradiance spectral measurements were performed during a total solar eclipse. The spectral effect of the limb darkening to the global, direct irradiance and actinic flux measurements was investigated. This effect leads to wavelength dependent changes in the measured solar spectra showing a much more pronounced decrease in the radiation at the lower wavelengths. Radiative transfer model results were used for the computation of a correction for the total ozone measurements due to the limb darkening. This correction was found too small to explain the large decrease in total ozone column derived from the standard Brewer measurements, which is an artifact in the measured irradiance due to the increasing contribution of diffuse radiation against the decreasing direct irradiance caused by the eclipse. Calculations of the Extraterrestrial spectrum and the effective sun's temperatures, as measured from ground based direct irradiance measurements, showed an artificial change in the calculations of both quantities due to the fact that radiation coming from the visible part of the sun during the eclipse phases differs from the back body radiation described by the Planck's law

Monitoring dust particle orientation with measurements of sunlight dichroic extinction

© 2021 COMECAP CONFERENCE. All rights reserved. No part of this book may be reproduced or transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, without the prior written permission of the author.Alignment of irregularly shaped dust aerosols leading to linear dichroism has been reported in atmospheric layers. The present study intents to quantify the excess linear polarization of direct solar radiation propagating through atmospheric layers, when these contain oriented dust particles. In order to record the linear polarization, we have used the Solar Polarimeter (SolPol). SolPol is an instrument that measures the polarization of direct solar irradiance at 550nm. It is installed on an astronomical tracker in order target the solar disk. Using the measurements, the Stokes parameters are retrieved (I, Q/I, U/I and V/I) with an accuracy of ~1% and precision of 1 ppm. Collocated measurements of a sun-photometer (Aerosol Robotic Network; AERONET) and lidar are used to quantify the Aerosol Optical Depth (AOD) and identify the vertical distribution of dust layers, respectively. We will present indications of dust particle orientation recorded at the PANGEA station in the island of Antikythera, Greece, and at Nicosia, Cyprus during the preparatory phase for the ASKOS campaign in July 2021. The relation of the linear polarization of the solar irradiance to other optical properties of the dust layer is investigated