scholarly journals Analysis of actinic flux profiles measured from an ozonesonde balloon

2015 ◽  
Vol 15 (8) ◽  
pp. 4131-4144 ◽  
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

scholarly journals Analysis of actinic flux profiles measured from an ozone sonde balloon

2014 ◽  
Vol 14 (22) ◽  
pp. 31169-31201
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozone sonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analyzed using the Doubling Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times of the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK simulated actinic flux profiles and the observations for single layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth to further develop the instrument and launch it together with atmospheric chemistry composition sensors.

The impact of time-dependent stellar activity on the atmospheric chemistry and observability of exoplanets

2021 ◽  
Author(s):  
Amy Louca ◽  
Yamila Miguel ◽  
Shang-Min Tsai
Keyword(s):  
Atmospheric Chemistry ◽  
Emission Spectra ◽  
Time Dependent ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Stellar Spectrum ◽  
Stellar Spectra ◽  
Chemical Tracers ◽  
Atmospheric Escape ◽  
The Impact

<p class="p1">Observations of exoplanets used to characterize the chemistry and dynamics of atmospheres have developed considerably throughout the years. Nonetheless, it remains a difficult task to give a full and detailed description using solely observations. With future space missions such as JWST and ARIEL, both expected to be launched within this decade, it becomes even more crucial to be able to fully explain and predict the underlying chemistry and physics involved. In this research, we focus on modeling star-planet interactions by using synthetic flare spectra to predict chemical tracers for future missions. We make use of a chemical kinetics code that includes synthetic time-dependent stellar spectra and thermal atmospheric escape to simulate the atmospheres of known exoplanets. Using a radiative transfer model we then retrieve emission spectra. This ongoing study is focused on various known planetary systems of which the stellar spectrum has been obtained by the (mega-)MUSCLES collaboration. Preliminary results on these systems show that stellar flares and thermal escape can have a significant effect on the chemistry in atmospheres. </p>

scholarly journals Inter-Comparison Campaign of Solar UVR Instruments under Clear Sky Conditions at Reunion Island (21°S, 55°E)

2020 ◽  
Vol 17 (8) ◽  
pp. 2867
Author(s):  
Jean-Maurice Cadet ◽  
Thierry Portafaix ◽  
Hassan Bencherif ◽  
Kévin Lamy ◽  
Colette Brogniez ◽  
...  
Keyword(s):  
Low Cost ◽  
Solar Light ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Solar Ultraviolet Radiation ◽  
Good Reliability ◽  
Clear Sky ◽  
Moderate Cost ◽  
Sky Conditions ◽  
Over Time

Measurement of solar ultraviolet radiation (UVR) is important for the assessment of potential beneficial and adverse impacts on the biosphere, plants, animals, and humans. Excess solar UVR exposure in humans is associated with skin carcinogenesis and immunosuppression. Several factors influence solar UVR at the Earth’s surface, such as latitude and cloud cover. Given the potential risks from solar UVR there is a need to measure solar UVR at different locations using effective instrumentation. Various instruments are available to measure solar UVR, but some are expensive and others are not portable, both restrictive variables for exposure assessments. Here, we compared solar UVR sensors commercialized at low or moderate cost to assess their performance and quality of measurements against a high-grade Bentham spectrometer. The inter-comparison campaign took place between March 2018 and February 2019 at Saint-Denis, La Réunion. Instruments evaluated included a Kipp&Zonen UVS-E-T radiometer, a Solar Light UV-Biometer, a SGLux UV-Cosine radiometer, and a Davis radiometer. Cloud fraction was considered using a SkyCamVision all-sky camera and the Tropospheric Ultraviolet Visible radiative transfer model was used to model clear-sky conditions. Overall, there was good reliability between the instruments over time, except for the Davis radiometer, which showed dependence on solar zenith angle. The Solar Light UV-Biometer and the Kipp&Zonen radiometer gave satisfactory results, while the low-cost SGLux radiometer performed better in clear sky conditions. Future studies should investigate temporal drift and stability over time.

scholarly journals Aerosol Layering in the Free Troposphere over the Industrial City of Raciborz in Southwest Poland and Its Influence on Surface UV Radiation

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 812
Author(s):  
Alnilam Fernandes ◽  
Aleksander Pietruczuk ◽  
Artur Szkop ◽  
Janusz Krzyścin
Keyword(s):  
Radiative Transfer ◽  
Uv Radiation ◽  
Hybrid Model ◽  
Radiative Transfer Model ◽  
Asymmetry Factor ◽  
Transfer Model ◽  
Free Troposphere ◽  
Clear Sky ◽  
Sky Conditions ◽  
The Impact

Atmospheric aerosol and ultraviolet index (UVI) measurements performed in Racibórz (50.08° N, 18.19° E) were analyzed for the period June–September 2019. Results of the following observations were taken into account: columnar characteristics of the aerosols (aerosol thickness, Angstrom exponent, single scattering albedo, asymmetry factor) obtained from standard CIMEL sun-photometer observations and parameters of aerosol layers (ALs) in the free troposphere (the number of layers and altitudes of the base and top) derived from continuous monitoring by a CHM-15k ceilometer. Three categories of ALs were defined: residues from the daily evolution of the planetary boundary layer (PBL) aerosols, from the PBL-adjacent layer, and from the elevated layer above the PBL. Total column ozone measurements taken by the Ozone-Monitoring Instrument on board NASA’s Aura satellite completed the list of variables used to model UVI variability under clear-sky conditions. The aim was to present a hybrid model (radiative transfer model combined with a regression model) for determining ALs’ impact on the observed UVI series. First, a radiative transfer model, the Tropospheric Ultraviolet–Visible (TUV) model, which uses typical columnar characteristics to describe UV attenuation in the atmosphere, was applied to calculate hypothetical surface UVI values under clear-sky conditions. These modeled values were used to normalize the measured UVI data obtained during cloudless conditions. Next, a regression of the normalized UVI values was made using the AL characteristics. Random forest (RF) regression was chosen to search for an AL signal in the measured data. This explained about 55% of the variance in the normalized UVI series under clear-sky conditions. Finally, the UVI values were calculated as the product of the RF regression and the relevant UVIs by the columnar TUV model. The root mean square error and mean absolute error of the hybrid model were 1.86% and 1.25%, respectively, about 1 percentage point lower than corresponding values derived from the columnar TUV model. The 5th–95th percentile ranges of the observation/model differences were [−2.5%, 2.8%] and [−3.0%, 5.3%] for the hybrid model and columnar TUV model, respectively. Therefore, the impact of ALs on measured surface UV radiation could be demonstrated using the proposed AL characteristics. The statistical analysis of the UVI differences between the models allowed us to identify specific AL configuration responsible for these differences.

scholarly journals Homogeneity criteria within IASI pixels for the preparation of an all-sky assimilation

2018 ◽  
Author(s):  
Imane Farouk ◽  
Nadia Fourrie ◽  
Vincent Guidard
Keyword(s):  
Mesoscale Model ◽  
Positive Impact ◽  
Weather Prediction ◽  
Liquid Water Content ◽  
Current Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Detection ◽  
Clear Sky ◽  
The Impact

Abstract. This article focuses on a selection of satellite infra-red IASI observations and their simulation in the global Numerical Weather Prediction (NWP) system ARPEGE (Action de Recherche Petite Echelle Grande Echelle), using the sophisticated radiative transfer model RTTOV-CLD which takes into account the cloud multi-layers and the cloud scattering from atmospheric profiles and cloudy microphysical parameters (liquid water content, ice content and cloud fraction). The aim of this work is to select homogeneous scenes by using information of the collocated Advanced Very High Resolution Radiometer (AVHRR) pixels inside each IASI field of view and to retain the most favourable cases for the assimilation of IASI infrared radiances. Two methods to select homogeneous scenes using homogeneity criteria already proposed en the literature were employed; criteria derived from Martinet et al. (2013) for cloudy sky selection in the French mesoscale model AROME (Applications of Research to Operations at MEsoscale), and the criteria from Eresmaa (2014) for clear sky selection in the global model IFS (Integrated Forecasting System). An intercomparison between these methods reveals considerable differences, either in the method to compute the criteria or in the statistical results. From this comparison a revised method is proposed that is a compromise between the different tested methods, using the two infrared AVHRR channels to define the homogeneity criteria in the brightness temperature space. This revised method has a positive impact on the observation statistics minus the 15 simulation statistics, while retaining 36 % observations for the assimilation. It was then tested in the NWP system ARPEGE and tested for the clear-sky assimilation. These criteria were added to the current data selection based on the Mc Nally and Watts (2003) cloud detection. It appears that the impact on analyses and forecast is rather neutral.

scholarly journals Homogeneity criteria from AVHRR information within IASI pixels in a numerical weather prediction context

2019 ◽  
Vol 12 (6) ◽  
pp. 3001-3017
Author(s):  
Imane Farouk ◽  
Nadia Fourrié ◽  
Vincent Guidard
Keyword(s):  
Numerical Weather Prediction ◽  
Mesoscale Model ◽  
Positive Impact ◽  
Weather Prediction ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Detection Scheme ◽  
Numerical Weather ◽  
Clear Sky ◽  
The Impact

Abstract. This article focuses on the selection of satellite infrared IASI (Infrared Atmospheric Sounding Interferometer) observations in the global numerical weather prediction (NWP) system ARPEGE (Action de Recherche Petite Echelle Grande Echelle). The observation simulation is performed with the sophisticated radiative transfer model RTTOV-CLD, which takes into account the cloud scattering and the multilayer clouds from atmospheric profiles and cloud microphysical profiles (liquid water content, ice content and cloud fraction). The aim of this work is to select homogeneous scenes by using the information of the collocated Advanced Very High Resolution Radiometer (AVHRR) pixels inside each IASI field of view and to retain the most favourable cases for the assimilation of IASI infrared radiances. Two methods to select homogeneous scenes using homogeneity criteria already proposed in the literature were adapted: the criteria derived from Martinet et al. (2013) for cloudy sky selection in the French mesoscale model AROME (Applications of Research to Operations at MEsoscale) and the criteria from Eresmaa (2014) for clear-sky selection in the global model IFS (Integrated Forecasting System). A comparison between these methods reveals considerable differences, in both the method to compute the criteria and the statistical results. From this comparison a revised method representing a kind of compromise between the different tested methods is proposed and it uses the two infrared AVHRR channels to define the homogeneity criteria in the brightness temperature space. This revised method has a positive impact on the observation minus the simulation statistics, while retaining 36 % of observations for the assimilation. It was then tested in the NWP system ARPEGE for the clear-sky assimilation. These criteria were added to the current data selection based on the McNally and Watts (2003) cloud detection scheme. It appears that the impact on analyses and forecasts is rather neutral.

scholarly journals Observation-Based Longwave Cloud Radiative Kernels Derived from the A-Train

2016 ◽  
Vol 29 (6) ◽  
pp. 2023-2040 ◽  
Author(s):  
Qing Yue ◽  
Brian H. Kahn ◽  
Eric J. Fetzer ◽  
Mathias Schreier ◽  
Sun Wong ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Single Layer ◽  
Cloud Fraction ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The authors present a new method to derive both the broadband and spectral longwave observation-based cloud radiative kernels (CRKs) using cloud radiative forcing (CRF) and cloud fraction (CF) for different cloud types using multisensor A-Train observations and MERRA data collocated on the pixel scale. Both observation-based CRKs and model-based CRKs derived from the Fu–Liou radiative transfer model are shown. Good agreement between observation- and model-derived CRKs is found for optically thick clouds. For optically thin clouds, the observation-based CRKs show a larger radiative sensitivity at TOA to cloud-cover change than model-derived CRKs. Four types of possible uncertainties in the observed CRKs are investigated: 1) uncertainties in Moderate Resolution Imaging Spectroradiometer cloud properties, 2) the contributions of clear-sky changes to the CRF, 3) the assumptions regarding clear-sky thresholds in the observations, and 4) the assumption of a single-layer cloud. The observation-based CRKs show the TOA radiative sensitivity of cloud types to unit cloud fraction change as observed by the A-Train. Therefore, a combination of observation-based CRKs with cloud changes observed by these instruments over time will provide an estimate of the short-term cloud feedback by maintaining consistency between CRKs and cloud responses to climate variability.

scholarly journals The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

2016 ◽  
Vol 16 (2) ◽  
pp. 873-905 ◽  
Author(s):  
E. W. Butt ◽  
A. Rap ◽  
A. Schmidt ◽  
C. E. Scott ◽  
K. J. Pringle ◽  
...  
Keyword(s):  
Eastern Europe ◽  
Human Health ◽  
Atmospheric Aerosol ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
So2 Emissions ◽  
Residential Sector ◽  
Residential Combustion ◽  
Combustion Emissions ◽  
The Impact

Abstract. Combustion of fuels in the residential sector for cooking and heating results in the emission of aerosol and aerosol precursors impacting air quality, human health, and climate. Residential emissions are dominated by the combustion of solid fuels. We use a global aerosol microphysics model to simulate the impact of residential fuel combustion on atmospheric aerosol for the year 2000. The model underestimates black carbon (BC) and organic carbon (OC) mass concentrations observed over Asia, Eastern Europe, and Africa, with better prediction when carbonaceous emissions from the residential sector are doubled. Observed seasonal variability of BC and OC concentrations are better simulated when residential emissions include a seasonal cycle. The largest contributions of residential emissions to annual surface mean particulate matter (PM2.5) concentrations are simulated for East Asia, South Asia, and Eastern Europe. We use a concentration response function to estimate the human health impact due to long-term exposure to ambient PM2.5 from residential emissions. We estimate global annual excess adult (>  30 years of age) premature mortality (due to both cardiopulmonary disease and lung cancer) to be 308 000 (113 300–497 000, 5th to 95th percentile uncertainty range) for monthly varying residential emissions and 517 000 (192 000–827 000) when residential carbonaceous emissions are doubled. Mortality due to residential emissions is greatest in Asia, with China and India accounting for 50 % of simulated global excess mortality. Using an offline radiative transfer model we estimate that residential emissions exert a global annual mean direct radiative effect between −66 and +21 mW m−2, with sensitivity to the residential emission flux and the assumed ratio of BC, OC, and SO2 emissions. Residential emissions exert a global annual mean first aerosol indirect effect of between −52 and −16 mW m−2, which is sensitive to the assumed size distribution of carbonaceous emissions. Overall, our results demonstrate that reducing residential combustion emissions would have substantial benefits for human health through reductions in ambient PM2.5 concentrations.

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

2008 ◽  
Vol 26 (7) ◽  
pp. 1965-1975
Author(s):  
C. Topaloglou ◽  
B. Mayer ◽  
S. Kazadzis ◽  
A. F. Bais ◽  
M. Blumthaler
Keyword(s):  
Empirical Method ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Satellite Measurements ◽  
Absolute Level ◽  
Actinic Flux ◽  
Photolysis Frequencies ◽  
Flux Measurements ◽  
Meteorological Observations ◽  
Level Of Agreement

Abstract. A study on the estimation of J(O1D) and J(NO2) 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(O1D) and less than 1% for J(NO2) for the first method, while for the second method it rises up to 25% for the case of J(O1D) and 12% for J(NO2), 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.

scholarly journals Data-Driven Localization Mappings in Filtering the Monsoon–Hadley Multicloud Convective Flows

2018 ◽  
Vol 146 (4) ◽  
pp. 1197-1218
Author(s):  
Michèle De La Chevrotière ◽  
John Harlim
Keyword(s):  
Learning Algorithm ◽  
Data Driven ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Errors ◽  
Accurate Analysis ◽  
Perfect Model ◽  
Nonlinear Stochastic Model ◽  
Correlation Statistics ◽  
The Impact

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon–Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect-model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect-model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect- and imperfect-model data are comparable.

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