scholarly journals UV-Indien network: ground-based measurements dedicated to the monitoring of UV radiation over the western Indian Ocean

2021 ◽  
Vol 13 (9) ◽  
pp. 4275-4301
Author(s):  
Kevin Lamy ◽  
Thierry Portafaix ◽  
Colette Brogniez ◽  
Kaisa Lakkala ◽  
Mikko R. A. Pitkänen ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Uv Radiation ◽  
Western Indian Ocean ◽  
Cloud Fraction ◽  
Monitoring Instrument ◽  
Clear Sky ◽  
Wide Range ◽  
Ozone Monitoring ◽  
Main Station

Abstract. Within the framework of the UV-Indien network, nine ground stations have been equipped with ultraviolet broadband radiometers, five of them have also been equipped with an all-sky camera, and the main station in Saint-Denis de la Réunion is also equipped with a spectroradiometer. These stations are spatially distributed to cover a wide range of latitudes, longitudes, altitudes, and environmental conditions in five countries of the western Indian Ocean region (Comoros, France, Madagascar, Mauritius, and Seychelles), a part of the world where almost no measurements have been made so far. The distribution of the stations is based on the scientific interest of studying ultraviolet radiation not only in relation to atmospheric processes but also in order to provide data relevant to fields such as biology, health (prevention of skin cancer), and agriculture. The main scientific objectives of this network are to study the annual and inter-annual variability in the ultraviolet (UV) radiation in this area, to validate the output of numerical models and satellite estimates of ground-based UV measurements, and to monitor UV radiation in the context of climate change and projected ozone depletion in this region. A calibration procedure including three types of calibrations responding to the various constraints of sustaining the network has been put in place, and a data processing chain has been set up to control the quality and the format of the files sent to the various data centres. A method of clear-sky filtering of the data is also applied. Here, we present an intercomparison with other datasets, as well as several daily or monthly representations of the UV index (UVI) and cloud fraction data, to discuss the quality of the data and their range of values for the older stations (Antananarivo, Anse Quitor, Mahé, and Saint-Denis). Ground-based measurements of the UVI are used to validate satellite estimates – Ozone Monitoring Instrument (OMI), the TROPOspheric Monitoring Instrument (TROPOMI), and the Global Ozone Monitoring Experiment (GOME) – and model forecasts of UVI – Tropospheric Emission Monitoring Internet Service (TEMIS) and Copernicus Atmospheric Monitoring Service (CAMS). The median relative differences between satellite or model estimates and ground-based measurements of clear-sky UVI range between −34.5 % and 15.8 %. Under clear skies, the smallest UVI median difference between the satellite or model estimates and the measurements made by ground-based instruments is found to be 0.02 (TROPOMI), 0.04 (OMI), −0.1 (CAMS), and −0.4 (CAMS) at Saint-Denis, Antananarivo, Anse Quitor, and Mahé, respectively. The diurnal variability in UVI and cloud fraction, as well as the monthly variability in UVI, is evaluated to ensure the quality of the dataset. The data used in this study are available at https://doi.org/10.5281/zenodo.4811488 (Lamy and Portafaix, 2021a).

scholarly journals UV-Indien Network ground-based measurements: comparisons with satellite and model estimates of UV radiation over the Western Indian Ocean

2021 ◽  
Author(s):  
Kevin Lamy ◽  
Thierry Portafaix ◽  
Colette Brogniez ◽  
Kaisa Lakkala ◽  
Mikko R. A. Pitkänen ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Uv Radiation ◽  
Numerical Models ◽  
Western Indian Ocean ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Clear Sky ◽  
The Mean ◽  
Ozone Monitoring ◽  
Sky Conditions

Abstract. As part of the UV-Indien Network, 9 ground-based stations have been equipped with one spectroradiometer, radiometers and all-sky cameras. These stations are homogeneously distributed in 5 countries of the Western Indian Ocean region (Comoros, France, Madagascar, Mauritius and Seychelles), a part of the world where almost no measurements have been made so far. The main scientific objectives of this network are to study the annual and inter-annual variability of the ultraviolet (UV) radiation in this area, to validate the output of numerical models and satellite estimates of ground-based UV measurements, and to monitor UV radiation in the context of climate change and projected ozone depletion in this region. The first results are presented here for the oldest stations (Antananarivo, Anse Quitor, Mahé and Saint-Denis). Ground-based measurements of UV index (UVI) are compared against satellite estimates (Ozone Monitoring Instrument (OMI), the TROPOspheric Monitoring Instrument (TROPOMI), the Global Ozone Monitoring Experiment (GOME) and model forecasts of UVI (Tropospheric Emission Monitoring Internet Service (TEMIS) and Copernicus Atmospheric Monitoring Service (CAMS). The median relative differences between satellite or model estimates and ground-based measurements of clear-sky UVI range between −34.5 % and 15.8 %. Under clear skies, the smallest UVI median difference between the satellites or model estimates and the measurements of ground-based instruments is found to be 0.02 (TROPOMI), 0.04 (OMI), −0.1 (CAMS) and −0.4 (CAMS) at St-Denis, Antananarivo, Anse Quitor and Mahé respectively. The cloud fraction and UVI diurnal profile are calculated for these four stations. The mean UVI values at local solar noon range between 10 (Antananarivo, Anse Quitor and Saint-Denis) and 14 at Mahé. The mean UVIs in clear-sky conditions are higher than mean UVI in all-sky conditions, although it can still be noted that UVI maxima are higher for all-sky conditions than for clear sky conditions. This is the result of UVI enhancement induced by clouds, observed at these four stations. The greatest increase in UV radiation under cloudy conditions was observed at the Mahé station, with increases of more than 4. The data used in this study is available at https://doi.org/10.5281/zenodo.4572026 (Lamy and Portafaix, 2021).

scholarly journals Fibropapillomatosis infection in a population of green turtles at Watamu Bay, Kenya

2021 ◽  
Vol 20 (1) ◽  
pp. 111-123
Author(s):  
Sharon M. Jones ◽  
Itamar Caspi ◽  
Charles Lucas
Keyword(s):  
Indian Ocean ◽  
Horizontal Transmission ◽  
Western Indian Ocean ◽  
Chelonia Mydas ◽  
Infection Prevalence ◽  
Marine Biota ◽  
Community Factors ◽  
Green Turtles ◽  
Wide Range ◽  
Kenyan Coast

Anthropogenic stressors from onshore and offshore activities can act as driving factors of disease for a wide range of marine organisms. Green turtles (Chelonia mydas) are prominently afflicted with a tumour-causing disease known as fibropapillomatosis (FP) caused by the chelonid alphaherpesvirus ChHV5. Previous studies indicate that pathways of FP transmission may be genetic (vertical transmission) or linked to causal factors in a turtle’s environment (horizontal transmission). In this paper patterns of FP prevalence were examined in 10,896 records of green turtles caught or found stranded around Watamu Bay, Kenya, between 2003 – 2020. Findings were focused on locational and seasonal factors that may potentially influence infection. The findings show that FP prevalence varies significantly on an annual basis. Location significantly influenced infection prevalence, with prevalence higher in open ocean sites than sites located within the creek. Infection prevalence was highest at sites around the creek mouth and north of the creek mouth, with both regions exhibiting disparate annual patterns of infection. This paper is the first to examine long-term trends of FP prevalence in-depth in this region and has implications for the health of turtles and marine biota found along the Kenyan coast, and potentially within the wider Western Indian Ocean region. The findings emphasize the need to distinguish the infection pathways of causative agents via: i) further examination of the links between infection and environmental and/or biont community factors; and ii) the collection of data pertinent to the genetic diversity of green turtles and associated ChHV5 viral strains occurring in the Western Indian Ocean.

scholarly journals The Ozone Monitoring Instrument: overview of 14 years in space

2018 ◽  
Vol 18 (8) ◽  
pp. 5699-5745 ◽  
Author(s):  
Pieternel F. Levelt ◽  
Joanna Joiner ◽  
Johanna Tamminen ◽  
J. Pepijn Veefkind ◽  
Pawan K. Bhartia ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Trace Gases ◽  
Ozone Monitoring Instrument ◽  
Unique Role ◽  
Monitoring Instrument ◽  
New Findings ◽  
Wide Range ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
Direct Readout

Abstract. This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

scholarly journals Validation of OMI, GOME-2A and GOME-2B tropospheric NO<sub>2</sub>, SO<sub>2</sub> and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

2017 ◽  
Vol 17 (8) ◽  
pp. 5007-5033 ◽  
Author(s):  
Yang Wang ◽  
Steffen Beirle ◽  
Johannes Lampel ◽  
Mariliza Koukouli ◽  
Isabelle De Smedt ◽  
...  
Keyword(s):  
Cloud Fraction ◽  
Satellite Observations ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Air Mass ◽  
Clear Sky ◽  
Satellite Retrievals ◽  
Mass Factor ◽  
Ozone Monitoring

Abstract. Tropospheric vertical column densities (VCDs) of NO2, SO2 and HCHO derived from the Ozone Monitoring Instrument (OMI) on AURA and the Global Ozone Monitoring Experiment 2 aboard METOP-A (GOME-2A) and METOP-B (GOME-2B) are widely used to characterize the global distributions, trends and dominating sources of these trace gases. They are also useful for the comparison with chemical transport models (CTMs). We use tropospheric VCDs and vertical profiles of NO2, SO2 and HCHO derived from MAX-DOAS measurements from 2011 to 2014 in Wuxi, China, to validate the corresponding products (daily and bi-monthly-averaged data) derived from OMI and GOME-2A/B by different scientific teams. Prior to the comparison, the spatial and temporal coincidence criteria for MAX-DOAS and satellite data are determined by a sensitivity study using different spatial and temporal averaging conditions. Cloud effects on both MAX-DOAS and satellite observations are also investigated. Our results indicate that the discrepancies between satellite and MAX-DOAS results increase with increasing effective cloud fraction and are dominated by the effects of clouds on the satellite products. In comparison with MAX-DOAS, we found a systematic underestimation of all SO2 (40 to 57 %) and HCHO products (about 20 %), and an overestimation of the GOME-2A/B NO2 products (about 30 %), but good consistency with the DOMINO version 2 NO2 product. To better understand the reasons for these differences, we evaluated the a priori profile shapes used in the OMI retrievals (derived from CTM) by comparison with those derived from the MAX-DOAS observations. Significant differences are found for the SO2 and HCHO profile shapes derived from the IMAGES model, whereas on average good agreement is found for the NO2 profile shapes derived from the TM4 model. We also applied the MAX-DOAS profile shapes to the satellite retrievals and found that these modified satellite VCDs agree better with the MAX-DOAS VCDs than the VCDs from the original data sets by up to 10, 47 and 35 % for NO2, SO2 and HCHO, respectively. Furthermore, we investigated the effect of aerosols on the satellite retrievals. For OMI observations of NO2, a systematic underestimation is found for large AOD, which is mainly attributed to effect of the aerosols on the cloud retrieval and the subsequent application of a cloud correction scheme (implicit aerosol correction). In contrast, the effect of aerosols on the clear-sky air mass factor (explicit aerosol correction) has a smaller effect. For SO2 and HCHO observations selected in the same way, no clear aerosol effect is found, probably because for the considered data sets no cloud correction is applied (and also because of the larger scatter). From our findings we conclude that for satellite observations with cloud top pressure (CTP) > 900 hPa and effective cloud fraction (eCF) < 10 % the application of a clear-sky air mass factor might be a good option if accurate aerosol information is not available. Another finding of our study is that the ratio of morning-to-afternoon NO2 VCDs can be considerably overestimated if results from different sensors and/or retrievals (e.g. OMI and GOME-2) are used, whereas fewer deviations for HCHO and SO2 VCDs are found.

scholarly journals The TROPOMI surface UV algorithm

2017 ◽  
Author(s):  
Anders V. Lindfors ◽  
Jukka Kujanpää ◽  
Niilo Kalakoski ◽  
Anu Heikkilä ◽  
Kaisa Lakkala ◽  
...  
Keyword(s):  
Dose Rate ◽  
Uv Radiation ◽  
Near Infrared ◽  
European Space Agency ◽  
Atmospheric Composition ◽  
Ozone Monitoring Instrument ◽  
Satellite Mission ◽  
Free Atmosphere ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) is the only payload of the Sentinel-5 Precursor (S5P), which is a polar orbiting satellite mission of the European Space Agency (ESA). TROPOMI is a nadir-viewing spectrometer measuring in the ultraviolet, visible, near-infrared and the shortwave infrared that provides near-global daily coverage. Among other things, TROPOMI measurements will be used for calculating the UV radiation reaching Earth's surface. Thus, the TROPOMI Surface UV product will contribute to the need of monitoring UV radiation by providing daily information on the prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on the heritage of the OMI (Ozone Monitoring Instrument) and AC SAF (Satellite Application Facility for Atmospheric Composition and UV Radiation) algorithms. This paper provides a description of the algorithm that will be used for estimating surface UV radiation from TROPOMI observations. The TROPOMI Surface UV product includes the following UV quantities: the UV irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV; the vitamin-D weighted UV. Each of these are available as (i) daily dose or daily accumulated irradiance, (ii) overpass dose rate or irradiance, and (iii) local noon dose rate or irradiance. In addition, all quantities are available corresponding to actual cloud conditions and as clear-sky values, corresponding to otherwise the same conditions but assuming a cloud-free atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm has been tested using input based on OMI and GOME-2 (Global Ozone Monitoring Experiment–2) satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.

scholarly journals The TROPOMI surface UV algorithm

2018 ◽  
Vol 11 (2) ◽  
pp. 997-1008 ◽  
Author(s):  
Anders V. Lindfors ◽  
Jukka Kujanpää ◽  
Niilo Kalakoski ◽  
Anu Heikkilä ◽  
Kaisa Lakkala ◽  
...  
Keyword(s):  
Dose Rate ◽  
Uv Radiation ◽  
Near Infrared ◽  
European Space Agency ◽  
Atmospheric Composition ◽  
Ozone Monitoring Instrument ◽  
Satellite Mission ◽  
Free Atmosphere ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) is the only payload of the Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of the European Space Agency (ESA). TROPOMI is a nadir-viewing spectrometer measuring in the ultraviolet, visible, near-infrared, and the shortwave infrared that provides near-global daily coverage. Among other things, TROPOMI measurements will be used for calculating the UV radiation reaching the Earth's surface. Thus, the TROPOMI surface UV product will contribute to the monitoring of UV radiation by providing daily information on the prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on the heritage of the Ozone Monitoring Instrument (OMI) and the Satellite Application Facility for Atmospheric Composition and UV Radiation (AC SAF) algorithms. This paper provides a description of the algorithm that will be used for estimating surface UV radiation from TROPOMI observations. The TROPOMI surface UV product includes the following UV quantities: the UV irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV; and the vitamin-D weighted UV. Each of these are available as (i) daily dose or daily accumulated irradiance, (ii) overpass dose rate or irradiance, and (iii) local noon dose rate or irradiance. In addition, all quantities are available corresponding to actual cloud conditions and as clear-sky values, which otherwise correspond to the same conditions but assume a cloud-free atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm has been tested using input based on OMI and the Global Ozone Monitoring Experiment-2 (GOME-2) satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.

scholarly journals The Ozone Monitoring Instrument: Overview of twelve years in space

2017 ◽  
Author(s):  
Pieternel Levelt ◽  
Joanna Joiner ◽  
Johanna Tamminen ◽  
Pepijn Veefkind ◽  
Pawan K. Bhartia ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Ozone Monitoring Instrument ◽  
Unique Role ◽  
Monitoring Instrument ◽  
Wide Range ◽  
Research Findings ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
New Research ◽  
Direct Readout

Abstract. This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) spanning more than 12 years of the OMI data record. Data from OMI has been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality and climate change, including new research findings using these satellite data. Due to the operational Very Fast Delivery (VFD) (direct readout) and Near Real Time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

scholarly journals Updated Smithsonian Astrophysical Observatory Ozone Monitoring Instrument (SAO OMI) formaldehyde retrieval

2015 ◽  
Vol 8 (1) ◽  
pp. 19-32 ◽  
Author(s):  
G. González Abad ◽  
X. Liu ◽  
K. Chance ◽  
H. Wang ◽  
T. P. Kurosu ◽  
...  
Keyword(s):  
Temporal Stability ◽  
Cloud Fraction ◽  
Retrieval Algorithm ◽  
Reference Spectrum ◽  
Ozone Monitoring Instrument ◽  
High Concentration ◽  
Monitoring Instrument ◽  
Mass Factor ◽  
Ozone Monitoring ◽  
Level 2

Abstract. We present and discuss the Smithsonian Astrophysical Observatory (SAO) formaldehyde (H2CO) retrieval algorithm for the Ozone Monitoring Instrument (OMI) which is the operational retrieval for NASA OMI H2CO. The version of the algorithm described here includes relevant changes with respect to the operational one, including differences in the reference spectra for H2CO, the fit of O2–O2 collisional complex, updates in the high-resolution solar reference spectrum, the use of a model reference sector over the remote Pacific Ocean to normalize the retrievals, an updated air mass factor (AMF) calculation scheme, and the inclusion of scattering weights and vertical H2CO profile in the level 2 products. The setup of the retrieval is discussed in detail. We compare the results of the updated retrieval with the results from the previous SAO H2CO retrieval. The improvement in the slant column fit increases the temporal stability of the retrieval and slightly reduces the noise. The change in the AMF calculation has increased the AMFs by 20%, mainly due to the consideration of the radiative cloud fraction. Typical values for retrieved vertical columns are between 4 × 1015 and 4 × 1016 molecules cm−2, with typical fitting uncertainties ranging between 45 and 100%. In high-concentration regions the errors are usually reduced to 30%. The detection limit is estimated at 1 × 1016 molecules cm−2.

scholarly journals OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B

2015 ◽  
Vol 8 (12) ◽  
pp. 13471-13524 ◽  
Author(s):  
R. Lutz ◽  
D. Loyola ◽  
S. Gimeno García ◽  
F. Romahn
Keyword(s):  
A Priori ◽  
Recognition Algorithm ◽  
Cloud Fraction ◽  
Polarization Measurement ◽  
Point Of View ◽  
Computational Time ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring ◽  
Priori Information

Abstract. This paper describes an approach for cloud parameter retrieval (radiometric cloud fraction estimation) using the polarization measurements of the Global Ozone Monitoring Experiment-2 (GOME-2) on-board the MetOp-A/B satellites. The core component of the Optical Cloud Recognition Algorithm (OCRA) is the calculation of monthly cloud-free reflectances for a global grid (resolution of 0.2° in longitude and 0.2° in latitude) and to derive radiometric cloud fractions. These cloud fractions will serve as a priori information for the retrieval of cloud top height (CTH), cloud top pressure (CTP), cloud top albedo (CTA) and cloud optical thickness (COT) with the Retrieval Of Cloud Information using Neural Networks (ROCINN) algorithm. This approach is already being implemented operationally for the GOME/ERS-2 and SCIAMACHY/ENVISAT sensors and here we present version 3.0 of the OCRA algorithm applied to the GOME-2 sensors. Based on more than six years of GOME-2A data (February 2007–June 2013), reflectances are calculated for &amp;approx; 35 000 orbits. For each measurement a degradation correction as well as a viewing angle dependent and latitude dependent correction is applied. In addition, an empirical correction scheme is introduced in order to remove the effect of oceanic sun glint. A comparison of the GOME-2A/B OCRA cloud fractions with co-located AVHRR geometrical cloud fractions shows a general good agreement with a mean difference of −0.15±0.20. From operational point of view, an advantage of the OCRA algorithm is its extremely fast computational time and its straightforward transferability to similar sensors like OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) on Sentinel 5 Precursor, as well as Sentinel 4 and Sentinel 5. In conclusion, it is shown that a robust, accurate and fast radiometric cloud fraction estimation for GOME-2 can be achieved with OCRA by using the polarization measurement devices (PMDs).

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