Retrieval of atmospheric temperature and water vapour content from thermal infrared hyperspectral data in a purpose of atmospheric compensation

2007 ◽  
Author(s):  
V. Achard ◽  
S. Lesage ◽  
L. Poutier
Keyword(s):  
Water Vapour ◽  
Thermal Infrared ◽  
Atmospheric Temperature ◽  
Hyperspectral Data ◽  
Water Vapour Content ◽  
Atmospheric Compensation

Influence of the daylight illumination a weather conditions on Airborne Thermal Infrared Hyperspectral geological mapping

2021 ◽  
Author(s):  
Stephane Boubanga Tombet ◽  
Jean-Philippe Gagnon ◽  
Holger Eichstaedt ◽  
Joanne Ho
Keyword(s):  
Near Infrared ◽  
Thermal Infrared ◽  
Hyperspectral Data ◽  
Geological Mapping ◽  
Electromagnetic Spectrum ◽  
Spectral Features ◽  
Absorption Bands ◽  
Mineral Mapping ◽  
Atmospheric Compensation ◽  
Spectral Ranges

<p>The use of airborne remote sensing techniques for geological mapping offers many benefits as it allows coverage of large areas in a very efficient way.  While hyperspectral imaging from airborne/spaceborne platforms is now a well-established method applied to resolve many geological problems, it has mostly been developed only in the Visible-Near Infrared (VNIR, 0.4–1.0 mm) and Shortwave Infrared (SWIR, 1.0–2.5 mm) regions of the electromagnetic spectrum. However, the reflectance spectral features measured in the VNIR and SWIR spectral ranges are generally overtones and combination bands from fundamental absorption bands at longer wavelengths, such as in the Longwave Infrared (LWIR, 8–12 mm). The single absorption bands in the VNIR and SWIR spectral ranges are often very closely spaced so that the reflectance features measured by common spectrometers in this spectral region are typically broad and/or suffer from strong overlapping, which raises selectivity issues for mineral identification in some cases.</p><p>The inherent self-emission associated with LWIR under ambient conditions allows airborne mineral mapping in various weather (cloudy, partly cloudy or clear sky) and illumination (day or night) conditions. For this reason, LWIR often refers to the thermal infrared (TIR) spectral range. Solid targets such as minerals not only emit but also reflect TIR radiation. Since the two phenomena occur simultaneously, they end-up mixed in the radiance measured at the sensor level. The spectral features observed in a TIR spectrum of the sky and the atmosphere mostly correspond to ozone, water  vapor, carbon dioxide, methane and nitrous oxide with pretty sharp and narrow features compared with the infrared signature of solid materials such as minerals. The sharp spectral features of atmospheric gases are mixed up with broad minerals features in the collected geological mapping data, to unveil the spectral features associated with minerals from TIR measurements, the respective contributions of self-emission and reflection in the measurement must be «unmixed» and the atmospheric contributions must be compensated. This procedure refers to temperature-emissivity separation (TES). Therefore, to achieve an efficient TES and atmospheric compensation, the collection time and conditions of LWIR airborne hyperspectral data is of importance. Data of a flight mission in Southern Spain collected systematically at different times of the day (morning, mid-day and night) and in different altitudes using the Telops Hyper-Cam airborne system, a passive TIR hyperspectral sensor based on Fourier transform spectroscopy, were analyzed. TES was carried out on the hyperspectral data using<strong> two</strong> different approaches: a) Telops Reveal FLAASH IR software and b) DIMAP In-scene atmospheric compensation algorithm in order to retrieve thermodynamic temperature map and spectral emissivity data. Spectral analysis of the emissivity data with different mineral mapping methods based on commercial spectral libraries was used to compare results obtained during the different flight times and altitudes using the two post-processing methodologies. The results are discussed in the light of optimizing LWIR-based airborne operations in time and altitude to achieve best results for routine field mineral mapping applications such as in mining, soil science or archaeology, where the spatial analysis of mineral and chemical distribution is essential</p>

Back radiation versus CO2 as the cause of climate change

2017 ◽  
Vol 28 (7) ◽  
pp. 661-672 ◽  
Author(s):  
H Douglas Lightfoot ◽  
Orval A Mamer
Keyword(s):  
Climate Change ◽  
Water Vapour ◽  
Fossil Fuels ◽  
Scientific Evidence ◽  
Atmospheric Temperature ◽  
Water Molecules ◽  
Water Vapour Content ◽  
Ipcc Report ◽  
Main Component ◽  
The Tropics

Robust scientific evidence shows the sun angle controls water vapour content of the atmosphere, the main component of back radiation, as it cycles annually. Water vapour content measured as the ratio of the number of water molecules to CO2 molecules varies from 1:1 near the Poles to 97:1 in the Tropics. The effect of back radiation on Earth’s atmosphere is up to 200 times larger than that of CO2 and works in the opposite direction. Thus, if CO2 has any effect on atmospheric temperature and climate change we show it is negligible. Consequently, current government policies to control atmospheric temperature by limiting consumption of fossil fuels will have negligible effect. Measured data reported in IPCC report Climate Change 2013: The Physical Science Basis ( AR5) indicate increased water vapour content of the atmosphere is the cause of the 0.5℃ temperature increase from the mid-1970s to 2011.

Estimation of atmospheric water vapour content from direct measurements of radiance in the thermal infrared region

2012 ◽  
Vol 3 (1) ◽  
pp. 31-38 ◽  
Author(s):  
Vicente García-Santos ◽  
Joan Miquel Galve ◽  
Enric Valor ◽  
Vicente Caselles ◽  
César Coll
Keyword(s):  
Water Vapour ◽  
Thermal Infrared ◽  
Infrared Region ◽  
Atmospheric Water ◽  
Water Vapour Content ◽  
Atmospheric Water Vapour ◽  
Direct Measurements

Measuring Water Vapour in High-Purity Gas

1969 ◽  
Vol 2 (6) ◽  
pp. 236-238
Author(s):  
G. W. Lord
Keyword(s):  
Heat Treatment ◽  
Water Vapour ◽  
High Purity ◽  
Semiconductor Materials ◽  
Direct Reading ◽  
Magnetic Alloys ◽  
Water Vapour Content

The desired properties of magnetic alloys, semiconductor materials and similar products are usually developed by heat treatment in a stream off pure dry gas … the presence of even a few parts per million of water vapour in this gas can cause unwanted changes in such properties … to monitor the water-vapour content, a direct-reading dewpoint meter has been developed which is claimed to be more rapid and sensitive than similar meters

scholarly journals Atmospheric Compensation of PRISMA Data by Means of a Learning Based Approach

2021 ◽  
Vol 13 (15) ◽  
pp. 2967
Author(s):  
Nicola Acito ◽  
Marco Diani ◽  
Gregorio Procissi ◽  
Giovanni Corsini
Keyword(s):  
Spectral Range ◽  
Near Infrared ◽  
Random Noise ◽  
Synthetic Data ◽  
Regression Function ◽  
Short Wave ◽  
Hyperspectral Data ◽  
Electromagnetic Spectrum ◽  
Great Opportunity ◽  
Atmospheric Compensation

Atmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named LBAC, has been proposed for the AC of airborne hyperspectral data in the visible and near-infrared (VNIR) spectral range. LBAC makes use of a parametric regression function whose parameters are learned by a strategy based on synthetic data that accounts for (1) a physics-based model for the radiative transfer, (2) the variability of the surface reflectance spectra, and (3) the effects of random noise and spectral miscalibration errors. In this work we extend LBAC with respect to two different aspects: (1) the platform for data acquisition and (2) the spectral range covered by the sensor. Particularly, we propose the extension of LBAC to spaceborne hyperspectral sensors operating in the VNIR and short-wave infrared (SWIR) portion of the electromagnetic spectrum. We specifically refer to the sensor of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission, and the recent Earth Observation mission of the Italian Space Agency that offers a great opportunity to improve the knowledge on the scientific and commercial applications of spaceborne hyperspectral data. In addition, we introduce a curve fitting-based procedure for the estimation of column water vapor content of the atmosphere that directly exploits the reflectance data provided by LBAC. Results obtained on four different PRISMA hyperspectral images are presented and discussed.

scholarly journals Evaluation of MUSICA IASI tropospheric water vapour profiles using theoretical error assessments and comparisons to GRUAN Vaisala RS92 measurements

2018 ◽  
Vol 11 (9) ◽  
pp. 4981-5006 ◽  
Author(s):  
Christian Borger ◽  
Matthias Schneider ◽  
Benjamin Ertl ◽  
Frank Hase ◽  
Omaira E. García ◽  
...  
Keyword(s):  
Water Vapour ◽  
Degrees Of Freedom ◽  
Global Climate ◽  
Atmospheric Temperature ◽  
Systematic Difference ◽  
Polar Regions ◽  
Mixing Ratio ◽  
Random Errors ◽  
The Tropics ◽  
Dry Bias

Abstract. Volume mixing ratio water vapour profiles have been retrieved from IASI (Infrared Atmospheric Sounding Interferometer) spectra using the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) processor. The retrievals are done for IASI observations that coincide with Vaisala RS92 radiosonde measurements performed in the framework of the GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) in three different climate zones: the tropics (Manus Island, 2° S), mid-latitudes (Lindenberg, 52° N), and polar regions (Sodankylä, 67° N). The retrievals show good sensitivity with respect to the vertical H2O distribution between 1 km above ground and the upper troposphere. Typical DOFS (degrees of freedom for signal) values are about 5.6 for the tropics, 5.1 for summertime mid-latitudes, 3.8 for wintertime mid-latitudes, and 4.4 for summertime polar regions. The errors of the MUSICA IASI water vapour profiles have been theoretically estimated considering the contribution of many different uncertainty sources. For all three climate regions, unrecognized cirrus clouds and uncertainties in atmospheric temperature have been identified as the most important error sources and they can reach about 25 %. The MUSICA IASI water vapour profiles have been compared to 100 individual coincident GRUAN water vapour profiles. The systematic difference between the data is within 11 % below 12 km altitude; however, at higher altitudes the MUSICA IASI data show a dry bias with respect to the GRUAN data of up to 21 %. The scatter is largest close to the surface (30 %), but never exceeds 21 % above 1 km altitude. The comparison study documents that the MUSICA IASI retrieval processor provides H2O profiles that capture the large variations in H2O volume mixing ratio profiles well from 1 km above ground up to altitudes close to the tropopause. Above 5 km the observed scatter with respect to GRUAN data is in reasonable agreement with the combined MUSICA IASI and GRUAN random errors. The increased scatter at lower altitudes might be explained by surface emissivity uncertainties at the summertime continental sites of Lindenberg and Sodankylä, and the upper tropospheric dry bias might suggest deficits in correctly modelling the spectroscopic line shapes of water vapour.

scholarly journals Convective hydration in the tropical tropopause layer during the StratoClim aircraft campaign: pathway of an observed hydration patch

2019 ◽  
Vol 19 (18) ◽  
pp. 11803-11820 ◽  
Author(s):  
Keun-Ok Lee ◽  
Thibaut Dauhut ◽  
Jean-Pierre Chaboureau ◽  
Sergey Khaykin ◽  
Martina Krämer ◽  
...  
Keyword(s):  
Water Vapour ◽  
Lower Stratosphere ◽  
Asian Summer Monsoon ◽  
Great Part ◽  
The South ◽  
Water Vapour Content ◽  
Tropical Tropopause Layer ◽  
Tropical Tropopause ◽  
Water Vapour Concentration ◽  
Ice Content

Abstract. The source and pathway of the hydration patch in the TTL (tropical tropopause layer) that was measured during the Stratospheric and upper tropospheric processes for better climate predictions (StratoClim) field campaign during the Asian summer monsoon in 2017 and its connection to convective overshoots are investigated. During flight no. 7, two remarkable layers are measured in the TTL, namely (1) the moist layer (ML) with a water vapour content of 4.8–5.7 ppmv in altitudes of 18–19 km in the lower stratosphere and (2) the ice layer (IL) with ice content up to 1.9 eq. ppmv (equivalent parts per million by volume) in altitudes of 17–18 km in the upper troposphere at around 06:30 UTC on 8 August to the south of Kathmandu (Nepal). A Meso-NH convection-permitting simulation succeeds in reproducing the characteristics of the ML and IL. Through analysis, we show that the ML and IL are generated by convective overshoots that occurred over the Sichuan Basin about 1.5 d before. Overshooting clouds develop at altitudes up to 19 km, hydrating the lower stratosphere of up to 20 km with 6401 t of water vapour by a strong-to-moderate mixing of the updraughts with the stratospheric air. A few hours after the initial overshooting phase, a hydration patch is generated, and a large amount of water vapour (above 18 ppmv) remains at even higher altitudes up to 20.5 km while the anvil cloud top descends to 18.5 km. At the same time, a great part of the hydrometeors falls shortly, and the water vapour concentration in the ML and IL decreases due to turbulent diffusion by mixing with the tropospheric air, ice nucleation, and water vapour deposition. As the hydration patch continues to travel toward the south of Kathmandu, tropospheric tracer concentration increases up to ∼30 % and 70 % in the ML and IL, respectively. The air mass in the layers becomes gradually diffused, and it has less and less water vapour and ice content by mixing with the dry tropospheric air.

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