Characterization of GEMS level 1B based on inter-comparison using the visible channel of AMI

2021 ◽  
Author(s):  
Yeeun Lee ◽  
Myoung-Hwan Ahn ◽  
Mijin Eo ◽  
Mina Kang ◽  
Kyung-jung Moon ◽  
...  
Keyword(s):  
Optical System ◽  
Solar Irradiance ◽  
Spectral Response ◽  
Atmospheric Composition ◽  
Asia Pacific ◽  
High Spectral Resolution ◽  
Data Set ◽  
Central Wavelength ◽  
The North ◽  
The Earth

<p>             The Geostationary Korean Multi-Purpose Satellite (GK-2) program consisting of GK-2A and GK-2B provides consistent monitoring information in the Asia Pacific region, including the Korean peninsula. The Geostationary Environment Monitoring Spectrometer (GEMS) onboard GK-2B in particular provides information on the atmospheric composition and aerosol properties, retrieved from the calibrated radiance (Level 1B) with high spectral resolution in 300-500 nm. GEMS started its extended validation measurement after the in-orbit test (IOT) in October following the launch of the satellite in February 2020. One of issues found during the IOT is that GEMS shows a spatial dependence in the measured solar irradiance along the north-south direction, albeit the solar irradiance does not have such a dependency. Thus, such a dependence should be from the optical system or the solar diffuser which is placed in front of the scan mirror. To clarify the root cause of the dependence, we utilize inter-comparison of the Earth measurement between GEMS and the Advanced Meteorological Imager (AMI), a multi-channel imager onboard GK-2A for meteorological monitoring. As the spectral range of GEMS fully covers the spectral response function (SRF) of the AMI visible channel having a central wavelength of 470 nm, spectral matching is properly done by convolving the SRF with the hyperspectral data of GEMS. By taking advantage of the fact that the position of GK-2A and GK-2B is maintained within a 0.5 degree square box centered at 128.2°E, match-up data set for the inter-comparison is prepared by temporal and spatial collocation. To reduce spatio-temporal mis-match and increase the signal to noise, zonal mean is applied to the collocated data. Results show that the north-south dependence occurs in the comparison of reflectance, the ratio between the earth radiance and solar irradiance, while not in the comparison of radiance. This indicates the dependence occurs due to the characteristics of the solar diffuser, not because of optical system. It is further deduced that dependence of diffuser transmittance on the solar azimuth angle is the main cause of the north-south dependency which was not characterized during the pre-flight ground test.</p>

Aerosol and Cloud Changes during the Corona Lockdown in 2020 – First highlights from the BLUESKY campaign

2021 ◽  
Author(s):  
Christiane Voigt ◽  
Jos Lelieveld ◽  
Hans Schlager ◽  
Johannes Schneider ◽  
Daniel Sauer ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atmospheric Composition ◽  
Data Set ◽  
The North ◽  
Aerosol Mass ◽  
Trace Species ◽  
Research Aircraft ◽  
Fine Mode ◽  
Cloud Modeling ◽  
Fine Mode Aerosol

<p>Worldwide regulations to control the COVID-19 pandemic caused significant reductions in ground and airborne transportation in spring 2020. This unprecedented situation provided the unique opportunity to directly measure the less perturbed atmosphere, notably near the tropopause, and derive the effects of anthropogenic emissions on atmospheric composition, aerosol, clouds and climate. These changes were investigated during the BLUESKY experiment by the two research aircraft HALO and the DLR Falcon, satellite observations and models. From 16 May to 9 June 2020, the two research aircraft performed 20 flights over Europe and the North Atlantic. Profiles of trace species were measured with an advanced in-situ trace gas, aerosol and cloud payload from the boundary layer to 14 km altitude. Here, we present an overview and selected highlights of the BLUESKY experiment. Continental aerosol profiles show significant reductions in aerosol mass in the boundary layer. The reduced aerosol optical thickness above Germany has also been detected by MODIS and its impact on the colour of the sky is investigated. A specific focus was the detection of aerosol and cirrus changes caused by up to 90% reductions in air traffic. We find reductions in fine mode aerosol in the UTLS at various levels compared to CARIBIC data. In addition, we derive reductions in contrail and cirrus cover using passive and active remote sensing from satellite combined with cloud modeling. The comprehensive data set acquired during the 2020 lockdown period allows better understanding and constraining the anthropogenic influence on the composition of the atmosphere and its impacts on air quality and climate.</p>

A New Highly Stable Multi-Decade Satellite Climate Data Set Derived from Polar Hyperspectral Infrared Sensors

2020 ◽  
Author(s):  
Chris Hepplewhite ◽  
Larrabee Strow ◽  
Howard Motteler ◽  
Sergio de Souza-Machad ◽  
Steven Buczkowski
Keyword(s):  
Spectral Resolution ◽  
Virtual Instrument ◽  
Spectral Response ◽  
Short Wave ◽  
High Spectral Resolution ◽  
Climate Data ◽  
Climate Trends ◽  
Polar Orbit ◽  
Data Set ◽  
Long Wave

<p>NASA's Atmospheric Infrared Sounder (AIRS) started the continuous measurement of the Earth's upwelling infrared radiation at high spectral resolution in Sept. 2002 in a 13:30 polar orbit.  The AIRS record was supplemented by the CrIS sensor flying on the NASA SNPP platform, also in the 13:30 polar orbit, in 2012.  In 2018 a second CrIS sensor on NOAA's JPSS-1 platform (NOAA-20) began operation, also in the 13:30 orbit.  Two more CrIS sensors are presently being procured for the JPSS-2 and 3 satellites, which will extend this record from 2002 through ~2040.  EUMETSAT's METOP-A/B/C provide very similar hyperspectral observations starting with the IASI sensors in the 09:30 orbit, starting in 2007, which will be continued with METOP-SG for years to come.  </p><p>Inter-calibration of all of the operating sensors shows agreement generally to 0.2K or better in brightness temperature.  More importantly, we have shown that the radiometric stability of the AIRS sensors is in the 0.002 K/year range or 0.02K/decade, based on measurements of CO2 and SST trends.   Similar stability is expected for CrIS and IASI.  Community consensus suggests that direct radiance trending, followed by conversion of these trends to geophysical quantities will yield the most accurate climate trends.  </p><p>Here we introduce a new satellite hyperspectral infrared radiance product we call the "Climate Hyperspectral InfraRed Product (CHIRP)" that combines AIRS, CrIS, and IASI into a homogeneous Level 1 radiance product with a common spectral response and channel centers for all three satellites.  This grid is equivalent to an interferometer with optical path differences of 0.8/0.6/0.4 cm for the long-wave/mid-wave/short-wave spectral bands.  This corresponds to a virtual instrument with the same spectral resolution of the JPSS-1 CrIS sensor in the long-wave, with 25/50% degradation in spectral resolution in the mid-wave/short-wave.  This choice allows accurate conversion of the long AIRS record to an equivalent interferometer record.  Conversion of IASI to CHIRP is trivial.  Conversion of all sensors to the CHIRP spectra grid permits simple adjustments of inter-satellite radiometric bias differences since all measurements are first converted to a common spectral grid.  Multiple methods (SNOs, statistical inter-comparisons) indicate these adjustments can be made to the 0.03K level or better.   </p><p>A sample application of CHIRP to climate trending will be given by showing multi-decade anomalies of temperature, humidity, and ozone profiles retrieved from CHIRP radiance anomalies, a retrieval that requires almost no a-priori information.  This data set should yield definitive measurements of water-vapor feedback and heavily contribute to our understanding of both tropospheric and stratospheric temperature trends.   Initial production of CHIRP radiances that combine AIRS and CrIS are expected to begin in late 2020.  </p>

scholarly journals Spectral Calibration of the MethaneAIR Instrument

2021 ◽  
Author(s):  
Carly Staebell ◽  
Kang Sun ◽  
Jenna Samra ◽  
Jonathan Franklin ◽  
Christopher Chan Miller ◽  
...  
Keyword(s):  
Spectral Response ◽  
Stray Light ◽  
Lookup Table ◽  
Colorado Front Range ◽  
High Spectral Resolution ◽  
Retrieval Algorithm ◽  
Co2 Absorption ◽  
Central Wavelength ◽  
Spectral Calibration ◽  
Basin Scale

Abstract. MethaneAIR is the airborne simulator of MethaneSAT, an area-mapping satellite currently under development with the goal of locating and quantifying large anthropogenic point CH4 sources as well as diffuse basin-scale emissions. Built to closely replicate the forthcoming satellite, MethaneAIR consists of two imaging spectrometers. One detects CH4 and CO2 absorption around 1.65 and 1.61 μm, respectively, while the other constrains the optical path in the atmosphere by detecting O2 absorption near 1.27 μm. The high spectral resolution and stringent retrieval accuracy requirements of greenhouse gas remote sensing in this spectral range necessitate a reliable spectral calibration. To this end, on-ground laboratory measurements were used to derive the spectral calibration of MethaneAIR, serving as a pathfinder for the future calibration of MethaneSAT. Stray light was characterized and corrected through Fast Fourier Transform (FFT)-based Van Cittert deconvolution. Wavelength registration was examined and found to be best described by a linear relationship for both bands with a precision of ~0.02 spectral pixel. The instrument spectral spread function (ISSF), measured with fine wavelength steps of 0.005 nm near a series of central wavelengths across each band, was oversampled to construct the instrument spectral response function (ISRF) at each central wavelength and spatial pixel. The ISRFs were smoothed with a Savitzky-Golay filter for use in a lookup table in the retrieval algorithm. The MethaneAIR spectral calibration was evaluated through application to radiance spectra from an instrument flight over the Colorado Front Range.

scholarly journals A note on the interannual variations of UV-B erythemal doses and solar irradiance from ground-based and satellite observations

2001 ◽  
Vol 19 (1) ◽  
pp. 115-120 ◽  
Author(s):  
C. Zerefos ◽  
D. Balis ◽  
M. Tzortziou ◽  
A. Bais ◽  
K. Tourpali ◽  
...  
Keyword(s):  
Annual Cycle ◽  
Solar Irradiance ◽  
Cloud Cover ◽  
San Diego ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Quasi Biennial Oscillation ◽  
Data Set ◽  
Composition And Structure ◽  
The Tropics

Abstract. This study examines three UV-B data sets: ground-based long-term spectral records at Thessaloniki, Greece (40.5° N, 22.9° E) and San Diego, California, USA (32.7° N, 117.2° W) as well as a global data set of daily erythemal dose obtained from the Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite. Both ground-based stations have long enough records of spectral UV-B measurements to allow independent time series analyses. For 63° solar zenith angle (SZA) and clear sky conditions the quasi biennial oscillation (QBO) effect in solar irradiance at 305nm E305 is about 32% of the annual cycle for both San Diego and Thessaloniki. The effect slightly increases with cloud cover of up to 4/8, and decreases thereafter for cloud cover greater than 4/8. The data reveal that cloudiness can-not offset interannual signals in UV-B records. The observations at San Diego provide an independent confirmation of the widespread nature of the QBO in UV-B, which about coincides in amplitude at the two station studies, both located in the latitude zone 30°– 40° N. The peak-to-peak amplitude of the QBO in erythemal dose derived from TOMS/Nimbus-7 data is 6.5% at Thessaloniki. This is similar to the values calculated from ground-based measurements from this station. Based on satellite data, we find that the amplitude of the QBO in the erythemal dose is almost 40% of the amplitude of the annual cycle only in the tropics. The ratio of the amplitudes of the QBO over the annual cycle in erythemal dose decreases towards the extratropics, becoming less than 5% over middle latitudes.Key words. Atmospheric composition and structure (geo-chemical cycles; transmission and scattering of radiation)

scholarly journals Spectral calibration of the MethaneAIR instrument

2021 ◽  
Vol 14 (5) ◽  
pp. 3737-3753
Author(s):  
Carly Staebell ◽  
Kang Sun ◽  
Jenna Samra ◽  
Jonathan Franklin ◽  
Christopher Chan Miller ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Spectral Response ◽  
Point Sources ◽  
Stray Light ◽  
Lookup Table ◽  
High Spectral Resolution ◽  
Retrieval Algorithm ◽  
Co2 Absorption ◽  
Central Wavelength ◽  
Spectral Calibration

Abstract. MethaneAIR is the airborne simulator of MethaneSAT, an area-mapping satellite currently under development with the goal of locating and quantifying large anthropogenic CH4 point sources as well as diffuse emissions at the spatial scale of an oil and gas basin. Built to closely replicate the forthcoming satellite, MethaneAIR consists of two imaging spectrometers. One detects CH4 and CO2 absorption around 1.65 and 1.61 µm, respectively, while the other constrains the optical path in the atmosphere by detecting O2 absorption near 1.27 µm. The high spectral resolution and stringent retrieval accuracy requirements of greenhouse gas remote sensing in this spectral range necessitate a reliable spectral calibration. To this end, on-ground laboratory measurements were used to derive the spectral calibration of MethaneAIR, serving as a pathfinder for the future calibration of MethaneSAT. Stray light was characterized and corrected for through fast-Fourier-transform-based Van Cittert deconvolution. Wavelength registration was examined and found to be best described by a linear relationship for both bands with a precision of ∼ 0.02 spectral pixel. The instrument spectral spread function (ISSF), measured with fine wavelength steps of 0.005 nm near a series of central wavelengths across each band, was oversampled to construct the instrument spectral response function (ISRF) at each central wavelength and spatial pixel. The ISRFs were smoothed with a Savitzky–Golay filter for use in a lookup table in the retrieval algorithm. The MethaneAIR spectral calibration was evaluated through application to radiance spectra from an instrument flight over the Colorado Front Range.

scholarly journals An efficient technique for CT scan images classification of COVID-19

2020 ◽  
pp. 1-14
Author(s):  
Esraa Hassan ◽  
Noha A. Hikal ◽  
Samir Elmuogy
Keyword(s):  
Neural Network ◽  
Diagnostic Tool ◽  
Deep Neural Network ◽  
Data Augmentation ◽  
Performance Metrics ◽  
Classification Model ◽  
Data Set ◽  
Training Models ◽  
The Earth ◽  
Diagnostic Time

Nowadays, Coronavirus (COVID-19) considered one of the most critical pandemics in the earth. This is due its ability to spread rapidly between humans as well as animals. COVID_19 expected to outbreak around the world, around 70 % of the earth population might infected with COVID-19 in the incoming years. Therefore, an accurate and efficient diagnostic tool is highly required, which the main objective of our study. Manual classification was mainly used to detect different diseases, but it took too much time in addition to the probability of human errors. Automatic image classification reduces doctors diagnostic time, which could save human’s life. We propose an automatic classification architecture based on deep neural network called Worried Deep Neural Network (WDNN) model with transfer learning. Comparative analysis reveals that the proposed WDNN model outperforms by using three pre-training models: InceptionV3, ResNet50, and VGG19 in terms of various performance metrics. Due to the shortage of COVID-19 data set, data augmentation was used to increase the number of images in the positive class, then normalization used to make all images have the same size. Experimentation is done on COVID-19 dataset collected from different cases with total 2623 where (1573 training,524 validation,524 test). Our proposed model achieved 99,046, 98,684, 99,119, 98,90 In terms of Accuracy, precision, Recall, F-score, respectively. The results are compared with both the traditional machine learning methods and those using Convolutional Neural Networks (CNNs). The results demonstrate the ability of our classification model to use as an alternative of the current diagnostic tool.

scholarly journals Trading Global Catastrophes: NATO’s Science Diplomacy and Nuclear Winter

2021 ◽  
pp. 002200942199391
Author(s):  
Simone Turchetti
Keyword(s):  
North Atlantic ◽  
North Atlantic Treaty Organization ◽  
Environmental Consequences ◽  
The North ◽  
The Earth ◽  
Science Diplomacy ◽  
The North Atlantic ◽  
Nuclear Winter ◽  
Scientific Debates ◽  
Public Criticism

This essay explores the reception of ‘nuclear winter’ at the North Atlantic Treaty Organization (NATO). This response is paradigmatic of how scientific predictions can work as stimuli for science diplomacy activities, and either inflate or deflate these forecasts’ public resonance. Those who elaborated the theory in the early 1980s predicted that the environmental consequences of a future nuclear conflict would have been catastrophic; possibly rendering the earth uninhabitable and leading to the extinction of humankind. This prospect was particularly problematic for the Western defence alliance, since it was difficult to reconcile with the tenets of its nuclear posture, especially after the 1979 Dual Track decision, engendering concerns about the environmental catastrophe that the scientists predicted. Thus, NATO officials refrained from commenting on nuclear winter and its implications for the alliance’s deterrence doctrine for some time in an effort to minimize public criticism. Meanwhile, they progressively removed research on nuclear winter from the set of studies and scientific debates sponsored by NATO in the context of its science initiatives. In essence, NATO officials ‘traded’ the promotion of these problematic studies with that of others more amenable to the alliance’s diplomacy ambitions.

Alexander and the Mongols

1979 ◽  
Vol 111 (2) ◽  
pp. 123-136 ◽  
Author(s):  
John Andrew Boyle
Keyword(s):  
Eighth Century ◽  
Alexander The Great ◽  
The Caucasus ◽  
The North ◽  
The Earth ◽  
Four Corners ◽  
Book Of Genesis ◽  
First Time

The association of Alexander the Great with the Mongols begins with the identification of the latter with the peoples of Gog and Magog. The evolution of this legend, which has its origin in the Book of Genesis, is curious in the extreme. In Genesis Magog is mentioned as one of the sons of Japhet, his name occurring between those of Gomer and Madai. Since Madai is clearly intended as the eponym of the Medes and Gomer has been located in Cappadocia and Phrygia it has been plausibly suggested that Magog at this stage corresponded to the territory in between, i.e. the region immediately south of the Caucasus in Eastern and Northern Armenia. In Ezekiel we hear for the first time of Gog “of the land of Magog”, who will come from his place out of the uttermost parts of the north, he and many peoples with him, “all of them riding on horses, a great company and a mighty army.” It will be seen that the “land of Magog” can no longer be located south of the Caucasus, and indeed Ezekiel's prophecy of the invasion of Gog has been interpreted as an echo of the invasions of the Cimmerians, who came southwards from the steppes through the Darial pass towards the end of the eighth century B.C.; or more probably of the invasion of the Scythians which took place in the following century by way of Darband. Finally we are told in Revelation that “when the thousand years are finished, Satan shall be loosed out of his prison, and shall come forth to deceive the nations which are in the four corners of the earth, Gog and Magog, to gather them together to the war; the number of whom is as the sand of the sea”.

scholarly journals Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

2021 ◽  
Vol 13 (9) ◽  
pp. 1693
Author(s):  
Anushree Badola ◽  
Santosh K. Panda ◽  
Dar A. Roberts ◽  
Christine F. Waigl ◽  
Uma S. Bhatt ◽  
...  
Keyword(s):  
Land Cover ◽  
Spectral Resolution ◽  
Hyperspectral Image ◽  
Spectral Response ◽  
Spectral Characteristics ◽  
Hyperspectral Data ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Fuel Mapping ◽  
Sentinel 2

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.

scholarly journals Regional differences in the evolution of the merger of /ʃ/ and /ç/ in Luxembourgish

2021 ◽  
pp. 1-18
Author(s):  
François Conrad
Keyword(s):  
Language Contact ◽  
Sound Change ◽  
Young Generation ◽  
The South ◽  
Data Set ◽  
West Germanic ◽  
The North ◽  
Minimal Pairs ◽  
Old Men ◽  
Middle Generation

The merger of post-alveolar /ʃ/ and palatal /ç/ into alveolopalatal /ɕ/ has recently gained growing interest in sociophonetic research, especially in the Middle German dialect area. In Luxembourgish, a Continental West Germanic language, the sound change has been linked to age differences, while its origins remain unclear. Two studies with a regional focus are presented in this paper. The first study examines the merger in the Centre and the South of Luxembourg. The acoustic examination of both the spectral peak and the centre of gravity of a spoken data set of five minimal pairs embedded in read and orally translated sentences from 48 speakers (three generations (old generation, 65–91 years; middle generation, 40–64 years; young generation, 20–39 years; each generation, n = 16), men and women) reveals interesting results related to their regional background. In the old generation, the merger is further advanced in the speech of old men from the former mining region in the South compared to their peers in the Centre, the former leading this sound change. On the other hand, young speakers in both regions produce only alveolopalatal /ɕ/, the merger being complete in this generation. The second study presents exploratory data from the East and the North of the country. The analysis of this smaller sample (n = 6 speakers) reveals patterns similar to the central region. Pointing to language contact with Romance in the South as cradle and/or catalyser of the merger, these results not only give further clues as to the development in Luxembourg, but also add to a deeper understanding of sound changes in process in complex sibilant systems.

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