scholarly journals Using ocean-glint scattered sunlight as a diagnostic tool for satellite remote sensing of greenhouse gases

2013 ◽  
Vol 6 (3) ◽  
pp. 4371-4400
Author(s):  
A. Butz ◽  
S. Guerlet ◽  
O. P. Hasekamp ◽  
A. Kuze ◽  
H. Suto

Abstract. Spectroscopic measurements of sunlight backscattered by the Earth's surface is a technique widely used for remote sensing of atmospheric constituent concentrations from space. Thereby, remote sensing of greenhouse gases poses particularly challenging accuracy requirements for instrumentation and retrieval algorithms which, in general, suffer from various error sources. Here, we investigate a method that helps disentangle sources of error for observations of sunlight backscattered from the glint spot on the ocean surface. The method exploits the backscattering characteristics of the ocean surface which is bright for glint geometry but dark for off-glint angles. This property allows for identifying a set of clean scenes where light scattering due to particles in the atmosphere is negligible such that uncertain knowledge of the lightpath can be excluded as a source of error. We apply the method to more than 3 yr of ocean-glint measurements by the Thermal And Near infrared Sensor for carbon Observation (TANSO) – Fourier Transform Spectrometer (FTS) onboard the Greenhouse Gases Observing Satellite (GOSAT) which aims at measuring carbon dioxide (CO2) and methane (CH4) concentrations. The proposed method is able to clearly monitor recent improvements in the instrument calibration of the oxygen (O2) A-band channel and suggests some residual uncertainty in our knowledge about the instrument. We further assess the consistency of CO2 retrievals from several absorption bands between 6400 cm−1 (1565 nm) and 4800 cm−1 (2100 nm) and find that the absorption bands commonly used for monitoring of CO2 dry air mole fractions from GOSAT allow for consistency better than 1.5 ppm. Usage of other bands reveals significant inconsistency among retrieved CO2 concentrations pointing at inconsistency of spectroscopic parameters.

2013 ◽  
Vol 6 (9) ◽  
pp. 2509-2520 ◽  
Author(s):  
A. Butz ◽  
S. Guerlet ◽  
O. P. Hasekamp ◽  
A. Kuze ◽  
H. Suto

Abstract. Spectroscopic measurements of sunlight backscattered by the Earth's surface is a technique widely used for remote sensing of atmospheric constituent concentrations from space. Thereby, remote sensing of greenhouse gases poses particularly challenging accuracy requirements for instrumentation and retrieval algorithms which, in general, suffer from various error sources. Here, we investigate a method that helps disentangle sources of error for observations of sunlight backscattered from the glint spot on the ocean surface. The method exploits the backscattering characteristics of the ocean surface, which is bright for glint geometry but dark for off-glint angles. This property allows for identifying a set of clean scenes where light scattering due to particles in the atmosphere is negligible such that uncertain knowledge of the lightpath can be excluded as a source of error. We apply the method to more than 3 yr of ocean-glint measurements by the Thermal And Near infrared Sensor for carbon Observation (TANSO) Fourier Transform Spectrometer (FTS) onboard the Greenhouse Gases Observing Satellite (GOSAT), which aims at measuring carbon dioxide (CO2) and methane (CH4) concentrations. The proposed method is able to clearly monitor recent improvements in the instrument calibration of the oxygen (O2) A-band channel and suggests some residual uncertainty in our knowledge about the instrument. We further assess the consistency of CO2 retrievals from several absorption bands between 6400 cm−1 (1565 nm) and 4800 cm−1 (2100 nm) and find that the absorption bands commonly used for monitoring of CO2 dry air mole fractions from GOSAT allow for consistency better than 1.5 ppm. Usage of other bands reveals significant inconsistency among retrieved CO2 concentrations pointing at inconsistency of spectroscopic parameters.


2016 ◽  
Vol 40 (2) ◽  
pp. 215-246 ◽  
Author(s):  
Jamie D. Shutler ◽  
Graham D. Quartly ◽  
Craig J. Donlon ◽  
Shubha Sathyendranath ◽  
Trevor Platt ◽  
...  

Physical oceanography is the study of physical conditions, processes and variables within the ocean, including temperature–salinity distributions, mixing of the water column, waves, tides, currents and air–sea interaction processes. Here we provide a critical review of how satellite sensors are being used to study physical oceanography processes at the ocean surface and its borders with the atmosphere and sea ice. The paper begins by describing the main sensor types that are used to observe the oceans (visible, thermal infrared and microwave) and the specific observations that each of these sensor types can provide. We then present a critical review of how these sensors and observations are being used to study: (i) ocean surface currents, (ii) storm surges, (iii) sea ice, (iv) atmosphere–ocean gas exchange and (v) surface heat fluxes via phytoplankton. Exciting advances include the use of multiple sensors in synergy to observe temporally varying Arctic sea ice volume, atmosphere–ocean gas fluxes, and the potential for four-dimensional water circulation observations. For each of these applications we explain their relevance to society, review recent advances and capability, and provide a forward look at future prospects and opportunities. We then more generally discuss future opportunities for oceanography-focused remote sensing, which includes the unique European Union Copernicus programme, the potential of the International Space Station and commercial miniature satellites. The increasing availability of global satellite remote-sensing observations means that we are now entering an exciting period for oceanography. The easy access to these high quality data and the continued development of novel platforms is likely to drive further advances in remote sensing of the ocean and atmospheric systems.


2014 ◽  
Vol 7 (3) ◽  
pp. 713-729 ◽  
Author(s):  
D. Fu ◽  
T. J. Pongetti ◽  
J.-F. L. Blavier ◽  
T. J. Crawford ◽  
K. S. Manatt ◽  
...  

Abstract. The Los Angeles basin is a significant anthropogenic source of major greenhouse gases (CO2 and CH4) and the pollutant CO, contributing significantly to regional and global climate change. We present a novel approach for monitoring the spatial and temporal distributions of greenhouse gases in the Los Angeles basin using a high-resolution spectroscopic remote sensing technique. A new Fourier transform spectrometer called CLARS-FTS has been deployed since May, 2010, at Jet Propulsion Laboratory (JPL)'s California Laboratory for Atmospheric Remote Sensing (CLARS) on Mt. Wilson, California, for automated long-term measurements of greenhouse gases. The instrument design and performance of CLARS-FTS are presented. From its mountaintop location at an altitude of 1673 m, the instrument points at a programmed sequence of ground target locations in the Los Angeles basin, recording spectra of reflected near-IR solar radiation. Column-averaged dry-air mole fractions of greenhouse gases (XGHG) including XCO2, XCH4, and XCO are retrieved several times per day for each target. Spectra from a local Spectralon® scattering plate are also recorded to determine background (free tropospheric) column abundances above the site. Comparisons between measurements from LA basin targets and the Spectralon® plate provide estimates of the boundary layer partial column abundances of the measured species. Algorithms are described for transforming the measured interferograms into spectra, and for deriving column abundances from the spectra along with estimates of the measurement precision and accuracy. The CLARS GHG measurements provide a means to infer relative, and possibly absolute, GHG emissions.


2001 ◽  
Vol 39 (5) ◽  
pp. 1049-1060 ◽  
Author(s):  
S.H. Yueh ◽  
R. West ◽  
W.J. Wilson ◽  
F.K. Li ◽  
E.G. Njoku ◽  
...  

2020 ◽  
Vol 12 (12) ◽  
pp. 1942
Author(s):  
Robert F. Paul ◽  
Yaping Cai ◽  
Bin Peng ◽  
Wendy H. Yang ◽  
Kaiyu Guan ◽  
...  

Climate change is increasing the frequency and intensity of heavy precipitation in the US Midwest, overwhelming existing tile drainage, and resulting in temporary soil ponding across the landscape. However, lack of direct observations of the dynamics of temporal soil ponding limits our understanding of its impacts on crop growth and biogeochemical cycling. Satellite remote sensing offers a unique opportunity to observe and analyze this dynamic phenomenon at the landscape scale. Here we analyzed a series of red–green–blue (RGB) and near infrared (NIR) remote sensing images from the Planet Labs CubeSat constellation following a period of heavy precipitation in May 2017 to determine the spatiotemporal characteristics of ponding events in the maize–soybean cropland of Champaign County, Illinois USA. We trained Random Forest algorithms for near-daily images to create binary classifications of surface water versus none, which achieved kappa values around 0.9. We then analyzed the morphology of classification results for connected pixels across space and time and found that 2.5% (5180 ha) of this cropland was classified as water surface at some point during this period. The frequency distribution of areal ponding extent exhibited a log–log relationship; the mean and median areas of ponds were 1231 m2 and 126 m2, respectively, with 26.1% of identified ponds being at the minimum threshold area of 45 m2, and 2.5% of the ponds having an area greater than 104 m2 (1 ha). Ponds lasted for a mean duration of 2.4 ± 1.7 days, and 2.3% of ponds lasted for more than a week. Our results suggest that transient ponding may be significant at the landscape scale and ought to be considered in assessments of crop risk, soil and water conservation, biogeochemistry, and sustainability.


2021 ◽  
Author(s):  
Prabir K Patra ◽  
Tomohiro Hajima ◽  
Ryu Saito ◽  
Naveen Chandra ◽  
Yukio Yoshida ◽  
...  

Abstract The measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by Japan Aerospace Exploration Agency (JAXA) in 2009 and National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. We attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) and the fluxes estimated by an inverse model (MIROC4-Inv) using in situ data by comparing with GOSAT and OCO-2 observations. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating total column CO2 mole fraction (XCO2) that are sampled at the time and location of the satellite measurements. Both the ACTM simulations agreed well with the GOSAT and OCO-2 satellite observations, within 2 ppm for the spatial maps and time evolutions of the zonal mean distributions. Our results suggest that the inverse model using in situ data are more consistent with the OCO-2 retrievals, compared to those of the GOSAT XCO2 data due to the higher accuracy of the former. This suggests that the MIROC4-Inv fluxes are of sufficient quality to evaluate MIROC-ES2L simulated fluxes. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared to that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared to those of ACTM_InvF vs GOSAT. Using remote sensing based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.


Author(s):  
Debra Wunch ◽  
Geoffrey C. Toon ◽  
Jean-François L. Blavier ◽  
Rebecca A. Washenfelder ◽  
Justus Notholt ◽  
...  

A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO 2 , CO, CH 4 , N 2 O and other molecules that absorb in the near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an accuracy and precision in total column measurements that is unprecedented for remote-sensing observations (better than 0.25% for CO 2 ). This has enabled carbon-cycle science investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network.


2020 ◽  
Author(s):  
Prabir K Patra ◽  
Tomohiro Hajima ◽  
Ryu Saito ◽  
Naveen Chandra ◽  
Yukio Yoshida ◽  
...  

Abstract The measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by Japan Aerospace Exploration Agency (JAXA) in 2009 and National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. In this article, we attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) using GOSAT observations and the fluxes estimated by an inverse model (MIROC4-Inv) for the period 2009-2014. Further, we use the OCO-2 measurements for testing the consistency of inversion results for the period 2014-2018, along with the GOSAT data. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating CO2 concentrations that are sampled at the time and location of the satellite measurements. Our results suggest the inverse model using in situ data are more consistent with the OCO-2 retrievals, compared to those of the GOSAT XCO2 data, suggesting possible improvements in the present GOSAT retrieval system by better accounting for the degradation correction of the Thermal And Near infrared Sensor for carbon Observations - Fourier Transform Spectrometer (TANSO-FTS). The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared to that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared to those of ACTM_InvF vs GOSAT. Using remote sensing based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.


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