Disentangling chlorophyll fluorescence from atmospheric scattering effects in O_2 A‐band spectra of reflected sun‐light

Global retrieval of solar induced fluorescence emitted by terrestrial vegetation can provide an unprecedented measure for photosynthetic efficiency. The GOSAT (JAXA, launched Feb. 2009) and OCO-2 (NASA, to be launched 2013) satellites record high-resolution spectra in the O_2 A-band region, overlapping part of the chlorophyll fluorescence spectrum. We show that fluorescence cannot be unambiguously discriminated from atmospheric scattering effects using O_2 absorption lines. This can cause systematic biases in retrieved scattering parameters (aerosol optical thickness, aerosol height, surface pressure, surface albedo) if fluorescence is neglected. Hence, we demonstrate an efficient alternative fluorescence least-squares retrieval method based solely on strong Fraunhofer lines in the vicinity of the O_2 A-band, disentangling fluorescence from scattering effects. Not only does the Fraunhofer line fit produce a more accurate estimate of fluorescence emission, but it also allows improved retrievals of atmospheric aerosols from the O_2 A-band

Using airborne HIAPER Pole-to-Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide

In recent years, space-borne observations of atmospheric carbon dioxide (CO_2) have been increasingly used in global carbon-cycle studies. In order to obtain added value from space-borne measurements, they have to suffice stringent accuracy and precision requirements, with the latter being less crucial as it can be reduced by just enhanced sample size. Validation of CO_2 column-averaged dry air mole fractions (XCO_2) heavily relies on measurements of the Total Carbon Column Observing Network (TCCON). Owing to the sparseness of the network and the requirements imposed on space-based measurements, independent additional validation is highly valuable. Here, we use observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) flights from 01/2009 through 09/2011 to validate CO_2 measurements from satellites (Greenhouse Gases Observing Satellite – GOSAT, Thermal Emission Sounder – TES, Atmospheric Infrared Sounder – AIRS) and atmospheric inversion models (CarbonTracker CT2013B, Monitoring Atmospheric Composition and Climate (MACC) v13r1). We find that the atmospheric models capture the XCO_2 variability observed in HIPPO flights very well, with correlation coefficients (r^2) of 0.93 and 0.95 for CT2013B and MACC, respectively. Some larger discrepancies can be observed in profile comparisons at higher latitudes, in particular at 300 hPa during the peaks of either carbon uptake or release. These deviations can be up to 4 ppm and hint at misrepresentation of vertical transport. Comparisons with the GOSAT satellite are of comparable quality, with an r^2 of 0.85, a mean bias μ of −0.06 ppm, and a standard deviation σ of 0.45 ppm. TES exhibits an r^2 of 0.75, μ of 0.34 ppm, and σ of 1.13 ppm. For AIRS, we find an r^2 of 0.37, μ of 1.11 ppm, and σ of 1.46 ppm, with latitude-dependent biases. For these comparisons at least 6, 20, and 50 atmospheric soundings have been averaged for GOSAT, TES, and AIRS, respectively. Overall, we find that GOSAT soundings over the remote Pacific Ocean mostly meet the stringent accuracy requirements of about 0.5 ppm for space-based CO_2 observations

A method for evaluating bias in global measurements of CO_2 total columns from space

We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO_2 (X_(CO_2)) from space, and we illustrate the method by applying it to the v2.8 Atmospheric CO_2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land. The approach exploits the lack of large gradients in X_(CO_2) south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the observed correlation between free-tropospheric potential temperature and X_(CO_2) in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors, but that extrapolation to conditions found outside the region south of 25° S may be problematic (e.g., high airmasses, large surface pressure biases, M-gain, measurements made over ocean). A preliminary evaluation of the improved v2.9 ACOS-GOSAT data is also discussed

Toward accurate CO_2 and CH_4 observations from GOSAT

The column-average dry air mole fractions of atmospheric carbon dioxide and methane (X_(CO_2) and X_(CH_4)) are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of −0.05% and −0.30% for X_(CO_2) and X_(CH_4) with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for X_(CO_2) and 0.015 ppm for X_(CH_4). Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of X_(CO_2) suggesting the use of the satellite retrievals for constraining surface fluxes

Reviews

The following publications have been reviewed by the mentioned authors;Art and Society One. War by Ken Baynes, reviewed by Ronald FrankenbergArt and Society Two. Work by Ken Baynes and Alan Robinson, reviewed by Ronald FrankenbergArt and Society Three. Worship by Ken and Kate Baynes, reviewed by Ronald FrankenbergArt and Science by Dolf Rieser, reviewed by M. K. PaffardA COMMON SYSTEM OF EXAMINING AT 16+ by the Schols Council Examinations Bulletin No.23, reviewed by W. G. SkinnerSchool Resource Centres, the Schools Council Working Paper 43, reviewed by L. BroughA History of English Furniture by John Harrison, reviewed by S. J. EgglestonTrends in School Design by Eric Pearson, reviewed by P. K. BodenWorking Space, A Place to Paint, Language Aeas by Jason Dean, reviewed by P. K. BodenAlive to Art by Jose Llobera, reviewed by John LancasterVisual Education in the primary school by John M. Pickering, reviewed by L. BroughArt & Design Cards. Packs 1 & 2 by Ian Pillinger, reviewed by Francis ZankerWorkshop Assignments, Book One by S. Dunkerley & A. Huxton, reviewed by L. BroughStep By Step Metalwork, Book 3 by Kenneth Wells, reviewed by M. SayerIntroducing Jewellery Making by John Crawford, reviewed by John DecorteMaggie Hayes Jewellery Book by Maggie Hayes, reviewed by S. J. Egglesto

Detecting forest response to droughts with global observations of vegetation water content

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analog of the pressure–volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions—which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts