Connor, B. J.

Deutscher, N. M.

Dupuy, E.

Griffith, D. W. T.

Hase, F.

Heikkinen, P.

Hillyard, P. W.

Iraci, L. T.

Kawakami, S.

Kivi, R.

Matsunaga, T.

Mazière, M. D.

Morino, I.

Notholt, J.

Petri, C.

Podolske, J. R.

Pollard, D. F.

Rettinger, M.

Roehl, C. M.

Sherlock, V.

Sussmann, R.

Toon, G. C.

Uchino, O.

Velazco, V. A.

Warneke, T.

Wennberg, P. O.

Wunch, D.

Yokota, T.

Yoshida, Y.

English

KITopen

remote sensing  CorrectionCorrection: Dupuy, E., et al. Comparison of XH2ORetrieved from GOSAT Short-Wavelength InfraredSpectra with Observations from the TCCON Network.Remote Sens. 2016, 8, 414Eric Dupuy 1,*, Isamu Morino 1, Nicholas M. Deutscher 2,3, Yukio Yoshida 1, Osamu Uchino 1,Brian J. Connor 4, Martine De Mazière 5, David W. T. Griffith 2, Frank Hase 6, Pauli Heikkinen 7,Patrick W. Hillyard 8,9, Laura T. Iraci 8, Shuji Kawakami 10, Rigel Kivi 7, Tsuneo Matsunaga 1,Justus Notholt 3, Christof Petri 3, James R. Podolske 8, David F. Pollard 11, Markus Rettinger 12,Coleen M. Roehl 13, Vanessa Sherlock 11, Ralf Sussmann 12, Geoffrey C. Toon 14,Voltaire A. Velazco 2, Thorsten Warneke 3, Paul O. Wennberg 13, Debra Wunch 13,†and Tatsuya Yokota 11 National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan;morino@nies.go.jp (I.M.); yoshida.yukio@nies.go.jp (Y.Y.); uchino.osamu@nies.go.jp (O.U.);matsunag@nies.go.jp (T.M.); yoko@nies.go.jp (T.Y.)2 Center for Atmospheric Chemistry, School of Chemistry, Northfields Ave., University of Wollongong,Wollongong NSW 2522, Australia; ndeutsch@uow.edu.au (N.M.D.); griffith@uow.edu.au (D.W.T.G.);voltaire@uow.edu.au (V.A.V.)3 Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, Bremen 28359, Germany;jnotholt@iup.physik.uni-bremen.de (J.N.); christof_p@iup.physik.uni-bremen.de (C.P.);warneke@iup.physik.uni-bremen.de (T.W.)4 BC Consulting Limited, 6 Fairway Dr., Alexandra 9320, New Zealand; bcconsulting@xtra.co.nz5 Institut d’Aéronomie Spatiale de Belgique (BIRA-IASB), 3 Avenue Circulaire, Brussels B-1180, Belgium;Martine.DeMaziere@bira-iasb.oma.be6 Karlsruhe Institute of Technology, IMK-ASF, Hermann-von-Helmholtz-Platz 1, Leopoldshafen 76344,Germany; frank.hase@kit.edu7 FMI-Arctic Research Center, Tähteläntie 62, Sodankylä FIN-99600, Finland; Pauli.Heikkinen@fmi.fi (P.H.);Rigel.Kivi@fmi.fi (R.K.)8 NASA Ames Research Center, Atmospheric Science Branch, Mail Stop 245-5, Moffett Field, CA 94035, USA;patrick.hillyard@nasa.gov (P.W.H.); Laura.T.Iraci@nasa.gov (L.T.I.); James.R.Podolske@nasa.gov (J.R.P.)9 Bay Area Environmental Research Institute, 625 2nd St., Suite 209, Petaluma, CA 94952, USA10 Earth Observation Research Center (EORC), Japan Aerospace Exploration Agency (JAXA), 2-1-1 Sengen,Tsukuba-city, Ibaraki 305-8505, Japan; kawakami.shuji@jaxa.jp11 National Institute of Water and Atmospheric Research (NIWA), Private bag 50061, Omakau 9352,New Zealand; Dave.Pollard@niwa.co.nz (D.F.P.); vj.sherlock@gmail.com (V.S.)12 Karlsruhe Institute of Technology, IMK-IFU, Kreuzeckbahnstr. 19, Garmisch-Partenkirchen 82467, Germany;markus.rettinger@kit.edu (M.R.); ralf.sussmann@kit.edu (R.S.)13 California Institute of Technology, MC 131-24, 1200 E. California Blvd., Pasadena, CA 91125, USA;coleen@gps.caltech.edu (C.M.R.); wennberg@gps.caltech.edu (P.O.W.); dwunch@caltech.edu (D.W.)14 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA;geoffrey.c.toon@jpl.nasa.gov* Correspondence: dupuy.eric-albert@nies.go.jp; Tel./Fax: +81-29-850-2751† Current address: Department of Physics, University of Toronto, 60 St. George Street, Toronto, ON M5S 1A7,Canada; dwunch@atmosp.physics.utoronto.ca.Academic Editor: Prasad S. ThenkabailReceived: 1 November 2016; Accepted: 23 November 2016; Published: 29 November 2016Remote Sens. 2016, 8, 982; doi:10.3390/rs8120982 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 982 2 of 7After publication of the research paper [1], an error was discovered in the extraction of thetimestamps of the TCCON (Total Carbon Column Observing Network) measurements from theTCCON data files. This induced sporadic shifts of the calculated TCCON dates, by one full day beforeof after the real measurement date (or no shift in some cases). These shifts led to an incorrect estimationof the time differences between the measurements of the TANSO-FTS (Thermal And Near-InfraredSensor Fourier Transform Spectrometer) instrument on GOSAT (Greenhouse Gases Observing Satellite)and the TCCON soundings. Therefore, the set of coincidences was partially incorrect, causing errors inthe bias estimates, standard deviations of the differences, linear regression and correlation coefficients.A new set of coincident measurements was selected based on corrected TCCON time information.The statistics of the comparison: bias estimates and standard deviation of the differences, linearregression and correlation coefficients, sensitivity to geophysical and retrieval parameters, werere-calculated based on the correct correlative ensemble. The corresponding tables and figures ofSections 5.1, 5.2 and 5.3 were updated accordingly. Note that the comparison methodology andalgorithms were not in question; thus, they have been used, unaltered, for the re-computation.Therefore, the main findings and conclusions of the research paper remain essentially the same.The updated numerical results (Abstract; Section 5.1 paragraphs 2, 5 and 6; Section 5.2 paragraph 3,Section 5.3 paragraphs 4 and 5, and Conclusions) can be inferred from the corrected tables and figurespresented here, except for the following elements only mentioned in the initial text [1]:• Section 5.3, middle of paragraph 2:‘The ensemble time series yield monthly mean differences globally equal to zero within theirstandard deviation: values between about −450 ppm to +120 ppm with an average of −100 ppm,standard deviations within 30 to 700 ppm. This shows that the seasonal variations in the Northernand Southern hemispheres, previously illustrated by the single-site XH2O time series, tend tocancel out. The fact that the monthly mean values are mostly negative is likely explained by theincreasingly low bias of TANSO-FTS XH2O for larger TCCON mole fractions.’• Section 5.3, end of paragraph 3:‘For example, target-mode observations around Park Falls, Lamont and Tsukuba respectivelyaccount for 62%, 99% and 100% of the coincidences found at each site using the nominal criteria(±1◦ in latitude/longitude, ±30 min in time). The exceptions are Sodankylä (0%), Darwin (8%),the JPL (31%) and Lauder (39%), which are sufficiently close to the standard GOSAT scanningpattern footprints to be observed routinely without requiring target-mode observations.’• Section 5.3, end of paragraph 5:‘There also seems to be a slight bias with respect to the SZA values for both datasets, withdifferences becoming larger and negative for SZAs smaller than 25◦ and a corresponding globalcorrelation of ∼0.16 for both GOSAT and TCCON (0.35 and 0.41 for TANSO-FTS and TCCON,respectively, for SZA values smaller than 25◦).’The corrected tables (initially Tables 2 and 3) and figures (initially Figures 3, 4 and 6–10) ofSection 5 are presented in the same order as in the initial research paper [1] as: Table 2, Figure 3, Table 3and Figures 4, 6, 7, 8, 9 and 10. The reader should disregard the numerical values of the published textand consider those of the corrected Tables 2 and 3 instead.We sincerely apologize to the journal and to the readers for any inconvenience this errorhas caused.Remote Sens. 2016, 8, 982 3 of 7Table 2. Correction of Table 2 in [1]. Results of the comparison between TANSO-FTS scans acquiredwithin ±1◦ in latitude and in longitude of the TCCON sites and the average of TCCON measurementswithin ±30 min of the corresponding GOSAT overpasses. The number of matched scans is given.The absolute and relative values of the mean bias and standard deviation (SD) are indicated for eachstation. The ensemble and site-by-site results are also given.TCCON # of Scans Bias±SD Bias±SDDataset (ppm) (%)Sodankylä 33 −264.0 ± 548.6 −8.50 ± 17.93Bialystok 23 −106.6 ± 265.1 −3.03 ± 9.56Bremen 13 2.6 ± 53.2 −0.26 ± 3.36Karlsruhe 39 −199.1 ± 303.0 −7.74 ± 11.54Orléans 96 −11.3 ± 247.0 −0.64 ± 10.89Garmisch 56 −120.9 ± 346.6 −2.98 ± 17.65Park Falls 165 −25.7 ± 289.6 −0.97 ± 12.62Lamont 346 −20.0 ± 239.6 1.06 ± 18.76Tsukuba 353 −28.9 ± 203.0 −0.66 ± 14.26Edwards 62 380.7 ± 410.5 26.79 ± 27.23JPL 65 −299.3 ± 574.9 −12.45 ± 31.18Pasadena 113 −107.1 ± 180.4 −4.77 ± 8.11Saga 72 −155.9 ± 289.6 −7.60 ± 13.67Darwin 116 −389.7 ± 536.0 −10.98 ± 14.71Wollongong 211 −410.1 ± 438.7 −16.50 ± 17.43Lauder 177 −6.9 ± 75.7 −0.51 ± 5.99Ensemble bias 1940 −103.2 ± 356.5 −3.09 ± 17.72Station bias 16 −110.1 ± 188.6 −3.11 ± 9.47Figure 3. Correction of Figure 3 in [1]. Mean relative bias (filled circles) and associated standarddeviation (“error bars” representing ± σ) as a function of the latitude of the TCCON sites, forcoincidence criteria of ±30 min and ±1◦ in latitude and longitude. The dataset names andcorresponding number of coincidences are shown on the right-hand side, color-coded from purple tored in order of decreasing latitude from the northernmost site (Sodankylä, 67.4◦N) to the southernmoststation (Lauder, 45.0◦S). The size of the symbols is proportional to the number of coincidences ateach site.Remote Sens. 2016, 8, 982 4 of 7Table 3. Correction of Table 3 in [1]. Linear regression parameters (slope and intercept) and correlationcoefficient (R) for TANSO-FTS scans acquired over land within ±1◦ in latitude and in longitude ofthe TCCON sites and the average of TCCON measurements within ±30 min of the correspondingGOSAT overpasses.TCCON # of Scans Slope Intercept RDataset (ppm/ppm) (ppm)Sodankylä 33 0.75 368.1 0.77Bialystok 23 0.93 62.7 0.97Bremen 13 1.02 −24.8 1.00Karlsruhe 39 0.88 82.6 0.97Orléans 96 0.99 8.0 0.97Garmisch 56 0.89 104.3 0.95Park Falls 165 0.99 7.7 0.96Lamont 346 0.93 130.5 0.98Tsukuba 353 0.94 53.4 0.97Edwards 62 0.91 557.5 0.94JPL 65 0.70 297.2 0.75Pasadena 113 0.94 17.4 0.99Saga 72 0.92 4.9 0.97Darwin 116 0.70 519.0 0.87Wollongong 211 0.83 10.0 0.93Lauder 177 1.00 −3.8 0.99Ensemble bias 1940 0.88 136.7 0.95Station bias 16 0.72 491.9 0.87Figure 4. Correction of Figure 4 in [1]. Scatter plot of the GOSAT TANSO-FTS XH2O and coincidentTCCON soundings (criteria of ±30 min and ±1◦ in latitude/longitude). For these criteria, there are nocoincident TANSO-FTS ocean scans. The caption and color-coding are identical to those of Figure 3.Figure 6. Correction of Figure 6 in [1]. Scatter plot of the GOSAT TANSO-FTS XH2O and coincidentTCCON soundings (criteria of ±30 min and ±1◦ in latitude/longitude) at the Lamont (left) and Lauder(right) TCCON sites. All coincidences were found for TANSO-FTS land scans.Remote Sens. 2016, 8, 982 5 of 7Figure 7. Correction of Figure 7 in [1]. Time series of XH2O at six TCCON sites for collocated TANSO-FTSdata (±1◦ latitude/longitude, no time constraint) and for the average of TCCON measurementsacquired within ±30 min of a GOSAT overpass. TCCON sites are ordered from top to bottom bydecreasing latitude. For each site, the top panel shows the XH2O time series of GOSAT (red diamonds)and TCCON (blue circles). Bottom panel: absolute differences (GOSAT−TCCON) for spatially- andtemporally-coincident pairs.Remote Sens. 2016, 8, 982 6 of 7Figure 8. Correction of Figure 8 in [1]. Evolution of the XH2O absolute differences (GOSAT−TCCON)for the nominal coincidence criteria (±1◦ latitude/longitude and ±30 min) as a function of themeasurement date (time series, top left panel) and of the collocation characteristics: time, latitude andlongitude differences (top right, bottom left and bottom right panels, respectively). The correspondinghistograms of the number of TANSO-FTS scans are plotted below each panel. The grey dots representthe single-scan differences; the red symbols with “error bars” show the average value and associatedstandard deviation within each histogram bin.sFigure 9. Correction of Figure 9 in [1]. Relative differences (GOSAT−TCCON)/TCCON as a functionof the difference, in meters, between the retrieved altitude of the GOSAT footprints and the altitude ofthe TCCON sites, for GOSAT land scans only. The caption and color-coding are identical to those ofFigure 3.Remote Sens. 2016, 8, 982 7 of 7Figure 10. Correction of Figure 10 in [1]. Evolution of the XH2O absolute differences (GOSAT−TCCON)for the nominal coincidence criteria (±1◦ latitude/longitude and ±30 min), as a function of geophysicaland retrieval parameters: the TANSO-FTS and TCCON XH2O (top row), the solar zenith angle valuesfor GOSAT and TCCON (middle row), the difference between the retrieved and the a priori valuesfor the surface pressure (bottom left) and the aerosol optical depth at 1.6µm retrieved from theTANSO-FTS spectra (bottom right). The corresponding histograms of the number of TANSO-FTS scansare plotted below each panel. The grey dots represent the single-scan differences; the red symbols with“error bars” show the average value and associated standard deviation within each histogram bin.Reference1. Dupuy, E.; Morino, I.; Deutscher, N.M.; Yoshida, Y.; Uchino, O.; Connor, B.J.; De Mazière, M.; Griffith, D.W.T.;Hase, F.; Heikkinen, P.; et al. Comparison of XH2O Retrieved from GOSAT Short-Wavelength InfraredSpectra with Observations from the TCCON Network. Remote Sens. 2016, 8, 414.c© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

Correction : Dupuy, E., et al. Comparison of XH₂O retrieved from gosat short-wavelength infrared spectra with observations from the tccon network. Remote Sens. 2016, 8, 414

https://publikationen.bibliothek.kit.edu/1000065608/4281055

Correction : Dupuy, E., et al. Comparison of XH₂O retrieved from gosat short-wavelength infrared spectra with observations from the tccon network. Remote Sens. 2016, 8, 414

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