GOSAT CH4 Vertical Profiles over the Indian Subcontinent: Effect of a Priori and Averaging Kernels for Climate Applications
<p>The map of the regional divisions for the analysis (<b>a</b>), depicted by unicolor boxes with the name abbreviations defined in <a href="#sec2dot1-remotesensing-13-01677" class="html-sec">Section 2.1</a>. The black lines in-land show major rivers in the plot domain; the human settlements along the rivers are major sources of CH<sub>4</sub>. The TIR CH<sub>4</sub> a priori with 1-σ SD uncertainty (red line with error bars) and TIR CH<sub>4</sub> profile with the retrieval error (blue line with shaded area) are shown in panels (<b>b</b>,<b>d</b>,<b>f</b>), and the 22 AK functions corresponding to the 22 retrieval layers are in panels (<b>c</b>,<b>e</b>,<b>g</b>). Data in panels (<b>b</b>–<b>g</b>) are shown for the regions Northeast India, Southern India, and the Bay of Bengal, averaged over the period July–September 2011.</p> "> Figure 2
<p>The surface CH<sub>4</sub> fluxes (g-CH<sub>4</sub>/m<sup>2</sup>/month) used for MIROC4-ACTM simulation: (<b>a1</b>,<b>a2</b>) from Cao scheme, (<b>b1</b>,<b>b2</b>) difference between schemes (WH—Cao). Panels (<b>a1</b>,<b>b1</b>), and (<b>a2</b>,<b>b2</b>) are for AMJ and JAS, respectively.</p> "> Figure 3
<p>Wind vectors for the JFM (panels <b>a1</b>–<b>a3</b>), AMJ (<b>b1</b>–<b>b3</b>), JAS (<b>c1</b>–<b>c3</b>), and OND (<b>d1</b>–<b>d3</b>) months of 2010 from the MIROC4-ACTM simulations are shown. Please note different vector scales for the levels of 800 (panels <b>a1</b>–<b>d1</b>), 500 (<b>a2</b>–<b>d2</b>), and 200 hPa (<b>a3</b>–<b>d3</b>), respectively. At the background: left panels (<b>a1</b>–<b>d1</b>) show monthly surface pressure (0.9950 sigma level) from the National Centers for Environmental Prediction (NCEP) reanalysis for 2011 (<a href="http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.html" target="_blank">http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.html</a> accessed on 27 March 2021), central panels (<b>a2</b>–<b>d2</b>) show monthly long term mean interpolated outgoing longwave radiation (OLR) from the National Oceanic and Atmospheric Administration (NOAA) for 2011 (<a href="https://www.esrl.noaa.gov/psd/data/gridded/data.interp_OLR.html" target="_blank">https://www.esrl.noaa.gov/psd/data/gridded/data.interp_OLR.html</a> accessed on 27 March 2021), and the right panels (<b>a3</b>–<b>d3</b>) show daily mean cloud top pressure (hPa) from the level-3 MODIS atmosphere daily global product (v6.1) downloaded from the Giovanni online data system (Acker and Leptoukh, 2007) for 2011.</p> "> Figure 4
<p>Latitude–longitude distributions of TIR CH<sub>4</sub> properties at the levels of 800, 500, and 300 hPa (the left, middle, and right panels, respectively) for the season AMJ 2011. The top (<b>a1</b>–<b>a3</b>) and bottom rows show TIR CH<sub>4</sub> observation points numbers, and TIR CH<sub>4</sub> 1-σ SD (<b>b1</b>–<b>b3</b>), respectively.</p> "> Figure 5
<p>Latitude–longitude distributions of CH<sub>4</sub> at the levels of 800, 500, and 300 hPa (the left, middle, and right panels, respectively) observed by GOSAT-TIR for the season AMJ 2011. The top (<b>a1</b>–<b>a3</b>), middle (<b>b1</b>–<b>b3</b>) and bottom (<b>c1</b>–<b>c3</b>) rows show TIR CH<sub>4</sub>, TIR CH<sub>4</sub> a priori, and difference between the TIR CH<sub>4</sub> and a priori distributions, respectively.</p> "> Figure 6
<p>Same as <a href="#remotesensing-13-01677-f005" class="html-fig">Figure 5</a>, but for JAS 2011.</p> "> Figure 7
<p>Latitude–longitude difference in CH<sub>4</sub> distributions simulated by MIROC4-ACTM and observed by GOSAT-TIR at the levels of 800, 500, and 300 hPa (the left, middle, and right panels, respectively) for JAS 2011. The top row (<b>a1</b>–<b>a3</b>) and bottom row (<b>b1</b>–<b>b3</b>) show the difference in CH<sub>4</sub> between GOSAT-TIR, and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>WH</mi> </mrow> </msub> </mrow> </semantics></math>, respectively.</p> "> Figure 8
<p>Seasonal mean CH<sub>4</sub> vertical profiles for pre-monsoon (April–June) and monsoon (July–September) of 2011 are shown in the left and right part of each panels (<b>b</b>–<b>k</b>) for the different regions as depicted in the central map (<b>a</b>). Black line with error bars shows the GOSAT-TIR data with 1-σ SD uncertainty. Blue and red lines with shaded areas correspond to the <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mrow> <mi>WH</mi> </mrow> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> data with 1-σ SD uncertainty, respectively.</p> "> Figure 9
<p>Seasonal mean CH<sub>4</sub> vertical profiles (<b>a</b>–<b>e</b>) for winter (January–March) and (<b>f</b>–<b>j</b>) monsoon (July–September) periods of 2011 are shown for the selected regions. Black line shows the GOSAT-TIR a priori data. Green and magenta lines with shaded areas correspond to the <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>WH</mi> </mrow> </msub> </mrow> </semantics></math> data with 1-σ SD uncertainty, respectively. Red and blue lines represent the CH<sub>4</sub> from <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mrow> <mi>WH</mi> </mrow> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> smoothed with the AK functions implementation.</p> "> Figure 10
<p>Time–altitude cross-section of CH<sub>4</sub> from GOSAT-TIR retrieval, GOSAT-TIR a priori, and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> (the left, middle, and right panels, respectively) for the Arabian Sea, Arid, and EIGP regions (for all regions please see <a href="#app1-remotesensing-13-01677" class="html-app">Figure S7</a>). Note that the profiles are shown for the tropospheric altitudes because the GOSAT-TIR retrieval system is not sensitive to the stratospheric altitudes (see <a href="#remotesensing-13-01677-f008" class="html-fig">Figure 8</a> and the associated text).</p> "> Figure 11
<p>Multi-year (2009–2014) seasonal variation of CH<sub>4</sub> (right <span class="html-italic">y</span>-axis) derived by implementation of the Prophet model for levels of 800 (red lines) and 300 hPa (blue lines) over considered regions from GOSAT-TIR (solid line), <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> (dashed line), and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>WH</mi> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math> (dotted line), respectively. At the background, bar plots represent Cao (dark grey) and WH (light grey) CH<sub>4</sub> fluxes (left <span class="html-italic">y</span>-axis), respectively. Please note the different scale of <span class="html-italic">y</span>-axes (left) for fluxes.</p> "> Figure 12
<p>Time series of CH<sub>4</sub> averaged over the area of South Asia for levels of (<b>a</b>) 300, (<b>b</b>) 500 and (<b>c</b>) 800 hPa. Symbols state the GOSAT-TIR observations, red and blue lines are for <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mrow> <mi>WH</mi> </mrow> </mrow> <mrow> <mi>AK</mi> </mrow> </msubsup> </mrow> </semantics></math>, respectively. Solid and dashed lines are for monthly and yearly averaged concentrations (left <span class="html-italic">y</span>-axis), and dotted line shows the difference between the model simulations (right <span class="html-italic">y</span>-axis), respectively. The same results, but without implementation of the AK functions is shown in <a href="#app1-remotesensing-13-01677" class="html-app">Figure S9</a>.</p> "> Figure 13
<p>Seasonal variation of monthly mean CH<sub>4</sub> derived from ground observations, GOSAT a priori, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>WH</mi> </mrow> </msub> </mrow> </semantics></math> over observational sites: (<b>a</b>) BKT, (<b>b</b>) CRI, (<b>c</b>) PBL, (<b>d</b>) PON, (<b>e</b>) SEY, and (<b>f</b>) WLG. Correlation coefficient (<span class="html-italic">r</span>) was calculated for observations vs. GOSAT a priori (<math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">r</mi> <mi mathvariant="normal">G</mi> </msub> </mrow> </semantics></math>), and observations vs. model simulations (<math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">r</mi> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>Cao</mi> </mrow> </msub> </mrow> </msub> <mo>,</mo> <mo> </mo> <msub> <mi mathvariant="normal">r</mi> <mrow> <msub> <mrow> <mi>ACTM</mi> </mrow> <mrow> <mi>WH</mi> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math>) for every site are shown in the upper part of the panels.</p> ">
Abstract
:1. Introduction
2. Methods
2.1. Study Domain
2.2. GOSAT-TIR Retrievals
2.3. TIR CH4 Profile Properties
2.4. MIROC4-ACTM Simulations
2.5. Data Processing
2.6. AK Functions and the Retrieval Sensitivity
2.7. The Prophet Analysis and Forecasting Model
3. Results
3.1. Prevailing Atmospheric Conditions over the Indian Subcontinent
3.2. CH4 over India Observed by GOSAT-TIR and Simulated by MIROC4-ACTM
3.3. CH4 Vertical Profiles
3.4. CH4 Time–Altitude Variation
3.5. Seasonal Variation of CH4
3.6. Regional CH4 Emission Estimation
3.7. Comparison with Ground Observations
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Regions | JFM | AMJ | JAS | OND | ||||
---|---|---|---|---|---|---|---|---|
800 hPa | 300 hPa | 800 hPa | 300 hPa | 800 hPa | 300 hPa | 800 hPa | 300 hPa | |
Arid | –2.4 ± 10.5 | –12.2 ± 3.6 | –42.0 ± 12.2 | –11.2 ± 10.4 | 24.7 ± 19.6 | 26.9 ± 18.0 | 19.7 ± 20.8 | –4.3 ± 4.0 |
Arabian Sea | 2.6 ± 5.6 | –1.1 ± 1.3 | –19.9 ± 14.7 | –4.1 ± 4.7 | –39.5 ± 13.5 | –10.3 ± 8.9 | 56.4 ± 23.8 | 15.4 ± 3.9 |
Bay of Bengal | 11.3 ± 8.2 | 8.3 ± 4.4 | –15.5 ± 26.3 | –5.8 ± 9.5 | –40.4 ± 19.6 | –21.8 ± 7.7 | 44.7 ± 15.7 | 19.2 ± 5.7 |
Central India | –3.1 ± 17.6 | –12.9 ± 4.3 | –51.3 ± 11.6 | –13.2 ± 7.1 | –10.3 ± 50.6 | 17.6 ± 13.9 | 64.6 ± 34.5 | 8.4 ± 12.2 |
Eastern India | 2.4 ± 14.9 | –5.8 ± 6.5 | –43.8 ± 15.4 | –10.9 ± 4.6 | –23.3 ± 50.8 | 1.8 ± 12.9 | 64.9 ± 42.7 | 14.7 ± 5.9 |
East IGP | –25.7 ± 7.8 | –11.2 ± 4.3 | –4.7 ± 11.8 | –4.9 ± 6.4 | 5.5 ± 39.7 | 12.7 ± 9.3 | 25.2 ± 34.4 | 3.5 ± 7.5 |
Northeast India | –3.3 ± 6.2 | –14.1 ± 2.8 | –25.8 ± 27.3 | 0.7 ± 6.0 | –28.2 ± 50.1 | 9.0 ± 10.3 | 57.2 ± 17.7 | 4.6 ± 10.1 |
Southern India | 20.2 ± 14.2 | 3.6 ± 6.7 | –38.8 ± 34.1 | –9.0 ± 7.8 | –60.6 ± 27.2 | –14.3 ± 10.5 | 82.1 ± 29.5 | 20.4 ± 5.8 |
Western India | 1.4 ± 15.0 | –14.4 ± 4.8 | –43.7 ± 10.3 | –11.0 ± 6.5 | –31.6 ± 37.1 | 21.2 ± 13.0 | 73.6 ± 40.8 | 4.3 ± 11.5 |
West IGP | –24.9 ± 6.0 | –11.9 ± 2.9 | –20.2 ± 14.3 | –10.0 ± 11.3 | 42.7 ± 8.5 | 29.5 ± 9.8 | 2.7 ± 26.0 | –7.7 ± 5.3 |
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Belikov, D.A.; Saitoh, N.; Patra, P.K.; Chandra, N. GOSAT CH4 Vertical Profiles over the Indian Subcontinent: Effect of a Priori and Averaging Kernels for Climate Applications. Remote Sens. 2021, 13, 1677. https://doi.org/10.3390/rs13091677
Belikov DA, Saitoh N, Patra PK, Chandra N. GOSAT CH4 Vertical Profiles over the Indian Subcontinent: Effect of a Priori and Averaging Kernels for Climate Applications. Remote Sensing. 2021; 13(9):1677. https://doi.org/10.3390/rs13091677
Chicago/Turabian StyleBelikov, Dmitry A., Naoko Saitoh, Prabir K. Patra, and Naveen Chandra. 2021. "GOSAT CH4 Vertical Profiles over the Indian Subcontinent: Effect of a Priori and Averaging Kernels for Climate Applications" Remote Sensing 13, no. 9: 1677. https://doi.org/10.3390/rs13091677