GHGs Trend Viewer
with GOSAT Long term target observation

NIES GOSAT retrieval

Last update: 2019/03/15

1. Introduction

TANSO-FTS simultaneously observes both reflected shortwave-infrared (SWIR) solar light and thermal infrared (TIR) emissions with a single FTS-mechanism. We use an entire TIR band to add only one piece of information in the troposphere. Assuming the CO2 and CH4 partial column-averaged dry air mole fractions of the two individual layers of LT and UT are constant, we retrieve the difference between the partial column-averaged dry mole fractions of the lower troposphere (LT) and upper troposphere (UT) by combining TIR and SWIR spectra data simultaneously, constraining accurate total column density. The pressure-height ranges of LT and UT are taken as 1 -0.6 and 0.6 -0.2 of the retrieved surface pressure, respectively.

The GHG long term trend viewer presents quick view and pick up data set of the target observation sites, where users are interested. Most of the target observations requested by the RA researchers are not included in the list.

2. Data description

About data category

About parameter

About data extraction

In order to use long term trend data of the point of interest, the viewer pick up data within the circle of 10km radius.

But the following adjacent site, the viewer pick up within the circle of 1km or 2km radius.

[circle of 1km radius]

Pasadena_downtown
Caltech_USA
Osaka3, Osaka4
Bakersfield4 - 6
Boston4, Boston5, Greece4, Greece5

[circle of 2km radius]

JPL
Tokyo6, 8, 11 - 13
Osaka5
Bakersfield2, Bakersfield3
Aliso_Canyon2 - 4
Namibia1 - 3
Antarctica1 - 4
Beijing1 - 16
Shanghai1 - 13
Delhi1 - 16
Dhaka1 - 16
MexicoCity1 - 16
Istanbul1 - 16
Cairo1 - 15
CebuIsland1, 2
Sacramento(Rice Field), Sacramento(CA Capitol)
Karachi1 - 16

The primary pointing system, which had been used between launch and Dec. 2014, larger pointing offset of about 5km.

Therefore, some cases include nearby target points.

3. Citation

Algorithm:

Ancillary data

5. Links

6. Acknowledgments

GHG Long term trend viewer was developed by JAXA/EORC. We would like to thank NIES GOSAT project members, and JAXA GOSAT project members.