Near Real Time SST Retrievals from Himawari-8 Data with ACSPO at NOAA

Near Real Time SST retrievals from Himawari-8 data with ACSPO at NOAA

Maxim Kramara,b, Alex Ignatovb, Boris Petrenkoa,b, Yury Kihaia,b, and Prasanjit Dashb,c aGlobal Science and Technology, Greenbelt, MD 20770, USA bNOAA, College Park, MD 20740, USA cCooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, USA

ABSTRACT The Advanced Himawari Imager (AHI) onboard the recently launched Himawari-8 geostationary satellite provides observations with an unprecedented combination of spatial and spectral resolutions and spectral coverage. Full disk (FD) (5500x5500 pixels, with 2 km resolution at the nadir) is available every 10 minutes in ﬁve SST bands centered at 3.9, 8.6, 10.4, 11.2, and 12.3 microns. The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) has been adapted to process the AHI data. Experimental near real time production of L2 SST with native AHI spatial and temporal resolution commenced at NOAA/STAR on July 6, 2015, and data from 11 June 2015 to present are processed and posted at ftp://ftp.star.nesdis.noaa.gov/pub/sod/sst/acspo_data/l2/ahi/. Normally, there are 142 FD AC- SPO granules per day in GDS2 format ( 45 Gbytes/day). The product is routinely monitored and validated against in situ data in the NOAA SST Quality Monitor (SQUAM; www.star.nesdis.noaa.gov/sod/sst/squam/GEO/). The 10-min validation statistics show a typical bias within ±0.2 and standard deviation within ∼ 0.6K. Work is underway to generate a reduced volume ACSPO AHI SST product (L2C collated in time, e.g. 1hr, in the original swath projection, or L3C collated in time and gridded in space by interpolating/approximating SST L2 data) and archive with NASA PO.DAAC and NOAA NCEI. The same ACSPO algorithms will be applied to the data of the Advanced Baseline Imager (ABI; a sister sensor to AHI) onboard the US new generation GOES-R satellite (to be launched in late 2016), and similar SST products will be generated. Keywords: Sea surface temperature, Himawari, AHI, GOES-R, ABI

1. INTRODUCTION Himawari-8 was launched on 7 October 2014 by JAXA. The AHI (Advanced Himawari Imager) onboard Himawari- 8/9 significantly improves upon the previous generation Himawari-7 (MTSAT-2) imager. AHI provides 5500 × 5500 Full Disk (FD) observation images in 16 channels with 10 minutes temporal resolution. The Advanced Clear-Sky Processor for Ocean (ACSPO), developed at the National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) in conjunction with the Office of Satellite and Product Operations (OSPO), is intended to produce clear-sky products over oceans for AVHRR, MODIS, VIIRS, and AHI. These products include clear-sky radiances (CSR), sea surface temperature (SST), and aerosol optical depths (AOD). ACSPO reads in appropriate AVHRR, MODIS, VIIRS, or AHI Level 1B files, performs retrievals, and writes the results to an output file.1 The ACSPO was previously developed and used for operational and experimental processing of polar-orbiting sensors, such as AVHRRs of NOAA-18 and -19, MetOp-A and B; Aqua and Terra MODIS and S-NPP VIIRS. This paper describes the structure of the AHI data processing and the related L2P SST product generated by ACSPO. Further author information: (Send correspondence to M.K. and A.I.) M.K.: E-mail: [email protected] A.I.: E-mail: [email protected] 2. ACSPO The Advanced Clear-Sky Processor for Ocean (ACSPO), developed at the National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) in conjunction with the Office of Satellite and Product Operations (OSPO), is intended to produce clear-sky products over oceans for AVHRR, MODIS, VIIRS, and AHI. These products include clear-sky radiances (CSR), sea surface temperature (SST), and aerosol optical depths (AOD). ACSPO reads in appropriate AVHRR, MODIS, VIIRS, or AHI Level 1B files, performs retrievals, and writes the results to an output file.1 The flow chart of the ACSPO SST retrieval is shown in Figure 1. The input for ACSPO includes brightness temperatures (BTs) measured in the AHI infrared bands 11, 13, 14, and 15 and the reflectance measured in the optical AHI band 4 as well as auxiliary data such as the analysis L4 SST by Canadian Mete- orological Centre (CMC)2 and the atmospheric profiles from the Global Forecast System (GFS, available at www.nco.ncep.noaa.gov/pmb/products/gfs/). The auxiliary data is used as input for the Community Radiative Transfer Model (CRTM),3 which is used in ACSPO to simulate clear-sky brightness temperatures. The ACSPO system effectively generates two SST products: the Baseline SST and the Piecewise Regression SST4 seeking to resolve the difference between skin and depth SST.5 The coefficients for both products are trained on the datasets of matchups of the ACSPO clear-sky BTs identified with the ACSPO Clear-Sky Mask (ACSM).6 and quality-controlled in situ SST from the NOAA in situ Quality Monitor (iQuam).1 The first product, the Baseline SST (BSST), is estimated with global regression equations trained on global datasets of matchups and implements a tradeoff between the precision of fitting in situ SST (i.e., depth SST), and sensitivity to skin SST.7 The second product, the Piecewise Regression (PWR) SST, is generated with multiple equations specific to separate segments of the global SST domain. The PWR SST fits TSis more precisely than BSST but does not guarantee high sensitivity to skin SST. The BSST equation for AHI is different for the one used for processing data of polar-orbiting sensors in ACSPO7 and exploits four AHI bands as follows:

TS = c0 + c1T10.4 + c2(T10.4 − T12) + [c3(T10.4 − T8.6)+ c4(T10.4 − T11)] Sθ + 0 + [c5(T10.4 − T8.6)+ c6(T10.4 − T11)+ c7(T10.4 − T12)] TS. (1)

Here T8.6, T10.4, T11, T12 are observed BTs at 8.6, 10.4, 11.2, and 12.3 µm (AHI bands 11, 13, 14, and 15, 0 ◦ respectively). Sθ = 1/ cos θ where θ is satellite view zenith angle. TS is first guess SST (in C) obtained from CMC. Coefficients c0, c1, c2, c3, c4, c5, c6, and c7 are regression coefficients with values shown in Table 1.

Table 1. Regression coeﬃcients.

c0 c1 c2 c3 c4 c5 c6 c7 38.112282 0.876435 0.826084 0.511226 0.561733 0.020591 0.034769 0.078092

The PWR SST uses a similar formulation of the SST equation, but with coefficients specific to different segments, on which the whole SST domain is subdivided. The theoretical basis for PWR SST is given in [4]. The aforementioned segmentation of the SST domain is also used to estimate sensor-specific error statistics (SSES), i.e., bias and standard deviation (SD) of retrieved SST, as required by the GHRSST Data Specification format (GDS 2.0).8 The SSES bias is estimated at each pixel as difference between BSST and PWR SST; SSES SD is estimated for each segment as SD of BSST and in situ SST within the training dataset of matchups. Only matches with drifters and tropical moored buoys were used. The time interval between in situ and satellite measurements was limited with 4 hours, and the distances between the buoy locations and the nearest clear-sky pixel were < 20 km. Cloud screening is performed with the ACSM (Reference), modified for AHI. 3. VALIDATION AGAINST IN-SITU DATA The Web-based SST quality monitor (SQUAM) is employed to continuously control the quality of the SST products.9 SQUAM performs analyses of SST differences between satellite derived SSTs and various in-situ and L4 products. Processing is done automatically and results are posted online in near real time. The SQUAM was previously used for monitoring of SST products for polar-orbiting sensors, such as AVHRRs of NOAA-18 and -19, MetOp-A and B; Aqua and Terra MODIS and S-NPP VIIRS. With the launch of Himawari-8, the SQUAM has been updated to monitor SST products based on data from various geostationary satellite, such as Himawari-7/8, GOES-R (http://www.star.nesdis.noaa.gov/sod/sst/squam/GEO/).

4. RESULTS Figure 2 shows histogram of differences between AHI SST and drifters and tropical moorings for two observation UTC times on July 15, 2015 - 02:20 (left) and 14:20 (right). UTC times of 02:20 and 14:20 closely (within about half an hour) correspond to local noon and local midnight at Himawari-8 sub-satellite point, respectively. Both histograms are close to Gaussian distribution with the mean and standard deviation of 0.19 and 0.51 K during local noon and 0.03 and 0.43 K during local midnight, respectively. It is interesting to compare AHI SST with that from previous generation geostationary satellite Himawari- 7/MTSAT-2. MTSAT-2 was stationed at around 145◦ east longitude, close to Himawari-8 (140.7◦ east longitude). SST based on MTSAT-2 data was routinely calculated at OSPO (reference). There are ∼ 150 matchups per granule for ACSPO Himawari-8, and ∼ 80 for MTSAT-2. Figure 3 shows histogram of differences between MTSAT-2 SST and drifters and tropical moorings for two observation UTC times on July 15, 2015 - 02:30 (left) and 14:30 (right). UTC times of 02:30 and 14:30 closely (within about half an hour) correspond to local noon and local midnight at MTSAT-2 sub-satellite point, respectively. We see that while the histograms for AHI and MTSAT-2 during local midnight are similar, the histograms for MTSAT-2 during local noon has a much wider distribution with the mean and standard deviation of −0.09 and 0.88 K, respectively. Why? A timeseries of median (left) and standard deviation (right) of differences between satellite derived SSTs and drifters and tropical moorings for SSTs based on both instruments are shown on Figure 4. Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point. Local noon and midnight for MTSAT-2 sub-satellite point are close to those of Himawari-8 within about 20 minutes. We see that the mean for AHI ACSPO SST is typically ∼ 0.1–0.2 K during local noon and close to zero during local midnight. Taking into account that the used in the analysis in-situ data are rather close to bulk SST, the AHI ACSPO SST is clearly follows diurnal cycle. Figure 5 shows timeseries of median (left) and standard deviation (right) of differences between satellite derived SSTs and CMC. The satellite derived SSTs are shown for Himawari-8 ACSPO (black) and Himawari-7 OSPO (red).

4.1 Comparison with AHI JAXA SST It is interesting to compare AHI ACSPO SST with similar product from JAXA.10 As JAXA has improved their product starting from mid December, 2015, we prefer to plot ACSPO and JAXA SST histograms and time series for appropriate time similarly to the comparison with MTSAT. Figures 6 and 7 shows histogram of differences between ACSPO and JAXA SST, respectively, and drifters and tropical moorings for two observation UTC times on January 7, 2016 - 02:30 (left) and 14:30 (right). We see that JAXA SST has lower bias and larger standard deviation than ACSPO SST. A timeseries of median (left) and standard deviation (right) of differences between the satellite derived SSTs and drifters and tropical moorings for ACSPO and JAXA SST are shown on Figure 8. Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point. Figure 9 shows timeseries of median (left) and standard deviation (right) of differences between satellite derived SSTs and CMC. The satellite derived SSTs are shown for Himawari-8 ACSPO (black) and Himawari-8 JAXA (red). A longer time series are shown on Figure 10. Figure 11 shows time series of coverage of the clear sky pixels over the ocean for all three analyzed SST products – ACSPO AHI, JAXA AHI, and OSTIA MTSAT. Figure 12 shows the same time series but for longer period.

5. CONCLUSION The ACSPO has been adapted to process the AHI data. Experimental near real time production of L2P SST with native AHI spatial and temporal resolution has been commenced at NOAA/STAR on July 6, 2015, and data from 11 June 2015 till present are processed and posted at ftp://ftp.star.nesdis.noaa.gov/pub/sod/sst/acspo_data/l2/ahi/. Normally, there are 142 FD ACSPO granules per day in GDS2 format ( 45 Gbytes/day). The product is routinely monitored and validated against in situ data in the NOAA SST Quality Monitor (SQUAM; www.star.nesdis.noaa.gov/sod/sst/squam/GEO/). The 10-min validation statistics show a typical bias within ±0.2 and standard deviation within ∼ 0.6K. That is close to JPSS specs (which again are much more stringent than the GOES-R specs) (reference).

REFERENCES [1] Xu, F. and Ignatov, A., “In situ sst quality monitor (iquam),” Journal of Atmospheric and Oceanic Tech- nology 31(1), 164–180 (2014). [2] Brasnett, B. and Colan, D. S., “Assimilating retrievals of sea surface temperature from viirs and amsr2,” Journal of Atmospheric and Oceanic Technology 33(2), 361–375 (2016). [3] Liang, X.-M., Ignatov, A., and Kihai, Y., “Implementation of the community radiative transfer model in advanced clear-sky processor for oceans and validation against nighttime avhrr radiances,” Journal of Geophysical Research: Atmospheres 114(D6), n/a–n/a (2009). D06112. [4] Petrenko, B., Ignatov, A., Kihai, Y., and Dash, P., “Sensor-speciﬁc error statistics for sst in the advanced clear-sky processor for oceans,” Journal of Atmospheric and Oceanic Technology 33(2), 345–359 (2016). [5] Donlon, C., Robinson, I., Casey, K. S., Vazquez-Cuervo, J., Armstrong, E., Arino, O., Gentemann, C., May, D., Leborgne, P., Pioll´e, J., Barton, I., Beggs, H., Poulter, D. J. S., Merchant, C. J., Bingham, A., Heinz, S., Harris, A., Wick, G., Emery, B., Minnett, P., Evans, R., Llewellyn-Jones, D., Mutlow, C., Reynolds, R. W., Kawamura, H., and Rayner, N., “The global ocean data assimilation experiment high-resolution sea surface temperature pilot project,” Bulletin of the American Meteorological Society 88, 1197 (2007). [6] Petrenko, B., Ignatov, A., Kihai, Y., and Heidinger, A., “Clear-sky mask for the advanced clear-sky processor for oceans,” Journal of Atmospheric and Oceanic Technology 27, 1609–1623 (Oct. 2010). [7] Petrenko, B., Ignatov, A., Kihai, Y., Stroup, J., and Dash, P., “Evaluation and selection of sst regression algorithms for jpss viirs,” Journal of Geophysical Research (Atmospheres) 119, 4580–4599 (Apr. 2014). [8] https://www.ghrsst.org/files/download.php?m=documents&f=121009233443-GDS20r5.pdf. [9] Dash, P., Ignatov, A., Kihai, Y., and Sapper, J., “The sst quality monitor (squam),” Journal of Atmospheric and Oceanic Technology 27(11), 1899–1917 (2010). [10] Kurihara, Y., Murakami, H., and Kachi, M., “Sea surface temperature from the new japanese geostationary meteorological himawari-8 satellite,” Geophysical Research Letters 43(3), 1234–1240 (2016). 2015GL067159. L4 CMC (Canadian Met Observed Brightness GFS atmospheric Center) SST Temperatures profiles

CRTM clear-sky simulations

Baseline SST (BSST) retrieval

Piecewise Regression (PWR) SST retrieval, Estimation of Sensor-Specific Errors Statistics (SSES)

ACSPO Clear-Sky Mask (ACSM)

Figure 1. The Flow Chart of ACSPO. Figure 2. Histogram of diﬀerences between AHI SST and drifters and tropical moorings for two observation UTC times on July 15, 2015 - 02:20 (left) and 14:20 (right). UTC times of 02:20 and 14:20 closely (within about half an hour) correspond to local noon and local midnight at Himawari-8 sub-satellite point, respectively.

Figure 3. Histogram of diﬀerences between Himawari-7 OSPO SST and drifters and tropical moorings for two observation UTC times on July 15, 2015 - 02:30 (left) and 14:30 (right). UTC times of 02:30 and 14:30 closely (within about half an hour) correspond to local noon and local midnight at Himawari-7 sub-satellite point, respectively. Figure 4. Timeseries of median (left) and standard deviation (right) of diﬀerences between satellite derived SSTs and drifters and tropical moorings. The satellite derived SSTs are shown for Himawari-8 ACSPO (black) and Himawari-7 OSPO (red). Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point.

Figure 5. Timeseries of median (left) and standard deviation (right) of diﬀerences between satellite derived SSTs and CMC. The satellite derived SSTs are shown for Himawari-8 ACSPO (black) and Himawari-7 OSPO (red). Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point. Figure 6. Histogram of diﬀerences between AHI SST and drifters and tropical moorings for two observation UTC times on January 7, 2016 - 02:30 (left) and 14:30 (right). UTC times of 02:30 and 14:30 closely (within about half an hour) correspond to local noon and local midnight at Himawari-8 sub-satellite point, respectively.

Figure 7. Histogram of diﬀerences between JAXA SST and drifters and tropical moorings for two observation UTC times on January 7, 2016 - 02:30 (left) and 14:30 (right). UTC times of 02:30 and 14:30 closely (within about half an hour) correspond to local noon and local midnight at Himawari-8 sub-satellite point, respectively. Figure 8. Timeseries of median (left) and standard deviation (right) of diﬀerences between satellite derived SSTs and drifters and tropical moorings. The satellite derived SSTs are shown for Himawari-8 ACSPO (black) and Himawari-8 JAXA (red). Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point.

Figure 9. Timeseries of median (left) and standard deviation (right) of diﬀerences between satellite derived SSTs and CMC. The satellite derived SSTs are shown for Himawari-8 ACSPO (black) and Himawari-8 JAXA (red). Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point. Figure 10. Timeseries of median (left) and standard deviation (right) of diﬀerences between satellite derived SSTs and CMC. The satellite derived SSTs are shown for Himawari-8 ACSPO (green), Himawari-8 JAXA (blue), and MTSAT OSPO (red). Figure 11. Timeseries of percentage of clear-sky pixels over the ocean for Himawari-8 ACSPO (black), Himawari-8 JAXA (red on right), and MTSAT OSPO (red on left). Vertical dashed lines mark local noon (green) and midnight (blue) for Himawari-8 sub-satellite point. Also on left in blue is Himawari-8 JAXA (temporaly for test).

Figure 12. Timeseries of percentage of clear-sky pixels over the ocean for Himawari-8 ACSPO (black), Himawari-8 JAXA (blue), and MTSAT OSPO (red). Left panel – original time series. Right panel obtained from the left one by time averaging over moving window of one day width.