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Shin Koyamatsu homes in on the most meaningful infrared sounder data
Using new machine learning methods to further the potential of EUMETSAT data
EUMETSAT
1
https://www-cdn.eumetsat.int/files/2020-04/pdf_iasi_val_rep.pdf
https://www-cdn.eumetsat.int/files/2020-04/pdf_ss_o2_ctp_metimage_fin_rep.pdf
https://www-cdn.eumetsat.int/files/2020-04/pdf_ss_eps_ascat_ocean_wind_fin_rep.pdf
https://www-cdn.eumetsat.int/files/2020-04/pdf_ss_epssg_3mi_grasp_final_rep.pdf
https://www-cdn.eumetsat.int/files/2022-07/Independent%20validation%20of%20CH4%20products%20from%20IASI%20%28ITT%2018_205%29%20-%20Final%20Report.pdf
https://www-cdn.eumetsat.int/files/2020-06/pdf_ss_3mi_aerosol_algorithm_final_pres.pdf
https://www-cdn.eumetsat.int/files/2020-06/pdf_ss_3mi_aerosol_algorithm_final_rep.pdf
https://www-cdn.eumetsat.int/files/2020-04/pdf_ss_o2_ctp_metimage.pdf
3
https://www-cdn.eumetsat.int/files/2023-01/EUMETSAT_UserDays2022-MTG-EPS-SG_Report.pdf
https://www-cdn.eumetsat.int/files/2020-04/pdf_ss_3mi_cloud_algor_develop_final_rep.pdf