Riverside team works on Artificial Intelligence project processing satellite data with MIIDAPS software.

                Window Channel Radiance

              Window Channel Radiance

Riverside team members Eric Maddy and Adam Neiss are supporting NOAA’s Center for Satellite Applications and Research (STAR) to develop a proof of concept algorithm utilizing machine learning (ML) and artificial intelligence (AI) techniques applied to remote sensing, data assimilation, numerical weather prediction, and radiative transfer. The team leveraged the Multi-Instrument Inversion and Data Assimilation Preprocessing System (MIIDAPS) - a software package for remote sensing, data assimilation, preprocessing, and quality control - to develop MIIDAPS-AI, the artificial intelligence extension of MIIDAPS.

           ABI water cloud top pressure

         ABI water cloud top pressure

Currently, MIIDAPS processes passive microwave (PMW) as well as geostationary and polar orbiting infrared (IR) sounder and imager observations to provide the simultaneous inversion / of profiles of temperature, humidity, cloud, rain and ice, trace gases (CO, CO2, CH4, N2O), as well as the surface emissivity and skin temperature.

 MIIDAPS-AI is applicable to the same sensors and applications and matches the performance of the traditional remote sensing algorithms. The main advantage of MIIDAPS-AI is the greatly improved efficiency in computing performance - excluding I/O and data preprocessing. The full-physics MIIDAPS-AI product generation takes just a few seconds compared to several hours for the 1DVAR physical MIIDAPS algorithm.

                                    ECMWF ice cloud top pressure

                                  ECMWF ice cloud top pressure

 ECMWF water cloud top pressure

ECMWF water cloud top pressure

Eric Maddy began development of MIIDPAS-AI 10 months ago by training the AI to process the data produced by the Suomi-NPP ATMS sensor. In the last six months, with the assistance from Adam Neiss, MIIDAPS-AI has been extended to six additional sensors: Suomi-NPP CrIS, MetOp-A AMSU-A/MHS, MetOp-B AMSU-A/MHS, NOAA-18 AMSU-A/MHS, NOAA-20 ATMS, and GOES-16 ABI. MIIDAPS-AI runs daily and produces research-level products for each sensor.  Below is an animation of GOES-16 ABI, ECMWF water and ice cloud top pressures, and ABI window channel radiances. MIIDAPS-AI products and more information can be found at: star.nesdis.noaa.gov/MIIDAPS-AI.