New satellite constellations to provide high-resolution atmospheric observations from microwave (MW) sounders operating in low-Earth orbit are now coming online and are providing operationally useful data. The first of these missions, the NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Earth Venture (EVI-3) mission, was successfully launched into orbit on May 7 and 25, 2023 (Eastern Daylight Time, two CubeSats in each of the two launches). TROPICS is now providing nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS is providing rapid-refresh MW measurements (median refresh rate of better than 60 min early in the mission with four functional CubeSats, and now approximately 70–90 min with three functional CubeSats) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. Hundreds of high-resolution images of TCs have been captured thus far by the TROPICS mission, revealing the detailed structure of the eyewall and surrounding rain bands. The new 205-GHz channel in particular (together with a traditional channel near 92 GHz) is providing new information on the inner storm structure, and, coupled with the relatively frequent revisit and low downlink latency, is already informing TC analysis at operational centers. Here, we present an overview of the TROPICS mission after two years of successful science operations with a focus on the suite of geophysical (Level 2) products (atmospheric vertical temperature and moisture profiles, instantaneous surface rain rate, and TC intensity) and the science investigations that have been enabled by these new measurements.

Active radar instruments provide vertically resolved clouds and precipitation measurements that cannot be provided by the passive instruments. These active measurements are not conventionally assimilated into the data assimilation systems because of the lack of fast forward radiative transfer models and also difficulties in the error modelling of the measurements. This paper describes the development, evaluation, and sensitivity analysis for a forward radar model implemented in the Community Radiative Transfer Model (CRTM). The scattering properties required by the forward model are provided by the hydrometeor lookup tables that were generated using the discrete dipole approximation. The model is able to calculate both the reflectivity and the attenuated reflectivity for any given radar instrument at any given zenith angles as long as CRTM instrument specific coefficients are available. The evaluation using CloudSat measurements shows a very good agreement between the simulations and measurements as long as the input profiles of hydrometeors are consistent with the measured reflectivity profiles. Major sources contributing to the differences between the measured and simulated reflectivities are input hydrometeor profiles, scattering lookup tables, lack of melting layer in the forward model, CRTM scattering solvers, and attenuation calculations. In addition to the forward model, both Tangent Linear and Adjoint of the model are also implemented and tested within CRTM. These components may be required by some data assimilation systems for the assimilation of radar measurements.

This paper presents an overview of the Hyperspectral Microwave Photonic Instrument (HyMPI), a 2021 NASA Instrument Incubation Proposal funded project aimed at developing the very first hyperspectral microwave sensor to augment thermodynamic sounding capability from space, with a focus on the Earth's Planetary Boundary Layer. This research responds to the recommendation expressed in the 2018 National Academies of Sciences decadal survey to accelerate the readiness of high-priority PBL observables not feasible for cost-effective spaceflight in 2017–2027. This paper provides an overview on HyMPI's design, configured as the objective instrument concept needed to fly in the future PBL mission and presents preliminary trade studies aim at demonstrating HyMPI's enhanced thermodynamic sounding skill in the Earth's Planetary Boundary Layer over conventional microwave sounders from the current Program of Record.

We present an overview of the Hyperspectral Microwave Photonic Instrument (HyMPI), a NASA Instrument Incubation Proposal funded research project aimed at developing a hyperspectral microwave instrument intended for enhanced remote sensing of atmospheric temperature and water vapor from space. This paper provides preliminary results on HyMPI's spectral and noise characteristics and a preliminary demonstration of its enhanced water vapor sensitivity and vertical resolution, with a particular focus on the Earth's Planetary Boundary Layer.

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA's Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs show RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations shows that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

In the recent years, the Earth observation (EO) capacity from space has grown with the multiplication of both institutional and commercial missions; in particular the domain of high-resolution optical sensors and SAR (Synthetic Aperture Radar) has dramatically increased. The “NewSpace players” are considered in full in the evolution of the EO international strategy. In this context, ESA and NASA put in place several activities that aim at assessing the data coming from these new missions, like the ESA’ s Earthnet Data Assessment Pilot (EDAP) project and the NASA's Commercial Smallsat Data Acquisition (CSDA) Program. Given the initial success of both of these activities and the multiplication of new missions in the context of the NewSpace, ESA and NASA are proposing to extend these activities with a coordinated approach and the definition of joint guidelines for data quality assessment.

NASA's Commercial Smallsat Data Acquisition (CSDA) program was initiated with a goal of acquiring data from commercial sources that support NASA's Earth science research and application goals. Over the last several years, the CSDA program has evolved into a long-term sustained program. This paper presents an overview of the program, a featured innovative application, and data management capabilities.

Under its Commercial Smallsat Data Acquisition (CSDA) Program, NASA has evaluated data from and entered into a sustained purchase agreement with Spire Global, Inc. The primary goal of this agreement is to make Spire datasets available to the research community to enhance the scientific objectives of the Earth Science Division (ESD), though the applicability to the NASA Heliophysics Division of these data is noted as well. The purpose of this talk is to present the data holdings from Spire and to present scientific results that have utilized these commercially acquired data.