Explore Tomorrow.io’s Satellite Data FAQs

We partner with agencies globally to complement their existing capabilities, offering rapid data delivery and insights to strengthen disaster response, climate monitoring, and resilience-building initiatives. For more information, reach out to [email protected].

Tomorrow.io integrates TMS data into numerical weather prediction (NWP) using the JEDI DA system with NOAA’s UFS model, alongside datasets already in NOAA’s GDAS. A detailed impact assessment of TMS data using Observation Simulation Experiments (OSEs) has been carried out and a paper has been submitted (Preprints will be available on open access but until then are available on request).

Our Unified Precipitation product combines multiple satellite instruments with machine learning for real-time global precipitation insights. A paper has been submitted on the methodology and the impact of TMS data on precipitation skill scores ( Preprints available here : https://essopenarchive.org/users/864703/articles/1251588-deep-learning-for-multi-satellite-precipitation-retrievals-impact-of-tomorrow-io-s-microwave-sounders). We are also advancing with modern techniques like score-based data assimilation, with a detailed methodology paper in preparation.

Our cloud-based data architecture is designed for scalability and low-latency delivery, providing real-time access to datasets in widely compatible formats like netCDF. For numerical weather prediction (NWP) and data assimilation, we leverage the JEDI framework, ensuring seamless integration with other observational and model datasets. To further minimize observation latency and ensure global coverage, we partner with multiple ground station providers, maximizing downlink opportunities across our constellation.

TMS delivers performance on par with leading heritage systems, with spatial resolution similar to ATMS, MHS, and SSMIS in the 183 GHz water vapor channels – and superior resolution in the 118 GHz temperature sounding channels. Data from our constellation has been benchmarked against GMI, ATMS, ERA5 reanalysis, and radiosonde observations, confirming its reliability. As we continue to expand our satellite network, temporal cadence is improving beyond the current global average revisit time of approximately 120 minutes, with increased frequency in high-priority regions. We have submitted a publication on the calibration of the L1 products. A preprint is available here: https://essopenarchive.org/users/943748/articles/1313761-on-orbit-calibration-of-the-tomorrow-io-microwave-sounders

TMS delivers global coverage comparable to the entire 11-satellite GPM constellation, with significantly better coverage than individual GMI/DPR instruments. As our constellation scales, we are reducing global refresh from roughly 2.5 hours to under 1 hour—providing newer, more actionable data. In addition, TMS offers a suite of Level 2 derived products, including precipitation, that align with and complement GPM outputs. To further reduce latency and increase responsiveness, we leverage multiple ground station providers for rapid downlink and global reach.

MSG/MTG are GEO infrared/visible imagers that see only cloud-top properties and struggle with low-level moisture, especially at night or through thick cloud. TMS is a low-Earth-orbiting microwave sounder: it penetrates cloud to provide vertical temperature & humidity profiles, filling critical gaps (oceans, tropics) and improving data assimilation skill. It complements – rather than replaces – existing radar or GEO assets.

Tomorrow.io is actively participating in NOAA’s Commercial Weather Data Pilot (CWDP), where our TMS data is being evaluated for long-term operational use. Early results have been favorable, confirming the value of our observations. In addition, several federal and university-based groups – including the U.S. Air Force and NASA – are independently assessing our satellite data as part of broader validation and integration efforts.

Tomorrow.io offers flexible licensing tailored to both national meteorological agencies and research institutions. We provide national-level subscriptions for operational forecasting as well as research licenses designed for universities and scientific organizations. For details, reach out to [email protected].

Tomorrow.io’s TMS constellation goes beyond standard atmospheric profiles. Alongside L1 brightness temperature and L2 temperature and water vapor, we deliver advanced products such as cloud ice and liquid water path, storm top height, and 2 m surface temperature. We also collaborate with NOAA Cooperative Institutes on tropical cyclone intensity products, which are publicly available (with a 24-hour delay) for select satellites. We have submitted a publication on our L2 products (Preprint will be on open archive soon but till then available on request)

Yes. Our microwave sounders already support the derivation of 3D cloud and precipitation profiles, which we leverage to produce storm-top height within our Level 2 products. In addition, we operate Ka-band precipitation radars (one currently active on orbit) that deliver 2D precipitation profiles with high vertical resolution, complementing our sounder data for more detailed atmospheric insights.

Yes, with high revisit rates from our growing satellite constellation, TMS is purpose-built for accurate tropical storm monitoring. Independent NOAA evaluations confirm that TMS delivers intensity estimates on par with state-of-the-art government satellites like ATMS. This combination of quality observations and rapid refresh makes TMS ideal for both standalone typhoon tracking and seamless integration into model assimilation workflows. As part of the NOAA evaluation, the Tropical Cyclone group at the Cooperative Institute of Meteorological Satellite Studies (CIMSS) is using TMS data (along with other satellite data) to monitor tropical cyclones here: https://tropic.ssec.wisc.edu/real-time/DMINT/ Content

Tomorrow.io’s TMS data is designed to enhance a wide range of applications, from improving global and regional weather forecasts to supporting early warning systems for extreme weather events. Its high temporal resolution and global coverage make it ideal for operational forecasting, disaster preparedness, aviation and maritime operations, and infrastructure planning. The data also supports research, climate monitoring, and any workflow that benefits from frequent, reliable observations of temperature, humidity, and precipitation.

TMS data is designed for operational resilience, with global median latency under 50 minutes, a science observation duty cycle of 85%, and sub-hourly revisit rates (when the entire constellation is operational) across ±60° latitude. All satellites are monitored 24/7 by three dedicated teams to ensure mission performance and science quality, with a centralized dashboard tracking the health and status of each satellite. Each satellite transitions from launch to full operational status in approximately 30 days, delivering consistent, high-quality observations even in challenging weather conditions.

Each TMS satellite is designed for a minimum 2-year operational life, with a target constellation of 12+ satellites maintained at all times. Replacements will continue through 2028, when our next-generation (Gen2) instruments — larger and more capable – will begin launching. For the same level of impact on NWP and precipitation analyses, TMS offers a significantly lower cost compared to large satellite instruments like ATMS.

TMS observations are processed in the cloud and typically reach customers 30–40 minutes after collection. Data can be pulled via HTTPS API, a cloud bucket, or pushed into a secure endpoint for direct assimilation into NWP / nowcasting pipelines.

TMS uses a combination of frequency channels to accurately measure both temperature and water vapor. While the 118 GHz band is primarily sensitive to atmospheric temperature, it has some response to low-level water vapor. By combining data from the 118 GHz and 183 GHz channels, we can isolate and retrieve water vapor independently, ensuring accurate temperature measurements and reliable vertical profiles.

In addition to our own internal validation of the level 1 calibration accuracy and NWP impact studies, the U.S. government’s premier satellite data authority, the Joint Center for Satellite Data Assimilation (JCSDA), independently validated TMS data, noting its ‘overwhelming positive impact on the system.’ Over six months, JCSDA conducted rigorous assessments using the JEDI-MPAS model, showing significant reductions in forecast errors across temperature, wind, and water vapor fields from the surface to the stratosphere. See the full study here: https://www.tomorrow.io/space/jcsda/

TMS uses a GSICS-aligned validation framework comparable to GPM’s XCAL approach. Our calibration study shows each channel is cross-checked against ERA5 simulations, ATMS, GMI, and radiosonde data, with biases under 1 K and long-term stability within 0.2 K across our first seven satellites. Learn more here: https://www.tomorrow.io/blog/tomorrow-io-demonstrates-breakthrough-calibration-accuracy-for-satellite-sounders-enhancing-storm-monitoring-from-space/