Peering Through Clouds: Microwave Radiometry’s Crucial Role in Weather Prediction

Microwave radiometry is a passive remote sensing technique that measures naturally emitted thermal radiation in the microwave portion (0.3–300 GHz) of the electromagnetic spectrum. In essence, a microwave radiometer detects weak microwave energy from Earth’s surface and atmosphere and expresses it as a brightness temperature, the equivalent blackbody temperature of the emitting source. Unlike optical or infrared sensors that rely on reflected sunlight or emitted thermal infrared, microwave radiometers sense Earth’s intrinsic microwave emissions day or night, penetrating through clouds, haze, and even light rain or snow. The atmosphere is only semi-opaque at microwave frequencies – even a cloudy sky is not completely opaque in this range. This “all-weather” capability provides a window into atmospheric conditions that visible and infrared sensors often miss.

Physical Principles: Microwave emissions follow Planck’s blackbody radiation law; however, at microwave wavelengths (millimeter to centimeter scale), emission can be described by the Rayleigh-Jeans approximation, and different materials and gases exhibit characteristic emissivities and absorption lines. Key atmospheric gases have distinct microwave absorption bands: for example, oxygen has a complex around 50–60 GHz (and another line at 118 GHz) used for temperature sounding, while water vapor strongly absorbs near 22.235 GHz (and 183 GHz) used for humidity profiling en.wikipedia.org. Between these absorption peaks lie atmospheric window frequencies (e.g. ~6–18 GHz, 30–37 GHz, etc.) where the atmosphere is relatively transparent, allowing radiometers to “see” the Earth’s surface or cloud liquid water emission. By tuning to multiple channels – some on absorption lines, others in windows – a radiometer can disentangle contributions from different altitudes and constituents. For instance, channels around 60 GHz (oxygen absorption) provide information on the vertical temperature profile, whereas a channel near 22 GHz (water vapor line) indicates humidity, and higher-frequency channels (>85 GHz) respond to cloud ice and precipitation (including scattering by raindrops or snowflakes). In passive sensing, no signal is transmitted; the radiometer simply “listens” to naturally emitted microwave noise. Because emission at these wavelengths is very low intensity, radiometers require highly sensitive, low-noise receivers (often cryogenically cooled or using advanced low-noise amplifiers) to detect minute temperature differences. They are typically calibrated with known temperature reference loads (a “hot” load at a known physical temperature and observations of cold space) to convert raw counts to accurate brightness temperatures.

How Microwave Radiometers Work (Instrumentation and Platforms)

Spaceborne Radiometers: Most microwave radiometers in meteorology are aboard satellites, scanning the Earth below. There are two main designs for scanning: conical scanners and cross-track scanners. Imaging radiometers (e.g. the Advanced Microwave Scanning Radiometer series, SSM/I, WindSat) use a continuous conical scan at a fixed off-nadir angle, typically measuring low-frequency “window” channels from ~1 to 100 GHz to observe surface and precipitation signals. By spinning the antenna and viewing Earth at a constant incidence angle (around ~50°), conical scanners achieve a consistent angle of observation (important for stable surface emissivity measurements) and a wide swath. For example, the GPM Microwave Imager (GMI) on the Global Precipitation Measurement core satellite uses a 1.2 m dish spinning at 32 rpm to cover a 140° sector, yielding a swath about 885 km wide. This conical geometry (illustrated in the figure below) ensures nearly contiguous coverage as the satellite orbits, with the radiometer collecting data across multiple channels each rotation. Cross-track (scanning) sounders, by contrast, sweep a beam from side to side (from one horizon to the other) in a plane perpendicular to the flight path. These instruments (e.g. NOAA’s AMSU and ATMS sounders, or EUMETSAT’s MWS) typically focus on absorptive bands (like oxygen near 60 GHz and water vapor near 183 GHz) to retrieve vertical profiles of temperature and humidity. Cross-track sounders stare at each Earth scene for a brief moment, then step the antenna to the next angle, producing a scan line of observations across the swath. This design provides finer vertical sounding information by exploiting how absorption varies with frequency and altitude. Some advanced sounders also include limb-sounding modes or special geometries (for example, the Microwave Limb Sounder on NASA’s Aura satellite) to observe trace gases in the upper atmosphere.

Modern satellite radiometers carry multiple feedhorns or receivers to cover numerous frequency channels (for example, 13 channels on GMI from 10 GHz up to 183 GHz, or 22 channels on NOAA’s ATMS sounder). They often measure dual polarization (horizontal and vertical) in the window channels, which aids in surface parameter retrievals (e.g. ocean wind speed and rain identification). Calibration is a critical aspect – satellites carry onboard hot loads and cold sky reflectors that periodically view an internal blackbody target and deep space, respectively, to recalibrate the radiometer’s gain and offset. This enables continuous, autonomous operation needed for operational weather monitoring.

Airborne and Ground-Based Radiometers: Besides satellites, microwave radiometers are deployed on aircraft and on the ground for research and local observations. Airborne radiometers allow targeted studies of weather systems at higher spatial resolution or testing of new technologies. For example, NASA’s High-Altitude MMIC Sounding Radiometer (HAMSR) is an aircraft instrument with 25 channels (50–183 GHz) that can retrieve 3D temperature and moisture structure even inside storms. It has flown on high-altitude research aircraft to study hurricanes, providing measurements analogous to satellite sounders but with finer detail for validation and algorithm development. Other airborne systems like the Conical Scanning Submillimeter-wave Radiometer (CoSSIR) operate up to sub-millimeter wavelengths (~640–874 GHz) to characterize ice clouds in detail – a precursor to future satellite capabilities. On the ground, ground-based microwave radiometers are used at weather observatories and airports to continuously monitor the overhead atmosphere. A typical ground radiometer (like the 14-channel HATPRO instrument) observes at a set of frequencies in the 20–35 GHz and 50–60 GHz bands, yielding continuous vertical temperature and humidity profiles and estimates of integrated water vapor and cloud liquid water above the site. These instruments operate in nearly all weather (except during heavy precipitation which can attenuate the signal) and provide high temporal resolution data (updates every few minutes or even seconds). Ground radiometer networks (e.g. the international MWRnet) have been established to standardize data and integrate such profiles into meteorological analyses en.wikipedia.org.

How Radiometers Support Weather Prediction: All these platforms – satellite, aircraft, and ground – complement each other. Satellites give global coverage; ground radiometers give detailed time series at fixed points (useful for nowcasting and model verification); aircraft and experimental radiometers drive instrument innovation and algorithm refinement. In operations, satellite microwave radiometer data are streamed in real time for ingestion into numerical weather prediction (NWP) models and for forecasters to analyze storm structure. Instruments are often collocated with other sensors (for example, on satellites, microwave sounders fly alongside infrared sounders like CrIS or IASI, and active sensors like radars or lidar on specialized missions) to provide a more complete picture of atmospheric conditions.

Historical Development and Key Microwave Radiometer Missions

Microwave radiometry’s origins trace back to the mid-20th century. Early experiments in the 1930s–40s aimed to measure cosmic microwave background and atmospheric emission, and the first microwave radiometer (a Dicke radiometer) was demonstrated in 1946 for astronomical purposes. By the 1960s, the technology was poised for spaceflight. NASA’s Mariner 2 Venus probe (1962) carried a microwave radiometer to scan Venus’ atmosphere, marking the first use of such an instrument beyond Earth. The success of these early radiometers led to rapid adoption in Earth observing satellites:

• Nimbus-7 SMMR (1978): NASA’s Nimbus-7 satellite carried the Scanning Multichannel Microwave Radiometer (SMMR) – a five-frequency (6, 10, 18, 21, 37 GHz), dual-polarization radiometer. SMMR was the first conical-scanning microwave imager in space. It demonstrated the ability to map ocean surface conditions, soil moisture, and even snow and ice cover globally en.wikipedia.org. Nimbus-7 SMMR data, for example, enabled global monitoring of sea ice extent and snow cover en.wikipedia.org. SMMR’s conical scan concept (rotating dish) set the template for many future imagers.
• DMSP SSM/I (1987): The U.S. Defense Meteorological Satellite Program (DMSP) introduced the Special Sensor Microwave/Imager (SSM/I) in 1987, continuing through multiple satellites. SSM/I had seven channels (19 to 85 GHz) and provided operational all-weather surveillance of ocean winds, rain rates, and snow cover. It was revolutionary for military and civilian meteorology – forecasters could, for the first time, see microwave-derived global rain maps and ocean wind speeds. An upgraded SSMIS (Sounder/Imager) later added sounding channels. SSM/I and SSMIS instruments, with their continuous coverage, proved the practical value of microwave radiometry for weather and have flown on numerous DMSP satellites.
• TIROS-N/NOAA Microwave Sounders (1979 onward): While imagers evolved, microwave sounders were also developed. The Microwave Sounding Unit (MSU) first flew on NOAA polar-orbiting weather satellites in 1979, measuring tropospheric temperatures via oxygen-band channels. The improved Advanced Microwave Sounding Units (AMSU-A and AMSU-B) flew from 1998 (NOAA-15) onward, greatly enhancing temperature and humidity profile retrievals in all weather. These cross-track sounders became workhorses of global forecasting systems. Today’s state-of-the-art sounder is the Advanced Technology Microwave Sounder (ATMS), first launched on the Suomi NPP satellite in 2011 and now aboard NOAA-20 and NOAA-21. ATMS has 22 channels from 23 GHz up to 183 GHz, combining the capabilities of AMSU-A and AMSU-B in one compact instrument. With its broad frequency coverage and lower noise electronics, ATMS provides more accurate and finer-resolution sounding data than its predecessors. When paired with an infrared sounder (like CrIS), ATMS yields 3D atmospheric profiles even under cloudy skies. Microwave sounders like AMSU and ATMS have become so vital that their data are considered the “backbone” of the global observing system for NWP.
• Tropical Rainfall Measuring Mission (TRMM, 1997–2015): A joint NASA-JAXA mission, TRMM was the first satellite dedicated to tropical precipitation. It carried the TRMM Microwave Imager (TMI), a conical scanner similar to SSM/I, and the first spaceborne precipitation radar. TMI’s data, combined with radar, produced unprecedented maps of rain inside tropical cyclones and monsoons. TRMM demonstrated the power of combining passive microwave and active sensors, and its success led to the expanded Global Precipitation Measurement program.
• Envisat and Aqua (2002): In the early 2000s, advanced radiometers focused on both research and operations. NASA’s Aqua satellite (2002) included AMSU-A and the AMSR-E (Advanced Microwave Scanning Radiometer–EOS) instrument. AMSR-E (built by JAXA) had 12 channels from 6.9 to 89 GHz and one of the largest antenna dishes (1.6 m) ever flown for higher resolution. AMSR-E’s observations enabled a plethora of geophysical products – ocean surface temperature and wind, atmospheric water vapor and cloud liquid water, rainfall, sea ice concentration, snow water equivalent, and soil moisture, all from one instrument. Importantly, Aqua’s combination of AMSR-E (microwave) and AIRS (infrared sounder) allowed direct comparisons of cloud-penetrating microwave soundings with cloud-limited IR soundings, highlighting microwaves’ all-weather value. In Europe, ESA’s Envisat (2002) carried a Microwave Radiometer (MWR) mainly to correct its radar altimeter for atmospheric water vapor; while not used for weather per se, it signaled Europe’s growing interest in microwave payloads.
• Global Precipitation Measurement (GPM, 2014–present): GPM, co-led by NASA and JAXA, took global precipitation monitoring to the next level. The GPM Core Observatory carries the GMI radiometer and a dual-frequency precipitation radar. GMI has 13 channels (10–183 GHz), including four high-frequency channels at 166 and 183 GHz to better detect falling snow and ice in clouds. With its large 1.2 m dish and improved calibration, GMI provides higher spatial resolution and accuracy than prior imagers. The GPM Core acts as a reference standard to inter-calibrate an entire constellation of partner satellites (each carrying microwave radiometers), including U.S., Japanese, European, and Indian satellites, to create the unified global precipitation dataset IMERG (updated every 3 hours). GPM’s international network exemplifies how microwave radiometry underpins an integrated observing system for a critical variable like precipitation.
• Current and Future Missions: Today, virtually all major weather satellite systems include microwave radiometers. EUMETSAT’s MetOp series (2006–present) carries microwave sounders (AMSU-A, MHS) and will soon deploy next-generation MetOp-SG satellites with the Microwave Sounder (MWS) and Microwave Imager (MWI) missions, plus a novel Ice Cloud Imager (ICI) extending into sub-millimeter wavelengths. The ICI, debuting around 2025, will be the first operational radiometer to observe frequencies up to 664 GHz, filling a gap in our ability to directly measure ice cloud properties and snowfall globally. In the U.S., NOAA’s Joint Polar Satellite System (JPSS) satellites will continue flying ATMS for the foreseeable future, and plans are being explored for potential geostationary microwave sounders to get continual coverage (a challenging endeavor requiring large antenna apertures or synthetic aperture techniques). China and India have also entered the field: China’s Fengyun-3 polar satellites carry microwave temperature and humidity sounders, and India has tested microwave radiometers for ocean applications. Decades of progress – from single-channel instruments to multi-channel, from single satellites to constellations – have firmly established microwave radiometry as an indispensable component of weather observation.

(Table: Selected Microwave Radiometer Missions)

(The above are a sampling of notable missions; many other satellites have carried microwave radiometers, underscoring the broad adoption of this technology.)

Applications in Meteorology

Microwave radiometry supports a wide array of meteorological applications by providing data that other observing systems often cannot:

• Atmospheric Temperature and Humidity Profiling: Microwave sounders (AMSU, ATMS, etc.) retrieve the vertical distribution of temperature and moisture even under cloud cover. By measuring upwelling radiance in oxygen and water vapor absorption bands, they infer atmospheric temperature at various layers (from the surface up to stratosphere) and the humidity profile in the troposphere en.wikipedia.org. While the vertical resolution is coarser than that of high-spectral-resolution infrared sounders, the key advantage is all-weather capability – microwave soundings are available in cloudy regions that infrared sounders miss. This makes them extremely valuable for global weather analysis, as clouds cover a large fraction of the Earth at any time. Data assimilation experiments have consistently shown that microwave sounder radiances rank among the highest-impact observations for weather forecast skill. In fact, a 2021 NOAA workshop confirmed that microwave sounders on polar satellites have been “the most impactful remote sensing observations in NWP models for the past two decades”. These radiometers essentially provide the temperature and moisture initialization that drives global models.
• Precipitation Measurement: Unlike weather radars (which actively send pulses), passive microwave radiometers infer precipitation by the natural emission and scattering signatures of hydrometeors. Certain channels (e.g. 37 GHz, 85 GHz) increase in brightness in the presence of cloud liquid water or moderate rain (emission by raindrops), while higher frequencies (e.g. 89 GHz, 183 GHz) actually decrease in brightness over a cold background when ice/snow in clouds scatter upwelling radiation. By combining frequencies, algorithms can distinguish heavy rain, light rain, and snow. Microwave radiometers are the primary source of quantitative precipitation estimates from satellites, since they can observe through clouds. They provide near-global rainfall maps (outside extreme polar regions) multiple times per day from LEO satellites. For example, the GMI radiometer’s multi-channel data is used to retrieve rainfall rates, with specific channel sets tuned to heavy rain vs. mixed rain/snow vs. snowfall detection. These retrievals feed into global precipitation products (like IMERG) used for flood forecasting, agricultural planning, and climate monitoring of precipitation. While an individual radiometer over a given location might provide data only a few times a day, the international constellation (e.g. GPM plus other satellites) ensures that combined microwave data can observe precipitation every 3 hours or better. Such data have dramatically improved our ability to monitor hurricanes (e.g. locating rainbands and eyewall structure through clouds) and track precipitation in remote oceanic or sparsely populated regions.
• Total Column Water Vapor and Clouds: Microwave window channels (e.g. ~18–37 GHz) are sensitive to water vapor and liquid water integrated along the column. Over oceans (where the background is cold and uniform), a channel near 22 GHz can be calibrated to retrieve precipitable water vapor – the total moisture in the column – with high accuracy. This is valuable for weather analysis (e.g. identifying moist vs. dry air masses, detecting atmospheric rivers, etc.). Likewise, by comparing a non-absorbing window channel (~31 GHz) to a water vapor channel (~23 GHz), one can estimate the liquid water path (total cloud liquid water in the column). These products inform forecasters about cloud thickness and moisture content even when clouds are not precipitating. Over land, microwave retrieval of water vapor is trickier due to the warm, varying land background, but multi-channel algorithms and ancillary data can still provide useful moisture estimates.
• Surface Sensing (Ocean and Land): In clear or moderately cloudy conditions, microwave imagers also measure surface parameters. For example, low-frequency channels (~6–10 GHz) respond to sea surface temperature (SST) and wind speed over water (rougher seas => more foam => higher emissivity). The AMSR and WindSat instruments have retrieved SST and ocean surface winds globally, complementing infrared-based SST measurements by working even under cloudy skies. Scatterometers (active sensors) are primary for vector winds, but radiometers provide an independent source of wind speed data. Over land, microwave emissivity varies with soil moisture and vegetation. Missions like SMOS (Soil Moisture Ocean Salinity) and SMAP (Soil Moisture Active Passive) specifically measure at L-band (~1.4 GHz) to retrieve soil moisture, but even standard radiometers at higher frequencies can detect relative wet vs. dry soil and snowpack properties. For instance, a combination of 19 GHz and 37 GHz channels has long been used to estimate snow water equivalent (SWE) by exploiting the fact that dry snow has lower emission at higher frequency due to scattering. Thus, weather radiometers also contribute to hydrological variables: tracking snow cover and depth, freeze/thaw state of ground, flood inundation (through changed emissivity), etc., which are important for broader Earth system monitoring.
• Data Assimilation in NWP Models: Perhaps the most impactful application of microwave radiometry is in global and regional data assimilation systems. Rather than producing stand-alone “weather products,” the majority of microwave radiance data (from sounders and imagers) is assimilated directly as radiances into numerical weather prediction models. Because these radiometers can observe in all weather and sense the atmospheric state (temperature, moisture, clouds) continuously, they greatly enhance the initial conditions of models. Studies consistently show that assimilating microwave sounder data reduces forecast errors significantly, improving predictions of hurricane tracks, mid-latitude storm development, and even daily temperature/wind patterns. For example, one study noted that out of all satellite observing systems, microwave sounders often have the largest positive impact on 24-hour and 72-hour forecast accuracy. This is in part because they cover the globe including ocean and cloud-covered areas where conventional data (like aircraft or ground stations) are sparse. Moreover, developments like all-sky assimilation now allow models to ingest radiances even in cloudy and precipitating scenes (using sophisticated radiative transfer and error modeling), thereby extracting information from microwave observations of clouds and precipitation that was once discarded. Agencies like ECMWF, NOAA, and others have invested heavily in assimilating microwave imager data for precipitation and cloud water, further increasing forecast skill especially for mesoscale and convective systems. In short, microwave radiometry provides an indispensable “through-cloud” view that has become a foundation of modern forecasting systems.
• Climate Monitoring: In addition to weather, the long-term records from microwave radiometers are vital to climate applications. The MSU and AMSU sounders, for instance, have provided a multi-decade record of global atmospheric temperatures which scientists use to monitor climate change (e.g. tropospheric warming rates). The consistency and stability of microwave brightness temperature records allow detection of trends in water vapor, cloudiness, and ice cover. In fact, the NOAA ATMS instrument webpage notes that the “long-term temperature records of our atmosphere [from microwave sounders] have played a key role in helping scientists determine that humans are the cause of climate change”. Similarly, microwave imagery has documented declines in Arctic sea ice, changes in ice sheet melt, and shifts in global precipitation patterns over decades. Thus, these sensors contribute both to immediate weather prediction and to understanding longer-term atmospheric behavior.

Benefits and Limitations (Microwave vs. Infrared vs. Radar)

Microwave radiometry offers a unique skill set compared to other remote sensing methods, with distinctive advantages as well as trade-offs:

• All-Weather Capability: Perhaps the greatest advantage of microwave sensors over infrared (IR) sensors is their ability to see through clouds. Infrared radiometers and imagers (like those on weather satellites and geostationary platforms) cannot penetrate thick clouds – a deep cloud layer appears as an opaque “wall” at IR wavelengths. Microwave radiometry, by contrast, can observe in almost all sky conditions, only significantly attenuated by heavy rain or very dense cloud liquid water paths. This means microwave instruments can obtain temperature/humidity data and even surface data under conditions that blind IR sensors spire.com spire.com. For example, a microwave sounder can retrieve a temperature profile in a cloudy region where an IR sounder like AIRS has no useful signal. This complementarity is why weather satellites often fly microwave and IR sounders together – as NOAA puts it, “because clouds are opaque in the infrared…and largely transparent at microwave frequencies, operating these two instruments together makes it possible to cover a broader range of weather conditions”. The benefit is especially crucial for high-impact weather (hurricanes, storms) which are cloud-obscured. Microwave > IR in coverage: it enables “all-sky” data availability.
• Information Content and Resolution: Infrared sounders generally have much higher spectral resolution (hundreds to thousands of channels across gas absorption spectra) and thus can achieve finer vertical resolution in clear air. Microwave sounders have fewer channels (tens) and broader weighting functions (each channel’s signal comes from a thick layer), so their vertical profiling is smoother. Additionally, IR measurements (when cloud-free) have higher native horizontal resolution from satellites (e.g. 4 km or better from geostationary). Microwave radiometers, limited by diffraction and antenna size, have relatively coarser spatial resolution – typically on the order of tens of kilometers for sounders (e.g. ~30–50 km for ATMS) and perhaps 5–25 km for imagers (higher frequencies yield smaller footprints). For instance, an 89 GHz channel might have ~10 km resolution, whereas a 23 GHz channel footprint might be 50 km wide. Thus, IR imagers provide finer detail (useful for small-scale cloud features) while microwave gives the all-weather view but with a “blurrier” picture. This is a fundamental trade-off due to physics of longer wavelengths.
• Surface and Diurnal Cycle: Infrared sensors measure skin temperature of surfaces but can be fooled by clouds and only work in clear skies; microwave measurements of surface variables (SST, soil moisture) are more robust to weather and can even work at night or high latitudes where IR has issues (e.g. darkness or temperature inversions). However, infrared has an advantage in detecting surface temperature with higher precision in clear conditions, whereas microwave-derived SST is lower resolution. Microwave signals also have relatively weak diurnal variation (except at very low frequencies where soil moisture can have dew effects), so they enable monitoring of phenomena like ocean winds or rain independent of sunlight. Radars vs. Radiometers: Radar (active microwave) and radiometers (passive microwave) are complementary as well. Radars (like weather radar or satellite precipitation radars) send pulses and measure returns, providing very high spatial resolution (often sub-kilometer) and the ability to profile precipitation (e.g. radar reflectivity vs. height). They excel at capturing convective structure and small-scale features. But radars cover a limited swath (e.g. the GPM DPR only ~245 km wide) and are complex/heavy instruments. Radiometers have much wider swaths (hundreds of km) and simpler design, scanning huge areas quickly – ideal for global coverage. However, radiometers infer precipitation indirectly and with coarser resolution. Radiometers also can’t provide vertical profiles of precipitation as a radar can. In terms of sensitivity, radiometers can miss very light precipitation (drizzle) or shallow snow that doesn’t change the microwave brightness enough, whereas a radar might detect it. On the other hand, radiometers can estimate integrated cloud and rain water content more directly via emission signals, whereas radars might struggle with attenuation in heavy rain. Cost and complexity: Passive microwave instruments are generally lighter and less power-hungry than radars (no high-power transmitter needed), making them easier to fly in multiples. This is one reason an international fleet of passive microwave sensors exists, while only a couple of precipitation radars have been flown due to resource limitations.

In summary, microwave radiometry fills critical gaps left by other methods: it is the go-to method for all-weather atmospheric sounding and precipitation mapping, albeit at a moderate resolution, whereas infrared gives fine detail in cloud-free areas, and radar gives very fine detail in limited swaths or from ground installations. The most effective observation strategies use them in tandem – for example, assimilation of both microwave and infrared radiances yields better forecast initial conditions than either alone, and using a radar to calibrate radiometer rain retrievals (as in GPM) combines radar’s accuracy with radiometer’s coverage.

Recent Innovations in Microwave Radiometry

The field of microwave remote sensing is continuously evolving, with recent innovations focused on improving resolution, coverage, and data utility:

• Small Satellite Constellations: Traditionally, microwave radiometers have been large instruments on big satellites, with only a handful in orbit. Recent advances in miniaturization now allow capable radiometers to be built on small satellite platforms. For example, NASA’s TROPICS mission deploys 3U CubeSats, each hosting a compact radiometer with 12 channels (covering 90, 118, 183, 205 GHz). The CubeSats are deployed as a constellation in multiple orbits to achieve rapid-revisit monitoring of tropical cyclones (targeting a median revisit ~60 minutes) weather.ndc.nasa.gov. This is a radical improvement in temporal resolution – a response to the need for “refreshing” weather observations more frequently (traditional single satellites revisit a given storm perhaps twice a day). Although some technical challenges (and launch losses) affected TROPICS, it exemplifies the trend toward many small radiometers working in concert. Another example is commercial companies: Spire Global is developing a network of small satellites with a Hyperspectral Microwave Sounder (HyMS) payload, aiming to launch dozens of minisatellites. By distributing many microwave sensors in orbit, these constellations promise faster updates (nowcasting applications) and resilience – if one fails, others cover. A NOAA expert panel in 2021 noted that smallsat radiometers “hold promise” to supplement the backbone satellites, potentially improving coverage, though they stressed careful study to design an optimal configuration. The convergence of lower-cost platforms and capable microwave tech is enabling this new paradigm of distributed observing.
• Hyperspectral Microwave and Digital Receiver Technology: A buzzword “hyperspectral” usually applies to infrared sounders, but now microwave sounders are beginning to vastly increase channel counts as well. Traditional microwave sounders sample a few discrete frequencies in each absorption band. Hyperspectral microwave sounders would collect data in many finely spaced channels (tens or even hundreds) across the band, providing more detailed sampling of the absorption line shape. This could improve vertical resolution of retrievals and allow better filtering of radio-frequency interference. Organizations like Spire (with its HyMS) and NOAA’s research (e.g. MicroMAS and MiRaTA CubeSat missions) have been pushing in this direction. The HyMS approach, for instance, uses a digital spectrometer back-end that instantaneously covers >16 GHz of bandwidth and divides it into many narrow channels spire.com. In practice, this yields much richer data – analogous to how an IR sounder like AIRS revolutionized vertical sounding by going from 20 channels to thousands. Spire claims their hyperspectral sensor will provide higher vertical resolution and accuracy in retrieved temperature and water vapor profiles spire.com, and importantly, intrinsic RFI detection capabilities by virtue of high spectral resolution spire.com. With 5G and other telecom signals threatening to leak into weather bands, having a hyperspectral sensor means one can identify and filter out stray signals (since a narrow bad channel can be spotted and omitted) spire.com. A NASA/NOAA team at MIT Lincoln Laboratory has also demonstrated wideband digital receivers that could allow “configurable” channels and enable this hyperspectral operation. While some experts caution that microwave absorption features are broad (so the benefit of too many channels faces diminishing returns and noise challenges), tapping unused parts of the spectrum and using digital tech for flexibility is undoubtedly the future. These advancements will make radiometers more adaptive and interference-resilient, and possibly enable entirely new measurement strategies (like simultaneous multi-angle or polarimetric sampling).
• Artificial Intelligence (AI) and Machine Learning Integration: The meteorological community is increasingly leveraging machine learning to enhance microwave data usage. Neural network retrievals of atmospheric profiles from radiometer data have shown improvements in accuracy and speed. For example, studies have applied deep learning models to ground-based microwave radiometer observations to retrieve temperature and humidity profiles, yielding better results (lower RMS error compared to radiosondes) than traditional physical algorithms. ML can efficiently handle the non-linear inversion from brightness temperatures to atmospheric state, and can fuse information from many channels. On the satellite side, AI-based techniques are being developed to blend microwave data with other data sources and even to emulate radiative transfer calculations for faster assimilation. Another area is using machine learning to enhance weather models (AI-driven forecast models) that directly ingest microwave observations. Spire’s concept, for instance, is to feed their HyMS data into high-resolution AI weather prediction systems for bespoke forecasts. Additionally, AI can assist in quality control and flagging of radiometer data (identifying cloud-affected or snowy-surface scenes) and super-resolution reconstruction (to sharpen images beyond the native resolution). While still emerging, these integrations mean microwave radiometry will benefit from the ongoing revolution in AI, achieving more information extraction from the same raw measurements.
• Higher Frequencies and New Observables: Recent and upcoming instruments are extending microwave radiometry into the millimeter and sub-millimeter wavelengths. Traditionally capped around 183 GHz, sensors like the Ice Cloud Imager (243–664 GHz) and proposed sub-mm wave sensors will open new frontiers. At these frequencies, radiometers become sensitive to smaller ice particles and thin ice clouds that were previously “microwave invisible.” ICI, for example, will allow monitoring of cirrus cloud properties and ice crystal size, improving representation of high-level clouds in both climate and NWP models. It effectively fills a gap between microwave and infrared by observing the strong ice scattering/absorption in the sub-mm regime. Other experimental developments include polarimetric radiometers (measuring different polarization orientations to deduce cloud particle shape and surface wind direction), and combination with GNSS radio occultation on small platforms for joint temperature-humidity sounding.

In summary, the latest innovations aim to make microwave radiometry more detailed (spectrally and spatially), more frequent in coverage, and smarter in data processing. The outcome in the coming years will likely be richer datasets (hyperspectral radiances), faster refresh rates from constellations, and improved products (e.g. AI-enhanced retrievals) that will feed the next generation of weather prediction systems.

Leading Organizations and Programs in Microwave Radiometry

This field is marked by strong international collaboration and leadership by major space and meteorological agencies:

• United States (NASA & NOAA): NASA has pioneered microwave radiometer technology and missions (from Nimbus satellites to Aqua, TRMM, GPM, and numerous airborne campaigns). It often develops new instruments (e.g. AMSR-E in partnership with JAXA, the CubeSat radiometers) and conducts research on retrieval algorithms and climate data records. NOAA, on the other hand, focuses on operational use – it flies microwave sounders on its polar-orbiting weather satellites (POES, now JPSS series) and ingests their data into weather models. NOAA’s role in sustaining long-term observations (MSU/AMSU/ATMS since 1979 continuously) has been critical. The impact of NOAA’s MW sounders on forecast accuracy is widely acknowledged, and NOAA invests in future technologies (such as sponsoring the Spire HyMS demo and exploring Geo microwave sounders). U.S. Department of Defense (USAF) also contributed via DMSP’s SSM/I series and now the Defense Weather Satellite System plans, whose data have been shared for civilian use.
• Europe (EUMETSAT & ESA): European agencies have become leaders especially in innovation for operational systems. EUMETSAT operates the MetOp polar satellites which carry microwave payloads provided by both NOAA (AMSU) and European industry (MHS). The upcoming MetOp-Second Generation is a flagship: ESA and EUMETSAT are deploying advanced radiometers (MWS, MWI, ICI) that will ensure Europe’s independent all-weather sounding and imaging capability through 2040s. These instruments are being built by European companies (Airbus, OHB, etc.) and will significantly enrich global data – for example, MWS is expected to improve all-sky radiance assimilation in models. ESA’s Earth observation program also developed unique missions like SMOS (L-band interferometric radiometer for soil moisture) and is developing CIMR (Copernicus Imaging Microwave Radiometer) for polar ice and ocean observations at L-band and C-band. Europe’s meteorological community (through EUMETSAT’s Satellite Application Facilities and EU’s Copernicus program) is deeply involved in microwave data utilization and product development (e.g. for snow, ice, and hydrology).
• Japan (JAXA): The Japan Aerospace Exploration Agency has made outsized contributions relative to its size. JAXA provided the AMSR series: AMSR-E on Aqua and AMSR2 on its own GCOM-W1 “Shizuku” satellite (launched 2012). AMSR2, with the world’s largest rotating dish (2m) for a radiometer, continues to deliver high-quality precipitation, water vapor, ocean, and cryosphere data. JAXA also partnered on TRMM and GPM, building the precipitation radar and hosting GPM data centers. Japan’s focus has often been the global water cycle – indeed GCOM-W’s mandate is long-term monitoring of Earth’s water changes global.jaxa.jp. The data from JAXA’s radiometers are used by NOAA and others (NOAA formally uses Shizuku/AMSR2 data in its products). JAXA’s cultural emphasis on engineering reliability has given AMSR instruments exceptional stability, which climate scientists value for consistent records. Japan is also exploring small satellite concepts and continues to be a key partner in international missions.
• Other Countries: China has emerged in the last two decades – the China Meteorological Administration’s Fengyun-3 polar satellites carry instruments like MWTS (Microwave Temperature Sounder) and MWHS (Microwave Humidity Sounder), analogous to AMSU-A/B. They have also flown microwave imagers and are developing their own next-gen sounders. China is reportedly studying a pathfinder geostationary microwave mission as well (as part of FY-4 series), which would be groundbreaking if realized. India has flown microwave radiometers for ocean applications (e.g. on Oceansat satellites and a microwave sounder on Megha-Tropiques, a joint mission with France). Russia historically had some radiometers (Meteor satellites) but data availability has been limited. In the private sector, companies like Spire Global and Orbital Micro Systems are new players launching commercial microwave radiometers and selling data/services, often in partnership with government (NOAA’s Commercial Weather Data Pilot has contracts for RO and might include microwave data in future).

International collaboration is strong: the WMO Integrated Global Observing System (WIGOS) coordinates satellite contributions, and through programs like GPM and the Joint Polar System (NOAA-EUMETSAT), agencies ensure coverage and share data openly. This global approach is crucial because microwave radiometry for weather is only effective as a planet-wide endeavor – no single nation can provide all the needed coverage and frequency protection. Efforts like the GSICS (Global Space-based Inter-Calibration System) ensure that radiometers from different agencies (e.g. NOAA ATMS, EUMETSAT MHS, JAXA AMSR2) are cross-calibrated, so their data can be merged seamlessly. The major space agencies (NASA, NOAA, EUMETSAT/ESA, JAXA) thus collectively lead the field, supported by research institutions and industry contractors building the instruments. They also jointly face the challenges discussed next, from spectrum preservation to technology hurdles, working through international bodies (e.g. ITU for spectrum, CEOS for observation planning).

Challenges and Future Prospects

Despite its successes, microwave radiometry for weather prediction faces several challenges moving forward, along with opportunities for significant advancements:

• Spatial Resolution vs. Antenna Size: A perennial technical challenge is the relatively coarse resolution of microwave radiometers from orbit. Achieving higher resolution requires larger antenna apertures (since diffraction limit ∼ wavelength/antenna diameter). For example, to get 5 km resolution at 50 GHz from a satellite, one would need an impractically large antenna. Engineers have pushed this by using deployable mesh antennas or large spinning dishes (AMSR2’s 2-meter antenna is one of the largest that can be accommodated on a moderate-sized satellite). Future concepts like deployable membrane antennas or synthetic aperture radiometry could break this barrier. Synthetic aperture microwave radiometer designs (e.g. NASA’s GeoSTAR concept) use an array of small antenna elements distributed on a boom, with signal processing to emulate a much larger dish. This could enable microwave sounders in geostationary orbit, where an equivalent dish might need to be 10-15 meters in diameter to achieve reasonable resolution. GeoSTAR prototypes have shown feasibility in labs – the idea is to permit continuous, full-disk microwave observations of Earth from GEO, revolutionizing temporal coverage. However, deployment, calibration, and noise management for such interferometric systems are complex, and thus GEO microwave sounders remain on the horizon of the 2030s. In the meantime, leveraging constellations of small LEO radiometers can improve effective sampling of small-scale features by swarm observation (multiple views over time can partially substitute spatial resolution).
• Radio-Frequency Interference (RFI) and Spectrum Protection: As commercial wireless communications expand (5G, 6G, satellite internet), they encroach upon frequency bands adjacent to or even within those used by weather sensors. Microwave radiometers are passive receivers and extremely sensitive, so man-made signals can cause RFI that corrupts the measurement. This is already a serious issue at L-band (1.4 GHz) for soil moisture missions, and concerns are growing at 24 GHz (near the 23.8 GHz water vapor line) due to 5G, and around 37 GHz and beyond. For instance, one Nature article warned that 5G networks could leak into the 23.8 GHz band and reduce the accuracy of water vapor measurements. International regulatory bodies allocate spectrum, but the pressure from telecom for bandwidth is relentless. The meteorological community, through WMO and national agencies, is actively fighting to protect key frequency bands for Earth observation. NOAA has explicitly noted that “expanding commercial demand for RF spectrum can degrade the ability to maintain and improve NWP forecast capability”. Future radiometers will need built-in RFI filtering and detection – such as using high spectral resolution to identify interference spikes spire.com or using polarization and time-domain checks to flag non-natural signals. Some newer radiometers (e.g. EUMETSAT’s MWI on MetOp-SG) include specific RFI mitigation hardware, dividing the band into sub-bands and detecting anomalous signals that don’t match thermal noise characteristics. In addition to technical fixes, securing the spectrum through policy is crucial. The future prospect is a bit of an arms race: as sources of RFI increase, radiometers must become smarter and more robust, or risk losing data quality. Nonetheless, the community is optimistic that with ingenuity and advocacy, weather-critical bands will remain usable. The push toward higher frequencies (e.g. sub-mm) is partly to move into bands less crowded by communications (for now).
• Calibration and Climate Continuity: For weather forecasting, inter-satellite calibration is important so that data from different radiometers can be used together. For climate, absolutely stable calibration over decades is needed to detect trends. Microwave radiometers can suffer calibration drifts (e.g. due to instrument aging or solar intrusion events). A challenge is establishing reference standards (e.g. reference radiometers on the International Space Station or on satellites with on-board calibration targets traceable to SI units). An emerging prospect is to use CubeSat radiometers to intercalibrate the bigger missions: a small satellite can be dedicated to flying under the path of multiple radiometers and comparing measurements, serving as a transfer standard. NOAA’s workshop highlighted the need for a “robust calibration strategy” for future mixed constellations, including inter-calibration, absolute calibration, and traceability across diverse missions. The community is investing in tools like the Global Precipitation Mission’s intercalibration for precipitation sensors, and GSICS for sounders, to ensure continuity. In the future, we might see on-board calibration advances like active cold loads (especially for sub-mm where cold space isn’t “cold” due to cosmic background emission), or even deployment of a reference radiometer in space that others can tie to.
• Integration with NWP and “Observation System Simulation Experiments” (OSSEs): As we plan new sensors (e.g. GEO sounders, smallsat constellations), a challenge is to demonstrate the value of these to weather forecasts to justify costs. This is being tackled through sophisticated simulations – OSSEs – where hypothetical data from proposed instruments are generated and fed into models to quantify forecast improvement. Recent OSSEs have shown, for instance, that a 3-orbit polar system plus smallsat sounders could potentially match or exceed the impact of just adding more channels to current sounders. The results guide what frequencies to choose or how many smallsats are ideal. In essence, the future prospect is a more designed observing system optimized via simulation to yield maximum forecast skill per dollar. The challenge is ensuring these simulations capture real-world complexities (e.g. model biases, unforeseen error correlations).
• Geostationary Microwave Observations: We touched on GEO sounders as a tech challenge, but from an application standpoint, having microwave radiometers on geostationary platforms would be transformative for regional weather nowcasting. Imagine continuously watching the evolution of temperature/humidity profiles and rain bands in a developing storm without the current gaps between LEO passes. This could improve short-range forecasts of convection and heavy rainfall (similar to how GOES IR imagery is used, but with microwave’s penetration giving the “inside view” of clouds). Several concepts, including the GeoSTAR interferometer and the JAXA concept for a GEO microwave radiometer, indicate it is feasible. If the engineering challenge of the antenna can be solved, by the late 2020s or 2030s we may see the first GEO microwave mission. China reportedly plans a GEO mm-wave sounder on the FY-4 series, and EUMETSAT and NOAA have studied it for future programs. The prospect here is a game-changer for rapidly evolving weather (e.g. severe thunderstorms, flash floods, hurricane intensification) – filling a gap in current observation capabilities.
• Expanded Environmental Products: Future microwave radiometry will likely expand into areas like 3D wind measurements (through polarimetry or Doppler shifts – though still largely experimental), more direct retrieval of cloud microphysics (with sub-mm channels to constrain ice particle sizes as ICI will do), air quality applications (e.g. certain frequencies can detect volcanic ash or have sensitivity to pollutants indirectly via absorption), and coupling with other sensors for enhanced products (e.g. using microwave + IR together in machine-learning frameworks to get the best of both). The challenge is to maintain accuracy while deriving more complex geophysical parameters, but as sensor technology and algorithms improve, we can expect a broader suite of outputs from microwave sensors beyond the traditional ones.

In conclusion, microwave radiometry has become an indispensable pillar of weather prediction, from daily forecasting to climate monitoring. Its ability to observe the hidden – peering through clouds and delivering data in all weather – makes it uniquely valuable. The coming years will see this technology made even more powerful by constellations of miniature sensors, advanced spectral and digital techniques, and deeper integration into forecasting systems through AI. There are challenges to overcome (technical, spectral, financial), but the trajectory is clear: microwave radiometers will continue to be at the forefront of meteorological innovation. As one NOAA summary aptly put it, for a relatively little-known instrument, the microwave sounder “has a major impact on our lives,” underpinning the forecasts we often take for granted and extending our understanding of the planet’s dynamic atmosphere. Each new development in this field brings us closer to the holy grail of weather science – accurate, timely, and detailed predictions through every storm and across every corner of the globe.

Sources:

• Ulaby, F.T. et al. (1981). Microwave Remote Sensing: Active and Passive. Volume I. Addison-Wesley. (Fundamental principles of microwave radiometry)
• Kneifel, S. et al. (2010). “Snow scattering signals in ground-based passive microwave radiometer measurements.” J. Geophys. Res. (study on cloud and snow effects on microwave signals)
• NASA NESDIS. “Advanced Technology Microwave Sounder (ATMS).” NOAA Satellite and Information Service. (Instrument overview and benefits)
• Bormann, N. et al. (2019). ECMWF All-sky Assimilation for Microwave Radiances – Tech Memo. (Describes assimilation of microwave radiances in numerical models)
• Microwave radiometer – Wikipedia (general description and history of microwave radiometers)
• NOAA NESDIS Workshop Report (2021). “Satellite Microwave Sounding Measurements in Weather Prediction”
• Spire Global (2025). “Hyperspectral Microwave Sounding: Spire’s revolutionary approach to weather forecasting” spire.com. (Company whitepaper on smallsat hyperspectral sounder concept)
• NASA (2020). “GPM Microwave Imager (GMI) Overview.” (Mission description for GPM radiometer)
• JAXA (2012). “Global Change Observation Mission – Water ‘Shizuku’ (GCOM-W)” (Mission page for AMSR2) global.jaxa.jp
• EUMETSAT (2023). “MetOp-SG Instruments: MWS, MWI, ICI.” (Instrument descriptions for next-gen European radiometers)
• Luo, Y. et al. (2023). “Machine Learning Retrieval of Temperature and Humidity Profiles from Microwave Radiometer.” Remote Sensing, 15, 3838. (Example of ML improving ground-based retrievals)
• Bennartz, R. and P. Bauer (2003). “Sensitivity of microwave radiances at 85–183 GHz to precipitating ice particles.” Radio Science, 38(4). (Use of high-frequency channels to detect ice in precipitation)
• NOAA OSPO. “AMSR-E and GMI Sensor Overviews.” (Technical specs of AMSR-E, GMI)
• Science@NASA – Microwaves (NASA, updated 2023). (Educational article highlighting microwave remote sensing uses)