13.2 Satellite and radar meteorology
5 min read•july 31, 2024
Satellite and radar meteorology are game-changers in weather forecasting. These tools give us a bird's-eye view of the atmosphere, helping meteorologists track storms, predict severe weather, and understand global weather patterns.
From watching entire hemispheres to detecting rain and wind, these technologies provide crucial data. They've revolutionized forecasting, allowing for more accurate predictions and earlier warnings of dangerous weather events.
Satellite Meteorology for Forecasting
Satellite Types and Sensing Techniques
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- Satellite meteorology uses artificial satellites to observe and analyze atmospheric conditions from space, providing a global perspective on weather patterns
- Two main types of meteorological satellites
- Geostationary satellites
- Remain stationary relative to Earth's surface
- Provide continuous coverage of a specific region
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- Orbit from pole to pole
- Provide global coverage with higher resolution at higher latitudes
- Geostationary satellites
- Satellites utilize various sensors to detect electromagnetic radiation across different wavelengths
- Visible spectrum (reflected sunlight)
- Infrared spectrum (emitted heat)
- Microwave spectrum (atmospheric moisture and temperature)
- Remote sensing techniques enable measurement of atmospheric parameters
- captures data across multiple wavelength bands
- determines vertical profiles of temperature and humidity
Applications and Products
- Satellite data crucial for monitoring severe weather events
- Tracking tropical cyclones (, typhoons)
- Detecting large-scale atmospheric circulation patterns (, frontal systems)
- Advanced satellite products contribute to numerical weather prediction models
- derived from cloud movement
- used to estimate
- for ocean-atmosphere interaction analysis
- Limitations of satellite meteorology
- Resolution constraints (especially for smaller-scale phenomena)
- Cloud obstruction of lower atmospheric layers
- Complex data interpretation algorithms required
Interpreting Satellite Imagery
Cloud Analysis and Weather System Identification
- Visible satellite imagery provides information during daylight hours
- reveal atmospheric dynamics
- indicate atmospheric stability
- suggests precipitation potential
- allows for 24-hour monitoring
- Cloud-top temperatures indicate cloud height and potential storm intensity
- (bright white in enhanced IR) suggest strong convection
- (darker in enhanced IR) indicate lower-level clouds
- reveals mid to upper-level moisture content
- Dark areas indicate dry air aloft
- Bright areas suggest high moisture content
- Aids in identifying jet streams and potential storm development areas
- Recognizing characteristic cloud patterns associated with specific weather systems
- indicate mid-latitude cyclones
- suggest tropical cyclones
- Clustered, circular patterns often represent thunderstorm complexes
Advanced Interpretation Techniques
- Cloud top temperature gradients in infrared imagery indicate storm intensity
- suggests intensifying convection
- may indicate storm weakening
- enhance feature distinction
- Combining visible and IR bands to differentiate cloud types
- Using water vapor and IR bands to assess atmospheric instability
- track weather system evolution
- Observing storm development and dissipation
- Analyzing frontal movement and interaction
- Monitoring large-scale circulation pattern changes
- Limitations in satellite interpretation
- Difficulty distinguishing cloud layers in
- Potential misinterpretation of low clouds in IR imagery (similar temperature to surface)
- Challenges in estimating precipitation rates solely from satellite data
Radar Meteorology for Forecasting
Radar Principles and Technologies
- Radar (Radio Detection and Ranging) emits and detects reflected radio waves
- Measures distance and intensity of precipitation and other atmospheric targets
- Operates in various wavelengths (S-band, C-band, X-band)
- in radar systems measures
- Detects movement towards or away from the radar
- Provides information on wind speeds and directions within storms
- enhances
- Transmits and receives both horizontal and vertical polarizations
- Distinguishes between different types of precipitation (rain, snow, hail)
- Improves estimation of precipitation rates and totals
- measured in dBZ (decibels relative to Z)
- Correlates with precipitation intensity
- Typical values: light rain (20-30 dBZ), heavy rain (50+ dBZ), hail (60+ dBZ)
- influence data interpretation
- Atmospheric refraction bends radar beam
- reduces signal strength over distance
- by terrain or structures creates data voids
Radar Networks and Limitations
- Weather radar networks provide comprehensive coverage
- (Next-Generation Radar) in the United States
- Similar networks in other countries (UK, Australia, Japan)
- Real-time monitoring of precipitation and severe weather events
- Continuous scanning at multiple elevation angles
- Data updates typically every 5-10 minutes
- Limitations of radar meteorology
- Beam blockage by terrain creates blind spots
- Range-dependent resolution (lower resolution at greater distances)
- Non-meteorological echoes can cause misinterpretation
- Ground clutter (buildings, mountains)
- Biological targets (birds, insects)
- Anomalous propagation in certain atmospheric conditions
Analyzing Radar Data
Reflectivity and Storm Structure Analysis
- patterns in displays
- Reveal spatial distribution of precipitation
- Higher dBZ values indicate stronger echoes and potentially more intense precipitation
- Typical patterns: stratiform rain (uniform), convective (cellular), linear (squall lines)
- Vertical cross-sections provide storm structure information
- Identify features like bright bands (melting layer)
- Detect hail cores and updraft regions
- offer three-dimensional storm analysis
- Crucial for identifying severe weather features
- (potential tornado signature)
- Bounded weak echo regions (intense updrafts)
- (rotating )
- Crucial for identifying severe weather features
- Dual-polarization products enhance precipitation classification
- indicates particle shape
- helps distinguish meteorological from non-meteorological targets
- improves heavy rain estimation
Velocity Data and Precipitation Estimation
- reveals storm dynamics
- Identifies mesocyclones (rotating updrafts in supercells)
- Detects divergence patterns (potential downbursts)
- Measures wind shear associated with severe thunderstorms and tornadoes
- Precipitation accumulation algorithms estimate rainfall totals
- Utilize reflectivity-rainfall (Z-R) relationships
- Account for variations in precipitation types
- Essential for hydrological forecasting and flash flood warnings
- Recognition of specific radar signatures aids in severe weather anticipation
- Bow echoes (potential for damaging straight-line winds)
- TVS (Tornado Vortex Signature) indicates possible tornado formation
- BWER (Bounded Weak Echo Region) suggests strong updraft and potential hail
- Integration of radar data with other sources enhances analysis
- Combining radar with satellite imagery for comprehensive storm structure
- Incorporating surface observations to verify precipitation types
- Using numerical model data to anticipate storm evolution and movement
Key Terms to Review (55)
Atmospheric motion vectors: Atmospheric motion vectors (AMVs) are measurements that describe the movement of air masses in the atmosphere, typically derived from satellite imagery and radar data. They provide essential information about wind patterns, which is critical for understanding weather systems, forecasting, and analyzing atmospheric dynamics. By tracking the displacement of cloud features or other atmospheric phenomena over time, AMVs help meteorologists assess the velocity and direction of winds at various altitudes.
Atmospheric sounding: Atmospheric sounding refers to the process of measuring the vertical profile of the atmosphere, typically using instruments like radiosondes attached to weather balloons. This technique provides critical data about temperature, humidity, pressure, and wind at various altitudes, which is essential for weather forecasting and understanding atmospheric processes. By analyzing these profiles, meteorologists can gain insights into weather patterns, stability, and potential severe weather events.
Attenuation: Attenuation refers to the reduction in strength or intensity of a signal as it travels through a medium. In the context of satellite and radar meteorology, this phenomenon affects the quality and accuracy of data transmitted through the atmosphere, impacting the ability to detect and analyze weather patterns effectively.
Beam blockage: Beam blockage refers to the phenomenon where an obstacle obstructs the radar or satellite signal, preventing the accurate detection or observation of meteorological phenomena. This occurs when structures such as buildings, trees, or terrain physically impede the line of sight between the radar or satellite and the target area, leading to incomplete or distorted data representation.
Beam propagation characteristics: Beam propagation characteristics refer to the behavior and attributes of electromagnetic waves, particularly how they travel through different mediums and interact with atmospheric phenomena. These characteristics are essential for understanding how satellite and radar systems transmit and receive signals, as the propagation can be influenced by factors like weather conditions, terrain, and atmospheric composition.
Bounded weak echo regions (bwer): Bounded weak echo regions (BWER) are specific areas within a thunderstorm that exhibit a significant decrease in radar reflectivity, indicating regions of weak precipitation or reduced particle density. These areas are often associated with the presence of an updraft and can signal the potential for severe weather phenomena, including tornadoes, as they are linked to the structure and dynamics of the storm.
Cloud patterns: Cloud patterns refer to the arrangement and formation of clouds in the atmosphere, which can indicate various weather conditions and atmospheric phenomena. These patterns are essential for meteorologists to predict weather events, understand storm systems, and identify climate trends. By analyzing cloud patterns through satellite and radar technology, meteorologists can gain insights into moisture levels, temperature changes, and potential severe weather outbreaks.
Cloud thickness: Cloud thickness refers to the vertical extent of a cloud, measured from its base to its top. It plays a crucial role in determining the cloud's physical properties, such as its potential for precipitation and its impact on local weather patterns. Understanding cloud thickness is essential for interpreting satellite imagery and radar data, as it influences the cloud's reflectivity and the dynamics of atmospheric processes.
Cloud top temperatures: Cloud top temperatures refer to the temperature measured at the highest point of a cloud, which is crucial for understanding cloud formation and development. This measurement helps meteorologists assess the altitude and structure of clouds, as well as their potential for precipitation and storm development. By analyzing cloud top temperatures using satellite data, forecasters can predict weather patterns more effectively.
Cloud types: Cloud types refer to the various classifications of clouds based on their appearance, altitude, and formation mechanisms. Understanding cloud types helps in predicting weather patterns and recognizing atmospheric processes that lead to precipitation and other meteorological phenomena. By categorizing clouds, meteorologists can analyze their role in weather systems and utilize satellite and radar technology to monitor and study these formations more effectively.
Cloud-top heights: Cloud-top heights refer to the altitude of the uppermost part of a cloud, which is crucial for understanding various meteorological phenomena. These heights can influence weather patterns, precipitation, and storm development, making them essential in both forecasting and analyzing atmospheric conditions. Remote sensing technologies like satellites and radar are commonly used to measure these heights, providing valuable data for meteorologists.
Clustered circular patterns: Clustered circular patterns refer to specific formations seen in weather data that are often represented as circular groupings or distributions of phenomena such as precipitation or cloud cover. These patterns can indicate certain meteorological conditions, helping forecasters identify the organization of weather systems, like storm formations or areas of convection, based on the distribution and intensity of weather features.
Cold cloud tops: Cold cloud tops refer to the uppermost regions of a cloud where temperatures are significantly lower than those at lower levels, typically found in high-altitude clouds like cumulonimbus. These colder areas are important because they can influence weather patterns and precipitation processes, serving as indicators for storm development and intensity when observed from satellite imagery or radar.
Comma-shaped clouds: Comma-shaped clouds are a type of cloud formation that resemble the shape of a comma, often associated with weather systems such as fronts or low-pressure areas. These clouds are typically observed on satellite imagery, indicating the presence of significant atmospheric processes like convergence and upward motion of air. The unique shape of these clouds can help meteorologists identify the organization and movement of weather systems.
Correlation coefficient (cc): The correlation coefficient (cc) is a statistical measure that quantifies the strength and direction of the relationship between two variables. It ranges from -1 to 1, where a value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 suggests no correlation. In meteorology, this measure helps in understanding how closely related different weather phenomena are, which is vital for analyzing data from satellite and radar observations.
Data assimilation: Data assimilation is the process of incorporating real-time observational data into numerical weather prediction models to improve their accuracy and reliability. This technique combines observed data from various sources, such as satellites and radar, with model forecasts to produce a more accurate representation of the current state of the atmosphere. By continuously updating models with new data, meteorologists can generate better short-term weather forecasts and improve long-term climate predictions.
Differential Reflectivity (ZDR): Differential Reflectivity (ZDR) is a radar measurement that quantifies the difference in the reflected power of horizontally polarized versus vertically polarized radar signals. This measurement is crucial for understanding precipitation characteristics, as it helps meteorologists distinguish between types of precipitation, such as rain, snow, and hail. By analyzing ZDR data, forecasters can gain insights into storm structure and intensity, which are essential for severe weather prediction.
Doppler Effect: The Doppler Effect refers to the change in frequency or wavelength of a wave in relation to an observer moving relative to the wave source. This phenomenon is crucial in meteorology, as it helps in measuring the velocity of precipitation and winds by analyzing the frequency shifts of radar signals reflected off moving targets, such as raindrops or snowflakes.
Doppler radar: Doppler radar is a specialized type of radar that uses the Doppler effect to measure the velocity of objects, such as precipitation and atmospheric movements. By emitting radio waves and analyzing their reflections off moving targets, it provides critical information about storm structure, wind patterns, and the potential for severe weather events.
Doppler Velocity Data: Doppler velocity data refers to the information obtained from Doppler radar that measures the velocity of moving targets, such as precipitation, by analyzing the frequency shift of the radar signal reflected back to the radar system. This data is crucial in meteorology as it allows for the tracking of storm movements, identifying wind patterns, and assessing the intensity of precipitation. By using this data, meteorologists can better understand storm dynamics and improve severe weather forecasts.
Dual-polarization radar technology: Dual-polarization radar technology is an advanced method used in weather radar systems that transmits and receives signals in both horizontal and vertical polarizations. This technology enhances the radar's ability to discriminate between different types of precipitation, such as rain, snow, or hail, by analyzing the shape, size, and orientation of hydrometeors. As a result, it provides meteorologists with more accurate and detailed information about storm structures and precipitation types, significantly improving weather forecasting and severe weather monitoring.
Geostationary satellites: Geostationary satellites are a type of satellite that orbit the Earth at the same rotational speed as the planet, allowing them to remain fixed over a specific point on the equator. This unique orbit, positioned approximately 35,786 kilometers above sea level, is crucial for continuous monitoring of weather patterns, providing real-time data and imagery essential for meteorology.
Ground truthing: Ground truthing is the process of validating data collected from remote sensing technologies, such as satellites and radar, by comparing it with direct observations made on the ground. This technique ensures that the information gathered through these technologies accurately reflects real-world conditions. By connecting satellite imagery and radar data to actual environmental features, ground truthing enhances the reliability of weather forecasts and climate studies.
Hook echoes: Hook echoes are distinctive radar signatures often associated with severe weather phenomena, particularly tornadoes. They appear as a hook-shaped feature on radar images, indicating the presence of rotating winds and significant precipitation, typically in the context of supercell thunderstorms. Understanding hook echoes is essential for meteorologists as they provide critical information for predicting severe weather events.
Hurricanes: Hurricanes are powerful tropical storms characterized by strong winds and heavy rainfall, forming over warm ocean waters. These storms are classified as cyclones and can cause significant damage when they make landfall, impacting weather patterns and atmospheric processes across regions. Understanding hurricanes involves studying their formation, structure, and the meteorological conditions that influence their development and movement.
Hydrometeor classification: Hydrometeor classification is the process of categorizing atmospheric water particles, such as precipitation and cloud droplets, based on their size, shape, and phase. This classification helps meteorologists understand and interpret weather patterns, enabling better predictions of storm behavior and intensity.
Image enhancement: Image enhancement refers to the process of improving the visibility and interpretability of images, especially those captured by satellites and radar systems. This technique plays a vital role in meteorology by allowing scientists to better analyze atmospheric phenomena, enabling clearer detection of clouds, precipitation, and other weather-related features.
Infrared imagery: Infrared imagery refers to the use of infrared radiation to capture images that depict heat emitted by objects, making it particularly useful in meteorology for analyzing cloud cover, surface temperatures, and atmospheric phenomena. This type of imagery enables meteorologists to monitor weather patterns, identify storm systems, and assess the intensity of precipitation by measuring the thermal characteristics of clouds and the Earth's surface.
Jet streams: Jet streams are narrow bands of strong winds in the upper levels of the atmosphere, typically found at altitudes of 30,000 to 40,000 feet. They play a crucial role in influencing weather patterns and temperature distribution across the globe, as they can steer weather systems and impact surface conditions.
Mesocyclones: Mesocyclones are large, rotating updrafts associated with severe thunderstorms, particularly supercell thunderstorms. These structures can produce intense weather phenomena such as tornadoes and heavy rainfall, making them significant in the study of severe weather and radar meteorology.
Multispectral analysis techniques: Multispectral analysis techniques involve capturing and interpreting data across multiple wavelengths of the electromagnetic spectrum to analyze various atmospheric and surface conditions. These techniques are crucial in meteorology as they provide detailed information about cloud properties, land use, vegetation health, and other environmental factors. By utilizing data from different spectral bands, meteorologists can enhance weather predictions, monitor climate changes, and assess natural disasters more effectively.
Multispectral imaging: Multispectral imaging is a technique that captures image data at specific wavelengths across the electromagnetic spectrum. This technology is particularly important in meteorology as it allows for the observation of atmospheric conditions, cloud properties, and surface characteristics by analyzing the reflected light from the Earth and its atmosphere. It enables scientists to derive valuable information about weather patterns, land use, and environmental changes through the detailed spectral analysis of the captured data.
Nexrad: NEXRAD, or Next Generation Radar, is a network of high-resolution Doppler weather radar systems operated by the National Oceanic and Atmospheric Administration (NOAA) in the United States. This technology provides meteorologists with real-time data on precipitation, storm intensity, and movement, allowing for improved weather forecasting and severe weather monitoring.
Plan Position Indicator (PPI): A Plan Position Indicator (PPI) is a radar display format that provides a two-dimensional view of weather echoes, showing their position relative to the radar site. This graphical representation is crucial for meteorologists as it allows for the tracking and analysis of precipitation patterns, storm movements, and other meteorological phenomena. By interpreting PPI data, meteorologists can make informed predictions about weather developments in real time.
Polar-orbiting satellites: Polar-orbiting satellites are spacecraft that orbit the Earth in a north-south direction, passing over the poles and allowing for comprehensive coverage of the planet's surface. This orbit enables these satellites to capture high-resolution images and data of the Earth's atmosphere and surface, providing crucial information for weather forecasting and environmental monitoring.
Precipitation Estimation: Precipitation estimation refers to the process of quantifying the amount of rainfall or other forms of precipitation over a specific area and time period. This estimation is crucial for weather forecasting, hydrological modeling, and understanding climate patterns. By utilizing various technologies, including satellite data and radar systems, meteorologists can accurately assess precipitation rates and distribution, which are vital for flood prediction and water resource management.
Radar Reflectivity: Radar reflectivity is a measure of the amount of transmitted radar energy that is scattered back to the radar receiver, typically expressed in decibels (dBZ). This measurement helps meteorologists determine the intensity and characteristics of precipitation, as different types of precipitation, such as rain, snow, or hail, will reflect radar waves differently. The reflectivity values can indicate areas of heavier or lighter precipitation and are essential for understanding storm structure and behavior.
Radial velocity: Radial velocity refers to the component of an object's velocity that points directly away from or towards an observer. In meteorology, it is crucial for understanding how storms and precipitation systems move through the atmosphere, as it helps in detecting motion relative to a specific point. This concept is fundamental in radar meteorology, as it enables meteorologists to analyze wind patterns and storm dynamics effectively.
Rapid cooling of cloud tops: Rapid cooling of cloud tops refers to the quick decrease in temperature at the upper surfaces of clouds, often associated with processes like evaporation, radiation, or convection. This phenomenon is critical for understanding cloud development, precipitation formation, and the overall dynamics of the atmosphere as it affects weather patterns and satellite imagery interpretation.
Reflectivity: Reflectivity refers to the measure of the amount of electromagnetic energy that is reflected off a surface, particularly in the context of radar meteorology where it indicates the intensity of precipitation. It plays a crucial role in radar systems, allowing meteorologists to assess and visualize weather phenomena such as rain, snow, and hail. The higher the reflectivity value, the more intense the precipitation is likely to be, which aids in forecasting and warning systems.
Roger W. Brown: Roger W. Brown was a prominent meteorologist known for his contributions to the development of satellite and radar meteorology. His work focused on enhancing the understanding and interpretation of atmospheric phenomena through advanced technology, which significantly improved weather forecasting and storm tracking capabilities. Brown's research laid the groundwork for integrating satellite data into operational meteorology, paving the way for modern forecasting techniques.
Sea Surface Temperatures: Sea surface temperatures (SST) refer to the temperature of the upper layer of the ocean, which significantly influences weather patterns and climate. SST affects atmospheric circulation, the development of storms, and the behavior of marine ecosystems. Understanding SST is essential for meteorological studies, especially in predicting phenomena like El Niño and hurricanes.
Sensor calibration: Sensor calibration is the process of adjusting and fine-tuning a sensor to ensure its measurements are accurate and reliable. This process is critical for satellite and radar meteorology, as it directly impacts the quality of data collected for weather observations, forecasting, and climate studies. Proper calibration ensures that the sensors provide data that reflects true atmospheric conditions, which is essential for accurate weather prediction and monitoring.
Severe weather detection: Severe weather detection refers to the process and techniques used to identify and monitor extreme weather phenomena, such as thunderstorms, tornadoes, and severe winds, often with the aim of issuing timely warnings to protect life and property. This detection is significantly enhanced through the use of advanced technologies, such as satellites and radar systems, which allow meteorologists to observe atmospheric conditions and track storm development in real time.
Specific differential phase (kdp): Specific differential phase (kdp) is a radar-derived quantity that measures the phase shift between horizontally and vertically polarized microwave signals as they propagate through precipitation. This parameter is particularly useful in meteorology for estimating rainfall rates, understanding precipitation type, and assessing storm intensity. By analyzing kdp, meteorologists can obtain insights into the microphysical properties of the precipitation, providing valuable information for forecasting and radar meteorology.
Spiral bands: Spiral bands are curved formations of clouds and precipitation that extend outward from the center of a tropical cyclone. These bands are a key feature of hurricanes and tropical storms, influencing both their structure and intensity. The organization of spiral bands helps to transport moisture and energy from the surrounding environment into the storm, playing a critical role in the cyclone's development and maintenance.
Storm intensity: Storm intensity refers to the strength or severity of a storm, characterized by factors such as wind speed, precipitation rates, and atmospheric pressure. Understanding storm intensity is crucial for predicting potential impacts on the environment and human activities, as it can significantly affect local weather conditions and lead to hazardous events like flooding, tornadoes, or hurricanes.
Thunderstorms: Thunderstorms are localized weather phenomena characterized by the presence of thunder, lightning, and often heavy rain or hail. They typically develop in warm, moist air when conditions are unstable, leading to the rapid ascent of air and the formation of cumulonimbus clouds. Understanding thunderstorms is essential for predicting severe weather, recognizing their relationship with frontal systems, interpreting data from satellite and radar technology, and planning for safe aviation operations.
Time-lapse sequences: Time-lapse sequences are a method of capturing images or video over a period of time and then playing them back at a faster rate to show changes that occur slowly. In the context of satellite and radar meteorology, these sequences provide a dynamic visual representation of atmospheric phenomena, enabling meteorologists to analyze and interpret weather patterns and developments more effectively.
Visible imagery: Visible imagery refers to satellite images that capture reflected sunlight from Earth's surface, allowing meteorologists to observe and analyze weather patterns and features during daylight hours. This type of imagery is crucial for identifying cloud cover, land features, and other atmospheric phenomena, providing a foundational tool for understanding weather systems.
Volume scans: Volume scans refer to a method of collecting radar data that captures a three-dimensional representation of the atmosphere at various heights. This technique allows meteorologists to analyze the structure and behavior of weather phenomena, such as precipitation and storm systems, by providing detailed information about the intensity and distribution of these elements across different altitudes. Volume scans play a critical role in real-time weather observation and forecasting, enhancing the understanding of complex atmospheric processes.
Warm cloud tops: Warm cloud tops refer to the upper regions of clouds where the temperature is relatively high compared to the surrounding atmosphere, typically above freezing. These cloud tops are significant in understanding precipitation processes, cloud formation, and their interaction with satellite and radar observations. Warm cloud tops are often associated with low-level clouds like stratus and cumulus that can lead to light precipitation or drizzle.
Warming of cloud tops: Warming of cloud tops refers to the phenomenon where the upper portions of clouds experience an increase in temperature, often observed using satellite imagery and radar. This warming can be indicative of various meteorological conditions, including changes in cloud composition and the potential for precipitation. It plays a crucial role in understanding cloud dynamics, energy transfer in the atmosphere, and the development of severe weather events.
Water vapor imagery: Water vapor imagery is a satellite-based technique that captures the distribution and movement of water vapor in the atmosphere. This imagery is crucial for meteorologists as it provides insights into moisture levels, storm development, and atmospheric dynamics, helping to predict weather patterns and analyze severe weather events.
William J. Black: William J. Black is a notable figure in the field of meteorology, particularly recognized for his contributions to satellite and radar meteorology. His work has significantly advanced the understanding of weather systems and phenomena through the development and implementation of technologies that enhance weather observation and forecasting capabilities.