Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA’s CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors’ type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts.
There is not much information available to diagnose large-scale vertical cloud structure and associated precipitation characteristics other than within the vicinity of ground-based radars. Spaceborne satellites and their onboard radars provide the opportunity to observe and analyze the entire vertical cloud structure. One such satellite, CloudSat, will fill this void of the ground-based radar network, expanding the data available to better understand weather systems and to produce more accurate weather models.
To diagnose storm structure, two spaceborne satellites and their radars, the CloudSat’s Cloud Profiling Radar (CPR) and the TRMM’s Precipitation Radar (PR), will be used. To offer cross-verification of the observations made by these two radars, a comparison with the National Mosaic and Multisensor QPE (NMQ) system, which employs the NEXRAD radar network, will be used. The vertical structure of a winter storm system will be analyzed, similar to the work done by Matrosov [
On 17 January, 2009, the researched storm had associated light freezing rain over Tennessee at 2000 UTC, leading to a crash involving 55 cars and trucks with over a dozen injuries, including one woman who broke both of her arms. On 18 January from 2000 to 2200 UTC, North Carolina experienced heavy snow from the same storm, with totals approaching six inches in some locations. Neither the TRMM or CloudSat satellites passed over the storm at these exact times or locations, due to CloudSat’s limited spatial coverage and TRMM’s latitudinal bounds. This storm, however, was still significant enough to warrant looking further into the storm structure and products through a comparison of CloudSat and NMQ as well as TRMM and NMQ.
The purpose of this paper is to use spaceborne satellites that are sensitive to precipitation and cloud hydrometeors to diagnose vertical storm structure. To cross-verify the observations made by these satellites, a comparison with a ground-based radar system (NMQ) will be performed. Specifically, the brightband level and freezing level will be compared, along with reflectivity values as measured by the different systems.
Section
The National Mosaic and Multisensor Quantitative Precipitation Estimation (QPE) (NMQ) system (
The NMQ system, through the collection of all the different weather products, offers a comprehensive view of storm structure. The system offers several products through which storm structure can be diagnosed, including 2D and 3D reflectivity, vertical profile of reflectivity (VPR), precipitation phase and type, and rainfall rates and rainfall totals. There is much more available through this comprehensive system, such as rain rates, rainfall totals, and vertically integrated liquid, but only a few products will be utilized for this research.
The National Aeronautics and Space Administration’s (NASA) Earth Science Enterprise (ESE), through various satellites, provides information about the influence clouds have on the atmosphere, including weather and climate. The afternoon “A-Train” satellite constellation is a satellite flying formation comprised of several different missions that simultaneously increase the information available about the condition of the Earth’s atmosphere [
The CloudSat satellite is one of the five satellites in the A-Train constellation, located at the second flying position behind Aqua. CloudSat was launched into the A-Train formation on 28 April, 2006 and is managed and maintained by NASA’s Jet Propulsion Laboratory (JPL) in Pasadena, CA. The onboard W-band nadir-pointing Cloud Profiling Radar (CPR) has been operating since 2 June, 2006, having lost only ten hours of data since the beginning of operations [
CloudSat offers many different products to better understand clouds’ effect on the climate and cloud structure. The CloudSat2B Cloud Geometrical Profile algorithm (2B-GEOPROF) provides CPR reflectivity values, allowing for a vertical time-height cross-section of reflectivities along the CloudSat track to be generated. The Cloud Classification algorithm (2B-CLDCLASS) is another useful product and provides the cloud classification for all vertical and horizontal levels within the observed storm, with nine classifications ranging from cirrus clouds to stratus clouds to deep convection. The European Centre for Medium-Range Weather Forecast (ECMWF) model data is contained within the ECMWF-AUX files and can be accessed to create temperature profiles, which can be useful in the identification of the freezing level. Additional products include those which contain data about ice and liquid water content, rainfall rates, heating rates, and heating fluxes. All algorithms and data products are described in full detail and retrievable from the CloudSat Data Processing Center (DPC) in one granule, or one orbit, increments (
The Tropical Rainfall Measuring mission (TRMM) satellite’s goal is to provide detailed information on the distribution of precipitation over the tropics to better understand the connection and interaction between oceans, land masses, and air masses and the shared effect on global rainfall and climate (
From the TRMM satellite, the 2A25 product used in Version 7, the TRMM Precipitation Radar (PR) Rainfall Rate and Profile Product, was used. The PR was built by JAXA in a joint contribution with the US/Japan TRMM. The PR began operating on 8 December, 1997. The PR was the first spaceborne instrument designed to provide a three-dimensional view of storm structure, providing some similar data products as those of CloudSat. The radar operates at a frequency of 13.8 GHz in the Ku-band and a wavelength of 2 cm, offering a geographic coverage from 38°S–38°N and 180°W–180°E, with a temporal resolution of sixteen orbits per day (~91.5 minutes per orbit), a horizontal resolution of 5.0 km, and vertical resolution of 0.25 km along the slant of the ray. TRMM has a swath width of 247 km with 49 rays per scan, with one scan lasting 0.6 seconds. The PR has a sensitivity less than that of CPR and is affected by Mie scattering. The PR, through all of its products, has expanded the knowledge available to understand the precipitation characteristics of the tropics.
One of the data products provided by the TRMM PR is the corrected
On 18 January, 2009, the CloudSat satellite passed over a winter storm in South Carolina at 1847 UTC, with its path dividing the state into nearly equal eastern and western halves, passing through Charleston county in the south and advancing northward through Lancaster county, covering latitude and longitude bounds of approximately 32°–35°N and 80°–82°W (Figure
The CloudSat track has been overlaid with the NMQ composite reflectivity from 18 January, 2009 at 1845 UTC.
Using the CloudSat products mentioned in Section
Reflectivity cross-sections from (a) CloudSat CPR and (b) NMQ.
Brightband features are faintly present at about 2 km MSL from about 33°-34°N on the CPR cross-section, where a tight vertical reflectivity gradient within the storm is observed, with local reflectivity maxima values of approximately 15 dBZ. The NMQ cross-section shows the largest reflectivity values in roughly the same area as CloudSat. Brightbands occur in stratiform precipitation, where a transition between hydrometeor phase from solid to liquid occurs [
The cloud classification determined from CloudSat CPR.
The brightband layer of the CPR reflectivity cross-section and freezing level and the height of the 0°C isotherm on the CPR temperature profile are located at nearly the same height. As shown in the temperature profile of Figure
The temperature profile determined from CloudSat CPR. The dark line shows the freezing level.
With the NMQ system, a VPR from Columbia, SC, can be used to compare the freezing level with that determined from CloudSat (Figure
The vertical profile of reflectivity from Columbia, SC. The blue line indicates the reflectivity values for stratiform precipitation, where the peak shows the brightband level.
Scatterplots of NMQ reflectivity values and CPR reflectivity values from (a) 33°–33.5°N, (b) 33.5°–34°N, (c) 34°–34.5°N, and (d) 34.5°–35°N. The diamonds indicate the ice region, the crosses indicate the melting layer, and the circles indicate the rain region.
At 1810 UTC, the TRMM satellite observed the same storm over the southeastern US about forty minutes before CloudSat. The chosen path to analyze stretches from Grady County in the far southwest of Georgia and extends northeastward to Horry County in eastern South Carolina, bounded approximately by 30°–34°N and 79°–85°W (Figure
The TRMM track shown over the NMQ composite reflectivity from 18 January, 2009 at 1810 UTC.
The vertical resolution of the TRMM satellite is worse than that of CloudSat, but the same features are still distinguishable. From 30°–32°N, the cloud tops are very low, at heights less than 5 km MSL in most cases, but the cloud tops stay fairly consistent around 5 km MSL from 32°–34°N (Figure
Reflectivity cross-sections from the (a) TRMM-PR and (b) NMQ.
Since the PR was developed to study precipitation, a temperature profile is not available through this dataset. The NMQ system’s VPRs, however, may still be used to compare the brightband levels as well as to see where the freezing level occurs in comparison to the brightband. The chosen TRMM track has passed closely within two different VPR locations, one in Tallahassee, FL (KTLX), and the other in Charleston, SC (KCLX) (Figure
Vertical profiles of reflectivity from (a) Tallahassee, FL, and (b) Charleston, SC. The dark line shows the reflectivity values for stratiform precipitation, where the peak shows the brightband.
Reflectivity values for the TRMM-PR and NMQ system were compared as scatterplots (Figure
Scatterplots of NMQ reflectivity values and PR reflectivity values from (a) 30°-31°N, (b) 31°-32°N, (c) 32°-33°N, and (d) 33°-34°N. The diamonds indicate the ice region, the crosses indicate the melting layer, and the circles indicate the rain region.
The CloudSat satellite’s Cloud Profiling Radar is very useful in the diagnosis of storm structure, due to the products that show the cross-section of reflectivity and temperature profile and also cloud classification and precipitation type. The CPR has a better resolution than the TRMM PR and is able to provide important information about the different levels within a storm, specifically above the freezing level and at the freezing level itself. To provide supplementary information, the ground-based NMQ radar system was used, which incorporates several weather products and will lead to improved quantitative precipitation estimation.
Through the combination of data available from ground and spaceborne radars, our understanding of vertical cloud structure has increased. Using different radar systems allows for cross-verification of observations, as shown by comparing the reflectivity cross-sections, temperature profile, and VPRs. This combination also allows for the classification of hydrometeors and microphysical retrieval through the usage of multimeasurements. Using CloudSat and TRMM products, the NMQ system has been used to verify the freezing level and brightband level, as well as to provide a comparison of the reflectivity values as recorded by the different systems. Through the analysis and comparison of these different radar systems, a better understanding of the vertical storm structure will lead to improved quantitative precipitation estimation and forecast modeling.
The authors thank Nicole Grams and Brittany Recker for their contributions to this research project. This material is based upon work supported by the National Science Foundation under Grant no. AGS-1062932.