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Evaluation of the MODIS Collection 6 Multilayer Cloud Detection Algorithm Through Comparisons with Cloudsat Cloud Profiling Radar and CALIPSO CALIOP Products
Since multilayer cloud scenes are common in the atmosphere and can be an important source of uncertainty in passive satellite sensor cloud retrievals, the MODIS MOD06 and MYD06 standard cloud optical property products include a multilayer cloud detection algorithm to assist with data quality assessment. This paper presents an evaluation of the Aqua MODIS MYD06 Collection 6 multilayer cloud detection algorithm through comparisons with active Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products that have the ability to provide cloud vertical distributions and directly classify multilayer cloud scenes and layer properties. To compare active sensor products with an imager such as MODIS, it is first necessary to define multilayer clouds in the context of their radiative impact on cloud retrievals. Three main parameters have thus been considered in this evaluation: (1) the maximum separation distance between two cloud layers, (2) the thermodynamic phase of those layers and (3) the upper-layer cloud optical thickness. The impact of including the Pavolonis–Heidinger multilayer cloud detection algorithm, introduced in Collection 6, to assist with multilayer cloud detection has also been assessed. For the year 2008, the MYD06 C6 multilayer cloud detection algorithm identifies roughly 20% of all cloudy pixels as multilayer (decreasing to about 13% if the Pavolonis–Heidinger algorithm output is not used). Evaluation against the merged CPR and CALIOP2B-CLDCLASS-lidar product shows that the MODIS multilayer detection results are quite sensitive to how multilayer clouds are defined in the radar and lidar product and that the algorithm performs better when the optical thickness of the upper cloud layer is greater than about 1.2 with a minimum layer separation distance of 1 km. Finally, we find that filtering the MYD06 cloud optical properties retrievals using the multilayer cloud flag improves aggregated statistics, particularly for ice cloud effective radius.
Radar concepts for the next generation of spaceborne observations of cloud and precipitation processes
Two decades of spaceborne cloud and precipitation radar data provided by the TRMM’s Precipitation Radar (PR) [1], CloudSat’s Cloud Profiling Radar (CPR) [2,3] and GPM’s Dual-frequency Precipitation Radar (DPR) [4] have enabled unprecedented advancements in the global mapping of occurrence and vertical structure of most types of meteorological events. After the immense success of these radars, two new spaceborne atmospheric radars, the EarthCARE Cloud Profiling Radar (CPR) [5], and the Radar in a CubeSat (RainCube) [6] have been developed and will be launched in the upcoming years, and several new radar concepts have been developed and are being considered for a variety of mission concepts. For example, spaceborne precipitation and cloud radars operating at multiple frequencies (e.g., Ku-, Ka- and W-band simultaneously) with a single antenna, and that provide scanning, polarimetric and Doppler capabilities at all frequencies; extremely compact radar architectures that enable accommodation of this category of radars in spacecrafts as small as a 6U CubeSats, as well as Doppler-capable millimeter-wave weather radars for Low Earth Orbit (LEO) or Geostationary Earth Orbit (GEO) satellites, are being defined and developed. These new instrument concepts are intended to fill the current observational gaps in the advancement of weather and climate models, and leverage on the TRMM, GPM and CloudSat experiences.
Seeking Augmented Information Content Concerning Diurnal Precipitation Achieved by Combining TRMM-PR and CloudSat-CPR Radar Data Sets
The CloudSat satellite's Cloud Profiling Radar (CPR) is a highly sensitive 94 GHz (W-band) nadir viewing radar system flown in retrograde sun synchronous orbit useful for determining the vertical structure of cloud hydrometeors down to sensitivity of approx. -30 dBZ reflectivity factor. Given this sensitivity, it is possible to unambiguously measure precipitation rates in clouds over a spectrum extending from approx. 0.08 - 3.0 mm hr (sup -1) down to altitudes of 0.5 km with approx.0.25 km vertical binning. This enables an effective means to measure a great deal of the drizzle and light rain spectrum. However, because of its near-polar sunsynchronous orbit, CloudSat cannot sample the diurnal cycle of precipitation, nor with its nadir-only CPR view can it obtain a high duty cycle in sampling precipitation at fixed local times over fixed positions. On the other hand, the TRMM satellite, which is flown in a non-sunsynchronous 35-degree inclined orbit carrying the 13.8 GHz KU-band Precipitation Radar (PR) scanning through nadir over an approx. 225 km swath, can sample both the diurnal cycle and with a much improved duty cycle relative to CloudSat. Moreover, the PR and CPR have the same 0.25 km vertical binning capability. The PR's greatest shortcoming is its approx. +17 dBZ sensitivity, which eliminates the possibility of measuring rain rates below -0.3-0.5 mm hr(sup -1), which can involve rainfall accumulations of up to 50% of the total over some regions. This begs the question of whether by combining CPR and PR data sets, whether it is possible to obtain an augmented measurement of the diurnal precipitation cycle. By collecting complimentary datasets during CloudSat and TRMM satellite orbit crossings within a delta t = 45-min proximity window, it is possible to demonstrate that whenever TRMM detects a precipitation signal, the correlations along the vertical axis between the reflectivities acquired from the CPR and PR are in inverse proportion to the magnitude of the delta t proximity window. By taking advantage of these underlying correlations, it is possible to develop a functional which can be used to broaden the reflectivity spectrum, concomitantly the rain rate spectrum, of the PR measurements based on the inherently broader reflectivity spectrum of the CPR at the lower reflectivity end of the spectrum, concomitantly at lighter rain rates. With the functional in place, it is then possible to produce synthetic CloudSat precipitation imagery over the PR track and thus over the diurnal time period. These augmented data are then used to study the spectral-vertical diurnal properties of precipitation over oceanic regions observed by TRMM.
Design and RF Characterization of Spaceborne 94.1 GHz Cassegrain Dual-Reflector Cloud Profiling Radar Antenna
This paper presents the design and RF characterization of 94.1 GHz Cassegrain dual-reflector antenna for the proposed Cloud Profiling Radar (CPR) instrument.
Relation of Cloud Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and CloudSat Merged Cloud Vertical Profiles
A cloud frequency of occurrence matrix is generated using merged cloud vertical profile derived from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical pro les can be related by a set of equations when the correlation distance of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches the random overlap with increasing distance separating cloud layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and CloudSat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The cloud correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when cloud fractions of both layers in a two-cloud layer system are the same.
A-Train Observations of Deep Convective Storm Tops
The paper highlights simultaneous observations of tops of deep convective clouds from several space-borne instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Aqua satellite, Cloud Profiling Radar (CPR) of the CloudSat satellite, and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) flown on the CALIPSO satellite. These satellites share very close orbits, thus together with several other satellites they are referred to as the "A-Train" constellation. Though the primary responsibility of these satellites and their instrumentation is much broader than observations of fine-scale processes atop convective storms, in this study we document how data from the A-Train can contribute to a better understanding and interpretation of various storm-top features, such as overshooting tops, cold-U/V and cold ring features with their coupled embedded warm areas, above anvil ice plumes and jumping cirrus. The relationships between MODIS multi-spectral brightness temperature difference (BTD) fields and cloud top signatures observed by the CPR and CALIOP are also examined in detail to highlight the variability in BTD signals across convective storm events.
A 94 GHz RF Electronics Subsystem for the CloudSat Cloud Profiling Radar
The CloudSat spacecraft, scheduled for launch in 2004, will carry the 94 GHz Cloud Profiling Radar (CPR) instrument. The design, assembly and test of the flight Radio Frequency Electronics Subsystem (RFES) for this instrument has been completed and is presented here. The RFES consists of an Upconverter (which includes an Exciter and two Drive Amplifiers (DA's)), a Receiver, and a Transmitter Calibrator assembly. Some key performance parameters of the RFES are as follows: dual 100 mW pulse-modulated drive outputs at 94 GHz, overall Receiver noise figure < 5.0 dB, a highly stable W-band noise source to provide knowledge accuracy of Receiver gain of < 0.4 dB over the 2 year mission life, and a W-band peak power detector to monitor the transmitter output power to within 0.5 dB over life. Some recent monolithic microwave integrated circuit (MMIC) designs were utilized which implement the DA's in 0.1 micron GaAs high electron-mobility transistor (HEMT) technology and the Receiver low-noise amplifier (LNA) in 0.1 micron InP HEMT technology.
Fast, Space Qualified 3000 V Modulator for a Cloud Profiling Radar
Cloudsat's Cloud Profiling Radar (CPR) delivers a 2 kW of RF pulse using an extended Interaction Klystron (EIK). 'To drive such an EIK, it was necessary to develop a -16.3 kV High Voltage Power Supply (HVPS) and a Focus Electrode Modulator (FEM), floating at Cathode potential to turn the EIK's Beam on and off -45V to -3kV with respect to the Cathode. This paper describes the design approach for the FEM and its performance at EM and Flight Configuration. In author's opinion it a simple but universal approach which allow designer to achieve greater flexibility and freedom in designing high swinging space qualifiable FEM.
Reducing Surface Clutter in Cloud Profiling Radar Data
An algorithm has been devised to reduce ground clutter in the data products of the CloudSat Cloud Profiling Radar (CPR), which is a nadir-looking radar instrument, in orbit around the Earth, that measures power backscattered by clouds as a function of distance from the instrument. Ground clutter contaminates the CPR data in the lowest 1 km of the atmospheric profile, heretofore making it impossible to use CPR data to satisfy the scientific interest in studying clouds and light rainfall at low altitude. The algorithm is based partly on the fact that the CloudSat orbit is such that the geodetic altitude of the CPR varies continuously over a range of approximately 25 km. As the geodetic altitude changes, the radar timing parameters are changed at intervals defined by flight software in order to keep the troposphere inside a data-collection time window. However, within each interval, the surface of the Earth continuously "scans through" (that is, it moves across) a few range bins of the data time window. For each radar profile, only few samples [one for every range-bin increment ((Delta)r = 240 m)] of the surface-clutter signature are available around the range bin in which the peak of surface return is observed, but samples in consecutive radar profiles are offset slightly (by amounts much less than (Delta)r) with respect to each other according to the relative change in geodetic altitude. As a consequence, in a case in which the surface area under examination is homogenous (e.g., an ocean surface), a sequence of consecutive radar profiles of the surface in that area contains samples of the surface response with range resolution (Delta)p much finer than the range-bin increment ((Delta)p << r). Once the high-resolution surface response has thus become available, the profile of surface clutter can be accurately estimated by use of a conventional maximum-correlation scheme: A translated and scaled version of the high-resolution surface response is fitted to the observed low-resolution profile. The translation and scaling factors that optimize the fit in a maximum-correlation sense represent (1) the true position of the surface relative to the sampled surface peak and (2) the magnitude of the surface backscatter. The performance of this algorithm has been tested on CloudSat data acquired over an ocean surface. A preliminary analysis of the test data showed a surface-clutter-rejection ratio over flat surfaces of >10 dB and a reduction of the contaminated altitude over ocean from about 1 km to about 0.5 km (over the ocean). The algorithm has been embedded in CloudSat L1B processing as of Release 04 (July 2007), and the estimated flat surface clutter is removed in L2B-GEOPROF product from the observed profile of reflectivity (see CloudSat product documentation for details and performance at http://www.cloudsat.cira.colostate.edu/ dataSpecs.php?prodid=1).
Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model
The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.
CloudSat: A Spacecraft to Measure the Vertical Structure of Clouds
CoudSat is being developed to measure the vertical structure of clouds from space. It integrates a 94-GHz cloud profiling radar (CPR) with an A-band spectrometer/visible image (ABSI) and submillimer-wave cloud ice radiometer (CLIR).
Current Scientific Progress and Future Scientific Prospects Enabled by Spaceborne Precipitation Radar Measurements
First, we examine current scientific progress and understanding that have been possible through use of spaceborne precipitation radar measurements being provided by the TRMM and CloudSat satellites. Second, we look across a future 20-year time frame to assess how and why anticipated improvements in space radar systems will further advance scientific progress into topic areas once considered beyond the realm of space-based remote sensing. JAXA's 13.8 GHz Ku-band cross-track scanning Precipitation Radar (PR) developed for flight on NASA's non-sun-synchronous, diurnally-precessing TRMM satellite, was the first Earth radar flown in space that was designed specifically for precipitation measurement. Its proven accuracy in measuring global rainfall in the tropics and sub-tropics and its unanticipated longevity in continuing these measurements beyond a full decade have established the standards against which all follow-up and future space radars will be evaluated. In regards to the current PR measurement time series, we will discuss a selection of major scientific discoveries and impacts which have set the stage for future radar measuring systems. In fact, the 2nd contemporary space radar applicable for terrestrial precipitation measurement, i.e., JPL-CSA's 94 GHz nadir-staring Cloud Profiling Radar (CPR) flown on NASA's sun-synchronous CloudSat satellite, although designed primarily for measurement of non-precipitating cloud hydrometeors and aerosols, has also unquestionably advanced precipitation measurement because CPR's higher frequency and greatly increased sensitivity (approximately 30 dBZ) has enabled global observations of light rain rate spectrum processes (i.e., rain rates below 0.05 mm per hourand of precipitation processes in the high troposphere (particularly ice phase processes). These processes are beyond reach of the TRMM radar because the PR sensitivity limit is approximately 17 dBZ which means its lower rain rate cutoff is around 0.3 mm per hour and its vertical profiling acuity is greatly limited above the melting layer. Thus, the newer CPR measurements have become important for a variety of scientific reasons that will be highlighted and assessed. In considering scientific progress likely to stem from future precipitation radar systems, we will specifically examine possible scientific impacts from three anticipated missions for which NASA and various of its space agency partners are expected to lead the way. These three missions are: (1) the nearterm Global Precipitation Measuring (GPM) Mission; (2) the decadal timeline Aerosol and Cloud Experiment (ACE) Mission; and the post-decadal timeline NEXRAD in Space (NIS) Mission. The observational capabilities of the planned radar systems for each of these three satellite missions are distinct from each other and each provides progressive improvements in precipitation measuring and scientific research capabilities relative to where we are now -- insofar as TRMM PR and the CloudSat CPR capabilities. The potential innovations in scientific research will be discussed in a framework of likely synergisms between next-generation radar capabilities and accessible dynamical and microphysical properties that have heretofore evaded detection.
NASA Spaceborne Radar Missions: CloudSat and QuickScat: To Observe Clouds and Sea Surface Winds
CloudSat is a joint US/Canadian spaceborne science mission for global measurements of atmospheric cloud structures. Cloud Profiling Radar (CPR) has already captured many stunning profiles of cloud/precipitation structures, some have not been seen before. Observation of storms' cloud formation, in conjunction with data from other remote sensors, will hopefully improve quality of natural hazards' forecasts.
First EarthCARE CPR Observations of Dynamics–Microphysics Coupling in Marine Cold‐Air Outbreak Clouds
Marine cold-air outbreak (MCAO) clouds begin as shallow cloud streets near the ice edge and evolve into broken open-cell convection downstream. Their rapid transitions in cloud structure and microphysics are closely linked to vertical motions, but this interplay has not previously been observed from space. The EarthCARE satellite, carrying the first spaceborne Doppler radar (Cloud Profiling Radar, CPR), now measures hydrometeor sedimentation velocity and vertical air motion. Using CPR observations over the Norwegian and Barents Seas (December 2024–May 2025), we analyze MCAO and non-MCAO clouds. We find that strong updrafts in MCAO clouds coincide with larger supercooled liquid water (SLW) path (LWP). These conditions are accompanied by increases in sedimentation velocity and its vertical gradient, reflecting rapid riming-driven ice growth. In contrast, non-MCAO clouds show lower riming efficiency at similar LWP due to relatively weaker dynamical support. This emphasizes the importance of dynamics in shaping polar cloud structure and microphysics.
CloudSat: the Cloud Profiling Radar Mission
The Cloud Profiling Radar (CPR), the primary science instrument of the CloudSat Mission, is a 94-GHz nadir-looking radar that measures the power backscattered by clouds as a function of distance from the radar. This instrument will acquire a global time series of vertical cloud structure at 500-m vertical resolution and 1.4-km horizontal resolution. CPR will operate in a short-pulse mode and will yield measurements at a minimum detectable sensitivity of -28 dBZ.