Бұлттарды анықтауға арналған радиолокациялық жүйелер

Weather radar tuned to cloud detection

Millimeter wave cloud radars, also denominated cloud radars, are radar systems designed to monitor clouds with operating frequencies between 24 and 110 GHz (Table 1). Accordingly, their wavelengths range from 1 mm to 1.11 cm, about ten times shorter than those used in conventional S band radars such as NEXRAD.

Band name Frequency range [GHz] Wavelength range [mm] Ka 24 40 7.5 11.1 W 75 100 2.7 4.0

The main purpose of these radars is the investigation of cloud properties and evolution. They typically operate at 35 GHz in the Ka band and at 94 GHz in the W band, where the atmospheric transmission is maximum. These frequencies correspond to wavelengths around 8 and 3 mm. Millimeter cloud radars have a high temporal and range resolution: temporal resolution is adjustable and typically ranges from 1 to 10 seconds, while the range resolution ranges from a few meters for cloud radars using frequency modulation of the transmitted signal (e. g. 4 m for the Frequency Modulated Continuous Wave (FMCW) 94 GHz cloud radar operating at UK Met Office), to several meters for magnetron based cloud radars (e. g. from 15 to 60 m for MIRA systems). The maximum detection range is between 14 and 20 km and the Doppler velocity resolution is of few cm/s. Most of the cloud radars are polarimetric, being able to measure the particles irregularity by means of the linear depolarization ratio (LDR). Usually they operate pointing to the zenith, but an increasing number of them have nowadays scanning units, that allow to retrieve additional information such as volume information when performing various Range Height Indicator (RHI) scans at different angles and at a relatively high speed, and vertical wind profiles, when performing plan position indicator (PPI) at few degrees from the zenith. Regarding the different cloud radars operating wavelengths, it must be taken into account that longer wavelengths are less attenuated by drizzle and rain, while shorter wavelengths are more sensitive to smaller particles. Accordingly, radar signals are less attenuated in Ka band than in W band, while W band radars are able to detect smaller particles. Even though, the cloud radar beams are much less attenuated by cloud or precipitation particles than the lidar beam. Cloud radars are used nowadays to determine cloud boundaries (e. g. cloud bases and tops) and to estimate clouds microphysical properties, such as particle size and mass content, which aids in understanding how clouds reflect, absorb and transform radiant energy passing through the atmosphere. They are also intensively used to investigate fog. Furthermore, cloud radars are being used for entomology studies for more than 40 years, since Ka and W band radars detect almost exclusively insect targets on warm cloudless days, and more recently are also used for the study of giant aerosols. Even though most cloud radar systems are ground based, they can also be airborne and space based. Examples of airborne systems are cloud radars installed on HALO (High Altitude and Long Range Research Aircraft) and Wyoming KingAir Research Aircraft. An example of spaceborne Cloud Profiling Radar (CPR) is operating in the CloudSAT satellite since 2006. The first spaceborne CPR with Doppler capability will be launched in March 2023 aboard the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission.

Mean Doppler velocity can be seen as the mean frequency of a power spectrum (Doppler velocity) of the backscattered power. Given the mean Doppler velocity (mean frequency of the power spectrum) of the measured volume along the line of sight – the radial velocity. For vertical measurements, the Doppler velocities is the sum of terminal velocity of particles, caused by gravity force, and air motions within the measured volume. Terminal velocity contains the information about microphysical properties of cloud particles. In order to obtain the terminal velocity from the cloud radar observations, the influence of air motions that shift the spectrum have to be removed from the Doppler spectra, improving in this way the microphysics representativity. An approach to correct this shift is given by Kollias et al., improving the accuracy of the relation between the corrected Doppler velocity and the particle fall velocities.

The Doppler width, or Doppler spectrum width, is the standard deviation of the spectrum. Accordingly, small values stand for narrow spectra, while higher spectrum width corresponds to a bigger spreading of the hydrometeors over the velocity domain (frequency domain). Reasons for a higher width could be bi or multiple modal spectra. This means that the measured volume contains more than one hydrometeor population, which leads to two or more modes in the Doppler spectrum because of the different terminal velocities. A rapid change in Doppler width in combination with the mean Doppler velocity can also be used to separate two hydrometeor population. Since the air motion in the atmosphere affects the Doppler width, this parameter provides information about turbulence within the measured volume. Up and downdrafts slow down the terminal fall velocities and can decrease or increase the Doppler width. If the measurements are not done pointing to the zenith, the horizontal wind component influences the width as well. The knowledge of the actual wind components in the atmosphere can be used to correct the Doppler spectrum, so that the retrieved microphysical parameters can be improved and the uncertainties decreased. This parameter relates the location of the spectrum peak in respect to the mean spectrum value. Therefore, a positive skewness value indicates that the peak is located to the left with respect to the mean. A negative skewed spectrum has its peak on the right side with respect to the spectrum mean. A value around zero indicates a symmetric spectrum. In this way, the shape of a Doppler gives information on changes of cloud microphysics or of dynamical changes within the measured volume. The higher the elevation of the radar is, the higher are the dynamical influences on this parameter. Because wind shears lead to a broadening of the Doppler spectrum width, they can lead to rapid changes in skewness as well. To be able to relate the change in skewness of the Doppler spectrum, the Doppler width should be cross checked as well. If the radar measurements are done vertically, the skewness of the Doppler spectrum gives information about measured cloud microphysics. The horizontal wind within the measured volumes cause only a shift of the whole spectrum within the Doppler domain. This means that the spectrum is shifted along the Doppler velocity axis but it did not influence the broadening of the spectra. So the changes in skewness give information
about: and, currently, are being implemented in ground based and airborne cloud radars. These techniques enable advanced clutter filtering, discrimination between meteorological and non meteorological targets, and classification of atmospheric scatterers. that is one of the main problems in remote observations of mixed phase clouds. The assumed shape of ice crystals is considered to be the main source of errors in size and number concentration retrievals based on vertical combined lidar and radar observations. Furthermore, in the existing numerical weather prediction models the assumed shape defines the depositional growth rate of ice particles and the area mass terminal velocity relations of ice crystals. Thus, ice habit can lead to significant uncertainties. A number of different polarimetric configurations were evaluated in theoretical and experimental studies and are explained below. Most of the existing pulse cloud radars operate in the LDR mode. In this mode, a radar transmits a horizontally polarized radiation and receives horizontal and vertical components of the scattered radiation in co polarized and cross polarized channels, respectively. The ratio of the power in the cross polarized channel over the power in the co polarized channel, named as linear depolarization ratio, is the polarimetric variable obtained by cloud radars of this type. Often cloud radars have two receiving units,

Some cloud radars operate in the SLDR mode, that is a modification of traditional LDR mode. use pulse to pulse switching between horizontal and vertical polarization state of the transmitted wave. In addition to LDR, such systems are able to measure differential reflectivity (ZDR) and correlation coefficient (ρHV). The combined analysis of LDR, ZDR, and ρHV can be used not only for classification of ice particle habit but also for characterization of their orientations. CDR mode cloud radars transmit a circularly polarized wave and receive co polarized and cross polarized components. The output polarimetric variable is the so called circular depolarization ratio (CDR), and it is calculated as the ratio of cross polarized power over the co polarized power. In comparison with LDR, CDR is not affected by particles aligned in polarization plane,

As the cloud radars sample the atmosphere, they measure the backscatter signal produced by different hydrometeor types (cloud droplets, drizzle, rain drops, ice particles, snow, etc.) and non hydrometeorological targets. All these targets have different vertical velocities and shapes, and therefore the Doppler spectra and LDR can be used to distinguish between targets. In the figure below, an example of the MIRA 36 cloud radar measurements in Potenza is shown, where using the information given by the different parameters, an identification of targets can be done:

Liquid water clouds produce a signature in the reflectivity but not in the LDR, since the liquid droplets are almost spherical. Ice clouds are characterized by relatively high LDR signals due to their irregular shapes. Insects produce high LDR values and are usually within the Convective Boundary Layer (CBL), where up and downdrafts are observed continuously. The melting layer can be identified by an enhancement of the LDR, which is caused by irregular ice particles coated by liquid water during the phase transition. Rain is characterized by high reflectivity values, high falling velocities and a broadening of the spectra. Liquid layers within mixed phase clouds can be detected by slightly higher peak width values, in accordance to the higher turbulence within.

Pacific Northwest National Laboratory (PNNL) and Prosensing Inc. designed the Scanning ARM Cloud Radar (SACR) to monitor clouds overhead at various testing sites of the United States Department of Energy's atmospheric radiation measurement program. The radars operate continuously at these sites in Oklahoma, Alaska and the tropical western Pacific Ocean, and are designed to function for at least ten years with minimal staff oversight. The SACR s operate at a frequency of 35 and 94 GHz, being designated as KaSACR and WSACR respectively. Since the late 2000s, a meteorological 35.5 GHz Ka band commercial cloud radar (MIRA 36) designed by METEK GmbH in collaboration with the Institute for Radio Astronomy, Kharkov (Ukraine) is in the market. Nowadays, there are eleven systems monitoring the cloud properties continuously in different sites, most of them in Europe. Cloudnet, a network of stations for the continuous evaluation of cloud and aerosol profiles in operational NWP models, assimilates their data, as well as data acquired by other instruments in the various sites with this purpose. Outside of these networks, some research sites are also operating cloud radars. For example, at the Chilbolton Observatory (UK), two mm wavelength radars are operating
continuously at 3.2 and 9 mm for the study of insects migrations, while a 35 GHz cloud radar is operating in Cabauw (the Netherlands).

Location Band Frequency [GHz] Wavelength [mm] Type Location ARM Mobile Facility 1 Ka 35 8.6 Ka SACR Mobile ARM Mobile Facility 1 W 94 3.2 W SACR Mobile ARM Mobile Facility 2 Ka 35 8.6 Ka SACR Mobile Chilbolton, UK Ka 35 9 Copernicus Chilbolton, UK W 94 3.2 Galileo Cleveland, Ohio, USA Ka 35.5 8.6 MIRA36 Galway, Ireland Ka 35.5 8.6 MIRA36 Hamburg, Germany Ka 35.5 8.6 MIRA36 Iqaluit, Canada Ka 35.5 8.6 MIRA36 Juelich, Germany Ka 35.5 8.6 MIRA36 Kalsruhe, Germany Ka 35.5 8.6 MIRA36 Leipzig, Germany Ka 35.5 8.6 MIRA36 Lindenberg, Germany Ka 35.5 8.6 MIRA36 Munich, Germany Ka 35.5 8.6 MIRA36 North Slope of Alaska, Barrow, Alaska, USA Ka 35 8.6 Ka SACR North Slope of Alaska, Barrow, Alaska, USA W 94 3.2 W SACR Palaiseau, France W 95 3.16 BASTA Potenza, Italy Ka 35.5 8.6 MIRA36 Sodankyla, Finland Ka 35.5 8.6 MIRA36 Southern Great Plains, Oklahoma, USA Ka 35 8.6 Ka SACR Southern Great Plains, Oklahoma, USA W 94 3.2 W SACR Tropical Western Pacific Darwin, Australia Ka 35 8.6 Ka SACR Tropical Western Pacific Manus, Papua New Guinea Ka 35 8.6 Ka SACR Zugspitze, Germany Ka 35.5 8.6 MIRA36