WIVERN: An ESA Earth Explorer Concept to Map Global in-Cloud Winds, Precipitation and Cloud Properties

The main objective of the proposed WIVERN mission is to provide global line-of-sight in-cloud winds in real time that can be assimilated into numerical weather prediction (NWP) models to improve weather forecasts. This will be achieved by a conically scanning dual polarisation Doppler 94 GHz radar with an 800 km wide ground track in a sun-synchronous polar orbit to provide daily visits poleward of 50°. According to the World Meteorological Organization (WMO), wind-storms are by far the largest contributor to economic losses caused by weather related hazards, resulting in approximately 500 billion USD (adjusted to 2011) of global damage over the last decade. A unique advantage of WIVERN is its ability to measure winds within active weather systems that are filled with thick cloud where there are currently very few wind observations, especially in tropical cyclones and hurricanes. These in-clouds winds will complement the predominantly clear air winds from the AEOLUS wind lidar launched in August 2018 which have been shown to have a significant impact in reducing forecast errors. A subsidiary objective of WIVERN is to provide high resolution reflectivity profiles of rain, snow and ice water content to validate and improve parameterisation schemes in NWP and climate models

Synergies and complementarities of CloudSat-CALIPSO snow observations

[1] Four years (2007–2010) of colocated 94 GHz CloudSat radar reflectivities and 532 nm CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscattering coefficients are used to globally characterize snow-precipitating clouds. CALIOP is particularly useful for the detection of mixed and supercooled liquid water (SLW) layers. Liquid layers are common in snow precipitating clouds: overall/over sea/over land 49%/57%/33% of the snowy profiles present SLW or mixed-phase layers. The spatial and seasonal dependencies of our results—with snowing clouds more likely to be associated with mixed phase during summer periods—are related to snow layer top temperatures. SLW occurs within the majority (>80%) of snow-precipitating clouds with cloud tops warmer than 250 K, and is present 50% of the time when the snow-layer top temperature is about 240 K. There is a marked tendency for such layers to occur close to the top of the snow-precipitating layer (75% of the times within 500 m). Both instruments can be synergetically used for profiling ice-phase-only snow, especially for light snow (Z<0 dBZ, S<0.16 mm/h) when CALIOP is capable of penetrating, on average, more than half of the snow layer depth. These results have profound impact for deepening our understanding of ice nucleation and snow growth processes, for improving active and passive snow remote sensing techniques, and for planning snow-precipitation missions

WIVERN: An ESA Earth Explorer Concept to Map Global in-Cloud Winds, Precipitation and Cloud Properties

The main objective of the proposed WIVERN mission is to provide global line-of-sight in-cloud winds in real time that can be assimilated into numerical weather prediction (NWP) models to improve weather forecasts. This will be achieved by a conically scanning dual polarisation Doppler 94 GHz radar with an 800 km wide ground track in a sun-synchronous polar orbit to provide daily visits poleward of 50°. According to the World Meteorological Organization (WMO), wind-storms are by far the largest contributor to economic losses caused by weather related hazards, resulting in approximately 500 billion USD (adjusted to 2011) of global damage over the last decade. A unique advantage of WIVERN is its ability to measure winds within active weather systems that are filled with thick cloud where there are currently very few wind observations, especially in tropical cyclones and hurricanes. These in-clouds winds will complement the predominantly clear air winds from the AEOLUS wind lidar launched in August 2018 which have been shown to have a significant impact in reducing forecast errors. A subsidiary objective of WIVERN is to provide high resolution reflectivity profiles of rain, snow and ice water content to validate and improve parameterisation schemes in NWP and climate models

The retrieval of ice-cloud properties from cloud radar and lidar synergy

Clouds are an important component of the earth's climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L'Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE'98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements

The characterization of ice cloud properties from Doppler radar measurements

The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology

Multifrequency radar observations collected in Southern France during HyMeX-SOPI

An ambitious radar deployment to collect high-quality observations of heavy precipitation systems developing over and in the vicinity of a coastal mountain chain is discussed.Geoscience and Remote SensingCivil Engineering and Geoscience