Triple frequency radar facilities have received attention over the last 5-10 years and their number has increased in both ground-based and airborne platforms. The availability of triple frequency radar observations allows seamless coverage from weak non-precipitating clouds to tropical convection and offer additional constraints in the retrieval of the hydrometeor characteristic size and water content through the application of differential scattering and absorption techniques. These advantages are expected to influence the design of the Clouds, Convection and Precipitation (CCP) future mission that was recently identify as one of the priority missions in the latest NASA’s Decadal Survey. The CCP mission is designated to study the coupled cloud-precipitation state and its dynamics. As part of early studies related to the CCP mission the potential of a multi-frequency radar-based mission for targeting cloud and precipitation microphysics will be explored. Some of the advantages in multi-frequency radar observations from space can be exploited using the coincident observations from the CloudSat Cloud Profiling Radar and the NASA-JAXA Global Precipitation Measuring Dual Precipitation Radar epitomize the potential of space-borne multi-frequency radar observations of the same precipitating system (Figure 1). Two aspects of the multi-frequency approach are paramount.1) Complementarity: cm and mm-radars are effective in mapping different parts of the precipitating system because of their different sensitivities and ranges of signal attenuation. 2) Synergy: in the regions where all radars produce detectable signals they can be used synergistically in order to better retrieve cloud microphysical properties by exploiting the complex interplay between non-Rayleigh and attenuation effects.



In the first part of this paper the benefits and potentials of a triple-frequency Ku-Ka-W band radar approach for better constraining rain and ice microphysics will be discussed on a theoretical basis and then demonstrated for a stratiform case study extracted from the OLYMPEx/RADEX (Olympic Mountain Experiment/Radar Definition Experiment 2015) field campaign with simultaneous Ku-Ka-W band radar and in-situ observations collected from two aircrafts. A variational method enables the retrieval of the full precipitation profile above and below the melting layer, by combining the observations from the three radars and from microwave radiometers. Even with three radar frequencies, the retrieval of rain properties is challenging over land, where the path integrated attenuation is not available. Otherwise, retrieved mean volume diameters and water contents of both solid and liquid precipitation are in agreement with in-situ observations and the multi-frequency approach is effective in capturing different ice microphysical processes (e.g. aggregation vs riming).
In the second part the feasibility in terms of technology readiness level, mass, weight, power consumption and size of a Ku-Ka-W band radar will be discussed. In particular the critical
subsystems will be identified and assessed by trade-off and analysis.

Figure: CloudSat and GPM coincident overpass observations of a convective precipitation system developed over the Banda Sea in the Maluku Islands of Indonesia. Top row: CloudSat W-band reflectivity; second row: GPM Ka-band reflectivities for the high sensitivity (HS) scan; third row: GPM Ku-band reflectivity for the normal scan (NS). The dataset of coincident overpasses is from the GPM product 2B-CSATGPM from the NASA Precipitation Processing System developed by J. Turk, JPL.

Area D - Board 382

High resolution Doppler measurements of meteorological target such as clouds and precipitation from space present a substantial challenge. The moving satellite platform induces a Doppler width to the target returns leading to a rapid decorrelation; to avoid this decorrelation, the pulse separation must be short, but this poses a problem since only one pulse should be in the atmosphere at any one time. We describe a conically scanning spaceborne Dopplerized 94-GHz radar Earth science mission concept: Wind Velocity Radar Nephoscope (WIVERN) that has been proposed to ESA in response to the recent call for Earth Explorer missions. WIVERN aims to provide global measurements of in-cloud winds using the Doppler-shifted radar returns from hydrometeors.The conically scanning radar could provide wind data with daily revisits poleward of 50°, 50-km horizontal resolution, and approximately 1-km vertical resolution. A key element is the use of closely spaced pulse pairs one of which is H polarised the other V polarised, so that the targets do not have time to reshuffle, and, providing there is no significant cross-talk between the two returns, the high velocities associated with wind storms can be retrieved. This talk will outline the technical challenges and the techniques that are proposed to over-come these challenges and how these have been validated with observations from ground based and airborne polarisation Doppler radars. The potential difficulties are: cross-talk between the H and V returns due to depolarisation by meteorological targets or when the leading pulse hits the depolarising surface leading to a blind zone close to the ground; wind biases introduced by the satellite motion if there is non-uniform beam filling, and wind biases due to wind shear across the beam. In addition, the rotating antenna will detect the 5km/s sinusoidal variation of the component of the satellite motion that must be subtracted if winds are to be retrieved with the required accuracy of 1m/s. This implies that the pointing of the rotating antenna must be known to within 200 urad, that is to say one fifth of the 1 mrad radar beamwidth.

Area D - Board 383

Since the launch of NASA Global Precipitation Mission and continuous proliferation of cloud profiling sites equipped with multi-frequency radars, operated by e.g. DOE ARM or the European Research Infrastructure for the observation of Aerosol, Clouds, and Trace gases (ACTRIS), there is a renewed interest in deriving ice cloud and precipitation properties from multi-frequency radar observations. To develop a robust retrieval method, snow microphysical properties, such as particle size distribution and mass-dimensional relations, need to be parametrized. Additionally, these properties have to be linked to radar observables. Both steps present a challenge.
In this study we observations collocated observations of winter precipitation microphysics and multi-frequency radar observations to test precipitation retrieval algorithms and measurement concepts. The measurements were collected at SMEAR-II research station of University of Helsinki located in Hyytiala, Finland are being carried out since January 2014.
The studied retrieval methods are based on triple and dual-frequency radar observations, which also include dual-polarization and Doppler measurements, and collocated microwave radiometer measurements of LWP.

Area D - Board 384

Precipitation estimation data based on remote sensing data are very important in several contexts, such as water resources assessment, extreme events of floods, droughts and agricultural production. In this sense, very long drought periods affect not only the level of water of water sources, as well as the reservoirs of hydroelectric plants, impacting the urban supply and generation of electricity. The objective of this work was to analyze the behavior of a recent series of rainfall estimation data considering the different seasonal patterns in the Amazon Delta, investigating the effect of rainfall intensity in the region. The global precipitation data are derived from the combination of soil moisture estimates from the European Space Agency Climate Change Initiative (ESA CCI), called the SM2RAIN-CII, with a spatial resolution in grid of 0.25,° daily available, with a period of analysis between the years 1998 and 2015. The spatial patterns and temporal variability of precipitation were selected using the Expert Team on Climate Change Detection and Indices (ETCCDI) indicators, computed in annual series for the total rainfall amount (PRCPTOT), the simple daily intensity (SDII), the number of precipitation days (R1), the number of consecutive dry and wet days (CDD and CWD), and the number of heavy precipitating days (R20). The results showed that rainfall data from SM2RAIN-CCI are compatible with surface observations, with a seasonal pattern typical of the region. During the rainy season in the Amazon Delta, data spatialization tends to overestimate rainfall in areas with more than 2,700 mm and intense convective activity. There is a significant increase in rainfall in the climatic indicators, especially in PRCPTOT and R20 during the occurrence of precipitation mechanisms of La Niña and Atlantic dipole in the months of March, April and May. The occurrence of rainfall deficits in September, October and November were also caused by another climatic phenomenon known as El Niño, observed in the values of R1 and CDD. The ability of a reasonable accuracy in the cumulative rainfall of the SM2RAIN-CCI demonstrates the efficiency of the product in identify different seasonal patterns that are influenced by climatic mechanisms on the coastal region of the Amazon.

Area D - Board 385

Surface air-pressure is one of the most important parameters used in the Numerical Weather Prediction (NWP) models. These models are critical for weather forecasting and global surface air-pressure measurements will reduce uncertainties dramatically. There are limited numbers of in-situ measurements by weather stations for surface air pressure. The network of such stations is very heterogeneously distributed, and has been shrinking over the last decades, because of the high costs of installation and maintenance.
The prediction of weather and climate, on timescales ranging from hours to centuries, remains a key challenge for society. In a warming climate it is expected that the frequency and intensity of extreme weather events, capable of widespread devastation, will increase. A reversal of this trend is not foreseen in the short term and thus there is an urgent need for improved weather prediction capabilities that will enable associated risks and impact of extreme weather events to be reduced and, ideally, fully mitigated. Key to achieving this goal is the timely forecasting of related weather and climate driving parameters, of which pressure is a critically important feature. Regular, accurate and global-scale measurement of surface air-pressure presents a substantial technical challenge, which can only be achieved by remote sensing from space. In the previous ESA project, an assessment of the feasibility of a space-borne air pressure mission was completed. Future users of the data were asked to specify their requirements with regards to accuracy, spatial resolution and temporal availability of the measurements. Possible technologies such as lidar, passive remote sensing, radio occultation and radar were considered. The best technique was found to be the differential absorption radar that measures received signals either on the left wing or the right wing of the oxygen band. Retrieval of atmospheric pressure from satellite observations requires very accurate knowledge of the atmospheric mixing ratio of the spectral feature to be targeted. In practice, molecular oxygen offers the only viable candidate, since its mixing ratio is effectively constant over the full range of atmospheric conditions. A concept design of surface air-pressure radar sensor will be presented.

Area D - Board 386