Profiling optimal-Estimates for RaIn-CLoud Efficiency Study (PERICLES)

Lead Research Organisation: University of Leicester
Department Name: Physics and Astronomy


Precipitation is unanimously recognized as one of the central variables of the global water and energy cycle, mainly because of its direct significance for the availability of water for human beings, agriculture and life on Earth in general, but also because of its impact on the energy budget and the atmospheric circulation through the associated latent heat release. Precipitation processes play a decisive role in controlling and thus predicting both weather phenomena and climate evolution in numerical weather prediction and general circulation models. Despite the importance of water to all creatures on Earth and to the Earth system as a whole, the life cycle of clouds and precipitation is not well understood; a seemingly simple process like the rapid formation of warm rain is still puzzling, and remains far from having a community-consensus explanation or model. The complexity of the microphysical processes underpinning the cloud evolution into the rain process represents the major obstacle for a considerable leap forward in this field and urgently calls for an effort towards combining modeling and observations. While the temporal and spatial scales of both Large-Eddy Simulation and Cloud Resolving Models are now suitable for studying cloud lifecycles, remote sensing observations (the only practically possible to look at such phenomena) have always suffered by the uncertainties deriving from ill-posed inversion problems. For instance the radar reflectivity signal is by definition strongly dependent on the drop size distribution of the scatterers, e.g., raindrops, in the beam volume and its interpretation is therefore related to the microphysical processes responsible for the formation of drop size distributions and their evolution. A unique deployment (to be completed by end of 2010) of multi-wavelength scanning radar with radiometric mode at all ARM facilities will provide unprecedented independent observations which should narrow down the uncertainties in the retrieval process and provide detailed observations of all phases of cloud evolution, from initiation, to development of updrafts and downdrafts, to hydrometeor evolution in time and space, to partitioning of condensate into precipitation and outflow anvils. We propose to take advantage of this upcoming opportunity by developing an optimal estimation approach capable of integrating different sensors in a consistent physical way. We will combine active (radar reflectivity) and passive (brightness temperatures) measurements because both yield different kinds of cloud microphysics information throughout the vertical extension: cloud and weather radars allow to range-resolve cloud structure, whereas passive microwave signals contain information about along-sight integrated water/ice contents. Our proposed technique combines measurements (and their error characteristics) with a priori information (and knowledge about its representativeness) into an optimal estimation framework to provide the atmospheric state together with uncertainty estimates. In order to optimally exploit the information content of remote sensing observations a first guess of the atmospheric state is iterated through the forward model - connecting atmospheric state with the measurement - up to a point where measurements and a priori information best match the retrieved atmospheric state. The ultimate product of the retrieval is represented by profiles of cloud and precipitation water content for the observed atmospheric columns, which will be extensively validated by independent methodologies during the MC3E campaign, planned for 2011 at the Oklahoma Southern Great Plain site. This cutting-edge product will help in developing, evaluating, and ultimately improving parameterization of cloud-precipitation processes in numerical models. As a test bed, a detailed cloud resolving model study oriented at the evaluation of different microphysical packages will be conducted in coincidence with MC3E.
Description A significant achievement is the development of a proper signal processing of the Atmospheric Radiation Measurement (ARM ) wind profilers for providing high quality precipitation measurements (Tridon et al., 2013b). These centimetre wavelength radar observations are well suited for the observation of intense rainfall and therefore complement the traditional ARM radar observations to provide a holistic view of the water cycle over the ARM sites, from clouds to intense rain, including cloud to light rain transition. The proposed processing is now part of an operational ARM product currently under evaluation before it provides continuous observations at every ARM sites.
Cloud and rain water content partitioning, one of the grant objectives, has not been met and is currently impracticable because lack of appropriate radiometer measurements following the failure of the ADMIRARI instrument during the MC3E field campaign. Instead, a focus has been made on the characterisation of rain water thanks to advanced multi-wavelength radar Doppler spectra observations. A novel technique that enables to improve our understanding of cloud radar measurements by disentangling Mie and attenuation effects has been proposed and has potential for a wide range of precipitation observations, including drizzling stratocumulus and snow observations (Tridon et al., 2013a).
The same technique has been proposed for cutting-edge G-band frequency radars (Battaglia et al., 2014). It also paves the way towards the resolution of a longstanding deadlock of rain radar science, i.e. the retrieval of rain drop size distribution by removing the influence of various air state variables on the shape of radar Doppler spectra (Tridon et al, under submission). The full exploitation of the data provided by this technique (study of rain variability and its vertical evolution, characterisation of rain microphysical processes in conjunction with detailed modelling of precipitation) is believed to last several years and will be the object of a future NERC or ARM grant application. Our poject has certainly laid the foundation for a seamless characterization of precipitation processes (from low to high rain rate) by multi-frequency Doppler remote sensing instruments.
Exploitation Route The full exploitation of the rain drop size distribution retrievals technique (study of rain variability and its vertical evolution, characterisation of rain microphysical processes) will provide invaluable information for modelling studies of precipitation microphysics and in turn, for weather prediction or climate modelling.
Sectors Aerospace, Defence and Marine,Environment

Description The findings made during this project improve the interpretation of precipitation measurements with ground-based radars and will provide improved understanding of precipitation processes for modelling studies of precipitation microphysics and, in cascade, for weather prediction and climate modelling.
First Year Of Impact 2010
Sector Aerospace, Defence and Marine,Environment
Impact Types Cultural

Description ESA ITT Multifrequency radar instrument study
Amount € 300,000 (EUR)
Organisation ESA - ESTEC 
Sector Public
Country Netherlands
Start 04/2017 
End 10/2018
Description Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation
Amount $750,000 (USD)
Organisation Government of the United States of America 
Sector Public
Country United States
Start 09/2017 
End 09/2020
Title Optimal Estimation retrieval for multi-wavelength radar/radiometer 
Description This is an optimal estimation methodology to retrieve profile of hydrometeors from radar reflectivity profiles derived from space-borne and airborne radars 
Type Of Material Improvements to research infrastructure 
Year Produced 2014 
Provided To Others? Yes  
Impact This retrieval method should be integrated for deriving Level2 NASA-GPM product and it is currently applied to measurements acquired by the NASA-DC8 aircraft 
Title Optimal estimation for dual-frequency Doppler radars 
Description A novel technique based on Ka-W band dual-wavelength Doppler spectra has been developed for the simultaneous retrieval of binned rain drop size distributions (DSD) and air state parameters like vertical wind and air broadening caused by turbulence and wind shear 
Type Of Material Improvements to research infrastructure 
Year Produced 2016 
Provided To Others? Yes  
Impact The technique will be applied to some of the US-DOE ARM sites to produce rainfall products 
Title Spatio-temporal variability of drop size distribution 
Description This database provides the temporal variability of drop size distributions profiles over ARM sites equipped with dual frequency Doppler radars 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
Impact The characterization of the spatio-temporal variability of the drop size distribution will help in refining satellite rainfall retrievals. This database has already been used to validate an assimilation method for the study of drop size distribution (Mercier, F., Chazottes, A., Barthès, L., and Mallet, C.: 4-D-VAR assimilation of disdrometer data and radar spectral reflectivities for raindrop size distribution and vertical wind retrievals, Atmos. Meas. Tech., 9, 3145-3163, doi:10.5194/amt-9-3145-2016, 2016) 
Description Clermont University (France) 
Organisation Blaise Pascal University
Department Laboratory of Physical Meteorology
Country France 
Sector Academic/University 
PI Contribution We provided retrievals of the vertical variability of rain microphysical parameters for a squall line observed over Oklahoma.
Collaborator Contribution They ran WRF simulations of the case study and performed sensitivity studies on the parametrization of rain microphysics in order to explain discrepancies with observations.
Impact The intercomparison of rain properties shows that the most used microphysical schemes of the WRF model can not reproduce observations. A paper is in preparation.
Start Year 2016
Description StonyBrook and ARM collaborators 
Organisation Stony Brook University
Department School of Marine and Atmospheric Sciences
Country United States 
Sector Academic/University 
PI Contribution We have been involved in analysing ARM datasets of multifrequency Doppler observations
Collaborator Contribution They have provided expertise in the quality control and calibration of radar data and their own retrieval
Impact Tridon F. and Battaglia, A., P. Kollias and E. Luke, Rain retrieval from dual-frequency radar Doppler spectra: validation and potential for a midlatitude precipitating case study, 2017, QJRMS, doi:10.1002/qj.3010 Kneifel, S., Kollias, P., Battaglia, A., Leinonen, J., Maahn, M., Kalesse, H., Tridon, F., First observations of triple-frequency radar Doppler spectra in snowfall: Interpretation and applications, Geophys. Res. Lett., 2016, 43, doi: 10.1002/2015GL067618. 49. F Tridon, A Battaglia, Dualfrequency radar Doppler spectral retrieval of rain drop size distributions and entangled dynamics variables, Journal of Geophysical Research: Atmospheres, 10.1002/2014JD023023
Start Year 2014