Polarimetric Radar Observations meet Atmospheric Modelling (PROM) []

Brings together scientists contributing with new approaches to improve the monitoring, understanding, nowcasting, and prediction of precipitation processes.

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In the PROM sub-project CORSIPP, scientists from the University of Leipzig are exploring the orographically influenced riming of snow particles, the associated secondary ice production and its effects on precipitation rates.

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The last PROM all-hands meeting took place in Kiel on 17-19 July 2023.

Doppler spectra derived from new operational C-band birdbath scan indicating simultaneously occurring fast-falling rimed snow (mode 1) and slower-falling more pristine snow particles (mode 2).

First TRIPEx-pol measurement campaign combining triple-frequency radar, Doppler spectra, and polarimetry took place in winter 2018/19 in Jülich close to Cologne.

In addition to the dominant hydrometeor type, polarimetry allows to derive hydrometeor partitioning ratios, defined as the relative mass contribution of a specific hydrometeor type.

Colocated radar and airborne in-situ measurements enable us to determine the accuracy of polarimetric microphysical retrievals. Recently developed ice water content retrievals show high correlation (0.96) and low RMSE=0.19g/m³.

Surface pressure tendency in nature run (left), after assimilation of radial wind and radar reflectivity with LETKF (middle) and with new integrated mass-flux adjustment filter (right).

Radiation diagram (3D) and cross-polar discrimination (projected) of a 4 by 4 sub-array tile of the forerunner phased-array weather radar prototype. Simulated (left) and measured results (right) at 45° scan angle.

Ice (top) and snow contributions (bottom) to Quasi-Vertical-Profiles of reflectivity derived from BoXPol measurements assuming an exponential distribution.

Simulated (left) and observed (right) cross-sections of differential reflectivity (ZDR) for a summertime convective storm on 5 July 2015.

Combined observations from C-band and Ka-band radars (POLDIRAD and miraMACS) allow to constrain the shape and size of aggregating snow particles.

Retrievals of riming based on vertically-pointing 94 GHz cloud radar Doppler spectra observations and 35 GHz SLDR observations during PICNICC in Punta Arenas, Sep 11, 2019.

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Polarimetric Radar Observations meet Atmospheric Modelling (PROM) –
Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes

Cloud and precipitation processes are the main source of uncertainties in weather prediction and climate change projections since decades. A major part of these uncertainties can be attributed to missing observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. The whole atmosphere over Germany is since recently monitored by 17 state-of-the-art polarimetric Doppler weather radars, which provide every five minutes 3D information on the liquid and frozen precipitating particles and their movements on a sub-kilometer resolution, which is also approached by the atmospheric models for weather prediction and climate studies. Data assimilation merges observations and models for state estimation as a requisite for prediction and can be considered as a smart interpolation between observations while exploiting the physical consistency of atmospheric models as mathematical constraints. However, considerable knowledge gaps exist both in radar polarimetry and atmospheric models, which impede the full exploitation of the triangle radar polarimetry – atmospheric models – data assimilation and call for a coordinated interdisciplinary effort. The priority programme will exploit the synergy of the new observations and state-of-the-art atmospheric models to better understand moist processes in the atmosphere, and to improve their representation in climate- and weather prediction models. The programme will extend our scientific understanding at the verges of the three disciplines for better predictions of precipitating cloud systems by addressing the following objectives:

Objective 1: Exploitation of radar polarimetry for quantitative process detection in precipitating clouds and for model evaluation

Objective 2: Improvement of cloud and precipitation schemes in atmospheric models based on process fingerprints detectable in polarimetric observations

Objective 3: Monitoring of the energy budget evolution due to phase changes in the cloudy, precipitating atmosphere for a better understanding of its dynamics

Objective 4: Generation of precipitation system analyses by assimilation of polarimetric radar observations into atmospheric models for weather forecasting