Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes

Abstract. Cloud and precipitation processes are still a main source of uncertainties in numerical weather prediction and climate change projections. The Priority Programme “Polarimetric Radar Observations meet Atmospheric Modelling (PROM)”, funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, at present be provided by the recently installed dual-polarization C-band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly complex microphysical modules, considerable knowledge gaps still exist in the interpretation of the observations and in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to increase the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parameterizations of moist processes in atmospheric models. As an overview article of the inter-journal special issue “Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes”, this article outlines the knowledge achieved in PROM during the past 2 years and gives perspectives for the next 4 years.

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Overview: Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes

10.5194/acp-2021-346 ◽

2021 ◽

Author(s):

Silke Trömel ◽

Clemens Simmer ◽

Ulrich Blahak ◽

Armin Blanke ◽

Florian Ewald ◽

...

Keyword(s):

Weather Prediction ◽

Polarimetric Radar ◽

Atmospheric Models ◽

German Research Foundation ◽

Radar Observations ◽

Atmospheric Modelling ◽

Radar Polarimetry ◽

Radar Network ◽

Precipitation Processes ◽

National Networks

Abstract. Cloud and precipitation processes are still the main source of uncertainties in numerical weather prediction and climate change projections. The Priority Program "Polarimetric Radar Observations meet Atmospheric Modelling (PROM)", funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis, that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, nowadays be provided e.g. by the recently installed dual-polarization C band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information e.g. on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly higher moment microphysical modules, still considerable knowledge gaps exist in the interpretation of the observations and large uncertainties in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to intensify the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parametrizations of moist processes in atmospheric models. As an overview article of the inter-journal special issue "Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes", it outlines the knowledge achieved in PROM during the past two years and gives perspectives for the next four years.

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From model to radar variables: a new forward polarimetric radar operator for COSMO

Atmospheric Measurement Techniques ◽

10.5194/amt-11-3883-2018 ◽

2018 ◽

Vol 11 (7) ◽

pp. 3883-3916 ◽

Cited By ~ 6

Author(s):

Daniel Wolfensberger ◽

Alexis Berne

Keyword(s):

Phase Shift ◽

Solid Phase ◽

Weather Prediction ◽

Doppler Spectrum ◽

Polarimetric Radar ◽

Dual Frequency ◽

Differential Phase Shift ◽

Radar Observations ◽

Differential Phase ◽

Differential Reflectivity

Abstract. In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows estimation of the full Doppler spectrum, as well a melting scheme which allows representing the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational one-moment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

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The Life-Cycle of Cloud and Precipitation Microphysics in Radar Observation and Numerical Model

10.5194/egusphere-egu21-15328 ◽

2021 ◽

Author(s):

Gregor Möller ◽

Florian Ewald ◽

Silke Groß ◽

Martin Hagen ◽

Christoph Knote ◽

...

Keyword(s):

Prediction Models ◽

Model Simulation ◽

Weather Prediction ◽

Horizontal Resolution ◽

Polarimetric Radar ◽

Dual Frequency ◽

Microphysics Scheme ◽

Ka Band ◽

Radar Observations ◽

Conversion Rates

<p>The representation of microphysical processes in numerical weather prediction models remains a main source of uncertainty. To tackle this issue, we exploit the synergy of two polarimetric radars to provide novel observations of model microphysics parameterizations. In the framework of the IcePolCKa project (Investigation of the initiation of Convection and the Evolution of Precipitationusing simulatiOns and poLarimetric radar observations at C- and Ka-band) we use these observations to study the initiation of convection as well as the evolution of precipitation. At a distance of 23 km between the C-band PoldiRad radar of the German Aerospace Center (DLR) in Oberpfaffenhofen and the Ka-band Mira35 radar of the Ludwig-Maximilians-University of Munich (LMU), the two radar systems allow targeted observations and coordinated scan patterns. A second C-band radar located in Isen and operated by the German Weather Service (DWD) provides area coverage and larger spatial context. By tracking the precipitation movement, the dual-frequency and polarimetric radar observations allow us to characterize important microphysical parameters, such as predominant hydrometeor class or conversion rates between these classes over a significant fraction of the life time of a convective cell. A WRF (Weather Research and Forecasting Model) simulation setup has been established including a Europe-, a nested Germany- and a nested Munich- domain. The Munich domain covers the overlap area of our two radars Mira35 and Poldirad with a horizontal resolution of 400 m. For each of our measurement days we conduct a WRF hindcast simulation with differing microphysics schemes. To allow for a comparison between model world and observation space, we make use of the radar forward-simulator CR-SIM. The measurements so far include 240 coordinated scans of 36 different convective cells over 10 measurement days between end of April and mid July 2019 as well as 40 days of general dual-frequency volume scans between mid April and early October 2020. The performance of each microphysics scheme is analyzed through a comparison to our radar measurements on a statistical basis over all our measurements.</p>

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Polarimetric Radar Observations Meet Atmospheric Modelling

2018 19th International Radar Symposium (IRS) ◽

10.23919/irs.2018.8448121 ◽

2018 ◽

Cited By ~ 1

Author(s):

Silke Tromel ◽

Johannes Quaas ◽

Susanne Crewell ◽

Andreas Bott ◽

Clemens Simmer

Keyword(s):

Polarimetric Radar ◽

Radar Observations ◽

Atmospheric Modelling

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Gamma Drop Size Distribution Assumptions in Bulk Model Parameterizations and Radar Polarimetry and Their Impact on Polarimetric Radar Moments

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-18-0178.1 ◽

2019 ◽

Vol 58 (3) ◽

pp. 467-478 ◽

Cited By ~ 2

Author(s):

Katharina Schinagl ◽

Petra Friederichs ◽

Silke Trömel ◽

Clemens Simmer

Keyword(s):

Size Distribution ◽

Drop Size ◽

Weather Prediction ◽

Numerical Weather Prediction Model ◽

Drop Size Distribution ◽

Polarimetric Radar ◽

Radar Polarimetry ◽

Empirical Relations ◽

Rain Drop ◽

Bulk Model

AbstractA suitable formulation of the rain drop size distribution (DSD) is a prerequisite for a successful assimilation of radar polarimetric information on rain into a numerical weather prediction model. Popular DSD parameterizations in two-moment bulk microphysics schemes use relations between the so-called mean-mass diameter and the DSD shape parameter μ, in order to prevent overly strong size sorting in the models. In radar polarimetry constrained-gamma DSDs with empirical relations between the shape and scale parameter are commonly used. This study compares the different DSD formulations and highlights the differences. Synthetic polarimetric radar observations for X band (9.39 GHz) and S band (3 GHz) were calculated from the different DSDs using the T-matrix method. Depending on the constraint that is assumed for the DSDs, the polarimetric moments exhibit quite different dependencies on the mean diameter, which are particularly striking for differential reflectivity ZDR. To successfully assimilate observed polarimetric moments into atmospheric models, formulations—possibly more flexible than those investigated in this study—have to be found that sufficiently represent microphysical processes and at the same time are consistent with empirical relations derived from disdrometer and radar polarimetric measurements.

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From model to radar variables: a new forward polarimetric radar operator for COSMO

10.5194/amt-2017-427 ◽

2017 ◽

Author(s):

Daniel Wolfensberger ◽

Alexis Berne

Keyword(s):

Phase Shift ◽

Solid Phase ◽

Weather Prediction ◽

Doppler Spectrum ◽

Polarimetric Radar ◽

Dual Frequency ◽

Differential Phase Shift ◽

Radar Observations ◽

Differential Phase ◽

Differential Reflectivity

Abstract. In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows to estimate the full Doppler spectrum, as well a melting scheme which allows to represent the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational one-moment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

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What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

Atmosphere ◽

10.3390/atmos11040362 ◽

2020 ◽

Vol 11 (4) ◽

pp. 362 ◽

Cited By ~ 1

Author(s):

Alexander V. Ryzhkov ◽

Jeffrey Snyder ◽

Jacob T. Carlin ◽

Alexander Khain ◽

Mark Pinsky

Keyword(s):

Cloud Model ◽

Weather Prediction ◽

Primary Source ◽

Polarimetric Radar ◽

Microphysical Process ◽

Weather Radars ◽

Cloud Models ◽

Cloud Modeling ◽

Bin Microphysics ◽

The Impact

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

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Impacts of Polarimetric Radar Observations on Hydrologic Simulation

Journal of Hydrometeorology ◽

10.1175/2010jhm1218.1 ◽

2010 ◽

Vol 11 (3) ◽

pp. 781-796 ◽

Cited By ~ 22

Author(s):

Jonathan J. Gourley ◽

Scott E. Giangrande ◽

Yang Hong ◽

Zachary L. Flamig ◽

Terry Schuur ◽

...

Keyword(s):

Pearson Correlation ◽

Extreme Rainfall ◽

Rain Gauge ◽

Hydrologic Model ◽

Laboratory Research ◽

Model Parameters ◽

Polarimetric Radar ◽

Storm Events ◽

Hydrologic Simulation ◽

Radar Observations

Abstract Rainfall estimated from the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler [WSR-88D (KOUN)] was evaluated using a dense Micronet rain gauge network for nine events on the Ft. Cobb research watershed in Oklahoma. The operation of KOUN and its upgrade to dual polarization was completed by the National Severe Storms Laboratory. Storm events included an extreme rainfall case from Tropical Storm Erin that had a 100-yr return interval. Comparisons with collocated Micronet rain gauge measurements indicated all six rainfall algorithms that used polarimetric observations had lower root-mean-squared errors and higher Pearson correlation coefficients than the conventional algorithm that used reflectivity factor alone when considering all events combined. The reflectivity based relation R(Z) was the least biased with an event-combined normalized bias of −9%. The bias for R(Z), however, was found to vary significantly from case to case and as a function of rainfall intensity. This variability was attributed to different drop size distributions (DSDs) and the presence of hail. The synthetic polarimetric algorithm R(syn) had a large normalized bias of −31%, but this bias was found to be stationary. To evaluate whether polarimetric radar observations improve discharge simulation, recent advances in Markov Chain Monte Carlo simulation using the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) were used. This Bayesian approach infers the posterior probability density function of model parameters and output predictions, which allows us to quantify HL-RDHM uncertainty. Hydrologic simulations were compared to observed streamflow and also to simulations forced by rain gauge inputs. The hydrologic evaluation indicated that all polarimetric rainfall estimators outperformed the conventional R(Z) algorithm, but only after their long-term biases were identified and corrected.

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