| Paper: | FR-A2.5 |
| Session: | Atmospheric Applications of Radiometry II |
| Time: | Friday, March 30, 12:00 - 12:20 |
| Presentation: |
Oral
|
| Topic: |
Clouds and precipitation: |
| Title: |
Simulation and cross validation of GPM space-born radar and radiometer observations using ground-based radar and numerical weather model |
| Authors: |
Chandrasekar Venkatachalam; Colorado State University | | |
| | Chandrasekar Radhakrishnan; Colorado State University | | |
| | Minda Le; Colorado State University | | |
| Abstract: |
The Global Precipitation Measurement (GPM) mission is an international program to advance the understanding of the Earth's water and energy cycle. The GPM core spacecraft is carrying a Dual-frequency Precipitation Radar (DPR) and a Global Precipitation Measurement (GPM) Microwave Imager (GMI). Also, the Core Spacecraft serves as a calibration standard for other satellites in the GPM constellation. The GMI radiometer consists of thirteen microwave channels ranging in frequency from 10 GHz to 183 GHz. The DPR consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR).
The primary objective of this study is to simulate the GMI and DPR observations for a convective storm over Dallas Fort Worth (DFW) area, that is simultaneously observed by the DFW ground radar network. The GPM radar is sensitive to the precipitation, whereas the radiometric observations are also sensitive to the non-precipitating constituents such as water vapor and cloud water. The Weather Research and Forecasting (WRF) model is used to simulate the storm to bring consistency between the space borned radar ground-based radar and radiometer to complete the picture. The ground-based polarimetric radar reflectivity and radial velocity data are assimilated into WRF to improve the space-time specificity of the model simulation. Radiance observations are estimated as brightness temperatures (TBs) at the GMI frequencies using a radiative transfer model (RTM). The observed reflectivity and radial velocity data from both KFWS (NEXRAD) and CASA network of radars are assimilated in every 5 minutes in WRF model. CSU hydrometeor classification algorithm is used to classify the hydrometers over storm with dual-polarimetric radar variables. Similarly, the profile classification module results from GPM DPR is used to accurately delineate the top and bottom of the melting layer in the storm. The water content of corresponding hydrometers are estimated and assimilated in WRF model. The vertical profiles from WRF after assimilation is used to simulate the GPM observations.
This research is primarily focused on completing the understanding of the constituents of the storm that is observed partly by the three different instrument set, and the model is brought in to provide the common basic for physical consistency or validation. This study also investigates the impact of assimilating high-resolution ground-based dual-polarimetric radars data in the reduction of uncertainties in the WRF simulation in the context of completing the picture between radar and radiometric inferences. |
