Virtual observatory using the Cloud-Resolving Model Radar Simulator (CR-SIM)
Oue, Mariko — Stony Brook University
Kollias, Pavlos — Stony Brook University
Area of research:
Ground-based observatories offer an integrated view of cloud and precipitation systems complementary to that available from satellites with excellent vertical resolution, especially in the boundary layer, along with an accompanying description of atmosphere. The ARM observatories, for example, offer observations from distributed networks of profiling and scanning radars, lidars, and radiometers. This paper introduces the use of CR-SIM to address the following questions: 1) How do we best compare numerical model output with data products developed using multiple sensors with different capabilities; and 2) how do we best quantify the measurement uncertainty introduced by the observational strategy?
CR-SIM, capable of multi-sensor simulations from model output including multi-wavelength radars and lidars, allows the simulation of sophisticated data products such as remotely sensed cloud locations and multi-radar wind retrievals. Application of CR-SIM to high-resolution model output allows for direct comparison with observations, while considering microphysical parameterizations and observation strategies, to quantify uncertainties in retrievals and observations and optimize observation sampling strategies. These applications lead to improved understanding of the representative error of the atmospheric model simulations.
Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. One challenge is how to design strategies to best use these observations to understand these properties and evaluate atmospheric models. We developed the Cloud-resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud-resolving models to emulate multi-wavelength, zenith-pointing, and scanning radar observables as well as multi-sensor products. CR-SIM allows direct comparison between the model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical scheme used in the model. The applications of CR-SIM as a virtual observatory operator enable a consistent comparison between model results and observations that accounts for observation limitations. The methodology is valuable to evaluate the microphysics and dynamics in the model, quantify uncertainties in observation-based retrievals such as remotely sensed cloud locations and multi-Doppler radar-based wind field, and optimize radar and lidar sampling strategies. These applications lead to a better interpretation and understanding of the representativeness errors due to the sampling limitations of the ground-based measurements. CR-SIM is licensed under the GNU GPL package and both the software and user guide are publicly available to the scientific community, allowing for interactive improvement of the code.