Using synthetic EarthCARE Cloud Profiling Radar data to develop validation methodologies for ground-based cloud radar sites

Abstract

The value of permanent, multi-sensor surface-based observatories that collect continuous long-term observations for satellite L2 data products has grown significantly over the last 10-15 years. Examples of such established surface-based networks include the Aerosol, Clouds, and Trace Gases Research Infrastructure (ACTRIS) network, the US Department of Energy Atmospheric Radiation Measurements (ARM) observatories, and the recently established 94-GHz Miniature Network for EarthCARE Reference Measurements (FRM4Radar). The core of the work presented is the use of the developed transformation of suborbital to orbital radar data by Orbital-Radar. This simple L1 transformational operator converts L1 suborbital (ground-based or airborne) measurements to the EarthCARE Cloud Profiling Radar (CPR) L1 observations. The transformational operator ensures that the orbital to suborbital comparison accounts for differences in the sampling geometry, measurement uncertainty, and instrument sensitivity and simulates the impact of the surface echo. Furthermore, the operator simulates the EarthCARE characteristic reflectivity and Doppler velocity errors. Applying such a tool to long-time data sets allows to generate the optimal foundation for a statistical analysis of the EarthCARE CPR performance. Hence, the optimal sampling for CPR and ground-based data can be estimated, and the CPR detection of clouds and precipitation processes near the ground can be analyzed and evaluated. In addition, it shows how critical ground-based networks are and that they play an essential role in evaluating satellite measurements and products. Tools like Orbital-Radar may help evaluate future CPR satellite missions, expanding the L1 transformational operator to other spaceborne radar systems.