A12C-07
Evaluation of cloud resolving model simulations of midlatitude cirrus with ARM and A-Train observations

Monday, 14 December 2015: 11:50
3008 (Moscone West)
Andreas D Muehlbauer, FM Global Research, Norwood, MA, United States
Abstract:
This paper evaluates cloud resolving model (CRM) and cloud system-resolving model (CSRM) simulations of a midlatitude cirrus case with comprehensive observations collected under the auspices of the Atmospheric Radiation Measurements (ARM) program and with spaceborne observations from the National Aeronautics and Space Administration (NASA) A-train satellites. Vertical profiles of temperature, relative humidity and wind speeds are reasonably well simulated by the CSRM and CRM but there are remaining biases in the temperature, wind speeds and relative humidity, which can be mitigated through nudging the model simulations toward the observed radiosonde profiles. Simulated vertical velocities are underestimated in all simulations except in the CRM simulations with grid spacings of 500m or finer, which suggests that turbulent vertical air motions in cirrus clouds need to be parameterized in GCMs and in CSRM simulations with horizontal grid spacings on the order of 1km. The simulated ice water content and ice number concentrations agree with the observations in the CSRM but are underestimated in the CRM simulations. The underestimation of ice number concentrations is consistent with the overestimation of radar reflectivity in the CRM simulations and suggests that the model produces too many large ice particles especially toward cloud base. Simulated cloud profiles are rather insensitive to perturbations in the initial conditions or the dimensionality of the model domain but the treatment of the forcing data has a considerable effect on the outcome of the model simulations. Despite considerable progress in observations and microphysical parameterizations, simulating the microphysical, macrophysical and radiative properties of cirrus remains challenging. Comparing model simulations with observations from multiple instruments and observational platforms is important for revealing model deficiencies and for providing rigorous benchmarks. However, there still is considerable need for reducing observational uncertainties and providing better observations especially for relative humidity and for the size distribution and chemical composition of aerosols in the upper troposphere.