Oliktok Point Site Science: Development of Advanced Observational Perspectives to Aid Model Evaluation
Poster PDF
Authors
Maximilian Maahn — Leipzig University
Gijs de Boer — University of Colorado
Jessie Creamean — Colorado State University
Christopher J Cox — Cooperative Institute for Research in Environmental Science
Sergey Matrosov — University of Colorado
Allison C. McComiskey — Brookhaven National Laboratory
Matthew Shupe — University of Colorado
Amy Solomon — University of Colorado/NOAA- Earth System Research Laboratory
David D. Turner — NOAA- Global Systems Laboratory
Christopher R Williams — University of Colorado, Boulder
Category
High-latitude clouds and aerosols
Description
Here, we give an overview of the model evaluation and data product development activities in the Oliktok Point Science Team.
Model evaluation efforts for Oliktok Point include both long-term and case-study periods. For example, Unmanned Aerial Systems (UAS) measurements collected in October 2016 as part of the ERASMUS and ICARUS campaigns are being used to evaluate the simulation of sea ice freeze up in a fully-coupled sea ice forecast model operated by NOAA’s Physical Sciences Division. Additionally, measurements from the site and its operational instrumentation are being used to evaluate the NOAA Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) operational weather-forecasting models.
With respect to data product development, the ShupeTurner multi-sensor cloud microphysics retrieval has been applied to Oliktok observations, harnessing phase specific signatures from multiple instruments to first identify the cloud phase, then applying a suite of microphysics retrievals based on different sensors. First-order results on cloud phase type occurrence and microphysical properties will be presented. Moreover, a novel method to retrieve the mean cloud liquid temperature using measurements from three-channel (24, 30 and 90 GHz) microwave radiometer measurements is evaluated. The new method has a broad applicability since it requires neither the use of active sensors to locate the boundaries of cloud layers nor information on the temperature profiles. Further, we present a study for identifying and removing ground clutter in KAZR Doppler velocity spectra before estimating radar moments (including velocity skewness, and velocity kurtosis) for multiple peaks identified in the spectra. This clutter removal algorithm was needed because the default ARM processing algorithms could not identify and remove the clutter before estimating radar moments. To improve the velocity skewness estimates, decluttered spectra collected over 15-s intervals were shifted to a common velocity and then averaged. Finally, data from the scanning KaSACR cloud radar is used to investigate the spatial variability of clouds in the Oliktok Point region and the impact of surface type (ocean, sea ice, bare soil, and snow) on cloud formation.
