Preprints
https://doi.org/10.5194/egusphere-2023-170
https://doi.org/10.5194/egusphere-2023-170
10 Feb 2023
 | 10 Feb 2023
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Observed Process-level Constraints of Cloud and Precipitation Properties over the Southern Ocean for Earth System Model Evaluation

McKenna Wallace Stanford, Ann Fridlind, Israel Silber, Andrew Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald

Abstract. Over the remote Southern Ocean, cloud feedbacks contribute substantially to Earth system model (ESM) radiative biases. The evolution of low Southern Ocean clouds (cloud top heights < ~ 3 km) is strongly modulated by precipitation and/or evaporation, which act as the primary sink of cloud condensate. Constraining precipitation processes in ESMs requires robust observations suitable for process-level evaluations. A year-long subset (April 2016 – March 2017) of ground-based profiling instrumentation deployed during the Macquarie Island Cloud and Radiation Experiment (MICRE) field campaign (54.5° S, 158.9° E) combines a 95 GHz (W-band) Doppler cloud radar, two lidar ceilometers, and balloon-borne soundings to quantify the occurrence frequency of precipitation from liquid-phase cloud base. Liquid-based clouds at Macquarie Island precipitate ~ 70 % of the time, with deeper and colder clouds precipitating more frequently and at a higher intensity compared to thinner and warmer clouds. Supercooled cloud layers precipitate more readily than layers with cloud top temperatures > 0 °C, regardless of the geometric thickness of the layer, and also evaporate more frequently. We further demonstrate an approach to employ these observational constraints for evaluation of a 9-year GISS-ModelE3 ESM simulation. Model output is processed through the Earth Model Column Collaboratory (EMC2) radar and lidar instrument simulator with the same instrument specifications as those deployed during MICRE, therefore accounting for instrument sensitivities and ensuring a coherent comparison. Relative to MICRE observations, the ESM produces a smaller cloud occurrence frequency, smaller precipitation occurrence frequency, and greater sub-cloud evaporation. The lower precipitation occurrence frequency by the ESM relative to MICRE contrasts with numerous studies that suggest a ubiquitous bias by ESMs to precipitate too frequently over the SO when compared with satellite-based observations, likely owing to sensitivity limitations of space-borne instrumentation and different sampling methodologies for ground- versus space-based observations. Despite these deficiencies, the ESM reproduces the observed tendency for deeper and colder clouds to precipitate more frequently and at a higher intensity. The ESM also reproduces specific cloud regimes, including near-surface clouds that account for ~ 25 % of liquid-based clouds during MICRE and optically thin, non-precipitating clouds that account for ~ 27 % of clouds with bases higher than 250 m. We suggest that the demonstrated framework, which merges observations with appropriately constrained model output, is a valuable approach to evaluate processes responsible for cloud radiative feedbacks in ESMs.

McKenna Wallace Stanford et al.

Status: open (until 24 Mar 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

McKenna Wallace Stanford et al.

Data sets

Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program ceilometer data Atmospheric Radiation Measurement (ARM) user facility https://doi.org/10.5439/1181954

Australian Bureau of Meteorology (BoM) surface meteorology station data Atmospheric Radiation Measurement (ARM) user facility https://doi.org/10.5439/1597382

Australian Bureau of Meteorology (BoM) Bistatic Radar System for Atmospheric Studies (BASTA) radar data Australian Antarctic Division's Data Centre https://doi.org/10.26179/5d91836ca8fc3

University of Canterbury ceilometer data Australian Antarctic Division's Data Centre https://doi.org/10.26179/5d91835e2ccc3

Australian Bureau of Meteorology (BoM) Upper Air Soundings at Macquarie Island Australian Antarctic Division's Data Centre https://data.aad.gov.au/metadata/records/Antarctic_Meteorology

Model code and software

Earth Model Column Collaboratory (EMC2) Radar and Lidar Instrument Simulator Package Israel Silber and Robert Jackson https://github.com/columncolab/EMC2

McKenna Wallace Stanford et al.

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Short summary
Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.