Role of updraft velocity in temporal variability of global cloud hydrometeor number

Abstract

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.global models | clouds | vertical velocity | sensitivity | attribution C loud radiative forcing remains one of the largest sources of uncertainty in the overall terrestrial radiative budget (1). Incloud phase partitioning, or the fraction of liquid versus ice hydrometeors, can be as important as cloud cover in the calculation of cloud radiative forcing (2). Cloud long-wave emissivity depends on cloud water path and hydrometeor sizes, along with cloud height and temperature. Cloud short-wave albedo also depends on particle size, because more and smaller hydrometeors yield a higher optical depth for the same water path (1). Global climate models (GCMs) predict a diversity of liquid and ice water paths (3), as well as cloud hydrometeor sizes, and the treatment of initial hydrometeor formation, i.e., droplet activation or ice nucleation, contributes to this spread for all cloud types (4, 5).The available supersaturation of a cloudy air parcel determines how many hydrometeors can form therein. Supersaturation strongly depends on aerosol and dynamical parameters. Updraft, or vertical velocity, is especially important because it is the driver of supersaturation generation, owing to the induced expansion cooling during air mass ascent. Aerosol particle surfaces upon which vapor can condense or deposit, called cloud condensation nuclei (CCN) or ice nucleating particles (INP), respectively, act as a sink of supersaturation. The balance between supersaturation generation and loss eventually determines the number of hydrometeors that form in the cloud. As part of the increasing trend to track both cloud hydrometeor mass and number density in GCM cloud modules (6-9), most state o...

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