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Andrew Ackerman

Publications and source records attributed to Andrew Ackerman.

6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Cloud-radiation Interactions and Cloud-climate Feedbacks from an Active-sensor Satellite Perspective

Clouds are ubiquitous in the troposphere. Their interactions with radiation may result in either a warming or a cooling of the Earth system and generate diverse climate feedbacks. The vertical structure of the radiative effects of clouds as well as the response of clouds to global warming (i.e., the cloud feedbacks) are inadequately constrained within the diversity of current climate models, which limits our ability to project the magnitude of future warming. In this chapter we show how relatively recent active-sensor spaceborne observations have narrowed constraints on cloud feedbacks. The value added beyond what can be retrieved from passive sensors is only just beginning to be exploited.

Cloud radiation↗
NASA NTRS2020

CMIP6 Historical Simulations (1850‐2014) with GISS‐E2.1

Simulations of the CMIP6 historical period 1850‐‐2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to forcing than their CMIP5 predecessors (GISS‐E2), but warm less during recent decades due to reduced total forcing. This forcing reduction is attributed to an increase in longwave opacity in pre‐industrial simulations, resulting in an atmosphere less sensitive to further increases in opacity that result from rising greenhouse gas concentrations. This demonstrates the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin.

NASA Goddard Institute for Space Studies (GISS) Ea↗
NASA NTRSDate not supplied

Evaluating and Constraining Models’ Stratocumulus and Cumulus Cloud Feedbacks in the Tropics using Satellite Observations to Reduce Uncertainties in Future Climate Projections

Low-cloud feedbacks are thought to be the greatest source of uncertainty in climate projections on the centennial scale. Past research has mainly focused on the global low-cloud feedback as a whole whereas only a few studies have examined separated contributions from the two main low cloud categories: stratocumulus (Sc) and shallow cumulus (Cu). Here we aim to evaluate and constrain Sc and Cu cloud feedbacks in models using satellite observations to ultimately reduce their contribution to the spread in equilibrium climate sensitivity. We utilize the Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD) recently developed by Cesana et al. (2019), which discriminates Sc from Cu clouds. This algorithm – based on cloud morphological characteristics at the orbital level – outperforms previous cloud-type classifications stemming from passive-sensor measurements. We investigate the observed relationship between the Sc and Cu cloud cover in tropical subsidence oceanic regions and their link to the primary low-cloud controlling factors (sea surface temperature, estimated inversion strength). To gain further insight into the Sc-Cu cloud partitioning, we explore the Sc-Cu relationship during the four meteorological seasons (DJF, MAM, JJA, SON) as well as on monthly timescale. We find a substantial negative correlation between the Sc and Cu cloud cover on annual, seasonal and monthly timescales. We finally evaluate how well climate models of the Coupled Model Intercomparison Project phase 5 (CMIP5) and phase 6 (CMIP6) agree with the observations. These results establish a framework to advance model parameterizations of the underlying physical processes driving the stratocumulus and shallow cumulus clouds (turbulence and convection).

Cloud feedbacks↗
NASA NTRSDate not supplied

The Impact of Dry Intrusions on Midlatitude Cold-Air Outbreak Cloud Transitions

Cold-air outbreaks (CAOs) form marine boundary layer (MBL) clouds that undergo rapid overcast-to-broken cloud regime transitions, initiated by substantial rain. CAOs are usually accompanied by dry intrusions (DIs) that subside as free-tropospheric (FT) air into the postfrontal sector of mid-latitude storms. For an exemplary cold-air outbreak in the NW Atlantic that showed faster transitions (corresponding to reduced extents of overcast clouds) closer to the low-pressure system, we posit that varying transitions are caused by an uneven meteorological pattern imposed by the prevailing DI. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MERRA2-based trajectories to show that postfrontal trajectories closer to the low-pressure system are uniquely favorable to rain formation (and, thus, cloud transitions) as they show (1) weaker FT subsidence rates, (2) greater FT humidity, (3) greater MBL windspeeds, and (4) a colder MBL as well as reduced lower-tropospheric stability. We present an updated conceptual view of postfrontal cloud formation that may guide future investigations.

Cold-air outbreaks↗
NASA NTRSDate not supplied

An LES Survey of Cold-Air Outbreaks Spanning ACTIVATE and COMBLE

Two recent field campaigns offer unique new opportunities to survey coupled aerosol and cloud processes operating within cold-air outbreaks (CAOs). NASA's 2019-2023 Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project provided airborne in situ and remote sensing observations in multiple CAOs off the central US Eastern Seaboard. Contemporaneously, DOE's 2019-2020 Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) provided continuous ground-based in situ and remote sensing measurements during hundreds of hours of CAO conditions at two sites flanking the Norwegian Sea. Here we highlight lessons learned from contrasting sets of aerosol-aware Lagrangian large-eddy simulation case studies derived from each campaign, as well as outstanding uncertainties. Cases simulated include all of the most extensively sampled CAO flights during ACTIVATE, and a wide range of CAO strengths and mesoscale structures during COMBLE. Each case study is also suitable for simulation with large-scale models in single-column model mode or with a limited-domain approach using periodic boundary conditions. We seek to address the central question: what microphysical process pathways control the Lagrangian evolution of surface and top-of-atmosphere radiative fluxes under ACTIVATE and COMBLE conditions? Many science team members, co-investigators, and collaborators will be gratefully acknowledged in association with their contributions to making this work possible.

cold-air outbreaks↗