Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5+-0.5 Wm-2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcings with estimates of anthropogenic Ta and satellite-retrieved Nd - Ta regression slopes, respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of -0.4+-0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7+-0.5 Wm-2, with a total estimate of -1.2+-0.4 Wm-2.

Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2017GL076101

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations

One of the most successful demonstrations of an integrated approach to observe Earth from multiple perspectives is the A-Train satellite constellation. The science enabled by this constellation flourished with the introduction of the two active sensors carried by the National Aeronautics and Space Administration (NASA) CloudSat and the NASA–Centre National d’Etudes Spatiales (CNES) Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites that were launched together on 28 April 2006. These two missions have provided a 10-yr demonstration of coordinated formation flying that made it possible to develop integrated products and that offered new insights into key atmospheric processes. The progress achieved over this decade of observations, summarized in this paper, clearly demonstrate the fundamental importance of the vertical structure of clouds and aerosol for understanding the influences of the larger-scale atmospheric circulation on aerosol, the hydrological cycle, t...

/pdf/cloudsat-and-calipso-within-the-a-train-ten-years-of-3jt7ucf83b.pdf

CloudSat and CALIPSO within the A-Train: Ten Years of Actively Observing the Earth System

https://backend.orbit.dtu.dk/ws/files/247661618/1_s2.0_S0273117721000594_main.pdf

Altimetry for the future: building on 25 years of progress

Observations taken over the last few decades indicate that dramatic changes are occurring in the ArcticBoreal Zone (ABZ), which are having significant impacts on ABZ inhabitants, infrastructure, flora and fauna, and economies. While suitable for detecting overall change, the current capability is inadequate for systematic monitoring and for improving processbased and largescale understanding of the integrated components of the ABZ, which includes the cryosphere, biosphere, hydrosphere, and atmosphere. Such knowledge will lead to improvements in Earth system models, enabling more accurate prediction of future changes and development of informed adaptation and mitigation strategies. In Duncan et al. (2020), we review the strengths and limitations of current spacebased observational capabilities for several important ABZ components and make recommendations for improving upon these current capabilities. We recommend an interdisciplinary and stepwise approach to develop a comprehensive ABZ Observing Network (ABZON), beginning with an initial focus on observing networks designed to gain processbased understanding for individual ABZ components and systems that can then serve as the building blocks for a comprehensive ABZON.

/pdf/space-based-observations-for-understanding-changes-in-the-3pkz1zm11w.pdf

Space-Based Observations for Understanding Changes in the Arctic-Boreal Zone

https://hal.archives-ouvertes.fr/hal-01491811/document

David Halpern

Papers

Observation and integrated Earth-system science: A roadmap for 2016–2025