Climate processes: publications

Quantification of Carbon Sequestration in Urban Forests

ArXiv 2106.00182 (2021)

Authors:

Levente J Klein, Wang Zhou, Conrad M Albrecht

AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements

Atmospheric Chemistry and Physics Copernicus Publications 21:9 (2021) 6895-6917

Authors:

Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, Philip Stier

Abstract:

Global measurements of absorbing aerosol optical depth (AAOD) are scarce and mostly provided by the ground network AERONET (AErosol RObotic NETwork). In recent years, several satellite products of AAOD have been developed. This study's primary aim is to establish the usefulness of these datasets for AEROCOM (Aerosol Comparisons between Observations and Models) model evaluation with a focus on the years 2006, 2008 and 2010. The satellite products are super-observations consisting of min aggregated retrievals.

This study consists of two papers, the current one that deals with the assessment of satellite observations and a second paper (Schutgens et al., 2021) that deals with the evaluation of models using those satellite data. In particular, the current paper details an evaluation with AERONET observations from the sparse AERONET network as well as a global intercomparison of satellite datasets, with a focus on how minimum AOD (aerosol optical depth) thresholds and temporal averaging may improve agreement between satellite observations.

All satellite datasets are shown to have reasonable skill for AAOD (three out of four datasets show correlations with AERONET in excess of 0.6) but less skill for SSA (single-scattering albedo; only one out of four datasets shows correlations with AERONET in excess of 0.6). In comparison, satellite AOD shows correlations from 0.72 to 0.88 against the same AERONET dataset. However, we show that performance vs. AERONET and inter-satellite agreements for SSA improve significantly at higher AOD. Temporal averaging also improves agreements between satellite datasets. Nevertheless multi-annual averages still show systematic differences, even at high AOD. In particular, we show that two POLDER (Polarization and Directionality of the Earth's Reflectances) products appear to have a systematic SSA difference over land of ∼0.04, independent of AOD. Identifying the cause of this bias offers the possibility of substantially improving current datasets.

We also provide evidence that suggests that evaluation with AERONET observations leads to an underestimate of true biases in satellite SSA.

In the second part of this study we show that, notwithstanding these biases in satellite AAOD and SSA, the datasets allow meaningful evaluation of AEROCOM models.

Climate Modelling in Low-Precision: Effects of both Deterministic & Stochastic Rounding

ArXiv 2104.15076 (2021)

Authors:

E Adam Paxton, Matthew Chantry, Milan Klöwer, Leo Saffin, Tim Palmer

Anthropogenic aerosols modulated twentieth-century Sahel rainfall variability via impacts on North Atlantic sea surface temperature

Copernicus GmbH (2021)

Authors:

Shipeng Zhang, Philip Stier, Guy Dagan, Minghuai Wang

Abstract:

<p>Sahel rainfall experienced significant multidecadal variability over the twentieth century. Previous work have proposed several drivers to explain the severe drought and the subsequent recovery of Sahel rainfall in the past century, including anthropogenic aerosols, GHGs, and internal variabilities. However, the attribution remained ambiguous. Sahel summertime monsoon has close teleconnections with North Atlantic sea surface temperature (NASST) variability, which has been proven to be affected by aerosols. Therefore, changes in regional aerosols emission can potentially drive multidecadal Sahel rainfall variability.</p><p>Here we use ensembles of state-of-the-art global climate models (the CESM-large ensemble and CMIP6 models) and observational datasets to demonstrate that anthropogenic aerosols have significant impacts on twentieth-century Sahel rainfall multidecadal variability through modifying NASST. Aerosol-induced multidecadal variations of downward solar fluxes over the North Atlantic Ocean cause NASST variability during the 20<sup>th</sup> century, altering the strength of the Hadley cell and the ITCZ position, therefore, dynamically linking aerosol effects to Sahel rainfall variability. While the observed linear trend of NASST might still be affected by a mix of various external and internal drivers, our results suggest that NASST variability is most likely caused by aerosol-induced changes in radiative fluxes rather than changes in ocean circulations, and that anthropogenic aerosols can explain most of the detrended Sahel rainfall variability. CMIP6 models further suggest that aerosol-cloud interactions contributed more to the variability than aerosol-radiation interactions. These findings highlight the importance of accurate representation of regional aerosol radiative effects for the simulation of Sahel rainfall variability.</p>

Using the learnings of machine learning to distill cloud controlling environmental regimes from satellite observations

(2021)

Authors:

Alyson Douglas, Philip Stier

Abstract:

<div> <div> <div> <div> <p>Cloud processes are the leading source of uncertainty in our current global climate models. Therefore understanding cloud formation, lifetime, and decay remains pivotal in order to reduce uncertainty in our global climate models future projections. Exploiting over ten years of satellite observations, the relationships between cloud properties and environmental factors, including aerosols, can be better understood and clustered into environmental regimes. We cluster regimes based on the regional strength of the relationships between the environment and cloud properties revealed using a random forest. Numerous processes, such as stratocumulus to cumulus transitions, may be constrained by the environmental regimes revealed by our analysis. Our results show that depending on the region, aerosol and the environment work to determine the baseline cloud properties. These observation based regimes can be compared to regimes derived from global climate models to understand how well model parameterizations capture the cloud controlling factors.</p> </div> </div> </div> </div>

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