scholarly journals Implementing a sectional scheme for early aerosol growth from new particle formation in the Norwegian Earth System Model v2: comparison to observations and climate impacts

2020 ◽  
Author(s):  
Sara M. Blichner ◽  
Moa K. Sporre ◽  
Risto Makkonen ◽  
Terje K. Berntsen

Abstract. Aerosol-cloud interactions contribute with a large portion of the spread in estimates of climate forcing, climate sensitivity and future projections. An important part of this uncertainty is how much new particle formation (NPF) contributes to cloud condensation nuclei (CCN), and furthermore, how this changes with changes in anthropogenic emissions. Incorporating NPF and early growth in Earth System Models (ESMs) is, however, challenging both due to uncertain parameters (e.g. participating vapours), structural challenges (numerical description of growth from ∼1 to ∼100 nm), and due to large scale of ESM grid compared to NPF scale.A common approach in ESMs is to represent the particle size distribution by a certain number of log-normal modes. Sectional schemes on the other hand, where the size distribution is represented by bins, are considered closer to first principles because they do not make an a priori assumption about the size distribution. In order to improve the representation of early growth, we have implemented a sectional scheme for the smallest particles (5–39.6 nm diameter) in the Norwegian Earth System Model (NorESM), feeding particles into the original aerosol scheme. This is, to our knowledge, the first time such an approach has been tried. We find that including the sectional scheme for early growth improves the aerosol number concentration in the model when comparing against observations, particularly in the 50–100 nm diameter range. Furthermore, we find that the model with the sectional scheme produces much less particles than the original scheme in polluted regions, while it produces more in remote regions and the free troposphere, indicating a potential impact on the estimated aerosol forcing. Finally, we analyse the effect on cloud-aerosol interactions and find that the effect of changes in NPF efficiency on clouds is highly heterogeneous in space. While in remote regions, more efficient NPF leads to higher cloud droplet number concentration (CDNC), in polluted regions the opposite is in fact the case.

2021 ◽  
Vol 14 (6) ◽  
pp. 3335-3359
Author(s):  
Sara M. Blichner ◽  
Moa K. Sporre ◽  
Risto Makkonen ◽  
Terje K. Berntsen

Abstract. Aerosol–cloud interactions contribute to a large portion of the spread in estimates of climate forcing, climate sensitivity and future projections. An important part of this uncertainty is how much new particle formation (NPF) contributes to cloud condensation nuclei (CCN) and, furthermore, how this changes with changes in anthropogenic emissions. Incorporating NPF and early growth in Earth system models (ESMs) is, however, challenging due to uncertain parameters (e.g. participating vapours), structural issues (numerical description of growth from ∼1 to ∼100 nm) and the large scale of an ESM grid compared to the NPF scale. A common approach in ESMs is to represent the particle size distribution by a certain number of log-normal modes. Sectional schemes, on the other hand, in which the size distribution is represented by bins, are considered closer to first principles because they do not make an a priori assumption about the size distribution. In order to improve the representation of early growth, we have implemented a sectional scheme for the smallest particles (5–39.6 nm diameter) in the Norwegian Earth System Model (NorESM), feeding particles into the original aerosol scheme. This is, to our knowledge, the first time such an approach has been tried. We find that including the sectional scheme for early growth improves the aerosol number concentration in the model when comparing against observations, particularly in the 50–100 nm diameter range. Furthermore, we find that the model with the sectional scheme produces much fewer particles than the original scheme in polluted regions, while it produces more in remote regions and the free troposphere, indicating a potential impact on the estimated aerosol forcing. Finally, we analyse the effect on cloud–aerosol interactions and find that the effect of changes in NPF efficiency on clouds is highly heterogeneous in space. While in remote regions, more efficient NPF leads to higher cloud droplet number concentration (CDNC), in polluted regions the opposite is in fact the case.


2021 ◽  
Author(s):  
Sara Marie Blichner ◽  
Moa Kristina Sporre ◽  
Terje Koren Berntsen

<p>Cloud-aerosol interactions are responsible for much of the uncertainty in forcing estimates from pre-industrial times and thus also climate sensitivity and future projections. Maybe the most important factor in this is our lack of knowledge about pre-industrial aerosols, their sources and their ability to act as cloud condensation nuclei (CCN). The number of CCN is highly dependent on secondary aerosol formation and in particular how much of this secondary aerosol mass that goes to new particle formation (NPF) and early particle growth, versus growing already large particles even larger. <br>Earth system models which seek to model this, face a challenge because we need to represent processes at a very fine scale (nanometers) to a sufficient accuracy, while simultaneously keeping computational costs low. A common approach is to use log-normal modes to represent the sizedistribution, while more computationally expensive sectional schemes are considered closer to first principles. </p><p>In this study, we investigate the effect of a newly developed scheme for early particle growth on the effective radiative forcing from cloud-aerosol interactions (ERF<sub>aci</sub>)  in the Norwegian Earth System Model v2 (NorESMv2). The new scheme, referred to as OsloAeroSec, presented in  Blichner et al. (2020), combines a sectional scheme for the growth of the smallest particles (5 - 39.6 nm), with the original semi-modal aerosol scheme which would simply parameterize the growth up to the smallest mode with Lehtinen et al. (2007). This was shown to to improve the representation of CCN relevant particle concentrations, when compared to measurement data.  </p><p>We find that ERF<sub>aci</sub> is weakened by approximately 10 % with the new scheme (from -1.29  to -1.16 Wm<sup>-2</sup>). The weakening originates from OsloAeroSec (the new scheme) reducing particle formation in regions with high aerosol concentrations while increasing it in very pristine regions. We find, perhaps surprisingly, that an important factor for the overall forcing, is that  NPF inhibits aerosol activation into cloud droplets in high-aerosol-concentration regions, while the opposite is true in pristine regions. <br>This is because the NPF particles act as a condensation sink, and if they cannot activate directly themselves, they may reduce the growth of the larger particles which would otherwise activate. <br>Furthermore, we find that the increase in particle hygroscopicity with present day emissions of sulphate pre-cursors, decreases the size of the activated particles, and thus makes NPF particles more relevant for cloud droplet activation. </p><p><strong>References: </strong></p><p>Lehtinen, Kari E. J., Miikka Dal Maso, Markku Kulmala, and Veli-Matti Kerminen. “Estimating Nucleation Rates from Apparent Particle Formation Rates and Vice Versa: Revised Formulation of the Kerminen–Kulmala Equation.” Journal of Aerosol Science (2007): https://doi.org/10.1016/j.jaerosci.2007.06.009.</p><p>Blichner, Sara M., Moa K. Sporre, Risto Makkonen, and Terje K. Berntsen. “Implementing a sectional scheme for early aerosol growth from new particle formation in the Norwegian Earth System Model v2: comparison to observations and climate impacts.” Geoscientific Model Development Discussions (2020): https://doi.org/10.5194/gmd-2020-357</p>


2021 ◽  
Author(s):  
Shuaiqi Tang ◽  
Jerome D. Fast ◽  
Kai Zhang ◽  
Joseph C. Hardin ◽  
Adam C. Varble ◽  
...  

Abstract. An Earth System Model (ESM) aerosol-cloud diagnostics package is developed to facilitate the routine evaluation of aerosols, clouds and aerosol-cloud interactions simulated by the Department of Energy’s (DOE) Energy Exascale Earth System Model (E3SM). The first version focuses on comparing simulated aerosol properties with aircraft, ship, and surface measurements, most of them are measured in-situ. The diagnostics currently covers six field campaigns in four geographical regions: Eastern North Atlantic (ENA), Central U.S. (CUS), Northeastern Pacific (NEP) and Southern Ocean (SO). These regions produce frequent liquid or mixed-phase clouds with extensive measurements available from the Atmospheric Radiation Measurement (ARM) program and other agencies. Various types of diagnostics and metrics are performed for aerosol number, size distribution, chemical composition, CCN concentration and various meteorological quantities to assess how well E3SM represents observed aerosol properties across spatial scales. Overall, E3SM qualitatively reproduces the observed aerosol number concentration, size distribution and chemical composition reasonably well, but underestimates Aitken mode and overestimates accumulation mode aerosols over the CUS region, and underestimates aerosol number concentration over the SO region. The current version of E3SM struggles to reproduce new particle formation events frequently observed over both the CUS and ENA regions, indicating missing processes in current parameterizations. The diagnostics package is coded and organized in a way that can be easily extended to other field campaign datasets and adapted to higher-resolution model simulations. Future releases will include comprehensive cloud and aerosol-cloud interaction diagnostics.


2015 ◽  
Vol 15 (21) ◽  
pp. 12283-12313 ◽  
Author(s):  
A. Lupascu ◽  
R. Easter ◽  
R. Zaveri ◽  
M. Shrivastava ◽  
M. Pekour ◽  
...  

Abstract. Accurate representation of the aerosol lifecycle requires adequate modeling of the particle number concentration and size distribution in addition to their mass, which is often the focus of aerosol modeling studies. This paper compares particle number concentrations and size distributions as predicted by three empirical nucleation parameterizations in the Weather Research and Forecast coupled with chemistry (WRF-Chem) regional model using 20 discrete size bins ranging from 1 nm to 10 μm. Two of the parameterizations are based on H2SO4, while one is based on both H2SO4 and organic vapors. Budget diagnostic terms for transport, dry deposition, emissions, condensational growth, nucleation, and coagulation of aerosol particles have been added to the model and are used to analyze the differences in how the new particle formation parameterizations influence the evolving aerosol size distribution. The simulations are evaluated using measurements collected at surface sites and from a research aircraft during the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted in the vicinity of Sacramento, California. While all three parameterizations captured the temporal variation of the size distribution during observed nucleation events as well as the spatial variability in aerosol number, all overestimated by up to a factor of 2.5 the total particle number concentration for particle diameters greater than 10 nm. Using the budget diagnostic terms, we demonstrate that the combined H2SO4 and low-volatility organic vapor parameterization leads to a different diurnal variability of new particle formation and growth to larger sizes compared to the parameterizations based on only H2SO4. At the CARES urban ground site, peak nucleation rates are predicted to occur around 12:00 Pacific (local) standard time (PST) for the H2SO4 parameterizations, whereas the highest rates were predicted at 08:00 and 16:00 PST when low-volatility organic gases are included in the parameterization. This can be explained by higher anthropogenic emissions of organic vapors at these times as well as lower boundary-layer heights that reduce vertical mixing. The higher nucleation rates in the H2SO4-organic parameterization at these times were largely offset by losses due to coagulation. Despite the different budget terms for ultrafine particles, the 10–40 nm diameter particle number concentrations from all three parameterizations increased from 10:00 to 14:00 PST and then decreased later in the afternoon, consistent with changes in the observed size and number distribution. We found that newly formed particles could explain up to 20–30 % of predicted cloud condensation nuclei at 0.5 % supersaturation, depending on location and the specific nucleation parameterization. A sensitivity simulation using 12 discrete size bins ranging from 1 nm to 10 μm diameter gave a reasonable estimate of particle number and size distribution compared to the 20 size bin simulation, while reducing the associated computational cost by ~ 36 %.


2020 ◽  
Vol 13 (7) ◽  
pp. 3383-3438 ◽  
Author(s):  
Veronika Eyring ◽  
Lisa Bock ◽  
Axel Lauer ◽  
Mattia Righi ◽  
Manuel Schlund ◽  
...  

Abstract. The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.


2018 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g. 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multi-millennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speedup is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean-sea ice horizontal grid configuration that allows an increase of the ocean-sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasises model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates, and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.


2019 ◽  
Vol 12 (11) ◽  
pp. 4823-4873 ◽  
Author(s):  
Neil C. Swart ◽  
Jason N. S. Cole ◽  
Viatcheslav V. Kharin ◽  
Mike Lazare ◽  
John F. Scinocca ◽  
...  

Abstract. The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization, and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large-scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three-dimensional atmosphere (T63 spectral resolution equivalent roughly to 2.8∘) and ocean (nominally 1∘) general circulation models, a sea-ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science and service applications in Canada.


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