scholarly journals Cold cloud microphysical process rates in a global chemistry–climate model

2021 ◽  
Vol 21 (3) ◽  
pp. 1485-1505
Author(s):  
Sara Bacer ◽  
Sylvia C. Sullivan ◽  
Odran Sourdeval ◽  
Holger Tost ◽  
Jos Lelieveld ◽  
...  

Abstract. Microphysical processes in cold clouds which act as sources or sinks of hydrometeors below 0 ∘C control the ice crystal number concentrations (ICNCs) and in turn the cloud radiative effects. Estimating the relative importance of the cold cloud microphysical process rates is of fundamental importance to underpin the development of cloud parameterizations for weather, atmospheric chemistry, and climate models and to compare the output with observations at different temporal resolutions. This study quantifies and investigates the ICNC rates of cold cloud microphysical processes by means of the chemistry–climate model EMAC (ECHAM/MESSy Atmospheric Chemistry) and defines the hierarchy of sources and sinks of ice crystals. Both microphysical process rates, such as ice nucleation, aggregation, and secondary ice production, and unphysical correction terms are presented. Model ICNCs are also compared against a satellite climatology. We found that model ICNCs are in overall agreement with satellite observations in terms of spatial distribution, although the values are overestimated, especially around high mountains. The analysis of ice crystal rates is carried out both at global and at regional scales. We found that globally the freezing of cloud droplets and convective detrainment over tropical land masses are the dominant sources of ice crystals, while aggregation and accretion act as the largest sinks. In general, all processes are characterized by highly skewed distributions. Moreover, the influence of (a) different ice nucleation parameterizations and (b) a future global warming scenario on the rates has been analysed in two sensitivity studies. In the first, we found that the application of different parameterizations for ice nucleation changes the hierarchy of ice crystal sources only slightly. In the second, all microphysical processes follow an upward shift in altitude and an increase by up to 10 % in the upper troposphere towards the end of the 21st century.

2020 ◽  
Author(s):  
Sara Bacer ◽  
Sylvia C. Sullivan ◽  
Holger Tost ◽  
Jos Lelieveld ◽  
Andrea Pozzer

Abstract. Microphysical processes in cold clouds which act as sources or sinks of hydrometeors below 0 °C control the ice crystal number concentrations (ICNCs) and in turn the cloud radiative effects. Estimating the relative importance of the cold cloud microphysical process rates is of fundamental importance to underpin the development of cloud parameterizations for weather, atmospheric chemistry and climate models and compare the output with observations at different temporal resolutions. This study quantifies and investigates the cold cloud microphysical process rates by means of the chemistry-climate model EMAC and defines the hierarchy of sources and sinks of ice crystals. The analysis is carried out both at global and at regional scales. We found that globally the freezing of cloud droplets, along with convective detrainment over tropical land masses, are the dominant sources of ice crystals, while aggregation and accretion act as the largest sinks. In general, all processes are characterised by highly skewed distribution. Moreover, the influence of (a) different ice nucleation parameterizations and (b) a future global warming scenario on the rates has been analysed in two sensitivity studies. In the first, we found that the application of different parameterizations for ice nucleation changed only slightly the hierarchy of ice crystal sources. In the second, all microphysical processes followed an upward shift (in altitude) and an increase by up to 10 % in the upper troposphere towards the end of the 21st century. This increase could have important feedbacks, such as leading to enhanced longwave warming of the uppermost atmosphere.


2021 ◽  
Author(s):  
Tom Choularton ◽  
Gary Lloyd ◽  
Keith Bower ◽  
Martin Gallagher

<p>Ground based and airborne observations of ice crystal concentrations are often found to exceed the concentration of ice nucleating particles by many orders of magnitude. This discrepancy between the expected ice particle concentrations formed through primary ice nucleation and observed ice particle concentration has led to the search for missing physical processes capable of creating new ice crystals. Secondary ice production (SIP) is a mechanism that produces new ice crystals without requiring the action of an ice nucleating particle. Evidence has now been found for several of these</p><p>Increasingly sophisticated cloud microphysical representations are being used in Numerical Weather Prediction and climate models to provide more realistic simulations of clouds. This drive towards greater complexity is motivated by the recognition of the importance of microphysical processes to the evolution of clouds, precipitation and the atmospheric environment.  </p><p>One important challenge for the successful implementation of cloud microphysics is the prediction of ice crystal concentrations, these influence the water budget of the cloud s through precipitation processes and the radiative properties of clouds especially when the ice crystals are in the majority over water droplets. The understanding and quantification of primary ice nucleation has grown in recent years, secondary ice production processes have received relatively little attention but are potentially very important for controlling the ice concentrations found in some types of clouds. </p><p>In this stalk a number of SIP mechanisms will be discussed: The Hallett-Mossop process, by far the most powerful mechanism when conditions are right; the fracture on freezing of supercooled raindrops, the fragmentation of falling snow flakes; the detachment of frost crystals from a surface.</p>


2018 ◽  
Vol 11 (10) ◽  
pp. 4021-4041 ◽  
Author(s):  
Sara Bacer ◽  
Sylvia C. Sullivan ◽  
Vlassis A. Karydis ◽  
Donifan Barahona ◽  
Martina Krämer ◽  
...  

Abstract. A comprehensive ice nucleation parameterization has been implemented in the global chemistry-climate model EMAC to improve the representation of ice crystal number concentrations (ICNCs). The parameterization of Barahona and Nenes (2009, hereafter BN09) allows for the treatment of ice nucleation taking into account the competition for water vapour between homogeneous and heterogeneous nucleation in cirrus clouds. Furthermore, the influence of chemically heterogeneous, polydisperse aerosols is considered by applying one of the multiple ice nucleating particle parameterizations which are included in BN09 to compute the heterogeneously formed ice crystals. BN09 has been modified in order to consider the pre-existing ice crystal effect and implemented to operate both in the cirrus and in the mixed-phase regimes. Compared to the standard EMAC parameterizations, BN09 produces fewer ice crystals in the upper troposphere but higher ICNCs in the middle troposphere, especially in the Northern Hemisphere where ice nucleating mineral dust particles are relatively abundant. Overall, ICNCs agree well with the observations, especially in cold cirrus clouds (at temperatures below 205 K), although they are underestimated between 200 and 220 K. As BN09 takes into account processes which were previously neglected by the standard version of the model, it is recommended for future EMAC simulations.


2021 ◽  
Author(s):  
Georgia Sotiropoulou ◽  
Anna Lewinschal ◽  
Annica Ekman ◽  
Athanasios Nenes

<p>Arctic clouds are among the largest sources of uncertainty in predictions of Arctic weather and climate. This is mainly due to errors in the representation of the cloud thermodynamic phase and the associated radiative impacts, which largely depends on the parameterization of cloud microphysical processes. Secondary ice processes (SIP) are among the microphysical processes that are poorly represented, or completely absent, in climate models. In most models, including the Norwegian Earth System Model -version 2 (NorESM2), Hallet-Mossop (H-M) is the only SIP mechanism available. In this study we further improve the description of H-M and include two additional SIP mechanisms (collisional break-up and drop-shattering) in NorESM2. Our results indicate that these additions improve the agreement between observed and modeled ice crystal number concentrations and liquid water path in mixed-phase clouds observed at Ny-Alesund in 2016-2017. We then conclude by quantifying the impact of these overlooked SIP mechanisms for cloud microphysical characteristics, properties and the radiative balance throughout the Arctic.</p><p> </p>


2018 ◽  
Author(s):  
Sara Bacer ◽  
Sylvia C. Sullivan ◽  
Vlassis A. Karydis ◽  
Donifan Barahona ◽  
Martina Krämer ◽  
...  

Abstract. A comprehensive ice nucleation parameterization has been implemented in the global chemistry-climate model EMAC to realistically represent ice crystal number concentrations. The parameterization of Barahona and Nenes (2009, hereafter BN09) allows the treatment of ice nucleation, taking into account the competition for water vapour between homogeneous and heterogeneous nucleation and pre-existing ice crystals in cold clouds. Furthermore, the influence of chemically-heterogeneous, polydisperse aerosols is considered via multiple ice nucleating particle spectra, which are included in the parameterization to compute the heterogeneously formed ice crystals. BN09 has been implemented to operate both in the cirrus and in the mixed-phase regimes. Compared to the standard EMAC results, BN09 produces fewer ice crystals in the upper troposphere but higher ice crystal number concentrations in the middle troposphere, especially in the Northern Hemisphere where ice nucleating mineral dust particles are relatively abundant. The comparison with a climatological data set of aircraft measurements shows that BN09 used in the cirrus regime improves the model results and, therefore, is recommended for future EMAC simulations.


2012 ◽  
Vol 5 (3) ◽  
pp. 2811-2842 ◽  
Author(s):  
M. A. Chandler ◽  
L. E. Sohl ◽  
J. A. Jonas ◽  
H. J. Dowsett

Abstract. Climate reconstructions of the mid-Pliocene Warm Period (mPWP) bear many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change. In particular, marine and terrestrial paleoclimate data point to high latitude temperature amplification, with associated decreases in sea ice and land ice and altered vegetation distributions that show expansion of warmer climate biomes into higher latitudes. NASA GISS climate models have been used to study the Pliocene climate since the USGS PRISM project first identified that the mid-Pliocene North Atlantic sea surface temperatures were anomalously warm. Here we present the most recent simulations of the Pliocene using the AR5/CMIP5 version of the GISS Earth System Model known as ModelE2-R. These simulations constitute the NASA contribution to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. We provide discussion of features that show considerable improvement compared with simulations from previous versions of the NASA GISS models, improvement defined here as simulation results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene climate. In some regions even qualitative agreement between model results and paleodata are an improvement over past studies, but the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea in these new simulations is by far the most accurate portrayal ever of this key geographic region by the GISS climate model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterizations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.


2018 ◽  
Vol 11 (6) ◽  
pp. 2033-2048 ◽  
Author(s):  
Richard Hyde ◽  
Ryan Hossaini ◽  
Amber A. Leeson

Abstract. Clustering – the automated grouping of similar data – can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model–observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry–climate model (CCM) output of tropospheric ozone – an important greenhouse gas – from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ∼ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ∼ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere – where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.


2021 ◽  
Author(s):  
Ramiro Checa-Garcia ◽  
Didier Didier Hauglustaine ◽  
Yves Balkanski ◽  
Paola Formenti

<p>Glyoxal (GL) and methylglyoxal (MGL) are the smallest di-carbonyls present in the atmosphere. They hydrate easily, a process that is followed by an oligomerisation. As a consequence, it is considered that they participate actively in the formation of secondary organic aerosols (SOA) and therefore, they are being introduced in the current climate models with interactive chemistry to assess their importance on atmospheric chemistry. In our study we present the introduction of glyoxal in the INCA global model. A new closed set of gas-phase  reactions is analysed first with a box model. Then the simulated global distribution of glyoxal by the global climate model is compared with satellite observations. We show that the oxidation of volatile organic compounds and acetylene, together with the photolysis of more complex di-carbonyls allows us to reproduce well glyoxal seasonal cycle in the tropics but it requires an additional sink in several northern hemispheric regions. Additional sensitivity studies are being conducted by introducing  GL and MGL interactions with dust and SOA according to new uptake  coefficients obtained by dedicated experiments in the CESAM instrument (Chamber of Experimental Simulation of Atmospheric Multiphases). The effects of these heterogeneous chemistry processes will be quantified in the light of the new chamber measurements  and also evaluated in terms of optical properties of aged dust aerosol  and the changes in direct radiative effects  of the involved aerosol species.</p>


2021 ◽  
Author(s):  
Ulrike Proske ◽  
Sylvaine Ferrachat ◽  
David Neubauer ◽  
Ulrike Lohmann

<p>Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedláček, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.</p><p>This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time.<br>The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.</p><p> </p><p><br>Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). “Climate Models Are Uncertain, but We Can Do Something About It”. In: Eos 99. doi: 10.1029/2018EO093757</p><p>Knutti, Reto and Jan Sedláček (Apr. 2013). “Robustness and Uncertainties in the New CMIP5 Climate Model Projections”. In: Nature Climate Change 3.4, pp. 369–373. doi: 10.1038/nclimate1716</p>


2013 ◽  
Vol 13 (8) ◽  
pp. 4057-4072 ◽  
Author(s):  
K. W. Bowman ◽  
D. T. Shindell ◽  
H. M. Worden ◽  
J.F. Lamarque ◽  
P. J. Young ◽  
...  

Abstract. We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5–20 ppb) in the Southern Hemisphere (SH) and modest high bias (5–10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005–2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750–2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.


Sign in / Sign up

Export Citation Format

Share Document