scholarly journals Constraints on global aerosol number concentration, SO<sub>2</sub> and condensation sink in UKESM1 using ATom measurements

2021 ◽  
Vol 21 (6) ◽  
pp. 4979-5014
Author(s):  
Ananth Ranjithkumar ◽  
Hamish Gordon ◽  
Christina Williamson ◽  
Andrew Rollins ◽  
Kirsty Pringle ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Vertical Profile ◽  
Dimethyl Sulfide ◽  
Dominant Role ◽  
Model Performance ◽  
Lower Troposphere ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Atmospheric Processes ◽  
Condensation Sink

Abstract. Understanding the vertical distribution of aerosol helps to reduce the uncertainty in the aerosol life cycle and therefore in the estimation of the direct and indirect aerosol forcing. To improve our understanding, we use measurements from four deployments of the Atmospheric Tomography (ATom) field campaign (ATom1–4) which systematically sampled aerosol and trace gases over the Pacific and Atlantic oceans with near pole-to-pole coverage. We evaluate the UK Earth System Model (UKESM1) against ATom observations in terms of joint biases in the vertical profile of three variables related to new particle formation: total particle number concentration (NTotal), sulfur dioxide (SO2) mixing ratio and the condensation sink. The NTotal, SO2 and condensation sink are interdependent quantities and have a controlling influence on the vertical profile of each other; therefore, analysing them simultaneously helps to avoid getting the right answer for the wrong reasons. The simulated condensation sink in the baseline model is within a factor of 2 of observations, but the NTotal and SO2 show much larger biases mainly in the tropics and high latitudes. We performed a series of model sensitivity tests to identify atmospheric processes that have the strongest influence on overall model performance. The perturbations take the form of global scaling factors or improvements to the representation of atmospheric processes in the model, for example by adding a new boundary layer nucleation scheme. In the boundary layer (below 1 km altitude) and lower troposphere (1–4 km), inclusion of a boundary layer nucleation scheme (Metzger et al., 2010) is critical to obtaining better agreement with observations. However, in the mid (4–8 km) and upper troposphere (> 8 km), sub-3 nm particle growth, pH of cloud droplets, dimethyl sulfide (DMS) emissions, upper-tropospheric nucleation rate, SO2 gas-scavenging rate and cloud erosion rate play a more dominant role. We find that perturbations to boundary layer nucleation, sub-3 nm growth, cloud droplet pH and DMS emissions reduce the boundary layer and upper tropospheric model bias simultaneously. In a combined simulation with all four perturbations, the SO2 and condensation sink profiles are in much better agreement with observations, but the NTotal profile still shows large deviations, which suggests a possible structural issue with how nucleation or gas/particle transport or aerosol scavenging is handled in the model. These perturbations are well-motivated in that they improve the physical basis of the model and are suitable for implementation in future versions of UKESM.

scholarly journals Constraints on global aerosol number concentration, SO<sub>2</sub> and condensation sink in UKESM1 using ATom measurements

2020 ◽  
Author(s):  
Ananth Ranjithkumar ◽  
Hamish Gordon ◽  
Christina Williamson ◽  
Andrew Rollins ◽  
Kirsty J. Pringle ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Vertical Profile ◽  
Dominant Role ◽  
Model Performance ◽  
Lower Troposphere ◽  
Number Concentration ◽  
Sampled Data ◽  
Upper Troposphere ◽  
Atmospheric Processes ◽  
Condensation Sink

Abstract. Understanding the vertical distribution of aerosol helps to reduce the uncertainty in the aerosol lifecycle and therefore in the estimation of the direct and indirect aerosol forcing. To improve our understanding, we use measurements from four deployments of the Atmospheric Tomography (ATom) field campaign (ATom1-4) which systematically sampled data over the Pacific and Atlantic Oceans with near pole-to-pole coverage. We evaluate the UK Earth system model (UKESM1) against ATom observations in terms of joint biases in the vertical profile of three variables related to new particle formation: total particle number concentration (NTotal), sulphur dioxide (SO2) mixing ratio and the condensation sink. The NTotal, SO2 and condensation sink are interdependent quantities and have a controlling influence on the vertical profile of each other. Improving only one of these quantities in comparison with observations can lead to a misleading impression that overall model performance has improved. Analysing NTotal, SO2 and condensation sink simultaneously helps reduce the probability of getting the right answer for the wrong reasons. The model's condensation sink is within a factor of 2 of observations, but the NTotal and SO2 shows larger biases mainly in the tropics and high latitudes. Algorithmic improvements to the model and perturbations to key atmospheric processes help reduce tropospheric model biases consistently. We performed a series of model sensitivity tests to identify atmospheric processes that have the strongest influence on overall model performance (NTotal, SO2 and condensation sink simultaneously). In the boundary layer (which we define in this study as below 1 km altitude) and lower troposphere (1–4 km) inclusion of a boundary layer nucleation scheme (Metzger et al., 2010), which is switched off in the default version of UKESM, is critical to obtaining better agreement with observations. However, in the mid (4–8 km) and upper troposphere (> 8 km), sub-3 nm particle growth, pH of cloud droplets, DMS emissions, upper tropospheric nucleation rate, SO2 gas scavenging rate and cloud erosion rate are found to play a more dominant role. Analysing the data with altitude, we find that perturbations to boundary layer nucleation, sub 3 nm growth, cloud droplet pH and DMS emissions reduces the boundary layer and upper tropospheric model bias. We performed a combined simulation with all 4 perturbations included and found that the model's NTotal, SO2 and condensation sink biases were reduced in most cases (up to a 50 % reduction) in both the boundary layer and upper troposphere simultaneously. These perturbations are well-motivated in that they improve the physical basis of the model and are suitable for implementation in future versions of UKESM.

scholarly journals Investigation of NO<sub>2</sub> vertical distribution using two DOAS retrievals for GOME-2A measurements in the UV and vis spectral range

2017 ◽  
Author(s):  
Lisa K. Behrens ◽  
Andreas Hilboll ◽  
Andreas Richter ◽  
Enno Peters ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Radiative Transfer ◽  
Vertical Distribution ◽  
Spectral Range ◽  
Biomass Burning ◽  
Vertical Profile ◽  
Lower Troposphere ◽  
Tropical Africa ◽  
Profile Shape ◽  
Spectral Ranges

Abstract. In this study, we present a novel NO2 DOAS retrieval in the ultraviolet (UV) spectral range for satellite observations from the Global Ozone Monitoring Instrument 2 on board EUMETSAT’s MetOp-A (GOME-2A) satellite. We compare the results to those from an established NO2 retrieval in the visible (vis) spectral range from the same instrument and infer information about the NO2 vertical profile shape in the troposphere. As expected, radiative transfer calculations for satellite geometries show that the sensitivity close to the ground is higher in the vis than in the UV spectral range. Consequently, NO2 slant column densities (SCDs) in the vis are usually higher than in the UV, if the NO2 is close to the surface. Therefore, these differences in NO2 SCDs between the two spectral ranges contain information on the vertical distribution of NO2 in the troposphere. We combine these results with radiative transfer calculations and simulated NO2 fields from the TM5 chemistry transport model to evaluate the simulated NO2 vertical distribution. We investigate regions representative for both anthropogenic and biomass burning NO2 pollution. Anthropogenic air pollution is mostly located in the boundary layer close to the surface, which is reflected by the large differences between UV and vis SCDs of ~ 60 %. Biomass burning NO2 in contrast is often uplifted into elevated layers above the boundary layer. This is best seen in tropical Africa south of the equator, where the biomass burning NO2 is well observed in the UV, and the difference between the two spectral ranges is only ~ 36 %. In tropical Africa north of the equator, however, the biomass burning NO2 is located closer to the ground, reducing its visibility. While not enabling a full retrieval of the vertical NO2 profile shape in the troposphere, our results can help to constrain the vertical profile of NO2 in the lower troposphere and, when analyzed together with simulated NO2 fields, can help interpret the model output.

scholarly journals GOME-2A retrievals of tropospheric NO<sub>2</sub> in different spectral ranges – influence of penetration depth

2018 ◽  
Vol 11 (5) ◽  
pp. 2769-2795 ◽  
Author(s):  
Lisa K. Behrens ◽  
Andreas Hilboll ◽  
Andreas Richter ◽  
Enno Peters ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Radiative Transfer ◽  
Spectral Range ◽  
Biomass Burning ◽  
Vertical Profile ◽  
Lower Troposphere ◽  
Optical Absorption Spectroscopy ◽  
Tropical Africa ◽  
Profile Shape ◽  
Spectral Ranges

Abstract. In this study, we present a novel nitrogen dioxide (NO2) differential optical absorption spectroscopy (DOAS) retrieval in the ultraviolet (UV) spectral range for observations from the Global Ozone Monitoring Instrument 2 on board EUMETSAT's MetOp-A (GOME-2A) satellite. We compare the results to those from an established NO2 retrieval in the visible (vis) spectral range from the same instrument and investigate how differences between the two are linked to the NO2 vertical profile shape in the troposphere.As expected, radiative transfer calculations for satellite geometries show that the sensitivity close to the ground is higher in the vis than in the UV spectral range. Consequently, NO2 slant column densities (SCDs) in the vis are usually higher than in the UV if the NO2 is close to the surface. Therefore, these differences in NO2 SCDs between the two spectral ranges contain information on the vertical distribution of NO2 in the troposphere. We combine these results with radiative transfer calculations and simulated NO2 fields from the TM5-MP chemistry transport model to evaluate the simulated NO2 vertical distribution.We investigate regions representative of both anthropogenic and biomass burning NO2 pollution. Anthropogenic air pollution is mostly located in the boundary layer close to the surface, which is reflected by large differences between UV and vis SCDs of  ∼  60 %. Biomass burning NO2 in contrast is often uplifted into elevated layers above the boundary layer. This is best seen in tropical Africa south of the Equator, where the biomass burning NO2 is well observed in the UV, and the SCD difference between the two spectral ranges is only  ∼  36 %. In tropical Africa north of the Equator, however, the biomass burning NO2 is located closer to the ground, reducing its visibility in the UV.While not enabling a full retrieval of the vertical NO2 profile shape in the troposphere, our results can help to constrain the vertical profile of NO2 in the lower troposphere and, when analysed together with simulated NO2 fields, can help to better interpret the model output.

scholarly journals Aerosol indirect effects on continental low-level clouds over Sweden and Finland

2014 ◽  
Vol 14 (22) ◽  
pp. 12167-12179 ◽  
Author(s):  
M. K. Sporre ◽  
E. Swietlicki ◽  
P. Glantz ◽  
M. Kulmala
Keyword(s):  
Boundary Layer ◽  
Radiative Forcing ◽  
Remote Sensing Data ◽  
Cloud Droplet ◽  
Weather Radar ◽  
Number Concentration ◽  
Effective Radius ◽  
Distribution Data ◽  
Low Level ◽  
Radar Images

Abstract. Aerosol effects on low-level clouds over the Nordic Countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds is investigated using reanalysis data from the European Centre for Medium-Range Weather Forecasts. The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosol–cloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.

scholarly journals Time-dependent entrainment of smoke presents an observational challenge for assessing aerosol–cloud interactions over the southeast Atlantic Ocean

2018 ◽  
Vol 18 (19) ◽  
pp. 14623-14636 ◽  
Author(s):  
Michael S. Diamond ◽  
Amie Dobracki ◽  
Steffen Freitag ◽  
Jennifer D. Small Griswold ◽  
Ashley Heikkila ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atlantic Ocean ◽  
Marine Boundary Layer ◽  
Climate Modeling ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Properties ◽  
History Of ◽  
Cloud Droplet Number Concentration ◽  
The Relationship

Abstract. The colocation of clouds and smoke over the southeast Atlantic Ocean during the southern African biomass burning season has numerous radiative implications, including microphysical modulation of the clouds if smoke is entrained into the marine boundary layer. NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign is studying this system with aircraft in three field deployments between 2016 and 2018. Results from ORACLES-2016 show that the relationship between cloud droplet number concentration and smoke below cloud is consistent with previously reported values, whereas cloud droplet number concentration is only weakly associated with smoke immediately above cloud at the time of observation. By combining field observations, regional chemistry–climate modeling, and theoretical boundary layer aerosol budget equations, we show that the history of smoke entrainment (which has a characteristic mixing timescale on the order of days) helps explain variations in cloud properties for similar instantaneous above-cloud smoke environments. Precipitation processes can obscure the relationship between above-cloud smoke and cloud properties in parts of the southeast Atlantic, but marine boundary layer carbon monoxide concentrations for two case study flights suggest that smoke entrainment history drove the observed differences in cloud properties for those days. A Lagrangian framework following the clouds and accounting for the history of smoke entrainment and precipitation is likely necessary for quantitatively studying this system; an Eulerian framework (e.g., instantaneous correlation of A-train satellite observations) is unlikely to capture the true extent of smoke–cloud interaction in the southeast Atlantic.

scholarly journals Improving NCEP HWRF Simulations of Surface Wind and Inflow Angle in the Eyewall Area

2018 ◽  
Vol 33 (3) ◽  
pp. 887-898 ◽  
Author(s):  
Weiguo Wang ◽  
Jason A. Sippel ◽  
Sergio Abarca ◽  
Lin Zhu ◽  
Bin Liu ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Layer ◽  
Vertical Profile ◽  
Surface Wind ◽  
Model Performance ◽  
Eddy Diffusivity ◽  
Weather Research And Forecasting ◽  
Low Level ◽  
The Vertical Distribution ◽  
Hwrf Model

Abstract This note describes a modification of the boundary layer parameterization scheme in the Hurricane Weather Research and Forecasting (HWRF) Model, which improves the simulations of low-level wind and surface inflow angle in the eyewall area and has been implemented in the HWRF system and used in the operational system since 2016. The modification is on an observation-based adjustment of eddy diffusivity previously implemented in the model. It is needed because the previous adjustment resulted in a discontinuity in the vertical distribution of eddy diffusivity near the surface-layer top, which increases the friction within the surface layer and compromises the surface-layer constant-flux assumption. The discontinuity affects the simulation of storm intensity and intensification, one of the main metrics of model performance, particularly in strong tropical cyclones. This issue is addressed by introducing a height-dependent adjustment so that the vertical profile of eddy diffusivity is continuous throughout the boundary layer. It is shown that the implementation of the modification results in low-level winds and surface inflow angles in the storm’s eyewall region closer to observations.

Quantification of aerosol effects on marine boundary layer clouds with machine learning

2021 ◽  
Author(s):  
Lukas Zipfel ◽  
Hendrik Andersen ◽  
Jan Cermak
Keyword(s):  
Machine Learning ◽  
Boundary Layer ◽  
Marine Boundary Layer ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Satellite Observations ◽  
Radiative Properties ◽  
Cloud Base ◽  
Boundary Layer Clouds ◽  
Cloud Droplet Number Concentration

&lt;p&gt;Satellite observations are used in regional machine learning models to quantify sensitivities of marine boundary-layer clouds (MBLC) to aerosol changes.&lt;/p&gt;&lt;p&gt;MBLCs make up a large part of the global cloud coverage as they are persistently present over more than 20% of the Earth&amp;#8217;s oceans in the annual mean.They play an important role in Earth&amp;#8217;s energy budget by reflecting solar radiation and interacting with thermal radiation from the surface, leading to a net cooling effect. Cloud properties and their radiative characteristics such as cloud albedo, horizontal and vertical extent, lifetime and precipitation susceptibility are dependent on environmental conditions. Aerosols in their role as condensation nuclei affect these cloud radiative properties through changes in the cloud droplet number concentration and subsequent cloud adjustments to this perturbation. However, the magnitude and sign of these effects remain among the largest uncertainties in future climate predictions.&lt;/p&gt;&lt;p&gt;In an effort to help improve these predictions a machine learning approach in combination with observational data is pursued:&lt;/p&gt;&lt;p&gt;Satellite observations from the collocated A-Train dataset (C3M) for 2006-2011 are used in combination with ECMWF atmospheric reanalysis data (ERA5) to train regional Gradient Boosting Regression Tree (GBRT) models to predict changes in key physical and radiative properties of MBLCs. The cloud droplet number concentration (N&lt;sub&gt;d&lt;/sub&gt;) and the liquid water path (LWP) are simulated for the eastern subtropical oceans, which are characterised by a high annual coverage of MBLC due to the occurrence of semi-permanent stratocumulus sheets. Relative humidity above cloud, cloud top height and temperature below the cloud base and at the surface are identified as important predictors for both N&lt;sub&gt;d&lt;/sub&gt; and LWP.&amp;#160; The impact of each predictor variable on the GBRT model's output is analysed using Shapley values as a method of explainable machine learning, providing novel sensitivity estimates that will improve process understanding and help constrain the parameterization of MBLC processes in Global Climate Models.&lt;/p&gt;

scholarly journals Time-dependent entrainment of smoke presents an observational challenge for assessing aerosol–cloud interactions over the southeast Atlantic Ocean

2018 ◽  
Author(s):  
Michael S. Diamond ◽  
Amie Dobracki ◽  
Steffen Freitag ◽  
Jennifer D. Small Griswold ◽  
Ashley Heikkila ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atlantic Ocean ◽  
Marine Boundary Layer ◽  
Climate Modeling ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Properties ◽  
History Of ◽  
Cloud Droplet Number Concentration ◽  
The Relationship

Abstract. The colocation of clouds and smoke over the southeast Atlantic Ocean during the southern African biomass burning season has numerous radiative implications, including microphysical modulation of the clouds if smoke is entrained into the marine boundary layer. NASA’s ObseRvtions of Aerosols above CLouds and their intEractionS (ORACLES) campaign is studying this system with aircraft in three field deployments between 2016 and 2018. Results from ORACLES-2016 show that the relationship between cloud droplet number concentration and smoke below cloud is consistent with previously reported values, whereas cloud droplet number concentration is only weakly associated with smoke immediately above cloud at the time of observation. Combining field observations, regional chemistry–climate modeling, and theoretical boundary layer aerosol budget equations, we show that the history of smoke entrainment (which has a characteristic mixing timescale on the order of days) helps explain variations in cloud properties for similar instantaneous above-cloud smoke environments. Precipitation processes are also expected to obscure the relationship between above-cloud smoke and cloud properties in parts of the southeast Atlantic, although marine boundary layer carbon monoxide concentrations for two case study flights suggest that smoke entrainment history drove the observed differences in cloud properties for those days. A Lagrangian framework following the clouds and accounting for the history of smoke entrainment and precipitation is likely necessary for quantitatively studying this system: an Eulerian framework (e.g., instantaneous correlation of A-train satellite observations) is unlikely to capture the true extent of smoke–cloud interaction in the southeast Atlantic.

Sign in / Sign up

Export Citation Format

Share Document