ALBERT

Description: The concept of cloud radiative forcing (CRF) is commonly applied to quantify the impact of clouds on the surface radiative energy budget (REB). In the Arctic, specific radiative interactions between microphysical and macrophysical properties of clouds and the surface strongly modify the warming or cooling effect of clouds, complicating the estimate of CRF obtained from observations or models. Clouds tend to increase the broadband surface albedo over snow or sea ice surfaces compared to cloud-free conditions. However, this effect is not adequately considered in the derivation of CRF in the Arctic so far. Therefore, we have quantified the effects caused by surface-albedo–cloud interactions over highly reflective snow or sea ice surfaces on the CRF using radiative transfer simulations and below-cloud airborne observations above the heterogeneous springtime marginal sea ice zone (MIZ) during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. The impact of a modified surface albedo in the presence of clouds, as compared to cloud-free conditions, and its dependence on cloud optical thickness is found to be relevant for the estimation of the shortwave CRF. A method is proposed to consider this surface albedo effect on CRF estimates by continuously retrieving the cloud-free surface albedo from observations under cloudy conditions, using an available snow and ice albedo parameterization. Using ACLOUD data reveals that the estimated average shortwave cooling by clouds almost doubles over snow- and ice-covered surfaces (−62 W m−2 instead of −32 W m−2), if surface-albedo–cloud interactions are considered. As a result, the observed total (shortwave plus longwave) CRF shifted from a warming effect to an almost neutral one. Concerning the seasonal cycle of the surface albedo, it is demonstrated that this effect enhances shortwave cooling in periods when snow dominates the surface and potentially weakens the cooling by optically thin clouds during the summertime melting season. These findings suggest that the surface-albedo–cloud interaction should be considered in global climate models and in long-term studies to obtain a realistic estimate of the shortwave CRF to quantify the role of clouds in Arctic amplification.

Description: As knowledge about the cirrus clouds in the lower stratosphere is limited, reliable long-term measurements are needed to assess their characteristics, radiative impact and important role in upper troposphere and lower stratosphere (UTLS) chemistry. We used 6 years (2006–2012) of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measurements to investigate the global and seasonal distribution of stratospheric cirrus clouds and compared the MIPAS results with results derived from the latest version (V4.x) of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data. For the identification of stratospheric cirrus clouds, precise information on both the cloud top height (CTH) and the tropopause height is crucial. Here, we used lapse rate tropopause heights estimated from the ERA-Interim global reanalysis. Considering the uncertainties of the tropopause heights and the vertical sampling grid, we define CTHs more than 0.5 km above the tropopause as stratospheric for CALIPSO data. For MIPAS data, we took into account the coarser vertical sampling grid and the broad field of view so that we considered cirrus CTHs detected more than 0.75 km above the tropopause as stratospheric. Further sensitivity tests were conducted to rule out sampling artefacts in MIPAS data. The global distribution of stratospheric cirrus clouds was derived from night-time measurements because of the higher detection sensitivity of CALIPSO. In both data sets, MIPAS and CALIPSO, the stratospheric cirrus cloud occurrence frequencies are significantly higher in the tropics than in the extra-tropics. Tropical hotspots of stratospheric cirrus clouds associated with deep convection are located over equatorial Africa, South and Southeast Asia, the western Pacific, and South America. Stratospheric cirrus clouds were more often detected in December–February (15 %) than June–August (8 %) in the tropics (±20∘). At northern and southern middle latitudes (40–60∘), MIPAS observed about twice as many stratospheric cirrus clouds (occurrence frequencies of 4 %–5 % for MIPAS rather than about 2 % for CALIPSO). We attribute more frequent observations of stratospheric cirrus clouds with MIPAS to the higher detection sensitivity of the instrument to optically thin clouds. In contrast to the difference between daytime and night-time occurrence frequencies of stratospheric cirrus clouds by a factor of about 2 in zonal means in the tropics (4 % and 10 %, respectively) and at middle latitudes for CALIPSO data, there is little diurnal cycle in MIPAS data, in which the difference of occurrence frequencies in the tropics is about 1 percentage point in zonal mean and about 0.5 percentage point at middle latitudes. The difference between CALIPSO day and night measurements can also be attributed to their differences in detection sensitivity. Future work should focus on better understanding the origin of the stratospheric cirrus clouds and their impact on radiative forcing and climate.

Description: Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be assumed and is hard to quantify. We present a methodology to produce a weighted-model ensemble projection, accounting for model performance and model independence. Model weights are calculated by comparing model hindcasts to a selection of metrics chosen for their physical relevance to the process or phenomena of interest. This weighting methodology is applied to the Chemistry–Climate Model Initiative (CCMI) ensemble to investigate Antarctic ozone depletion and subsequent recovery. The weighted mean projects an ozone recovery to 1980 levels, by 2056 with a 95 % confidence interval (2052–2060), 4 years earlier than the most recent study. Perfect-model testing and out-of-sample testing validate the results and show a greater projective skill than a standard multi-model mean. Interestingly, the construction of a weighted mean also provides insight into model performance and dependence between the models. This weighting methodology is robust to both model and metric choices and therefore has potential applications throughout the climate and chemistry–climate modelling communities.

Description: Accurate reference spectroscopic information for the water molecule from the microwave to the near-ultraviolet is of paramount importance in atmospheric research. A semi-empirical potential energy surface for the ground electronic state of H216O has been created by refining almost 4000 experimentally determined energy levels. These states extend into regions with large values of rotational and vibrational excitation. For all states considered in our refinement procedure, which extend to 37 000 cm−1 and J=20 (total angular momentum), the average root-mean-square deviation is approximately 0.05 cm−1. This potential energy surface offers significant improvements when compared to recent models by accurately predicting states possessing high values of J. This feature will offer significant improvements in calculated line positions for high-temperature spectra where transitions between high J states become more prominent. Combining this potential with the latest dipole moment surface for water vapour, a line list has been calculated which extends reliably to 37 000 cm−1. Obtaining reliable results in the ultraviolet is of special importance as it is a challenging spectral region for the water molecule both experimentally and theoretically. Comparisons are made against several experimental sources of cross sections in the near-ultraviolet and discrepancies are observed. In the near-ultraviolet our calculations are in agreement with recent atmospheric retrievals and the upper limit obtained using broadband spectroscopy by Wilson et al. (2016, p. 194), but they do not support recent suggestions of very strong absorption in this region.

Description: North African dust reaches the southeastern United States every summer. Size-resolved dust mass measurements taken in Miami, Florida, indicate that more than one-half of the surface dust mass concentrations reside in particles with geometric diameters less than 2.1 µm, while vertical profiles of micropulse lidar depolarization ratios show dust reaching above 4 km during pronounced events. These observations are compared to the representation of dust in the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis and closely related Goddard Earth Observing System model version 5 (GEOS-5) Forward Processing (FP) aerosol product, both of which assimilate satellite-derived aerosol optical depths using a similar protocol and inputs. These capture the day-to-day variability in aerosol optical depth well, in a comparison to an independent sun-photometer-derived aerosol optical depth dataset. Most of the modeled dust mass resides in diameters between 2 and 6 µm, in contrast to the measurements. Model-specified mass extinction efficiencies equate light extinction with approximately 3 times as much aerosol mass, in this size range, compared to the measured dust sizes. GEOS-5 FP surface-layer sea salt mass concentrations greatly exceed observed values, despite realistic winds and relative humidities. In combination, these observations help explain why, despite realistic total aerosol optical depths, (1) free-tropospheric model volume extinction coefficients are lower than those retrieved from the micro-pulse lidar, suggesting too-low model dust loadings in the free troposphere, and (2) model dust mass concentrations near the surface can be higher than those measured. The modeled vertical distribution of dust, when captured, is reasonable. Large, aspherical particles exceeding the modeled dust sizes are also occasionally present, but dust particles with diameters exceeding 10 µm contribute little to the measured total dust mass concentrations after such long-range transport. Remaining uncertainties warrant a further integrated assessment to confirm this study's interpretations.

Description: Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. Further uncertainties in the cloud structure arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean, where biomass burning aerosol is transported from the African continent. As the aerosol plume progresses across the southeast Atlantic Ocean, radiative heating within the aerosol layer has the potential to alter the thermodynamic environment and therefore the cloud structure; however, limited work has been done to quantify this along the trajectory of the aerosol plume in the region. The deployment of the first Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF1) in support of the Layered Atlantic Smoke Interactions with Clouds field campaign provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96∘ S, 14.35∘ W). Using observed profiles of temperature, humidity, and clouds from the field campaign alongside aerosol optical properties from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM), profiles of the radiative heating rate due to aerosols and clouds were computed. Radiative heating is also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Idealized experiments using the RRTM with and without aerosols and a range of values for the single-scattering albedo (SSA) demonstrate that shortwave (SW) heating within the aerosol layer above Ascension Island can locally range between 2 and 8 K d−1 depending on the aerosol optical properties, though impacts of the aerosol can be felt elsewhere in the atmospheric column. When considered under clear conditions, the aerosol has a cooling effect at the TOA, and based on the observed cloud properties at Ascension Island, the cloud albedo is not large enough to overcome this. Shortwave radiative heating due to biomass burning aerosol is not balanced by additional longwave (LW) cooling, and the net radiative impact results in a stabilization of the lower troposphere. However, these results are extremely sensitive to the single-scattering albedo assumptions in models.

Description: This paper addresses the question of how much uncertainties in CO2 fluxes over Australia can be reduced by assimilation of total-column carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite instrument. We apply a four-dimensional variational data assimilation system, based around the Community Multiscale Air Quality (CMAQ) transport-dispersion model. We ran a series of observing system simulation experiments to estimate posterior error statistics of optimized monthly-mean CO2 fluxes in Australia. Our assimilations were run with a horizontal grid resolution of 81 km using OCO-2 data for 2015. Based on four representative months, we find that the integrated flux uncertainty for Australia is reduced from 0.52 to 0.13 Pg C yr−1. Uncertainty reductions of up to 90 % were found at grid-point resolution over productive ecosystems. Our sensitivity experiments show that the choice of the correlation structure in the prior error covariance plays a large role in distributing information from the observations. We also found that biases in the observations would significantly impact the inverted fluxes and could contaminate the final results of the inversion. Biases in prior fluxes are generally removed by the inversion system. Biases in the boundary conditions have a significant impact on retrieved fluxes, but this can be mitigated by including boundary conditions in our retrieved parameters. In general, results from our idealized experiments suggest that flux inversions at this unusually fine scale will yield useful information on the carbon cycle at continental and finer scales.

Description: In order to track progress towards the global climate targets, the parties that signed the Paris Climate Agreement will regularly report their anthropogenic carbon dioxide (CO2) emissions based on energy statistics and CO2 emission factors. Independent evaluation of this self-reporting system is a fast-growing research topic. Here, we study the value of satellite observations of the column CO2 concentrations to estimate CO2 anthropogenic emissions with 5 years of the Orbiting Carbon Observatory-2 (OCO-2) retrievals over and around China. With the detailed information of emission source locations and the local wind, we successfully observe CO2 plumes from 46 cities and industrial regions over China and quantify their CO2 emissions from the OCO-2 observations, which add up to a total of 1.3 Gt CO2 yr−1 that accounts for approximately 13 % of mainland China's annual emissions. The number of cities whose emissions are constrained by OCO-2 here is 3 to 10 times larger than in previous studies that only focused on large cities and power plants in different locations around the world. Our satellite-based emission estimates are broadly consistent with the independent values from China's detailed emission inventory MEIC but are more different from those of two widely used global gridded emission datasets (i.e., EDGAR and ODIAC), especially for the emission estimates for the individual cities. These results demonstrate some skill in the satellite-based emission quantification for isolated source clusters with the OCO-2, despite the sparse sampling of this instrument not designed for this purpose. This skill can be improved by future satellite missions that will have a denser spatial sampling of surface emitting areas, which will come soon in the early 2020s.

Description: Aerosol–cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (Nd). Even though rigorous first-principle approaches exist to calculate Nd, the cloud and aerosol research community also relies on empirical approaches such as relating Nd to aerosol mass concentration. Here we analyze relationships between Nd and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 80 chemical species. Single- and multispecies log–log linear regressions were performed to predict Nd using chemical composition. Single-species regressions reveal that the species that best predicts Nd is total sulfate (Radj2=0.40). Multispecies regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multispecies regressions that produce the highest correlation with Nd was that most included sulfate (either total or non-sea-salt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed for examination of the effect of these environmental factors on the composition–Nd correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between Nd with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with Nd for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea-salt sulfate and sodium correlated best with Nd at cloud top, whereas iron and oxalate correlated best with Nd at cloud base.

Description: The aerosol mass spectrometer (AMS), combined with statistical methods such as positive matrix factorization (PMF), has greatly advanced the quantification of primary organic aerosol (POA) sources and total secondary organic aerosol (SOA) mass. However, the use of thermal vaporization and electron ionization yields extensive thermal decomposition and ionization-induced fragmentation, which limit chemical information needed for SOA source apportionment. The recently developed extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) provides mass spectra of the organic aerosol fraction with a linear response to mass and no thermal decomposition or ionization-induced fragmentation. However, the costs and operational requirements of online instruments make their use impractical for long-term or spatially dense monitoring applications. This challenge was overcome for AMS measurements by measuring re-nebulized water extracts from ambient filter samples. Here, we apply the same strategy for EESI-TOF measurements of 1 year of 24 h filter samples collected approximately every fourth day throughout 2013 at an urban site. The nebulized water extracts were measured simultaneously with an AMS. The application of positive matrix factorization (PMF) to EESI-TOF spectra resolved seven factors, which describe water-soluble OA: less and more aged biomass burning aerosol (LABBEESI and MABBEESI, respectively), cigarette-smoke-related organic aerosol, primary biological organic aerosol, biogenic secondary organic aerosol, and a summer mixed oxygenated organic aerosol factor. Seasonal trends and relative contributions of the EESI-TOF OA sources were compared with AMS source apportionment factors, measured water-soluble ions, cellulose, and meteorological data. Cluster analysis was utilized to identify key factor-specific ions based on PMF. Both LABB and MABB contribute strongly during winter. LABB is distinguished by very high signals from C6H10O5 (levoglucosan and isomers) and C8H12O6, whereas MABB is characterized by a large number of CxHyOz and CxHyOzN species of two distinct populations: one with low H:C and high O:C and the other with high H:C and low O:C. Two oxygenated summertime SOA sources were attributed to terpene-derived biogenic SOA, a major summertime aerosol source in central Europe. Furthermore, a primary biological organic aerosol factor was identified, which was dominated by plant-derived fatty acids and correlated with free cellulose. The cigarette-smoke-related factor contained a high contribution of nicotine and high abundance of organic nitrate ions with low m∕z.