Stratospheric sulfate geoengineering could enhance the terrestrial photosynthesis rate

Stratospheric sulfate geoengineering could impact the terrestrial carbon cycle by enhancing the carbon sink. With an 8 Tg yr−1 injection of SO2 to produce a stratospheric aerosol cloud to balance anthropogenic radiative forcing from the Representative Concentration Pathway 6.0 (RCP6.0) scenario, we conducted climate model simulations with the Community Earth System Model – the Community Atmospheric Model 4 fully coupled to tropospheric and stratospheric chemistry (CAM4–chem). During the geoengineering period, as compared to RCP6.0, land-averaged downward visible (300–700 nm) diffuse radiation increased 3.2 W m−2 (11 %). The enhanced diffuse radiation combined with the cooling increased plant photosynthesis by 0.07 ± 0.02 µmol C m−2 s−1, which could contribute to an additional 3.8 ± 1.1 Gt C yr−1 global gross primary productivity without explicit nutrient limitation. This increase could potentially increase the land carbon sink. Suppressed plant and soil respiration due to the cooling would reduce natural land carbon emission and therefore further enhance the terrestrial carbon sink during the geoengineering period. This potentially beneficial impact of stratospheric sulfate geoengineering would need to be balanced by a large number of potential risks in any future decisions about the implementation of geoengineering

Improved cloud-phase determination of low-level liquid and mixed-phase clouds by enhanced polarimetric lidar

The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system nonlinear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud-phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud-phase fractional occurrence estimates on the order of 30 % causing errors in attribution of cloud radiative effects on the order of 10–30 %. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses co-located sensors at Summit to evaluate this method. Enhanced measurements are achieved in this work with non-orthogonal polarization retrievals as well as analog and photon counting detection facilitating a more complete attribution of radiative effects linked to cloud properties

Correcting for mobile X-band weather radar tilt using solar interference

Precise knowledge of the antenna pointing direction is a key facet to ensure the accuracy of observations from scanning weather radars. The sun is an often-used reference point to aid accurate alignment of weather radar systems and is particularly useful when observed as interference during normal scanning operations. In this study, we combine two online solar interference approaches to determine the pointing accuracy of an X-band mobile weather radar system deployed for 26 months in northern England (54.517°N, 3.615°W). During the deployment, several shifts in the tilt of the radar system are diagnosed between site visits. One extended period of time (>11 months) is shown to have a changing tilt that is independent of human intervention. To verify the corrections derived from this combined approach, quantitative precipitation estimates (QPEs) from the radar system are compared to surface observations: an approach that takes advantage of the variations in the magnitude of partial beam blockage corrections required due to tilting of the radar system close to mountainous terrain. The observed improvements in QPE performance after correction support the use of the derived tilt corrections for further applications using the corrected dataset. Finally, recommendations for future deployments are made, with particular focus on higher latitudes where solar interference spikes show more seasonality than those at mid-latitudes

Anatomy of wintertime ozone associated with oil and natural gas extraction activity in Wyoming and Utah

Winter maximum daily 8-hour average (MDA8) ozone concentrations in the Upper Green River Basin, Wyoming (UGRBWY) and the Uintah Basin, Utah (UBUT) have frequently exceeded 100 ppb in January, February and March, in the past few years. Such levels are well above the U.S. air quality standard of 75 ppb. In these two remote basins in the Rockies, local ozone precursor emissions result from intense oil and gas extraction activities that release methane, volatile organic compounds (VOCs), and nitrogen oxides (NOx) to the atmosphere. These emissions become trapped beneath a stable and shallow (~50–200 m) boundary layer maintained in low wind conditions. Wintertime surface ozone formation conditions are more likely in the UBUT than in the UGRBWY as the topography of the UBUT is an enclosed basin whereas the UGRBWY is open on its southern perimeter thus allowing for more air turnover. With snow-covered ground, high ozone events regularly begin in mid-December and last into early March in the UBUT whereas they usually do not begin in earnest until about a month later in the UGRBWY and may persist until mid-March. Winters without snow cover and the accompanying cold pool meteorological conditions do not experience high ozone events in either basin. For nine years with ozone observations in the UGRBWY (2005–2013) and four in the UBUT (2010–2013), all years with adequate (≥6 inches) and persistent snow cover, experienced days with ozone values ≥75 ppb except in 2012 in the UGRBWY when persistent high wind (>5 m/s) conditions were prevalent. Year to year differences in the occurrences of high ozone episodes appear to be driven primarily by differing meteorological conditions rather than by variations in ozone precursor levels

Assessing precipitation from a dual-polarisation X-band radar campaign using the Grid-to-Grid hydrological model

A set of Quantitative Precipitation Estimates (QPEs) from a dual-polarisation X-band radar observation campaign in a mountainous area of Northern Scotland is assessed with reference to observed river flows as well as being compared to estimates from the UK C-band radar and raingauge networks. Employing estimation methods of varying complexity, the X-band QPEs are trialled as alternative inputs to Grid-to-Grid (G2G), a distributed hydrological model, to produce simulated river flows for comparison with observations. This hydrological assessment complements and extends a previous meteorological assessment that used point raingauge data only. Precipitation estimates for two periods over the observation campaign in 2016 (March to April and June to August) are assessed. During the second period, increased incorporation of dual-polarisation variables into the radar processing chain is found to be of considerable benefit, whereas during the first period the low height of the melting layer often restricts their use. As a result of the complex topography in Northern Scotland, the Lowest Usable Elevation (LUE) of the X-band radar observations is found to be a stronger indicator of the hydrological model performance than range from the radar. For catchments with an LUE of less than 3 km, the best X-band QPE typically performs better for modelling river flow than using an estimate from the UK C-band radar network. The hydrological assessment framework used here brings fresh insights into the performance of the different QPEs, as well as providing a stimulus for targeted improvements to dual-polarisation radar-based QPEs that have wider relevance beyond the case study situation

Global volcanic aerosol properties derived from emissions, 1990-2014, using CESM1(WACCM)

Accurate representation of global stratospheric aerosols from volcanic and non-volcanic sulfur emissions is key to understanding the cooling effects and ozone-losses that may be linked to volcanic activity. Attribution of climate variability to volcanic activity is of particular interest in relation to the post-2000 slowing in the rate of global average temperature increases. We have compiled a database of volcanic SO2 emissions and plume altitudes for eruptions from 1990 to 2014, and developed a new prognostic capability for simulating stratospheric sulfate aerosols in the Community Earth System Model (CESM). We used these combined with other non-volcanic emissions of sulfur sources to reconstruct global aerosol properties from 1990 to 2014. Our calculations show remarkable agreement with ground-based lidar observations of stratospheric aerosol optical depth (SAOD), and with in situ measurements of stratospheric aerosol surface area density (SAD). These properties are key parameters in calculating the radiative and chemical effects of stratospheric aerosols. Our SAOD calculations represent a clear improvement over available satellite-based analyses, which generally ignore aerosol extinction below 15 km, a region that can contain the vast majority of stratospheric aerosol extinction at mid- and high-latitudes. Our SAD calculations greatly improve on that provided for the Chemistry-Climate Model Initiative, which misses about 60% of the SAD measured in situ on average during both volcanically active and volcanically quiescent periods

Meteorological and cloud conditions during the Arctic Ocean 2018 expedition

The Arctic Ocean 2018 (AO2018) took place in the central Arctic Ocean in August and September 2018 on the Swedish icebreaker Oden. An extensive suite of instrumentation provided detailed measurements of surface water chemistry and biology, sea ice and ocean physical and biogeochemical properties, surface exchange processes, aerosols, clouds, and the state of the atmosphere. The measurements provide important information on the coupling of the ocean and ice surface to the atmosphere and in particular to clouds. This paper provides (i) an overview of the synoptic-scale atmospheric conditions and their climatological anomaly to help interpret the process studies and put the detailed observations from AO2018 into a larger context, both spatially and temporally; (ii) a statistical analysis of the thermodynamic and near-surface meteorological conditions, boundary layer, cloud, and fog characteristics; and (iii) a comparison of the results to observations from earlier Arctic Ocean expeditions – in particular AOE1996 (Arctic Ocean Expedition 1996), SHEBA (Surface Heat Budget of the Arctic Ocean), AOE2001 (Arctic Ocean Experiment 2001), ASCOS (Arctic Summer Cloud Ocean Study), ACSE (Arctic Clouds in Summer Experiment), and AO2016 (Arctic Ocean 2016) – to provide an assessment of the representativeness of the measurements. The results show that near-surface conditions were broadly comparable to earlier experiments; however the thermodynamic vertical structure was quite different. An unusually high frequency of well-mixed boundary layers up to about 1 km depth occurred, and only a few cases of the “prototypical” Arctic summer single-layer stratocumulus deck were observed. Instead, an unexpectedly high amount of multiple cloud layers and mid-level clouds were present throughout the campaign. These differences from previous studies are related to the high frequency of cyclonic activity in the central Arctic in 2018

Controls on surface aerosol particle number concentrations and aerosol-limited cloud regimes over the central Greenland Ice Sheet

This study presents the first full annual cycle (2019–2020) of ambient surface aerosol particle number concentration measurements (condensation nuclei > 20 nm, N20) collected at Summit Station (Summit), in the centre of the Greenland Ice Sheet (72.58∘ N, −38.45∘ E; 3250 ma.s.l.). The mean surface concentration in 2019 was 129 cm−3, with the 6 h mean ranging between 1 and 1441 cm−3. The highest monthly mean concentrations occurred during the late spring and summer, with the minimum concentrations occurring in February (mean: 18 cm−3). High-N20 events are linked to anomalous anticyclonic circulation over Greenland and the descent of free-tropospheric aerosol down to the surface, whereas low-N20 events are linked to anomalous cyclonic circulation over south-east Greenland that drives upslope flow and enhances precipitation en route to Summit. Fog strongly affects particle number concentrations, on average reducing N20 by 20 % during the first 3 h of fog formation. Extremely-low-N20 events (< 10 cm−3) occur in all seasons, and we suggest that fog, and potentially cloud formation, can be limited by low aerosol particle concentrations over central Greenland

Evaluating Arctic meteorology modelled with the Unified Model and Integrated Forecasting System

By synthesising remote-sensing measurements made in the central Arctic into a model-gridded Cloudnet cloud product, we evaluate how well the Met Office Unified Model (UM) and the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) capture Arctic clouds and their associated interactions with the surface energy balance and the thermodynamic structure of the lower troposphere. This evaluation was conducted using a 4-week observation period from the Arctic Ocean 2018 expedition, where the transition from sea ice melting to freezing conditions was measured. Three different cloud schemes were tested within a nested limited-area model (LAM) configuration of the UM – two regionally operational single-moment schemes (UM_RA2M and UM_RA2T) and one novel double-moment scheme (UM_CASIM-100) – while one global simulation was conducted with the IFS, utilising its default cloud scheme (ECMWF_IFS). Consistent weaknesses were identified across both models, with both the UM and IFS overestimating cloud occurrence below 3 km. This overestimation was also consistent across the three cloud configurations used within the UM framework, with >90 % mean cloud occurrence simulated between 0.15 and 1 km in all the model simulations. However, the cloud microphysical structure, on average, was modelled reasonably well in each simulation, with the cloud liquid water content (LWC) and ice water content (IWC) comparing well with observations over much of the vertical profile. The key microphysical discrepancy between the models and observations was in the LWC between 1 and 3 km, where most simulations (all except UM_RA2T) overestimated the observed LWC. Despite this reasonable performance in cloud physical structure, both models failed to adequately capture cloud-free episodes: this consistency in cloud cover likely contributes to the ever-present near-surface temperature bias in every simulation. Both models also consistently exhibited temperature and moisture biases below 3 km, with particularly strong cold biases coinciding with the overabundant modelled cloud layers. These biases are likely due to too much cloud-top radiative cooling from these persistent modelled cloud layers and were consistent across the three UM configurations tested, despite differences in their parameterisations of cloud on a sub-grid scale. Alarmingly, our findings suggest that these biases in the regional model were inherited from the global model, driving a cause–effect relationship between the excessive low-altitude cloudiness and the coincident cold bias. Using representative cloud condensation nuclei concentrations in our double-moment UM configuration while improving cloud microphysical structure does little to alleviate these biases; therefore, no matter how comprehensive we make the cloud physics in the nested LAM configuration used here, its cloud and thermodynamic structure will continue to be overwhelmingly biased by the meteorological conditions of its driving model