Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models

We examine the influence of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. The biases are the warm eastern tropical oceans, the double Intertropical Convergence Zone (ITCZ), the warm Southern Ocean, and the cold North Atlantic. Atmosphere resolution increases from ∼100–200 to ∼25–50 km, and ocean resolution increases from ∼1∘ (eddy-parametrized) to ∼0.25∘ (eddy-present). For one model, ocean resolution also reaches 1/12∘ (eddy-rich). The ensemble mean and individual fully coupled general circulation models and their atmosphere-only versions are compared with satellite observations and the ERA5 reanalysis over the period 1980–2014. The four studied biases appear in all the low-resolution coupled models to some extent, although the Southern Ocean warm bias is the least persistent across individual models. In the ensemble mean, increased resolution reduces the surface warm bias and the associated cloud cover and precipitation biases over the eastern tropical oceans, particularly over the tropical South Atlantic. Linked to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double-ITCZ bias is also reduced with increased resolution. The Southern Ocean warm bias increases or remains unchanged at higher resolution, with small reductions in the regional cloud cover and net cloud radiative effect biases. The North Atlantic cold bias is also reduced at higher resolution, albeit at the expense of a new warm bias that emerges in the Labrador Sea related to excessive ocean deep mixing in the region, especially in the ORCA025 ocean model. Overall, the impact of increased resolution on the surface temperature biases is model-dependent in the coupled models. In the atmosphere-only models, increased resolution leads to very modest or no reduction in the studied biases. Thus, both the coupled and atmosphere-only models still show large biases in tropical precipitation and cloud cover, and in midlatitude zonal winds at higher resolutions, with little change in their global biases for temperature, precipitation, cloud cover, and net cloud radiative effect. Our analysis finds no clear reductions in the studied biases due to the increase in atmosphere resolution up to 25–50 km, in ocean resolution up to 0.25∘, or in both. Our study thus adds to evidence that further improved model physics, tuning, and even finer resolutions might be necessary.

Contrasting source contributions of Arctic black carbon to atmospheric concentrations, deposition flux, and atmospheric and snow radiative effects

Black carbon (BC) particles in the Arctic contribute to rapid warming of the Arctic by heating the atmosphere and snow and ice surfaces. Understanding the source contributions to Arctic BC is therefore important, but they are not well understood, especially those for atmospheric and snow radiative effects. Here we estimate simultaneously the source contributions of Arctic BC to near-surface and vertically integrated atmospheric BC mass concentrations (MBC_SRF and MBC_COL), BC deposition flux (MBC_DEP), and BC radiative effects at the top of the atmosphere and snow surface (REBC_TOA and REBC_SNOW), and show that the source contributions to these five variables are highly different. In our estimates, Siberia makes the largest contribution to MBC_SRF, MBC_DEP, and REBC_SNOW in the Arctic (defined as > 70° N), accounting for 70 %, 53 %, and 43 %, respectively. In contrast, Asia’s contributions to MBC_COL and REBC_TOA are largest, accounting for 38 % and 45 %, respectively. In addition, the contributions of biomass burning sources are larger (24−34 %) to MBC_DEP, REBC_TOA, and REBC_SNOW, which are highest from late spring to summer, and smaller (4.2−14 %) to MBC_SRF and MBC_COL, whose concentrations are highest from winter to spring. These differences in source contributions to these five variables are due to seasonal variations in BC emission, transport, and removal processes and solar radiation, as well as to differences in radiative effect efficiency (radiative effect per unit BC mass) among sources. Radiative effect efficiency varies by a factor of up to 4 among sources (1465−5439 W g–1) depending on lifetimes, mixing states, and heights of BC and seasonal variations of emissions and solar radiation. As a result, source contributions to radiative effects and mass concentrations (i.e., REBC_TOA and MBC_COL, respectively) are substantially different. The results of this study demonstrate the importance of considering differences in the source contributions of Arctic BC among mass concentrations, deposition, and atmospheric and snow radiative effects for accurate understanding of Arctic BC and its climate impacts.

Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

The Surface Longwave Cloud Radiative Effect derived from Space Lidar Observations

Clouds warm the surface in the longwave (LW) and this warming effect can be quantified through the surface LW cloud radiative effect (CRE). The global surface LW CRE is estimated using long-term observations from space-based radiometers (2000–2021) but has some bias over continents and icy surfaces. It is also estimated globally using the combination of radar, lidar and space-based radiometer over the 5–year period ending in 2011. To develop a more reliable long time series of surface LW CRE over continental and icy surfaces, we propose new estimates of the global surface LW CRE from space-based lidar observations. We show from 1D atmospheric column radiative transfer calculations, that surface LW CRE linearly decreases with increasing cloud altitude. These computations allow us to establish simple relationships between surface LW CRE, and five cloud properties that are well observed by the CALIPSO space-based lidar: opaque cloud cover and altitude, and thin cloud cover, altitude, and emissivity. We use these relationships to retrieve the surface LW CRE at global scale over the 2008–2020 time period (27 Wm−2). We evaluate this new surface LW CRE product by comparing it to existing satellite-derived products globally on instantaneous collocated data at footprint scale and on global averages, as well as to ground-based observations at specific locations. Our estimate appears to be an improvement over others as it appropriately capture the surface LW CRE annual variability over bright polar surfaces and it provides a dataset of more than 13 years long.

Mechanisms of hydrological responses to volcanic eruptions in the Asian monsoon and westerlies-dominated subregions

Explosive volcanic eruptions affect surface climate especially in monsoon regions, but responses vary in different regions and to volcanic aerosol injection (VAI) in different hemispheres. Here we use six ensemble members from last millennium experiment of the Coupled Model Intercomparison Project Phase 5, to investigate the mechanism of regional hydrological responses to different hemispheric VAI in the Asian monsoon region (AMR). It brings a significant drying effect over the AMR after northern hemisphere VAI (NHVAI), spatially, a distinct “wet get drier, dry gets wetter” response pattern emerges with significant drying effect in the wettest area (RWA) but significant wetting effect in the driest area (RDA) of the AMR. After southern hemisphere VAI (SHVAI), it shows a significant wetting effect over the AMR, but spatial response pattern is not that clear due to small aerosol magnitude. The mechanism of the hydrological impact relates to the indirect change of atmospheric circulation due to the direct radiative effect of volcanic aerosols. The decreased thermal contrast between the land and the ocean after NHVAI results in weakened EASM and SASM. This changes the moisture transport and cloud formation in the monsoon and westerlies-dominated subregions. The subsequent radiative effect and physical feedbacks of local clouds lead to different drying and wetting effects in different areas. Results here indicate that future volcanic eruptions may alleviate the uneven distribution of precipitation in the AMR, which should be considered in the near-term decadal prediction and future strategy of local adaptation to global warming. The local hydrological responses and mechanisms found here can also provide reference to stratospheric aerosol engineering.

Measurement report: The importance of biomass burning in light extinction and direct radiative effect of urban aerosol during the COVID-19 lockdown in China

To mitigate climate change in China, a better understanding of optical properties of aerosol is required due to the complexity in emission sources. Here, an intensive real-time measurement was conducted in an urban area of China before and during the lockdown of Coronavirus Disease 2019 (COVID-19), to explore the impacts of anthropogenic activities on aerosol light extinction and direct radiative effect (DRE). The mean light extinction coefficient (bext) reduced from 774.7 ± 298.1 Mm−1 during the normal period to 544.3 ± 179.4 Mm−1 during the lockdown period. The generalized addictive model analysis indicated that the large decline of bext (29.7 %) was entirely attributed to the sharp reductions in anthropogenic emissions. Chemical calculation of bext based on the ridge regression analysis showed that organic aerosol (OA) was the largest contributor to bext in both periods (45.1–61.4 %), and contributions of two oxygenated OAs to bext increased by 3.0–14.6 % during the lockdown. A hybrid environmental receptor model combining with chemical and optical variables identified six sources of bext. It was found that bext from traffic-related emission, coal combustion, fugitive dust, nitrate plus secondary OA (SOA) source, and sulfate plus SOA source decreased by 21.4–97.9 % in the lockdown, whereas bext from biomass burning increased by 27.1 % mainly driven by undiminished needs of residential cooking and heating. The atmospheric radiative transfer model was further used to illustrate that biomass burning instead of traffic-related emission became the largest positive effect (10.0 ± 10.9 W m−2) on aerosol DRE in the atmosphere during the lockdown. Our study provides insights into aerosol bext and DRE from anthropogenic sources, and the results implied the importance of biomass burning for tackling climate change in China in the future.