Mechanisms of multiple, anomalous melt events at Summit Station, Greenland in summer 2019

<p>Above freezing temperatures and melting surface snow have occurred at Summit Station (3250 m asl), atop the Greenland Ice Sheet, only five times in the last 800 years, including once in 2012 and twice 2019 (June 12; July 29-31). Such events are linked to southerly advection of continental air that cross the North Atlantic as atmospheric rivers (ARs). The specific mechanisms that are responsible for these rare events appear to be varied and complex. While the 2012 event was supported by anomalous cloud forcing caused by thin, liquid-bearing clouds, the two events in 2019 occurred under both clear and cloudy conditions. The net surface radiation measured during the 2019 events was actually similar between clear (~47 W m<sup>-2</sup>) and cloudy (~52 W m<sup>-2</sup>) conditions, and, surprisingly, these values are unremarkable for afternoon conditions in summer at Summit Station.</p><p>Observations from the ICECAPS-ACE project at Summit Station (including radiative and turbulent fluxes, surface skin temperature, snow pit stratigraphy) allow a process-level analysis of the mechanisms that transfer energy from the AR events into local melting. By combining the measurements with a finite-volume diffusion model of the sub-surface temperature field, we find that a concentration of energy in the surface layer caused by converging fluxes toward the surface from both directions (upward from within the snowpack and downward from the atmosphere) led to initiation of both of the 2019 melt events. Thus, coupling between the atmosphere and the snowpack, and the timing of atmospheric fluctuations, appear important, and are suggestive that preconditioning of the snowpack from events prior to the day of melt may be a factor. Both sensible and latent heat fluxes were relatively small during these melt events while several regimes of commonly occurring radiative processes were observed. Under cloudy conditions, longwave cloud radiative forcing played a role, while under clear skies, lower surface albedo was sufficient to make up the difference of the absence of cloud forcing. For example, during the July 2019 event, the surface snow albedo decreased significantly from 0.86 to 0.80, which facilitated greater absorption of solar radiation. These findings are supportive of the notion that longwave processes are triggers of melt while shortwave processes persist melt. he co-dependent roles of the radiative and subsurface heat fluxes during the 2019 events suggest that the rarity of melt at Summit Station may be explained by preconditioning processes, and that a particular sequence of events over several days leading up to melt may be important.</p>

Effects of marine organic aerosols as sources of immersion-mode ice-nucleating particles on high-latitude mixed-phase clouds

Mixed-phase clouds are frequently observed in high-latitude regions and have important impacts on the surface energy budget and regional climate. Marine organic aerosol (MOA), a natural source of aerosol emitted over ∼ 70 % of Earth's surface, may significantly modify the properties and radiative forcing of mixed-phase clouds. However, the relative importance of MOA as a source of ice-nucleating particles (INPs) in comparison to mineral dust, and MOA's effects as cloud condensation nuclei (CCN) and INPs on mixed-phase clouds are still open questions. In this study, we implement MOA as a new aerosol species into the Community Atmosphere Model version 6 (CAM6), the atmosphere component of the Community Earth System Model version 2 (CESM2), and allow the treatment of aerosol–cloud interactions of MOA via droplet activation and ice nucleation. CAM6 reproduces observed seasonal cycles of marine organic matter at Mace Head and Amsterdam Island when the MOA fraction of sea spray aerosol in the model is assumed to depend on sea spray biology but fails when this fraction is assumed to be constant. Model results indicate that marine INPs dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer, while dust INPs are more abundant elsewhere. By acting as CCN, MOA exerts a shortwave cloud forcing change of −2.78 W m−2 over the Southern Ocean in the austral summer. By acting as INPs, MOA enhances the longwave cloud forcing by 0.35 W m−2 over the Southern Ocean in the austral winter. The annual global mean net cloud forcing changes due to CCN and INPs of MOA are −0.35 and 0.016 W m−2, respectively. These findings highlight the vital importance for Earth system models to consider MOA as an important aerosol species for the interactions of biogeochemistry, hydrological cycle, and climate change.

Cirrus Cloud Top-of-the-Atmosphere Net Daytime Forcing in the Alaskan Subarctic from Ground-Based MPLNET Monitoring

Cirrus cloud daytime top-of-the-atmosphere radiative forcing (TOA CRF) is estimated for a 2-yr NASA Micro-Pulse Lidar Network (532 nm; MPLNET) dataset collected at Fairbanks, Alaska. Two-year-averaged daytime TOA CRF is estimated to be between −1.08 and 0.78 W·m−2 (from −0.49 to 1.10 W·m−2 in 2017, and from −1.67 to 0.47 W·m−2 in 2018). This subarctic study completes a now trilogy of MPLNET ground-based cloud forcing investigations, following midlatitude and tropical studies by Campbell et al. at Greenbelt, Maryland, and Lolli et al. at Singapore. Campbell et al. hypothesize a global meridional daytime TOA CRF gradient that begins as positive at the equator (2.20–2.59 W·m−2 over land and from −0.46 to 0.42 W·m−2 over ocean at Singapore), becomes neutral in the midlatitudes (0.03–0.27 W·m−2 over land in Maryland), and turns negative moving poleward. This study does not completely confirm Campbell et al., as values are not found as exclusively negative. Evidence in historical reanalysis data suggests that daytime cirrus forcing in and around the subarctic likely once was exclusively negative. Increasing tropopause heights, inducing higher and colder cirrus, have likely increased regional forcing over the last 40 years. We hypothesize that subarctic interannual cloud variability is likely a considerable influence on global cirrus cloud forcing sensitivity, given the irregularity of polar versus midlatitude synoptic weather intrusions. This study and hypothesis lay the basis for an extrapolation of these MPLNET experiments to satellite-based lidar cirrus cloud datasets.

Uncertainty quantification based cloud parameterization sensitivity analysis in the NCAR community atmosphere model

Using uncertainty quantification techniques, we carry out a sensitivity analysis of a large number (17) of parameters used in the NCAR CAM5 cloud parameterization schemes. The LLNL PSUADE software is used to identify the most sensitive parameters by performing sensitivity analysis. Using Morris One-At-a-Time (MOAT) method, we find that the simulations of global annual mean total precipitation, convective, large-scale precipitation, cloud fractions (total, low, mid, and high), shortwave cloud forcing, longwave cloud forcing, sensible heat flux, and latent heat flux are very sensitive to the threshold-relative-humidity-for-stratiform-low-clouds ($$rhminl)$$ r h m i n l ) and the auto-conversion-size-threshold-for-ice-to-snow $$\left( {dcs} \right).$$ dcs . The seasonal and regime specific dependence of some parameters in the simulation of precipitation is also found for the global monsoons and storm track regions. Through sensitivity analysis, we find that the Somali jet strength and the tropical easterly jet associated with the south Asian summer monsoon (SASM) show a systematic dependence on $$dcs$$ dcs and $$rhminl$$ rhminl . The timing of the withdrawal of SASM over India shows a monotonic increase (delayed withdrawal) with an increase in $$dcs$$ dcs . Overall, we find that $$rhminl$$ rhminl , $$dcs$$ dcs , $$ai,$$ a i , and $$as$$ as are the most sensitive cloud parameters and thus are of high priority in the model tuning process, in order to reduce uncertainty in the simulation of past, present, and future climate.

Effects of Marine Organic Aerosols as Sources of Immersion-Mode Ice Nucleating Particles on High Latitude Mixed-Phase Clouds

Mixed-phase clouds are frequently observed in the Arctic, Antarctic, and over the Southern Ocean, and have important impacts on the surface energy budget and regional climate. Marine organic aerosol (MOA), a natural source of aerosol emitted over ~ 70 % of Earth’s surface, may significantly modify the properties and radiative forcing of mixed-phase clouds. However, the relative importance of MOA as a source of ice nucleating particles (INPs) in comparison to mineral dust, and its effects as cloud condensation nuclei (CCN) and INPs on mixed-phase clouds are still open questions. In this study, we implement MOA as a new aerosol species into the Community Atmosphere Model version 6 (CAM6), the atmosphere component of the Community Earth System Model version 2 (CESM2), and allow the treatments of aerosol-cloud interactions of MOA via droplet activation and ice nucleation. CAM6 reproduces observed seasonal cycles of marine organic matter at Mace Head and Amsterdam Island when the MOA fraction of sea spray aerosol in the model is assumed to depend on sea spray biology, but fails when this fraction is assumed to be constant. Model results indicate that marine INPs dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer, while dust INPs are more abundant elsewhere. By acting as CCN, MOA exerts a shortwave cloud forcing change of −2.78 W m–2 over the Southern Ocean in the austral summer. By acting as INPs, MOA enhances the longwave cloud forcing by 0.35 W m–2 over the Southern Ocean in the austral winter. The annual global mean net cloud forcing changes due to CCN and INPs of MOA are −0.35 and 0.016 W m–2, respectively. These findings highlight the vital importance of Earth System Models to consider the MOA as an important aerosol species for the interactions of biogeochemistry, hydrological cycle, and climate change.

Comparing different generations of idealized solar geoengineering simulations in the Geoengineering Model Intercomparison Project (GeoMIP)

Solar geoengineering has been receiving increased attention in recent years as a potential temporary solution to offset global warming. One method of approximating global-scale solar geoengineering in climate models is via solar reduction experiments. Two generations of models in the Geoengineering Model Intercomparison Project (GeoMIP) have now simulated offsetting a quadrupling of the CO2 concentration with solar reduction. This simulation is artificial and designed to elicit large responses in the models. Here we show that energetics, temperature, and hydrological cycle changes in this experiment are statistically indistinguishable between the two ensembles. Of the variables analyzed here, the only major differences involve highly parameterized and uncertain processes, such as cloud forcing or terrestrial net primary productivity. We conclude that despite numerous structural differences and uncertainties in models over the past 20 years, including an increase in climate sensitivity in the latest generation of models, broad conclusions about the climate response to global solar dimming remain robust.

A Decomposition of Feedback Contributions to the Arctic Temperature Biases in the CMIP5 Climate Models

<p>The systematic temperature biases over the Arctic Sea in the CMIP5 models are decomposed into partial biases due to physical and dynamical processes, based upon the climate feedback-responses analysis method (CFRAM). In the frame of the CFRAM, physical processes are also divided into water vapor, cloud, and albedo feedbacks. Though the Arctic temperature biases largely depend on models, considerable cold bias are found in most of models and ensemble mean. Overall, temperature biases corresponding to physical and dynamical processes tend to cancel each other out and total biases equal to their sums are geographically similar to those related to physical processes. For the physics-related biases, a contribution of albedo feedback is the largest, followed by cloud and water vapor feedbacks in turn. Quantitative contributions of the processes to temperature biases are evaluated from area-mean values over the entire Arctic Sea, Barents-Kara Sea, and Beaufort Sea. While relationships between total and partial biases over the Arctic Sea show the large model-dependency, in the local-scale, total temperature biases over Barents-Kara Sea and Beaufort Sea are made from consistent contributions among models. An overestimate (underestimate) of specific humidity and cloud fraction in models are responsible for an overall warm (cold) biases through longwave heating rates of the greenhouse effect. Shortwave cloud forcing by cloud fraction biases offsets a substantial part of biases related to longwave cloud forcing, while shortwave effect of specific humidity bias plays a minor role on water vapor feedback. The fact that geographical distribution of sea-ice biases is mostly opposite to that of partial temperature bias due to albedo feedback indicates that the biased simulation of sea-ice in models are the main contributors in albedo feedback.</p>

Evaluating Simulated Climate Patterns from theCMIP Archives Using Satellite and Reanalysis Datasets

An objective approach is presented for scoring coupled climate simulations through an evaluation against satellite and reanalysis datasets during the satellite era (i.e. since 1979). Here, the approach is described and applied to available Coupled Model Intercomparison Project (CMIP) archives and the Community Earth System Model Version 1 Large Ensemble archives, with the goal of benchmarking model performance and its evolution across CMIP generations. The approach adopted is designed to minimize the sensitivity of scores to internal variability, external forcings, and model tuning. Toward this end, models are scored based on pattern correlations of their simulated mean state, seasonal contrasts, and ENSO teleconnections. A broad range of feedback-relevant fields is considered and summarized on various timescales (climatology, seasonal, interannual) and physical realms (energy budget, water cycle, dynamics). Fields are also generally chosen for which observational uncertainty is small compared to model structural differences and error. Highest mean variable scores across models are reported for well-observed fields such as sea level pressure, precipitable water, and outgoing longwave radiation while the lowest scores are reported for 500 hPa vertical velocity, net surface energy flux, and precipitation minus evaporation. The fidelity of CMIP models is found to vary widely both within and across CMIP generations. Systematic increases in model fidelity across CMIP generations are identified with the greatest improvements in dynamic and energetic fields. Examples include 500 hPa eddy geopotential height and relative humidity, and shortwave cloud forcing. Improvements for ENSO scores are substantially greater than for the annual mean or seasonal contrasts. Analysis output data generated by this approach is made freely available online for a broad range of model ensembles, including the CMIP archives and various single-model large ensembles. These multi-model archives allow for an exploration of relationships between metrics across a range of simulations while the single-model large ensemble archives enable an estimation of the influence of internal variability on reported scores. The entire output archive, updated regularly, can be accessed at: http://webext.cgd.ucar.edu/Multi-Case/CMAT/index.html chosen for which observational uncertainty is small compared to model structural error. 20 Highest mean variable scores across models are reported for well-observed fields such as sea level pressure, precipitable water, and outgoing longwave radiation while the lowest scores are reported for 500 hPa vertical velocity, net surface energy flux, and precipitation minus evaporation. The fidelity of CMIP models is found to vary widely both within and across CMIP generations. CMATv1 scores report systematic increases in model fidelity across CMIP generations with the greatest improvements in dynamic and energetic fields. Examples include 500 hPa eddy geopotential height and relative humidity, 25 and shortwave cloud forcing. Improvements for ENSO scores are substantially greater than for the annual mean or seasonal contrasts. Analysis output data is made freely available online for a broad range of model ensembles, including the CMIP archives and various single-model large ensembles. These multi-model archives allow for an exploration of relationships between metrics 30 across a range of simulations while the single-model large ensemble archives enable an estimation of the influence of internal variability on CMATV1 scores. The entire CMATv1 archive, updated regularly, can be accessed at: http://webext.cgd.ucar.edu/Multi-Case/CMAT/index.html.

Investigating the sensitivity to resolving aerosol interactions in downscaling regional model experiments with WRFv3.8.1 over Europe

In this work we present a sensitivity study of eight WRF (Weather Research and Forecasting model) regional climate simulations for the EURO-CORDEX domain regarding aerosol implementation and their impact on European climate. The sensitivities differ in the aerosol properties (optical characteristics) and effects implemented (direct/indirect), as well as in the aerosol input data used (Tegen, MACv1, MACC, GOCART). Simulations have a resolution of 0.44° and are forced by the ERA-Interim reanalysis. A basic evaluation has been performed against ground (E-OBS) and satellite-based observational data (CMSAF Sarah, Clara). Implementation of the direct radiative effect of aerosol reduces the direct component of the incoming surface solar radiation by 20–30 % in all seasons, due to enhanced aerosol scattering. The diffuse shortwave component augments 30–40 % in summer and 5–8 % in winter, while downward shortwave radiation at the surface is attenuated by 3–8 %. The resulting aerosol radiative effect is negative and stronger in summer (−12 W/m2) than inwinter (−2 W/m2) due to a balance between the more negative direct aerosol effect (−17 to −5 W/m2) and positive changes in the cloud forcing (+5 W/m2) representing the semi-direct effect. We also show that modeling direct and indirect effects can lead to small changes in cloudiness, mainly regarding low-level clouds, and circulation anomalies in the lower and mid-troposphere, which in some cases can be statistically significant. Precipitation is not affected in a consistent pattern by the aerosol implementation and changes do not exceed ±10 %. Temperature, on the other hand, systematically decreases by −0.1 to −0.5 °C due to the direct effect with regional changes that can be up to −1.5 °C.