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At least 523 records · Page 29

Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage

Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.

Engineering↗

One-Pot Synthesis of Melamine Formaldehyde Resin-Derived N-Doped Porous Carbon for CO 2 Capture Application

The design and synthesis of porous carbons for CO 2 adsorption have attracted tremendous interest owing to the ever-soaring concerns regarding climate change and global warming. Herein, for the first time, nitrogen-rich porous carbon was prepared with chemical activation (KOH) of commercial melamine formaldehyde resin (MF) in a single step. It has been shown that the porosity parameters of the as-prepared carbons were successfully tuned by controlling the activating temperature and adjusting the amount of KOH. Thus, as-prepared N-rich porous carbon shows a large surface area of 1658 m 2 /g and a high N content of 16.07 wt%. Benefiting from the unique physical and textural features, the optimal sample depicted a CO 2 uptake of up to 4.95 and 3.30 mmol/g at 0 and 25 °C under 1 bar of pressure. More importantly, as-prepared adsorbents show great CO 2 selectivity over N 2 and outstanding recyclability, which was prominently important for CO 2 capture from the flue gases in practical application. An in-depth analysis illustrated that the synergetic effect of textural properties and surface nitrogen decoration mainly determined the CO 2 capture performance. However, the textural properties of carbons play a more important role than surface functionalities in deciding CO 2 uptake. In view of cost-effective synthesis, outstanding textural activity, and the high adsorption capacity together with good selectivity, this advanced approach becomes valid and convenient in fabricating a unique highly efficient N-rich carbon adsorbent for CO 2 uptake and separation from flue gases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrating Reanalysis and Satellite Cloud Information to Estimate Surface Downward Long-Wave Radiation

The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m –2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.

54 ENVIRONMENTAL SCIENCES↗

Warming of the Willamette River, 1850–present: the effects of climate change and river system alterations

Abstract. Using archival research methods, we recovered and combined data from multiple sources to produce a unique, 140-year record of daily water temperature (Tw) in the lower Willamette River, Oregon (1881–1890, 1941–present). Additional daily weather and river flow records from the 1850s onwards are used to develop and validate a statistical regression model of Tw for 1850–2020. The model simulates the time-lagged response of Tw to air temperature and river flow and is calibrated for three distinct time periods: the late 19th, mid-20th, and early 21st centuries. Results show that Tw has trended upwards at 1.1 ∘C per century since the mid-19th century, with the largest shift in January and February (1.3 ∘C per century) and the smallest in May and June (∼ 0.8 ∘C per century). The duration that the river exceeds the ecologically important threshold of 20 ∘C has increased by about 20 d since the 1800s, to about 60 d yr−1. Moreover, cold-water days below 2 ∘C have virtually disappeared, and the river no longer freezes. Since 1900, changes are primarily correlated with increases in air temperature (Tw increase of 0.81 ± 0.25 ∘C) but also occur due to alterations in the river system such as depth increases from reservoirs (0.34 ± 0.12 ∘C). Managed release of water affects Tw seasonally, with an average reduction of up to 0.56 ∘C estimated for September. River system changes have decreased variability (σ) in daily minimum Tw by 0.44 ∘C, increased thermal memory, reduced interannual variability, and reduced the response to short-term meteorological forcing (e.g., heat waves). These changes fundamentally alter the response of Tw to climate change, posing additional stressors on fauna.

54 ENVIRONMENTAL SCIENCES↗

Future precipitation increase constrained by climatological pattern of cloud effect

The fractional increase in global mean precipitation (?P ¯/P ¯) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, ?P ¯/P ¯ varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in ?P ¯/P ¯ stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). Here, by investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, we find that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of cloud shortwave effect. The observed pattern of cloud effect thus constrains both sensitivities and consequently constrains ?P ¯/P ¯. The 5%-95% uncertainty range of ?P ¯/P ¯ from 1979-2005 to 2080-2100 under the high-emission (moderate-emission) scenario is constrained from 6.34±3.53% (4.19±2.28%) in the raw ensemble-model projection to 7.03±2.59% (4.63±1.71%). The constraint thus suggests a higher most-likely ?P ¯/P ¯ and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

Zhou, Wenyu↗

Trading water for carbon in the future: Effects of elevated CO 2 and warming on leaf hydraulic traits in a semiarid grassland

Abstract The effects of climate change on plants and ecosystems are mediated by plant hydraulic traits, including interspecific and intraspecific variability of trait phenotypes. Yet, integrative and realistic studies of hydraulic traits and climate change are rare. In a semiarid grassland, we assessed the response of several plant hydraulic traits to elevated CO 2 (+200 ppm) and warming (+1.5 to 3°C; day to night). For leaves of five dominant species (three graminoids and two forbs), and in replicated plots exposed to 7 years of elevated CO 2 , warming, or ambient climate, we measured: stomatal density and size, xylem vessel size, turgor loss point, and water potential (pre‐dawn). Interspecific differences in hydraulic traits were larger than intraspecific shifts induced by elevated CO 2 and/or warming. Effects of elevated CO 2 were greater than effects of warming, and interactions between treatments were weak or not detected. The forbs showed little phenotypic plasticity. The graminoids had leaf water potentials and turgor loss points that were 10% to 50% less negative under elevated CO 2 ; thus, climate change might cause these species to adjust their drought resistance strategy away from tolerance and toward avoidance. The C4 grass also reduced allocation of leaf area to stomata under elevated CO 2 , which helps explain observations of higher soil moisture. The shifts in hydraulic traits under elevated CO 2 were not, however, simply due to higher soil moisture. Integration of our results with others' indicates that common species in this grassland are more likely to adjust stomatal aperture in response to near‐term climate change, rather than anatomical traits; this contrasts with apparent effects of changing CO 2 on plant anatomy over evolutionary time. Future studies should assess how plant responses to drought may be constrained by the apparent shift from tolerance (via low turgor loss point) to avoidance (via stomatal regulation and/or access to deeper soil moisture).

54 ENVIRONMENTAL SCIENCES↗

Multi-Frequency Analysis of Simulated versus Observed Variability in Tropospheric Temperature

Studies seeking to identify a human-caused global warming signal generally rely on climate model estimates of the “noise” of intrinsic natural variability. Assessing the reliability of these noise estimates is of critical importance. We evaluate here the statistical significance of differences between climate model and observational natural variability spectra for global-mean mid- to upper-tropospheric temperature (TMT). We use TMT information from satellites and large multimodel ensembles of forced and unforced simulations. Our main goal is to explore the sensitivity of model-versus-data spectral comparisons to a wide range of subjective decisions. These include the choice of satellite and climate model TMT datasets, the method for separating signal and noise, the frequency range considered, and the statistical model used to represent observed natural variability. Of particular interest is the amplitude of the interdecadal noise against which an anthropogenic tropospheric warming signal must be detected. We find that on time scales of 5–20 years, observed TMT variability is (on average) overestimated by the last two generations of climate models participating in the Coupled Model Intercomparison Project. This result is relatively insensitive to different plausible analyst choices, enhancing confidence in previous claims of detectable anthropogenic warming of the troposphere and indicating that these claims may be conservative. A further key finding is that two commonly used statistical models of short-term and long-term memory have deficiencies in their ability to capture the complex shape of observed TMT spectra.

54 ENVIRONMENTAL SCIENCES↗

Reservoirs Modify River Thermal Regime Sensitivity to Climate Change: A Case Study in the Southeastern United States

Seasonal thermal stratification in reservoirs changes the thermal regime of regulated river systems as well as stream temperature responses to climate change. Cold releases from reservoir hypolimnion can depress downstream river temperature during warm seasons. Recent large-scale climate change studies on stream temperature have largely ignored reservoir thermal stratification. In this study, we used established models to develop a framework which considers water demand and reservoir regulation with thermal stratification, and applied this model framework to the southeastern US. About half of all 271 reservoirs in our study area retain strong thermal stratification by the 2080s (2070-2099) under RCP8.5 even as median residence times decrease to 60 days from 69 days in the historic period (1979-2010). Reservoir impacts on downstream temperatures become slightly weaker in the future because of higher air temperature and stronger solar radiation. We defined a “cooling potential” to quantify the thermal energy that a water body can absorb before exceeding a water temperature threshold. In the future, higher river temperatures will reduce the cooling potential for all river segments, but more so for river segments minimally impacted by thermal stratification. Reservoir impacts on cooling potential remain strong for river segments downstream of reservoirs with strong thermal stratification. We conducted a sensitivity analysis to evaluate the robustness of our findings to errors in the hydrological simulations. While river segments subject to reservoir regulation are more sensitive to errors in hydrology than those without regulation impacts, our overall findings do not materially change due to these errors.

54 ENVIRONMENTAL SCIENCES↗

Little influence of Arctic amplification on mid-latitude climate

Observations and model simulations show enhanced warming in the Arctic under increasing greenhouse gases, a phenomenon known as the Arctic amplification (AA), that is likely caused by sea-ice loss. AA reduces meridional temperature gradients linked to circulation, thus mid-latitude weather and climate changes have been attributed to AA, often on the basis of regression analysis and atmospheric simulations. However, other modelling studies show only a weak link. This inconsistency may result from deficiencies in separating the effects of AA from those of natural variability or background warming. In this work, using coupled model simulations with and without AA, we show that cold-season precipitation, snowfall and circulation changes over northern mid-latitudes come mostly from background warming. AA and sea-ice loss increase precipitation and snowfall above ~60° N and reduce meridional temperature gradients above ~45° N in the lower–mid troposphere. However, minimal impact on the mean climate is seen below ~60° N, with weak reduction in zonal wind over 50°–70° N and 150–700 hPa, mainly over the North Atlantic and northern central Asia. These results suggest that the climatic impacts of AA are probably small outside the high latitudes, thus caution is needed in attributing mid-latitude changes to AA and sea-ice loss on the basis of statistical analyses that cannot distinguish the impact of AA from other correlated changes.

54 ENVIRONMENTAL SCIENCES↗

Energy and Exergy Analysis of Low-Global Warming Potential Refrigerants as Replacement for R410A in Two-Speed Heat Pumps for Cold Climates

Heat pumps (HPs) are being developed with a new emphasis on cold climates. To lower the environmental impact of greenhouse gas (GHG) emissions, alternate low global warming potential (GWP) refrigerants must also replace the exclusive use of the refrigerant R410A, preferably without re-engineering the mechanical hardware. In this paper, we analyze the performance of four low-GWP alternative refrigerants (R32, R452B, R454B, and R466A) relative to the conventional R410A and draw conclusions on the relative performances for providing heating in cold climates based on the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) 210/240 standard for two-speed heat pumps. The simulations are carried using the Department of Energy, Oak Ridge National Laboratory (DOE/ORNL) Heat Pump Design Model (HPDM), a well-known heating, ventilation, and air conditioning (HVAC) modeling and design tool in the public domain and the HVAC research and development community. The results of the simulation are further scrutinized using exergy analysis to identify sources of systemic inefficiency, the root cause of lost work. This rigorous approach provides an exhaustive analysis of alternate low-GWP refrigerants to replace R410A using available compressors and system components, without compromising performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Antarctic lake phytoplankton and bacteria from near‐surface waters exhibit high sensitivity to climate‐driven disturbance

Abstract The McMurdo Dry Valleys (MDVs), Antarctica, represent a cold, desert ecosystem poised on the threshold of melting and freezing water. The MDVs have experienced dramatic signs of climatic change, most notably a warm austral summer in 2001–2002 that caused widespread flooding, partial ice cover loss and lake level rise. To understand the impact of these climatic disturbances on lake microbial communities, we simulated lake level rise and ice‐cover loss by transplanting dialysis‐bagged communities from selected depths to other locations in the water column or to an open water perimeter moat. Bacteria and eukaryote communities residing in the surface waters (5 m) exhibited shifts in community composition when exposed to either disturbance, while microbial communities from below the surface were largely unaffected by the transplant. We also observed an accumulation of labile dissolved organic carbon in the transplanted surface communities. In addition, there were taxa‐specific sensitivities: cryptophytes and Actinobacteria were highly sensitive particularly to the moat transplant, while chlorophytes and several bacterial taxa increased in relative abundance or were unaffected. Our results reveal that future climate‐driven disturbances will likely undermine the stability and productivity of MDV lake phytoplankton and bacterial communities in the surface waters of this extreme environment.

54 ENVIRONMENTAL SCIENCES↗

Data from: "Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions"

This archive contains data files that were used to draw conclusions in “Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions”, by Moyes et al., 2015. All field research was completed in common garden plots set up as part of the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA.There are two main data file formats in this archive: comma-separated values (.csv), and Microsoft Excel (.xls and .xlsx). .xlsx files can be read using Microsoft Excel and Google Sheets, and .csv files can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). This .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software. Seedling photographs and their corresponding leaf area-processed images are available in .jpg/.JPG image format, and can be opened using Preview (Mac) and Photos (Windows). To provide additional spatial context, two types of geospatial files are also published in this data package: ESRI shapefiles (.shp) and .kml files. Shapefiles are compatible with any GIS software able to read the file type (such as QGIS or ESRI’s ArcGIS suite), and .kml files can be opened with Google Earth or Google Maps. Figures 3 and 4 in the publication contain data from Moyes et al. 2013. This publication is cited in the References section in this archive, and data files can be accessed via the Alpine Treeline Warming Experiment project portal on ESS-DIVE. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Climate change is altering plant species distributions globally, and warming is expected to promote uphill shifts in mountain trees. However, at many cold-edge range limits, such as alpine treelines in the western United States, tree establishment may be colimited by low temperature and low moisture, making recruitment patterns with warming difficult to predict.- We measured response functions linking carbon (C) assimilation and temperature- and moisture-related microclimatic factors for limber pine (Pinus flexilis) seedlings growing in a heating × watering experiment within and above the alpine treeline. We then extrapolated these response functions using observed microclimate conditions to estimate the net effects of warming and associated soil drying on C assimilation across an entire growing season.- Moisture and temperature limitations were each estimated to reduce potential growing season C gain from a theoretical upper limit by 15–30% (c. 50% combined). Warming above current treeline conditions provided relatively little benefit to modeled net assimilation, whereas assimilation was sensitive to either wetter or drier conditions.- Summer precipitation may be at least as important as temperature in constraining C gain by establishing subalpine trees at and above current alpine treelines as seasonally dry subalpine and alpine ecosystems continue to warm.

54 ENVIRONMENTAL SCIENCES↗

Regional tropical rainfall shifts under global warming: an energetic perspective

Abstract Future climate simulations feature pronounced spatial shifts in the structure of tropical rainfall. We apply a novel atmospheric energy flux analysis to diagnose late 21st century tropical rainfall shifts in a large ensemble of simulations of 21st century climate. The method reconstructs 2D spatial changes in rainfall based on horizontal shifts in the lines of zero meridional and zonal divergent energy flux, called the energy flux equator (EFE) and energy flux prime meridian (EFPM), respectively. Two main sources of future atmospheric energy flux changes, and hence rainfall shifts, are identified by the analysis: the high-latitude North Atlantic due to a weakened Atlantic Meridional Overturning Circulation that shifts tropical rainfall southwards over the greater Tropical Atlantic sector and eastern Pacific; and the eastern tropical Pacific due to a permanent El-Niño-like response that produces zonal shifts over the Maritime Continent and South America. To first order, the shifts in the EFE and EFPM mirror gross distributional changes in tropical precipitation, with a southward shift in rainfall over the tropical Atlantic, West Africa, and eastern tropical Pacific and an eastward shift over the Maritime Continent and western Pacific. When used to reconstruct future rainfall shifts in the tropical Atlantic and Sahel, the method reasonably represents the simulated meridional structure of rainfall shifts but does not do so for the zonal structures.

54 ENVIRONMENTAL SCIENCES↗

The Energy Modeling Forum (EMF)-30 Study on Short-Lived Climate Forcers: Introduction and Overview

The Energy Modeling Forum (EMF)-30 inter-comparison study on short-lived climate forcers (SLCFs) focuses on black carbon (BC) and methane, two of the most important warming SLCFs. The potential impact on climate change of methane and BC-focused emission reductions in the transport and residential sectors were quantified using nine integrated assessment models and a simple climate model. These SLCF reductions reduced global temperatures by 0.18–0.26 °C in 2050 across the models for central climate parameters, with methane being the dominant contributor. The incremental impact of SLCF-focused reductions is much smaller when combined with a broader climate policy. Individual modeling groups examined the health benefits of air pollutant reductions, climate policy co-benefits, and quantified market impacts from air pollutant damages. Model structure and set-up impact on results are discussed along with areas for future work.

Smith, Steven J.↗

The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7

The first version of the Detection and Attribution Model Intercomparison Project (DAMIP v1.0) coordinated key simulations exploring the role of individual forcings in past, current and future climate as part of the Coupled Model Intercomparison Project, Phase 6 (CMIP6). The simulations have been used extensively in the literature for detection and attribution of long-term changes, constraining projections of climate change, attributing extreme events and understanding drivers of past and future simulated climate changes. Attribution studies using DAMIP v1.0 simulations underpinned prominent assessments of human-induced warming in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. Here, we describe the set of DAMIP v2.0 simulations, proposed for the next phase of CMIP, CMIP7. Detection and attribution studies rely on pre-industrial control simulations and historical simulations, which will be part of the Diagnostic, Evaluation and Characterization of Klima (DECK) set of simulations for CMIP7. In addition, we identify the three highest-priority single-forcing experiments for CMIP7 to be run as “Assessment Fast Track” simulations in support of the Seventh Assessment Report of the IPCC: simulations with natural forcings only, anthropogenic well-mixed greenhouse gases only and anthropogenic aerosols only. Beyond this, the DAMIP v2.0 experimental design includes full-column ozone-only simulations and land-use-only simulations, such that the set of individual forcing experiments, when these are considered together, represents the full set of historical forcings. While concentration-driven simulations are prioritised for attribution, emissions-driven versions of the DAMIP experiments are also proposed to support understanding of the influence of carbon-cycle feedbacks on the simulated responses to individual forcings.

Gillett, Nathan P. [Environment and Climate Change↗

Global field observations of tree die-off reveal hotter-drought fingerprint for Earth’s forests

Earth’s forests face grave challenges in the Anthropocene, including hotter droughts increasingly associated with widespread forest die-off events. But despite the vital importance of forests to global ecosystem services, their fates in a warming world remain highly uncertain. Lacking is quantitative determination of commonality in climate anomalies associated with pulses of tree mortality—from published, field-documented mortality events—required for understanding the role of extreme climate events in overall global tree die-off patterns. Here we established a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970. Our analysis quantifies a global “hotter-drought fingerprint” from these tree-mortality sites—effectively a hotter and drier climate signal for tree mortality—across 675 locations encompassing 1,303 plots. Frequency of these observed mortality-year climate conditions strongly increases nonlinearly under projected warming. Our database also provides initial footing for further community-developed, quantitative, ground-based monitoring of global tree mortality.

54 ENVIRONMENTAL SCIENCES↗

Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments

Tropical cyclones (TCs) rank as the deadliest and most financially crippling natural disasters in the United States for the last half-century. It is imperative to assess potential shifts in TC intensity within the paradigm of an evolving climate. In this study, we have modeled the intensities of 620 historical TC events in the North Atlantic Basin using the Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep learning intensity model. By applying a thermodynamic warming signal extrapolated from Global Climate Models, we rerun historical events under eight different future climate scenarios, providing a spectrum of potential TC intensity outcomes. One of the future simulations indicates a staggering 43% increase in the number of major hurricanes, underscoring the critical impact of climate change on TC intensity. Additionally, an interactive dashboard has been created to enable users to explore individual storm simulations and understand the influence of future climate signals on environmental conditions of TC development and resulting TC intensities. This dataset and the user-friendly tool offer invaluable resources for systematic exploration of the discrete effects that changes in the air-sea thermodynamic state have on the intensities of TCs.

Climate Change↗

Insights on sources and formation mechanisms of liquid-bearing clouds over MOSAiC examined from a Lagrangian framework

Understanding Arctic stratiform liquid-bearing cloud life cycles and properly representing these life cycles in models is crucial for evaluations of cloud feedbacks as well as the faithfulness of climate projections for this rapidly warming region. Examination of cloud life cycles typically requires analyses of cloud evolution and origins on short time scales, on the order of hours to several days. Measurements from the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide a unique view of the current state of the central Arctic over an annual cycle. Here, we use the MOSAiC radiosonde measurements to detect liquid-bearing cloud layers over full atmospheric columns and to examine the cloud-generating air masses’ properties. We perform 5-day (120 h) back-trajectory calculations for every detected cloud and cluster them using a unique set of variables extracted from these trajectories informed by ERA5 reanalysis data. This clustering method enables us to separate between the air mass source regions such as ice-covered Arctic and midlatitude open water. We find that moisture intrusions into the central Arctic typically result in multilayer liquid-bearing cloud structures and that more than half of multilayer profiles include overlying liquid-bearing clouds originating in different types of air masses. Finally, we conclude that Arctic cloud formation via prolonged radiative cooling of elevated stable subsaturated air masses circulating over the Arctic can occur frequently (up to 20% of detected clouds in the sounding data set) and may lead to a significant impact of ensuing clouds on the surface energy budget, including net surface warming in some cases.

54 ENVIRONMENTAL SCIENCES↗