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NASA NTRS2023

Lifetimes of Overshooting Convective Events using High-Frequency Gridded Radar Composites

Deep convection that penetrates the tropopause, referred to here as overshooting convection, is capable of lifting tropospheric air well into the stratosphere. In addition to water, these overshoots also transport various chemical species, affecting chemistry and radiation in the stratosphere. It is not currently known, however, how much transport is a result of this mechanism. To better understand overshooting convection, this study aims to characterize the durations of overshooting events. To achieve this, radar data from the Next Generation Weather Radar (NEXRAD) network is composited onto a three-dimensional grid at 5-min intervals. Overshoots are identified by comparing echo-top heights with tropopause estimates derived from ERA5 reanalysis data. These overshoots are linked in space from one analysis time to the next to form tracks. This process is performed for 12 four-day sample windows in the months May–August of 2017–19. Track characteristics such as duration, overshoot area, tropopause-relative altitude, and column-maximum reflectivity are investigated. Positive correlations are found between track duration and other track characteristics. Integrated track volume is found as a product of the overshoot area, depth, and duration, and provides a measure of the potential stratospheric impact of each track. Short-lived tracks are observed to contribute the most total integrated volume when considering track duration, while tracks that overshoot by 2–3 km show the largest contribution when considering overshoot depth. A diurnal cycle is observed, with peak track initiation around 1600–1700 local time. Track-mean duration peaks a few hours earlier, while track-mean area and tropopause-relative height peak a few hours later.

Atmosphere↗
NASA NTRSDate not supplied

Hunga Tonga-Hunga Ha’apai Water Vapour and Composition of the Stratospheric Polar Vortices

We investigate the impacts of water vapor from the Hunga Tonga-Hunga Ha'apai (HTHH) eruption on the Antarctic stratospheric vortices in 2022 and 2023 and the Arctic stratospheric vortex in 2022/2023. Trace gas abundances from the Aura Microwave Limb Sounder (MLS) and the Modern Era Retrospective-analysis for Research and Applications (MERRA-2) Stratospheric Composition REanalysis with Aura MLS (M2-SCREAM), along with meteorological fields from the longer MERRA-2 record, are used to detail the evolution of the stratospheric polar vortex and its composition during these winter/spring seasons. Through austral winter and spring 2022, HTHH water vapor was effectively excluded from the Antarctic vortex until it broke up. The 2022 Antarctic vortex itself was large, strong, and long-lived, but not exceptionally so. By austral fall 2023, HTHH stratospheric water vapor had spread globally, and Antarctic vortex values in the lower through middle stratosphere were over 2 ppmv higher than usual when the vortex formed; these record-shattering water vapor concentrations led to earlier polar stratospheric cloud formation and chlorine activation, especially at levels that are typically the highest altitudes for polar processing. In the 2022/2023 Arctic winter/spring, HTHH water vapor reached the Arctic vortex region after the vortex had formed and was largely excluded until a major sudden stratospheric warming in mid-February 2023 eroded the vortex and mixed midlatitude and vortex air throughout the hemisphere.

Gloria L Manney↗
NASA NTRSDate not supplied

Regional Impacts of Ice Sheet Surface Representation Improvements in an Earth System Model

Ice sheet surface conditions and their subsequent impact on surface mass balance play an important role in ice sheet dynamics and ice sheet interaction with the overlying atmosphere and surrounding ocean. The NASA Global Modeling and Assimilation Office’s (GMAO) Goddard Earth Observing System (GEOS) ecosystem of models and reanalyses model ice sheet and glacier surface mass balance with a moderately complex snow and ice module, including prognostic surface albedo evolution, fractional snow cover, and snowpack hydrology and meltwater retention. With this configuration, Greenland near surface air temperatures and ice sheet melt are well represented in MERRA-2, GMAO’s current atmospheric reanalysis; however, the similarity to observations in some regions is due, in part, to compensating biases in surface energy budget. Recent improvements to GEOS’ cloud microphysics and longwave radiation parameterizations reduced biases in surface net longwave radiation and exacerbated surface net shortwave radiation biases, effectively increasing near surface temperatures and melting, particularly during the summer months. Here, we demonstrate the Earth system response to an improved representation of the ice sheet surface focused on minimizing the surface energy biases and increasing spatial and temporal representativeness. New changes to the surface albedo parameterization, including the introduction of a prognostic aerosol darkening scheme, help mitigate shortwave biases, while modifications to surface roughness characteristics improve near surface sensible heat fluxes. Focusing on the Arctic and Greenland, we examine the combined impact on these changes on regional weather conditions and ice sheet surface mass balance using a high resolution atmospheric only experiment, and we use a coupled model configuration to assess the impact on oceanic conditions and subseasonal-to-seasonal prediction. Overall, these improvements increase modeled ice sheet surface realism and provide a strong basis for more accurate ice sheet mass balance in GMAO’s future reanalyses and forecasting systems.

Lauren C Andrews↗
NASA NTRSDate not supplied

GEOS Constituent Data Assimilation beyond Aura MLS: Assimilating NASA SAGE III/ISS profiles of stratospheric water vapor

Water vapor in the lower stratosphere is an important trace gas for atmospheric chemistry and radiative budget with direct impact on climate. During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the stratospheric ozone loss and the subsequent recovery as well as trends in water vapor linked to surface temperature trends. The SAGE III instrument aboard the International Space Station (ISS) continues the SAGE mission record, with high vertical resolution profiles of water vapor (and other constituents) since mid-2017. The NASA GEOS Earth system model has the capability to assimilate multi-constituents from ground and space-based instruments using the GEOS Constituent Data Assimilation System (CoDAS). Reanalysis products of stratospheric water vapor without data constraints are historically poor, and two recent reanalyses which assimilated stratospheric constituents observed by the Microwave Limb Sounder (MLS) improve the representation of stratospheric composition, including water vapor, when compared against independent observations. The MLS instrument is on NASA's Aura satellite which is expected to be decommissioned in the coming years. Here we demonstrate that while the number of solar occultation observations a day from SAGE III/ISS is about 1 % of the total number of profiles observed globally by MLS, the chemical timescales of water vapor in the lower stratosphere are long enough that the SAGE III/ISS data can provide a useful constraint on the assimilated product. Analyzed water vapor fields from assimilating only SAGE III/ISS water vapor profiles agree well with independent stratospheric observations, including when compared against the frost-point hygrometers at the three NOAA stations. Over the five-year period from 2017 through 2022, the analyzed water vapor using SAGE III/ISS captures many of the features seen with the assimilation of MLS observations. Note, this ability is reduced over regions where the SAGE III/ISS instrument provides infrequent or no observations (associated with the orbit of the ISS), as highlighted in the case study period following the eruption of the tropical underwater volcano Hunga Tonga in early 2022. Nevertheless, there is a clear benefit to the assimilation of stratospheric water vapor from SAGE III/ISS observations, allowing us to continue to monitor stratospheric composition for climate assessments following the impending loss of Aura.

K. Emma Knowland↗
NASA NTRS2022

Summer Greenland Blocking Diversity and Its Impact on the Surface Mass Balance of the Greenland Ice Sheet

The increase in Greenland Ice Sheet (GrIS) surface runoff since the turn of the century has been linked to a rise in Greenland blocking frequency. However, a range of synoptic patterns can be considered blocked flow and efforts that summarize all blocking types indiscriminately likely fail to capture consequential differences in GrIS response. To account for these differences, we employ ERA5 reanalysis to identify summer blocking using two independent blocking metrics: the Greenland Blocking Index (GBI) and the blocking index of Pelly and Hoskins (2003, https://doi.org/10.1175/1520-0469(2003)060<0743:ANPOB>2.0.CO;2). We then conduct a self-organizing map analysis to objectively classify synoptic conditions during Greenland blocking episodes and identify three primary blocking types: (a) a high-amplitude Omega block, (b) a lower-amplitude, stationary summer ridge, and (c) a cyclonic wave breaking pattern. Using Modèle Atmosphérique Régional output, we document the spatiotemporal progression of the surface energy and mass balance for each blocking type. Relative to all blocking episodes, summer ridge patterns produce more melt over the southern ice sheet, Omega blocks produce more melt across the northern ice sheet, and cyclonic wave breaking patterns produce more melt in northeast Greenland. Our results indicate that the recent trend in summer Greenland blocking was largely driven by an increase in Omega patterns and suggest that Omega blocks have played a central role in the recent acceleration of GrIS mass loss. Furthermore, the GBI exhibited a relative bias toward Omega patterns, which may help explain why it has measured stronger trends in summer Greenland blocking than other blocking metrics.

atmospheric blocking↗
NASA NTRSDate not supplied

The Seasonal Evolution of Atmospheric Vertical Structure of Smoke and Humidity Over the Southeast Atlantic Biomass Burning Region

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region; this correlation is persistent through the biomass burning season, although varying through the course of the season. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. We use the ORACLES observations to assess this smoke-vapor relationship. First, we discuss the good agreement between the airborne ORACLES dataset and the ECMWF ERA5 and CAMS reanalyses, as well as results from NASA’s MERRA-2, as seen over the three deployment years. We then use the reanalyses to develop a framework in which to understand more broadly the radiative and dynamical interactions between the elevated smoke and water vapor over the SEA through the biomass burning season, beyond the three ORACLES observation periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalyses, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. The radiative heating of both aerosol and water vapor has potential to influence the cloud-top entrainment and atmospheric turbulence, thus modifying the underlying stratocumulus cloud properties. We next discuss how these smoke-humidity variations influence both the low-cloud fraction (as observed by MODIS and VIIRS, and output by ERA5) and the boundary layer height in the region. This classification will ultimately allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗
NASA NTRSDate not supplied

The Impact of Large Scale Atmospheric and Cyclone Variability on the Sea-Ice Edge in the Labrador Sea

We study the temporal variability of the wintertime Labrador Sea ice area. The driving factors of these intraseasonal and interannual variations are related to large scale atmospheric variability and cyclone variability both of which can be characterized by the Arctic Oscillation (AO) index. We observe negative trends in the maximum sea-ice area over the past 40 years, and a positive correlation between the AO index and Labrador Sea ice area. Using satellite-derived daily ice area along with reanalysis-derived cyclones, turbulent flux, wind, humidity, air and sea temperature fields, we delve into the physical coupling mechanisms by which cyclones influence the position of the ice edge in the Labrador Sea throughout the winter.

Sea ice↗
NASA NTRSDate not supplied

The Impact of Dry Intrusions on Midlatitude Cold-Air Outbreak Cloud Transitions

Cold-air outbreaks (CAOs) form marine boundary layer (MBL) clouds that undergo rapid overcast-to-broken cloud regime transitions, initiated by substantial rain. CAOs are usually accompanied by dry intrusions (DIs) that subside as free-tropospheric (FT) air into the postfrontal sector of mid-latitude storms. For an exemplary cold-air outbreak in the NW Atlantic that showed faster transitions (corresponding to reduced extents of overcast clouds) closer to the low-pressure system, we posit that varying transitions are caused by an uneven meteorological pattern imposed by the prevailing DI. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MERRA2-based trajectories to show that postfrontal trajectories closer to the low-pressure system are uniquely favorable to rain formation (and, thus, cloud transitions) as they show (1) weaker FT subsidence rates, (2) greater FT humidity, (3) greater MBL windspeeds, and (4) a colder MBL as well as reduced lower-tropospheric stability. We present an updated conceptual view of postfrontal cloud formation that may guide future investigations.

Cold-air outbreaks↗
NASA NTRS2023

Using Orbiting Carbon Observatory-2 (OCO-2) column CO2 retrievals to rapidly detect and estimate biospheric surface carbon flux anomalies

The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations, which are partly reduced by terrestrial biosphere and ocean carbon uptake. Greenhouse gas satellites have been shown to be useful in retrieving atmospheric carbon concentrations and observing surface and atmospheric CO2 seasonal-to-interannual variations. However, limited attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere without advanced inversion models at low latency. Such applications could be useful to monitor, in near real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs and/or advanced inversion modelling estimates become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) column-averaged dry air CO2 (XCO2) retrievals to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass-balance approach. An initial global analysis of surface–atmospheric CO2 coupling and transport conditions reveals that the western US, among a handful of other regions, is a feasible candidate for using XCO2 for detecting terrestrial biosphere CO2 flux anomalies. Using the CarbonTracker model reanalysis as a test bed, we first demonstrate that a well-established mass-balance approach can estimate monthly surface CO2 flux anomalies from XCO2 enhancements in the western United States. The method is optimal when the study domain is spatially extensive enough to account for atmospheric mixing and has favorable advection conditions with contributions primarily from one background region. We find that errors in individual soundings reduce the ability of OCO-2 XCO2 to estimate more frequent, smaller surface CO2 flux anomalies. However, we find that OCO-2 XCO2 can often detect and estimate large surface flux anomalies that leave an imprint on the atmospheric CO2 concentration anomalies beyond the retrieval error/uncertainty associated with the observations. OCO-2 can thus be useful for low-latency monitoring of the monthly timing and magnitude of extreme regional terrestrial biosphere carbon anomalies.

Andrew F. Feldman↗
NASA NTRS2023

Explainable deep learning for insights in El Niño and river flows

The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections. Recent research has demonstrated the value of Deep Learning (DL) methods for improving ENSO prediction as well as Complex Networks (CN) for understanding teleconnections. However, gaps in predictive understanding of ENSO-driven river flows include the black box nature of DL, the use of simple ENSO indices to describe a complex phenomenon and translating DL-based ENSO predictions to river flow predictions. Here we show that eXplainable DL (XDL) methods, based on saliency maps, can extract interpretable predictive information contained in global SST and discover SST information regions and dependence structures relevant for river flows which, in tandem with climate network constructions, enable improved predictive understanding. Our results reveal additional information content in global SST beyond ENSO indices, develop understanding of how SSTs influence river flows, and generate improved river flow prediction, including uncertainty estimation. Observations, reanalysis data, and earth system model simulations are used to demonstrate the value of the XDL-CN based methods for future interannual and decadal scale climate projections.

SST↗
NASA NTRSDate not supplied

The Impact of Assimilating Large Volumes of GNSS Radio Occultation Observations from Spire’s Commercial Constellation into NASA’s Global Earth Observing System

The upcoming retrospective analysis for the 21st century (R21C) reanalysis product from NASA will include the full dataset of GNSS Radio Occultation (RO) observations collected by Spire with their constellation of smallsats. The Spire RO dataset, which was purchased by NASA for its Commercial Smallsat Data Acquisition (CSDA) archive, has global coverage and includes approximately 6 thousand RO profiles per day during 2019 increasing to nearly 20 thousand in 2022-2023. This more than doubles the volume of RO profiles from all other routinely assimilated RO missions combined during 2023. The increase in the number of RO profiles available is particularly important in the extratropics as the next largest RO constellation, the state-of-the-science Formosa Satellite Mission 7 (FORMOSAT-7)/Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) mission (hereafter COSMIC-2), is focused on the Tropics and only provides approximately 4 thousand RO profiles per day. The large number of observations in the Spire RO dataset have great potential to improve analyses and forecasts of the Earth’s atmosphere produced by numerical weather prediction systems. Their impact is assessed through numerical experiments using NASA’s Global Earth Observing System (GEOS) Atmospheric Data Assimilation System (ADAS) with and without the observations from the COSMIC-2 mission. The ability of the Spire RO observations to make up for the omission of the RO observations from COSMIC-2 is directly assessed over the tropics and the impact of Spire over the extratropics is compared to that of the available RO missions that sample over this region. Finally, the quality of the Spire RO observations is compared to that of the routinely assimilated RO missions using Forecast Sensitivity-based Observation Impact (FSOI).

Michael J. Murphy, Jr.↗
NASA NTRS2023

Some Applications of SiFSAP for Wildfires, Weather and Atmospheric Dynamics Studies

The Single Field of View (SFOV) Sounder Atmospheric Product (SiFSAP) derived from Cross-track Infrared Sounder (CrIS) on SNPP and JPSS have a spatial resolution ( ~14.5 km) better than most global weather and climate models. Most recent improvement in the quality of these products enables us to use these high-resolution observation-based sounding data for air quality, weather and atmospheric dynamics studies. A few cases studies through a synergistic use of SiFSAP from S-NPP and J-1 and the reanalysis data from ERA5 and MERRA-2 will be presented, which include a process-oriented analysis of (1) a stratospheric intrusion (SI) event occurred on June 11-13, 2017 in the southwestern US, (2) one extreme cold air break (CAO) episode occurred on 27-31 January 2019 across much of the US Midwest and its impact from stratospheric downward transport, and (3) dynamic transport of carbon monoxide (CO) associated with Australia’s unprecedented fire from the end of 2019 to early 2020. These examples will demonstrate the value of SiFSAP for weather, atmospheric dynamics, air quality, wildfires studies and for model evaluations.

Xiaozhen (Shawn) Xiong↗
NASA NTRSDate not supplied

Generating a 4D Global CH(4) Product by Assimilating TROPOMI column CH(4) in NASA’s GEOS GCM

Examination of temporal and spatial CH4 variability is crucial for better understanding the human and natural processes driving climate change and ultimately designing mitigation strategies. Here we present an analysis framework that uses NASA’s GEOS General Circulation Model (GCM) to construct a high-resolution, time varying picture of atmospheric CH4 consistent with measurements from a variety of platforms, both in situ and remotely sensed. The resulting time varying atmospheric CH4 product can (i) support interpretation of high-resolution point source detection approaches, (ii) provide reanalysis fields for CH4 and other greenhouse gases, and (iii) supply boundary conditions for regional models. Our approach starts with a set of CH4 emissions from various inventories that have been adjusted to match the global annual growth rate over recent decades. These emissions are transported by the GEOS GCM, which in turn is constrained by meteorology from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product. The simulated atmospheric field is compared with CH4 measurements, such as those from the TROPOspheric Monitoring Instrument (TROPOMI), and adjustments calculated following a Bayesian protocol. The accuracy of the resultant optimal atmospheric CH4 field can be demonstrated by its improved agreement (compared to a direct simulation of the CH4 inventories) with a host of independent CH4 measurements, such as those from the Total Carbon Column Observation Network (TCCON) and in situ observations from surface and airborne platforms.

Nikolay V. Balashov↗
NASA NTRS2023

The Hydrological Cycle and Ocean Circulation of the Maritime Continent in the Mid-Pliocene: Results From PlioMIP2

The Maritime Continent (MC) forms the western boundary of the tropical Pacific Ocean, and relatively small changes in this region can impact the climate locally and remotely. In the mid-Piacenzian warm period of the Pliocene (mPWP; 3.264 to 3.025 Ma) atmospheric CO2 concentrations were ∼ 400 ppm, and the subaerial Sunda and Sahul shelves made the land–sea distribution of the MC different to today. Topographic changes and elevated levels of CO2, combined with other forcings, are therefore expected to have driven a substantial climate signal in the MC region at this time. By using the results from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), we study the mean climatic features of the MC in the mPWP and changes in Indonesian Throughflow (ITF) with respect to the preindustrial. Results show a warmer and wetter mPWP climate of the MC and lower sea surface salinity in the surrounding ocean compared with the preindustrial. Furthermore, we quantify the volume transfer through the ITF; although the ITF may be expected to be hindered by the subaerial shelves, 10 out of 15 models show an increased volume transport compared with the preindustrial. In order to avoid undue influence from closely related models that are present in the PlioMIP2 ensemble, we introduce a new metric, the multi-cluster mean (MCM), which is based on cluster analysis of the individual models. We study the effect that the choice of MCM versus the more traditional analysis of multi-model mean (MMM) and individual models has on the discrepancy between model results and data. We find that models, which reproduce modern MC climate well, are not always good at simulating the mPWP climate anomaly of the MC. By comparing with individual models, the MMM and MCM reproduce the preindustrial sea surface temperature (SST) of the reanalysis better than most individual models and produce less discrepancy with reconstructed sea surface temperature anomalies (SSTA) than most individual models in the MC. In addition, the clusters reveal spatial signals that are not captured by the MMM, so that the MCM provides us with a new way to explore the results from model ensembles that include similar models.

Hydrological cycle↗
NASA NTRSDate not supplied

NASA GEOS-CF: Overview, Applications, Future Direction

Since 2019, the NASA Global Earth Observing System (GEOS) model has been used to generate global, near-real-time estimates and daily five-day forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). Because GEOS-CF includes atmospheric levels up through the stratosphere, this system has been leveraged to support the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite mission and provide stratospheric intrusion alerts to ground-based monitoring stations. We will present recent advances to GEOS-CF which includes assimilation of satellite observations to produce more accurate model analyses. We further discuss our future plans for a composition reanalysis.

K. Emma Knowland↗
NASA NTRSDate not supplied

Simulations of X-59 Sonic Thumps and Traditional Sonic Booms Propagated Around the World for Three Atmospheric Models

Propagation simulations of sonic booms from supersonic aircraft through atmospheric data over time at fixed locations provides the opportunity to assess noise exposure statistics for different climate regions. Knowledge of climate-based differences in sonic boom noise exposure statistics is important to ensure that future civil supersonic aircraft noise certification standards are globally applicable and effective. In this presentation, simulated sonic booms from the NASA X-59 Quesst quiet supersonic aircraft and conventional supersonic aircraft were propagated through atmospheric data at 100 locations across the world using PCBoom. Noise exposure statistics are compared for propagation results from three different atmospheric databases (NOAA Global Forecast System, NOAA Climate Forecast System Version 2, and the ECMWF Reanalysis Version 5). These atmospheric models were chosen due to their global coverage, popularity, and database availability. Preliminary statistical models are fit to assess the impact of several factors including flight direction, season, ground elevation, and climate on noise exposure size and loudness. Areas with prevalence of higher noise due to their climate are identified, which could help inform future supersonic aircraft noise standards.

X-59↗
NASA NTRS2023

Role of Snowfall Versus Air Temperatures for Greenland Ice Sheet Melt-Albedo Feedbacks

The Greenland Ice Sheet is a leading contributor to global sea-level rise because climate warming has enhanced surface meltwater runoff. Melt rates are particularly sensitive to air temperatures due to feedbacks with albedo. The primary melt-albedo feedback, fluctuation of seasonal snowlines, however, is determined not only by melt but also by antecedent snowfall which could delay the onset of dark glacier ice exposure. Here we investigate the role of snowfall versus air temperatures on ice sheet melt-albedo feedbacks using satellite remote sensing and atmospheric reanalysis data. We find several lines of evidence that snowline fluctuations are driven primarily by air temperatures and that snowfall is a secondary control. First, standardized linear regressions indicate that the timing of glacier ice exposure is nearly twice as sensitive to air temperatures than antecedent snowfall. Second, in 74% of the ablation zone by area, winter snowfall rates are not significantly correlated with winter air temperatures. This relationship implies that ice sheet melt due to climate warming is unlikely to be compensated by higher snowfall rates in the ablation zone. Third, we find no significant change in snowfall rates in the ablation zone during our 1981–2021 study period. Our findings demonstrate that snowfall is unlikely to reduce future ice sheet melt and that ice sheet meltwater runoff should be accurately predicted by air temperatures. Although given the importance of melt-albedo feedbacks, ice sheet models that parameterize albedo or are coupled with regional climate models are likely to provide the most accurate projections of mass loss.

J. C. Ryan↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We investigate two related approaches to prediction of GS cloud properties from SGS variability: the critical saturation ratio method, and the critical relative humidity method. We find significant correlation between GS cloud water and SGS supersaturation when the critical saturation ratio is set at 100%, as well as a notable relationship between GS cloud water and the width of the SGS total water distribution. Critical relative humidity also compares well with GS cloud water. However, we also find that the assumptions of a static critical saturation ratio of 100% to be unrealistic, as well as a fixed SGS distribution width. Empirical calculations from the ARISE data show a large sensitivity of these SGS variables to GS relative humidity, and so a SGS parameterization allowing them to vary according to GS thermodynamic properties may result in more realistic GS cloud water values.

J. Brant Dodson↗