Search NASA⌕ Search

SEARCH · Search NASA

Results for “Arctic change”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

Clean Air Policies Are Key for Successfully Mitigating Arctic Warming

A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050.

Atmospheric chemistry↗

Atmospheric Drivers of Greenland Surface Melt Revealed by Self-Organizing Maps

Recent acceleration in surface melt on the Greenland ice sheet (GrIS) has occurred concurrently with a rapidly warming Arctic and has been connected to persistent, anomalous atmospheric circulation patterns over Greenland. To identify synoptic setups favoring enhanced GrIS surface melt and their decadal changes, we develop a summer Arctic synoptic climatology by employing self-organizing maps. These are applied to daily 500 hPa geopotential height fields obtained from the Modern Era Retrospective Analysis for Research and Applications reanalysis, 1979-2014. Particular circulation regimes are related to meteorological conditions and GrIS surface melt estimated with outputs from the Modèle Atmosphérique Régional. Our results demonstrate that the largest positive melt anomalies occur in concert with positive height anomalies near Greenland associated with wind, temperature, and humidity patterns indicative of strong meridional transport of heat and moisture. We find an increased frequency in a 500 hPa ridge over Greenland coinciding with a 63% increase in GrIS melt between the 1979-1988 and 2005-2014 periods, with 75.0% of surface melt changes attributed to thermodynamics, 17% to dynamics, and 8.0% to a combination. We also confirm that the 2007-2012 time period has the largest dynamic forcing relative of any period but also demonstrate that increased surface energy fluxes, temperature, and moisture separate from dynamic changes contributed more to melt even during this period. This implies that GrIS surface melt is likely to continue to increase in response to an ever warmer future Arctic, regardless of future atmospheric circulation patterns.

anomalies↗

Spatially Mapped Reductions in the Length of the Arctic Sea Ice Season

Satellite data are used to determine the number of days having sea ice coverage in each year 1979-2013 and to map the trends in these ice-season lengths. Over the majority of the Arctic seasonal sea ice zone, the ice season shortened at an average rate of at least 5 days/decade between 1979 and 2013, and in a small area in the northeastern Barents Sea the rate of shortening reached over 65 days/decade. The only substantial non-coastal area with lengthening sea ice seasons is the Bering Sea, where the ice season lengthened by 5-15 days/decade. Over the Arctic as a whole, the area with ice seasons shortened by at least 5 days/decade is 12.4 × 10(exp 6) square kilimeters, while the area with ice seasons lengthened by at least 5 days/decade is only 1.1 × 10(exp 6) square kilometers. The contrast is even greater, percentage-wise, for higher rates.

Arctic↗

Global Total Ozone Recovery Trends Attributed to Ozone-Depleting Substance (ODS) Changes Derived From Five Merged Ozone Datasets

We report on updated trends using different merged zonal mean total ozone datasets from satellite and ground-based observations for the period from 1979 to 2020. This work is an update of the trends reported in Weber et al. (2018) using the same datasets up to 2016. Merged datasets used in this study include NASA MOD v8.7 and NOAA Cohesive Data (COH) v8.6, both based on data from the series of Solar Backscatter Ultraviolet (SBUV), SBUV-2, and Ozone Mapping and Profiler Suite (OMPS) satellite instruments (1978–present), as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone – Essential Climate Variable (GTO-ECV) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (both 1995–present), mainly comprising satellite data from GOME, SCIAMACHY, OMI, GOME-2A, GOME-2B, and TROPOMI. The fifth dataset consists of the annual mean zonal mean data from ground-based measurements collected at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. The addition of 4 more years consolidated the fact that total ozone is indeed slowly recovering in both hemispheres as a result of phasing out ozone-depleting substances (ODSs) as mandated by the Montreal Protocol. The near-global (60° S–60° N) ODS-related ozone trend of the median of all datasets after 1995 was 0.4 ± 0.2 (2σ) %/decade, which is roughly a third of the decreasing rate of 1.5 ± 0.6 %/decade from 1978 until 1995. The ratio of decline and increase is nearly identical to that of the EESC (equivalent effective stratospheric chlorine or stratospheric halogen) change rates before and after 1995, confirming the success of the Montreal Protocol. The observed total ozone time series are also in very good agreement with the median of 17 chemistry climate models from CCMI-1 (Chemistry-Climate Model Initiative Phase 1) with current ODS and GHG (greenhouse gas) scenarios (REF-C2 scenario). The positive ODS-related trends in the Northern Hemisphere (NH) after 1995 are only obtained with a sufficient number of terms in the MLR accounting properly for dynamical ozone changes (Brewer–Dobson circulation, Arctic Oscillation (AO), and Antarctic Oscillation (AAO)). A standard MLR (limited to solar, Quasi-Biennial Oscillation (QBO), volcanic, and El Niño–Southern Oscillation (ENSO)) leads to zero trends, showing that the small positive ODS-related trends have been balanced by negative trend contributions from atmospheric dynamics, resulting in nearly constant total ozone levels since 2000.

Total Column Ozone Trends↗

Anthropogenic Pathways for Modeling and Managing Future Arctic Fires

Wildland fires, including extreme fire events and seasons, are becoming more common in the boreal and Arctic regions due to climate change. Current climate modeling approaches do not include country- or region-specific socioeconomic pathways that specifically address the drivers of and potential mitigation techniques for wildland fires. Forest management, energy extraction, and tourism, together with firefighting capacity and readiness as well as fuels treatment, can have a significant impact on future wildland fire risks and impacts. To assess the impacts of anthropogenic factors and to align with previous work done on shared socioeconomic pathways (SSPs), climate pathways for future wildfires up to 2050 were created for the states that compose the original Arctic Council countries: Canada, the United States, the Kingdom of Denmark, Iceland, Sweden, Norway, and Finland as well as the Russian Federation (with whom the other seven countries withdrew participation from in May 2022 due to the invasion and ongoing war in Ukraine). High and low fire activity and risk pathways for all states comprising the Arctic were made, with expert ‘best guess’ pathways for each state created separately to represent the middle of road. The low activity and low fire risk pathways, named “We Got This”, assume active fire suppression via citizenry participation and official land management, efficient and extensive fuel treatments, and consistent and active wildland firefighting for each new ignition. The high activity and high fire risk pathways, named “Let It Burn”, assume nearly the opposite, due to lack of government and community response and no action on climate change drivers that increase wildland fire risk. The ‘best guess’ pathway, named “The Fire Will Come”, indicates that some countries are currently on the pathway for less fire compared to other Arctic and Boreal states but not a ‘no-fire’ future. For example, in the Nordic countries, human ignition sources from tourism, timber and energy extraction, summer cottages, and expanding wildland-urban intermix due to exurban growth may increase. In North America, these same risks will apply but also may see an expansion of agriculture that increases the likelihood of open burning in croplands. Drier fuel condition and extreme heat events due to climate change create favorable conditions for extreme wildfires from any ignition source. Throughout the Arctic and boreal lightning is expected to increase, increasing the risk of tundra fires in addition to forest fires in hard-to-reach locations that are more difficult to coordinate and execute wildland firefighting. To move the future Arctic fire SSPs forward, several short-term and long-term actions must be completed. Certain data needs are required, like a harmonized pan-Arctic and pan-boreal fuels geospatial product, while also a need to refine and socialize current definitions of fire seasons and fire management – including developing an open-source system to track and share innovation, mitigation, and adaptation strategies across Arctic states.

Arctic↗

Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

Kurtz, N. T.↗

The Surface Albedo of Sea Ice in CMIP6 and the Implications for the Surface Albedo Feedback

The Arctic has experienced rapid sea ice loss and a substantial decline in surface albedo, significantly impacting its radiation budget. Climate models from the Coupled Model Intercomparison Project (CMIP6) reproduce these changes. However, inconsistencies remain among models regarding the magnitude, spatial distribution, and seasonal patterns of Arctic surface albedo evolution. This study investigates these discrepancies by comparing model outputs with observation from the Clouds and the Earth's Radiant Energy System (CERES). We develop a decomposition method to assess the contributions of sea ice albedo, sea ice concentration, and sea ice extent to Arctic surface albedo. Over land, differences in snow cover account for the substantial inter-model spread in surface albedo, while over the ocean, sea ice albedo, concentration, and extent all contribute. Comparisons between CMIP6 and the Atmospheric Model Intercomparison Project (AMIP) simulations, which use identically prescribed sea ice concentrations, reveals considerable inter-model spread in Arctic Ocean surface albedo due to differences in sea ice albedo. Applying the decomposition method to projections shows that models predicting larger decreases in sea ice concentration and extent, especially in the Central Arctic, exhibit lower surface albedo and stronger sea ice albedo feedback. Beyond 2050, Arctic Ocean surface albedo decline is mainly influenced by sea ice extent indicating that the retreat of the ice edge is the most important process to constrain the surface albedo feedback. This study provides insights into factors contributing to the spread and changes in Arctic surface albedo and the associated sea ice albedo feedback.

Patrick C Taylor↗

The Influence of Sea ice on Arctic Cloud Properties: What Can We Learn by Applying a In Situ Observational Strategy to Satellite Data?

Sea ice is declining because of anthropogenic climate change. This change alters many aspects of the Arctic climate system, including the way that the surface and atmosphere interact. Atmosphere-surface coupling processes represent an important cloud feedback mechanism that can alter the Arctic surface energy budget. For the Arctic, it has been hypothesized that a reduction in sea ice cover could lead to an increase in clouds. If this process were to occur as originally hypothesized, sea ice loss in all seasons would lead to an increase in clouds. Recent observational studies find a cloud response to sea ice loss in non-summer months and no cloud response in summer months. However, previous studies rely on inter-annual variability and reanalysis to control for the influence of meteorology, reducing the confidence in the resulting conclusions. We adopt a phenomenological, event-based approach that does not need to use meteorological reanalysis. The approach analyzes cloud properties derived from CALIPSO-CloudSat over sea ice and adjacent ice-free footprints by compositing individual satellite ground tracks that cross the Arctic sea ice edge. The underlying assumption, which we verify, is that footprints that are close to each other in space and time experience similar large-scale meteorological conditions. Our results show larger cloud fraction and more cloud liquid water over ice-free than over sea ice footprints and provide additional evidence for a seasonal dependence of cloud-sea ice coupling that is in line with previous work. We find a different result where the maximum cloud property differences between sea ice and ice-free ocean occurs in spring, not fall as earlier studies suggest. We argue that these cloud differences between sea ice and ice-free ocean are primarily caused by the influence of the surface type on the thermodynamic stability of the lower troposphere and not principally from an increase in surface evaporation. In addition, we explore the sensitivity of these results to marginal ice zone width, season, Atlantic vs. Pacific sector, and the cloud property dependence on the distance from the sea ice edge. Overall, our results provide further evidence that cloud-sea ice coupling processes are not offsetting the observed surface energy budget perturbation due to sea ice loss in summer; thus, the cloud response to declining sea ice appears to contribute to amplified Arctic warming.

Patrick C Taylor↗

Preliminary design for Arctic atmospheric radiative transfer experiments

If current plans are realized, within the next few years, an extraordinary set of coordinated research efforts focusing on energy flows in the Arctic will be implemented. All are motivated by the prospect of global climate change. SHEBA (Surface Energy Budget of the Arctic Ocean), led by the National Science Foundation (NSF) and the Office of Naval Research (ONR), involves instrumenting an ice camp in the perennial Arctic ice pack, and taking data for 12-18 months. The ARM (Atmospheric Radiation Measurement) North Slope of Alaska and Adjacent Arctic Ocean (NSA/AAO) Cloud and Radiation Testbed (CART) focuses on atmospheric radiative transport, especially in the presence of clouds. The NSA/AAO CART involves instrumenting a sizeable area on the North Slope of Alaska and adjacent waters in the vicinity of Barrow, and acquiring data over a period of about 10 years. FIRE (First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment) Phase 3 is a program led by the National Aeronautics and Space Administration (NASA) which focuses on Arctic clouds, and which is coordinated with SHEBA and ARM. FIRE has historically emphasized data from airborne and satellite platforms. All three program anticipate initiating Arctic data acquisition during spring, 1997. In light of his historic opportunity, the authors discuss a strawman atmospheric radiative transfer experimental plan that identifies which features of the radiative transport models they think should be tested, what experimental data are required for each type of test, the platforms and instrumentation necessary to acquire those data, and in general terms, how the experiments could be conducted. Aspects of the plan are applicable to all three programs.

Zak, B. D.↗

Analysis of atmosphere-sea ice interactions in the Arctic basin using ESMR microwave data

Data from the Electrically Scanning Microwave Radiometer (ESMR) on Nimbus-5 are used to determine the spatial and temporal patterns of change in microwave brightness signatures of Arctic sea ice during a full annual cycle (1973/74). Interactions of ice conditions with the atmosphere are examined using grid point data for surface air temperature and atmospheric pressure. Principal components analysis is used to examine the major elements present in the microwave and atmospheric data. Component scores from these analyses are then used in a canonical correlation analysis to determine interassociations present between the ice and atmosphere in the Beaufort Sea and the European sectors on a synoptic time scale. The synoptic weather conditions associated with the pattern of snow melt on the ice in spring 1974 are described, and a clarification of possible alternative interpretations of features identified as polynyi occurring at 80-85 deg N during the late summer 1974 is presented.

Crane, R. G.↗

Polar stratospheric cloud climatology based on Stratospheric Aerosol Measurement II observations from 1978 to 1989

The probability of polar stratospheric cloud (PSC) occurrence in the Antarctic and Arctic has been estimated using Stratospheric Aerosol Measurement (SAM) II aerosol extinction data from 1978 to 1989. Antarctic PSCs are typically observed by SAM II from mid-May to early November, with a maximum zonal average probability of about 0.6 at 18-20 km in August. The typical Arctic PSC season extends only from late November to early March, with a peak zonal average probability of about 0.1 in early February at 20-22 km. There is considerable year-to-year variability in Arctic PSC sightings because of changes in the dynamics of the northern polar vortex. Year-to-year variability in Antarctic sightings is most prominent in the number of late season clouds. Maximum PSC sighting probabilities in both polar regions occur in the region from 90 deg W through the Greenwich meridian to 90 deg E, where temperatures are coldest on average. Arctic sighting probabilities approach zero outside this region, but clouds have been sighted in the Antarctic at all longitudes during most months. Inferred PSC formation temperatures remain constant throughout the Arctic winter and are similar to those in early Antarctic winter. PSC formation temperatures in the Antarctic drop markedly in the 15 to 20-km region by September, a pattern consistent with the irreversible loss of HNO3 and H2O vapor in sedimenting PSC particles.

Poole, Lamont R.↗

Harnessing: Technologies for Sustainable Reindeer Husbandry in the Arctic

To accelerate the development of sustainable reindeer husbandry under the lead of indigenous reindeer herders, it is critical to empower reindeer herders with the best available technologies and to promote a new kind of science where traditional knowledge is fully integrated into the scientific management of the natural environment in the Arctic. This is particularly true given the dramatic environmental, climatic, economic, social and industrial changes, which have taken place across the Arctic in recent years, all of which have had serious impacts on the reindeer herding communities of the North. The Anar Declaration, adopted by the 2d World Reindeer Herders Congress (WRHC), in Inari, Finland, June 2001drew guidelines for the development of a sustainable reindeer husbandry based on reindeer peoples values and goals. The declaration calls for the reindeer herding peoples to be given the possibilities to develop and influence the management of the reindeer industry and its natural environment because of their knowledge and traditional practices. At the same time, Arctic scientists from many institutions and governments are carrying out increasingly highly technical reindeer related research activities. It is important that the technologies and results of these activities be more commonly co-produced with the reindeer herder community and/or made more readily available to the reindeer peoples for comparison with traditional knowledge for improved herd management. This paper describes a project in which reindeer herders and scientists are utilizing technologies to create a system for collecting and sharing knowledge. The project, Reindeer Mapper, is creating an information management and knowledge sharing system, which will help make technologies more readily available to the herder community for observing, data collection and analysis, monitoring, sharing, communications, and dissemination of information - to be integrated with traditional, local knowledge. The paper describes some of the technologies which comprise the system including an intranet system to enable the team members to work together and share information electronically, remote sensing data for monitoring environmental parameters important to reindeer husbandry (e.g. SAR, Landsat), acquisition of ground-based measurements, and the GIS-based information management and knowledge sharing system.

Maynard, Nancy G.↗

Defining Burned Area in the Arctic: Examples from Small Fires in the Southeastern United States

Burning of small fires in the Arctic is important to climate change related processes and in the past the importance has been overlooked. Similarly, small fire burning in the Southeast United states has been underestimated and overlooked, but has just as much burned area as wildfires in the Western United States. Using FIREX-AQ campaign data, we are looking at the ability of satellites to detected the fires. Possible similarities in small fires between the Central and Southeastern US and the Arctic give ideas for collaboration and quantification of burned area.

Emily Gargulinski↗

Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.

land data assimilation↗

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗

Effect of Recent Sea Surface Temperature Trends on the Arctic Stratospheric Vortex

The springtime Arctic polar vortex has cooled significantly over the satellite era, with consequences for ozone concentrations in the springtime transition season. The causes of this cooling trend are deduced by using comprehensive chemistry-climate model experiments. Approximately half of the satellite era early springtime cooling trend in the Arctic lower stratosphere was caused by changing sea surface temperatures (SSTs). An ensemble of experiments forced only by changing SSTs is compared to an ensemble of experiments in which both the observed SSTs and chemically- and radiatively-active trace species are changing. By comparing the two ensembles, it is shown that warming of Indian Ocean, North Pacific, and North Atlantic SSTs, and cooling of the tropical Pacific, have strongly contributed to recent polar stratospheric cooling in late winter and early spring, and to a weak polar stratospheric warming in early winter. When concentrations of ozone-depleting substances and greenhouse gases are fixed, polar ozone concentrations show a small but robust decline due to changing SSTs. Ozone changes are magnified in the presence of changing gas concentrations. The stratospheric changes can be understood by examining the tropospheric height and heat flux anomalies generated by the anomalous SSTs. Finally, recent SST changes have contributed to a decrease in the frequency of late winter stratospheric sudden warmings.

Arctic↗