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NASA NTRS1997

A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I

Global climate studies have shown that sea ice is a critical component in the global climate system through its effect on the ocean and atmosphere, and on the earth's radiation balance. Polar energy studies have further shown that the distribution of thin ice and open water largely controls the distribution of surface heat exchange between the ocean and atmosphere within the winter Arctic ice pack. The thickness of the ice, the depth of snow on the ice, and the temperature profile of the snow/ice composite are all important parameters in calculating surface heat fluxes. In recent years, researchers have used various combinations of DMSP SSMI channels to independently estimate the thin ice type (which is related to ice thickness), the thin ice temperature, and the depth of snow on the ice. In each case validation efforts provided encouraging results, but taken individually each algorithm gives only one piece of the information necessary to compute the energy fluxes through the ice and snow. In this paper we present a comparison of the results from each of these algorithms to provide a more comprehensive picture of the seasonal ice zone using passive microwave observations.

St.Germain, Karen↗

NASA NTRS2024

Physics of the Seasonal Sea Ice Zone

The seasonal sea ice zone encompasses the region between the winter maximum and summer minimum sea ice extent. In both the Arctic and Antarctic, the majority of the ice cover can now be classified as seasonal. Here, we review the sea ice physics that governs the evolution of seasonal sea ice in the Arctic and Antarctic, spanning sea ice growth, melt, and dynamics and including interactions with ocean surface waves as well as other coupled processes. The advent of coupled wave–ice modeling and discrete-element modeling, together with improved and expanded satellite observations and field campaigns, has yielded advances in process understanding. Many topics remain in need of further investigation, including rheologies appropriate for seasonal sea ice, wave-induced sea ice fracture, welding for sea ice freeze-up, and the distribution of snow on seasonal sea ice. Future research should aim to redress biases (such as disparities in focus between the Arctic and Antarctic and between summer and winter processes) and connect observations to modeling across spatial scales.

sea ice↗

NASA NTRS1993

The seasonal cycle of low stratiform clouds

The seasonal cycle of low stratiform clouds is studied using data from surface-based cloud climatologies. The impact of low clouds on the radiation budget is illustrated by comparison of data from the Earth Radiation Budget Experiment with the cloud climatologies. Ten regions of active stratocumulus convection are identified. These regions fall into four categories: subtropical marine, midlatitude marine, Arctic stratus, and Chinese stratus. With the exception of the Chinese region, all the regions with high amounts of stratus clouds are over the oceans. In all regions except the Arctic, the season of maximum stratus corresponds to the season of greatest lower-troposphere static stability. Interannual variations in stratus cloud amount also are related to changes in static stability. A linear analysis indicates that a 6 percent increase in stratus fractional area coverage is associated with each 1 C increase in static stability. Over midlatitude oceans, sky-obscuring fog is a large component of the summertime stratus amount. The amount of fog appears to be related to warm advection across sharp gradients of SST.

Klein, Stephen A.↗

NASA NTRSDate not supplied

High Latitude Atmospheric Rivers: Teleconnections and Impacts

Atmospheric rivers (ARs) are long, narrow synoptic scale features that act as moisture transport vehicles by moving water vapor poleward. They are typically found in storm tracks and often have profound implications for regional hydroclimate. For high latitude locales such as Antarctica and the Arctic, ARs are fewer in number but often have an outsized impact by either producing significant snow accumulation events, or, depending on their thermal characteristics, initiating melt events on ice sheets, ice shelves, and sea ice. In this study, we apply both reanalysis and climate model data to evaluate high latitude ARs for both the Arctic and Antarctic in the context of teleconnections and modes of variability. Specifically, we fold in both MERRA-2 and ERA5 reanalysis as well as historical and climate change simulations from the CESM2 (Community Earth System Model, Version 2) and E3SMv2 (Energy Exascale Earth System Model, v2) with multiple ensemble members to better understand natural variability versus climate change signals. An overview of AR climatology and impacts will be presented, including a baseline uncertainty quantification analysis using data from ARTMIP (the Atmospheric River Tracking Method Intercomparison Project). AR impacts during specific modes of variability will be characterized by diagnosing precipitation and boundary layer temperature associated with Ars influencing the cryosphere. Modes of variability investigated include the SAM (Southern Annular Mode), PDO (Pacific Decadal Oscillation), PSA2 (Pacific South American Mode 2), the IOD (Indian Ocean Dipole), and the AO (Arctic Oscillation).

Atmospheric Rivers↗

NASA NTRS2009

NASA Global Hawk: A New Tool for Earth Science Research

This slide presentation reviews the Global Hawk, a unmanned aerial vehicle (UAV) that NASA plans to use for Earth Sciences research. The Global Hawk is the world's first fully autonomous high-altitude, long-endurance aircraft, and is capable of conducting long duration missions. Plans are being made for the use of the aircraft on missions in the Arctic, Pacific and Western Atlantic Oceans. There are slides showing the Global Hawk Operations Center (GHOC), Flight Control and Air Traffic Control Communications Architecture, and Payload Integration and Accommodations on the Global Hawk. The first science campaign, planned for a study of the Pacific Ocean, is reviewed.

Hall, Phill↗

NASA NTRS2022

The Future Intensification of the North Atlantic Winter Storm Track: The Key Role of Dynamic Ocean Coupling

Climate models project an intensification of the wintertime North Atlantic storm track, over its downstream region, by the end of this century. Previous studies have suggested that ocean-atmosphere coupling plays a key role in this intensification, but the precise role of the different components of the coupling has not been explored and quantified. In this paper, using a hierarchy of ocean coupling experiments, we isolate and quantify the respective roles of thermodynamic (changes in surface heat fluxes) and dynamic (changes in ocean heat flux convergence) ocean coupling in the projected intensification of North Atlantic transient eddy kinetic energy (TEKE). We show that dynamic coupling accounts for nearly all of the future TEKE strengthening as it overcomes the much smaller effect of surface heat flux changes to weaken the TEKE. We further show that by reducing the Arctic amplification in the North Atlantic, ocean heat flux convergence increases the meridional temperature gradient aloft, causing a larger eddy growth rate, and resulting in the strengthening of North Atlantic TEKE. Our results stress the importance of better monitoring and investigating the changes in ocean heat transport, for improving climate change adaptation strategies.

North Atlantic winter storms↗

NASA NTRS1998

Monitoring Oceanic Islands Via Radarsat Imaging Radar

Oceanic islands represent an often overlooked aspect of the land surface of Earth, yet they are sensitive, natural laboratories for investigating the impacts of environmental change on landscapes and land-cover systems. For this reason, we have utilized the Canadian Space Agency's RADARSAT satellite to initiate a program for monitoring the landscapes of approximately 20 oceanic islands as part of the RADARSAT Background Mission. To date, we have analyzed high resolution SAR images of 12 islands that extend from the Arctic, throughout the Atlantic and Southern Indian oceans, and into the equatorial Pacific. We have selected islands for monitoring on the basis of their known or suspected history of landscape change in association with environmental factors or anthropogenic effects.

Garvin, James B.↗

NASA NTRS1988

Preliminary observations of polar sea ice with the Special Sensor Microwave Imager

The Special Sensor Microwave Imager (SSM/I) was launched as part of the Defense Meteorological Satellite Program. The SSM/I operates at 19.4, 22.2, 37.0, and 85.5 GHz with horizontal and vertical polarizations measured at each frequency except 22 GHz which has only a vertical polarization channel. Examination of polarization and spectral gradient ratios derived from the SSM/I radiances for open ocean, first-year, and multiyear Arctic sea ice reveals striking differences between the ratios calculated using lower frequencies and those ratios using the 85 GHz channels. These differences may serve as the basis for deriving sea ice information.

Cavalieri, D. J.↗

NASA NTRS2000

UV 380 nm Reflectivity of the Earth's Surface

The 380 nm radiance measurements of TOMS (Total Ozone Mapping Spectrometer) have been converted into a global data set of daily (1979 to 1992) Lambert equivalent reflectivities R of the Earth's surface and boundary layer (clouds, aerosols, surface haze, and snow/ice). Since UV surface reflectivity is between 2 and 8% for both land and water during all seasons of the year (except for ice and snow cover), reflectivities larger than the surface value indicates the presence of clouds, haze, or aerosols in the satellite field of view. Statistical analysis of 14 years of daily data show that most snow/ice-free regions of the Earth have their largest fraction of days each year when the reflectivity is low (R less than 10%). The 380 nm reflectivity data shows that the true surface reflectivity is 2 to 3% lower than the most frequently occurring reflectivity value for each TOMS scene. The most likely cause of this could be a combination of frequently occurring boundary-layer water or aerosol haze. For most regions, the observation of extremely clear conditions needed to estimate the surface reflectivity from space is a comparatively rare occurrence. Certain areas (e.g., Australia, southern Africa, portions of northern Africa) are cloud-free more than 80% of the year, which exposes these regions to larger amounts of UV radiation than at comparable latitudes in the Northern Hemisphere. Regions over rain-forests, jungle areas, Europe and Russia, the bands surrounding the Arctic and Antarctic regions, and many ocean areas have significant cloud cover (R greater than 15%) more than half of each year. In the low to middle latitudes, the areas with the heaviest cloud cover (highest reflectivity for most of the year) are the forest areas of northern South America, southern Central America, the jungle areas of equatorial Africa, and high mountain regions such as the Himalayas or the Andes. The TOMS reflectivity data show the presence of large nearly clear ocean areas and the effects of the major ocean currents on cloud production.

Herman, J. R.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-27659-DND

The Arctic is warming fast, a trend expected to continue. Rapid Arctic warming has far-reaching implications affecting the global energy budget, sea level rise, the global carbon cycle, and potentially the atmospheric and oceanic circulation. Our understanding of the forcing mechanisms driving Arctic climate change has rapidly evolved in the last decade. For 40 years, the melting of sea ice and snow has been implicated as the primary driver of amplified Arctic warming, however our results indicate a shift, whereby changes in the atmospheric temperature, humidity, and clouds have surpassed the warming effects of snow and sea ice loss in the latest CMIP5 model simulations. We examine the impacts of climate feedbacks on the Arctic surface energy budget: namely surface albedo, clouds, shortwave clear-sky feedbacks, longwave clear-sky feedbacks, ocean heat content, and surface turbulent fluxes. Simulations from 16 CMIP5 models running RCP8.5, a high-emission scenario are used. We employ the methodology used in Lu and Cai (2009) on a single CMIP3 model allowing an analysis of changes between CMIP3 and CMIP5.

Robyn C Boeke↗

NASA NTRS2024

Connecting Global Modes of Variability to Climate in High Mountain Asia

Oscillations in global modes of variability (MoV) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Un-derstanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic Oscillation (AO), Eurasian teleconnection, Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (Nino34), with winter and summer climate in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2-m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and also using a lagged correlation analysis to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and Central China in both winter and summer and a positive correlation in Western China in summer. PRECTOT has a positive correlation with all MoV in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, espe-cially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time-windows and specific regions within HMA that exhibit high correlation between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.

teleconnections↗

NASA NTRS1999

The Great White Ocean

Satellite data have revealed overall decreases in the Arctic sea ice cover since the late 1970s, although with substantial interannual variability. The ice reductions are likely tied to an overall warming in the Arctic region over the same time period, although both the warming and the ice reductions could be connected to large-scale oscillations within the system. Should the ice reductions continue, consequences to the Arctic ecosystems and climate could be considerable.

Parkinson, Claire L.↗

NASA NTRS1988

Arctic Sea ice studies with passive microwave satellite observations

The objectives of this research are: (1) to improve sea ice concentration determinations from passive microwave space observations; (2) to study the role of Arctic polynyas in the production of sea ice and the associated salinization of Arctic shelf water; and (3) to study large scale sea ice variability in the polar oceans. The strategy is to analyze existing data sets and data acquired from both the DMSP SSM/I and recently completed aircraft underflights. Special attention will be given the high resolution 85.5 GHz SSM/I channels for application to thin ice algorithms and processes studies. Analysis of aircraft and satellite data sets is expected to provide a basis for determining the potential of the SSM/I high frequency channels for improving sea ice algorithms and for investigating oceanic processes. Improved sea ice algorithms will aid the study of Arctic coastal polynyas which in turn will provide a better understanding of the role of these polynyas in maintaining the Arctic watermass structure. Analysis of satellite and archived meteorological data sets will provide improved estimates of annual, seasonal and shorter-term sea ice variability.

Cavalieri, D. J.↗

NASA NTRS1996

(abstract) High-Resolution Satellite Microwave Radar Observation of Climate-Related Sea-Ice Anomalies

Since 1991 a suite of international satellites have collected large amounts of high-resolution microwave radar images over Arctic and Antarctic sea ice. Together with complementary synthetic aperture radar (SAR) 100 m resolution microwave imaging, these data provide a powerful tool for addressing the characteristics of sea ice which directly influence the polar oceans and climate.

NSCAT Arctic Antarctic imaging open-ocean polynyas↗

NASA NTRSDate not supplied

On the Nature of the Arctic’s Positive Lapse-rate Feedback: Cause or Symptom of Arctic Amplification

Radiative energy fluxes exiting the atmosphere towards the surface and to space are sensitive to the vertical structure of temperature. Under anthropogenic forcing, this sensitivity gives rise to the lapse-rate feedback. Shown to be negative in the tropics and positive in the Arctic, studies argue that the lapse-rate feedback is the primary cause of Arctic Amplification. While mechanistically the negative tropical lapse-rate feedback is understood, the mechanics of the positive Arctic lapse-rate feedback are less clear. Previous arguments state that the Arctic’s stable stratification is the origin of its positive lapse-rate feedback. We present results using CMIP5 and CMIP6 model output that arguing that the magnitude, spatial variability, seasonality, and inter-model spread in the Arctic lapse-rate feedback is controlled by surface properties and atmosphere-ocean-sea ice energy exchanges, not the degree of stable stratification. We argue that the Arctic’s positive lapse-rate feedback is a seasonal and regional phenomenon that manifests from local surface characteristics and surface albedo, ice insulation, and thermal inertia feedbacks that cause surface warming to outpace atmospheric warming in sea ice-retreat regions. We view the Arctic’s positive lapse-rate feedback as a symptom rather than the primary cause of Arctic Amplification.

Patrick Charles Taylor↗

NASA NTRSDate not supplied

On the Nature of the Arctic’s Positive Lapse Rate Feedback Cause or Symptom of Arctic Amplification

Patrick C Taylor↗

NASA NTRS2012

The Search for Life on Mars

For centuries, the planet Mars has been regarded as a possible abode for life. Serious searches for the signatures of life began in the 19th century, and continue via telescopic investigations and landed missions. While early work focused on phenomenology and bordered on fantasy, modern scientific inquiry has emphasized the search for chemical signatures of life in the soil and rocks at the planet's surface, and the search for biomarker gases in the atmosphere. Living systems produce more than 90% of Earth's atmospheric methane; the balance is of geochemical origin. The discovery of methane on Mars will be described, along with the ongoing extended search for clues to its origins. The possible origins of Mars methane will be discussed in the context of terrestrial analogue sites where geologic and biologic methane production now occurs - ranging from sub-permafrost zones in the arctic to hydrothermal vents in the deep ocean. Terrestrial organisms that could prosper on Mars today will be mentioned. I will briefly touch upon experiments conducted by landed spacecraft, ranging from the Viking Life Science Experiments in 1976 to the impending Mars Science laboratory, and the Trace Gas Orbiter and ExoMars missions now being developed for flight in the coming decade.

Mumma, Michael J.↗

NASA NTRS2022

Assimilation of Sea Ice Thickness Derived from Cryosat-2 Along-Track Freeboard Measurements into the Met Office's Forecast Ocean Assimilation Model (FOAM)

The feasibility of assimilating sea ice thickness (SIT) observations derived from CryoSat-2 along-track measurements of sea ice freeboard is successfully demonstrated using a 3D-Var assimilation scheme, NEMOVAR, within the Met Office's global, coupled ocean–sea-ice model, Forecast Ocean Assimilation Model (FOAM). The CryoSat-2 Arctic freeboard measurements are produced by the Centre for Polar Observation and Modelling (CPOM) and are converted to SIT within FOAM using modelled snow depth. This is the first time along-track observations of SIT have been used in this way, with other centres assimilating gridded and temporally averaged observations. The assimilation leads to improvements in the SIT analysis and forecast fields generated by FOAM, particularly in the Canadian Arctic. Arctic-wide observation-minus-background assimilation statistics for 2015–2017 show improvements of 0.75 m mean difference and 0.41 m root-mean-square difference (RMSD) in the freeze-up period and 0.46 m mean difference and 0.33 m RMSD in the ice break-up period. Validation of the SIT analysis against independent springtime in situ SIT observations from NASA Operation IceBridge (OIB) shows improvement in the SIT analysis of 0.61 m mean difference (0.42 m RMSD) compared to a control without SIT assimilation. Similar improvements are seen in the FOAM 5 d SIT forecast. Validation of the SIT assimilation with independent Beaufort Gyre Exploration Project (BGEP) sea ice draft observations does not show an improvement, since the assimilated CryoSat-2 observations compare similarly to the model without assimilation in this region. Comparison with airborne electromagnetic induction (Air-EM) combined measurements of SIT and snow depth shows poorer results for the assimilation compared to the control, despite covering similar locations to the OIB and BGEP datasets. This may be evidence of sampling uncertainty in the matchups with the Air-EM validation dataset, owing to the limited number of observations available over the time period of interest. This may also be evidence of noise in the SIT analysis or uncertainties in the modelled snow depth, in the assimilated SIT observations, or in the data used for validation. The SIT analysis could be improved by upgrading the observation uncertainties used in the assimilation. Despite the lack of CryoSat-2 SIT observations available for assimilation over the summer due to the detrimental effect of melt ponds on retrievals, it is shown that the model is able to retain improvements to the SIT field throughout the summer months due to prior, wintertime SIT assimilation. This also results in regional improvements to the July modelled sea ice concentration (SIC) of 5 % RMSD in the European sector, due to slower melt of the thicker sea ice.

Emma K. Fiedler↗