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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Interannual differences of Geosat altimeter heights and sea level - The importance of a datum

Sea surface height data from the Geosat altimeter are compared with island sea level data from 18 gages in the western and central tropical Pacific during December 1986 to November 1987. Care was taken to ensure that the two data sets are referenced to the same mean surface. This was done by requiring that both data sets have a zero mean sea level over the period April 1985 to April 1986. When the annual means are computed at each station in the later time period, it is found that the annual mean sea surface height values have drifted away from the corresponding sea level values by as much as 16 cm. Further, the pattern of differences that develop between the two data sets is not random but is spatially coherent with a strong east-west gradient. These observations illustrate the necessity for sea surface height data to be referred to a well-defined zero point, a datum, in order to reliably monitor interannual changes in the sea surface topography. Until these differences can be eliminated, it will be necessary to use tide gage data as benchmarks for the altimeter sea surface height data.

Wyrtki, Klaus↗
NASA NTRS1998

Sea Ice on the Southern Ocean

Year-round satellite records of sea ice distribution now extend over more than two decades, providing a valuable tool to investigate related characteristics and circulations in the Southern Ocean. We have studied a variety of features indicative of oceanic and atmospheric interactions with Antarctic sea ice. In the Amundsen & Bellingshausen Seas, sea ice extent was found to have decreased by approximately 20% from 1973 through the early 1990's. This change coincided with and probably contributed to recently warmer surface conditions on the west side of the Antarctic Peninsula, where air temperatures have increased by approximately 0.5 C/decade since the mid-1940's. The sea ice decline included multiyear cycles of several years in length superimposed on high interannual variability. The retreat was strongest in summer, and would have lowered the regional mean ice thickness, with attendant impacts upon vertical heat flux and the formation of snow ice and brine. The cause of the regional warming and loss of sea ice is believed to be linked to large-scale circulation changes in the atmosphere and ocean. At the eastern end of the Weddell Gyre, the Cosmonaut Polyna revealed greater activity since 1986, a recurrence pattern during recent winters and two possible modes of formation. Persistence in polynya location was noted off Cape Ann, where the coastal current can interact more strongly with the Antarctic Circumpolar Current. As a result of vorticity conservation, locally enhanced upwelling brings warmer deep water into the mixed layer, causing divergence and melting. In the Ross Sea, ice extent fluctuates over periods of several years, with summer minima and winter maxima roughly in phase. This leads to large interannual cycles of sea ice range, which correlate positively with meridinal winds, regional air temperatures and subsequent shelf water salinities. Deep shelf waters display considerable interannual variability, but have freshened by approximately 0.03/decade since the late 1950's. That could have slowed the thermohaline circulation beneath the Ross Ice Shelf and the properties or volume of local bottom water production.

Jacobs, Stanley S.↗
NASA NTRS1998

Spatial Distribution of Trends and Seasonality in the Hemispheric Sea Ice Covers

We extend earlier analyses of a 9-year sea ice data set that described the local seasonal and trend variations in each of the hemispheric sea ice covers to the recently merged 18.2-year sea ice record from four satellite instruments. The seasonal cycle characteristics remain essentially the same as for the shorter time series, but the local trends are markedly different, in some cases reversing sign. The sign reversal reflects the lack of a consistent long-term trend and could be the result of localized long-term oscillations in the hemispheric sea ice covers. By combining the separate hemispheric sea ice records into a global one, we have shown that there are statistically significant net decreases in the sea ice coverage on a global scale. The change in the global sea ice extent, is -0.01 +/- 0.003 x 10(exp 6) sq km per decade. The decrease in the areal coverage of the sea ice is only slightly smaller, so that the difference in the two, the open water within the packs, has no statistically significant change.

Gloersen, P.↗
NASA NTRS1997

ERS satellite microwave radar observations of Antarctic sea-ice dynamics

ERS-1 and ERS-2 scatterometer and synthetic aperture radar (SAR) data are used to monitor and track large and small scale sea ice dynamics in the Southern Ocean, and in particular in the Weddell Sea, Antarctica. Sea ice formation in the Weddell Sea regulates vertical and horizontal thermohaline circulation and influences bottom water production rates. Significant seasonal to interannual variability is observed in the sea ice drift dynamics. Coupled model simulations reproduce this variability and indicate that there is significant interannual variability in Weddelll Sea ice formation, drifts and extent on the El Nino southern oscillation (ENSO) timescale, with a period of approximately eight years. Changes in ice dynamics on these timescales regulate the amount of sea ice divergence and polynya formation. Anomalies in the timing and duration of the opening of the Ronne ice shelf polynya system are closely related to the variability in outflow of Weddell Sea bottom water measured at Joinville Island.

Drinkwater, Mark R.↗
NASA NTRS1998

Wind Forcing of the North Sea Pole Tide

The Chandler wobble of the earth's rotation has a period near 14 months and sets up the 0.5 cm amplitude pole tide in the deep oceans, However, the pole tide is anomalously large in the North Sea, where the amplitude increases sharply up to 3 cm along the continental coast. It is shown here that the sea levels are well correlated with winds at the pole tide frequency. The Princeton Ocean Model is used to investigate the response of the North Sea to wind forcing. The barotropic numerical ocean model depicts realistic coastlines and bathymetry at 5 ft x 5 ft resolution, with 97 x 73 grid points. The monthly mean wind fields for the 40-year period (1958-1997) from the National Centers for Atmospheric Prediction (NCEP) reanalysis were used to force the model. The winds were converted to stress with a neutral drag coefficient that varied linearly with windspeed (instead of using the NCEP windstress). A 5-day simulation was made for each month until the resulting flow regime came into equilibrium, and model water levels at various station locations were saved for comparison with tidal-gauge observed sea levels from the Permanent Service for Mean Sea Level (PSMSL). The comparison is made for 10 North Sea stations with high quality tide gauge data. We find: (1) good agreement in annual and semi-annual phases and in the trend of amplitude w.r.t. latitude; (2) more importantly for this study, the model-predicted and observed non-seasonal sea level variations show a very significant temporal correlation as well as spectral coherence. However, a large amplitude difference exists between the two sets -- the overall amplitude variability of the observed is generally a factor of 2-3 larger than the model prediction (this same phenomenon has been reported in ocean circulation studies, although the cause is not yet clear.) Our results indicate that the wind forcing is the main cause of the observed large pole tide in the North Sea.

OConnor, W.↗
NASA NTRS1999

The Formation each Winter of the Circumpolar Wave in the Sea Ice around Antarctica

Seeking to improve upon the visualization of the Antarctic Circumpolar Wave (ACW) , we compare a 16-year sequence of 6-month winter averages of Antarctic sea ice extents and concentrations with those of adjacent sea surface temperatures (SSTs). Here we follow SSTs around the globe along the maximum sea ice edge rather than in a zonal band equatorward of it. The results are similar to the earlier ones, but the ACWs do not propagate with equal amplitude or speed. Additionally in a sequence of 4 polar stereographic plots of these SSTs and sea ice concentrations, we find a remarkable correlation between SST minima and sea ice concentration maxima, even to the extent of matching contours across the ice-sea boundary, in the sector between 900E and the Palmer Peninsula. Based on these observations, we suggest that the memory of the ACW in the sea ice is carried from one Austral winter to the next by the neighboring SSTS, since the sea ice is nearly absent in the Austral summer.

Gloersen, Per↗
NASA NTRS2001

Comparison of DMSP SSM/I and Landsat 7 ETM+ Sea Ice Concentrations During Summer Melt

As part of NASA's EOS Aqua sea ice validation program for the Advanced Microwave Scanning Radiometer (AMSR-E), Landsat 7 Enhanced Thematic Mapper (ETM+) images were acquired to develop a sea ice concentration data set with which to validate AMSR-E sea ice concentration retrievals. The standard AMSR-E Arctic sea ice concentration product will be obtained with the enhanced NASA Team (NT2) algorithm. The goal of this study is to assess the accuracy to which the NT2 algorithm, using DMSP Special Sensor Microwave Imager radiances, retrieves sea ice concentrations under summer melt conditions. Melt ponds are currently the largest source of error in the determination of Arctic sea ice concentrations with satellite passive microwave sensors. To accomplish this goal, Landsat 7 ETM+ images of Baffin Bay were acquired under clear sky conditions on the 26th and 27th of June 2000 and used to generate high-resolution sea ice concentration maps with which to compare the NT2 retrievals. Based on a linear regression analysis of 116 25-km samples, we find that overall the NT2 retrievals agree well with the Landsat concentrations. The regression analysis yields a correlation coefficient of 0.98. In areas of high melt ponding, the NT2 retrievals underestimate the sea ice concentrations by about 12% compared to the Landsat values.

Cavalieri, Donald J.↗
NASA NTRS2005

Sea Ice Kinematics and Thickness from RGPS: Observations and Theory

The RADARSAT Geophysical Processor System (RGPS) has produced a wealth of data on Arctic sea ice motion, deformation, and thickness with broad geographical coverage and good temporal resolution. These data provide unprecedented spatial detail of the structure and evolution of the sea ice cover. The broad purpose of this study was to take advantage of the strengths of the RGPS data set to investigate sea ice kinematics and thickness, which affect the climate through their influence on ice production, ridging, and transport (i.e. mass balance); heat flux to the atmosphere; and structure of the upper ocean mixed layer. The objectives of this study were to: (1) Explain the relationship between the discontinuous motion of the ice cover and the large-scale, smooth wind field that drives the ice; (2) Characterize the sea ice deformation in the Arctic at different temporal and spatial scales, and compare it with deformation predicted by a state-of-theart ice/ocean model; and (3) Compare RGPS-derived sea ice thickness with other data, and investigate the thinning of the Arctic sea ice cover as seen in ULS data obtained by U.S. Navy submarines. We briefly review the results of our work below, separated into the topics of sea ice deformation and sea ice thickness. This is followed by a list of publications, meetings and presentations, and other activities supported under this grant. We are attaching to this report copies of all the listed publications. Finally, we would like to point out our community service to NASA through our involvement with the ASF User Working Group and the RGPS Science Working Group, as evidenced in the list of meetings and presentations below.

Stern, Harry↗
NASA NTRS2006

EOS Aqua AMSR-E Arctic Sea-Ice Validation Program: Arctic2006 Aircraft Campaign Flight Report

In March 2006, a coordinated Arctic sea-ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed. This campaign was the second Alaskan Arctic field campaign for validating the Earth Observing System (EOS) Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. The first campaign was completed in March 2003. The AMSR-E, designed and built by the Japanese Space Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The AMSR-E sea-ice products to be validated include sea-ice concentration, sea-ice temperature, and snow depth on sea ice. The focus of this campaign was on the validation of snow depth on sea ice and sea-ice temperature. This flight report describes the suite of instruments flown on the P-3, the objectives of each of the six flights, the Arctic regions overflown, and the coordination among satellite, aircraft, and surface-based measurements.

Cavalieri, D. J.↗
NASA NTRS2006

Microwave Signatures of Snow on Sea Ice: Modeling

Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and ra- 'diometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances.

Powell, D. C.↗
NASA NTRS2011

Regional Changes in the Sea Ice Cover and Ice Production in the Antarctic

Coastal polynyas around the Antarctic continent have been regarded as sea ice factories because of high ice production rates in these regions. The observation of a positive trend in the extent of Antarctic sea ice during the satellite era has been intriguing in light of the observed rapid decline of the ice extent in the Arctic. The results of analysis of the time series of passive microwave data indicate large regional variability with the trends being strongly positive in the Ross Sea, strongly negative in the Bellingshausen/Amundsen Seas and close to zero in the other regions. The atmospheric circulation in the Antarctic is controlled mainly by the Southern Annular Mode (SAM) and the marginal ice zone around the continent shows an alternating pattern of advance and retreat suggesting the presence of a propagating wave (called Antarctic Circumpolar Wave) around the circumpolar region. The results of analysis of the passive microwave data suggest that the positive trend in the Antarctic sea ice cover could be caused primarily by enhanced ice production in the Ross Sea that may be associated with more persistent and larger coastal polynyas in the region. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate-of-increase in the net ice export of about 30,000 km2 per year. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 km3/year, which is almost identical, within error bars, to our estimate of the trend in ice production. In addition to the possibility of changes in SAM, modeling studies have also indicated that the ozone hole may have a role in that it causes the deepening of the lows in the western Antarctic region thereby causing strong winds to occur offthe Ross-ice shelf.

Comiso, Josefino C.↗
NASA NTRS2011

Experiments in Reconstructing Twentieth-Century Sea Levels

One approach to reconstructing historical sea level from the relatively sparse tide-gauge network is to employ Empirical Orthogonal Functions (EOFs) as interpolatory spatial basis functions. The EOFs are determined from independent global data, generally sea-surface heights from either satellite altimetry or a numerical ocean model. The problem is revisited here for sea level since 1900. A new approach to handling the tide-gauge datum problem by direct solution offers possible advantages over the method of integrating sea-level differences, with the potential of eventually adjusting datums into the global terrestrial reference frame. The resulting time series of global mean sea levels appears fairly insensitive to the adopted set of EOFs. In contrast, charts of regional sea level anomalies and trends are very sensitive to the adopted set of EOFs, especially for the sparser network of gauges in the early 20th century. The reconstructions appear especially suspect before 1950 in the tropical Pacific. While this limits some applications of the sea-level reconstructions, the sensitivity does appear adequately captured by formal uncertainties. All our solutions show regional trends over the past five decades to be fairly uniform throughout the global ocean, in contrast to trends observed over the shorter altimeter era. Consistent with several previous estimates, the global sea-level rise since 1900 is 1.70 +/- 0.26 mm/yr. The global trend since 1995 exceeds 3 mm/yr which is consistent with altimeter measurements, but this large trend was possibly also reached between 1935 and 1950.

Ray, Richard D.↗
NASA NTRS2012

Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

Huntsberger, Terrance L.↗
NASA NTRS2011

Terrestrial Waters and Sea Level Variations on Interannual Time Scale

On decadal to multi-decadal time scales, thermal expansion of sea waters and land ice loss are the main contributors to sea level variations. However, modification of the terrestrial water cycle due to climate variability and direct anthropogenic forcing may also affect sea level. For the past decades, variations in land water storage and corresponding effects on sea level cannot be directly estimated from observations because these are almost non-existent at global continental scale. However, global hydrological models developed for atmospheric and climatic studies can be used for estimating total water storage. For the recent years (since mid-2002), terrestrial water storage change can be directly estimated from observations of the GRACE space gravimetry mission. In this study, we analyse the interannual variability of total land water storage, and investigate its contribution to mean sea level variability at interannual time scale. We consider three different periods that, each, depend on data availability: (1) GRACE era (2003-2009), (2) 1993-2003 and (3) 1955-1995. For the GRACE era (period 1), change in land water storage is estimated using different GRACE products over the 33 largest river basins worldwide. For periods 2 and 3, we use outputs from the ISBA-TRIP (Interactions between Soil, Biosphere, and Atmosphere-Total Runoff Integrating Pathways) global hydrological model. For each time span, we compare change in land water storage (expressed in sea level equivalent) to observed mean sea level, either from satellite altimetry (periods 1 and 2) or tide gauge records (period 3). For each data set and each time span, a trend has been removed as we focus on the interannual variability. We show that whatever the period considered, interannual variability of the mean sea level is essentially explained by interannual fluctuations in land water storage, with the largest contributions arising from tropical river basins.

Llovel, W.↗
NASA NTRS2020

Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline

Autotrophic single-celled algae living in sea ice (ice algae) and water column (phytoplankton) are the main primary producers in the Arctic Ocean. Through photosynthesis, they transform dissolved inorganic carbon into organic material. Consequently, primary production provides a key ecosystem service by providing energy to the entire food web in the oceans. Primary productivity is strongly dependent upon light availability and the presence of nutrients, and thus is highly seasonal in the Arctic. The melting and retreat of sea ice during spring are strong drivers of primary production in the Arctic Ocean and its adjacent shelf seas, owing to enhanced light availability and stratification (Barber et al. 2015; Leu et al. 2015; Ardyna et al. 2017). Recent studies have emphasized that primary production occurs under lower light conditions and earlier in the seasonal cycle than previously recognized (Randelhoff et al. 2020). Other studies suggest that increased nutrient supply have also influenced overall production (Henley et al. 2020; Lewis et al. 2020). Furthermore, while declines in Arctic sea ice extent over the past several decades (see essay Sea Ice) have contributed substantially to shifts in primary productivity throughout the Arctic Ocean, the response of primary production to sea ice loss has been both seasonally and spatially variable (e.g., Tremblay et al. 2015; Hill et al. 2018). Here we present satellite-based estimates of algal chlorophyll-a (occurring in all species of phytoplankton), based on ocean color, and subsequently provide calculated primary production estimates. These results are shown for ocean areas with less than 10% sea ice concentration and, therefore, do not include production by sea ice algae or under-ice phytoplankton blooms, which can be significant (e.g., Lalande et al. 2019).

K. E. Frey↗
NASA NTRSDate not supplied

Estimating the Arctic Cloud-Sea Ice Feedback With Observations during the EOS Period

Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.

Patrick C. Taylor↗
NASA NTRSDate not supplied

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗
NASA NTRS2023

Passive Microwave Arctic Sea Ice Melt Onset Dates From the Advanced Horizontal Range Algorithm 1979 - 2022

The onset of the summer melt season is a key stage of the Arctic sea ice seasonal cycle and is an indicator of climate change. Surface melting of the bare or snow-covered sea ice is detected using passive microwave satellite observations. The data set presented here is a 44 year record of Arctic sea ice annual melt onset (MO) dates for 1979–2022 produced using an updated version of the Advanced Horizontal Range Algorithm (AHRA). This data product contains annual maps of the sea ice MO date and a set of descriptive statistics summarizing the data. This paper describes a new update of the AHRA methodology, now AHRA V5, including key changes to the algorithm starting date and sea ice mask methodology to improve estimates of early-season MO dates especially near the sea ice periphery. AHRA V5 data are suitable for monitoring trends in Arctic and regional sea ice MO dates and for process studies of atmosphere-sea ice interactions during the early spring and summer months.

Angela C. Bliss↗