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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A New Ecosystem Model for Arctic Phytoplankton Phenology From Ice‐Covered to Open‐Water Periods: Implications for Future Sea Ice Retreat Scenarios

Abstract To predict ecosystem change in the Arctic Ocean, understanding Arctic phytoplankton phenology is essential. We develop a marine ecosystem model focusing on phytoplankton dynamics and the competition for multiple resources based on knowledge from in situ data obtained in the Chukchi Sea. The model is designed to include the unique ecological characteristics of the Arctic Ocean. To the best of our knowledge, this is the first model successfully simulating the current paradigm for Arctic phytoplankton phenology, including both under‐ice blooms and succession of phytoplankton groups. Sensitivity experiments show that the dominance of diatoms can be sustained by lateral transport of a high‐silicate water mass (Pacific Winter Water). Experiments for future scenarios show that sea ice retreat drives a decrease in large diatoms and an increase in the other relatively small non‐diatom groups. These results suggest that dominant phytoplankton groups can be shifted from diatoms to non‐diatoms under ongoing Arctic Ocean sea ice retreat.

Choi, Jang‐Geun↗
NASA NTRS1999

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Bosilovich, Michael G.↗
NASA NTRS2011

Maritime Aerosol Network as a Component of AERONET - First Results and Comparison with Global Aerosol Models and Satellite Retrievals

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurement areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops handheld sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations.

Smirnov, A.↗
NASA NTRS2020

A Global End-Member Approach to Derive aCDOM(440) from Near-Surface Optical Measurements

This study establishes an optical inversion scheme for deriving the absorption coefficient of colored (or chromophoric, depending on the literature) dissolved organic material (CDOM) at the 440 nm wavelength, which can be applied to global water masses with near-equal efficacy. The approach uses a ratio of diffuse attenuation coefficient spectral end members, i.e., a short and long wavelength pair. The global perspective is established by sampling "extremely" clear water plus a generalized extent in turbidity and optical properties that each span three decades of dynamic range. A unique data set was collected in oceanic, coastal, and inland waters (as shallow as 0.6 m) from the North Pacific Ocean, the Arctic Ocean, Hawaii, Japan, Puerto Rico, and the east and west coasts of the United States. The data were partitioned using subjective categorizations to define a validation quality subset of conservative water masses, i.e., the inflow and outflow of properties constrain the range in the gradient of a constituent, plus 15 subcategories of water masses that were not evolving conservatively. The dependence on subcategories was confirmed with an objective methodology based on cluster analysis techniques. The latter defined five distinct classes with validation quality data present in all classes, but which also decreased in percent composition as a function of increasing class number and optical complexity. Four different algorithms based on different validation quality end members were validated with accuracies of 1.–6.2 %, wherein pairs with the largest spectral span were most accurate. Although algorithm accuracy decreased with the inclusion of more subcategories containing non-conservative water masses, changes to the algorithm fit were small when a preponderance of subcategories were included. The high accuracy for all end-member algorithms was the result of data acquisition and data processing improvements, e.g., increased vertical sampling resolution to less than 1mm and a boundary constraint to mitigate wave focusing effects, respectively. An independent evaluation with a historical database confirmed the consistency of the algorithmic approach and its application to quality assurance, e.g., to flag data outside expected ranges, identify suspect spectra, and objectively determine the in-water extrapolation interval by converging agreement for all applicable end-member algorithms. The legacy data exhibit degraded performance (as 44 % uncertainty) due to a lack of high-quality near-surface observations, especially for clear waters wherein wave-focusing effects are problematic. The novel optical approach allows the in situ estimation of an in-water constituent in keeping with the accuracy obtained in the laboratory.

Stanford B Hooker↗
NASA NTRS2017

Radiative Impacts of Further Arctic Sea Ice Melt: Using past Observations to Inform Future Climate Impacts

The Arctic region has seen dramatic changes over the past several decades, from polar amplification of global temperature rise to ecosystem changes to the decline of the sea ice. While there has been much speculation as to when the world will see an ice-free Arctic, the radiative impacts of an eventual disappearance of the Arctic sea ice are likely to be significant regardless of the timing. Using CERES radiation and microwave satellite sea ice data, Pistone et al (2014) estimated the radiative forcing due to albedo changes associated with the Arctic sea ice retreat over the 30 years of the satellite data record. In this study, we found that the Arctic Ocean saw a decrease in all-sky albedo of 4% (from 52% to 48%), for an estimated increase in solar heating of 6.4 W/m(exp 2) between 1979 and 2011, or 0.21 W/m(exp 2) when averaged over the globe. This value is substantial--approximately 25% as large as the forcing due to the change in CO2 during the same period. Here we update and expand upon this previous work and use the CERES broadband shortwave observations to explore the radiative impacts of a transition to completely ice-free Arctic Ocean. We estimate the annually-averaged Arctic Ocean planetary albedo under ice-free and cloud-free conditions to be 14% over the region, or approximately 25% lower in absolute terms than the Arctic Ocean cloud-free albedo in 1979. However, the question of all-sky conditions (i.e. including the effects of clouds) introduces a new level of complexity. We explore several cloud scenarios and the resultant impact on albedo. In each of these cases, the estimated forcing is not uniformly distributed throughout the year. We describe the relative contributions of ice loss by month as well as the spatial distributions of the resulting changes in absorbed solar energy. The seasonal timing and location—in addition to magnitude—of the altered solar absorption may have significant implications for atmospheric and ocean dynamics in the Arctic and at lower latitudes; this observationally-based estimate of the large-scale characteristics of an ice-free Arctic thus provides a valuable tool to complement and validate model-based assessments of future climate.

Pistone, K.↗
NASA NTRS2018

On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review

Forty years ago, climate scientists predicted the Arctic to be on of Earth’s most sensitive climate regions and thus extremely vulnerable to increased CO2. The rapid and unprecedented changes observed in the Arctic confirm this prediction, which has consequences that ripple through the global climate system. Especially significant, sea ice loss is altering the exchange of mass, energy, and momentum between the atmosphere and Arctic Ocean. A thick, extensive, and multiyear ice cover has historically limited such exchanges, however, the summertime Arctic Ocean is expected to be nearly ice‐free within 15 years increasing the potential for air‐sea exchange. Changes in surface turbulent fluxes can alter the Arctic surface energy budget, sea ice, clouds, boundary layer temperature and humidity, and atmospheric and oceanic circulations. This paper reviews current knowledge of surface turbulent fluxes across the Arctic Ocean and the known effects on climate. We conclude that Arctic air‐sea energy exchanges are becoming an increasingly consequential factor driving Arctic climate. Arctic Ocean surface turbulent energy exchanges are not smooth and steady but rather irregular and episodic, considering this nature of air‐sea energy exchanges is essential for improving Arctic climate projections. New field data focusing on the episodic nature of air‐sea exchange will accelerate our understanding of Arctic climate change.

Taylor, Patrick C.↗
NASA NTRS1979

Arctic Sea ice decay simulated for a CO2-induced temperature rise

A large scale numerical time-dependent model of sea ice that takes into account the heat fluxes in and out of the ice, the seasonal occurrence of snow, and ice motions was used in an experiment to determine the response of the Arctic Ocean ice pack to a warming of the atmosphere. The degree of warming specified is that expected for a doubling of atmospheric carbon dioxide with its associated greenhouse effect, a condition that could occur before the middle of the next century. The results of three 5-year simulations with a warmer atmosphere and varied boundary conditions were: (1) that in the face of a 5 K surface atmospheric temperature increase the ice pack disappeared completely in August and September but reformed in the central Arctic Ocean in mid fall; (2) that the simulations were moderately dependence on assumptions concerning cloud cover; and (3) that even when atmospheric temperature increases of 6-9 K were combined with an order-of-magnitude increase in the upward heat flux from the ocean, the ice still appeared in winter. It should be noted that a year-round ice-free Arctic Ocean has apparently not existed for a million years or more.

Heat flux↗
NASA NTRS2000

Arctic Climate and Atmospheric Planetary Waves

Analysis of a fifty-year record (1946-1995) of monthly-averaged sea level pressure data provides a link between the phases of planetary-scale sea level pressure waves and Arctic Ocean and ice variability. Results of this analysis show: (1) a breakdown of the dominant wave I pattern in the late 1960's, (2) shifts in the mean phase of waves 1 and 2 since this breakdown, (3) an eastward shift in the phases of both waves 1 and 2 during the years of simulated cyclonic Arctic Ocean circulation relative to their phases during the years of anticyclonic circulation, (4) a strong decadal variability of wave phase associated with simulated Arctic Ocean circulation changes. Finally, the Arctic atmospheric circulation patterns that emerge when waves 1 and 2 are in their extreme eastern and western positions suggest an alternative approach to determine significant forcing patterns of sea ice and high-latitude variability.

Cavalieri, D. J.↗
NASA NTRS2001

Arctic Climate and Atmospheric Planetary Waves

Analysis of a fifty-year record (1946-1995) of monthly-averaged sea level pressure data provides a link between the phases of planetary-scale sea level pressure waves and Arctic Ocean and ice variability. Results of this analysis show: (1) a breakdown of the dominant wave 1 pattern in the late 1960's, (2) shifts in the mean phase of waves 1 and 2 since this breakdown, (3) an eastward shift in the phases of both waves 1 and 2 during the years of simulated cyclonic Arctic Ocean circulation relative to their phases during the years of anticyclonic circulation, (4) a strong decadal variability of wave phase associated with simulated Arctic Ocean circulation changes. Finally, the Arctic atmospheric circulation patterns that emerge when waves 1 and 2 are in their extreme eastern and western positions suggest an alternative approach for determining significant forcing patterns of sea ice and high-latitude variability.

Cavalieri, D. J.↗
NASA NTRS2021

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences

The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×10^6 sq.km, compared to 6.46×10^6 sq.km for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×10^6 sq.km for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 %/yr) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Arctic sea ice↗
NASA NTRS2022

The Transformation and Export of Organic Carbon Across an Arctic River-Delta-Ocean Continuum

The Arctic Ocean is surrounded by land that feeds highly seasonal rivers with water enriched in high concentrations of dissolved and particulate organic carbon (DOC and POC). Explicit estimates of the flux of organic carbon across the land-ocean interface are difficult to quantify and many interdependent processes makes source attribution difficult. A high-resolution 3-D biogeochemical model was built for the lower Yukon River and coastal ocean to estimate biogeochemical cycling across the land-ocean continuum. The model solves for complex reactions related to organic carbon transformation, including mechanistic photodegradation and multi-reactivity microbial processing, DOC to POC flocculation, and phytoplankton dynamics. The baseline DOC and POC flux out of the delta from April to September 2019, was 977 and 536 Gg C (~80% of the annual total), but only 50% of the DOC and 25% of the POC exited the plume across the 10 m isobath. Microbial breakdown of DOC accounted for a net loss of 168 Gg C (17% of delta export) within the plume and photodegradation accounted for a net loss of 46.6 Gg C DOC (5% of delta export) in 2019. Flocculation decreased the total organic carbon flux by only 6.4 Gg C (~1%), while POC sinking accounted for 63.3 Gg C (10%) settling in the plume. The loss of chromophoric dissolved organic matter (CDOM) due to photodegradation increased the light available for phytoplankton growth throughout the coastal ocean, demonstrating the secondary effects that organic carbon reactions can have on biological processes and the net coastal carbon flux.

Land-Ocean Continuum↗
NASA NTRS2001

A 21-Year Record of Arctic Sea Ice Extents and Their Regional, Seasonal, and Monthly Variability and Trends

Satellite passive-microwave data have been used to calculate sea ice extents over the period 1979-1999 for the north polar sea ice cover as a whole and for each of nine regions. Over this 21-year time period, the trend in yearly average ice extents for the ice cover as a whole is -32,900 +/- 6,100 sq km/yr (-2.7 +/- 0.5 %/decade), indicating a reduction in sea ice coverage that has decelerated from the earlier reported value of -34,000 +/- 8,300 sq km/yr (-2.8 +/- 0.7 %/decade) for the period 1979-1996. Regionally, the reductions are greatest in the Arctic Ocean, the Kara and Barents Seas, and the Seas of Okhotsk and Japan, whereas seasonally, the reductions are greatest in summer, for which season the 1979-1999 trend in ice extents is -41,600 +/- 12,900 sq km/ yr (-4.9 +/- 1.5 %/decade). On a monthly basis, the reductions are greatest in July and September for the north polar ice cover as a whole, in September for the Arctic Ocean, in June and July for the Kara and Barents Seas, and in April for the Seas of Okhotsk and Japan. Only two of the nine regions show overall ice extent increases, those being the Bering Sea and the Gulf of St. Lawrence.For neither of these two regions is the increase statistically significant, whereas the 1079 - 1999 ice extent decreases are statistically significant at the 99% confidence level for the north polar region as a whole, the Arctic Ocean, the Seas of Okhotsk and Japan, and Hudson Bay.

Parkinson, Claire L.↗
NASA NTRS2017

Understanding Arctic Surface Temperature Differences in Reanalyses

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70ÂdegN-90ÂdegN) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

Surface Temperatur↗