Engineering topics

Cavalieri, Donald J.

Publications and source records attributed to Cavalieri, Donald J..

At least 37 records · Page 2

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 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 NTRS2001

The Potential of Using Landsat 7 Data for the Classification of Sea Ice Surface Conditions During Summer

During spring and summer, the Surface of the Arctic sea ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt pond diameters generally do not exceed a couple of meters, the spatial resolutions of sensors like AVHRR and MODIS are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the pan-chromatic band). The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and meltponded areas, have different signatures in the individual Landsat bands. Consistent with in-situ albedo measurements, melt ponds show up as blueish whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable the distinction of melt ponds. The melt pond fraction for the scene studied in this paper was 37%.

Markus, Thorsten↗

NASA NTRS2001

Arctic Sea Ice Export Through Fram Strait and Atmospheric Planetary Waves

A link is found between the variability of Arctic sea ice export through Ram Strait and the phase of the longest atmospheric planetary wave (zonal wave 1) in SLP for the period 1958-1997. Previous studies have identified a link between From Strait ice export and the North Atlantic Oscillation (NAO), but this link has been described as unstable because of a lack of consistency over time scales longer than the last two decades. Inconsistent and low correlations are also found between From Strait ice export and the Arctic Oscillation (AD) index. This paper shows that the phase of zonal wave 1 explains 60% - 70% of the simulated From Strait ice export variance over the Goodyear period 1958 - 1997. Unlike the NAB and AD links, these high variances are consistent for both the first and second halves of the Goodyear period. This consistency is attributed to the sensitivity of the wave I phase at high latitudes to the presence of secondary low pressure systems in the Barents Sea that serve to drive sea ice southward through From Strait. These results provide further evidence that the phase of zonal wave 1 in SLP at high latitudes drives regional as well as hemispheric low frequency Arctic Ocean and sea ice variability.

Cavalieri, Donald J.↗

NASA NTRS2000

EOS Aqua AMSR-E Sea Ice Validation Program: Meltpond2000 Flight Report

This flight report describes the field component of Meltpond2000, the first in a series of Arctic and Antarctic aircraft campaigns planned as part of NASA's Earth Observing System Aqua sea ice validation program for the Advanced Microwave Scanning Radiometer (AMSR-E). This prelaunch Arctic field campaign was carried out between June 25 and July 6, 2000 from Thule, Greenland, with the objective of quantifying the errors incurred by the AMSR-E sea ice algorithms resulting from the presence of melt ponds. A secondary objective of the mission was to develop a microwave capability to discriminate between melt ponds and seawater using low-frequency microwave radiometers. Meltpond2000 was a multiagency effort involving personnel from the Navy, NOAA, and NASA. The field component of the mission consisted of making five 8-hour flights from Thule Air Base with a Naval Air Warfare Center P-3 aircraft over portions of Baffin Bay and the Canadian Arctic. The aircraft sensors were provided and operated by the Microwave Radiometry Group of NOAA's Environmental TechnologyLaboratory. A Navy ice observer from the National Ice Center provided visual documentation of surface ice conditions during each of the flights. Two of the five flights were coordinated with Canadian scientists making surface measurements of melt ponds at an ice camp located near Resolute Bay, Canada. Coordination with the Canadians will provide additional information on surface characteristics and will be of great value in the interpretation of the aircraft and high-resolution satellite data sets.

Cavalieri, Donald J.↗

NASA NTRS2000

EOS Aqua AMSR-E Sea Ice Validation Program: Meltpond 2000 Flight Report

This flight report describes the field component of Meltpond2000, the first in a series of Arctic and Antarctic aircraft campaigns planned as part of NASA's Earth Observing System Aqua sea ice validation program for the Advanced Microwave Scanning Radiometer (AMSR-E). This prelaunch Arctic field campaign was carried out between June 25 and July 6, 2000 from Thule, Greenland, with the objective of quantifying the errors incurred by the AMSR-E sea ice algorithms resulting from the presence of melt ponds. A secondary objective of the mission was to develop a microwave capability to discriminate between melt ponds and seawater using low-frequency microwave radiometers. Meltpond2000 was a multiagency effort involving personnel from the Navy, National Oceanic and Atmospheric Administration (NOAA), and NASA. The field component of the mission consisted of making five eight-hour flights from Thule Air Base with a Naval Air Warfare Center P-3 aircraft over portions of Baffin Bay and the Canadian Arctic. The aircraft sensors were provided and operated by the Microwave Radiometry Group of NOAA's Environmental Technology Laboratory. A Navy ice observer from the National Ice Center provided visual documentation of surface ice conditions during each of the flights. Two of the five flights were coordinated with Canadian scientists making surface measurements of melt ponds at an ice camp located near Resolute Bay, Canada. Coordination with the Canadians will provide additional information on surface characteristics and will be of great value in the interpretation of the aircraft and high-resolution satellite data sets.

Cavalieri, Donald J.↗

NASA NTRS2000

Modeling of Dense Water Production and Salt Transport from Alaskan Coastal Polynyas

The main significance of this paper is that a realistic, three-dimensional, high-resolution primitive equation model has been developed to study the effects of dense water formation in Arctic coastal polynyas. The model includes realistic ambient stratification, realistic bottom topography, and is forced by time-variant surface heat flux, surface salt flux, and time-dependent coastal flow. The salt and heat fluxes, and the surface ice drift, are derived from satellite observations (SSM/I and NSCAT sensors). The model is used to study the stratification, salt transport, and circulation in the vicinity of Barrow Canyon during the 1996/97 winter season. The coastal flow (Alaska coastal current), which is an extension of the Bering Sea throughflow, is formulated in the model using the wind-transport regression. The results show that for the 1996/97 winter the northeastward coastal current exports 13% to 26% of the salt produced by coastal polynyas upstream of Barrow Canyon in 20 to 30 days. The salt export occurs more rapidly during less persistent polynyas. The inclusion of ice-water stress in the model makes the coastal current slightly weaker and much wider due to the combined effects of surface drag and offshore Ekman transport.

Signorini, Sergio R.↗

NASA NTRS2000

Sea Ice Variability in the Sea of Okhotsk from Passive Microwave Satellite Observations

The Sea of Okhotsk, located between 50 and 60 N, is bounded by the Kamchatka Peninsula, Siberia, Sakhalin Island, and the Kuril Island chain and is the largest midlatitude seasonal sea ice zone in the Northern Hemisphere. The winter sea ice cover begins to form in November and expands to cover most of the sea by March. Over the following three months, the ice retreats with only small ice-covered areas remaining by the beginning of June. The sea is ice free or nearly ice free on average for six months of the year, from June through November. The recent compilation of a consistent, long-term record of Northern Hemisphere sea ice extents based on passive microwave satellite observations from the Nimbus 7 Scanning Multichannel Microwave Radiometer and from four Defense Meteorological Satellite Program Special Sensor Microwave Imagers provides the basis for assessing long-term sea ice extent variability in the Sea of Okhotsk. Analysis of this 20-year data record (1979-1998) shows that based on yearly averages the overall extent of the Sea of Okhotsk ice cover is decreasing at the rate of -8.1+/-2.1x10(exp 3) sq km/yr (-17.2%/decade), in contrast to the rate of decrease of -33.3+/-0.7x10(exp 3) sq km/yr (-2.7%/decade) for the Northern Hemisphere as a whole. There is large regional sea ice extent variability of the Arctic ice cover. Two of the nine Arctic regions analyzed, the Bering Sea and the Gulf of St. Lawrence, show increases of 0.8+/-1.4xl0(exp 3) sq km/yr (2.7%/decade) and 1.2+/-0.5xl0(exp 3) sq km/yr (17.1%/decade), respectively. Interestingly, the Sea of Okhotsk and the Gulf of St. Lawrence show about equal percentage changes, but of opposite sign. The Sea of Okhotsk exhibits its greatest percent decrease (-24.3%/decade) during spring (April-June). The year of maximum winter sea ice extent for the Sea of Okhotsk was 1979, whereas the minimum winter sea ice extent occurred in 1984.

Cavalieri, Donald J.↗

NASA NTRS1998

A Revision of the NASA Team Sea Ice Algorithm

In a recent paper, two operational algorithms to derive ice concentration from satellite multichannel passive microwave sensors have been compared. Although the results of these, known as the NASA Team algorithm and the Bootstrap algorithm, have been validated and are generally in good agreement, there are areas where the ice concentrations differ, by up to 30%. These differences can be explained by shortcomings in one or the other algorithm. Here, we present an algorithm which, in addition to the 19 and 37 GHz channels used by both the Bootstrap and NASA Team algorithms, makes use of the 85 GHz channels as well. Atmospheric effects particularly at 85 GHz are reduced by using a forward atmospheric radiative transfer model. Comparisons with the NASA Team and Bootstrap algorithm show that the individual shortcomings of these algorithms are not apparent in this new approach. The results further show better quantitative agreement with ice concentrations derived from NOAA AVHRR infrared data.

Markus, T.↗

NASA NTRS1998

A Modified NASA Team Sea Ice Algorithm for the Antarctic

A recent comparative study of the NASA Team and Bootstrap passive microwave sea ice algorithms revealed significantly different sea ice concentration retrievals in some parts of the Antarctic. The study identified potential reasons for the discrepancies including the influence of sea ice temperature variability on the Bootstrap retrievals and the influence of ice surface reflectivity on the horizontally polarized emissivity in the NASA Team retrievals. In this study, we present a modified version of the NASA Team algorithm which reduces the error associated with the use of horizontally polarized radiance data, while retaining the relative insensitivity to ice temperature variations provided by radiance ratios. By retaining the 19 GHz polarization as an independent variable, we also maintain a relatively large dynamic range in sea ice concentration. The modified algorithm utilizes the 19 GHz polarization (PR19) and both gradient ratios, GRV and GRH defined by (37V-19V)/(37V+19V) and (37H-19H)/(37H+19H), respectively, rather than just GRV used in the current NASA Team algorithm. A plot of GRV versus GRH shows that the preponderance of points lie along a quadratic curve, whereas those points affected by surface reflectivity anomalies deviate from this curve. This serves as a method of identifying the problems points. The 19H brightness temperature of these problem points is increased so they too fall along quadratic curve. Sea ice concentrations derived from AVHRR imagery illustrate the extent to which this method reduces the error associated with surface layering.

Cavalieri, Donald J.↗

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 NTRS1997

Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques

The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.

Comiso, Josefino C.↗

NASA NTRS1997

A Microwave Technique for Mapping Ice Temperature in the Arctic Seasonal Sea Ice Zone

A technique for deriving ice temperature in the Arctic seasonal sea ice zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses ice concentration and type from a previously developed thin ice algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observations from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the ice temperature depends on ice type.

St.Germain, Karen M.↗

NASA NTRS1995

An improved land mask for the SSM/I grid

This paper discusses the development of a new land/ocean/coastline mask for use with Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) data, and other types of data which are mapped to the polar stereographic SSM/I grid. Pre-existing land masks were found to disagree, to lack certain land features, and to disagree with land boundaries that are visible in high resolution sensor imagery, such as imagery from the Synthetic Aperture Radar (SAR) on the Earth Resources Satellite (ERS-1). The Digital Chart of the World (DCW) database was initially selected as a source of shoreline data for this effort. Techniques for developing a land mask from these shoreline data are discussed. The resulting land mask, although not perfect, is seen to exhibit significant improvement over previous land mask products.

Martino, Michael G.↗

NASA NTRS1994

The contribution of Alaskan, Siberian, and Canadian coastal polynas to the cold halocline layer of the Arctic Ocean

Numerous Arctic Ocean circulation and geochemical studies suggest that ice growth in polynyas over the Alaskan, Siberian, and Canadian continental shelves is a source of cold, saline water which contributes to the maintenance of the Arctic Ocean halocline. The purpose of this study is to estimate for the 1978-1987 winters the contributions of Arctic coastal polynyas to the cold halocline layer of the Arctic Ocean. The study uses a combination of satellite, oceanographic, and weather data to calculate the brine fluxes from the polynyas; then an oceanic box model is used to calculate their contributions to the cold halocline layer of the Arctic Ocean. This study complements and corrects a previous study of dense water production by coastal polynyas in the Barents, Kara, and Laptev Seas.

Cavalieri, Donald J.↗

NASA NTRS1994

A microwave technique for mapping thin sea ice

A technique is presented for mapping the distribution of new, young and first-year sea ice in seasonal sea ice zones that utilizes microwave spectral and polarization information from the Defense Meteorological Satellite Program Special Sensor Microwave/Imager (DMSP SSM/I). The motivation for this work stems from the need for accurate estimates of open water and thin ice within the Arctic ice pack. The technique utilizes the microwave polarization and spectral characteristics of these three ice types through two microwave radiance ratios: the 19.4 GHz polarization and the spectral gradient ratio, which is a measure of the spectral difference between the 19.4-GHz and the 37.0-GHz vertically polarized radiance components. The combined use of the spectral gradient ratio and polarization reduces the low ice concentration bias generally associated with the presence of thin ice types. The microwave polarization, which is sensitive to changes in ice thickness and ice surface characteristics, is used to classify new, young, and first-year ice types.

Cavalieri, Donald J.↗

NASA NTRS1992

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided.

Cavalieri, Donald J.↗

NASA NTRS1992

Arctic and Antarctic Sea Ice, 1978-1987: Satellite Passive-Microwave Observations and Analysis

This book contains a description and analysis of the spatial and temporal variations in the Arctic and Antarctic sea ice covers from October 26, 1978 through August 20, 1987. It is based on data collected by the Scanning Multichannel Microwave Radiometer (SMMR) onboard the NASA Nimbus 7 satellite. The 8.8-year period, together with the 4 years of the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR) observations presented in two earlier volumes, comprises a sea ice record spanning almost 15 years.

Gloersen, Per↗