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At least 37 records · Page 2
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NASA NTRS1997

The Perennial Ice Cover of the Beaufort Sea from Active- and Passive-Microwave Observations

The perennial ice concentration in the Beaufort Sea was examined using active- and passive-microwave observations. We compared the ice type and concentration estimates from SSM/I and ERS-1 SAR data over a seasonal cycle from January 1992 to January 1993. It was found the multi-year (MY) ice-concentration estimates from the SAR data were very stable and were nearly equivalent to the ice concentration estimated at the end of the previous summer. We contrast this with the variability of the MY ice-concentration and ice-fraction estimates obtained using the NASA Team algorithm. The passive- and active-microwave algorithms provide total ice concentrations that are comparable during the winter, but the passive estimates are significantly lower during the summer. Passive-microwave estimates of multi-year-ice concentrations are consistently lower (up to 30%) than those from the SAR data. We discuss reasons for these discrepancies and the possible biases introduced by the active and passive algorithms.

Kwok, R.↗
NASA NTRSDate not supplied

Evaluating Subgrid-Scale Properties of Low Clouds over the Beaufort Sea in Arctic System Reanalysis using ARISE Airborne In Situ Observations

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. To better understand the magnitude and possible causes of this problem, we analyze the disagreements between the Arctic System Reanalysis version 2 (ASR) and data taken during the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign conducted over the Beaufort Sea. Previous analysis of grid scale-averaged meteorological variables revealed a lack of cloud water produced in ASR, related to warm/dry biases, a failure to produce sufficient cloud water in conditions that are observed to be favorable for large cloud water values, and sampling issues with the ARISE flight paths. However, ARISE collected meteorological observations at one second intervals, offering spatial data resolution comparable to the subgrid scale of ASR. Subgrid scale properties and processes must be parameterized in conventional atmospheric models and reanalyses such as ASR, and often rely on assumed distributions of meteorological variables about the grid box mean state. To enable an examination of the realism of ASR’s subgrid scale properties, we use high resolution data from ARISE determine the “subgrid scale” distributions of cloud water and thermodynamic variables in the real atmosphere. Preliminary results show that the subgrid scale distribution of thermodynamic variables about the grid scale mean resembles the triangular distribution assumed in many bulk microphysical parameterization schemes, but also with tails resembling Gaussian distributions. The main goal is to understand the partitioning of the total available atmospheric water into water vapor and cloud water. Models typically covert some percentage of total water in a grid box to cloud water based on the estimated amount of supersaturation from the assumed vapor distribution. The ARISE measurements can reveal the relationship between subgrid scale supersaturation and the partition between cloud water and water vapor.

Jason Brant Dodson↗
NASA NTRS1976

Beaufort Sea ice zones as delineated by microwave imagery

Microwave and infrared data were obtained from a research aircraft over the Beaufort Sea ice from the shoreline of Harrison Bay northward to a latitude of almost 81 deg N. The data acquired were compared with microwave data obtained on the surface at an approximate position of 75 deg N, 150 deg W. Over this north-south transect of the polar ice canopy it was discovered that the sea ice could be divided into five distinct zones. The shorefast sea ice was found to consist uniformly of first-year sea ice. The second zone was found to be a mixture of first-year sea ice, medium size multiyear floes, and many recently refrozen leads, polynyas, and open water; considerable shearing activity was evident in this zone. The third zone was a mixture of first-year and multiyear sea ice which had a uniform microwave signature. The fourth zone was found to be a mixture of first-year sea ice and medium-to-large size multiyear floes which was similar in composition to the second zone. The fifth zone was almost exclusively multiyear ice extending to the North Pole.

Campbell, W. J.↗
NASA NTRS1972

Coastal environment of the Beaufort Sea from field data and ERTS-1 imagery, summer 1972

The author has identified the following significant results. An extensive field program during the spring and summer in the coastal Beaufort Sea test site has been completed using a wide variety of sensing techniques. Reduction of field data and ERTS-1 image analysis have shown the coastal environment to be complexly influenced by unique processes, most of which involve or are related to sea ice. Active sedimentologic processes along the Arctic coast are set in motion by the melting, flooding, and eventual overflow of rivers onto the sea ice. It is now apparent that only minor amounts of sediment are transported offshore at this stage; however, scouring of the bottom is significant beneath the strudels (drain holes) which develop in the fast ice canopy in the region of overflow. Areal salinity and turbidity patterns together with ERTS-1 imagery confirm a consistent influx of colder, clearer, saltier water towards the coast just east of the Colville River. Strong (up to 3 knots) bidirectional but intermittent currents often manifest themselves in imagery and aerial photographs as wakes behind grounded ice. Ice movement vectors generated from repetitive images indicate that ice drift is closely associated with wind direction, especially in shallow bays, and displacements of 4-22 kilometers were noted in 24 hours.

Reimnitz, E.↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). Multiple models/reanalyses use SGS supersaturated total water (relative to GS saturation) as a threshold for partitioning available water for condensation, and indeed we find significant correlation between GS cloud water and SGS supersaturation. However, we also find that the assumption of a static threshold of 100% saturation to be unrealistic. Empirical calculations from the ARISE data show a large sensitivity of this threshold to GS relative humidity, and so a microphysical parameterization allowing the threshold to vary according to GS thermodynamic properties may result in more realistic GS cloud water values. Finally, to determine how sensitive the ARISE-derived results are to that particular campaign, we include additional data from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) conducted in 1998. The inclusion of the second dataset will help with demonstrating the robustness of the results and their utility in improving the representation of Arctic clouds in models and reanalyses.

J Brant Dodson↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We investigate two related approaches to prediction of GS cloud properties from SGS variability: the critical saturation ratio method, and the critical relative humidity method. We find significant correlation between GS cloud water and SGS supersaturation when the critical saturation ratio is set at 100%, as well as a notable relationship between GS cloud water and the width of the SGS total water distribution. Critical relative humidity also compares well with GS cloud water. However, we also find that the assumptions of a static critical saturation ratio of 100% to be unrealistic, as well as a fixed SGS distribution width. Empirical calculations from the ARISE data show a large sensitivity of these SGS variables to GS relative humidity, and so a SGS parameterization allowing them to vary according to GS thermodynamic properties may result in more realistic GS cloud water values.

J. Brant Dodson↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We examine the influence of three assumed SGS parameters on the estimation of GS cloud water: the width of the SGS PDF of total water (ΔQT), the shape of the SGS PDF, and the critical saturation ratio (Scrit), which partitions the SGS PDF into water that is available or not for conversion to cloud water. Both Scrit and ΔQT influence predicted GS cloud water strongly. ARISE and FIRE-ACE disagree somewhat in the details, but both campaigns support the possibility that more realistic representations of these two parameters may lead to more realistic GS cloud water. In particular, both parameters are sensitive to GS relative humidity, and so we examine the effects of allowing these quantities to vary as an empirically-derived linear function of GS relative humidity. In contrast, the shape of the PDF has little effect on the predicted cloud water – a surprising result that merits additional investigation.

J Brant Dodson↗
NASA NTRS1996

Seasonal Characteristics of the Perennial Ice Cover of the Beaufort Sea

By definition, ice which survives the summer is classified as multiyear ice. Thus the area covered by multiyear ice during the winter should be nearly equivalent to the ice area during the previous summer's minima. This condition provides a reasonable criterion for the evaluation of ice concentration and ice type retrieval algorithms using remote-sensing data sets. From special sensor microwave imager (SSM/I) data the NASA Team algorithm estimates the multiyear, first-year, and total ice concentrations during the winter using combinations of the polarization and spectral gradient ratios. The Team algorithm provides only estimates of ice concentration in the summer. From ERS 1 synthetic aperture radar (SAR) data the remarkably stable contrast between multiyear ice and first-year ice in winter provides consistent estimates of multiyear ice concentrations. In the summer, multiyear ice concentration cannot be estimated from SAR or SSM/I data because free water on the surface effectively masks the backscatter and emissivity signature of this ice type. From SAR data a technique which takes advantage of the high backscatter of wind-roughened open water as a discrimination feature is used to estimate the total ice concentration in the summer. With a year-long (January 1992 to January 1993) data set from the Beaufort Sea we found that the multiyear ice concentration estimates from the SAR data are stable and are nearly equivalent to the ice concentration estimated at the end of the previous summer. We contrast this with the variability of the multiyear ice concentration and ice friction estimates obtained using SSM/I data. The Team algorithm produces ice concentration and multiyear ice estimates which are consistently lower than those from the SAR data. We discuss reasons for these discrepancies and the implications of the higher than previously noted multiyear ice concentrations.

Kwok, R.↗
NASA NTRS1996

The Character of the Beaufort Sea Ice Cover From Active and Passive Microwave Observations

By definition, ice which survives the summer is classified as multiyear ice. Thus, multiyear ice concentration during the winter should be nearly equivalent to the ice concentration during the previous summer's minima. This condition provides a reasonable criterion for evaluation of ice concentration and ice type retrieval algorithms from remote sensing datasets. From SSM/I data, the NASA Team algorithm estimates the multiyear, first-year and total ice concentrations throughout the sea ice season using combinations of the polarization and spectral gradient ratios.

Beaufort Sea↗
NASA NTRS1972

Studies of the inner shelf and coastal sedimentation environment of the Beaufort Sea from ERTS-1

The author has identified the following significant results. Field studies of the initiation of river flow onto the frozen Arctic Ocean were made by a group of scientists from May 15 to June 10, 1972. A time lapse camera mounted on a 40-ft. tower near the mouth of the Kaparuk River, west of Prudhoe Bay, provided a detailed 10-day record (24 hours a day) of flow direction and water level. It is believed that wind build-up, discharge variance of the river, and through-ice drainage rates are the prime factors influencing overflow onto the sea ice. Current meter, transmissometer, temperature, salinity, and thermoprobe data were collected from holes drilled in the shorefast ice from seal holes and from the river water overflow. Depth and a real distribution of the overflow water were monitored from the ice using snowmobiles, and from the air using helicopters and fixed-wing aircraft. Photographic records were made on 35mm KII, KX, Ektachrome IR, Plus X, and IR black and white film. A simple two camera frame permitted simultaneous exposures of two types of film. Preliminary comparisons of the IR and conventional films, both color and black and white, showed no advantage to using the infrared film. However, the low altitude photography taken during this study will be very helpful in the interpretation of ERTS-1 imagery.

Reimnitz, E.↗