Geology topics

N. M. Mognard

Publications and source records attributed to N. M. Mognard.

8 recordsLinked to original sources

USGS2008

A satellite snow depth multi-year average derived from SSM/I for the high latitude regions

The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987-1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is - 0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient - 0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America (where the correlation coefficient decreases to 0.29). ?? 2007 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗

USGS2005

Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the Northern Great Plains

Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 ?? 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1?? ?? 1?? in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations. ?? 2005 American Meteorological Society.

Journal of Hydrometeorology↗

USGS2004

Comparison of AMSR-E and SSM/I snow parameter retrievals over the Ob river basin

Passive microwave observations from the Advanced Microwave Scanning Radiometer - EOS (AMSR-E) and from the Special Sensor Microwave Imager (SSM/I) are used to analyse the evolution of the snow pack in the Ob river basin during the snow season of 2002-03. The Ob river is the biggest Russian river with respect to its watershed area (2 975 000 km2). The Ob originates in the Altai mountains and flows northward across the vast West Siberian lowland towards the Arctic Ocean. The majority of snow cover is contained in the lowlands rather than in mountainous regions and persists for six months or more. During the snow season, surface air temperatures are very cold. Therefore, the combination of cold dry snow and large areas of uniform topography is ideal for snowpack extent and water equivalent retrievals from passive microwave observations. The thermal gradient through the snow pack is estimated and used to model the growth of the snow grain size and to compute the evolution of the passive microwave derived snow depth over the region. A comparison between the AMSR-E and SSM/I estimates is performed and the differences between the snow parameters from the two satellite instruments are analysed.

Conference Paper↗

USGS2003

Global Snow-Cover Evolution from Twenty Years of Satellite Passive Microwave Data

Starting in 1979 with the SMMR (Scanning Multichannel Microwave Radiometer) instrument onboard the satellite NIMBUS-7 and continuing since 1987 with the SSMI (Special Sensor Microwave Imager) instrument on board the DMSP (Defence Meteorological Satellite Program) series, more then twenty years of satellite passive microwave data are now available. This dataset has been processed to analyse the evolution of the global snow cover. This work is part of the AICSEX project from the 5th Framework Programme of the European Community. The spatio-temporal evolution of the satellite-derived yearly snow maximum extent and the timing of the spring snow melt were estimated and analysed over the Northern Hemisphere. Significant differences between the evolution of the yearly maximum snow extent in Eurasia and in North America were found. A positive correlation between the maximum yearly snow cover extent and the ENSO index was obtained. High interannual spatio-temporal variability characterises the timing of snow melt in the spring. Twenty-year trends in the timing of spring snow melt have been computed and compared with spring air temperature trends for the same period and the same area. In most parts of Eurasia and in the central and western parts of North America the tendency has been for earlier snow melt. In northeastern Canada, a large area of positive trends, where snow melt timing starts later than in the early 1980s, corresponds to a region of positive trends of spring air temperature observed over the same period.

Conference Paper↗

USGS2002

A passive microwave snow depth algorithm with a proxy for snow metamorphism

Passive microwave brightness temperatures of snowpacks depend not only on the snow depth, but also on the internal snowpack properties, particularly the grain size, which changes through the winter. Algorithms that assume a constant grain size can yield erroneous estimates of snow depth or water equivalent. For snowpacks that are subject to temperatures well below freezing, the bulk temperature gradient through the snowpack controls the metamorphosis of the snow grains. This study used National Weather Service (NWS) station measurements of snow depth and air temperature from the Northern US Great Plains to determine temporal and spatial variability of the snow depth and bulk snowpack temperature gradient. This region is well suited for this study because it consists primarily of open farmland or prairie, has little relief, is subject to very cold temperatures, and has more than 280 reporting stations. A geostatistical technique called Kriging was used to grid the randomly spaced snow depth measurements. The resulting snow depth maps were then compared with the passive microwave observations from the Special Sensor Microwave Imager (SSM/I). Two snow seasons were examined: 1988-89, a typical snow year, and 1996-97, a record year for snow that was responsible for extensive flooding in the Red River Basin. Inspection of the time series of snow depth and microwave spectral gradient (the difference between the 19 and 37 GHz bands) showed that while the snowpack was constant, the spectral gradient continued to increase. However, there was a strong correlation (0.6 < R2 < 0.9) between the spectral gradient and the cumulative bulk temperature gradient through the snowpack (TGI). Hence, TGI is an index of grain size metamorphism that has occurred within the snowpack. TGI time series from 21 representative sites across the region and the corresponding SSM/I observations were used to develop an algorithm for snow depth that requires daily air temperatures. Copyright ?? 2002 John Wiley & Sons, Ltd.

Hydrological Processes↗

USGS2002

Estimating terrestrial snow depth with the Topex-Poseidon altimeter and radiometer

Active and passive microwave measurements obtained by the dual-frequency Topex-Poseidon radar altimeter from the Northern Great Plains of the United States are used to develop a snow pack radar backscatter model. The model results are compared with daily time series of surface snow observations made by the U.S. National Weather Service. The model results show that Ku-band provides more accurate snow depth determinations than does C-band. Comparing the snow depth determinations derived from the Topex-Poseidon nadir-looking passive microwave radiometers with the oblique-looking Satellite Sensor Microwave Imager (SSM/I) passive microwave observations and surface observations shows that both instruments accurately portray the temporal characteristics of the snow depth time series. While both retrievals consistently underestimate the actual snow depths, the Topex-Poseidon results are more accurate.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS1996

Southern Ocean monthly wave fields for austral winters 1985-1988 by Geosat radar altimeter

Four years of monthly averaged wave height fields for the austral winters 1985–1988 derived from the Geosat altimeter data show a spatial variability of the scale of 500–1000 km that varies monthly and annually. This variability is superimposed on the zonal patterns surrounding the Antarctic continent and characteristic of the climatology derived from the U.S. Navy [1992] Marine Climatic Atlas of the World. The location and the intensity of these large-scale features, which are not found in the climatological fields, exhibit strong monthly and yearly variations. A global underestimation of the climatological mean wave heights by more than 1 m is also found over large regions of the Southern Ocean. The largest monthly averaged significant wave heights are above 5 m and are found during August of every year in the Indian Ocean, south of 40°S. The monthly wave fields show more variability in the Atlantic and Pacific Oceans than in the Indian Ocean. The Seasat data from 1978 and the Geosat data from 1985 and 1988 show an eastward rotation of the largest wave heights. However, this rotation is absent in 1986 and 1987; the former was a year of unusually low sea states, and the latter was a year of unusually high sea states, which suggests a link to the El Niño-Southern Oscillation event of 1986.

Journal of Geophysical Research C: Oceans↗

USGS1980

Ocean eddy structure by satellite radar altimetry required for iceberg towing

Models for the towing of large tabular icebergs give towing speeds of 0.5 knots to 1.0 knots relative to the ambient near surface current. Recent oceanographic research indicates that the world oceans are not principally composed of large steady-state current systems, like the Gulf Stream, but that most of the ocean momentum is probably involved in intense rings, formed by meanders of the large streams, and in mid-ocean eddies. These rings and eddies have typical dimensions on the order of 200 km with dynamic height anomalies across them of tens-of-centimeters to a meter. They migrate at speeds on the order of a few cm/sec. Current velocities as great as 3 knots have been observed in rings, and currents of 1 knot are common. Thus, the successful towing of icebergs is dependent on the ability to locate, measure, and track ocean rings and eddies. To accomplish this systematically on synoptic scales appears to be possible only by using satelliteborne radar altimeters. Ocean current and eddy structures as observed by the radar altimeters on the GEOS-3 and Seasat-1 satellites are presented and compared. Several satellite programs presently being planned call for flying radar altimeters in polar or near-polar orbits in the mid-1980 time frame. Thus, by the time tows of large icebergs will probably be attempted, it is possible synoptic observations of ocean rings and eddies which can be used to ascertain their location, size, intensity, and translation velocity will be a reality.

Cold Regions Science and Technology↗