R. L. Armstrong

Recent northern hemisphere snow extent: A comparison of data derived from visible and microwave satellite sensors

During the past four decades much important information on Northern Hemisphere snow extent has been provided by the NOAA weekly snow extent charts derived from visible-band satellite imagery. Passive microwave satellite remote sensing can enhance snow measurements based on visible data alone because of the ability to penetrate clouds, provide data during darkness and the potential to provide an index of snow depth or water equivalent. We compare the fluctuation of Northern Hemisphere snow cover over the past twenty years using these two satellite remote sensing techniques. Results show comparable inter-annual variability with similar long-term hemispheric-scale trends indicating decreases in snow extent of approximately 0.2 percent per year. The passive microwave snow algorithm applied in this study indicates less snow-covered area than the visible data during fall and early winter when the snow is shallow. New algorithms designed to reduce this apparent error are being developed and tested.

An earth-gridded SSM/I data set for cryospheric studies and global change monitoring

Abstract The National Snow and Ice Data Center (NSIDC) has distributed DMSP Special Sensor Microwave Imager (SSM/I) brightness temperature grids for the Polar Regions on CD-ROM since 1987. In order to expand this product to include all potential snow covered regions, the area of coverage is now global. The format for the global SSM/I data set is the Equal Area SSM/I Earth Grid (EASE-Grid) developed at NSIDC. The EASE-Grid has been selected as the format for the NASA/NOAA Pathfinder Program Level 3 Products which include both SSM/I and SMMR (Scanning Multichannel Microwave Radiometer) data (1978–1987). Providing both data sets in the EASE-Grid will result in a 15 year time-series of satellite passive microwave data in a common format. The extent and variability of seasonal snow cover is recognized to be an important parameter in climate and hydrologic systems and trends in snow cover serve as an indicator of global climatic changes. Passive microwave data from satellites afford the possibility to monitor temporal and spatial variations in snow cover on the global scale, avoiding the problems of cloud cover and darkness. NSIDC is developing the capability to produce daily snow products from the DMSP-SSM/I satellite with a spatial resolution of 25 km. In order to provide a standard environment in which to validate SSM/I algorithm output, it is necessary to assemble baseline data sets using other, more direct, methods of measurement. NSIDC has compiled a validation data set of surface station measurements for the northern hemisphere with specific focus on the United States, Canada, and the former Soviet Union. Digital image substraction is applied to compare the surface station and satellite measurements.

Challenges and recommendations in mapping of glacier parameters from space: results of the 2008 Global Land Ice Measurements from Space (GLIMS) workshop, Boulder, Colorado, USA

Abstract On 16–18 June 2008 the US National Snow and Ice Data Center held a GLIMS workshop in Boulder, CO, USA, focusing on formulating procedures and best practices for operational glacier mapping using satellite imagery. Despite the progress made in recent years, there still remain many cases where automatic delineation of glacier boundaries in satellite imagery is difficult, error prone or time-consuming. This workshop identified six themes for consideration by focus groups: (1) mapping clean ice and lakes; (2) mapping ice divides; (3) mapping debris-covered glaciers; (4) assessing changes in glacier area and elevation through comparisons with older data; (5) digital elevation model (DEM) generation from satellite stereo pairs; and (6) accuracy and error analysis. Talks presented examples and work in progress for each of these topics, and focus groups worked on compiling a summary of available algorithms and procedures to address and avoid identified hurdles. Special emphasis was given to establishing standard protocols for glacier delineation and analysis, creating illustrated tutorials and providing source code for available methods. This paper summarizes the major results of the 2008 GLIMS workshop, with an emphasis on definitions, methods and recommendations for satellite data processing. While the list of proposed methods and recommendations is not comprehensive and is still a work in progress, our goal here is to provide a starting point for the GLIMS regional centers as well as for the wider glaciological community in terms of documentation on possible pitfalls along with potential solutions.

Snow depth derived from passive microwave remote-sensing data in China

Abstract In this study, we report on the spatial and temporal distribution of seasonal snow depth derived from passive microwave satellite remote-sensing data (e.g. SMMR from 1978 to 1987 and SMM/ I from 1987 to 2006) in China. We first modified the Chang algorithm and then validated it using meteorological observation data, considering the influences from vegetation, wet snow, precipitation, cold desert and frozen ground. Furthermore, the modified algorithm is dynamically adjusted based on the seasonal variation of grain size and snow density. Snow-depth distribution is indirectly validated by MODIS snow-cover products by comparing the snow-extent area from this work. The final snow-depth datasets from 1978 to 2006 show that the interannual snow-depth variation is very significant. The spatial and temporal distribution of snow depth is illustrated and discussed, including the steady snow-cover regions in China and snow-mass trend in these regions. Though the areal extent of seasonal snow cover in the Northern Hemisphere indicates a weak decrease over a long period, there is no clear trend in change of snow-cover area extent in China. However, snow mass over the Qinghai–Tibetan Plateau and northwestern China has increased, while it has weakly decreased in northeastern China. Overall, snow depth in China during the past three decades shows significant interannual variation, with a weak increasing trend.

Soil freeze/thaw cycles over snow‐free land detected by passive microwave remote sensing

The timing, duration, and areal extent of the near-surface soil freeze/thaw status were investigated using passive microwave satellite remote sensing data for the 1997/98 winter over the contiguous United States. A frozen soil algorithm was validated using soil temperature data at 0 cm and 5 cm depths from more than 20 sites over the study area. Results indicated that a negative spectral gradient and a cut-off 37-GHz vertical polarized brightness temperature of 258.2K can be used to determine near-surface soil freeze/thaw status with confidence. The microwave freeze/thaw boundary generally agreed with −5.0°C isotherm of air temperature although frozen soils occurred sporadically between 0°C and −5.0°C isotherms. The maximum frozen soil area over snow-free land surface was about 3.75 × 106 km² or about 37% of the total study area during the 1997/98 winter. The near-surface soils often froze before snow covered the land surface, but soil freeze/thaw status under snow cover cannot be detected using this microwave technique. The onset of soil freeze mainly occurred in October and November, while the last days of soil freeze occurred in March and April, resulting in the duration of soil freezing varying from five to seven months over the majority of the study areas. The number of days of surface soil freezing varied from several days to longer than five months.

Hemispheric-scale comparison and evaluation of passive-microwave snow algorithms

Abstract Passive-microwave satellite remote sensing can greatly enhance large-scale snow measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. This study provides preliminary results from the comparison and evaluation of several different passive-microwave algorithms. These algorithms represent examples which include both mid- and high-frequency channels, vertical and horizontal polarizations and polarization-difference approaches. In our comparisons we utilize larger, more comprehensive, validation datasets which can be expected to provide a full range of snow/climate conditions rather than limited data which may only represent a snapshot in time and space. Evaluation of snow extent derived from passive-microwave data is undertaken through comparison with the U.S. National Oceanic and Atmospheric Administration (NOAA) Northern Hemisphere snow charts which are based on visible-band satellite data. Results clearly indicate those time periods and geographic regions where the two techniques agree and where they tend to consistently disagree. Validation of snow water equivalent derived from passive-microwave data is undertaken using measurements from snow-course transects in the former Soviet Union. Preliminary results indicate a general tendency for nearly all of the algorithms to underestimate snow water equivalent.

Application of Satellite Remote Sensing Techniques to Frozen Ground Studies

Permafrost and seasonally frozen ground regions occupy approximately 24% and 55%, respectively, of the exposed land surface in the Northern Hemisphere. The areal extent, timing, duration, and depth of the near-surface soil freeze and thaw have a significant impact on plant growth, energy, and water and trace gas exchanges between the atmosphere and the soils in cold seasons/cold regions. Satellite remote sensing combined with ground “truth” measurements have been used to investigate seasonally frozen ground and permafrost at local to regional scales with some success. The objective of this paper is to provide an overview of satellite remote sensing techniques applied to study seasonally frozen ground and permafrost over the last few decades. Remote sensing of permafrost terrain and surface freeze/thaw cycles typically uses a combination of imaging in optical and thermal wavelengths, passive microwave sensing, and active microwave remote sensing using scatterometer and Synthetic Aperture Radar (SAR). No single sensor is capable of providing the range of observations needed. SAR imaging provides information on the timing, duration, and regional progression of the near-surface soil freeze/thaw status in cold seasons/regions with a relatively high spatial resolution, but repeat times of existing satellites are relatively long compared to the rate of change of the soil freeze/thaw cycle in fall and spring. Spaceborne passive microwave sensors offer more frequent coverage at several wavelengths, but with substantially lower spatial resolution. Optical and thermal sensors provide a middle ground in spatial resolution and temporal sampling between SAR and passive microwave satellites, but a known relationship between permafrost (and freeze/thaw depth) and corresponding environmental factors needs to be provided. Overall, microwave remote sensing is a promising technique for detecting near-surface soil freeze/thaw cycles over snow-free land. The potential for using land surface temperature derived from satellite visible and near-infrared sensors to study soil freezing and thawing processes is substantial. Satellite remote sensing data products—such as for snow cover extent, snow depth, snowmelt, land surface type, Normalized Difference Vegetation Index (NDVI), surface albedo, surface wetness, and soil moisture—can be very helpful for frozen ground studies at local, regional, and global scales.

NASA Cold Land Processes Experiment (CLPX 2002/03): Field Measurements of Snowpack Properties and Soil Moisture

A field measurement program was undertaken as part NASA’s Cold Land Processes Experiment (CLPX). Extensive snowpack and soil measurements were taken at field sites in Colorado over four study periods during the two study years (2002 and 2003). Measurements included snow depth, density, temperature, grain type and size, surface wetness, surface roughness, and canopy cover. Soil moisture measurements were made in the near-surface layer in snow pits. Measurements were taken in the Fraser valley, North Park, and Rabbit Ears Pass areas of Colorado. Sites were chosen to gain a wide representation of snowpack types and physiographies typical of seasonally snow-covered regions of the world. The data have been collected with rigorous protocol to ensure consistency and quality, and they have undergone several levels of quality assurance to produce a high-quality spatial dataset for continued cold lands hydrological research. The dataset is archived at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado.

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

Abstract 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 deriva...

Catskill Mountain Water Resources: Vulnerability, Hydroclimatology, and Climate-Change Sensitivity

We present an initial assessment of the potential impact of climate change on water supply in the Metropolitan East Coast (MEC) region of the U.S. National Assessment of the Potential Consequences of Climate Variability and Change. A version of the Thornthwaite water-balance model is applied to one of six basins in the Catskill Mountains that together provide water for approximately 10 million people in New York City and other municipalities. In addition to Thornthwaite’s original soil moisture reservoir, the model includes the snow pack water reservoir of Willmott, Rowe, and Mintz (1985), a ground-water storage term, and several additional modifications. Following a review of the vulnerability of water supplies and historical hydroclimatology of this region, we estimate (1) the sensitivity of water supply to altered temperature and precipitation regimes and (2) the potential impacts of specific climate-change scenarios used by national and regional climate-change assessments. The sensitivity of runoff to temperature changes is approximately 6 percent per degree C; its sensitivity to precipitation changes is approximately 1.5 – 2 percent per percent change in precipitation, for annual mean values. Under all scenarios, rising temperatures will lead to significantly diminished water supplies unless precipitation increases dramatically. Due to disagreement between precipitation projections from different models and scenarios, projected changes in mean annual water supply range from approximately +10 percent to −30 percent by the 2080s. Under the driest scenario, water supplies under mean climatic conditions will be comparable to the worst extended drought period of the twentieth century in this region. Equally important are the likely effects on the annual cycle, which include an earlier peak runoff and a reduction of the snowpack by at least 50 percent. Considered in the context of likely increased demands, these changes may be significant.