Assimilation of snow covered area information into hydrologic and land-surface models

This paper describes a data assimilation method that uses observations of snow covered area (SCA) to update hydrologic model states in a mountainous catchment in Colorado. The assimilation method uses SCA information as part of an ensemble Kalman filter to alter the sub-basin distribution of snow as well as the basin water balance. This method permits an optimal combination of model simulations and observations, as well as propagation of information across model states. Sensitivity experiments are conducted with a fairly simple snowpack/water-balance model to evaluate effects of the data assimilation scheme on simulations of streamflow. The assimilation of SCA information results in minor improvements in the accuracy of streamflow simulations near the end of the snowmelt season. The small effect from SCA assimilation is initially surprising. It can be explained both because a substantial portion of snowmelts before any bare ground is exposed, and because the transition from 100% to 0% snow coverage occurs fairly quickly. Both of these factors are basin-dependent. Satellite SCA information is expected to be most useful in basins where snow cover is ephemeral. The data assimilation strategy presented in this study improved the accuracy of the streamflow simulation, indicating that SCA is a useful source of independent information that can be used as part of an integrated data assimilation strategy.     

The Bragg Crystal Spectrometer for SOLAR-A

The Bragg Crystal Spectrometer (BCS) is one of the instruments which makes up the scientific payload of the SOLAR-A mission. The spectrometer employs four bent germanium crystals, views the whole Sun and observes the resonance line complexes of H-like Fexxvi and He-like Fexxv, Caxix, and Sxv in four narrow wavelength ranges with a resolving power (/) of between 3000 and 6000. The spectrometer has approaching ten times better sensitivity than that of previous instruments thus permitting a time resolution of better than 1 s to be achieved. The principal aim is the measurement of the properties of the 10 to 50 million K plasma created in solar flares with special emphasis on the heating and dynamics of the plasma during the impulsive phase. This paper summarizes the scientific objectives of the BCS and describes the design, characteristics, and performance of the spectrometers.After the launch the name of SOLAR-A has been changed to YOHKOH.Tragically Professor K. Tanaka died on January 2, 1990.     

A 3D ERT study of solute transport in a large experimental tank

A high resolution, cross-borehole, 3D electrical resistivity tomography (ERT) study of solute transport was conducted in a large experimental tank. ERT voxels comprising the time sequence of electrical images were converted into a 3D array of ERT estimated fluid conductivity breakthrough curves and compared with direct measurements of fluid conductivity breakthrough made in wells. The 3D ERT images of solute transport behaviour were also compared with predictions based on a 3D finite-element, coupled flow and transport model, accounting for gravity induced flow caused by concentration differences.The tank (dimensions 185×245×186 cm) was filled with medium sand, with a gravel channel and a fine sand layer installed. This heterogeneous system was designed to complicate solute transport behaviour relative to a homogeneous sand tank, and to thus provide a challenging but insightful analysis of the ability of 3D ERT to resolve transport phenomena. Four ERT arrays and 20 piezometers were installed during filling. A NaCl tracer (conductivity 1.34 S/m) was injected and intensively monitored with 3D ERT and direct sampling of fluid chemistry in piezometers.We converted the bulk conductivity estimate for 250 voxels in the ERT imaged volume into ERT estimated voxel fluid conductivity by assuming that matrix conduction in the tank is negligible. In general, the ERT voxel response is in reasonable agreement with the shape of fluid conductivity breakthrough observed in six wells in which direct measurements of fluid conductivity were made. However, discrepancies occur, particularly at early times, which we attribute to differences between the scale of the image voxels and the fluid conductivity measurement, measurement errors mapped into the electrical inversion and artificial image roughness resulting from the inversion.ERT images revealed the 3D tracer distribution at 15 times after tracer injection. The general pattern and timing of solute breakthrough observed with ERT agreed with that predicted from the flow/transport modelling. However, the ERT images indicate a vertical component of tracer transport and preferential flow paths in the medium sand. We attribute this to transient vertical gradients established during tracer injection, and heterogeneity caused by sorting of the sand resulting from the filling procedure. In this study, ERT provided a unique dataset of 250 voxel breakthrough curves in 1.04 m³. The use of 3D ERT to generate an array of densely sampled estimated fluid conductivity breakthrough curves is a potentially powerful tool for quantifying solute transport processes.     

The contribution of snow condition trends to future ground climate

Global climate models predict that terrestrial northern high-latitude snow conditions will change substantially over the twenty-first century. Results from a Community Climate System Model simulation of twentieth and twenty-first (SRES A1B scenario) century climate show increased winter snowfall (+10–40%), altered maximum snow depth (?5 ± 6 cm), and a shortened snow-season (?14 ± 7 days in spring, +20 ± 9 days in autumn). By conducting a series of prescribed snow experiments with the Community Land Model, we isolate how trends in snowfall, snow depth, and snow-season length affect soil temperature trends. Increasing snowfall, by countering the snowpack-shallowing influence of warmer winters and shorter snow seasons, is effectively a soil warming agent, accounting for 10–30% of total soil warming at 1 m depth and ~16% of the simulated twenty-first century decline in near-surface permafrost extent. A shortening snow season enhances soil warming due to increased solar absorption whereas a shallowing snowpack mitigates soil warming due to weaker winter insulation from cold atmospheric air. Snowpack deepening has comparatively less impact due to saturation of snow insulative capacity at deeper snow depths. Snow depth and snow-season length trends tend to be positively related, but their effects on soil temperature are opposing. Consequently, on the century timescale the net change in snow state can either amplify or mitigate soil warming. Snow state changes explain less than 25% of total soil temperature change by 2100. However, for the latter half of twentieth century, snow state variations account for as much as 50–100% of total soil temperature variations.