Gutmann, E. D. | Search NASA

DOE OSTI2023

Mass‐Conserving Downscaling of Climate Model Precipitation Over Mountainous Terrain for Water Resource Applications

Abstract A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined.

Geology↗

NASA NTRS2005

The Effect of Soil Hydraulic Properties vs. Soil Texture in Land Surface Models

This study focuses on the effect of Soil Hydraulic Property (SHP) selection on modeled surface fluxes following a rain storm in a semi-arid environment. SHPs are often defined based on a Soil Texture Class (STC). To examine the effectiveness of this approach, the Noah land surface model was run with each of 1306 soils in a large SHP database. Within most STCs, the outputs have a range of 350 W/m2 for latent and sensible heat fluxes, and 8K for surface temperature. The average difference between STC median values is only 100 W/m2 for latent and sensible heat. It is concluded that STC explains 5-15% of the variance in model outputs and should not be used to determine SHPs.

Gutmann, E. D.↗

NASA NTRS1999

Quantifying BRDF Effects in Comparing Landsat-7 and AVIRIS Near-Simultaneous Acquisitions for Studies of High Plains Vegetation Cover

Approximately 100,000 sq. km of the High Plains of the central United States are covered by sand dunes and sand sheets deposited during the Holocene. Soil-dating evidence shows that there were at least four periods of dune reactivation during major droughts in the last 10,000 years. The dunes in this region are anchored by vegetation. We have undertaken a study of land-use change in the High Plains from 1985 to the present using Landsat 5 TM and Landsat 7 ETM+ images to map variation in vegetation cover during wet and dry years. Mapping vegetation cover of less than 20% is important in modeling potential surface reactivation since at this level the vegetation no longer sufficiently shields sandy surfaces from movement by wind. Landsat TM data have both the spatial resolution and temporal coverage to facilitate vegetation cover analysis for model development and verification. However, there is still the question of how accurate TM data are for the measurement of both growing and senescent vegetation in and and semi-arid regions. AVIRIS provides both high spectral resolution as well as high signal-to-noise ratio and can be used to test the accuracy of Landsat TM and ETM+ data. We have analyzed data from AVIRIS flown nearly concurrently with a Landsat 7 overpass. The comparison between an AVIRIS image swath of 11 km width subtending a 30 deg. angle and the same area covered by a 0.8 deg. angle from Landsat required accounting for the BRDF. A normalization technique using the ratio of the reflectances from registered AVIRIS and Landsat data proved superior to the techniques of column averaging on AVIRIS data alone published previously by Kennedy et al. This technique can be applied to aircraft data covering a wider swath angle than AVIRIS to develop BRDF responses for a wide variety of surfaces more efficiently than from ground measurements.

Goetz, A. F. H.↗