An approach to the development of isohyetal maps for mountainous areas

Abstract

A technique was developed in which anomalies from precipitation‐elevation relationships were used in preparing isohyetal maps of Utah. October–April and May–September precipitation normals (averages for the 1921 to 1950 period) were computed for all available Utah precipitation records. The double‐mass analysis technique was used in the derivation of the October–April normals, and for this purpose the state was separated into eight climatic divisions. Relationships between precipitation and water equivalent of snow cover at a network of 29 stations were used in estimating normal October–April precipitation for snow courses located above 8000 feet. The May–September precipitation values for short‐term stations were adjusted to the 1921–1950 period by the ratio method. The state was divided into 20 geographic zones, and for these zones it was found that good correlations existed between precipitation and station elevation for both the October–April and May–September periods. The precipitation‐elevation relationships showed marked differences for some adjacent areas separated by high mountain ranges. From combined data for several zones, general precipitation‐elevation curves for larger areas were obtained and departures of individual station normals from these curves were plotted on a contour base map. Analysis of these anomalies showed that the departures were related to physiographic features. Normal May–September and October–April values were determined for a grid of points over the state by using the anomaly pattern and general precipitation‐elevation relationships. These values, together with the observed and adjusted normals, were used to locate the October–April and May–September isohyetals. The large variations in normal precipitation due to topography were taken into account, yet the general precipitation‐elevation relationships for small zones were retained. The accuracy of the isohyetal maps is considered comparable to that obtained by presently known methods, and the technique is less time consuming.

REGEOTOP: New climatic data fields for East Asia based on localized relief information and geostatistical methods

“…24: (2004 are interpolated via a geostatistical method (kriging) and added to the regression field to account for any remaining spatial variation. Peck and Brown (1962) initially introduced the idea to add an interpolated field of residuals to the results of a functional relationship between climatic processes and topography to account better for both topography-related processes and any other remaining influences. The regionalization method has been termed 'AURELHY' ('Analysis Using the Relief for Hydrometeorology'; Benichou and Lebreton, 1987) and has been adopted by the French Weather Service (Météo France) as the standard for the preparation of climate maps.…”

A knowledge-based approach to the statistical mapping of climate

“…Human-expert methods use human experience, expertise, and knowledge acquisition capabilities to infer climate patterns from meteorological regimes, physiographic features, biotic characteristics, and other information sources. They involve the manual preparation of climate maps (Reed & Kincer 1917, Peck & Brown 1962, often based on topographic analyses involving the correlation of point climate data with an array of topographic and synoptic parameters such as topographic position, slope, exposure, elevation, location of barriers, and wind speed and direction (Spreen 1947, Burns 1953, Stoeckeler 1963, Schermerhorn 1967, Hovecar & Martsolf 1971, Bootsma 1976, Houghton 1979, Basist et al 1994. Most of the 'official' precipitation maps for US states were created in the 1960s by federal agencies using humanexpert methods.…”

Analysis of Regional Difference in Altitude Dependence of Snow Depth Using High Resolve Numerical Experiments

“…Previous studies have reported a simple proportionality relation between altitude and snow water equivalent (SWE) (e.g., Peck and Brown 1962). The relation is used to estimate the snow cover distribution.…”