A simple method of computing the variation of annual precipitation over mountainous terrain

Danard, Maurice B.

doi:10.1007/bf00192129

Cited by 8 publications

(1 citation statement)

References 13 publications

(10 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cayan and Roads also examined the relative vorticity advection component (which is related to vertical velocity [see Trenberth, 1978]) and the orographically forced vertical velocity (v. IZh), both of which show useful predictive power for area average precipitation. The latter term has also been considered by Danard [1971]. There are, however, resolution problems with vorticity-based predictors.…”

Section: The Above Examples Show That Useful Small-scale Climate Chanmentioning

confidence: 99%

Obtaining sub‐grid‐scale information from coarse‐resolution general circulation model output

Wigley¹,

Jones²,

Briffa³

et al. 1990

J. Geophys. Res.

271

157

View full text Add to dashboard Cite

The predictor variables employed are area averages (over ~2.5 × 106 km2) of temperature and precipitation and propinquitous grid point values of mean sea level pressure and 700 mbar height, together with the zonal and meridional gradients of these two variables. Regression analyses are performed using monthly-mean data from Oregon, with separate analyses for each month. In independent verification, Spatial-mean explained variances range from 58 to 87% for temperature and from 39 to 76% for precipitation. Most of the variance explained arises from the area average of the variable which is the predictand: in other words, if the temperature, say, at point x is to be estimated, the best predictor is generally the area average temperature

show abstract

Section: The Above Examples Show That Useful Small-scale Climate Chanmentioning

confidence: 99%