Identification

Title

Bayesian exploration of multivariate orographic precipitation sensitivity for moist stable and neutral flows

Abstract

Recent idealized studies examined the sensitivity of topographically forced rain and snowfall to changes in mountain geometry and upwind sounding in moist stable and neutral environments. These studies were restricted by necessity to small ensembles of carefully chosen simulations. Research presented here extends earlier studies by utilizing a Bayesian Markov chain Monte Carlo (MCMC) algorithm to create a large ensemble of simulations, all of which produce precipitation concentrated on the upwind slope of an idealized Gaussian bell-shaped mountain. MCMC-based probabilistic analysis yields information about the combinations of sounding and mountain geometry favorable for upslope rain, as well as the sensitivity of orographic precipitation to changes in mountain geometry and upwind sounding. Exploration of the multivariate sensitivity of rainfall to changes in parameters also reveals a nonunique solution: multiple combinations of flow, topography, and environment produce similar surface rainfall amount and distribution. Finally, the results also divulge that the nonunique solutions have different sensitivity profiles, and that changes in observation uncertainty also alter model sensitivity to input parameters.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7k075m6

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

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Temporal reference

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End position

Dataset reference date

date type

publication

effective date

2015-11-01T00:00:00Z

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Use constraints

Copyright 2015 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact