Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?

In this study, a Lagrangian radar echo extrapolation scheme (MAPLE) was tested for use in very short-term forecasting of precipitation over a complex orographic region. The high-resolution forecasts from MAPLE for lead times of 5 min-5 h are evaluated against the radar observations for 20 summer rai...

Full description

Saved in:
Bibliographic Details
Main Authors: Mandapaka, Pradeep V., Germann, Urs., Panziera, Luca., Hering, Alessandro.
Format: Article
Language:English
Published: 2012
Subjects:
Online Access:https://hdl.handle.net/10356/94062
http://hdl.handle.net/10220/8181
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-94062
record_format dspace
spelling sg-ntu-dr.10356-940622020-09-26T21:26:56Z Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography? Mandapaka, Pradeep V. Germann, Urs. Panziera, Luca. Hering, Alessandro. DRNTU::Science::Physics::Meteorology and climatology In this study, a Lagrangian radar echo extrapolation scheme (MAPLE) was tested for use in very short-term forecasting of precipitation over a complex orographic region. The high-resolution forecasts from MAPLE for lead times of 5 min-5 h are evaluated against the radar observations for 20 summer rainfall events by employing a series of categorical, continuous, and neighborhood evaluation techniques. The verification results are then compared with those from Eulerian persistence and high-resolution numerical weather prediction model [the Consortium for Small-scale Modeling model (COSMO2)] forecasts. The forecasts from the MAPLE model clearly outperformed Eulerian persistence forecasts for all the lead times, and had better skill compared to COSMO2 up to lead time of 3 h on average. The results also showed that the predictability achieved from the MAPLE model depends on the spatial structure of the precipitation patterns. This study is a first implementation of the MAPLE model over a complex Alpine region. In addition to comprehensive evaluation of precipitation forecast products, some open questions related to the nowcasting of rainfall over a complex terrain are discussed. Published version 2012-05-29T09:09:56Z 2019-12-06T18:50:11Z 2012-05-29T09:09:56Z 2019-12-06T18:50:11Z 2012 2012 Journal Article Mandapaka, P. V., Germann, U., Panziera, L., & Hering, A. (2012). Can Lagrangian Extrapolation of Radar Fields Be Used for Precipitation Nowcasting over Complex Alpine Orography?. Weather and Forecasting, 27(1), 28-49. https://hdl.handle.net/10356/94062 http://hdl.handle.net/10220/8181 10.1175/WAF-D-11-00050.1 en Weather and forecasting © 2012 American Meteorological Society. This paper was published in Weather and Forecasting and is made available as an electronic reprint (preprint) with permission of American Meteorological Society. The paper can be found at DOI: [http://dx.doi.org/10.1175/WAF-D-11-00050.1]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 23 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Science::Physics::Meteorology and climatology
spellingShingle DRNTU::Science::Physics::Meteorology and climatology
Mandapaka, Pradeep V.
Germann, Urs.
Panziera, Luca.
Hering, Alessandro.
Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?
description In this study, a Lagrangian radar echo extrapolation scheme (MAPLE) was tested for use in very short-term forecasting of precipitation over a complex orographic region. The high-resolution forecasts from MAPLE for lead times of 5 min-5 h are evaluated against the radar observations for 20 summer rainfall events by employing a series of categorical, continuous, and neighborhood evaluation techniques. The verification results are then compared with those from Eulerian persistence and high-resolution numerical weather prediction model [the Consortium for Small-scale Modeling model (COSMO2)] forecasts. The forecasts from the MAPLE model clearly outperformed Eulerian persistence forecasts for all the lead times, and had better skill compared to COSMO2 up to lead time of 3 h on average. The results also showed that the predictability achieved from the MAPLE model depends on the spatial structure of the precipitation patterns. This study is a first implementation of the MAPLE model over a complex Alpine region. In addition to comprehensive evaluation of precipitation forecast products, some open questions related to the nowcasting of rainfall over a complex terrain are discussed.
format Article
author Mandapaka, Pradeep V.
Germann, Urs.
Panziera, Luca.
Hering, Alessandro.
author_facet Mandapaka, Pradeep V.
Germann, Urs.
Panziera, Luca.
Hering, Alessandro.
author_sort Mandapaka, Pradeep V.
title Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?
title_short Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?
title_full Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?
title_fullStr Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?
title_full_unstemmed Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography?
title_sort can lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex alpine orography?
publishDate 2012
url https://hdl.handle.net/10356/94062
http://hdl.handle.net/10220/8181
_version_ 1681056709793021952