Ensemble adaptive data assimilation techniques applied to land-falling north American cyclones

Brian C. Ancell; Lynn A. McMurdie

doi:10.1007/978-3-642-35088-7_23

Ensemble adaptive data assimilation techniques applied to land-falling north American cyclones

Brian C. Ancell, Lynn A. McMurdie

Geosciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

5 Scopus citations

Abstract

Adaptive data assimilation is becoming an increasingly important aspect of numerical weather prediction. Traditional data assimilation involves combining a set of routine observations with a first-guess field provided by a numerical weather prediction model to produce an analysis of the atmospheric state. These analyses subsequently serve as the initial conditions for extended forecasts.

Original language	English
Title of host publication	Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
Publisher	Springer Berlin Heidelberg
Pages	555-575
Number of pages	21
ISBN (Electronic)	9783642350887
ISBN (Print)	9783642350870
DOIs	https://doi.org/10.1007/978-3-642-35088-7_23
State	Published - Jan 1 2013

Access to Document

10.1007/978-3-642-35088-7_23

Cite this

@inbook{680826c4b494425b8c121622745ddde5,

title = "Ensemble adaptive data assimilation techniques applied to land-falling north American cyclones",

abstract = "Adaptive data assimilation is becoming an increasingly important aspect of numerical weather prediction. Traditional data assimilation involves combining a set of routine observations with a first-guess field provided by a numerical weather prediction model to produce an analysis of the atmospheric state. These analyses subsequently serve as the initial conditions for extended forecasts.",

author = "Ancell, {Brian C.} and McMurdie, {Lynn A.}",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2013.",

year = "2013",

month = jan,

day = "1",

doi = "10.1007/978-3-642-35088-7_23",

language = "English",

isbn = "9783642350870",

pages = "555--575",

booktitle = "Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)",

publisher = "Springer Berlin Heidelberg",

}

TY - CHAP

T1 - Ensemble adaptive data assimilation techniques applied to land-falling north American cyclones

AU - Ancell, Brian C.

AU - McMurdie, Lynn A.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Adaptive data assimilation is becoming an increasingly important aspect of numerical weather prediction. Traditional data assimilation involves combining a set of routine observations with a first-guess field provided by a numerical weather prediction model to produce an analysis of the atmospheric state. These analyses subsequently serve as the initial conditions for extended forecasts.

AB - Adaptive data assimilation is becoming an increasingly important aspect of numerical weather prediction. Traditional data assimilation involves combining a set of routine observations with a first-guess field provided by a numerical weather prediction model to produce an analysis of the atmospheric state. These analyses subsequently serve as the initial conditions for extended forecasts.

UR - http://www.scopus.com/inward/record.url?scp=84892451422&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-35088-7_23

DO - 10.1007/978-3-642-35088-7_23

M3 - Chapter

AN - SCOPUS:84892451422

SN - 9783642350870

SP - 555

EP - 575

BT - Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)

PB - Springer Berlin Heidelberg

ER -

Ensemble adaptive data assimilation techniques applied to land-falling north American cyclones

Abstract

Access to Document

Other files and links

Fingerprint

Cite this