Dynamical random-set modeling of concentrated precipitation in North America

Noel Cressie, Renato Assunçao, Scott H. Holan, Michael Levine, Orietta Nicolis, Jun Zhang, Jian Zou

Resultado de la investigación: Article

5 Citas (Scopus)

Resumen

In order to study climate at scales where policy decisions can be made, regional climate models (RCMs) have been developed with much finer resolution (~50 km) than the ~500 km resolution of atmosphere-ocean general circulation models (AOGCMs). The North American Regional Climate Change Assessment Program (NARCCAP) is an international program that provides 50-km resolution climate output for the United States, Canada, and northern Mexico. In Phase I, there are six RCMs, from which we choose one to illustrate our methodology. The RCMs are updated every 3 hours and contain a number of variables, including temperature, precipitation, wind speed, wind direction, and air pressure; output is available from the years 1968-2000 and from the years 2038-2070. Precipitation is of particular interest to climate scientists, but it can be difficult to study because of its patchy nature: At hourly-up-to-monthly time scales, there are generally many zeroes over the precipitation field. In this research, we study sets of concentrated precipitation (i.e., the union of RCM pixels whose precipitation is above a given threshold), where we are interested in the way these sets evolve from one 3-hour period to the next. Assuming the sets are a realization of a time series of random sets, we are able to build dynamical models for the passage of rainfall fronts over 1-2 days. The dynamics are characterized by a growth/recession model for a time series of random sets, with several parameters that control how the concentrated precipitation changes over time.

Idioma originalEnglish
Páginas (desde-hasta)169-182
Número de páginas14
PublicaciónStatistics and its Interface
Volumen5
N.º2
EstadoPublished - 2 ago 2012

Huella dactilar

Climate models
Random Sets
Climate Models
Modeling
Climate
Time series
Precipitation (meteorology)
Climate change
Rain
Output
Pixels
Wind Speed
Climate Change
Rainfall
Dynamical Model
Ocean
Control Parameter
Atmosphere
Time Scales
Union

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics

Citar esto

Cressie, N., Assunçao, R., Holan, S. H., Levine, M., Nicolis, O., Zhang, J., & Zou, J. (2012). Dynamical random-set modeling of concentrated precipitation in North America. Statistics and its Interface, 5(2), 169-182.
Cressie, Noel ; Assunçao, Renato ; Holan, Scott H. ; Levine, Michael ; Nicolis, Orietta ; Zhang, Jun ; Zou, Jian. / Dynamical random-set modeling of concentrated precipitation in North America. En: Statistics and its Interface. 2012 ; Vol. 5, N.º 2. pp. 169-182.
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Cressie, N, Assunçao, R, Holan, SH, Levine, M, Nicolis, O, Zhang, J & Zou, J 2012, 'Dynamical random-set modeling of concentrated precipitation in North America', Statistics and its Interface, vol. 5, n.º 2, pp. 169-182.

Dynamical random-set modeling of concentrated precipitation in North America. / Cressie, Noel; Assunçao, Renato; Holan, Scott H.; Levine, Michael; Nicolis, Orietta; Zhang, Jun; Zou, Jian.

En: Statistics and its Interface, Vol. 5, N.º 2, 02.08.2012, p. 169-182.

Resultado de la investigación: Article

TY - JOUR

T1 - Dynamical random-set modeling of concentrated precipitation in North America

AU - Cressie, Noel

AU - Assunçao, Renato

AU - Holan, Scott H.

AU - Levine, Michael

AU - Nicolis, Orietta

AU - Zhang, Jun

AU - Zou, Jian

PY - 2012/8/2

Y1 - 2012/8/2

N2 - In order to study climate at scales where policy decisions can be made, regional climate models (RCMs) have been developed with much finer resolution (~50 km) than the ~500 km resolution of atmosphere-ocean general circulation models (AOGCMs). The North American Regional Climate Change Assessment Program (NARCCAP) is an international program that provides 50-km resolution climate output for the United States, Canada, and northern Mexico. In Phase I, there are six RCMs, from which we choose one to illustrate our methodology. The RCMs are updated every 3 hours and contain a number of variables, including temperature, precipitation, wind speed, wind direction, and air pressure; output is available from the years 1968-2000 and from the years 2038-2070. Precipitation is of particular interest to climate scientists, but it can be difficult to study because of its patchy nature: At hourly-up-to-monthly time scales, there are generally many zeroes over the precipitation field. In this research, we study sets of concentrated precipitation (i.e., the union of RCM pixels whose precipitation is above a given threshold), where we are interested in the way these sets evolve from one 3-hour period to the next. Assuming the sets are a realization of a time series of random sets, we are able to build dynamical models for the passage of rainfall fronts over 1-2 days. The dynamics are characterized by a growth/recession model for a time series of random sets, with several parameters that control how the concentrated precipitation changes over time.

AB - In order to study climate at scales where policy decisions can be made, regional climate models (RCMs) have been developed with much finer resolution (~50 km) than the ~500 km resolution of atmosphere-ocean general circulation models (AOGCMs). The North American Regional Climate Change Assessment Program (NARCCAP) is an international program that provides 50-km resolution climate output for the United States, Canada, and northern Mexico. In Phase I, there are six RCMs, from which we choose one to illustrate our methodology. The RCMs are updated every 3 hours and contain a number of variables, including temperature, precipitation, wind speed, wind direction, and air pressure; output is available from the years 1968-2000 and from the years 2038-2070. Precipitation is of particular interest to climate scientists, but it can be difficult to study because of its patchy nature: At hourly-up-to-monthly time scales, there are generally many zeroes over the precipitation field. In this research, we study sets of concentrated precipitation (i.e., the union of RCM pixels whose precipitation is above a given threshold), where we are interested in the way these sets evolve from one 3-hour period to the next. Assuming the sets are a realization of a time series of random sets, we are able to build dynamical models for the passage of rainfall fronts over 1-2 days. The dynamics are characterized by a growth/recession model for a time series of random sets, with several parameters that control how the concentrated precipitation changes over time.

KW - Boolean model

KW - Kernel density estimation

KW - Laslett's theorem

KW - Method-of-moments estimation

KW - Narccap

KW - Regional climate model (RCM)

KW - Setvalued Autoregression (SVAR)

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JO - Statistics and its Interface

JF - Statistics and its Interface

SN - 1938-7989

IS - 2

ER -

Cressie N, Assunçao R, Holan SH, Levine M, Nicolis O, Zhang J y otros. Dynamical random-set modeling of concentrated precipitation in North America. Statistics and its Interface. 2012 ago 2;5(2):169-182.