A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation

A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature ass...
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Autor*in:	Feifei Pan [verfasserIn] Lisa Nagaoka [verfasserIn] Steve Wolverton [verfasserIn] Samuel F. Atkinson [verfasserIn] Timothy A. Kohler [verfasserIn] Marty O’Neill [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation

Übergeordnetes Werk:	In: Atmosphere - MDPI AG, 2011, 12(2021), 2, p 135
Übergeordnetes Werk:	volume:12 ; year:2021 ; number:2, p 135

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/atmos12020135

Katalog-ID:	DOAJ050010557

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520			\|a A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values.
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allfields	10.3390/atmos12020135 doi (DE-627)DOAJ050010557 (DE-599)DOAJ17d500bacdd541bc9b2e9d6f63e36c6c DE-627 ger DE-627 rakwb eng QC851-999 Feifei Pan verfasserin aut A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values. stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation Meteorology. Climatology Lisa Nagaoka verfasserin aut Steve Wolverton verfasserin aut Samuel F. Atkinson verfasserin aut Timothy A. Kohler verfasserin aut Marty O’Neill verfasserin aut In Atmosphere MDPI AG, 2011 12(2021), 2, p 135 (DE-627)657584010 (DE-600)2605928-9 20734433 nnns volume:12 year:2021 number:2, p 135 https://doi.org/10.3390/atmos12020135 kostenfrei https://doaj.org/article/17d500bacdd541bc9b2e9d6f63e36c6c kostenfrei https://www.mdpi.com/2073-4433/12/2/135 kostenfrei https://doaj.org/toc/2073-4433 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021 2, p 135
spelling	10.3390/atmos12020135 doi (DE-627)DOAJ050010557 (DE-599)DOAJ17d500bacdd541bc9b2e9d6f63e36c6c DE-627 ger DE-627 rakwb eng QC851-999 Feifei Pan verfasserin aut A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values. stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation Meteorology. Climatology Lisa Nagaoka verfasserin aut Steve Wolverton verfasserin aut Samuel F. Atkinson verfasserin aut Timothy A. Kohler verfasserin aut Marty O’Neill verfasserin aut In Atmosphere MDPI AG, 2011 12(2021), 2, p 135 (DE-627)657584010 (DE-600)2605928-9 20734433 nnns volume:12 year:2021 number:2, p 135 https://doi.org/10.3390/atmos12020135 kostenfrei https://doaj.org/article/17d500bacdd541bc9b2e9d6f63e36c6c kostenfrei https://www.mdpi.com/2073-4433/12/2/135 kostenfrei https://doaj.org/toc/2073-4433 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021 2, p 135
allfields_unstemmed	10.3390/atmos12020135 doi (DE-627)DOAJ050010557 (DE-599)DOAJ17d500bacdd541bc9b2e9d6f63e36c6c DE-627 ger DE-627 rakwb eng QC851-999 Feifei Pan verfasserin aut A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values. stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation Meteorology. Climatology Lisa Nagaoka verfasserin aut Steve Wolverton verfasserin aut Samuel F. Atkinson verfasserin aut Timothy A. Kohler verfasserin aut Marty O’Neill verfasserin aut In Atmosphere MDPI AG, 2011 12(2021), 2, p 135 (DE-627)657584010 (DE-600)2605928-9 20734433 nnns volume:12 year:2021 number:2, p 135 https://doi.org/10.3390/atmos12020135 kostenfrei https://doaj.org/article/17d500bacdd541bc9b2e9d6f63e36c6c kostenfrei https://www.mdpi.com/2073-4433/12/2/135 kostenfrei https://doaj.org/toc/2073-4433 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021 2, p 135
allfieldsGer	10.3390/atmos12020135 doi (DE-627)DOAJ050010557 (DE-599)DOAJ17d500bacdd541bc9b2e9d6f63e36c6c DE-627 ger DE-627 rakwb eng QC851-999 Feifei Pan verfasserin aut A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values. stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation Meteorology. Climatology Lisa Nagaoka verfasserin aut Steve Wolverton verfasserin aut Samuel F. Atkinson verfasserin aut Timothy A. Kohler verfasserin aut Marty O’Neill verfasserin aut In Atmosphere MDPI AG, 2011 12(2021), 2, p 135 (DE-627)657584010 (DE-600)2605928-9 20734433 nnns volume:12 year:2021 number:2, p 135 https://doi.org/10.3390/atmos12020135 kostenfrei https://doaj.org/article/17d500bacdd541bc9b2e9d6f63e36c6c kostenfrei https://www.mdpi.com/2073-4433/12/2/135 kostenfrei https://doaj.org/toc/2073-4433 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021 2, p 135
allfieldsSound	10.3390/atmos12020135 doi (DE-627)DOAJ050010557 (DE-599)DOAJ17d500bacdd541bc9b2e9d6f63e36c6c DE-627 ger DE-627 rakwb eng QC851-999 Feifei Pan verfasserin aut A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values. stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation Meteorology. Climatology Lisa Nagaoka verfasserin aut Steve Wolverton verfasserin aut Samuel F. Atkinson verfasserin aut Timothy A. Kohler verfasserin aut Marty O’Neill verfasserin aut In Atmosphere MDPI AG, 2011 12(2021), 2, p 135 (DE-627)657584010 (DE-600)2605928-9 20734433 nnns volume:12 year:2021 number:2, p 135 https://doi.org/10.3390/atmos12020135 kostenfrei https://doaj.org/article/17d500bacdd541bc9b2e9d6f63e36c6c kostenfrei https://www.mdpi.com/2073-4433/12/2/135 kostenfrei https://doaj.org/toc/2073-4433 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021 2, p 135
language	English
source	In Atmosphere 12(2021), 2, p 135 volume:12 year:2021 number:2, p 135
sourceStr	In Atmosphere 12(2021), 2, p 135 volume:12 year:2021 number:2, p 135
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authorswithroles_txt_mv	Feifei Pan @@aut@@ Lisa Nagaoka @@aut@@ Steve Wolverton @@aut@@ Samuel F. Atkinson @@aut@@ Timothy A. Kohler @@aut@@ Marty O’Neill @@aut@@
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callnumber-first	Q - Science
author	Feifei Pan
spellingShingle	Feifei Pan misc QC851-999 misc stochastic weather generator misc annual mean air temperature misc annual precipitation misc daily mean air temperature misc daily precipitation misc Meteorology. Climatology A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation
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topic_title	QC851-999 A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation stochastic weather generator annual mean air temperature annual precipitation daily mean air temperature daily precipitation
topic	misc QC851-999 misc stochastic weather generator misc annual mean air temperature misc annual precipitation misc daily mean air temperature misc daily precipitation misc Meteorology. Climatology
topic_unstemmed	misc QC851-999 misc stochastic weather generator misc annual mean air temperature misc annual precipitation misc daily mean air temperature misc daily precipitation misc Meteorology. Climatology
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title	A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation
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title_full	A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation
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author_browse	Feifei Pan Lisa Nagaoka Steve Wolverton Samuel F. Atkinson Timothy A. Kohler Marty O’Neill
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title_sort	constrained stochastic weather generator for daily mean air temperature and precipitation
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title_auth	A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation
abstract	A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values.
abstractGer	A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values.
abstract_unstemmed	A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values.
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container_issue	2, p 135
title_short	A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation
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A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation

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