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Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation.

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Title: Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation.
Authors: LAI, YUCHUAN1 (AUTHOR) ylai1@andrew.cmu.edu, DZOMBAK, DAVID A.1 (AUTHOR)
Source: Journal of Applied Meteorology & Climatology. May2021, Vol. 60 Issue 5, p695-710. 16p.
Subjects: Atmospheric models, Computer simulation of climate change, Long-range weather forecasting, Precipitation forecasting, Weather forecasting
Abstract: An integrated technique combining global climate model (GCM) simulation results and a statistical time series forecasting model [the autoregressive integrated moving average (ARIMA) model] was developed to bring together the climate change signal from GCMs to city-level historical observations as an approach to obtain location-specific temperature and precipitation projections. This approach assumes that regional temperature and precipitation time series reflect a combination of an underlying climate change signal series and a regional-deviation-from-the-signal series. An ensemble of GCMs is used to describe and provide the climate change signal, and the ARIMA model is used to model and project the regional deviation. Qualitative and quantitative assessments were conducted for evaluating the projection performance of the hybrid GCM-ARIMA (G-ARIMA) model. The results indicate that the G-ARIMA model can provide projected city-specific daily temperature and precipitation series comparable to historical observations and can have improved projection accuracy for several assessed annual indices compared to a commonly used downscaled projection product. The G-ARIMA model is subject to some limitations and uncertainties from the GCM-provided climate change signal. A notable feature of the G-ARIMA model is the efficiency with which projections can be updated when new observations become available, thus facilitating updating of regional temperature and precipitations projections. Given the increasing need for and use of location-specific climate projections in practical engineering applications, the G-ARIMA model is an option for regional temperature and precipitation projection for such applications. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Items – Name: Title
  Label: Title
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  Data: Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation.
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  Data: <searchLink fieldCode="AR" term="%22LAI%2C+YUCHUAN%22">LAI, YUCHUAN</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ylai1@andrew.cmu.edu</i><br /><searchLink fieldCode="AR" term="%22DZOMBAK%2C+DAVID+A%2E%22">DZOMBAK, DAVID A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Meteorology+%26+Climatology%22">Journal of Applied Meteorology & Climatology</searchLink>. May2021, Vol. 60 Issue 5, p695-710. 16p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Atmospheric+models%22">Atmospheric models</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation+of+climate+change%22">Computer simulation of climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Long-range+weather+forecasting%22">Long-range weather forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Precipitation+forecasting%22">Precipitation forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Weather+forecasting%22">Weather forecasting</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: An integrated technique combining global climate model (GCM) simulation results and a statistical time series forecasting model [the autoregressive integrated moving average (ARIMA) model] was developed to bring together the climate change signal from GCMs to city-level historical observations as an approach to obtain location-specific temperature and precipitation projections. This approach assumes that regional temperature and precipitation time series reflect a combination of an underlying climate change signal series and a regional-deviation-from-the-signal series. An ensemble of GCMs is used to describe and provide the climate change signal, and the ARIMA model is used to model and project the regional deviation. Qualitative and quantitative assessments were conducted for evaluating the projection performance of the hybrid GCM-ARIMA (G-ARIMA) model. The results indicate that the G-ARIMA model can provide projected city-specific daily temperature and precipitation series comparable to historical observations and can have improved projection accuracy for several assessed annual indices compared to a commonly used downscaled projection product. The G-ARIMA model is subject to some limitations and uncertainties from the GCM-provided climate change signal. A notable feature of the G-ARIMA model is the efficiency with which projections can be updated when new observations become available, thus facilitating updating of regional temperature and precipitations projections. Given the increasing need for and use of location-specific climate projections in practical engineering applications, the G-ARIMA model is an option for regional temperature and precipitation projection for such applications. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1175/JAMC-D-20-0204.1
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 16
        StartPage: 695
    Subjects:
      – SubjectFull: Atmospheric models
        Type: general
      – SubjectFull: Computer simulation of climate change
        Type: general
      – SubjectFull: Long-range weather forecasting
        Type: general
      – SubjectFull: Precipitation forecasting
        Type: general
      – SubjectFull: Weather forecasting
        Type: general
    Titles:
      – TitleFull: Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation.
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            NameFull: LAI, YUCHUAN
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            NameFull: DZOMBAK, DAVID A.
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            – D: 01
              M: 05
              Text: May2021
              Type: published
              Y: 2021
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              Value: 60
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              Value: 5
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            – TitleFull: Journal of Applied Meteorology & Climatology
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