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  4. A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales
 
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A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Journal
Geoscientific Model Development
Journal Volume
14
Journal Issue
1
Pages
73-90
Date Issued
2021
Author(s)
Ma H.-Y
Zhou C
Zhang Y
Klein S.A
Zelinka M.D
Zheng X
Xie S
Chen W.-T
CHIEN-MING WU  
WEI-TING CHEN  
DOI
10.5194/gmd-14-73-2021
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099124751&doi=10.5194%2fgmd-14-73-2021&partnerID=40&md5=b060a159b23041e10b6a0a09f10d6aca
https://scholars.lib.ntu.edu.tw/handle/123456789/571794
Abstract
We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes-the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden-Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Ni?o-Southern Oscillation-are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-Term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment. ? 2021 Royal Society of Chemistry. All rights reserved.
Subjects
climate modeling; diurnal variation; El Nino-Southern Oscillation; experimental study; heating; hindcasting; Madden-Julian oscillation; precipitation (climatology); sea surface temperature; temperature anomaly; wind stress; zonal wind; United States
SDGs

[SDGs]SDG13

Other Subjects
climate modeling; diurnal variation; El Nino-Southern Oscillation; experimental study; heating; hindcasting; Madden-Julian oscillation; precipitation (climatology); sea surface temperature; temperature anomaly; wind stress; zonal wind; United States
Type
journal article

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