Impact of initial conditions on seasonal simulations with an atmospheric general circulation model

Abstract

Many previous studies have examined the use of very long integrations of atmospheric general circulation models (AGCMs) forced by observed sea surface temperatures (SSTs) as proxies for seasonal atmospheric predictions. These long simulations explore a boundary-value problem in which significant deviations from the model's long-term climatology must be a result of the SST forcing. Seasonal lead simulations starting with observed initial conditions (ICs) for the atmosphere and land surface while retaining observed SST forcing are an intermediate step between the pure boundary-value problem and the pure initial-value forecast problem in which SSTs are also predicted. As part of the Dynamical Seasonal Prediction (DSP) experiment, an ensemble of AGCM integrations with observed atmospheric ICs and model climatology land surface ICs was integrated from mid-December through March for 16 years. These DSP simulation ensembles are compared to ensembles of long boundary-value simulations from the same AGCM in a perfect-model setting (no comparisons of simulations to observations are attempted). Significant differences must be due to the impact of the DSP ICs. Surprisingly large and long-lived differences are found in both the mean and the variance of the ensembles. Many appear to occur because the ICs of the DSP runs are inconsistent with the AGCM climatology; an extended period of model 'spinup' is the result. Some differences are related to local impacts of the land surface ICs while others, like shifts in the distribution of tropical precipitation and a cooling of the northern hemisphere, are less obviously related to the ICs. The results suggest that care will be needed when inserting observed ICs into seasonal predictions in order to avoid the long-term effects of model spin-up.

Simulation capability of tropical and extratropical seasonal climate anomalies over South America

“…The atmospheric general circulation models (AGCM) constitute one of the most powerful tools for the study of climate variability and seasonal or longer scale climate forecast. Numerous works published in recent years exemplify the progressive advances achieved on the matters and the challenges foreseen for the near future (Chen and Van den Dool 1997;De´que´1997;Shukla et al 2000;Anderson and Ploshay 2000;Chang et al 2000). A discussion on the main theoretical and practical topics of the climate forecast, and a survey on the status of the acquired knowledge and of the developed capability can be found in the revision carried on by Goddard et al (2001).…”

“…The hindcast of climate anomalies using atmospheric models forced with observed SST data provides an important piece of information: The skill of the atmospheric model can be considered as the maximum skill attainable when coupled to any oceanic model for the forecast of climate anomalies. The inclusion of the initial conditions of the system and the boundary condi-tions in the soil-atmosphere interface, controlled by factors as diverse and heterogeneous as the physical properties and state of the soil, type and physiological status of the vegetation, and terrain topography, adds new challenges to the problem (Anderson and Ploshay 2000).…”

Comparative Study on the Seasonal Predictability Dependency of Boreal Winter 2m Temperature and Sea Surface Temperature on CGCM Initial Conditions

“…Phone : +82-51-514-1932, Fax : +82-51-514-1932 leejl@pusan.ac.kr 기 술 노 트 (Technical Note) 한국기상학회 대기 제25권 2호 (2015) 리적 과정 (Stensrud et al, 1999 (Alves et al, 2004;Balmaseda and Anderson, 2009). 세계 여러 현업기관(operational center)에서도 계절 예측성을 향상시키기 위하여 모델 의 물리적 과정과 해상도를 개선하는 것 외에도 접합 대순환모형 초기조건의 질을 향상시켜 모형의 예측성 을 개선하고 있다(e.g., Wang et al, 2001;Palmer et al, 2004;Saha et al, 2006;Molteni et al, 2011;Kim et al, 2012;Saha et al, 2014 (Saha et al, 2010(Saha et al, , 2014 (Gates, 1992;Koster et al, 2009;Sun and Ahn, 2014 (Ji et al, 1998 Ghil and Malanotte-Rizzoli, 1991;Wunsch, 1996;Bennett, 2002;Dommenget et al, 2004;Wikle and Berliner, 2007;Yang et al, 2009 Reichler and Roads, 1999;Kessler and Kleeman, 2000;Hendon et al, 2007;Shi et al, 2009) 재분석자료를 초기조건으로 사용하되, 이 초기조건에 서 발생하는 모델 내에 충격을 피하기 위해 하루의 spin-up을 수행하였다 (Anderson and Ploshay, 2000). 보 다 자세한 방법에 대한 설명은 2장에서 설명하였다.…”