scholarly journals Seasonal-to-decadal predictions with the ensemble Kalman filter and the Norwegian Earth System Model: a twin experiment

2014 ◽  
Vol 66 (1) ◽  
pp. 21074 ◽  
Author(s):  
Francois Counillon ◽  
Ingo Bethke ◽  
Noel Keenlyside ◽  
Mats Bentsen ◽  
Laurent Bertino ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Decadal Predictions

Parameter estimation for ocean biogeochemical component in a global model using Ensemble Kalman Filter: a twin experiment

2021 ◽  
Author(s):  
Tarkeshwar Singh ◽  
Francois Counillon ◽  
Jerry F. Tjiputra ◽  
Mohamad El Gharamti
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
Parameter Values

<p>Ocean biogeochemical (BGC) models utilize a large number of poorly-constrained global parameters to mimic unresolved processes and reproduce the observed complex spatio-temporal patterns. Large model errors stem primarily from inaccuracies in these parameters whose optimal values can vary both in space and time. This study aims to demonstrate the ability of ensemble data assimilation (DA) methods to provide high-quality and improved BGC parameters within an Earth system model in idealized twin experiment framework.  We use the Norwegian Climate Prediction Model (NorCPM), which combines the Norwegian Earth System Model with the Dual-One-Step ahead smoothing-based Ensemble Kalman Filter (DOSA-EnKF). The work follows on Gharamti et al. (2017) that successfully demonstrates the approach for one-dimensional idealized ocean BGC models. We aim to estimate five spatially varying BGC parameters by assimilating Salinity and Temperature hydrographic profiles and surface BGC (Phytoplankton, Nitrate, Phosphorous, Silicate, and Oxygen) observations in a strongly coupled DA framework – i.e., jointly updating ocean and BGC state-parameters during the assimilation. The method converges quickly (less than a year), largely reducing the errors in the BGC parameters and eventually it is shown to perform nearly as well as that of the system with true parameter values. Optimal parameter values can also be recovered by assimilating climatological BGC observations and challenging sparse observational networks. The findings of this study demonstrate the applicability of the approach for tuning the system in a real framework.</p><p> </p><p><strong>References</strong>:</p><p>Gharamti, M. E., Tjiputra, J., Bethke, I., Samuelsen, A., Skjelvan, I., Bentsen, M., & Bertino, L. (2017). Ensemble data assimilation for ocean biogeochemical state and parameter estimation at different sites. Ocean Modelling, 112, 65-89.</p>

scholarly journals Full-field initialized decadal predictions with the MPI earth system model: an initial shock in the North Atlantic

2017 ◽  
Vol 51 (7-8) ◽  
pp. 2593-2608 ◽  
Author(s):  
Jürgen Kröger ◽  
Holger Pohlmann ◽  
Frank Sienz ◽  
Jochem Marotzke ◽  
Johanna Baehr ◽  
...  
Keyword(s):  
North Atlantic ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Full Field ◽  
The North ◽  
Initial Shock ◽  
The North Atlantic ◽  
Decadal Predictions

Korea Institute of Ocean Science and Technology Earth System Model and Its Simulation Characteristics

2021 ◽  
Author(s):  
Gyundo Pak ◽  
Yign Noh ◽  
Myong-In Lee ◽  
Sang-Wook Yeh ◽  
Daehyun Kim ◽  
...  
Keyword(s):  
Science And Technology ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Ocean Science

scholarly journals Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

2021 ◽  
Author(s):  
Hyun Min Sung ◽  
Jisun Kim ◽  
Sungbo Shim ◽  
Jeong-byn Seo ◽  
Sang-Hoon Kwon ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Scientific Information ◽  
Earth System Model ◽  
First Century ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Future Projections ◽  
Twenty First Century

AbstractThe National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

scholarly journals Quantifying the Cloud Particle‐Size Feedback in an Earth System Model

2019 ◽  
Vol 46 (19) ◽  
pp. 10910-10917
Author(s):  
Jiang Zhu ◽  
Christopher J. Poulsen
Keyword(s):  
Particle Size ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Cloud Particle

scholarly journals Simulations of the Mid-Pliocene Warm Period using the NASA/GISS ModelE2-R Earth System Model

2012 ◽  
Vol 5 (3) ◽  
pp. 2811-2842 ◽  
Author(s):  
M. A. Chandler ◽  
L. E. Sohl ◽  
J. A. Jonas ◽  
H. J. Dowsett
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Climate Model ◽  
Geographic Region ◽  
Earth System Model ◽  
Warm Period ◽  
System Model ◽  
Earth System ◽  
Intergovernmental Panel ◽  
Future Global Warming

Abstract. Climate reconstructions of the mid-Pliocene Warm Period (mPWP) bear many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change. In particular, marine and terrestrial paleoclimate data point to high latitude temperature amplification, with associated decreases in sea ice and land ice and altered vegetation distributions that show expansion of warmer climate biomes into higher latitudes. NASA GISS climate models have been used to study the Pliocene climate since the USGS PRISM project first identified that the mid-Pliocene North Atlantic sea surface temperatures were anomalously warm. Here we present the most recent simulations of the Pliocene using the AR5/CMIP5 version of the GISS Earth System Model known as ModelE2-R. These simulations constitute the NASA contribution to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. We provide discussion of features that show considerable improvement compared with simulations from previous versions of the NASA GISS models, improvement defined here as simulation results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene climate. In some regions even qualitative agreement between model results and paleodata are an improvement over past studies, but the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea in these new simulations is by far the most accurate portrayal ever of this key geographic region by the GISS climate model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterizations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

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