Estimates of Mass Transport of the Antarctic Bottom Water with Earth System Model and Data Assimilation Technique

2018 ◽  
Author(s):  
Eugene Morozov ◽  
Konstantin Belyaev ◽  
Natalia Tuchkova ◽  
Guriy Mickailov
Keyword(s):  
Data Assimilation ◽  
Mass Transport ◽  
Bottom Water ◽  
Earth System Model ◽  
System Model ◽  
Antarctic Bottom Water ◽  
Earth System ◽  
Data Assimilation Technique ◽  
The Antarctic

scholarly journals Meridional mass transport of bottom water in the South Atlantic

2019 ◽  
Vol 55 (4) ◽  
pp. 73-81
Author(s):  
K. P. Belyaev ◽  
E. G. Morozov ◽  
N. P. Tuchkova
Keyword(s):  
Data Assimilation ◽  
Mass Transport ◽  
Bottom Water ◽  
Dynamic Method ◽  
Original Data ◽  
System Model ◽  
Antarctic Bottom Water ◽  
Model Calculations ◽  
Flow Transport ◽  
Generalized Kalman Filter

Estimates of the meridional mass transport of Antarctic Bottom Water, calculated using the coupled ocean- atmosphere model called “Earth System Model” in conjunction with the original data assimilation method are presented. We used the data of the latitudinal CTD sections of temperature and salinity of the WOCE international experiment in 1991-1995 for assimilation. Estimates of the current velocities of Antarctic Bottom Water with the assimilation of observational data are given. We used the author’s data assimilation method, which was previously referred as the generalized Kalman Filter (GKF) method. In the particular case it coincides with the classical Kalman method (EnKF). We also analyze the estimates of the mass transport by the standard dynamic scheme. It is shown that model calculations with data assimilation are qualitatively the same and are quantitatively close to the estimates of geostrophic flow transport based on the dynamic method.

scholarly journals Tropical climate variability in the Community Earth System Model: Data Assimilation Research Testbed

2019 ◽  
Vol 54 (1-2) ◽  
pp. 793-806 ◽  
Author(s):  
Jonathan Eliashiv ◽  
Aneesh C. Subramanian ◽  
Arthur J. Miller
Keyword(s):  
Data Assimilation ◽  
Climate Variability ◽  
Tropical Climate ◽  
Earth System Model ◽  
The Other ◽  
System Model ◽  
Earth System ◽  
Ocean Atmosphere ◽  
Community Earth System Model ◽  
Free Running

AbstractA new prototype coupled ocean–atmosphere Ensemble Kalman Filter reanalysis product, the Community Earth System Model using the Data Assimilation Research Testbed (CESM-DART), is studied by comparing its tropical climate variability to other reanalysis products, available observations, and a free-running version of the model. The results reveal that CESM-DART produces fields that are comparable in overall performance with those of four other uncoupled and coupled reanalyses. The clearest signature of differences in CESM-DART is in the analysis of the Madden–Julian Oscillation (MJO) and other tropical atmospheric waves. MJO energy is enhanced over the free-running CESM as well as compared to the other products, suggesting the importance of the surface flux coupling at the ocean–atmosphere interface in organizing convective activity. In addition, high-frequency Kelvin waves in CESM-DART are reduced in amplitude compared to the free-running CESM run and the other products, again supportive of the oceanic coupling playing a role in this difference. CESM-DART also exhibits a relatively low bias in the mean tropical precipitation field and mean sensible heat flux field. Conclusive evidence of the importance of coupling on data assimilation performance will require additional detailed direct comparisons with identically formulated, uncoupled data assimilation runs.

scholarly journals Snowpack and firn densification in the Energy Exascale Earth System Model (E3SM) (version 1.2)

2020 ◽  
Author(s):  
Adam M. Schneider ◽  
Charles S. Zender ◽  
Stephen F. Price
Keyword(s):  
Empirical Model ◽  
Land Surface ◽  
Large Fraction ◽  
Ice Sheets ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Community Land Model ◽  
Semi Empirical ◽  
The Antarctic

Abstract. Earth's largest island, Greenland, and the Antarctic continent are both covered by massive ice sheets. A large fraction of their surfaces consist of multi-year snow, known as firn, which has undergone a process of densification since falling from the atmosphere. Until now this firn densification has not been fully accounted for in the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM). Here, we expand the E3SM Land Model (ELM) snowpack from 1 m to up to 60 m to enable more accurate simulation of snowpack evolution. We test four densification models in a series of century-scale land surface simulations forced by atmospheric re-analyses, and evaluate these parameterizations against empirical density-versus-depth data. To tailor candidate densification models for use across the ice sheets' dry-snow zones, we optimize parameters using a regularized least squares algorithm applied to two distinct stages of densification. We find that a dynamic implementation of a semi-empirical compaction model, originally calibrated to measurements from the Antarctic peninsula, gives results more consistent with ice core measurements from the cold, dry snow zones of Greenland and Antarctica, compared to when using the original ELM snow compaction physics. In its latest release, the Community Land Model (CLM) (version 5) provides updated snow compaction physics that we test in ELM, resulting in top 10 m firn densities that are in better agreement with observations than densities simulated with the semi-empirical model. Below 10 m, however, the semi-empirical model gives results that more closely match observations, while the current CLM(v5) compaction physics predict firn densities that increase too slowly with depth and are thus unable to simulate pore close off (a phenomenon of particular interest to paleoclimate studies). Because snow and firn density play roles in snowpack albedo, liquid water storage, and ice sheet surface mass balance, these improvements will contribute to broader E3SM efforts to simulate the response of land ice to atmospheric forcing and the resulting impacts on global sea level.

Ice-shelf Basal Melt Rates in the Energy Exascale Earth System Model (E3SM)

2021 ◽  
Author(s):  
Darin Comeau ◽  
Xylar Asay-Davis ◽  
Carolyn Begeman ◽  
Matthew Hoffman ◽  
Wuyin Lin ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Ice Sheet ◽  
High Sensitivity ◽  
Ocean Model ◽  
Earth System Model ◽  
System Model ◽  
Freshwater Flux ◽  
Earth System ◽  
Ice Shelf ◽  
The Antarctic

<p>The processes responsible for freshwater flux from the Antarctic Ice Sheet (AIS) -- ice-shelf basal melting and iceberg calving -- are generally poorly represented in current Earth System Models (ESMs). Here, we document the first effort to date at simulating the ocean circulation and exchanges of heat and freshwater within ice-shelf cavities in a coupled ESM, the Department of Energy's Energy Exascale Earth System Model (E3SM). As a step towards full ice-sheet coupling, we implemented static Antarctic ice-shelf cavities and the ability to calculate ice-shelf basal melt rates from the heat and freshwater fluxes computed by the ocean model. In addition, we added the capability to prescribe forcing from iceberg melt, allowing us to realistically represent the other dominant mass loss process from the AIS. In global, low resolution (i.e., non-eddying ocean) simulations, we find high sensitivity of modeled ocean/ice shelf interactions to the ocean state, which can result in a tipping point to high melt regimes under certain ice shelves, presenting a significant challenge to representing the ocean/ice shelf system in a coupled ESM. We show that inclusion of a spatially dependent parameterization of eddy-induced transport reduces biases in water mass properties on the Antarctic continental shelf. With these improvements, E3SM produces realistic and stable ice-shelf basal melt rates across the continent under pre-industrial climate forcing. We also show preliminary results using an ocean/sea-ice grid that makes use of E3SM’s regional-refinement capability, where increased resolution (down to 12km) is placed in the Southern Ocean around Antarctica, bypassing the need for parameterization of eddy-induced transport in this region. The accurate representation of these processes within a coupled ESM is an important step towards reducing uncertainties in projections of the Antarctic response to climate change and Antarctica's contribution to global sea-level rise.</p>

Exploring and reducing biases in sub-ice-shelf melt rates in an Earth system model

2020 ◽  
Author(s):  
Xylar Asay-Davis ◽  
Carolyn Begeman ◽  
Darin Comeau ◽  
Matthew Hoffman ◽  
Wuyin Lin ◽  
...  
Keyword(s):  
Continental Shelf ◽  
Critical Role ◽  
Ice Sheet ◽  
Earth System Model ◽  
System Model ◽  
Recent Experience ◽  
Earth System ◽  
Ice Shelf ◽  
Ocean Properties ◽  
The Antarctic

<p>Sub-ice-shelf melting plays a critical role in the dynamics of the Antarctic Ice  Sheet and also feeds back on the regional climate, transforming ocean properties (e.g., affecting deep-water production and sea-ice formation).  A full understanding of these processes, as well as the ability to project their response to a changing climate, requires Earth System Models (ESMs) that include coupling with ice-sheet processes.  However, biases in regional Antarctic climate can be amplified through sub-ice-shelf melting, and biased melt rates can have significant adverse effects on ice-sheet model initialization and evolution.  In preparation for inclusion of dynamic ice sheets in ESMs, this presentation discusses our recent experience in understanding the causes of biases in ocean properties on the Antarctic continental shelf and their relationship to ice-shelf melting.  Differences in model behavior across configurations and simulations using the Energy Exascale Earth System Model (E3SM) demonstrates a sensitivity of melt rates to climate. We assess the sensitivity of those melt rates to changes in the region’s climate, including freshening on the continental shelf and shoaling of the thermocline. We also show that ice-shelf meltwater feeds back onto the climate, for example, by affecting melting under neighboring ice shelves, sometimes dramatically so.  We demonstrate that significant reductions in melt-rate biases can be achieved through modifications to ocean model mixing parameterizations. This work charts a path forward for configuring ESMs to produce realistic Antarctic melt rates.</p>

scholarly journals Representation of the Antarctic Oscillation and related precipitation patterns in the MPI Earth System Model

2016 ◽  
Vol 25 (6) ◽  
pp. 767-774 ◽  
Author(s):  
Stella Babian ◽  
Henning W. Rust ◽  
Jens Grieger ◽  
Kerstin Prömmel ◽  
Ulrich Cubasch
Keyword(s):  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Antarctic Oscillation ◽  
Precipitation Patterns ◽  
The Antarctic

scholarly journals Coupling of a sediment diagenesis model (MEDUSA) and an Earth system model (CESM1.2): a contribution toward enhanced marine biogeochemical modelling and long-term climate simulations

2020 ◽  
Vol 13 (2) ◽  
pp. 825-840 ◽  
Author(s):  
Takasumi Kurahashi-Nakamura ◽  
André Paul ◽  
Guy Munhoven ◽  
Ute Merkel ◽  
Michael Schulz
Keyword(s):  
Chemical Composition ◽  
Model Uncertainty ◽  
Bottom Water ◽  
Coupled Model ◽  
Earth System Model ◽  
System Model ◽  
Future Application ◽  
Earth System ◽  
Climate Simulations

Abstract. We developed a coupling scheme for the Community Earth System Model version 1.2 (CESM1.2) and the Model of Early Diagenesis in the Upper Sediment of Adjustable complexity (MEDUSA), and explored the effects of the coupling on solid components in the upper sediment and on bottom seawater chemistry by comparing the coupled model's behaviour with that of the uncoupled CESM having a simplified treatment of sediment processes. CESM is a fully coupled atmosphere–ocean–sea-ice–land model and its ocean component (the Parallel Ocean Program version 2; POP2) includes a biogeochemical component (the Biogeochemical Elemental Cycling model; BEC). MEDUSA was coupled to POP2 in an offline manner so that each of the models ran separately and sequentially with regular exchanges of necessary boundary condition fields. This development was done with the ambitious aim of a future application for long-term (spanning a full glacial cycle; i.e. ∼105 years) climate simulations with a state-of-the-art comprehensive climate model including the carbon cycle, and was motivated by the fact that until now such simulations have been done only with less-complex climate models. We found that the sediment–model coupling already had non-negligible immediate advantages for ocean biogeochemistry in millennial-timescale simulations. First, the MEDUSA-coupled CESM outperformed the uncoupled CESM in reproducing an observation-based global distribution of sediment properties, especially for organic carbon and opal. Thus, the coupled model is expected to act as a better “bridge” between climate dynamics and sedimentary data, which will provide another measure of model performance. Second, in our experiments, the MEDUSA-coupled model and the uncoupled model had a difference of 0.2 ‰ or larger in terms of δ13C of bottom water over large areas, which implied a potentially significant model uncertainty for bottom seawater chemical composition due to a different way of sediment treatment. For example, an ocean model that does not treat sedimentary processes depending on the chemical composition of the ambient water can overestimate the amount of remineralization of organic matter in the upper sediment in an anoxic environment, which would lead to lighter δ13C values in the bottom water. Such a model uncertainty would be a fundamental issue for paleo model–data comparison often relying on data derived from benthic foraminifera.

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 An Online Ensemble Coupled Data Assimilation Capability for the Community Earth System Model: System Design and Evaluation

2021 ◽  
Author(s):  
Jingzhe Sun ◽  
Yingjing Jiang ◽  
Shaoqing Zhang ◽  
Weimin Zhang ◽  
Lv Lu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Coupled Model ◽  
Model Atmosphere ◽  
Earth System Model ◽  
System Model ◽  
Ocean Temperature ◽  
Earth System ◽  
Cross Covariance ◽  
Community Earth System Model ◽  
Coupled Data Assimilation

Abstract. The Community Earth System Model (CESM) developed at the National Center of Atmospheric Research (NCAR) has been used worldwide for climate studies. This study extends the efforts of CESM development to include an online (i.e., in-core) ensemble coupled data assimilation system (CESM-ECDA) to enhance CESM’s capability for climate predictability studies and prediction applications. The CESM-ECDA system consists of an online atmospheric data assimilation (ADA) component implemented to both the finite-volume and spectral-element dynamical cores, and an online oceanic data assimilation (ODA) component. In ADA, surface pressures (Ps) are assimilated, while in ODA, gridded sea surface temperature (SST) and ocean temperature and salinity profiles at real Argo locations are assimilated. The system has been evaluated within a perfect twin experiment framework, showing significantly reduced errors of the model atmosphere and ocean states through “observation”-constraints by ADA and ODA. The weakly CDA in which both the online ADA and ODA are conducted during the coupled model integration shows smaller errors of air-sea fluxes than the single ADA and ODA, facilitating the future utilization of cross-covariance between the atmosphere and ocean at the air-sea interface. A three-year CDA reanalysis experiment is also implemented by assimilating Ps, SST and ocean temperature and salinity profiles from the real world spanning the period 1978 to 1980 using 12 ensemble members. Results show that Ps RMSE is smaller than 20CR and SST RMSE is better than ERA-20C and close to CFSR. The success of the online CESM-ECDA system is the first step to implement a high-resolution long-term climate reanalysis once the algorithm efficiency is much improved.

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