scholarly journals Using machine learning and artificial intelligence to improve model-data integrated earth system model predictions of water and carbon cycle extremes

2021 ◽  
Author(s):  
Jinyun Tang
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Carbon Cycle ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Data ◽  
Improve Model ◽  
Model Predictions

scholarly journals Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM)

2013 ◽  
Vol 6 (2) ◽  
pp. 301-325 ◽  
Author(s):  
J. F. Tjiputra ◽  
C. Roelandt ◽  
M. Bentsen ◽  
D. M. Lawrence ◽  
T. Lorentzen ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Deep Water ◽  
Earth System Model ◽  
Carbon Pool ◽  
System Model ◽  
Carbon Uptake ◽  
Generation Model ◽  
Earth System ◽  
Model Data ◽  
Overturning Circulation

Abstract. The recently developed Norwegian Earth System Model (NorESM) is employed for simulations contributing to the CMIP5 (Coupled Model Intercomparison Project phase 5) experiments and the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC-AR5). In this manuscript, we focus on evaluating the ocean and land carbon cycle components of the NorESM, based on the preindustrial control and historical simulations. Many of the observed large scale ocean biogeochemical features are reproduced satisfactorily by the NorESM. When compared to the climatological estimates from the World Ocean Atlas (WOA), the model simulated temperature, salinity, oxygen, and phosphate distributions agree reasonably well in both the surface layer and deep water structure. However, the model simulates a relatively strong overturning circulation strength that leads to noticeable model-data bias, especially within the North Atlantic Deep Water (NADW). This strong overturning circulation slightly distorts the structure of the biogeochemical tracers at depth. Advancements in simulating the oceanic mixed layer depth with respect to the previous generation model particularly improve the surface tracer distribution as well as the upper ocean biogeochemical processes, particularly in the Southern Ocean. Consequently, near-surface ocean processes such as biological production and air–sea gas exchange, are in good agreement with climatological observations. The NorESM adopts the same terrestrial model as the Community Earth System Model (CESM1). It reproduces the general pattern of land-vegetation gross primary productivity (GPP) when compared to the observationally based values derived from the FLUXNET network of eddy covariance towers. While the model simulates well the vegetation carbon pool, the soil carbon pool is smaller by a factor of three relative to the observational based estimates. The simulated annual mean terrestrial GPP and total respiration are slightly larger than observed, but the difference between the global GPP and respiration is comparable. Model-data bias in GPP is mainly simulated in the tropics (overestimation) and in high latitudes (underestimation). Within the NorESM framework, both the ocean and terrestrial carbon cycle models simulate a steady increase in carbon uptake from the preindustrial period to the present-day. The land carbon uptake is noticeably smaller than the observations, which is attributed to the strong nitrogen limitation formulated by the land model.

scholarly journals Description and evaluation of NorESM1-F: A fast version of the Norwegian Earth System Model (NorESM)

2018 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Large Scale ◽  
Coupled Model ◽  
Coupled System ◽  
Internal Variability ◽  
Earth System Model ◽  
Meridional Overturning Circulation ◽  
System Model ◽  
Earth System

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g. 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multi-millennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speedup is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean-sea ice horizontal grid configuration that allows an increase of the ocean-sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasises model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates, and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.

scholarly journals Description and evaluation of NorESM1-F: a fast version of the Norwegian Earth System Model (NorESM)

2019 ◽  
Vol 12 (1) ◽  
pp. 343-362 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Large Scale ◽  
Coupled Model ◽  
Coupled System ◽  
Internal Variability ◽  
Earth System Model ◽  
Meridional Overturning Circulation ◽  
System Model ◽  
Earth System

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g., 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multimillennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speed-up is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean–sea ice horizontal grid configuration that allows an increase of the ocean–sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasizes model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.

scholarly journals Bergen Earth system model (BCM-C): model description and regional climate-carbon cycle feedbacks assessment

2010 ◽  
Vol 3 (1) ◽  
pp. 123-141 ◽  
Author(s):  
J. F. Tjiputra ◽  
K. Assmann ◽  
M. Bentsen ◽  
I. Bethke ◽  
O. H. Otterå ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Regional Climate ◽  
Earth System Model ◽  
System Model ◽  
Model Description ◽  
Earth System ◽  
Carbon Cycle Model ◽  
Enhanced Production ◽  
Positive Climate

Abstract. We developed a complex Earth system model by coupling terrestrial and oceanic carbon cycle components into the Bergen Climate Model. For this study, we have generated two model simulations (one with climate change inclusions and the other without) to study the large scale climate and carbon cycle variability as well as its feedback for the period 1850–2100. The simulations are performed based on historical and future IPCC CO2 emission scenarios. Globally, a pronounced positive climate-carbon cycle feedback is simulated by the terrestrial carbon cycle model, but smaller signals are shown by the oceanic counterpart. Over land, the regional climate-carbon cycle feedback is highlighted by increased soil respiration, which exceeds the enhanced production due to the atmospheric CO2 fertilization effect, in the equatorial and northern hemisphere mid-latitude regions. For the ocean, our analysis indicates that there are substantial temporal and spatial variations in climate impact on the air-sea CO2 fluxes. This implies feedback mechanisms act inhomogeneously in different ocean regions. In the North Atlantic subpolar gyre, the simulated future cooling of SST improves the CO2 gas solubility in seawater and, hence, reduces the strength of positive climate carbon cycle feedback in this region. In most ocean regions, the changes in the Revelle factor is dominated by changes in surface pCO2, and not by the warming of SST. Therefore, the solubility-associated positive feedback is more prominent than the buffer capacity feedback. In our climate change simulation, the retreat of Southern Ocean sea ice due to melting allows an additional ~20 Pg C uptake as compared to the simulation without climate change.

scholarly journals Lossy compression of Earth system model data based on a hierarchical tensor with Adaptive-HGFDR (v1.0)

2021 ◽  
Vol 14 (2) ◽  
pp. 875-887
Author(s):  
Zhaoyuan Yu ◽  
Dongshuang Li ◽  
Zhengfang Zhang ◽  
Wen Luo ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Field Data ◽  
Large Scale ◽  
Data Representation ◽  
Lossy Compression ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Data ◽  
Compression Method ◽  
Compression Parameter

Abstract. Lossy compression has been applied to the data compression of large-scale Earth system model data (ESMD) due to its advantages of a high compression ratio. However, few lossy compression methods consider both global and local multidimensional coupling correlations, which could lead to information loss in data approximation of lossy compression. Here, an adaptive lossy compression method, adaptive hierarchical geospatial field data representation (Adaptive-HGFDR), is developed based on the foundation of a stream compression method for geospatial data called blocked hierarchical geospatial field data representation (Blocked-HGFDR). In addition, the original Blocked-HGFDR method is also improved from the following perspectives. Firstly, the original data are divided into a series of data blocks of a more balanced size to reduce the effect of the dimensional unbalance of ESMD. Following this, based on the mathematical relationship between the compression parameter and compression error in Blocked-HGFDR, the control mechanism is developed to determine the optimal compression parameter for the given compression error. By assigning each data block an independent compression parameter, Adaptive-HGFDR can capture the local variation of multidimensional coupling correlations to improve the approximation accuracy. Experiments are carried out based on the Community Earth System Model (CESM) data. The results show that our method has higher compression ratio and more uniform error distributions compared with ZFP and Blocked-HGFDR. For the compression results among 22 climate variables, Adaptive-HGFDR can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity and fast changing rate. This study provides a new potential method for the lossy compression of the large-scale Earth system model data.

scholarly journals Impact of an extremely large magnitude volcanic eruption on the global climate and carbon cycle estimated from ensemble Earth System Model simulations

2012 ◽  
Vol 9 (7) ◽  
pp. 8693-8732 ◽  
Author(s):  
J. Segschneider ◽  
A. Beitsch ◽  
C. Timmreck ◽  
V. Brovkin ◽  
T. Ilyina ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Content ◽  
Volcanic Eruption ◽  
Global Climate ◽  
Earth System Model ◽  
System Model ◽  
Carbon Pools ◽  
Earth System ◽  
Ensemble Mean ◽  
Atmospheric Carbon

Abstract. The response of the global climate-carbon cycle system to an extremely large Northern Hemisphere mid latitude volcanic eruption is investigated using ensemble integrations with the comprehensive Earth System Model MPI-ESM. The model includes dynamical compartments of the atmosphere and ocean and interactive modules of the terrestrial biosphere as well as ocean biogeochemistry. The MPI-ESM was forced with anomalies of aerosol optical depth and effective radius of aerosol particles corresponding to a super eruption of the Yellowstone volcanic system. The model experiment consists of an ensemble of fifteen model integrations that are started at different pre-ENSO states of a contol experiment and run for 200 yr after the volcanic eruption. The climate response to the volcanic eruption is a maximum global monthly mean surface air temperature cooling of 3.8 K for the ensemble mean and from 3.3 K to 4.3 K for individual ensemble members. Atmospheric pCO2 decreases by a maximum of 5 ppm for the ensemble mean and by 3 ppm to 7 ppm for individual ensemble members approximately 6 yr after the eruption. The atmospheric carbon content only very slowly returns to near pre-eruption level at year 200 after the eruption. The ocean takes up carbon shortly after the eruption in response to the cooling, changed wind fields, and ice cover. This physics driven uptake is weakly counteracted by a reduction of the biological export production mainly in the tropical Pacific. The land vegetation pool shows a distinct loss of carbon in the initial years after the eruption which has not been present in simulations of smaller scale eruptions. The gain of the soil carbon pool determines the amplitude of the CO2 perturbation and the long term behaviour of the overall system: an initial gain caused by reduced soil respiration is followed by a rather slow return towards pre-eruption levels. During this phase, the ocean compensates partly for the reduced atmospheric carbon content in response to the land's gain. In summary, we find that the volcanic eruption has long lasting effects on the carbon cycle: after 200 yr, the ocean and the land carbon pools are still different from the pre-eruption state, and the land carbon pools (vegetation and soil) show some long lasting local anomalies that are only partly visible in the global signal.

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