scholarly journals Rise and fall of vegetation annual primary production resilience to climate variability projected by a large ensemble of Earth System Models’ simulations

2021 ◽  
Author(s):  
Matteo Zampieri ◽  
Bruna Grizzetti ◽  
Andrea Toreti ◽  
Pierluca De Palma ◽  
Alessio Collalti
Keyword(s):  
Climate Variability ◽  
Primary Production ◽  
Earth System ◽  
Large Ensemble ◽  
System Models ◽  
Earth System Models ◽  
Annual Primary Production

scholarly journals Plant functional type mapping for earth system models

2011 ◽  
Vol 4 (3) ◽  
pp. 2081-2121 ◽  
Author(s):  
B. Poulter ◽  
P. Ciais ◽  
E. Hodson ◽  
H. Lischke ◽  
F. Maignan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Climate Variability ◽  
Forest Cover ◽  
Plant Functional Type ◽  
Earth System ◽  
Functional Type ◽  
System Models ◽  
Satellite Sensors ◽  
Earth System Models

Abstract. The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM) rely on the concept of plant functional types (PFT) to group shared traits of thousands of plant species into just several classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution) that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (β) diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP) and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30 % (20 %) uncertainty in the sensitivity of GPP (transpiration) to precipitation. The availability of plant functional type datasets that are consistent with current satellite products and adapted for earth system models is an important component for reducing the uncertainty of terrestrial biogeochemistry to climate variability.

scholarly journals Oceanic primary production decline halved in eddy-resolving simulations of global warming

2021 ◽  
Vol 18 (14) ◽  
pp. 4321-4349
Author(s):  
Damien Couespel ◽  
Marina Lévy ◽  
Laurent Bopp
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Primary Production ◽  
Nutrient Transport ◽  
Biogeochemical Model ◽  
Earth System ◽  
System Models ◽  
Marine Biomass ◽  
Fish Catch ◽  
Earth System Models

Abstract. The decline in ocean primary production is one of the most alarming consequences of anthropogenic climate change. This decline could indeed lead to a decrease in marine biomass and fish catch, as highlighted by recent policy-relevant reports. Because of computational constraints, current Earth system models used to project ocean primary production under global warming scenarios have to parameterize flows occurring below the resolution of their computational grid (typically 1∘). To overcome these computational constraints, we use an ocean biogeochemical model in an idealized configuration representing a mid-latitude double-gyre circulation and perform global warming simulations under an increasing horizontal resolution (from 1 to 1/27∘) and under a large range of parameter values for the eddy parameterization employed in the coarse-resolution configuration. In line with projections from Earth system models, all our simulations project a marked decline in net primary production in response to the global warming forcing. Whereas this decline is only weakly sensitive to the eddy parameters in the eddy-parameterized coarse 1∘ resolution simulations, the simulated decline in primary production in the subpolar gyre is halved at the finest eddy-resolving resolution (−12 % at 1/27∘ vs. −26 % at 1∘) at the end of the 70-year-long global warming simulations. This difference stems from the high sensitivity of the sub-surface nutrient transport to model resolution. Although being only one piece of a much broader and more complicated response of the ocean to climate change, our results call for improved representation of the role of eddies in nutrient transport below the seasonal mixed layer to better constrain the future evolution of marine biomass and fish catch potential.

scholarly journals Oceanic Primary production decline halved in eddy-resolving simulations of global warming

2021 ◽  
Author(s):  
Damien Couespel ◽  
Marina Lévy ◽  
Laurent Bopp
Keyword(s):  
Global Warming ◽  
Primary Production ◽  
Nutrient Transport ◽  
Biogeochemical Model ◽  
Earth System ◽  
System Models ◽  
Coarse Resolution ◽  
Marine Biomass ◽  
Fish Catch ◽  
Earth System Models

<p>The decline in ocean primary production is one of the most alarming consequences of anthropogenic climate change. This decline could indeed lead to a decrease in marine biomass and fish catch, as highlighted by recent policy-relevant reports. Because of computational constraints, current Earth System Models used to project ocean primary production under global warming scenarios have to parameterize flows occurring below the resolution of their computational grid (typically 1°). To overcome these computational constraints, we use an ocean biogeochemical model in an idealized configuration representing a mid-latitude double-gyre circulation, and perform global warming simulations under increasing horizontal resolution  (from 1° to 1/27°) and under a large range of parameter values for the eddy parameterization employed in the coarse resolution configuration. In line with projections from Earth System Models, all our simulations project a marked decline in net primary production in response to the global warming forcing. Whereas this decline is only weakly sensitive to the eddy parameters in the eddy-parametrized coarse resolution, the simulated decline in primary production is halved at the finest eddy-resolving resolution (-12% at 1/27° vs -26 at 1°). This difference stems from the high sensitivity of the subsurface nutrient transport to model resolution. Our results call for improved representation of the role of eddies on nutrient transport below the seasonal mixed-layer to better constrain the future evolution of marine biomass and fish catch potential for decision-making.</p>

Causes of uncertainty in China's net primary production over the 21st century projected by the CMIP5 Earth system models

2015 ◽  
Vol 36 (5) ◽  
pp. 2323-2334 ◽  
Author(s):  
Tao Wang ◽  
Xin Lin ◽  
Yongwen Liu ◽  
Sarah Dantec-Nédélec ◽  
Catherine Ottlé
Keyword(s):  
Primary Production ◽  
21St Century ◽  
Net Primary Production ◽  
Earth System ◽  
System Models ◽  
Earth System Models

From the last interglacial to the future – new insights from modeling the last glacial-interglacial cycle in PalMod

2021 ◽  
Author(s):  
Kerstin Fieg ◽  
Mojib Latif ◽  
Michael Schulz ◽  
Tatjana Ilyina
Keyword(s):  
Climate Variability ◽  
Ice Sheet ◽  
Earth System ◽  
Glacial Cycle ◽  
System Models ◽  
Last Glacial ◽  
The Future ◽  
Fully Coupled ◽  
Earth System Models ◽  
The Last Glacial

<p>We present new insights from the project PalMod, which started in 2016 and is envisioned to run for a decade. The modelling initiative PalMod aims at filling the long-standing scientific gaps in our understanding of the dynamics and variability of the climate system during the last glacial-interglacial cycle. One of the grand challenges in this context is to quantify the processes that determine the spectrum of climate variability on timescales that range from seasons to millennia. Climatic processes are intimately coupled across these timescales. Understanding variability at any one timescale requires understanding of the whole spectrum. If we could successfully simulate the spectrum of climate variability during the last glacial cycle in Earth system models, would this enable us to more reliably assess the future climate change? Such simulations are necessary to deduce, for example, if a regime shift in climate variability could occur during the next centuries and millennia in response to global warming. PalMod is specifically designed to enhance our understanding of the Earth system dynamics and its variability on timescales up to the multimillennial with complex Earth System Models.</p><p>The following major goals were achieved up to now:</p><ul><li>Full coupling of atmosphere, ocean and ice-sheet models, enabling investigation of Heinrich Events and bi-stability of the AMOC, and millennial-scale transient climate-ice sheet simulations.</li> <li>Implementation of a coupled ocean and land biogeochemistry enabling simulations with prognostic atmospheric CO<sub>2</sub> concentrations and including improved representation of methane (CH<sub>4</sub>) in transient deglaciation runs.</li> <li>Systematic comparison of newly compiled proxy data with model simulations.</li> </ul><p>The major goal for the next two years is to set up the fully coupled physical-biogeochemical model which will be tested for three time periods: deglaciation, glacial inception and Marine Isotope Stage 3 (MIS3). This fully coupled model will be eventually used to simulate the complete glacial cycle and project the climate over the next few millennia.</p>

scholarly journals Plant functional type mapping for earth system models

2011 ◽  
Vol 4 (4) ◽  
pp. 993-1010 ◽  
Author(s):  
B. Poulter ◽  
P. Ciais ◽  
E. Hodson ◽  
H. Lischke ◽  
F. Maignan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Climate Variability ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Earth System ◽  
State Variables ◽  
System Models ◽  
Satellite Sensors ◽  
Earth System Models

Abstract. The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM) rely on the concept of plant functional types (PFT) to group shared traits of thousands of plant species into usually only 10–20 classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution) that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (ß) diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP) and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30% (20%) uncertainty in the sensitivity of GPP (transpiration) to precipitation. The availability of PFT datasets that are consistent with current satellite products and adapted for earth system models is an important component for reducing the uncertainty of terrestrial biogeochemistry to climate variability.

scholarly journals Resolving and Parameterising the Ocean Mesoscale in Earth System Models

2020 ◽  
Vol 6 (4) ◽  
pp. 137-152
Author(s):  
Helene T. Hewitt ◽  
Malcolm Roberts ◽  
Pierre Mathiot ◽  
Arne Biastoch ◽  
Ed Blockley ◽  
...  
Keyword(s):  
Climate Variability ◽  
Meridional Overturning Circulation ◽  
Earth System ◽  
System Models ◽  
Recent Developments ◽  
Meridional Overturning ◽  
The Mean ◽  
The Impact ◽  
Earth System Models ◽  
Mean State

Abstract Purpose of Review Assessment of the impact of ocean resolution in Earth System models on the mean state, variability, and future projections and discussion of prospects for improved parameterisations to represent the ocean mesoscale. Recent Findings The majority of centres participating in CMIP6 employ ocean components with resolutions of about 1 degree in their full Earth System models (eddy-parameterising models). In contrast, there are also models submitted to CMIP6 (both DECK and HighResMIP) that employ ocean components of approximately 1/4 degree and 1/10 degree (eddy-present and eddy-rich models). Evidence to date suggests that whether the ocean mesoscale is explicitly represented or parameterised affects not only the mean state of the ocean but also the climate variability and the future climate response, particularly in terms of the Atlantic meridional overturning circulation (AMOC) and the Southern Ocean. Recent developments in scale-aware parameterisations of the mesoscale are being developed and will be included in future Earth System models. Summary Although the choice of ocean resolution in Earth System models will always be limited by computational considerations, for the foreseeable future, this choice is likely to affect projections of climate variability and change as well as other aspects of the Earth System. Future Earth System models will be able to choose increased ocean resolution and/or improved parameterisation of processes to capture physical processes with greater fidelity.

scholarly journals Intercomparison of Terrestrial Carbon Fluxes and Carbon Use Efficiency Simulated by CMIP5 Earth System Models

2016 ◽  
Author(s):  
Dongmin Kim ◽  
Myong-In Lee ◽  
Su-Jong Jeong ◽  
Jungho Im ◽  
Dong Hyun Cha ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Primary Production ◽  
Carbon Fluxes ◽  
Earth System ◽  
Terrestrial Carbon ◽  
System Models ◽  
Carbon Use Efficiency ◽  
Terrestrial Carbon Cycle ◽  
Use Efficiency ◽  
Earth System Models

Abstract. This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.

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