Global transpiration modelling: can the optimality hypothesis improve partitioning of ecosystem-scale evapotranspiration?

2020 ◽  
Author(s):  
Alison Prior ◽  
Iain-Colin Prentice
Keyword(s):  
Climate Models ◽  
Gross Primary Production ◽  
Vapour Pressure Deficit ◽  
Co2 Concentration ◽  
Water Model ◽  
Model Parameters ◽  
Water Runoff ◽  
Vegetation Growth ◽  
Green Vegetation ◽  
Surface Water Runoff

<p>The volume of water entering the atmosphere through transpiration is thought to be greater than the flow of all rivers to the oceans. It makes up the majority of evapotranspiration (ET) and significantly contributes to rainfall and therefore also to surface water runoff. However, there is no consensus on how transpiration responds to a changing environment; or even as to whether it is increasing over time. Global transpiration estimates are most commonly made through the partitioning of ET models.  However, in many ET models, the dynamics of vegetation growth and associated impacts on evapotranspiration are overlooked. Therefore, global estimates of transpiration from climate models are poorly constrained, with large uncertainties especially in stomatal conductance.</p><p>The ‘P model’ (for Production) is a recently developed, ‘next-generation’ model for Gross Primary Production, GPP. Derived from biochemical process of plants, the P model is built upon the established standard model for photosynthesis – combined with optimality hypotheses for the adaptation and acclimation of key model parameters – to determine GPP. The P model has the potential to provide a coupled global carbon and water model that responds correctly to changing environmental conditions. It requires only elevation, CO2 concentration, incident solar radiation, vapour pressure deficit (VPD) and temperature as inputs, in addition to remotely sensed green vegetation cover (fAPAR). The key idea motivating this research is that by exploiting the coupling of land-atmosphere carbon and water exchanges through stomatal behaviour, it should be possible to develop a near real-time transpiration monitoring system in which fAPAR is a key input. The P-model provides the means to do this. Initial results will be shown for both transpiration and GPP, with validation at >100 eddy-covariance flux-tower sites.</p>

scholarly journals Biophsyical constraints on gross primary production by the terrestrial biosphere

2014 ◽  
Vol 11 (20) ◽  
pp. 5987-6001 ◽  
Author(s):  
H. Wang ◽  
I. C. Prentice ◽  
T. W. Davis
Keyword(s):  
Primary Production ◽  
Optimality Theory ◽  
Vegetation Cover ◽  
Gross Primary Production ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Water Shortage ◽  
C3 Plants ◽  
Environmental Controls ◽  
Green Vegetation

Abstract. Persistent divergences among the predictions of complex carbon-cycle models include differences in the sign as well as the magnitude of the response of global terrestrial primary production to climate change. Such problems with current models indicate an urgent need to reassess the principles underlying the environmental controls of primary production. The global patterns of annual and maximum monthly terrestrial gross primary production (GPP) by C3 plants are explored here using a simple first-principles model based on the light-use efficiency formalism and the Farquhar model for C3 photosynthesis. The model is driven by incident photosynthetically active radiation (PAR) and remotely sensed green-vegetation cover, with additional constraints imposed by low-temperature inhibition and CO2 limitation. The ratio of leaf-internal to ambient CO2 concentration in the model responds to growing-season mean temperature, atmospheric dryness (indexed by the cumulative water deficit, Δ E) and elevation, based on an optimality theory. The greatest annual GPP is predicted for tropical moist forests, but the maximum (summer) monthly GPP can be as high, or higher, in boreal or temperate forests. These findings are supported by a new analysis of CO2 flux measurements. The explanation is simply based on the seasonal and latitudinal distribution of PAR combined with the physiology of photosynthesis. By successively imposing biophysical constraints, it is shown that partial vegetation cover – driven primarily by water shortage – represents the largest constraint on global GPP.

Sensitivity of global gross primary production to environmental drivers

2020 ◽  
Author(s):  
Wenjia Cai ◽  
Iain Colin Prentice
Keyword(s):  
Primary Production ◽  
Vegetation Cover ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Vapour Pressure Deficit ◽  
Terrestrial Ecosystems ◽  
Environmental Drivers ◽  
Generic Model ◽  
Terrestrial Plants ◽  
Green Vegetation

<p>Terrestrial Gross Primary Production (GPP), the total amount of carbon taken up by terrestrial plants, is one of the largest fluxes in the global carbon cycle – and a key process governing the capacity of terrestrial ecosystems to partly offset continuing anthropogenic CO<sub>2</sub> emissions. Accurate simulation of land carbon uptake and its response to environmental change is therefore essential for reliable future projections of the terrestrial carbon sink. However, there are still large uncertainties in the sensitivity of global GPP to environmental drivers. Here we use a recently developed and extensively tested generic model of GPP (the ‘P-model’), which uses satellite-derived green vegetation cover as an input, to simulate (a) trends in site-level GPP, as observed at eddy-covariance flux sites; (b) trends in global GPP, for comparison with independent geophysical estimates; and (c) quantitative spatial patterns of the sensitivity of grid-based GPP to green vegetation cover, vapour pressure deficit, temperature, solar radiation, soil moisture and atmospheric CO<sub>2.</sub></p>

scholarly journals Biophysical constraints on gross primary production by the terrestrial biosphere

2014 ◽  
Vol 11 (2) ◽  
pp. 3209-3240 ◽  
Author(s):  
H. Wang ◽  
I. C. Prentice ◽  
T. W. Davis
Keyword(s):  
Primary Production ◽  
Optimality Theory ◽  
Vegetation Cover ◽  
Gross Primary Production ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Water Shortage ◽  
C3 Plants ◽  
Environmental Controls ◽  
Green Vegetation

Abstract. Persistent divergences among the predictions of complex carbon cycle models include differences in the sign as well as the magnitude of the response of global terrestrial primary production to climate change. This and other problems with current models indicate an urgent need to re-assess the principles underlying the environmental controls of primary production. The global patterns of annual and maximum monthly terrestrial gross primary production (GPP) by C3 plants are explored here using a simple first-principles model based on the light-use efficiency formalism and the Farquhar model for C3 photosynthesis. The model is driven by incident photosynthetically active radiation (PAR) and remotely sensed green vegetation cover, with additional constraints imposed by low-temperature inhibition and CO2 limitation. The ratio of leaf-internal to ambient CO2 concentration in the model responds to growing-season mean temperature, atmospheric dryness (indexed by the cumulative water deficit, ΔE) and elevation, based on optimality theory. The greatest annual GPP is predicted for tropical moist forests, but the maximum (summer) monthly GPP can be as high or higher in boreal or temperate forests. These findings are supported by a new analysis of CO2 flux measurements. The explanation is simply based on the seasonal and latitudinal distribution of PAR combined with the physiology of photosynthesis. By successively imposing biophysical constraints, it is shown that partial vegetation cover – driven primarily by water shortage – represents the largest constraint on global GPP.

scholarly journals Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

2019 ◽  
Vol 147 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
Yuchu Zhao ◽  
Zhengyu Liu ◽  
Fei Zheng ◽  
Yishuai Jin
Keyword(s):  
Data Assimilation ◽  
Parameter Optimization ◽  
Real World ◽  
Climate Models ◽  
Coupled Model ◽  
Prediction Skill ◽  
Model Parameters ◽  
Real World Data ◽  
The Real ◽  
Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

Gaussian Process emulation of multi-model ice sheet and glacier projections

2021 ◽  
Author(s):  
Tamsin Edwards ◽  
Keyword(s):  
Gaussian Process ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Ice Sheet ◽  
Surface Air Temperature ◽  
Model Parameters ◽  
Gaussian Process Emulation ◽  
Model Ensembles ◽  
Global Mean

<p><strong>The land ice contribution to global mean sea level rise has not yet been predicted with ice sheet and glacier models for the latest set of socio-economic scenarios (SSPs), nor with coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects (ISMIP6 and GlacierMIP) generated a large suite of projections using multiple models, but mostly used previous generation scenarios and climate models, and could not fully explore known uncertainties. </strong></p><p><strong>Here we estimate probability distributions for these projections for the SSPs using Gaussian Process emulation of the ice sheet and glacier model ensembles. We model the sea level contribution as a function of global mean surface air temperature forcing and (for the ice sheets) model parameters, with the 'nugget' allowing for multi-model structural uncertainty. Approximate independence of ice sheet and glacier models is assumed, because a given model responds very differently under different setups (such as initialisation). </strong></p><p><strong>We find that limiting global warming to 1.5</strong>°<strong>C </strong><strong>would halve the land ice contribution to 21<sup>st</sup> century </strong><strong>sea level rise</strong><strong>, relative to current emissions pledges: t</strong><strong>he median decreases from 25 to 13 cm sea level equivalent (SLE) by 2100. However, the Antarctic contribution does not show a clear response to emissions scenario, due to competing processes of increasing ice loss and snowfall accumulation in a warming climate. </strong></p><p><strong>However, under risk-averse (pessimistic) assumptions for climate and Antarctic ice sheet model selection and ice sheet model parameter values, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 cm SLE under current policies and pledges, with the 95<sup>th</sup> percentile exceeding half a metre even under 1.5</strong>°<strong>C warming. </strong></p><p><strong>Gaussian Process emulation can therefore be a powerful tool for estimating probability density functions from multi-model ensembles and testing the sensitivity of the results to assumptions.</strong></p>

A new ensemble-based statistical methodology to verify changes in weather and climate models

2021 ◽  
Author(s):  
Christian Zeman ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Hypothesis Test ◽  
Model Development ◽  
Atmospheric Model ◽  
Statistical Hypothesis ◽  
Model Parameters ◽  
Rounding Errors ◽  
Weather And Climate

<p>Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.</p><p>Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.</p><p>We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.</p>

scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Middle Miocene ◽  
Climate Models ◽  
Global Climate ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Ice Volume ◽  
Climate Transition

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

scholarly journals Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

2021 ◽  
Vol 12 (3) ◽  
pp. 919-938
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Weidong Guo ◽  
...  
Keyword(s):  
Land Surface ◽  
Forest Canopy ◽  
Climate Models ◽  
Root Zone ◽  
Stomatal Closure ◽  
Capillary Rise ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Surface Model ◽  
The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

scholarly journals A return to large-scale features of Pliocene climate: the Pliocene Model Intercomparison Project Phase 2

2020 ◽  
Author(s):  
Alan M. Haywood ◽  
Julia C. Tindall ◽  
Harry J. Dowsett ◽  
Aisling M. Dolan ◽  
Kevin M. Foley ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Temperature Response ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Mean Value ◽  
System Response ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ~ 400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution and based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.4 and 4.7 °C relative to pre-industrial with a multi-model mean value of 2.8 °C. Annual mean total precipitation rates increase by 6 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases are 1.3 °C greater over the land than over the oceans, and there is a clear pattern of polar amplification with warming polewards of 60° N and 60° S exceeding the global mean warming by a factor of 2.4. In the Atlantic and Pacific Oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. Although there are some modelling constraints, there is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (Equilibrium Climate Sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble earth system response to doubling of CO2 (including ice sheet feedbacks) is approximately 50 % greater than ECS, consistent with results from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea-surface temperatures are used to assess model estimates of ECS and indicate a range in ECS from 2.5 to 4.3 °C. This result is in general accord with the range in ECS presented by previous IPCC Assessment Reports.

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