scholarly journals Technical Note: A simple theoretical model framework to describe plant stomatal sluggishness in response to elevated ozone concentrations

2018 ◽  
Author(s):  
Chris Huntingford ◽  
Rebecca J. Oliver ◽  
Lina M. Mercado ◽  
Stephen Sitch
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Net Primary Productivity ◽  
Model Development ◽  
Technical Note ◽  
Climate Impacts ◽  
Terrestrial Vegetation ◽  
Stomatal Response ◽  
Model Framework ◽  
Elevated Ozone

Abstract. Elevated levels of tropospheric Ozone [O3] causes damage to terrestrial vegetation, affecting leaf stomatal functioning and reducing photosynthesis. Climatic impacts under future raised atmospheric Greenhouse Gas (GHG) concentrations will also impact on the Net Primary Productivity (NPP) of vegetation, which might for instance alter viability of some crops. Together, ozone damage and climate change may adjust the current ability of terrestrial vegetation to offset a significant fraction of carbon dioxide (CO2) emissions. Climate impacts on the land surface are well studied, but arguably large-scale modelling of raised surface level [O3] effects is less advanced. To date most models representing ozone damage use either [O3] concentration or, more recently, flux-uptake related reduction of stomatal opening, estimating suppressed land-atmosphere water and CO2 fluxes. However there is evidence that for some species, [O3] damage can also cause an inertial sluggishness of stomatal response to changing surface meteorological conditions. In some circumstances e.g. droughts, this loss of stomata control can cause them to be more open than without ozone interference. The extent of this effect may be dependent on magnitude and cumulated time of exposure to raised [O3], suggesting experiments to analyze this require operation over long timescales such as full growing seasons. To both aid model development and provide empiricists with a system on to which measurements can be mapped, we present a parameter-sparse framework specifically designed to capture sluggishness. This contains a single time-delay parameter τO3, characterising the timescale for stomata to catch up with the level of opening they would have with- out damage. The larger the value of this parameter, the more sluggish the modelled stomatal response. Through variation of τO3, we find it is possible to have qualitatively similar responses to factorial experiments with and without raised [O3], when comparing to measurement timeseries presented in the literature. This low-parameter approach lends itself to the inclusion of ozone-induced inertial effects being incorporated in the terrestrial vegetation component of Earth System Models (ESMs).

scholarly journals Technical note: A simple theoretical model framework to describe plant stomatal “sluggishness” in response to elevated ozone concentrations

2018 ◽  
Vol 15 (17) ◽  
pp. 5415-5422 ◽  
Author(s):  
Chris Huntingford ◽  
Rebecca J. Oliver ◽  
Lina M. Mercado ◽  
Stephen Sitch
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Net Primary Productivity ◽  
Model Development ◽  
Technical Note ◽  
Climate Impacts ◽  
Terrestrial Vegetation ◽  
Stomatal Response ◽  
Model Framework ◽  
Elevated Ozone

Abstract. Elevated levels of tropospheric ozone, O3, cause damage to terrestrial vegetation, affecting leaf stomatal functioning and reducing photosynthesis. Climatic impacts under future raised atmospheric greenhouse gas (GHG) concentrations will also impact on the net primary productivity (NPP) of vegetation, which might for instance alter viability of some crops. Together, ozone damage and climate change may adjust the current ability of terrestrial vegetation to offset a significant fraction of carbon dioxide (CO2) emissions. Climate impacts on the land surface are well studied, but arguably large-scale modelling of raised surface level O3 effects is less advanced. To date most models representing ozone damage use either O3 concentration or, more recently, flux-uptake-related reduction of stomatal opening, estimating suppressed land–atmosphere water and CO2 fluxes. However there is evidence that, for some species, O3 damage can also cause an inertial “sluggishness” of stomatal response to changing surface meteorological conditions. In some circumstances (e.g. droughts), this loss of stomata control can cause them to be more open than without ozone interference. To both aid model development and provide empiricists with a system on to which measurements can be mapped, we present a parameter-sparse framework specifically designed to capture sluggishness. This contains a single time-delay parameter τO3, characterizing the timescale for stomata to catch up with the level of opening they would have without damage. The larger the value of this parameter, the more sluggish the modelled stomatal response. Through variation of τO3, we find it is possible to have qualitatively similar responses to factorial experiments with and without raised O3, when comparing to reported measurement time series presented in the literature. This low-parameter approach lends itself to the inclusion of ozone-induced inertial effects being incorporated in the terrestrial vegetation component of Earth system models (ESMs).

Local Regimes of Atmospheric Variability: A Case Study of Southern California

2006 ◽  
Vol 19 (17) ◽  
pp. 4308-4325 ◽  
Author(s):  
Sebastien Conil ◽  
Alex Hall
Keyword(s):  
Spatial Structure ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Spatial Scales ◽  
Surface Wind ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Atmospheric Variability ◽  
Composite Surface

Abstract The primary regimes of local atmospheric variability are examined in a 6-km regional atmospheric model of the southern third of California, an area of significant land surface heterogeneity, intense topography, and climate diversity. The model was forced by reanalysis boundary conditions over the period 1995–2003. The region is approximately the same size as a typical grid box of the current generation of general circulation models used for global climate prediction and reanalysis product generation, and so can be thought of as a laboratory for the study of climate at spatial scales smaller than those resolved by global simulations and reanalysis products. It is found that the simulated circulation during the October–March wet season, when variability is most significant, can be understood through an objective classification technique in terms of three wind regimes. The composite surface wind patterns associated with these regimes exhibit significant spatial structure within the model domain, consistent with the complex topography of the region. These regimes also correspond nearly perfectly with the simulation’s highly structured patterns of variability in hydrology and temperature, and therefore are the main contributors to the local climate variability. The regimes are approximately equally likely to occur regardless of the phase of the classical large-scale modes of atmospheric variability prevailing in the Pacific–North American sector. The high degree of spatial structure of the local regimes and their tightly associated climate impacts, as well as their ambiguous relationship with the primary modes of large-scale variability, demonstrate that the local perspective offered by the high-resolution model is necessary to understand and predict the climate variations of the region.

scholarly journals Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network

2014 ◽  
Vol 11 (10) ◽  
pp. 2661-2678 ◽  
Author(s):  
M. Balzarolo ◽  
S. Boussetta ◽  
G. Balsamo ◽  
A. Beljaars ◽  
F. Maignan ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Meteorological Data ◽  
Model Development ◽  
Vapour Pressure Deficit ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Simulation Performance ◽  
Large Scale Simulations

Abstract. This paper reports a comparison between large-scale simulations of three different land surface models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 eddy covariance (EC) flux tower sites in Europe. The results show that the three simulations have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three simulations have difficulties capturing the seasonality of Mediterranean and sub-tropical biomes, characterized by dry summers. This reduced simulation performance is also reflected in deficiencies in diagnosed light-use efficiency (LUE) and vapour pressure deficit (VPD) dependencies compared to observations. Shortcomings in the forcing data may also play a role. These results indicate that more research is needed on the LUE and VPD functions for Mediterranean and sub-tropical biomes. Finally, this study highlights the importance of correctly representing phenology (i.e. leaf area evolution) and management (i.e. rotation–irrigation for cropland, and grazing–harvesting for grassland) to simulate the carbon dynamics of European ecosystems and the importance of ecosystem-level observations in model development and validation.

Progressive Midlatitude Afforestation: Impacts on Clouds, Global Energy Transport, and Precipitation

2016 ◽  
Vol 29 (15) ◽  
pp. 5561-5573 ◽  
Author(s):  
Marysa M. Laguë ◽  
Abigail L. S. Swann
Keyword(s):  
Vegetation Cover ◽  
Land Surface ◽  
Large Scale ◽  
Forest Cover ◽  
Energy Transport ◽  
Climate Impacts ◽  
Heat Fluxes ◽  
Tree Cover ◽  
Climate Response ◽  
Cloud Feedbacks

Abstract Vegetation influences the atmosphere in complex and nonlinear ways, such that large-scale changes in vegetation cover can drive changes in climate on both local and global scales. Large-scale land surface changes have been shown to introduce excess energy to one hemisphere, causing a shift in atmospheric circulation on a global scale. However, past work has not quantified how the climate response scales with the area of vegetation. Here, the response of climate to linearly increasing the area of forest cover in the northern midlatitudes is systematically evaluated. This study shows that the magnitude of afforestation of the northern midlatitudes determines the local climate response in a nonlinear fashion, and the authors identify a threshold in vegetation-induced cloud feedbacks—a concept not previously addressed by large-scale vegetation manipulation experiments. Small increases in tree cover drive compensating cloud feedbacks, while latent heat fluxes reach a threshold after sufficiently large increases in tree cover, causing the troposphere to warm and dry, subsequently reducing cloud cover. Increased absorption of solar radiation at the surface is driven by both surface albedo changes and cloud feedbacks. This study shows how atmospheric cross-equatorial energy transport changes as the area of afforestation is incrementally increased. The results highlight the importance of considering both local and remote climate effects of large-scale vegetation change and explore the scaling relationship between changes in vegetation cover and resulting climate impacts.

scholarly journals Analysis and Reduction of Systematic Errors through a Seamless Approach to Modeling Weather and Climate

2010 ◽  
Vol 23 (22) ◽  
pp. 5933-5957 ◽  
Author(s):  
G. M. Martin ◽  
S. F. Milton ◽  
C. A. Senior ◽  
M. E. Brooks ◽  
S. Ineson ◽  
...  
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Full Range ◽  
Model Development ◽  
Model Performance ◽  
Systematic Errors ◽  
Wide Range

Abstract The reduction of systematic errors is a continuing challenge for model development. Feedbacks and compensating errors in climate models often make finding the source of a systematic error difficult. In this paper, it is shown how model development can benefit from the use of the same model across a range of temporal and spatial scales. Two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions. Each of these errors affects the model performance on time scales ranging from a few days to several decades. In both cases, the characteristics of the long-time-scale errors are found to develop during the first few days of simulation, before any large-scale feedbacks have taken place. The ability to compare the model diagnostics from the first few days of a forecast, initialized from a realistic atmospheric state, directly with observations has allowed physical deficiencies in the physical parameterizations to be identified that, when corrected, lead to improvements across the full range of time scales. This study highlights the benefits of a seamless prediction system across a wide range of time scales.

scholarly journals Description and Validation of the Simple, Efficient, Dynamic, Global, Ecological Simulator (SEDGES v.1.0)

2017 ◽  
Author(s):  
Pablo Paiewonsky ◽  
Oliver Elison Timm
Keyword(s):  
Primary Productivity ◽  
Land Surface ◽  
Large Scale ◽  
Net Primary Productivity ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Bare Soil ◽  
Relative Advantage ◽  
Coupling Scheme ◽  
Area Index

Abstract. In this paper, we present a simple vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare soil albedo. We evaluate the model's performance by running it using a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this set up, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large scale vegetation and land surface characteristics under non-present day conditions.

A CLASSIFICATION INDICES-BASED MODEL FOR NET PRIMARY PRODUCTIVITY (NPP) AND POTENTIAL PRODUCTIVITY OF VEGETATION IN CHINA

2012 ◽  
Vol 05 (03) ◽  
pp. 1260009 ◽  
Author(s):  
HUILONG LIN ◽  
JUN ZHAO ◽  
TIANGANG LIANG ◽  
JAN BOGAERT ◽  
ZHENQING LI
Keyword(s):  
Primary Productivity ◽  
Large Scale ◽  
Net Primary Productivity ◽  
Global Climate ◽  
Terrestrial Ecosystem ◽  
Terrestrial Vegetation ◽  
Moisture Index ◽  
Potential Productivity ◽  
Climate Conditions ◽  
Factors Affecting

Net Primary Productivity (NPP) is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate-vegetation interaction is the basis for research on the responses of terrestrial ecosystem to global change and mainly comprises two important components: climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0°C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It provides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China's position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China's commitment of reducing greenhouse gases.

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