As an experiment, I thought I’d try posting some science instead of nonsense or mountains. From Nurture (Peter van der Sleen et al., Nature Geoscience 8, 24–28 (2015) doi:10.1038/ngeo2313):
The biomass of undisturbed tropical forests has likely increased in the past few decades1, 2, probably as a result of accelerated tree growth. Higher CO2 levels are expected to raise plant photosynthetic rates3 and enhance water-use efficiency4, that is, the ratio of carbon assimilation through photosynthesis to water loss through transpiration. However, there is no evidence that these physiological responses do indeed stimulate tree growth in tropical forests. Here we present measurements of stable carbon isotopes and growth rings in the wood of 1,100 trees from Bolivia, Cameroon and Thailand. Measurements of carbon isotope fractions in the wood indicate that intrinsic water-use efficiency in both understorey and canopy trees increased by 30–35% over the past 150 years as atmospheric CO2 concentrations increased. However, we found no evidence for the suggested concurrent acceleration of individual tree growth when analysing the width of growth rings. We conclude that the widespread assumption of a CO2-induced stimulation of tropical tree growth may not be valid.
This is a partial antidote to the CO2-is-plant-food people, but also to the ZOMG-crop-yields-are-falling people, since increased water efficiency is good. Mind you, not all plants are exactly the same, so it may not apply to the crops we care about in the circumstances we care about. Biology is complex, no?
Carbon cycle extremes during the 21st century in CMIP5 models: Future evolution and attribution to climatic drivers
While I’m here, Zscheischler et al., DOI: 10.1002/2014GL062409 is on a similar theme:
Climate extremes such as droughts and heat waves affect terrestrial ecosystems and may alter local carbon budgets. However, it still remains uncertain to what degree extreme impacts in the carbon cycle influence the carbon cycle-climate feedback both today and the near future. Here we analyze spatiotemporally contiguous negative extreme anomalies in gross primary production (GPP) and net ecosystem production (NEP) in model output of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble and investigate their future development and attribution to climatic drivers. We find that relative to the overall increase in global carbon uptake, negative extremes in GPP and NEP lose importance toward the end of the 21st century. This effect can be related to elevated CO2 concentrations and higher amounts of available water at the global scale, partially mitigating the impacts of droughts and heat waves, respectively. Overall, based on CMIP5 models, we hypothesize that terrestrial ecosystems might be more resilient against future climate extremes than previously thought. Future work will have to further scrutinize these results considering that various biological and biogeochemical feedbacks are not yet integrated within Earth system models.
And to complete the trilogy, one including our very own William Ingram:
Correcting precipitation feature location in general circulation models
There is much evidence that precipitation responses to global warming involve wet regions becoming wetter and dry regions drier. This presents challenges for the interpretation of projections from general circulation models (GCMs) which have substantial biases in the location of precipitation features. While improving GCM simulated precipitation is the most desirable solution, adaptation and mitigation decisions must be made with the models already available. Many techniques have been developed to correct biases in grid point precipitation intensities, but few have been introduced to correct for location biases. Here, we describe a new technique for correcting the spatial and seasonal location of climatological precipitation features. We design this technique to respect the geometry of the problem (spherical spatial dimensions, with cyclic seasons), while conserving either precipitation intensities, or integrated precipitation amount. We discuss the mathematical basis of the technique and investigate its behaviour in different regimes. We find that the resulting warps depend smoothly on the most influential parameter, which determines the balance between smoothness and closeness of fit. We show that the technique is capable of removing more than half the RMS error in a model’s climatology, obtaining consistently better results when conserving integrated precipitation. To demonstrate the ability of the new technique to improve simulated precipitation changes, we apply our transformations to historical anomalies and show that RMS error is reduced relative to GPCP’s anomalies by approximately 10% for both types of warp. This verifies that errors in precipitation changes can be reduced by correcting underlying location errors in a GCM’s climatology.
I don’t really approve of correcting the models, though.