Emergent constraint regarding carbon-climate feedbacks

<p>Codes for the main analyses</p&gt

Reply to: Large influence of atmospheric vapor pressure deficit on ecosystem production efficiency

ISSN:2041-172

Drivers of intermodel uncertainty in land carbon sink projections

Over the past decades, land ecosystems removed from the atmosphere approximately one-third of anthropogenic carbon emissions, highlighting the importance of the evolution of the land carbon sink for projected climate change. Nevertheless, the latest cumulative land carbon sink projections from 11 Earth system models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) show an intermodel spread of 150 Pg C (i.e., similar to 15 years of current anthropogenic emissions) for a policy-relevant scenario, with mean global warming by the end of the century below 2 degrees C relative to preindustrial conditions. We hypothesize that this intermodel uncertainty originates from model differences in the sensitivities of net biome production (NBP) to atmospheric CO2 concentration (i), to air temperature (ii), and to soil moisture (iii), as well as model differences in average conditions of air temperature (iv) and soil moisture (v). Using multiple linear regression and a resampling technique, we quantify the individual contributions of these five drivers for explaining the cumulative NBP anomaly of each model relative to the multi-model mean. We find that the intermodel variability of the contributions of each driver relative to the total NBP intermodel variability is 52.4 % for the sensitivity to temperature, 44.2 % for the sensitivity to soil moisture, 44 % for the sensitivity to CO2, 26.2 % for the average temperature, and 21.9 % for the average soil moisture. Furthermore, the sensitivities of NBP to temperature and soil moisture, particularly at tropical regions, contribute to explain 34 % to 65 % of the cumulative NBP deviations from the ensemble mean of the two models with the lowest carbon sink (ACCESS-ESM1-5 and UKESM1-0-LL) and of the two models with the highest sink (CESM2 and NorESM2-LM), highlighting the primary role of the response of NBP to interannual climate variability. Overall, this study provides in- sights on why each Earth system model projects either a low or high land carbon sink globally and across regions relative to the ensemble mean, which can focalize efforts to identify the representation of processes that lead to intermodel uncertainty.ISSN:1726-4170ISSN:1726-417

Soil moisture dominates dryness stress on ecosystem production globally

Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk.ISSN:2041-172

Revisiting assessments of ecosystem drought recovery

The time taken for ecosystems to recover from drought (drought recovery time) is critically important for the ecosystem state. However, recent literature presents contradictory conclusions on this feature: one study concludes that drought recovery time in the tropics and high northern latitudes is shortest (12 months) in these regions. Here we explore the reasons for these contradictory results and revisit assessments of drought recovery time. We find that the study period, drought identification method and recovery level definition are main factors contributing to the contradictory conclusions. Further, we emphasize that including droughts that did not decrease ecosystem production or using a period of abnormal water availability to define ecosystem recovery level can strongly bias drought recovery time estimates. Based on our refined methods, we find the drought recovery time is also longest in some tropical regions but not in high northern latitudes during 1901–2010. Our study helps to resolve the recent controversy and provides insight for future drought recovery assessments.ISSN:1748-9326ISSN:1748-931

Climate change impacts on planned supply–demand match in global wind and solar energy systems

Climate change modulates both energy demand and wind and solar energy supply but a globally synthetic analysis of supply–demand match (SDM) is lacking. Here, we use 12 state-of-the-art climate models to assess climate change impacts on SDM, quantified by the fraction of demand met by local wind or solar supply. For energy systems with varying dependence on wind or solar supply, up to 32% or 44% of non-Antarctic land areas, respectively, are projected to experience robust SDM reductions by the end of this century under an intermediate emission scenario. Smaller and more variable supply reduces SDM at northern middle-to-high latitudes, whereas reduced heating demand alleviates or reverses SDM reductions remarkably. By contrast, despite supply increases at low latitudes, raised cooling demand reduces SDM substantially. Changes in climate extremes and climate mean make size-comparable contributions. Our results provide early warnings for energy sectors in climate change adaptation.ISSN:2058-754

Spatiotemporal Characteristics of the Surface Urban Heat Island and Its Driving Factors Based on Local Climate Zones and Population in Beijing, China

The increasing degree of urbanization has continuously aggravated the surface urban heat island (sUHI) effect in China. To investigate the correlation between spatiotemporal changes of sUHI and urbanization in Beijing, land surface temperature in summer from 2000 to 2017 and the distribution of local climate zones (LCZs) in 2003, 2005, 2010, and 2017 was retrieved using remote sensing data and used to analyze the sUHI area and intensity change. The statistical method GeoDetector was utilized to investigate the explanatory ability of LCZs and population as the driving factors. The year of 2006 was identified as the main turning year for sUHI evolution. The variation the sUHI from 2000 showed first an increasing trend, and then a decreasing one. The sUHI pattern changed before and after 2009. Before 2009, the sUHI mainly increased in the suburbs, and then, the enhancement area moved to the central area. The sUHI intensity change under different LCZ conversion conditions showed that the LCZ conversion influences the sUHI intensity significantly. Based on population distribution data, we found that the relationship between population density and sUHI gets weaker with increasing population density. The result of GeoDetector indicated that the LCZ is the main factor influencing the sUHI, but population density is an important auxiliary factor. This research reveals the sUHI variation pattern in Beijing from 2000 and could help city managers plan thermally comfortable urban environments with a better understanding of the effect of urban spatial form and population density on sUHIs

Climate change impacts on planned supply–demand match in global wind and solar energy systems

Climate change modulates both energy demand and wind and solar energy supply but a globally synthetic analysis of supply–demand match (SDM) is lacking. Here, we use 12 state-of-the-art climate models to assess climate change impacts on SDM, quantified by the fraction of demand met by local wind or solar supply. For energy systems with varying dependence on wind or solar supply, up to 32% or 44% of non-Antarctic land areas, respectively, are projected to experience robust SDM reductions by the end of this century under an intermediate emission scenario. Smaller and more variable supply reduces SDM at northern middle-to-high latitudes, whereas reduced heating demand alleviates or reverses SDM reductions remarkably. By contrast, despite supply increases at low latitudes, raised cooling demand reduces SDM substantially. Changes in climate extremes and climate mean make size-comparable contributions. Our results provide early warnings for energy sectors in climate change adaptation