Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

This lecture provides a critical analysis of drought indices, emphasizing their role in evaluating drought severity while addressing the challenges associated with their application. It highlights the inherent complexity of drought assessment, given the multifaceted nature of drought phenomena, the various types of drought, and the intricate mechanisms underlying their development. A central focus is the distinction between drought and aridity, as well as between drought metrics and indices—concepts that are frequently misunderstood or conflated.Particular attention is given to atmospheric drought indices, especially those incorporating atmospheric evaporative demand (AED). These indices are crucial for assessing water stress but have faced criticism for certain limitations. One notable issue is the "index-impact gap," where atmospheric drought indices often indicate more severe droughts than those reflected in hydrological and ecological metrics derived from Earth System Models (ESMs), particularly in future climate scenarios. Atmospheric indices do not directly account for soil moisture or vegetation dynamics. Nonetheless, AED reflects atmospheric conditions rather than direct water reservoirs and fluxes, making AED-based indices valuable for understanding atmospheric drivers of drought. This value is reinforced by AED's critical role in intensifying drought through increased evaporation, heightened plant water stress, and reduced photosynthesis.The lecture further focuses into the uncertainties inherent in ESM projections of ecological and hydrological variables, such as soil moisture and runoff. These uncertainties arise because ESMs often underestimate drought severity due to challenges in simulating complex hydrological and physiological processes. The difficulties stem from limitations in modelling plant physiology, water cycles, and ecosystem responses, compounded by biases in key variables such as evapotranspiration. While ESM outputs are valuable for drought assessments, relying exclusively on them risks producing misleading conclusions.This issue connects with the role of rising atmospheric CO₂ concentrations, a factor commonly incorporated into ESM simulations, which adds another layer of complexity. Elevated CO₂ levels can enhance plant water-use efficiency and photosynthesis but also introduce uncertainties regarding their impacts on evapotranspiration and soil moisture. These dynamics generate complex feedbacks with AED and other variables, further complicating drought severity assessments, particularly in future ESM simulations.To address these challenges, the lecture advocates for an integrated approach that combines atmospheric drought indices with hydrological and ecological metrics. Such an approach ensures that the intensifying role of AED under global warming is neither overlooked nor overstated, thereby improving the accuracy of drought assessments, especially in the context of future climate scenarios.

Global climate and the concentration of atmospheric carbon dioxide (CO2) are correlated over recent glacial cycles. The combination of processes responsible for a rise in atmospheric CO2 at the last glacial termination (23,000 to 9,000years ago), however, remains uncertain. Establishing the timing and rate of CO2 changes in the past provides critical insight into the mechanisms that influence the carbon cycle and helps put present and future anthropogenic emissions in context. Here we present CO2 and methane (CH4) records of the last deglaciation from a new high-accumulation West Antarctic ice core with unprecedented temporal resolution and precise chronology. We show that although low-frequency CO2 variations parallel changes in Antarctic temperature, abrupt CO2 changes occur that have a clear relationship with abrupt climate changes in the Northern Hemisphere. A significant proportion of the direct radiative forcing associated with the rise in atmospheric CO2 occurred in three sudden steps, each of 10 to 15 parts per million. Every step took place in less than two centuries and was followed by no notable change in atmospheric CO2 for about 1,000 to 1,500years. Slow, millennial-scale ventilation of Southern Ocean CO2-rich, deep-ocean water masses is thought to have been fundamental to the rise in atmospheric CO2 associated with the glacial termination, given the strong covariance of CO2 levels and Antarctic temperatures. Our data establish a contribution from an abrupt, centennial-scale mode of CO2 variability that is not directly related to Antarctic temperature. We suggest that processes operating on centennial timescales, probably involving the Atlantic meridional overturning circulation, seem to be influencing global carbon-cycle dynamics and are at present not widely considered in Earth system models.

This study provides a global analysis of the relationship between drought metrics obtained from several climatic, hydrologic and ecological variables in a climate change framework using CMIP6 model data. A comprehensive analysis of the evolution of drought severity on a global scale is carried out for the historical experiment (1850–2014) and for future simulations under a high emissions scenario (SSP5‐8.5). This study focuses on comparing trends in the magnitude and duration of drought events according to different standardized indices over the world land‐surface area. The spatial and temporal relationship between the different drought indices on a global scale was also evaluated. Overall, there is a fairly large consensus among models and drought metrics in pointing to drought increase in southern North America, Central America, the Amazon region, the Mediterranean, southern Africa and southern Australia. Our results show important spatial differences in drought projections, which are highly dependent on the drought metric employed. While a strong relationship between climatic indices was evident, climatic and ecological drought metrics showed less dependency over both space and time. Importantly, our study demonstrates uncertainties in future projections of drought trends and their interannual variability related to the relationship among indices, stressing the importance of coherent climatic, hydrological and plant physiological patterns when analyzing CMIP6 model simulations of droughts under a warming climate scenario.

Differentiated responses of plant water use regulation to drought in Robinia pseudoacacia plantations on the Chinese Loess Plateau

A perturbed physics Hadley Centre climate model ensemble was used to study changes in drought on doubling atmospheric CO2. The drought metrics analyzed were based on 1) precipitation anomalies, 2) soil moisture anomalies, and 3) the Palmer drought severity index (PDSI). Drought was assumed to occur 17% of the time under single CO2. On doubling CO2, in general, PDSI drought occurs more often than soil moisture drought, which occurs more often than precipitation drought. This paper explores the relative sensitivity of each drought metric to changes in the main drivers of drought, namely precipitation and available energy. Drought tends to increase when the mean precipitation decreases, the mean available energy increases, the standard deviation of precipitation increases, and the standard deviation of available energy decreases. Simple linear approximations show that the sensitivity of drought to changes in mean precipitation is similar for the three different metrics. However, the sensitivity of drought to changes in the mean available energy (which is projected to increase under increased atmospheric CO2) is highly dependent on metric: with PDSI drought the most sensitive, soil moisture less sensitive, and precipitation independent of available energy. Drought metrics are only slightly sensitive to changes in the variability of the drivers. An additional driver of drought is the response of plants to increased CO2. This process reduces evapotranspiration and increases soil moisture, and generally causes less soil moisture drought. In contrast, the associated increase in available energy generally causes an increase in PDSI drought. These differing sensitivities need to be taken into consideration when developing adaptation strategies.

In drylands, water‐limited regions that cover ~40% of the global land surface, ecosystems are primarily controlled by access to soil moisture and exposure to simultaneously hot and dry conditions. Quantifying ecologically relevant environmental metrics is difficult in drylands because the response of vegetation to moisture and temperature conditions is not easily explained solely by climate‐based metrics. To address this knowledge gap, we developed and examined 27 climate and ecological drought metrics across dryland areas of the western United States. Included in the 27 metrics is a suite of 19 largely new “ecological drought metrics” that are designed to quantify multiple aspects of environmental limitation in drylands, including overall growing conditions, seasonal fluctuations, seasonal moisture timing, exposure to extreme drought and recruitment potential for perennial plants. To quantify these metrics, we simulated water balance pools and fluxes of daily soil moisture at multiple depths with historical weather from 1970 to 2010 using the SOILWAT2 ecosystem water balance model. We assessed the relationships among these metrics and their spatial and temporal patterns. We found that the inclusion of ecological drought metrics substantially increased the dimensionality of the climate metrics dataset; the number of independent variables needed to explain 90% of the variance in the dataset increased with the addition of ecological drought metrics. Spatial patterns in overall growing conditions represented well‐known differences among ecoregions, for example, high temperatures and low precipitation in the southwest and cool temperatures and greater precipitation in the northeast. Seasonal fluctuation in soil water availability (SWA) was greatest in the southwest (Mojave Desert), whereas fluctuation in climatic water deficit (CWD) was greatest in the northwest (northern Great Basin and Columbia Plateau). Seasonal timing of moisture also differed among metrics; the timing of wet degree days (WDD), the timing of SWA and the timing of CWD were only weakly related to seasonal timing of precipitation. Plant recruitment metrics varied strongly across western drylands. In the Great Plains, recruitment events occurred more frequently and lasted longer than in the intermountain regions, where recruitment events were comparatively rare and short. These ecological drought metrics provide new insight into patterns of soil moisture and temperature that shape the structure and function of dryland ecosystems. The metrics will be useful for assessing the potential impact of climate change on dryland ecosystems and developing adaptive resource management strategies to sustain dryland ecosystem services in a changing world.

Increasing heat and aridity in coming decades is expected to negatively impact tree growth and threaten forest sustainability in dry areas. Maintaining low stand density has the potential to mitigate the negative effects of increasingly severe droughts by minimizing competitive intensity. However, the direct impact of stand density on the growing environment (i.e. soil moisture), and the specific drought metrics that best quantify that environment, are not well explored for any forest ecosystem. We examined the relationship of varying stand density (i.e. basal area) on soil moisture and stand‐level growth in a long‐term (multi‐decadal), ponderosa pine Pinus ponderosa, forest management experiment. We accounted for the influence of stand‐level density on moisture availability by measuring and modelling soil moisture using an ecosystem water balance model. To quantify the growing environment, we developed metrics of ecological drought that integrate the influence of moisture availability in the soil with moisture demand by the atmosphere. We paired these results with stand‐level dendrochronological data, avoiding the potential bias introduced from individual tree‐based assessments, and used critical climate period analysis to identify the timing and duration of these drought metrics that most relate to forest growth. We found that stand‐level growth is highly responsive to the combination of high temperature and low soil moisture. Growth in all stands was negatively related to temperature and positively related to moisture availability, although the sensitivity of growth to those conditions varied among stand density treatments. Growth enhancement during cool years is greatest in low density stands. In addition, low density stands displayed substantially higher long‐term average growth than higher density stands and maintained higher growth even when temperatures were high. Growth in low density stands also increased more than higher density stands in response to greater long‐term moisture availability. Synthesis and applications. We quantified the influence of stand‐level density on the environmental conditions that determine tree growth and related forest growth to patterns of moisture supply and demand. Our drought metrics, and analytical approach for quantifying drought impacts on forest growth, are a novel approach for assessing forest vulnerability to drought under climate change. These results provide new perspective on the potential for density management to mitigate drought stress and maintain forest stand growth during and after drought events in water‐limited forests.

<p>The controls of a climate metric, the Transient Climate Response to cumulative carbon Emissions (TCRE), are assessed using a suite of Earth system models, 9 CMIP6 and 7 CMIP5, following an annual 1% rise in atmospheric CO2 over 140 years. The TCRE is interpreted in terms of a product of three dependences: (i) a thermal response involving the surface warming dependence on radiative forcing (including the effects of physical climate feedbacks and planetary heat uptake), (ii) a radiative response involving the radiative forcing dependence on changes in atmospheric carbon and (iii) a carbon response involving the airborne fraction (involving terrestrial and ocean carbon uptake). The near constancy of the TCRE is found to result primarily from a compensation between two factors: (i) the thermal response strengthens  in time from more surface warming per radiative forcing due to a strengthening in surface warming from short-wave cloud feedbacks and a declining effectiveness of ocean heat uptake, while  (ii) the radiative response weakens in time due to a saturation in the radiative forcing with increasing atmospheric carbon. This near constancy of the TCRE at least in complex Earth system models appears to be rather fortuitous given the competing effects of physical climate feedbacks, saturation in radiative forcing, changes in ocean heat uptake and changes in terrestrial and ocean carbon uptake.</p><p>Intermodel differences in the TCRE are mainly controlled by the thermal response, which arise through large differences in physical climate feedbacks that are only partly compensated by smaller differences in ocean heat uptake. The other contributions to the TCRE from the radiative and carbon responses are of comparable importance to the contribution from the thermal response on timescales of 50 years and longer for our subset of CMIP5 models, and 100 years and longer for our subset of CMIP6 models.</p><p> </p>

Modern precipitation over northeastern (NE) South America is strongly controlled by the seasonal meridional migration of the Intertropical Convergence Zone (ITCZ). Ample evidence from the Northern Hemisphere suggests a mid‐ to late Holocene southward migration of the ITCZ. Such a shift would be expected to increase precipitation over semi‐arid northern NE Brazil (Southern Hemisphere). However, the most robust precipitation record from northern NE Brazil shows a drying trend throughout the Holocene. Here, we address this issue presenting a high‐temporal resolution reconstruction of precipitation over northern NE Brazil based on data from a marine sediment core, together with analyses of mid‐ and late Holocene simulations performed with the fully coupled climate model FGOALS‐s2. Both, our data and the climate model simulations show a decrease in precipitation over northern NE Brazil from the mid‐ to the late Holocene. The model outputs further indicate a latitudinal contraction of the seasonal migration range of the ITCZ that, together with an intensification of the regional Walker circulation, were responsible for the mid‐ to late Holocene changes in precipitation over NE South America. Our results reconcile apparently conflicting precipitation records and climate mechanisms used to explain changes in precipitation over NE South America.

<p>This paper addresses how large-scale terrestrial water cycling is represented in the land surface schemes of Earth System Models (ESMs). Good representation is essential, for example in regional planning for climate change adaptation and in preparation for hydro-climatic extremes that have recently set records world-wide in devastating consequences for societies and deaths of thousands of people. ESMs provide simulations and projections for the climate system and its interactions with the terrestrial hydrological cycle, and are widely used to study and prepare for associated impacts of climate change. However, the reliability of ESMs is unclear with regard to their representation of large-scale terrestrial hydrology and its changes and interactions between its key variables‎. Despite being crucial for model realism, analysis of co-variations among terrestrial hydrology variables is still largely missing in ESM performance evaluations. To bridge this research gap, we have studied and identified large-scale co-variation patterns between soil moisture (SM) and the main freshwater fluxes of runoff (R), precipitation (P), and evapotranspiration (ET) from observational data and across 6405 hydrological catchments in different parts and climates of the world. Furthermore, we have compared the identified observation-based relationships with those emerging from ESMs and reanalysis products. Our results show that the most strongly correlated freshwater variables based on observational data are also the most misrepresented hydrological patterns in ESMs and reanalysis simulations. In particular, we find SM and R to have the generally strongest large-scale correlations according to the observation-based data, across the numerous studied catchments with widely different hydroclimatic characteristics. Compared to the SM-R correlation signals, the observation-based correlations are overall weaker for the commonly expected closer dependencies of: R on P; ET on P; SM on P; and ET on SM. Nevertheless, this strongest SM-R correlation and the P-R correlation are the most misrepresented hydrological patterns in reanalysis products and ESMs. Our results also show that ESM outputs can perform relatively well in simulating individual hydrological variables, while exhibiting essential inconsistencies in simulated co-variations between variables. Such investigations of large-scale terrestrial hydrology representation by ESMs can enhance our understanding of fundamental ESM biases and uncertainties while providing important insights for systematic ESM improvement with regard to the large-scale hydrological cycling over the world’s continents and regional land areas.</p>

The increase in vegetation productivity in India (net primary productivity; NPP) has been observed in recent decades; however, substantial uncertainty exists about the continued strength of these land carbon sinks under climate change. The enhanced NPP is driven by the strong positive carbon-concentration feedback (CO2 fertilization effect; CFE), but the temporal dynamics of this feedback are unclear. Using the carbon fluxes from the multiple Earth System Models (ESMs) of Coupled Model Inter-comparison Project (CMIP6), we showed an increasing trend in NPP would continue under climate change with projections of NPP to 2.00 ± 0.12 PgCyr-1 (25% increase) during 2021-2049, 2.36 ± 0.12 PgCyr-1 (18% increase) during 2050-2079, and 2.67 ± 0.07 PgCyr-1 (13% increase) during 2080-2099 in Indian tropic forests under SSP585 scenario. This suggests a significant decline in the growth rate of NPP in future periods. To understand the feedbacks that drive the NPP increase, we analyzed the relative effects of CFE and warming. We compared the simulations from the biogeochemical coupled model (BGC) from ESMs, which exclude the warming effects, with the fully coupled model, which includes both CFE and warming effects. The BGC model projected a 74.7% increase in NPP by the end of the century, significantly higher than the 55.9% increase projected by the fully coupled model. This shows that the consistent increase in the NPP was associated with the rise in atmospheric CO2. More importantly, results reveal that the decrease in the growth rate of NPP was due to the decline in the contribution of CFE across the different vegetations at a rate of -0.62% 100 ppm-1. Such a decline could be attributed to nutrient limitation, negative responses to high temperatures, droughts, heat waves, etc. Additionally, statistically significant shifts in the strength of carbon sinks (at a rate of -1.15% per decade) were identified in abating anthropogenic CO2 emissions. These shifts in land carbon sinks can potentially exacerbate global warming and impose additional challenges on our collective efforts to meet climate policy targets.

Soil moisture (SM) is an important variable in mediating the land-atmosphere interactions. Earth System Models (ESMs) are the key tools for predicting the response of SM to future climate change. Many ESMs provide outputs for SM; however, the estimated SM accuracy from different ESMs varies geographically as each ESM has its advantages and limitations. This study aimed to develop a merged SM product with improved accuracy and spatial resolution in China for 2015-2100 through data fusion of 25 ESMs with a deep-learning (DL) method. A DL model that can simultaneously perform data fusion and spatial downscaling was used to analyze SM’s future trend in China. Through the model, monthly SM data in four future scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) from 2015 to 2100, with a high resolution at 0.25°, was obtained. The evaluation metrics include mean absolute error (MAE), root mean square difference (RMSD), unbiased root mean square difference (ubRMSD), and coefficient of correlation (r). The evaluation results showed that our merged SM product is significantly better than each of the ESMs and the ensemble mean of all ESMs in terms of accuracy and spatial distribution. In the temporal dimension, the merged product is equivalent to the original data after deviation correction and equivalent to reconstructing the fluctuation of the whole series in a high error area. By further analyzing the spatiotemporal patterns of SM with the merged product in China, we found that northeast China will become wetter whereas South China will become drier. Northwest China and the Qinghai-Tibet Plateau would change from wetting to drying under a medium emission scenario. From the temporal scale of the results, the rate of SM variations is accelerated with time in the future under different scenarios. This study demonstrates the feasibility and effectiveness of the proposed procedure for simultaneous data fusion and spatial downscaling to generate improved SM data. The merged data have great practical and scientific implications.

We examine the intensity, duration, and physical drivers of Northern Hemisphere summer heat extremes in observations, reanalyses, CMIP6 models, and prescribed sea surface temperature (SST) simulations representing historical- and future-projected climates. Extremes are defined using a 90th percentile anomaly defined relative to a 29-day × 11-yr running mean to examine how the tail of temperature anomaly distributions changes in projections. Models generally capture the observed regional variations of intensity and duration. The magnitude of 90th percentile temperature anomalies shows a generally positive meridional gradient with some zonal variation but with warm biases over eastern India and southern North America. Both the reanalysis and climate model simulations exhibit positive biases in the duration of heat extremes in regions where the lowest model level temperature budget shows that diabatic effects dominate: Mexico extending through Central America, northeastern South America, and India. By investigating both prescribed SST forced by observations and coupled ocean simulations, heat extreme biases do not seem to be SST driven. In the warming simulations, projections under medium [shared socioeconomic pathway (SSP) 2–4.5] and high emission (SSP5–8.5) scenarios for late twenty-first century demonstrate sign change agreement for more intense anomalies over the Southeast United States, the Sahel and central Africa, and polar regions, along with weaker anomalies over Greenland brought on by melting ice. In terms of duration, the models have lesser agreement, likely due to internal variability, but nonetheless project increased duration over Northwest and Southeast United States and a reduction in northwest Canada and northern Africa.

Traits such as transpiration efficiency (TE) that are influenced by plant water use can be used to characterise the adaptability of crops to specific growth environments. TE is defined as the amount of biomass produced per unit of water used, and can ensure continued crop production in drought-prone regions. Where TE is associated with reduced use of soil water during the vegetative growth phase, water availability during grain filling may be greater, which can delay the onset of drought stress and increase grain yield under water-limited conditions. This may become even more pertinent with predicted increases in severity and frequency of droughts with climate change. The aims of this study were to firstly dissect TE into its leaf-level physiological components to better understand the effects of genetic variation in these components on TE in sorghum. Secondly, to examine whether TE responses observed under well-watered conditions were preserved under drought, and whether transpiration response was an adaptive response to drought. Twenty-seven genotypes were screened for TE under well-watered conditions using a fully automated lysimetry platform to obtain accurate plant water use data. To determine whether variation in TE among these genotypes was associated with differences in maximum photosynthesis (Amax) or leaf conductance (g) we measured the net carbon assimilation rate of the second last fully expanded leaf at high light intensity, using an infrared gas analyser, and leaf water flux was measured using a porometer, as a proxy for conductance. Genotypic variation in TE among the sorghum germplasm used was mainly associated with differences in the response of transpiration rates to vapour pressure deficit (VPD). Genotypes with low transpiration rates per unit green leaf area (T/GLA) tended to have high TE. Variation in Amax explained some of the differences in TE that could not be explained by T/GLA and may have been a result of mechanisms associated with differences in biochemical pathways that affect the efficiency of conversion of CO2 into photosynthate. While drought tended to increase TE, genotypic variation in TE was largely conserved. However, the response of transpiration rates to drought stress differed across genotypes, with some genotypes showing reduced T/GLA under drought when VPD was high, whereas others did not. These contrasting responses were associated with differences in stomatal responses to drought stress, such that some genotypes were better able to conserve water under drought stress than others. This adaptive response was not related to TE per se and may have important implications for adaptation to drought stress. Hence, the phenotyping of sorghum lines using the associated physiological traits underpinning TE differences is beneficial in identifying traits that may support growth in certain environments and can optimise grain yield production under water-limited conditions.

Abstract. The terrestrial biosphere absorbs about one third of anthropogenic CO2 emissions, thereby significantly slowing human-induced climate change. Its capacity to act as a carbon sink strongly depends on climate conditions, particularly soil moisture (SM), which can constrain plant growth and amplify land–atmosphere feedbacks. Therefore, accurately capturing these effects in Earth System Models (ESMs) is critical. Using dedicated experiments of the Land Feedback Intercomparison Project (LFMIP, an experiment within the Land Surface, Snow, and Soil Moisture Model Intercomparison Project, LS3MIP) from the latest generation of ESMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we show that projected SM changes substantially reduce the land carbon sink by the end of the century (2070–2099). This reduction is mainly driven by SM variability, highlighting the importance of SM extremes, which are projected to become more frequent and intense under climate change. Our results confirm those of the previous model generation based on the Global Land–Atmosphere Climate Experiment-Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5). The results show that the strong negative impact of SM changes on the land carbon sink shown for GLACE-CMIP5 is less severe in LFMIP. A more in-depth analysis reveals that this is due at least in part to the specific ESM sampling of the respective experiments, with participating ESMs from CMIP5 generally showing a stronger drying trend. Despite agreement on the negative impact of SM on the land carbon sink in most tropical and mid-latitude ecosystems in both sets of multi-model experiments, there are large intermodel differences in the projected magnitudes. As SM can influence land carbon uptake both directly and indirectly via land–atmosphere coupling, we conduct a contribution analysis on the impact of direct and indirect SM effects on carbon uptake, which reveals that SM–atmosphere interaction dominate SM-induced changes globally. However, models show disagreement on the magnitude of these effects. Intermodel differences arise mainly from varying sensitivities of GPP to SM-related direct and indirect effects, suggesting that differences likely stem from varying representations of water-stress related processes across ESMs. Our findings highlight SM–atmosphere coupling as a critical factor for future land carbon uptake. Improving the representation of water stress processes, plant hydraulics, and vegetation characteristics in ESMs is essential for reducing uncertainty in projections. Maintaining and possibly extending the experimental setup to a larger set of models in future CMIP generations will be key to advancing our understanding of SM-carbon interactions and consequently of the evolution of the land carbon sink under human-induced climate change.