Increasingly negative tropical water-interannual CO2 growth rate coupling.

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks.

Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage.

Land ecosystems absorb on average 30 per cent of anthropogenic carbon dioxide (CO2) emissions, thereby slowing the increase of CO2 concentration in the atmosphere1. Year-to-year variations in the atmospheric CO2 growth rate are mostly due to fluctuating carbon uptake by land ecosystems1. The sensitivity of these fluctuations to changes in tropical temperature has been well documented2-6, but identifying the role of global water availability has proved to be elusive. So far, the only usable proxies for water availability have been time-lagged precipitation anomalies and drought indices3-5, owing to a lack of direct observations. Here, we use recent observations of terrestrial water storage changes derived from satellite gravimetry7 to investigate terrestrial water effects on carbon cycle variability at global to regional scales. We show that the CO2 growth rate is strongly sensitive to observed changes in terrestrial water storage, drier years being associated with faster atmospheric CO2 growth. We demonstrate that this global relationship is independent of known temperature effects and is underestimated in current carbon cycle models. Our results indicate that interannual fluctuations in terrestrial water storage strongly affect the terrestrial carbon sink and highlight the importance of the interactions between the water and carbon cycles.

Correction to: A novel method for assessing climate change impacts in ecotron experiments.

The article was published bearing a typographical error to the second author name listed. The author group regret the error and the name should be referenced and credited as Jakob Zscheischler and not the former.

A novel method for assessing climate change impacts in ecotron experiments.

Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change.

Soil Moisture Effects on Afternoon Precipitation Occurrence in Current Climate Models.

Soil moisture-precipitation feedbacks in a large ensemble of global climate model simulations are evaluated. A set of three metrics are used to assess the sensitivity of afternoon rainfall occurrence to morning soil moisture in terms of their spatial, temporal, and heterogeneity characteristics. Positive (negative) spatial feedback indicates that the afternoon rainfall occurs more frequently over wetter (drier) land surface than its surroundings. Positive (negative) temporal feedback indicates preference over temporally wetter (drier) conditions, and positive (negative) heterogeneity feedback indicates preference over more spatially heterogeneous (homogeneous) soil moisture conditions. We confirm previous results highlighting a dominantly positive spatial feedback in the models as opposed to observations. On average, models tend to agree better with observations for temporal and heterogeneity feedback characteristics, although intermodel variability is largest for these metrics. The collective influence of the three feedbacks suggests that they may lead to more localized precipitation persistence in models than in observations.

Observational Constraints Reduce Likelihood of Extreme Changes in Multidecadal Land Water Availability.

Future changes in multidecadal mean water availability, represented as the difference between precipitation and evapotranspiration, remain highly uncertain in ensemble simulations of climate models. Here we identify a physically meaningful relationship between present-day mean precipitation and projected changes in water availability. This suggests that the uncertainty can be reduced by conditioning the ensemble on observed precipitation, which is achieved through a novel probabilistic approach that uses Approximate Bayesian Computation. Comparing the constrained with the full ensemble shows that projected extreme changes in water availability, denoted by the 5th and 95th percentile of the full ensemble, are less likely over 73% and 63% of land, respectively. There is also an overall shift toward wetter conditions over Europe, Southern Africa, and Western North America, whereas the opposite occurs over the Amazon. Finally, the constrained projections support adaptation to shifts in regional water availability as imposed by different global warming levels.

Anthropogenic climate change has influenced global river flow seasonality.

Riverine ecosystems have adapted to natural discharge variations across seasons. However, evidence suggesting that climate change has already impacted magnitudes of river flow seasonality is limited to local studies, mainly focusing on changes of mean or extreme flows. This study introduces the use of apportionment entropy as a robust measure to assess flow-volume nonuniformity across seasons, enabling a global analysis. We found that ~21% of long-term river gauging stations exhibit significant alterations in seasonal flow distributions, but two-thirds of these are unrelated to trends in annual mean discharge. By combining a data-driven runoff reconstruction with state-of-the-art hydrological simulations, we identified a discernible weakening of river flow seasonality in northern high latitudes (above 50°N), a phenomenon directly linked to anthropogenic climate forcing.

Caravan - A global community dataset for large-sample hydrology.

High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called Caravan (a series of CAMELS) that standardizes and aggregates seven existing large-sample hydrology datasets. Caravan includes meteorological forcing data, streamflow data, and static catchment attributes (e.g., geophysical, sociological, climatological) for 6830 catchments. Most importantly, Caravan is both a dataset and open-source software that allows members of the hydrology community to extend the dataset to new locations by extracting forcing data and catchment attributes in the cloud. Our vision is for Caravan to democratize the creation and use of globally-standardized large-sample hydrology datasets. Caravan is a truly global open-source community resource.

Globally observed trends in mean and extreme river flow attributed to climate change.

Anthropogenic climate change is expected to affect global river flow. Here, we analyze time series of low, mean, and high river flows from 7250 observatories around the world covering the years 1971 to 2010. We identify spatially complex trend patterns, where some regions are drying and others are wetting consistently across low, mean, and high flows. Trends computed from state-of-the-art model simulations are consistent with the observations only if radiative forcing that accounts for anthropogenic climate change is considered. Simulated effects of water and land management do not suffice to reproduce the observed trend pattern. Thus, the analysis provides clear evidence for the role of externally forced climate change as a causal driver of recent trends in mean and extreme river flow at the global scale.

Intergenerational inequities in exposure to climate extremes.

Young generations are severely threatened by climate change.

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.

State-of-the-art global models underestimate impacts from climate extremes.

Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.

Assessing Global Water Storage Variability from GRACE: Trends, Seasonal Cycle, Subseasonal Anomalies and Extremes.

Throughout the past decade, the Gravity Recovery and Climate Experiment (GRACE) has given an unprecedented view on global variations in terrestrial water storage. While an increasing number of case studies have provided a rich overview on regional analyses, a global assessment on the dominant features of GRACE variability is still lacking. To address this, we survey key features of temporal variability in the GRACE record by decomposing gridded time series of monthly equivalent water height into linear trends, inter-annual, seasonal, and subseasonal (intra-annual) components. We provide an overview of the relative importance and spatial distribution of these components globally. A correlation analysis with precipitation and temperature reveals that both the inter-annual and subseasonal anomalies are tightly related to fluctuations in the atmospheric forcing. As a novelty, we show that for large regions of the world high-frequency anomalies in the monthly GRACE signal, which have been partly interpreted as noise, can be statistically reconstructed from daily precipitation once an adequate averaging filter is applied. This filter integrates the temporally decaying contribution of precipitation to the storage changes in any given month, including earlier precipitation. Finally, we also survey extreme dry anomalies in the GRACE record and relate them to documented drought events. This global assessment sets regional studies in a broader context and reveals phenomena that had not been documented so far.