Year-to-year changes in carbon uptake by terrestrial ecosystems have an essential role in determining atmospheric carbon dioxide concentrations
. It remains uncertain to what extent temperature and ...water availability can explain these variations at the global scale
. Here we use factorial climate model simulations
and show that variability in soil moisture drives 90 per cent of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture-atmosphere feedback amplifies temperature and humidity anomalies and enhances the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate that soil moisture has a dominant role
, which is not readily apparent from land surface model simulations and observational analyses
. These findings highlight the need to account for feedback between soil and atmospheric dryness when estimating the response of the carbon cycle to climatic change globally
, as well as when conducting field-scale investigations of the response of the ecosystem to droughts
. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects that are controlled by soil moisture.
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The amount of water stored on continents is an important constraint for
water mass and energy exchanges in the Earth system and exhibits large
inter-annual variability at both local and continental ...scales. From 2002 to
2017, the satellites of the Gravity Recovery and Climate Experiment
(GRACE) mission have observed changes in terrestrial water storage (TWS) with an
unprecedented level of accuracy. In this paper, we use a statistical model
trained with GRACE observations to reconstruct past climate-driven changes
in TWS from historical and near-real-time meteorological datasets at daily
and monthly scales. Unlike most hydrological models which represent water
reservoirs individually (e.g., snow, soil moisture) and usually provide
a single model run, the presented approach directly reconstructs total TWS
changes and includes hundreds of ensemble members which can be used to
quantify predictive uncertainty. We compare these data-driven TWS estimates
with other independent evaluation datasets such as the sea level budget,
large-scale water balance from atmospheric reanalysis, and in situ streamflow
measurements. We find that the presented approach performs overall as well
or better than a set of state-of-the-art global hydrological models (Water
Resources Reanalysis version 2). We provide reconstructed TWS anomalies at a
spatial resolution of 0.5∘, at both daily and monthly scales over
the period 1901 to present, based on two different GRACE products and three
different meteorological forcing datasets, resulting in six reconstructed TWS
datasets of 100 ensemble members each. Possible user groups and applications
include hydrological modeling and model benchmarking, sea level budget
studies, assessments of long-term changes in the frequency of droughts, the
analysis of climate signals in geodetic time series, and the interpretation
of the data gap between the GRACE and GRACE Follow-On missions. The
presented dataset is published at https://doi.org/10.6084/m9.figshare.7670849 (Humphrey and Gudmundsson, 2019) and updates will be
published regularly.
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The causes of sea-level rise since 1900 Frederikse, Thomas; Landerer, Felix; Caron, Lambert ...
Nature (London),
08/2020, Volume:
584, Issue:
7821
Journal Article
Peer reviewed
The rate of global-mean sea-level rise since 1900 has varied over time, but the contributing factors are still poorly understood
. Previous assessments found that the summed contributions of ice-mass ...loss, terrestrial water storage and thermal expansion of the ocean could not be reconciled with observed changes in global-mean sea level, implying that changes in sea level or some contributions to those changes were poorly constrained
. Recent improvements to observational data, our understanding of the main contributing processes to sea-level change and methods for estimating the individual contributions, mean another attempt at reconciliation is warranted. Here we present a probabilistic framework to reconstruct sea level since 1900 using independent observations and their inherent uncertainties. The sum of the contributions to sea-level change from thermal expansion of the ocean, ice-mass loss and changes in terrestrial water storage is consistent with the trends and multidecadal variability in observed sea level on both global and basin scales, which we reconstruct from tide-gauge records. Ice-mass loss-predominantly from glaciers-has caused twice as much sea-level rise since 1900 as has thermal expansion. Mass loss from glaciers and the Greenland Ice Sheet explains the high rates of global sea-level rise during the 1940s, while a sharp increase in water impoundment by artificial reservoirs is the main cause of the lower-than-average rates during the 1970s. The acceleration in sea-level rise since the 1970s is caused by the combination of thermal expansion of the ocean and increased ice-mass loss from Greenland. Our results reconcile the magnitude of observed global-mean sea-level rise since 1900 with estimates based on the underlying processes, implying that no additional processes are required to explain the observed changes in sea level since 1900.
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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.
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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.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Freshwater resources are of high societal relevance, and understanding their past variability is vital to water management in the context of ongoing climate change. This study introduces a global ...gridded monthly reconstruction of runoff covering the period from 1902 to 2014. In situ streamflow observations are used to train a machine learning algorithm that predicts monthly runoff rates based on antecedent precipitation and temperature from an atmospheric reanalysis. The accuracy of this reconstruction is assessed with cross-validation and compared with an independent set of discharge observations for large river basins. The presented dataset agrees on average better with the streamflow observations than an ensemble of 13 state-of-the art global hydrological model runoff simulations. We estimate a global long-term mean runoff of 38 452 km3 yr−1 in agreement with previous assessments. The temporal coverage of the reconstruction offers an unprecedented view on large-scale features of runoff variability in regions with limited data coverage, making it an ideal candidate for large-scale hydro-climatic process studies, water resource assessments, and evaluating and refining existing hydrological models. The paper closes with example applications fostering the understanding of global freshwater dynamics, interannual variability, drought propagation and the response of runoff to atmospheric teleconnections. The GRUN dataset is available at https://doi.org/10.6084/m9.figshare.9228176 (Ghiggi et al., 2019).
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The terrestrial carbon and water cycles are strongly coupled. As atmospheric carbon dioxide concentration increases, climate and the coupled hydrologic cycle are modified, thus altering the ...terrestrial water cycle and the availability of soil moisture necessary for plants' carbon dioxide uptake. Concomitantly, rising surface carbon dioxide concentrations also modify stomatal (small pores at the leaf surface) regulation as well as biomass, thus altering ecosystem photosynthesis and transpiration rates. Those coupled changes have profound implications for the predictions of the carbon and water cycles. This paper reviews the main mechanisms behind the coupling of the terrestrial water and carbon cycles. We especially focus on the key role of dryness (atmospheric dryness and terrestrial water availability) on carbon uptake, as well as the predicted impact of rising carbon dioxide on the water cycle. Challenges related to this coupling and the necessity to constrain it based on observations are finally discussed.
Abstract
Global fluctuations in annual land carbon uptake (NEE
IAV
) depend on water and temperature variability, yet debate remains about local and seasonal controls of the global dependences. Here, ...we quantify regional and seasonal contributions to the correlations of globally-averaged NEE
IAV
against terrestrial water storage (TWS) and temperature, and respective uncertainties, using three approaches: atmospheric inversions, process-based vegetation models, and data-driven models. The three approaches agree that the tropics contribute over 63% of the global correlations, but differ on the dominant driver of the global NEE
IAV
, because they disagree on seasonal temperature effects in the Northern Hemisphere (NH, >25°N). In the NH, inversions and process-based models show inter-seasonal compensation of temperature effects, inducing a global TWS dominance supported by observations. Data-driven models show weaker seasonal compensation, thereby estimating a global temperature dominance. We provide a roadmap to fully understand drivers of global NEE
IAV
and discuss their implications for future carbon–climate feedbacks.
Increases in air temperature lead to increased dryness of the air and potentially develops increased dryness in the soil. Extreme dryness (in the soil and/or in the atmosphere) affects the capacity ...of ecosystems for functioning and for modulating the climate. Here, we used long-term high temporal resolution (daily) soil moisture (SM) and vapor pressure deficit (VPD) data of high spatial resolution (∼0.1° × 0.1°) to show that compared to the reference period (1950–1990), the overall frequency of extreme soil dryness, extreme air dryness, and extreme compound dryness (i.e., co-occurrence of extreme soil dryness and air dryness) has increased by 1.2-fold 0.8,1.6 (median 10th,90th percentile, 1.6-fold 1,2.3, and 1.7-fold 0.9,2.5, respectively, over the last 31 years (1991–2021) across Europe. Our results also indicate that this increase in frequency of extreme compound dryness (between reference and 1991–2021 period) is largely due to increased SM-VPD coupling across Northern Europe, and due to decreasing SM and/or increasing VPD trend across Central and Mediterranean Europe. Furthermore, under the RCP8.5 (Representative Concentration Pathways 8.5) emission scenario, this increase in frequency of extreme compound dryness would be 3.3-fold 2.0,5.8, and 4.6-fold 2.3,11.9 by mid-21st century (2031–2065) and late-21st century (2066–2100), respectively. Additionally, we segregated the changes in frequency of extreme dryness across the most recent (year 2021) land cover types in Europe to show that croplands, broadleaved forest, and urban areas have experienced more than twice as much extreme dryness during 1990–2021 compared to the reference period of 1990–2021, which based on the future projection data will increase to more than three-fold by mid 21st century. Such future climate-change induced increase in extreme dryness could have negative implications for functioning of ecosystems and compromise their capacity to adapt to rapidly rising dryness levels.
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Vegetation Optical Depth (VOD) has emerged as a valuable metric to quantify water stress on vegetation's carbon uptake from a remote sensing perspective. However, existing spaceborne microwave remote ...sensing platforms face limitations in capturing the diurnal VOD variations and global products lack site‐level validation against plant physiology. To address these challenges, we leveraged the Global Navigation Satellite System (GNSS) L‐band microwave signal, measuring its attenuation by the canopy of a temperate broadleaf forest using a pair of GNSS receivers. This approach allowed us to collect continuous VOD observations at a sub‐hourly scale. We found a significant seasonal‐scale correlation between VOD and leaf water potential. The VOD diurnal amplitude is affected by soil moisture, plant transpiration and leaf surface water. Additionally, VOD can help independently estimate plant transpiration. Our findings pave the way for a deeper understanding of response of the vegetation to water stress at finer temporal scales.
Plain Language Summary
Microwave satellite measurements offer valuable insights into Vegetation Optical Depth (VOD), which reflects the amount of water present in plants. However, most VOD products currently available only offer observations at two times of the day, which fail to capture the variations of VOD over the course of the day. In this study, we installed Global Navigation Satellite System (GNSS) signal receivers at the top and bottom of a temperate broadleaf forest canopy located at a flux tower in Missouri, USA. This setup allowed us to obtain continuous observations of VOD at sub‐hourly scale. The strong correlation observed between GNSS VOD and local leaf water potential suggests that this robust and cost‐effective technique can complement other labor‐intensive measurements. The VOD diurnal amplitude is influenced by soil water content, evapotranspiration, and leaf surface water in the form of dew and interception. GNSS VOD also exhibits the potential to aid in estimating plant transpiration, which can be further used for partitioning evapotranspiration. The investigation of plant water content dynamics in this study will enhance our understanding of the carbon‐water coupling at a finer temporal scale.
Key Points
Sub‐hourly Vegetation Optical Depth (VOD) retrieved from Global Navigation Satellite Systems attenuation relates to soil and leaf water dynamics
Daily maximum VOD correlates well with field measurements of predawn leaf water potential
Plant transpiration can be reconstructed from VOD principal components
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