The representation of nonlinear subgrid processes, especially clouds, has been a major source of uncertainty in climate models for decades. Cloud-resolving models better represent many of these ...processes and can now be run globally but only for short-term simulations of at most a few years because of computational limitations. Here we demonstrate that deep learning can be used to capture many advantages of cloud-resolving modeling at a fraction of the computational cost. We train a deep neural network to represent all atmospheric subgrid processes in a climate model by learning from a multiscale model in which convection is treated explicitly. The trained neural network then replaces the traditional subgrid parameterizations in a global general circulation model in which it freely interacts with the resolved dynamics and the surface-flux scheme. The prognostic multiyear simulations are stable and closely reproduce not only the mean climate of the cloud-resolving simulation but also key aspects of variability, including precipitation extremes and the equatorial wave spectrum. Furthermore, the neural network approximately conserves energy despite not being explicitly instructed to. Finally, we show that the neural network parameterization generalizes to new surface forcing patterns but struggles to cope with temperatures far outside its training manifold. Our results show the feasibility of using deep learning for climate model parameterization. In a broader context, we anticipate that data-driven Earth system model development could play a key role in reducing climate prediction uncertainty in the coming decade.
Satellite-retrieved solar-induced chlorophyll fluorescence (SIF) has shown great potential to monitor the photosynthetic activity of terrestrial ecosystems. However, several issues, including low ...spatial and temporal resolution of the gridded datasets and high uncertainty of the individual retrievals, limit the applications of SIF. In addition, inconsistency in measurement footprints also hinders the direct comparison between gross primary production (GPP) from eddy covariance (EC) flux towers and satellite-retrieved SIF. In this study, by training a neural network (NN) with surface reflectance from the MODerate-resolution Imaging Spectroradiometer (MODIS) and SIF from Orbiting Carbon Observatory-2 (OCO-2), we generated two global spatially contiguous SIF (CSIF) datasets at moderate spatiotemporal (0.05° 4-day) resolutions during the MODIS era, one for clear-sky conditions (2000–2017) and the other one in all-sky conditions (2000–2016). The clear-sky instantaneous CSIF (CSIF(sub clear-inst)) shows high accuracy against the clear-sky OCO-2 SIF and little bias across biome types. The all-sky daily average CSIF (CSIF(sub all-daily)) dataset exhibits strong spatial, seasonal and interannual dynamics that are consistent with daily SIF from OCO-2 and the Global Ozone Monitoring Experiment-2 (GOME-2). An increasing trend (0.39 %) of annual average CSIFall-daily is also found, confirming the greening of Earth in most regions. Since the difference between satellite-observed SIF and CSIF is mostly caused by the environmental down-regulation on SIF(sub yield), the ratio between OCO-2 SIF and CSIF(sub clear-inst) can be an effective indicator of drought stress that is more sensitive than the normalized difference vegetation index and enhanced vegetation index. By comparing CSIF(sub all-daily) with GPP estimates from 40 EC flux towers across the globe, we find a large cross-site variation (c.v. = 0.36) of the GPP–SIF relationship with the highest regression slopes for evergreen needleleaf forest. However, the cross-biome variation is relatively limited (c.v. = 0.15). These two contiguous SIF datasets and the derived GPP–SIF relationship enable a better understanding of the spatial and temporal variations of the GPP across biomes and climate.
Evaporative loss of interception (E
) is the first process occurring during rainfall, yet its role in large-scale surface water balance has been largely underexplored. Here we show that E
can be ...inferred from flux tower evapotranspiration measurements using physics-informed hybrid machine learning models built under wet versus dry conditions. Forced by satellite and reanalysis data, this framework provides an observationally constrained estimate of E
, which is on average 84.1 ± 1.8 mm per year and accounts for 8.6 ± 0.2% of total rainfall globally during 2000-2020. Rainfall frequency regulates long-term average E
changes, and rainfall intensity, rather than vegetation attributes, determines the fraction of E
in gross precipitation (E
/P). Rain events have become less frequent and more intense since 2000, driving a global decline in E
(and E
/P) by 4.9% (6.7%). This suggests that ongoing rainfall changes favor a partitioning towards more soil moisture and runoff, benefiting ecosystem functions but simultaneously increasing flood risks.
Weather extremes have widespread harmful impacts on ecosystems and human communities with more deaths and economic losses from flash floods than any other severe weather-related hazards. Flash floods ...attributed to storm runoff extremes are projected to become more frequent and damaging globally due to a warming climate and anthropogenic changes, but previous studies have not examined the response of these storm runoff extremes to naturally and anthropogenically driven changes in surface temperature and atmospheric moisture content. Here we show that storm runoff extremes increase in most regions at rates higher than suggested by Clausius-Clapeyron scaling, which are systematically close to or exceed those of precipitation extremes over most regions of the globe, accompanied by large spatial and decadal variability. These results suggest that current projected response of storm runoff extremes to climate and anthropogenic changes may be underestimated, posing large threats for ecosystem and community resilience under future warming conditions.
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.
Previous studies seldom consider humidity when examining heat‐related extremes, and none have explored the effects of humidity on concurrent extremes of high heat stress and low river streamflow. ...Here, we present the first global picture of projected changes in compound lethal heat stress (Th)‐drought hazards (CHD) across 11,637 catchments. Our observational datasets show that atmospheric conditions (e.g., energy and vapor flux) play an important role in constraining the heat extremes, and that Th (32% ± 11%) yields a higher coincidence rate of global CHD than wet‐bulb temperature (28% ± 11%), driven by lower relative humidity (RH) and thus air dryness in Th extremes. Our large model ensemble projects a 10‐fold intensification of bivariate CHD risks by 2071–2100, mainly driven by increases in heat extremes. Future declines in RH, wind, snow, and precipitation in many regions are likely to exacerbate such water and weather‐related hazards (e.g., drought and CHD).
Plain Language Summary
Water and weather‐related extremes such as droughts and heatwaves typically occur simultaneously, posing larger risks to humans and ecosystem than any individual hazard. Extreme high lethal heat stress, which is governed by both temperature and humidity, inhibits the evaporative cooling function of the human body. However, changes in lethal heat stress under past and future climate are poorly understood at the global scale, and no study has yet explored their influences on the risk of compound heat stress‐drought events. Here, we provide the first global picture of the concurrent high heat stress–low streamflow extremes and their projected changes. The fraction of lethal heat extremes accompanied by drought hazards is projected to rise markedly throughout the 21st century. The global magnitude and occurrence of compound hazards is projected to intensify by 4–10 times by 2071–2100, mainly due to the increasing severity of heat extremes. Our study reveals an increasing global risk of compounding hazards, highlighting the need to better prepare adaptation and mitigation solutions in the Anthropocene.
Key Points
We present the first global assessment of compound extremes of high lethal heat stress and low river streamflow
Lethal heat stress yields a higher coincidence rate of compound hazards than wet‐bulb temperature
Future lethal heat stress‐drought events are mainly exacerbated by changes in heat extremes
About 50% of the solar energy absorbed at the Earth's surface drives evaporation, fueling the water cycle that affects various renewable energy resources, such as wind and hydropower. Recent advances ...demonstrate our nascent ability to convert evaporation energy into work, yet there is little understanding about the potential of this resource. Here we study the energy available from natural evaporation to predict the potential of this ubiquitous resource. We find that natural evaporation from open water surfaces could provide power densities comparable to current wind and solar technologies while cutting evaporative water losses by nearly half. We estimate up to 325 GW of power is potentially available in the United States. Strikingly, water's large heat capacity is sufficient to control power output by storing excess energy when demand is low, thus reducing intermittency and improving reliability. Our findings motivate the improvement of materials and devices that convert energy from evaporation.The evaporation of water represents an alternative source of renewable energy. Building on previous models of evaporation, Cavusoglu et al. show that the power available from this natural resource is comparable to wind and solar power, yet it does not suffer as much from varying weather conditions.
Although the terrestrial biosphere absorbs about 25 per cent of anthropogenic carbon dioxide (CO
) emissions, the rate of land carbon uptake remains highly uncertain, leading to uncertainties in ...climate projections
. Understanding the factors that limit or drive land carbon storage is therefore important for improving climate predictions. One potential limiting factor for land carbon uptake is soil moisture, which can reduce gross primary production through ecosystem water stress
, cause vegetation mortality
and further exacerbate climate extremes due to land-atmosphere feedbacks
. Previous work has explored the impact of soil-moisture availability on past carbon-flux variability
. However, the influence of soil-moisture variability and trends on the long-term carbon sink and the mechanisms responsible for associated carbon losses remain uncertain. Here we use the data output from four Earth system models
from a series of experiments to analyse the responses of terrestrial net biome productivity to soil-moisture changes, and find that soil-moisture variability and trends induce large CO
fluxes (about two to three gigatons of carbon per year; comparable with the land carbon sink itself
) throughout the twenty-first century. Subseasonal and interannual soil-moisture variability generate CO
as a result of the nonlinear response of photosynthesis and net ecosystem exchange to soil-water availability and of the increased temperature and vapour pressure deficit caused by land-atmosphere interactions. Soil-moisture variability reduces the present land carbon sink, and its increase and drying trends in several regions are expected to reduce it further. Our results emphasize that the capacity of continents to act as a future carbon sink critically depends on the nonlinear response of carbon fluxes to soil moisture and on land-atmosphere interactions. This suggests that the increasing trend in carbon uptake rate may not be sustained past the middle of the century and could result in accelerated atmospheric CO
growth.
Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and ...atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land–atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture–precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land–atmosphere feedbacks is projected to increase in the 21st century. Importantly, land–atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.
Predicting how increasing atmospheric CO
2
will affect the hydrologic cycle is of utmost importance for a wide range of applications. It is typically thought that future dryness will depend on ...precipitation changes, i.e., change in water supply, and changes in evaporative demand due to either increased radiation or temperature. Opposite to this viewpoint, using Earth system models, we show that changes in key water-stress variables will be strongly modified by vegetation physiological effects in response to increased CO
2
at the leaf level. These results emphasize that the continental carbon and water cycles have to be studied as an interconnected system.
Predicting how increasing atmospheric CO
2
will affect the hydrologic cycle is of utmost importance for a range of applications ranging from ecological services to human life and activities. A typical perspective is that hydrologic change is driven by precipitation and radiation changes due to climate change, and that the land surface will adjust. Using Earth system models with decoupled surface (vegetation physiology) and atmospheric (radiative) CO
2
responses, we here show that the CO
2
physiological response has a dominant role in evapotranspiration and evaporative fraction changes and has a major effect on long-term runoff compared with radiative or precipitation changes due to increased atmospheric CO
2
. This major effect is true for most hydrological stress variables over the largest fraction of the globe, except for soil moisture, which exhibits a more nonlinear response. This highlights the key role of vegetation in controlling future terrestrial hydrologic response and emphasizes that the carbon and water cycles are intimately coupled over land.
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