Evaporation (E) is a key process in land-atmosphere water and energy exchanges. Among the evaporation methods, the complementary relationship (CR) approach builds upon the dynamic feedbacks of water and heat fluxes between the land-atmosphere interface, providing a straightforward framework for estimating evaporation using basic meteorological inputs, without relying on complex land surface information. Although CR is a simple and effective method, traditional CR mechanisms/models still face two main challenges. First, the wet boundary condition of CR is inaccurately characterized. When the land surface is not water-limited, evaporation is defined as potential evaporation (Epo). However, Epo estimates using conventional methods often do not align with its fundamental definition, as meteorological variables observed under real conditions differ from those over a hypothetical wet surface. Here, we estimate Epo using the maximum evaporation approach (Epo_max) that does follow the original Epo definition. Our findings show that using Epo_max significantly reduces the asymmetry in the CR. Second, traditional CR mechanisms focus on the feedback between water vapor and temperature in the land-atmosphere system, while overlooking the impact of these changes on radiation. As the surface transitions from dry to wet, enhanced actual evaporation and reduced sensible heat flux lead to cooler and wetter air above the surface, reducing the vapor pressure deficit and further decreasing atmospheric evaporative capacity (or apparent potential evaporation, Epa). Building on this, we found temperature reduction overall increases the radiation term in Epa and partially offsets the traditional view that water vapor weakens the aerodynamic term. Based on the above modifications, we developed a physically-based, calibration-free CR model, which requires few input variables and thus facilitates evaporation estimation. More importantly, the CR method, grounded in land-atmosphere coupling, offers a simpler framework for studying the feedback of evaporation on climate, making it a promising tool compared to complex coupled climate models.

Water vapour in the lower troposphere plays a major role in the energy balance at the Earth's surface through modifying radiative and latent heat fluxes. Here we develop an analytic model for the probability density function (PDF) of relative humidity in the lower troposphere based on the advection-condensation paradigm. Our theory represents a significant advance on previous work by describing the continuous vertical structure of the PDF throughout the lower troposphere, including the sub-cloud layer. The PDF depends on only three parameters: the decay scale of saturation specific humidity with height, the near-surface relative humidity, and the strength of the mean vertical (synoptic) motion at a given location. The theoretical PDFs closely match those derived from the ERA5 reanalysis at both global and regional scales. Our theory thus provides a basis to understand the distribution of tropospheric water vapour better in current and future climates.

The downwelling longwave radiation at the surface (DLR) is a key component of the Earth's surface energy budget. We present a novel set of equations that explicitly account for both clouds and the CO2 effect to calculate the all-sky DLR. This paper first extends the clear-sky DLR model of Shakespeare and Roderick (2021, https://doi.org/10.1002/qj.4176) to include temperature inversions and clouds. We parameterize relevant cloud properties through theoretical and empirical considerations to formulate an all-sky model. Our model is more accurate than existing methods (reduces Root Mean Squared Error by 2.1-8.7 W/m(2) and 1.2-10.1 W/m(2) compared to ERA5 reanalysis and in-situ data respectively), and provides a strong physical basis for the estimation of the downwelling longwave from near-surface information. We highlight the important role of CO2 dependence by showing our model largely captures the change in atmospheric emissivity purely due to CO2 (i.e., the instantaneous radiative forcing) in CMIP6 models. Plain Language Summary The downwelling longwave radiation (DLR) at the surface is a key component of the energy balance at the Earth's surface. Understanding how the DLR will change under future climate conditions is vital. For the first time, we explicitly write a set of equations to calculate the DLR that sufficiently account for the impact of CO(2 )and clouds simultaneously. Our model is more accurate than existing methods, and provides a much stronger physical basis for the estimation of the downwelling longwave from near-surface information. In this paper, we extend an existing method for estimating the DLR under clear-sky conditions (i.e., no clouds) to operate under all sky conditions. This method can be used to inform models where the DLR is needed, but only basic observations are available.

AbstractObservations and models show that near‐surface relative humidity is nearly constant at ∼80% over the ocean in the current climate, and almost invariant in the global mean in projected future climates. Here, this behavior is investigated through the development of a simple theoretical model for near‐surface relative humidity by considering the moisture balance above a uniform ocean surface. The relative humidity is predicted to depend on only the near‐surface wind speed, air‐surface temperature difference, surface wetness and large‐scale moisture convergence. Although developed in the context of moist over‐ocean convection, the theory is able to determine the relative humidity in a suite of idealized simulations over both wet and dry surfaces with a root‐mean‐square error of less than 3%. The theory also predicts the climatology of relative humidity over the ocean with a root‐mean‐square error of less than 3%. The theory thus provides a theoretical basis for investigating changes in relative humidity over the ocean, water vapor feedbacks and the water cycle in current and future climates.

We appreciate Dr Szilagyi's interest in our article on potential evaporation and the complementary relationship (CR). For his first concern on the assumption of constant net radiation versus constant net solar radiation in the estimation of potential evaporation, here we show that the constant net solar radiation condition is more universally applicable both in observations and from a theoretical perspective. For his second concern on the CR model calibration, we clarify herein that no calibrations were used in our applications of the various CR models. Instead, the parameter values were all directly taken from previous studies to ensure a fair and practically meaningful inter‐model comparison.

Abstract The complementary relationship (CR) provides a framework for estimating land surface evaporation with basic meteorological observations by acknowledging the relationship between actual evaporation, apparent potential evaporation and potential evaporation (Epo). As a key variable in the CR, Epo estimates by conventional models have a long‐standing problem in practical applications. That is, the meteorological forcings (i.e., radiation and temperature) employed in conventional Epo models are observed under actual conditions that are generally not saturated. Hence, conventional Epo models do not conform to the original definition of Epo (i.e., the evaporation that would occur with an unlimited water supply). Here, we estimate Epo using the maximum evaporation approach (Epo_max) that does follow the original Epo definition. We find that adopting Epo_max considerably reduces the asymmetry of the CR compared to when the conventional Priestley‐Taylor Epo is used. We then employ Epo_max and develop a new physically based, calibration‐free CR model, which shows an overall good performance in estimating actual evaporation in 705 catchments at the mean annual scale and 64 flux sites at monthly and mean annual scales (R2 ranges from 0.73 to 0.75 and root‐mean‐squared error ranges from 9.8 to 18.8 W m−2).Both the 705 catchments and 64 flux sites cover a wide range of climates. More importantly, the use of Epo_max leads to a new physical interpretation of the CR.

Methane (CH4) emissions in mangrove ecosystems may complicate the ecosystem’s potential carbon offset for climate change mitigation. Microbial processes and the mass balance of CH4 in mangrove sediment are responsible for the emissions from the ecosystems. This is the follow up of our previous research which found the super saturation of CH4 in the pore water of mangrove sediment compared to atmospheric CH4 and the lack of a correlation between pore water sulphate and CH4 concentrations. This study is going to investigate methane production pathways in the sediment of overwashed mangrove forests. Two approaches were used to study methanogens here: (1) the spread plate count method and the quantitative polymerase chain reaction (qPCR) method, and (2) laboratory experiments with additional methanogenic substrates (methanol, acetate, and hydrogen) to determine which substrates are more conducive to methane production. According to the qPCR method, methanogen abundance ranged from 72 to 6 × 105 CFU g−1 sediment, while SRB abundance ranged from 2 × 102 to 2 × 105 CFU g−1 sediment. According to the plate count method, the abundance of methylotrophic methanogens (the only group of methanogens capable of competing with SRBs) ranged from 8.3 × 102 to 5.1 × 104 CFU g−1, which is higher than the abundance of the other group of methanogens (0 to 7.7 × 102 CFU g−1). The addition of methanol to the sediment slurry, a substrate for methylotropic methanogens, resulted in a massive production of CH4 (up to 9 × 104 ppm) and intriguingly the control treatments with autoclaving did not kill methanogens. These findings suggested that mangrove ecosystems in the marine environment provide favourable conditions for methanogens and further characterisation of the methanogen involved in the process is required. As a result, future research in this ecosystem should include methane production in carbon offset calculations, particularly due to methylotropic methanogenesis.

Evapotranspiration (ET) — the distribution and partitioning of which is strongly mediated by vegetation — is central to the water, energy and carbon cycles. In this Review, we examine the spatiotemporal patterns of ET changes and their linkages with vegetation. A multi-decadal and accelerating rise in global ET is apparent since the 1980s. Diagnostic data sets indicate increases of 0.66 ± 0.38 mm year −2 (mean ± one standard deviation) over 1982–2011 and 1.19 ± 0.31 mm year −2 over 2001–2020. These changes are largely related to vegetation greening (increasing leaf area index (LAI)), hence large ET increases occur in northern high latitudes where greening predominates; increased precipitation and enhanced atmospheric evaporative demand have secondary roles. The impacts of specific drivers of vegetation change on ET, such as CO 2 fertilization, land use change and nitrogen deposition, are uncertain and difficult to quantify at the global scale but have strong impacts at local and/or regional scales. Owing to projected increases in LAI, global ET is expected to continue rising with future anthropogenic warming, although ET sensitivity to greening is lower than in the present climate. Enhanced model validation with respect to long-term trends and ET partitioning, improved mechanistic understanding of key processes and greater data-model fusion techniques are essential for improved understanding of ET characteristics.

To investigate the sensitivity of evaporation to changing long-wave radiation we developed a new experimental facility that locates a shallow water bath at the base of an insulated wind tunnel with evaporation measured using an accurate digital balance. The new facility has the unique ability to impose variations in the incoming long-wave radiation at the water surface whilst holding the air temperature, humidity and wind speed in the wind tunnel at fixed values. The underlying scientific aim is to isolate the effect of a change in the incoming long-wave radiation on both evaporation and surface temperature. In this paper, we describe the configuration and operation of the system and outline the experimental design and approach. We then evaluate the radiative and thermodynamic properties of the new system and show that the shallow water bath naturally adopts a steady-state temperature that closely approximates the thermodynamic wet-bulb temperature. We demonstrate that the long-wave radiation and evaporation are measured with sufficient precision to support the scientific aims.

State-of-the-art evaporation models usually assume net radiation (R-n) and surface temperature (T-s; or near-surface air temperature) to be independent forcings on evaporation. However, R-n depends directly on T-s via outgoing longwave radiation, and this creates a physical coupling between R-n and T-s that extends to evaporation. In this study, we test a maximum evaporation theory originally developed for the global ocean over saturated land surfaces, which explicitly acknowledges the interactions between radiation, T-s and evaporation Similar to the ocean surface, we find that a maximum evaporation (LEmax) emerges over saturated land that represents a generic trade-off between a lower R-n and a higher evaporation fraction as T-s increases. Compared with flux site observations at the daily scale, we show that LEmax corresponds well to observed evaporation under non-water-limited conditions and that the T-s value at which LEmax occurs also corresponds with the observed T-s. Our results suggest that saturated land surfaces behave essentially the same as ocean surfaces at timescales longer than a day and further imply that the maximum evaporation concept is a natural attribute of saturated land surfaces, which can be the basis of a new approach to estimating evaporation.

Climate model projections of the terrestrial water cycle are often described using simple empirical models (‘indices’) that can mislead. Instead, we should seek to understand climate model projections using simple physical models.

We appreciate Dr. Szilagyi's interest in our work of recovering surface temperature and evaporation to a "hypothetical" saturated condition. Dr. Szilagyi criticized our approach by arguing that the recovered surface temperature is unphysically low. Here we reply to Dr. Szilagyi's concern by showing that our recovered surface temperature is not unphysically low and is physically attainable. In addition, our approach strictly follows the definition of potential evaporation by Wilfried Brutsaert (2015).

Climate models predict large increases in downwelling longwave radiation (DLR) at Earth's surface as atmospheric CO2 concentrations increase. Here we introduce a novel methodology that allows these increases to be decomposed into direct radiative forcing due to enhanced CO2 and feedbacks due to subsequent changes in atmospheric properties. For the first time, we develop explicit analytic expressions for the radiative forcing and feedbacks, which are calculable from time-mean fields of near-surface air temperature, specific humidity, pressure, total column water vapor, and total cloud fraction. Our methodology captures 90%-98% of the variance in changes in clear-sky and all-sky DLR in five CMIP5 models, with a typical error of less than 10%. The longwave feedbacks are decomposed into contributions from changes in temperature, specific humidity, water vapor height scale, and cloud fraction. We show that changes in specific humidity and height scale are closely linked to changes in near-surface air temperature and therefore, in the global average, that 90% of the increase in all-sky DLR may be attributed to a feedback from increasing near-surface air temperature. Mean-state clouds play a major role in changes in DLR by masking the clear-sky longwave and enhancing the temperature feedback via increased blackbody radiation. The impact of changes in cloud cover (the cloud feedback) on the DLR is small (similar to 2%) in the global average, but significant in particular geographical regions.

Whether river flows remain stationary is of great concern to hydrologists, water engineers, and society in general, yet is subject to substantial debate. Here we provide the first comprehensive assessment of the long-term stationarity of annual streamflow for 11 069 catchments globally. Our observation-based evidence shows that the long-term annual streamflow remains stationary in 79% of catchments with minimal human disturbance, indicating that historical climate change alone has not led to non-stationarity in annual streamflow series in most catchments. In direct contrast, we found streamflow has remained stationary in only 38% of those catchments where substantial human interventions have occurred. These results demonstrate the scale of the human impact on the freshwater system, and highlight the ongoing need for dealing with the impacts of direct human interventions to ensure successful water management into the future.

Downwelling long-wave radiation is a crucial component of the energy balance of the land and ocean surface. Here we develop a semi-analytic model for the downwelling long-wave dependent on five governing parameters: the near-surface air temperature, the near-surface specific humidity, the surface air pressure, the e-folding height-scale of water vapour, and the CO2 concentration. The model predicts the hourly clear-sky long-wave in the ERA5 reanalysis product with a global mean error of 8.2 W center dot m-2, and on average captures 97% of the temporal variation at individual locations. We show that the model may be used to calculate clear-sky downwelling long-wave from only surface observations of temperature and humidity by using the time-mean water vapour height-scale from the ERA5, interpolated to the location of the observation. Using this method replicates sub-hourly observations from individual sites having a range of climates with errors of 12-25 W center dot m-2. Furthermore, the inclusion of CO2 allows the model to be used to study changes in downwelling long-wave at the surface as CO2 concentrations vary. We validate the model's representation of CO2 by comparison with five CMIP5 climate models. Our model thus provides a simple yet accurate framework to understand the key parameters controlling downwelling long-wave and its variability in the current and future climates.

Prolonged periods of extremely high temperatures with lack of precipitation mark heatwaves that pose health risks and damage ecosystems via rapid soil water depletion and reduced evaporative cooling. Identifying the conditions for the onset of heatwaves and their effects on land‐atmosphere energy and mass fluxes remains a challenge. We propose using the generalized complementary relationship (CR) to estimate actual evaporation from heterogeneous landscapes overlain by different vegetation types (i.e., grasslands and forests) and quantify responses to radiation and air temperature anomalies. A strong correlation between air temperature and sensible heat flux anomalies deduced from FLUXNET data suggests that abrupt exceedances of sensible heat flux above climatological means are indicators for the onset of heatwaves. We capitalize on the coupling between latent and sensible heat fluxes and their links to soil moisture availability within the CR framework to predict anomalous increases in regional sensible heat flux associated with soil water depletion (low precipitation) and extreme evaporative demand (hot air and high radiation). The systematic and energy‐constrained framework based on the CR concept provides insights into the triggering and feedbacks associated with heatwaves and hydro‐climatic extremes such as regional droughts.

Drylands are an essential component of the Earth System and are among the most vulnerable to climate change. In this Review, we synthesize observational and modelling evidence to demonstrate emerging differences in dryland aridity dependent on the specific metric considered. Although warming heightens vapour pressure deficit and, thus, atmospheric demand for water in both the observations and the projections, these changes do not wholly propagate to exacerbate soil moisture and runoff deficits. Moreover, counter-intuitively, many arid ecosystems have exhibited significant greening and enhanced vegetation productivity since the 1980s. Such divergence between atmospheric and ecohydrological aridity changes can primarily be related to moisture limitations by dry soils and plant physiological regulations of evapotranspiration under elevated CO2. The latter process ameliorates water stress on plant growth and decelerates warming-enhanced water losses from soils, while simultaneously warming and drying the near-surface air. We place these climate-induced aridity changes in the context of exacerbated water scarcity driven by rapidly increasing anthropogenic needs for freshwater to support population growth and economic development. Under future warming, dryland ecosystems might respond non-linearly, caused by, for example, complex ecosystem–hydrology–human interactions and increased mortality risks from drought and heat stress, which is a foremost priority for future research. Estimates of global dryland changes are often conflicting. This Review discusses and quantifies observed and projected aridity changes, revealing divergent responses between atmospheric and ecohydrological metrics that can be explained by plant physiological responses to elevated CO2.

This chapter highlights the potential carbon loss from mangrove sediments through methane (CH4) production. Better mangrove ecosystem management and mangrove rehabilitation and restoration have been proposed as a means of greenhouse gas (GHG) abatement. Mangrove rehabilitation and restoration could increase carbon biomass and even recover to natural and undisturbed states, particularly in productive land. However, because of limited data, net ecosystem carbon balance remains uncertain, and thus, long-term measurements on changes of carbon stocks and GHG fluxes following mangrove loss and regeneration are required. CH4 is a potent GHG, the second-largest contributor to global warming, after CO2. In freshwater wetlands, CH4 releases to the atmosphere represent 3% of primary productivity. This chapter provides data sets showing seasonal changes of porewater CH4 concentrations in regeneration sites of mangroves and its salient factors. The relevance of CH4 to net ecosystem carbon balance is illustrated by a conceptual model of changes in porewater CH4 concentrations and primary productivity following regeneration/successional stages.

Dryland vegetation productivity is strongly modulated by water availability. As precipitation patterns and variability are altered by climate change, there is a pressing need to better understand vegetation responses to precipitation variability in these ecologically fragile regions. Here we present a global analysis of dryland sensitivity to annual precipitation variations using long-term records of normalized difference vegetation index (NDVI). We show that while precipitation explains 66% of spatial gradients in NDVI across dryland regions, precipitation only accounts for <26% of temporal NDVI variability over most (>75%) dryland regions. We observed this weaker temporal relative to spatial relationship between NDVI and precipitation across all global drylands. We confirmed this result using three alternative water availability metrics that account for water loss to evaporation, and growing season and precipitation timing. This suggests that predicting vegetation responses to future rainfall using space-for-time substitution will strongly overestimate precipitation control on interannual variability in aboveground growth. We explore multiple mechanisms to explain the discrepancy between spatial and temporal responses and find contributions from multiple factors including local-scale vegetation characteristics, climate and soil properties. Earth system models (ESMs) from the latest Coupled Model Intercomparison Project overestimate the observed vegetation sensitivity to precipitation variability up to threefold, particularly during dry years. Given projections of increasing meteorological drought, ESMs are likely to overestimate the impacts of future drought on dryland vegetation with observations suggesting that dryland vegetation is more resistant to annual precipitation variations than ESMs project.

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.