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Hydrological extremes, in the form of droughts and floods, have impacts on a wide range of sectors including water availability, food security, and energy production. Given continuing large impacts of droughts and floods and the expectation for significant regional changes projected in the future, there is an urgent need to provide estimates of past events and their future risk, globally. However, current estimates of hydrological extremes are not robust and accurate enough, due to lack of long-term data records, standardized methods for event identification, geographical inconsistencies, and data uncertainties. To tackle these challenges, this article presents the development of the first Global Drought and Flood Catalogue (GDFC) for 1950–2016 by merging the latest in situ and remote sensing datasets with state-of-the-art land surface and hydrodynamic modeling to provide a continuous and consistent estimate of the terrestrial water cycle and its extremes. This GDFC also includes an unprecedented level of detailed analysis of drought and large-scale flood events using univariate and multivariate risk assessment frameworks, which incorporates regional spatial–temporal characteristics (i.e., duration, spatial extent, severity) and global hazard maps for different return periods. This Catalogue forms a basis for analyzing the changing risk of droughts and floods and can underscore national and international climate change assessments and provide a key reference for climate change studies and climate model evaluations. It also contributes to the growing interests in multivariate and compounding risk analysis.

We develop a novel climate-informed, policy-relevant framework to guide future managed aquifer recharge under deep uncertainties., Harvesting floodwaters to recharge depleted groundwater aquifers can simultaneously reduce flood and drought risks and enhance groundwater sustainability. However, deployment of this multibeneficial adaptation option is fundamentally constrained by how much water is available for recharge (WAFR) at present and under future climate change. Here, we develop a climate-informed and policy-relevant framework to quantify WAFR, its uncertainty, and associated policy actions. Despite robust and widespread increases in future projected WAFR in our case study of California (for 56/80% of subbasins in 2070–2099 under RCP4.5/RCP8.5), strong nonlinear interactions between diversion infrastructure and policy uncertainties constrain how much WAFR can be captured. To tap future elevated recharge potential through infrastructure expansion under deep uncertainties, we outline a novel robustness-based policy typology to identify priority areas of investment needs. Our WAFR analysis can inform effective investment decisions to adapt to future climate-fueled drought and flood risk over depleted aquifers, in California and beyond.

Mulching is a common and effective practice to artificially reduce evaporation for the purposes of water conservation in arid/semiarid ecosystems. Few studies have quantified the effects of plastic mulch on evapotranspiration (ET) partitioning impacted by different biophysical processes between bare and mulch-covered soil within a soil-mulch–plant-atmosphere continuum. Here, we partitioned ET flux into bare soil evaporation (Ebs), mulch-covered soil evaporation (Ems) and transpiration (T) in an oasis cropland ecosystem that was partially covered by plastic film, using an improved multisource energy balance model. The modeled water/energy fluxes agreed well with those measured by the eddy covariance. The modeled surface temperatures of both bare soil and mulch-covered soil were also consistent with measured fluxes, with a high R2 (0.81). During the growing season, the mean fractional contribution to total ET was 21 ± 12%, 6 ± 4%, and 73 ± 14% for Ebs, Ems and T, respectively. Comparisons of modeled output with and without considering mulching effects indicate that mulching increases the T/ET by decreasing E (0.02 ± 0.02 mm h−1), with a mean value of 7.2% and a range of 0–16% during the growing season. Mulching also increases soil temperature, while decreasing available energy at the land surface. These results show that the effects of mulching on ET partitioning varied with leaf development and were more sensitive during periods characterized by a lower leaf area index (e.g., the initial growing period and the period after clear cutting). Without considering mulch effects, the ET (E/ET) flux would be an overestimate, mainly because soil resistance and the availability of soil water would be underestimated. This study highlights the potential of plastic film mulch as a viable management option for soil water conservation and improving soil temperature, which is crucial for plant growth in arid and semiarid ecosystems.

A widely used approach for estimating actual evapotranspiration (AET) in hydrological and earth system models is to constrain potential evapotranspiration (PET) with a single empirical stress factor (Ω = AET/PET). Ω represents the water availability and is fundamentally linked to canopy-atmosphere coupling. However, the mean and seasonal variability of Ω in the models have rarely been evaluated against observations, and the model performances for different climates and biomes remain unclear. In this study, we first derived the observed Ω from 28 FLUXNET sites over North America during 2000-2007, which was then used to evaluate Ω in six large-scale model-based datasets. Our results confirm the importance of incorporating canopy height in the formulation of aerodynamic conductance in the case of forests. Furthermore, leaf area index (LAI) is central to the prediction of Ω and can be quantitatively linked to the partitioning between transpiration and soil evaporation (R2 = 0.43). The substantial differences between observed and model-based Ω in forests (range: 0.2~0.9) are highly related to the way these models estimated PET and the way they represented the responses of Ω to the environmental drivers, especially wind speed and LAI. This is the first assessment of Ω in models based on in situ observations. Our findings demonstrate that the observed Ω is useful for evaluating, validating, and optimizing the modeling of AET and thus of water and energy balances.

Terrestrial evapotranspiration (ET) consists of evaporation (E) from canopy-intercepted water, evaporation from soil and open water, and transpiration (T) from plants. Determining the contribution of T to ET (hereafter T/ET) is challenging but necessary for improving water resource management and understanding the response of ecosystem water/energy budgets to climate change. Water stable isotopes provide unique information on ecosystem processes and can be used to partition evapotranspiration at the ecosystem scale. In this paper, the aim is to review the state of the science on the isotope method for ecosystem ET partitioning, with a focus on uncertainties related to estimating the three isotopic end members (isotopic compositions of ET, T and E). The published results show larger T/ET variations during the growing season in croplands due to water management and rapid leaf area index (LAI) changes compared to in other natural ecosystems. Another robust result is that on average, grasslands have lower T/ET than woodlands. The isotopic composition of ET is provided by measurements, while the isotopic compositions of T and E are generally obtained using the Craig-Gordon model with appropriate modifications. Significant advances have been made in the techniques for estimating the isotopic composition of ET, largely due to the availability of fast-responding instruments for in situ measurements of water vapor isotopic composition. The largest source of uncertainty in the T/ET estimation comes from uncertainties in the isotopic composition of ET. Based on published results of the uncertainties in the three end members, we estimate that a typical uncertainty range for T/ET is ±21% (one standard deviation). This review provides background information and theoretical references for studies on isotopic hydrology, ecosystem processes and climate change.

Stable isotopes of water (H2O, HDO, and H218O) are tracers that provide powerful constraints on water transport processes in the atmosphere. This paper presents a description of an atmospheric boundary layer (ABL) simulation system called ISOLESC that couples water isotope fractionation processes with a land surface model, a large eddy simulation model, and a two‐moment cloud microphysics parameterization. Results from two model configurations—one with shallow precipitating cumulus and the other for a cloud‐free ABL—are presented to evaluate the model performance and determine its sensitivity to isotopic parameterizations. The coupled model successfully reproduces important ABL statistics (ABL height, cloud fraction, and cloud liquid water content), the expected effects of mixing and fractionation on the time evolution of ABL vapor isotopic composition, and observed diurnal variations of near‐surface water vapor isotopic composition. For the current configuration, nondiscriminating entrainment contributes 17% to the subdaily time variation of near‐surface vapor deuterium excess, while surface evapotranspiration contributes 83%. The isotopic compositions of water vapor and cloud water are insensitive to mesh resolution, but the profiles of cloud water specific humidity, rainwater specific humidity, and its isotopic ratios show moderate response to changes in grid size. Since ISOLESC resolves the energy containing scales of turbulent motions in the ABL and incorporates microphysical processes, it can be used for constraining ABL parameterizations. We find that a further improvement of raindrop reevaporation in the current cloud microphysical scheme is required in order to produce realistic near‐surface raindrop deuterium excess for the case simulated here. We suggest that ISOLESC provides a quantitative framework for utilizing vapor‐phase isotopic measurements to study local hydrological processes.

Recent rapid Arctic sea-ice reduction has been well documented in observations, reconstructions and model simulations. However, the rate of sea ice loss is highly variable in both time and space. The western Arctic has seen the fastest sea-ice decline, with substantial interannual and decadal variability, but the underlying mechanism remains unclear. Here we demonstrate, through both observations and model simulations, that the Pacific North American (PNA) pattern is an important driver of western Arctic sea-ice variability, accounting for more than 25% of the interannual variance. Our results suggest that the recent persistent positive PNA pattern has led to increased heat and moisture fluxes from local processes and from advection of North Pacific airmasses into the western Arctic. These changes have increased lower-tropospheric temperature, humidity and downwelling longwave radiation in the western Arctic, accelerating sea-ice decline. Our results indicate that the PNA pattern is important for projections of Arctic climate changes, and that greenhouse warming and the resultant persistent positive PNA trend is likely to increase Arctic sea-ice loss., The fastest sea-ice decline has been observed in the western Arctic, but the underlying mechanisms are still unclear. Here, the authors show that the Pacific North American pattern plays an important role in western Arctic sea-ice variability.

The isotopic composition of surface water vapor flux (δE) is a quantity frequently used to investigate the local and regional water cycle. This study reports the results of a comparative evaluation of δE determined with the Keeling plot and the flux‐gradient methods using high‐frequency data collected at a cropland site and a lake site. Three regression models, ordinary least squares (OLS), York's solution (YS), and geometric mean regression, were tested with the Keeling plot method. Results show that concentration‐dependent field characterization of measurement errors can improve the estimation of the YS regression. For both sites, broad agreement was achieved among the Keeling plot method with YS regression, the Keeling plot method with OLS regression and the flux‐gradient method. For the lake site, OLS was the least biased of the three regression models in reference to the δE calculated by the Craig‐Gordon (CG) model of isotopic evaporation of open water. Good agreement was aslo achieved between the flux‐gradient method and the CG model at the lake site under open‐fetch conditions. A footprint analysis suggests that the Keeling method with OLS regression may be less sensitive to fetch than the flux‐gradient method.

Earth system models use soil information to parameterize hard-to-measure soil hydraulic properties based on pedotransfer functions. However, current parameterizations rely on sample-scale information which often does not account for biologically-promoted soil structure and heterogeneities in natural landscapes, which may significantly alter infiltration-runoff and other exchange processes at larger scales. Here we propose a systematic framework to incorporate soil structure corrections into pedotransfer functions, informed by remote-sensing vegetation metrics and local soil texture, and use numerical simulations to investigate their effects on spatially distributed and areal averaged infiltration-runoff partitioning. We demonstrate that small scale soil structure features prominently alter the hydrologic response emerging at larger scales and that upscaled parameterizations must consider spatial correlations between vegetation and soil texture. The proposed framework allows the incorporation of hydrological effects of soil structure with appropriate scale considerations into contemporary pedotransfer functions used for land surface parameterization., Communications Earth & Environment, 2 (1), ISSN:2662-4435

Agriculture is expanding in tropical mountainous areas, yet its climatic effect is poorly understood. Here, we investigate how elevation regulates the biophysical climate impacts of deforestation over tropical mountainous areas by integrating satellite-observed forest cover changes into a high-resolution land–atmosphere coupled model. We show that recent forest conversion between 2000 and 2014 increased the regional warming by 0.022 ± 0.002 °C in the Southeast Asian Massif, 0.010 ± 0.007 °C in the Barisan Mountains (Maritime Southeast Asia), 0.042 ± 0.010 °C in the Serra da Espinhaco (South America) and 0.047 ± 0.008 °C in the Albertine Rift mountains (Africa) during the local dry season. The deforestation-driven local temperature anomaly can reach up to 2 °C where forest conversion is extensive. The warming from mountain deforestation depends on elevation, through the intertwined and opposing effects of increased albedo causing cooling and decreased evapotranspiration causing warming. As the elevation increases, the albedo effect increases in importance and the warming effect decreases, analogous to previously highlighted decreases of deforestation-induced warming with increasing latitude. As most new croplands are encroaching lands at low to moderate elevations, deforestation produces higher warming from suppressed evapotranspiration. Impacts of this additional warming on crop yields, land degradation and biodiversity of nearby intact ecosystems should be incorporated into future assessments. Deforestation causes elevation-dependent warming over tropical mountain regions, according to high-resolution climate simulations.

Quantification of the contribution of transpiration (T) to evapotranspiration (ET) is a requirement for understanding changes in carbon assimilation and water cycling in a changing environment. So far, few studies have examined seasonal variability of T/ET and compared different ET partitioning methods under natural conditions across diverse agro-ecosystems. In this study, we apply a two-source model to partition ET for three agro-ecosystems (rice, wheat and corn). The model is coupled with a plant physiology scheme for the canopy conductance. The model-estimated T/ET ranges from 0 to 1, with a near continuous increase over time in the early growing season when leaf area index (LAI) is less than 2.5 and then convergence towards a stable value beyond LAI of 2.5. The seasonal change in T/ET can be described well as a function of LAI, implying that LAI is a first-order factor affecting ET partitioning. Application of the model to seven other Ameriflux sites reveals that soil moisture and canopy conductance also influence the ET partitioning. The two-source model results show that the growing-season (May–September for rice, April–June for wheat and June–September for corn) T/ET is 0.50, 0.84 and 0.64, while an isotopic approach shows that T/ET is 0.74, 0.93 and 0.81 for rice, wheat and maize, respectively. The two-source model results are supported by soil lysimeter and eddy covariance measurements made during the same time period for wheat (0.87). Uncertainty analysis suggests that further improvements to the Craig-Gordon model prediction of the evaporation isotope composition and to measurement of the isotopic composition of ET are necessary to achieve accurate flux partitioning at the ecosystem scale using water isotopes as tracers. The program code for the two-source model is available at the open-source platform https://github.com/zhongwangwei/SiLSM_v3 .

Many paleoclimatic records in Southeast Asia rely on rainfall isotope ratios as proxies for past hydroclimatic variability. However, the physical processes controlling modern rainfall isotopic behaviors in the region is poorly constrained. Here, we combined isotopic measurements at six sites across Thailand with an isotope-incorporated atmospheric circulation model (IsoGSM) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to investigate the factors that govern the variability of precipitation isotope ratios in this region. Results show that rainfall isotope ratios are both correlated with local rainfall amount and regional outgoing longwave radiation, suggesting that rainfall isotope ratios in this region are controlled not only by local rain amount (amount effect) but also by large-scale convection. As a transition zone between the Indian monsoon and the western North Pacific monsoon, the spatial difference of observed precipitation isotope among different sites are associated with moisture source. These results highlight the importance of regional processes in determining rainfall isotope ratios in the tropics and provide constraints on the interpretation of paleo-precipitation isotope records in the context of regional climate dynamics.

Understanding the controls on temporal variation in plant leaf δ2H and δ18O values is important for understanding carbon–water dynamics of the biosphere and interpreting a wide range of proxies for past environments. Explaining the enrichment mechanisms under field conditions is challenging. To clarify the leaf water isotopic enrichment process at the ecosystem scale, four models with a range of complexities that were previously conducted at the leaf scale have been tested to simulate canopy foliage water in a multispecies grassland ecosystem. Although the exact importance of considering non-steady-state or/and isotopic diffusion in bulk leaf isotopic simulations has been reported in previous studies, our findings suggested that the steady-state assumption (SSA) is practically acceptable as a first-order approximation. The SSA two-pool model was the best option for reproducing seasonality of the bulk-leaf-water isotopic ratio for a grassland ecosystem. Relative humidity at canopy layer as the most controlling factor for canopy foliage water stable isotope composition because of its high sensitivity and variation. The results highlighted that canopy foliage water was a well-behaved property that was predictable for a multispecies grassland ecosystem at hourly or daily time-scales.

This is the data used in the manuscript“Response of surface temperature to afforestation in the Kubuqi Desert, Inner Mongolia” by Wang et al. for Journal of Geophysical Research - Atmospheres [MS#2017JD027522].

Open-path eddy covariance systems are widely used for measuring the CO2 flux between land and atmosphere. A common problem is that they often yield negative fluxes or physiologically unreasonable CO2 uptake fluxes in the nongrowing season under cold conditions. In this study, a meta-analysis was performed on the eddy flux data from 64 FLUXNET sites and the relationship between the observed CO2 flux and the sensible heat flux was analyzed. In theory, these two fluxes should be independent of each other in cold conditions (air temperature lower than 0°C) when photosynthesis is suppressed. However, the results show that a significant and negative linear relationship existed between these two fluxes at 37 of the sites. The mean linear slope value is −0.008 ± 0.001 µmol m−2 s−1 per W m−2 among the 64 sites analyzed. The slope value was not significantly different among the three gas analyzer models (LI-7500, LI-7500A, IRGASON/EC150) used at these sites, indicating that self-heating may not be the only reason for the apparent wintertime net CO2 uptake. These results suggest a systematic bias toward larger carbon uptakes in the FLUXNET sites that deploy open-path eddy covariance systems.

Transpiration represents more than 30% of the global land–atmosphere water exchange but is highly uncertain. Plant hydraulics was ignored in traditional land surface modeling, but recently plant hydraulics has been found to play an essential role in transpiration simulation. A new physical-based representation of plant hydraulic schemes (PHS) was recently developed and implemented in the Common Land Model (CoLM). However, it is unclear to what extent PHS can reduce these uncertainties. Here, we evaluated the PHS against measurements obtained at 81 FLUXNET sites. The transpiration of each site was estimated using an empirical evapotranspiration partitioning approach. The metric scores defined by the International Land Model Benchmarking Project (ILAMB) were used to evaluate the model performance and compare it with that of the CoLM default scheme (soil moisture stress (SMS)). The bias score of transpiration in PHS was higher than SMS for most sites, and more significant improvements were found in semi-arid and arid sites where transpiration was limited by soil moisture. The hydraulic redistribution in PHS optimized the soil water supply and thus improved the transpiration estimates. In humid sites, no significant improvement in seasonal or interannual variability of transpiration was simulated by PHS, which can be explained by the insensitivity of transpiration demand coupled to the photosynthesis response to precipitation. In arid and semi-arid sites, seasonal or interannual variability of transpiration was better captured by PHS than SMS, which was interpreted by the improved drought sensitivity for transpiration. Arid land is widespread and is expected to expand due to climate change, thus there is an urgent need to couple PHS in land surface models.

The influences of solar activity and large-scale climate modes (e.g. the El Nino/Southern Oscillation — ‘ENSO’) have been identified in many geophysical processes. However, few studies have attempted to investigate the frequency characteristics and corresponding spatial patterns of the interannual influence of either solar activity or large-scale climate modes on phenology. In this study, the influences of solar activity (represented by sunspot number ‘SSN’) and ENSO on the first leaf and bloom dates of the common lilac and cloned lilac in the United States were analyzed for time series spanning ≥ 33 years using the wavelet coherence method. The spatial patterns in the influence of ENSO on the first leaf and bloom dates were investigated for different times and periodicities, using time series of ≥ 20 years. The combined influences of solar activity and ENSO on the first leaf and bloom dates of lilacs were identified for most of the stations with records spanning ≥ 33 years. In the 11-year band, both increasing solar activity (SSN) and El Nino caused delays in the first leaf and bloom events of the cloned lilac during the 1980s in the northeastern United States. The frequency characteristics and the spatial patterns of the influence of ENSO on the first leaf day and first bloom day were essentially consistent, and such spatial patterns vary with time and periodicity.

Even though knowing the contributions of transpiration (T), soil and open water evaporation (E), and interception (I) to terrestrial evapotranspiration (ET = T + E + I) is crucial for understanding the hydrological cycle and its connection to ecological processes, the fraction of T is unattainable by traditional measurement techniques over large scales. Previously reported global mean T/(E + T + I) from multiple independent sources, including satellite-based estimations, reanalysis, land surface models, and isotopic measurements, varies substantially from 24% to 90%. Here we develop a new ET partitioning algorithm, which combines global evapotranspiration estimates and relationships between leaf area index (LAI) and T/(E + T) for different vegetation types, to upscale a wide range of published site-scale measurements. We show that transpiration accounts for about 57.2% (with standard deviation ± 6.8%) of global terrestrial ET. Our approach bridges the scale gap between site measurements and global model simulations,and can be simply implemented into current global climate models to improve biological CO2 flux simulations.

Publisher's version (útgefin grein), The isotopic composition of water vapour provides integrated perspectives on the hydrological histories of air masses and has been widely used for tracing physical processes in hydrological and climatic studies. Over the last two decades, the infrared laser spectroscopy technique has been used to measure the isotopic composition of water vapour near the Earth’s surface. Here, we have assembled a global database of high temporal resolution stable water vapour isotope ratios (δ18O and δD) observed using this measurement technique. As of March 2018, the database includes data collected at 35 sites in 15 Köppen climate zones from the years 2004 to 2017. The key variables in each dataset are hourly values of δ18O and δD in atmospheric water vapour. To support interpretation of the isotopologue data, synchronized time series of standard meteorological variables from in situ observations and ERA5 reanalyses are also provided. This database is intended to serve as a centralized platform allowing researchers to share their vapour isotope datasets, thus facilitating investigations that transcend disciplinary and geographic boundaries., This research has been supported by the National Science Foundation (Grant AGS-1520684 to X. L. and ATM-0546476 to T. G.) and a Faculty Development Grant from the College of Food, Agricultural, and Natural Resource Sciences, University of Minnesota (to T. G.). For the Camargue site, data acquisition was supported by the French CNRS-INSU-EC2CO program, and by “Région PACA”. For the Kourovka site, data acquisition was supported by the contract No.02.A03.21.0006 and by the research project No.3.6064.2017/8.9.

Tea plantations have expanded rapidly during the past several decades in China, the top tea-producing country, as a result of economic development, however, few studies have investigated the influence of tea plantations on the carbon cycle, especially from the perspective of climate change and increases in extreme weather events. Therefore, we employed combined observational and modeling methods to evaluate the water and carbon cycles at representative bamboo and tea plots in eastern China. Green tea growth and the corresponding water and carbon cycles were reproduced using the Community Land Model after applying fertilizer. Old-growth bamboo was reasonably simulated as broadleaf evergreen forest in this model. The mean observed soil respiration ranged from 1.79 to 2.57 and 1.34 to 1.50 &micro, mol m&minus, 2 s&minus, 1 at the bamboo and tea sites, respectively, from April 2016 to October 2017. The observed soil respiration decreased by 23% and 55% due to extreme dryness in August 2016 at the bamboo and tea plots, respectively, and the model reproduced these decreases well. The modeling results indicated that tea acted as a stronger carbon sink during spring and a stronger carbon source during autumn and winter compared with old-growth bamboo. The carbon cycle was affected more by extremely dry weather than by extremely wet weather in both the bamboo and tea plots. Extremely dry periods markedly reduced the carbon sink at both plots, although this trend was more pronounced at the tea plot.

Predicting river discharge and inundation is crucial for water resources management and flood hazard reduction; however, it is still unclear to what extent their variabilities can be captured on global scale. This study evaluates uncertainty sources in the quasi-global river discharge and inundation simulations using the Variable Infiltration Capacity (VIC) macroscale hydrologic model and the Catchment-based Macroscale Floodplain (CaMa-Flood) hydrodynamic model, forced with five high-resolution satellite precipitation datasets. The simulated discharge is first evaluated against more than 2852 sites selected from the Global Streamflow Indices and Metadata Archive (GSIM) dataset, and then the simulated inundation is compared with complementary multiple satellite observations. Globally, about 38% – 43% of the stations produce reasonable discharge simulations with positive Kling-Gupta Efficiency (KGE) on monthly time scale. The simulations show good agreement for flood fractions with mean correlations ranging from 0.47 to 0.62 for satellite detected events. The potential uncertainties sources of discharge and inundation simulation related to physics setting and forcing datasets, such as precipitation, land surface model, routing model, and observation from site and satellite are discussed, as well as future directions for improving large-scale model applications. By using default model settings, we hope our study can offer valuable insights into the applicability of flood simulations and provide guides for model development.

Since the early 1980s, large-scale revegetation has been implemented in Northwest China and has been found to be useful in desertification prevention. However, it remains unclear, how land cover changes affect local meteorological conditions, such as land surface temperature. In this study, the land surface temperature response to land-use changes was comparatively evaluated using micrometeorological observations from a cropland site, a mixed forest site, a shrubland site, and adjacent bare land sites in the Heihe River Basin, Northwest China. The surface temperature changes (ΔTs) are decomposed into contributions from changes in radiative forcing, heat resistance, evapotranspiration, soil heat flux and air temperature based on the intrinsic biophysical mechanism (IBM) and the two-resistance mechanism (TRM). The results indicate that 1) the IBM attribution method is more applicable than the TRM method in these arid ecosystems; 2) the influence of different types of vegetation cover on the surface temperature exhibits temporal variance on the diurnal and seasonal time scales; 3) the dominant biophysical components in the daytime of the growing season are evaporative cooling in the cropland paired sites and heat resistance change in the mixed forest paired sites, but these two components are both at a moderate level in the shrubland paired sites. This study provides a useful reference for local climate impact assessments when implementing environmental protection projects in similarly arid areas.

The drag coefficient $$(C_{D})$$ , experimentally determined from observed wind speed and surface stress, has been reported to increase in the low wind-speed range ( $$

Summary We observed stable isotopes in precipitation and atmospheric water vapor over a humid subtropical rice paddy field in Tsukuba, Japan, from June 2013 to May 2014. We used observed isotope ratios, in combination with an isotope-enabled general circulation model (GCM; Isotopes-incorporated Global Spectral Model: IsoGSM) to improve our understanding of the impacts of moisture sources and transport on the variability of water vapor isotopes. The isotopic measurements of water vapor and precipitation suggested that vapor isotopes in the study area were controlled by not only air-rain isotopic exchange, but also other kinetic effects associated with land evapotranspiration and large scale atmospheric circulation at the seasonal time scale. The contribution of land evapotranspiration to local water vapor content ( F ET ) was approximately 16.0 ± 12.3% as an annual average, with a summer maximum of 20.5 ± 12.9%. Our results show that large-scale atmospheric circulation is the primary control on the variability of near surface water vapor δ D . An IsoGSM tagging simulation experiment demonstrated that the large temporal variation of surface water vapor isotopes can primarily be attributed to advection and mixing of moisture from different oceanic source regions.

This study explores the utility of observations of deuterium excess (dx) of water vapor for attribution of vapor to remote source regions and local influences. A Lagrangian back trajectory model was combined with various parameterizations of the dx of ocean evaporation and land evapotranspiration to simulate daily vapor dx at a continental site, a marine site and a coastal site. The model reproduced reasonably well the observed variabilities in the vapor dx at the coastal and the marine site when water vapor at these sites were primarily influenced by large-scale advection from ocean sources. The simple parameterization relating dx of the ocean evaporation to relative humidity is a robust representation of the ocean isotopic evaporation. On the other hand, the model did poorly for the continental site and during the land evapotranspiration dominated months at the coastal and the marine site, confirming the published findings that the water vapor dx near the Earth’s surface can be significantly altered by land evapotranspiration and therefore is not a conserved tracer of humidity from the marine moisture source region. Several parameterizations for the dx of land evapotranspiration suggested by previous studies were tested with the trajectory model, but none brought improvement to the simulation of the dx at the continental site. Our study emphasizes that a fundamental challenge in isotopy hydrology is the lack of understanding of the different fractionation processes of 18O and D associated with land evapotranspiration.

The isotopic compositions of water fluxes provide valuable insights into the hydrological cycle and are widely used to quantify biosphere&ndash, atmosphere exchange processes. However, the combination of water isotope approaches with water flux components remains challenging. The Iso-SPAC (coupled heat, water with isotopic tracer in soil&ndash, plant&ndash, atmosphere-continuum) model is a useful framework for simulating the dynamics of water flux and its components, and for coupling with isotopic fractionation and mixing processes. Here, we traced the isotopic fractionation processes with separate soil evaporation (Ev) and transpiration (Tr), as well as their mixing in evapotranspiration (E) for simulating diurnal variations of isotope compositions in E flux (&delta, E). Three sub modules, namely isotopic steady state (ISS), non-steady-state (NSS), and NSS P&eacute, clet, were tested to determine the true value for the isotope compositions of plant transpiration (&delta, Tr) and &delta, E. In situ measurements of isotopic water vapor with the Keeling-plot approach for &delta, E and robust eddy covariance data for E agreed with the model output (R2 = 0.52 and 0.98, RMSD = 2.72&permil, and 39 W m&minus, 2), illustrating the robustness of the Iso-SPAC model. The results illustrate that NSS is a better approximation for estimating diurnal variations in &delta, Tr and &delta, E, specifically during the alternating periods of day and night. Leaf stomata conductance regulated by solar radiation controlled the diurnal variations in transpiration fraction (Tr/E). The study emphasized that transpiration and evaporation, respectively, acted to increase and decrease the &delta, 18O of water vapor that was affected by the diurnal trade-off between them.

Afforestation activities in the Kubuqi Desert, Inner Mongolia, China, have substantially increased tree and shrub coverage in this region. In this study, the response of the surface temperature to afforestation is simulated with the Weather Research and Forecasting model. The surface temperature changes are decomposed into contributions from the intrinsic surface biophysical effect and atmospheric feedback, using the theory of intrinsic biophysical mechanism. The effect of afforestation on the surface temperature is 1.34 K, &minus, 0.48 K, 2.09 K and 0.22 K for the summer daytime, the summer nighttime, the winter daytime and the winter nighttime, respectively, for the grid cells that have experienced conversion from bare soil to shrub. The corresponding domain mean values are 0.15 K, &minus, 0.2 K, 0.67 K, and 0.06 K. The seasonal variation of surface temperature change is mainly caused by changes in roughness and Bowen ratio. In the daytime, the surface temperature changes are dominated by the biophysical effect, with albedo change being the main biophysical factor. In the nighttime, the biophysical effect (mainly associated with roughness change) and the atmospheric feedback (mainly associated with change in the background air temperature) contribute similar amounts to the surface temperature changes. We conclude that the atmospheric feedback can amplify the influence of the surface biophysical effect, especially in the nighttime.