Search

Spring snowmelt occurs for a short duration on an annual time scale, but their timings considerably affect the carbon and hydrological cycle in high‐latitude ecosystems. Here, we developed a simple snowmelt model, treating the ecosystem surface as a bulk‐surface layer. Energy fluxes across this bulk surface and the snow‐soil boundary determine snow temperature and the energy utilized for snowmelt. Parameterizing the bulk surface using decade‐long eddy covariance site data from two Alaskan open black spruce forests offered an opportunity to quantitatively evaluate meteorological drivers affecting snowmelt timings without the needs for detailed canopy information. The sensitivity analysis suggested that the total snowfall on the forest floor, ranging from 0.35 m in 2016 to about 1 m in 2018 and 2020, was the most crucial driver for snowmelt timing. This factor accounted for a 10‐day difference in the interannual variations in snow disappearance dates. The importance of the snowfall varied from year to year, and in 2013, the late snowmelt was characterized by low air temperatures, which increased sensible heat loss from the snowpack. The importance of atmospheric radiation was revealed in relatively warm years, such as 2016 and 2019. Our modeling approach necessitates adjusting one empirical parameter that reflects the heat conductivity from the bulk surface to the snow, based on observations. Nevertheless, despite this need for adjustment, the bulk‐surface approach helps identify important meteorological drivers underlying observed snowmelt within a simple theoretical framework. Plain Language Summary: It is essential to understand why and how spring snowmelt occurs in boreal forests because of its impact on both the biological and hydrological processes in the ecosystem. However, meteorological drivers related to snowmelt often change simultaneously, which makes it challenging to determine which single driver is vital for snowmelt. To address this challenge, we constructed a simple snowmelt model that treats the ecosystem surface as a single bulk layer. The simple model bypasses the needs for detailed canopy information and is easily constrained by observed data. Applying the model to decadal observation data from Alaskan boreal forests, we found that snowfall, air temperature, and atmospheric radiation were important meteorological drivers for explaining interannual variations in snowmelt timing. Each of them explained about 1–2 weeks of snowmelt disappearance dates. We also demonstrated that the model helped explain why the snowmelt was late in 2013 and early in 2016 and 2019 and why snow disappearance dates differed between study sites. While a simple model has its limitations, it can be beneficial for understanding snowmelt characteristics within a simple theoretical framework. Key Points: A model‐based approach was introduced to delineate the roles of meteorological drivers on interannual variations in snowmelt timingSnowfall was the most important driver of the interannual variation in snowmelt timing followed by air temperature and atmospheric radiationLate snowmelt in 2013 was attributed to low air temperature, increasing sensible heat loss from the snowpack [ABSTRACT FROM AUTHOR]

Solar radiation‐topography interaction plays an important role in surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of solar radiation‐topography interaction over the TP. Land‐atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for solar radiation‐topography interaction improves E3SM simulation of surface climate. The winter cold bias in air temperature decreases from −4.57 to −3.79 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP's solar radiation‐topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts. Plain Language Summary: The Tibetan Plateau (TP) is characterized by high elevation and complex topography. Interaction between solar radiation and the undulating topography has important impacts on the regional surface energy balance and hydrologic cycle. Here we use Earth System Model simulations to show the local and remote impacts of the TP's solar radiation‐topography interaction on the surface climate of the Asian regions. Such interaction overall increases the air temperature especially in winter over the TP and reduces the summer precipitation in southern TP. Teleconnectedly, the interaction further alters the precipitation patterns in South and East Asia, by altering the atmospheric circulation that influences moisture transport and clouds. Accounting for such interaction generally improves the model performance when benchmarked against observations. These findings underscore the important roles of the TP's solar radiation‐topography interaction in modulating the climate of the local and remote Asian regions. Key Points: Solar radiation‐topography interaction over the Tibetan Plateau (TP) increases annual average regional near‐surface air temperature by 0.26 KSolar radiation‐topography interaction over the TP also affects the precipitation patterns in South and East AsiaIncluding solar radiation‐topography interaction improves the simulation of surface climate over the TP and Asian regions [ABSTRACT FROM AUTHOR]

Reliable precipitation simulation over the Tibetan Plateau (TP) remains a challenge, manifested by a prominent systematic wet bias in the warm season. Previous studies have generally neglected the potential linkage between surface radiation energy budget and precipitation bias. Prevalent scattered cumulus and thunderstorms over the TP in summer strongly influence surface radiation. A cloud fraction scheme considering subgrid temperature and humidity fluctuations is implemented in the WRF model and tested for a month‐long simulation. It is found that the scheme better reproduces the surface solar radiation compared to a default cloud fraction scheme in the WRF model. Using abundant surface observations, we find that overestimation of the downward surface shortwave radiation (DSSR) would lead to wet bias. DSSR overestimation contributes to higher surface temperature and larger evaporation and enhanced atmospheric instability, which favor more simulated convective precipitation. The study suggests that a better simulation of clouds and surface radiation would benefit precipitation simulation over the plateau. Plain Language Summary: Summer precipitation over the Tibetan Plateau (TP) is generally overestimated in general circulation models as well as regional weather forecasts and climate models. The prevailing "popcorn‐like" clouds over the TP in summer would strongly impact surface radiation. Considering the potential linkage between surface radiation energy budget and precipitation bias, a statistical cloud fraction and subgrid condensation scheme (GS‐PDF scheme) is implemented in the WRF model and tested for a month‐long simulation. The GS‐PDF scheme better captures clouds over the TP with more mid‐low cloud water (ice) than the default Xu‐Randall scheme. Increased mid‐low cloud water in the GS‐PDF scheme reduced simulated downward surface shortwave radiation, reduced simulated surface temperatures, atmospheric instabilities and convective precipitation, leading to alleviated wet bias over the TP. This study suggests that better simulations of cloud and surface radiation would be beneficial for simulations of hydrological cycles over the TP. Key Points: A new cloud macrophysics scheme considering subgrid temperature and humidity fluctuations is implemented in the WRF modelThe new macrophysics scheme reduced simulated downward surface shortwave radiation, surface temperatures and atmospheric instabilitiesA better simulation of clouds and surface radiation would benefit precipitation simulation over the Tibetan Plateau [ABSTRACT FROM AUTHOR]

Evaporation is controlled by soil moisture (SM) availability when conditions are not extremely wet. In such a moisture‐limited regime, land‐atmosphere coupling is active, and a chain of linked processes allow land surface anomalies to affect weather and climate. How frequently any location is in a moisture‐limited regime largely determines the intensity of land feedbacks on climate. Conventionally this has been quantified by shifting probability distributions of SM, but the boundary between moisture‐limited and energy‐limited regimes, called the critical soil moisture (CSM) value, can also change. CSM is an emergent property of the land‐atmosphere system, determined by the balance of radiative, thermal and kinetic energy factors. We propose a novel framework to separate the contributions of these separate effects on the likelihood that SM lies in the moisture‐limited regime. We confirm that global warming leads to a more moisture‐limited world. This is attributed to reduced SM in most regions: the moisture effect. CSM changes mainly due to shifts in the surface energy budget, significantly affecting 27.7% of the globe in analyzed climate change simulations. However, consistency among Earth system models regarding CSM change is low. The poor agreement hints that variability of CSM in models and the factors that determine CSM are not well represented. The fidelity of CSM in Earth system models has been overlooked as a factor in water cycle projections. Careful assessment of CSM in nature and for model development should be a priority, with potential benefits for multiple research fields including meteorology, hydrology, and ecology. Plain Language Summary: In the water cycle, moisture‐limited conditions exist when evaporation is limited by a lack of soil moisture. This occurs when soil moisture lies below a threshold called the critical soil moisture (CSM). As evaporation affects atmospheric temperature and humidity, the value of CSM is important for weather and climate, as it determines when land states can affect the atmosphere. Climate change simulations agree the world will become more moisture‐limited, mainly attributed to drying soils, but the value of CSM can also change because it is determined in part by local meteorology as part of a land‐atmosphere feedback. This study shows that simulations from different climate change models consistently agree on an overall drying of the soil in the future. Changes in CSM are also simulated, but Earth system models do not agree on the magnitude or direction of CSM change in most places. This disagreement introduces uncertainty in the places and times when soil moisture controls evaporation and its impact on the atmosphere. Models have not historically been calibrated or validated for CSM simulation; we advocate for more attention to be paid to observing and modeling CSM due to its importance for meteorology, hydrology, and ecology in a changing climate. Key Points: An increasingly moisture‐limited world under global warming depends on more than just reduced soil moistureEarth system models inconsistently simulate the critical soil moisture value that separates moisture‐limited and energy‐limited regimesPoor agreement among models on projected changes in critical soil moisture calls for greater focus on its observation and validation [ABSTRACT FROM AUTHOR]

Summary: Understanding the effects of temperature and moisture on radial growth is vital for assessing the impacts of climate change on carbon and water cycles. However, studies observing growth at sub‐daily temporal scales remain scarce.We analysed sub‐daily growth dynamics and its climatic drivers recorded by point dendrometers for 35 trees of three temperate broadleaved species during the years 2015–2020. We isolated irreversible growth driven by cambial activity from the dendrometer records. Next, we compared the intra‐annual growth patterns among species and delimited their climatic optima.The growth of all species peaked at air temperatures between 12 and 16°C and vapour pressure deficit (VPD) below 0.1 kPa. Acer pseudoplatanus and Fagus sylvatica, both diffuse‐porous, sustained growth under suboptimal VPD. Ring‐porous Quercus robur experienced a steep decline of growth rates with reduced air humidity. This resulted in multiple irregular growth peaks of Q. robur during the year. By contrast, the growth patterns of the diffuse‐porous species were always right‐skewed unimodal with a peak in June between day of the year 150–170.Intra‐annual growth patterns are shaped more by VPD than temperature. The different sensitivity of radial growth to VPD is responsible for unimodal growth patterns in both diffuse‐porous species and multimodal growth pattern in Q. robur. [ABSTRACT FROM AUTHOR]

Summary: Photosynthetic water‐use efficiency (WUE) describes the link between terrestrial carbon (C) and water cycles. Estimates of intrinsic WUE (iWUE) from gas exchange and C isotopic composition (δ13C) differ due to an internal conductance in the leaf mesophyll (gm) that is variable and seldom computed.We present the first direct estimates of whole‐tree gm, together with iWUE from whole‐tree gas exchange and δ13C of the phloem (δ13Cph). We measured gas exchange, online 13C‐discrimination, and δ13Cph monthly throughout spring, summer, and autumn in Eucalyptus tereticornis grown in large whole‐tree chambers. Six trees were grown at ambient temperatures and six at a 3°C warmer air temperature; a late‐summer drought was also imposed.Drought reduced whole‐tree gm. Warming had few direct effects, but amplified drought‐induced reductions in whole‐tree gm. Whole‐tree gm was similar to leaf gm for these same trees. iWUE estimates from δ13Cph agreed with iWUE from gas exchange, but only after incorporating gm. δ13Cph was also correlated with whole‐tree 13C‐discrimination, but offset by −2.5 ± 0.7‰, presumably due to post‐photosynthetic fractionations.We conclude that δ13Cph is a good proxy for whole‐tree iWUE, with the caveats that post‐photosynthetic fractionations and intrinsic variability of gm should be incorporated to provide reliable estimates of this trait in response to abiotic stress. [ABSTRACT FROM AUTHOR]

Climate change is intensifying the hydrologic cycle globally, increasing both the size and frequency of extreme precipitation events, or deluges. Arid and semi‐arid ecosystems are expected to be particularly responsive to this change because their ecological processes are largely driven by distinct soil moisture pulses. However, since soil moisture, air temperature and plant phenology vary throughout the growing season, deluges will likely have differing impacts on these systems depending on when they occur.We conducted a field experiment to assess how the seasonal timing (early, middle or late growing season) of a single deluge (70‐mm precipitation event) altered key ecological processes in the semi‐arid shortgrass steppe of North America.Regardless of timing, a single deluge stimulated most ecosystem processes, but a deluge at mid‐season caused the greatest increase in soil respiration, canopy greenness, above‐ground net primary production (ANPP) and growth and flowering of the dominant plant species Bouteloua gracilis. In contrast, below‐ground net primary production (BNPP) was insensitive to deluge timing, with a consistent BNPP increase in all the deluge treatments that was almost twice as large as the ANPP response. This BNPP response was largely driven by enhanced root production at the 10–20 cm, rather than 0–10 cm, soil depth.Synthesis. In a semi‐arid ecosystem, a single deluge can have season‐long impacts on many ecosystem processes, but responses can be mediated by event timing. Therefore, predicting responses of semi‐arid ecosystems to more dynamic precipitation regimes, and subsequent impacts on the global carbon budget, will require knowledge of how deluge magnitude, frequency and timing are being altered by climate change. [ABSTRACT FROM AUTHOR]

Hydrologic intensity is often quantified using precipitation without directly incorporating atmospheric water demand. We develop a hydrologic intensity index called the surplus deficit intensity (SDI) index that accounts for variation in supply and demand. SDI is the standardized sum of standardized surplus intensity (mean of daily surplus when supply > demand) and deficit time (mean of consecutive days when demand > supply). Using an observational ensemble of global daily precipitation and atmospheric water demand during 1979–2017, we document widespread hydrologic intensification (SDI; +0.11 z‐score per decade) driven primarily by increased surplus intensity. Using a climate model ensemble of the United States, hydrologic intensification is projected for the mid‐21st century (+0.86 in z‐score compared to 1971–2000), producing greater apparent intensification when compared to an index that does not explicitly incorporate demand. While incorporating demand had a minor effect on observed hydrologic intensification, it doubles hydrological intensification for the mid‐21st century. Plain Language Summary: Increasing air temperatures have resulted in an intensification, or acceleration, of the terrestrial hydrologic cycle, which is defined as an increase of the water fluxes (precipitation and evapotranspiration) between the surface and the atmosphere. Efforts to quantify hydrologic intensification have traditionally only considered "supply" variables such as precipitation rates without considering "demand" that varies over space and time. For this work we develop a method to quantify hydrologic intensification using supply and demand. This approach shows widespread hydrologic intensification from 1979–2017 across much of the global land surface, which is expected to continue into the future. We additionally compare this new method to a previously developed method that uses only supply without explicitly incorporating demand. Incorporating demand results in a notable hydrologic intensification compared to methods that only use supply or a simplified representation of supply and demand. This work suggests that demand needs to be considered when quantifying hydrologic intensification. Key Points: We develop a hydrologic intensity metric that incorporates daily supply and demand using precipitation and reference evapotranspirationWidespread hydrologic intensification occurred over the past four decades and will continue into the futureAdding demand couples intensity metrics to ecohydrologic conditions and produces greater increases than metrics with static demand [ABSTRACT FROM AUTHOR]