Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

Senior Lecturer in Hydrology



+44 (0)20 7594 6004a.paschalis




407Skempton BuildingSouth Kensington Campus





Publication Type

43 results found

Paschalis A, De Kauwe MG, Sabot M, Fatichi Set al., 2024, When do plant hydraulics matter in terrestrial biosphere modelling?, Glob Chang Biol, Vol: 30

The ascent of water from the soil to the leaves of vascular plants, described by the study of plant hydraulics, regulates ecosystem responses to environmental forcing and recovery from stress periods. Several approaches to model plant hydraulics have been proposed. In this study, we introduce four different versions of plant hydraulics representations in the terrestrial biosphere model T&C to understand the significance of plant hydraulics to ecosystem functioning. We tested representations of plant hydraulics, investigating plant water capacitance, and long-term xylem damages following drought. The four models we tested were a combination of representations including or neglecting capacitance and including or neglecting xylem damage legacies. Using the models at six case studies spanning semiarid to tropical ecosystems, we quantify how plant xylem flow, plant water storage and long-term xylem damage can modulate overall water and carbon dynamics across multiple time scales. We show that as drought develops, models with plant hydraulics predict a slower onset of plant water stress, and a diurnal variability of water and carbon fluxes closer to observations. Plant water storage was found to be particularly important for the diurnal dynamics of water and carbon fluxes, with models that include plant water capacitance yielding better results. Models including permanent damage to conducting plant tissues show an additional significant drought legacy effect, limiting plant productivity during the recovery phase following major droughts. However, when considering ecosystem responses to the observed climate variability, plant hydraulic modules alone cannot significantly improve the overall model performance, even though they reproduce more realistic water and carbon dynamics. This opens new avenues for model development, explicitly linking plant hydraulics with additional ecosystem processes, such as plant phenology and improved carbon allocation algorithms.

Journal article

Huang WTK, Masselot P, Bou-Zeid E, Fatichi S, Paschalis A, Sun T, Gasparrini A, Manoli Get al., 2023, Economic valuation of temperature-related mortality attributed to urban heat islands in European cities., Nat Commun, Vol: 14

As the climate warms, increasing heat-related health risks are expected, and can be exacerbated by the urban heat island (UHI) effect. UHIs can also offer protection against cold weather, but a clear quantification of their impacts on human health across diverse cities and seasons is still being explored. Here we provide a 500 m resolution assessment of mortality risks associated with UHIs for 85 European cities in 2015-2017. Acute impacts are found during heat extremes, with a 45% median increase in mortality risk associated with UHI, compared to a 7% decrease during cold extremes. However, protracted cold seasons result in greater integrated protective effects. On average, UHI-induced heat-/cold-related mortality is associated with economic impacts of €192/€ - 314 per adult urban inhabitant per year in Europe, comparable to air pollution and transit costs. These findings urge strategies aimed at designing healthier cities to consider the seasonality of UHI impacts, and to account for social costs, their controlling factors, and intra-urban variability.

Journal article

Zhang Z, Dobson B, Moustakis Y, Meili N, Mijic A, Butler A, Athanasios Pet al., 2023, Assessing the co-benefits of urban greening coupled with rainwater harvesting management under current and future climates across USA cities, Environmental Research Letters, Vol: 18, Pages: 1-11, ISSN: 1748-9326

Globally, urban areas face multiple challenges owing to climate change. Urban greening (UG) is an excellent option for mitigating flood risk and excess urban heat. Rainwater harvesting (RWH) systems can cope with plant irrigation needs and urban water management. In this study, we investigated how UG and RWH work together to mitigate environmental risks. By incorporating a new RWH module into the urban ecohydrological model Urban Tethys-Chloris (UT&C), we tested different uses of intervention approaches for 28 cities in the USA, spanning a variety of climates, population densities, and urban landscapes. UT&C was forced by the latest generation convection-permitting climate model simulations of the current (2001–2011) and end-of-century (RCP8.5) climate. Our results showed that neither UG nor RWH, through the irrigation of vegetation, could significantly contribute to mitigating the expected strong increase in 2 m urban canyon temperatures under a high-emission scenario. RWH alone can sufficiently offset the intensifying surface flood risk, effectively enhance water saving, and support UG to sustain a strong urban carbon sink, especially in dry regions. However, in these regions, RWH cannot fully fulfill plant water needs, and additional measures to meet irrigation demand are required to maximize carbon sequestration by urban vegetation.

Journal article

Pappas C, Babst F, Fatichi S, Klesse S, Paschalis A, Peters RLet al., 2023, A Circumpolar Perspective on the Contribution of Trees to the Boreal Forest Carbon Balance, Advances in Global Change Research, Pages: 271-294

Partitioned estimates of the boreal forest carbon (C) sink components are crucial for understanding processes and developing science-driven adaptation and mitigation strategies under climate change. Here, we provide a concise tree-centered overview of the boreal forest C balance and offer a circumpolar perspective on the contribution of trees to boreal forest C dynamics. We combine an ant’s-eye view, based on quantitative in situ observations of C balance, with a bird’s-eye perspective on C dynamics across the circumboreal region using large-scale data sets. We conclude with an outlook addressing the trajectories of the circumboreal C dynamics in response to projected environmental changes.

Book chapter

Chiu CTF, Wang K, Paschalis A, Erfani T, Peleg N, Fatichi S, Theeuwes N, Manoli Get al., 2022, An analytical approximation of urban heat and dry islands and their impact on convection triggering, Urban Climate, Vol: 46, Pages: 1-17, ISSN: 2212-0955

It is well known that cities increase air and surface temperatures compared to their rural surroundings, the so-called urban heat island (UHI) effect. However, the associated changes in atmospheric humidity (also known as urban dry island, UDI) and convection triggering remain largely unexplored and it is still unclear how urban modifications of the surface energy budget influence the diurnal evolution of temperature and humidity in the Atmospheric Boundary Layer (ABL) and ultimately control the initiation of convective clouds.Here we quantify the impact of different urban settings and free atmospheric conditions on UHI, UDI, and convection triggers by means of a zero-order model of the ABL. Specifically, we derive an approximate solution for urban-rural changes in surface energy fluxes and ABL potential temperature and humidity and we investigate the crossing between the ABL height and the lifting condensation level (LCL) which is a proxy for the triggering of convective clouds. We show that urban areas are generally warmer and drier, thus causing an increase in both ABL and LCL heights. However, the response of the ABL-LCL crossing to surface conditions is non-linear and there exists a range of free atmosphere conditions for which changes in imperviousness can impact convective clouds.

Journal article

Paschalis A, Bonetti S, Guo Y, Fatichi Set al., 2022, On the uncertainty induced by pedotransfer functions in terrestrial biosphere modeling, Water Resources Research, Vol: 58, Pages: 1-18, ISSN: 0043-1397

Hydrological, ecohydrological, and terrestrial biosphere models depend on pedotransfer functions for computing soil hydraulic parameters based on easily measurable variables, such as soil textural and physical properties. Several pedotransfer functions have been derived in the last few decades, providing divergent estimates of soil hydraulic parameters. In this study, we quantify how uncertainties embedded in using different pedotransfer functions propagate to ecosystem dynamics, including simulated hydrological fluxes and vegetation response to water availability. Using a state-of-the-art ecohydrological model applied at 79 sites worldwide, we show that uncertainties related to pedotransfer functions can affect both hydrological and vegetation dynamics. Uncertainties in evapotranspiration, plant productivity, and vegetation structure, quantified as leaf area, are in the order of ∼10% at annual time scales. Runoff and groundwater recharge uncertainties are one order of magnitude larger. All uncertainties are largely amplified when small-scale topography is taken into account in a distributed domain, especially for water-limited ecosystems with low permeability soils. Overall, pedotransfer function related uncertainties for a given soil type are higher than uncertainties across soil types in both hydrological and ecosystem dynamics. The magnitude of uncertainties is climate-dependent but not soil type-dependent. Evapotranspiration, vegetation structure, and plant productivity uncertainties are higher in water-limited semiarid climates, whereas groundwater recharge uncertainties are higher in climates where potential evapotranspiration is comparable to precipitation.

Journal article

Peleg N, Ban N, Gibson MJ, Chen AS, Paschalis A, Burlando P, Leitão JPet al., 2022, Mapping storm spatial profiles for flood impact assessments, Advances in Water Resources, Vol: 166, Pages: 104258-104258, ISSN: 0309-1708

Synthetic design storms are often used to plan new drainage systems or assess flood impacts on infrastructure.To simulate extreme rainfall events under climate change, design storms can be modified to match a differentreturn frequency of extreme rainfall events as well as a modified temporal distribution of rainfall intensities.However, the same magnitude of change to the rainfall intensities is often applied in space. Several hydrologicalapplications are limited by this. Climate change impacts on urban pluvial floods, for example, require the useof 2D design storms (rainfall fields) at sub-kilometer and sub-hourly scales. Recent kilometer scale climatemodels, also known as convection-permitting climate models (CPM), provide rainfall outputs at a high spatialresolution, although rainfall simulations are still restricted to a limited number of climate scenarios and timeperiods. We nevertheless explored the potential use of rainfall data obtained from these models for hydrologicalflood impact studies by introducing a method of spatial quantile mapping (SQM). To demonstrate the newmethodology, we extracted high-resolution rainfall simulations from a CPM for four domains representingdifferent urban areas in Switzerland. Extreme storms that are plausible under the present climate conditionswere simulated with a 2D stochastic rainfall model. Based on the CPM-informed stochastically generatedrainfall fields, we modified the design storms to fit the future climate scenario using three different methods:the SQM, a uniform quantile mapping, and a uniform adjustment based on a rainfall–temperature relationship.Throughout all storms, the temporal distribution of rainfall was the same. Using a flood model, we assessedthe impact of different rainfall adjustment methods on urban flooding. Significant differences were found inthe flood water depths and areas between the three methods. In general, the SQM method results in a higherflood impact than the storms that were modifie

Journal article

Zhang Z, Paschalis A, Mijic A, Meili N, Manoli G, Van Reeuwijk M, Fatichi Set al., 2022, A mechanistic assessment of urban heat island intensities and drivers across climates, Urban Climate, Vol: 44, Pages: 1-18, ISSN: 2212-0955

The urban heat island effect (UHI) has been widely observed globally, causing climate,health, and energy impacts in cities. The UHI intensities have been found to largelydepend on background climate and the properties of the urban fabric. Yet, a completemechanistic understanding of how UHIs develop at a global scale is still missing. Usingan urban ecohydrological and land-surface model (urban Tethys-Chloris) incombination with multi-source remote sensing data, we performed simulations for 49large urban clusters across the Northern Hemisphere in 2009-2019 and analysed howsurface and canopy air UHIs (SUHI and CUHI, respectively) develop during day andnight. Biophysical drivers triggering the development of SUHIs and CUHIs have similardependencies on background climate, but with different magnitudes. In humid regionsdaytime UHIs can be largely explained by the urban-rural difference inevapotranspiration, whereas heat convection and conduction are important in aridareas. Plant irrigation can largely promote daytime urban evapotranspiration only inarid and semi-arid climates. During night, heat conduction from the urban fabric to theenvironment creates large UHIs mostly in warm arid regions. Overall, this studypresents a mechanistic quantification of how UHIs develop worldwide and proposesviable solutions for sustainable climate-sensitive mitigation strategies.

Journal article

Parolari A, Paschalis A, 2022, Precipitation variability can bias estimates of ecological controls on ecosystem productivity response to precipitation change, Ecohydrology, Vol: 15, Pages: 1-13, ISSN: 1936-0584

Annual vegetation aboveground net primary productivity (ANPP) exhibits a non-linear dependence on annual precipitation. A common pattern of non-linearity, called asymmetry, arises when productivity responses in wet years are larger than declines in dry years. To date, ANPP asymmetry has been attributed primarily to vegetation water stress, an internal ecosystem response to precipitation and soil water availability. However, when quantified via the asymmetry index (AI) estimated from productivity measurements, the asymmetry can be a sampling artefact that arises from a positively skewed annual precipitation distribution. In this paper, we aimed to separate the sampling effect (from external precipitation variability) from the non-linear response of the system (the internal ecosystem dynamics). We constructed a probabilistic model that integrates the precipitation distribution with the precipitation-productivity response curve (PPT-ANPP curve), derived using empirical formulae and a process-based soil water balance model. The model was used to derive the probability density function of AI and to attribute its shape to the PPT distribution and the PPT-ANPP response curve. The models were compared to data from 47 grasslands. Results demonstrated that positively skewed precipitation produces a positive AI as a statistical artefact. The non-linear ecosystem PPT-ANPP dependence can further enhance or dampen this statistical artefact. In all sites, the precipitation skew highly affected the probability of correctly identifying asymmetry using AI. Observed negative asymmetry arises from a larger soil water holding capacity and positive asymmetry from plant water stress. More robust statistical indicators of non-linear ecological responses to climate variability are needed to improve ecosystem forecasts.

Journal article

Meili N, Paschalis A, Manoli G, Fatichi Set al., 2022, Diurnal and seasonal patterns of global urban dry islands, Environmental Research Letters, Vol: 17, ISSN: 1748-9326

Urban heat islands (UHIs) are a widely studied phenomenon, while research on urban-rural differences in humidity, the so called urban dry or moisture islands (UDIs, UMIs), is less common and a large-scale quantification of the seasonal and diurnal patterns of the UDI is still lacking. However, quantification of the UDI/UMI effect is essential to understand the impacts of humidity on outdoor thermal comfort, building energy consumption, and urban ecology in cities worldwide. Here, we use a set of globally distributed air temperature and humidity measurements (1089 stations) to quantify diurnal and seasonal patterns of UHI and UDI resulting from rapid urbanization over many regions of the world. The terms 'absolute UDI' and 'relative UDI' are defined, which quantify urban–rural differences in actual and relative humidity metrics, respectively.Results show that absolute UDI is largest during daytime with the peak humidity decrease in urban areas occurring during late afternoon hours. In contrast, relative UDI is largest during night and the peak urban relative humidity (RH) decrease and vapor pressure deficit (VPD) increase occurs in the late evening hours with values of around −10% to −11% for RH and 2.9–3.6 hPa for VPD between 20–00 local time during summer. Relative and absolute UDIs are largest during the warm season, except for daytime RH UDI, which does not show any seasonal pattern. In agreement with literature, canopy air UHI is shown to be a nighttime phenomenon, which is larger during summer than winter. Relative UDI is predominantly caused by changes in actual humidity during day and UHI during nighttime.

Journal article

Moustakis Y, Fatichi S, Onof CJ, Paschalis Aet al., 2022, Insensitivity of ecosystem productivity to predicted changes in fine‐scale rainfall variability, Journal of Geophysical Research: Biogeosciences, Vol: 127, Pages: 1-21, ISSN: 2169-8953

Changes in rainfall associated with climate change are expected to affect the tightly coupled water-carbon ecosystem dynamics. Here, we study the effects of altered rainfall at 33 sites in North America, as projected by the high-resolution/high-fidelity ( ∼ 4km, 1h) continental-wide WRF convection-permitting model under a high-emission scenario (RCP 8.5). We make use of a stochastic weather generator to extend WRF outputs, accounting for natural variability and simultaneously separate the changes in total rainfall, its seasonality, and its intraseasonal pattern. We used these rainfall scenarios to study ecosystem responses with the state-of-the-art Tethys-Chloris terrestrial biosphere model. Model simulations suggest that increases in mean annual rainfall dominate ecosystem responses at dry sites, while wet sites are less sensitive to rainfall changes. Sites of intermediate wetness face reductions in productivity, due to reduced growing season rainfall and increased water losses under altered seasonality, which outpace any possible benefits induced by increases in mean annual totals. Changes in the fine-scale temporal structure of rainfall have an insignificant impact on ecosystem productivity and only alter hydrological dynamics, contradicting expectations based on some field experiments, which, however, are not tailored to directly quantify climate change impacts, but rather to understand the mechanisms leading to ecosystem responses. We further demonstrate how approaches following the ”fewer but larger rainfall events” concept might exacerbate ecosystem responses.

Journal article

Chen Y, Paschalis A, Wang L-P, Onof Cet al., 2021, Can we estimate flood frequency with point-process spatial-temporal rainfall models?, Journal of Hydrology, Vol: 600, ISSN: 0022-1694

Stochastic rainfall models are commonly used in practice for long-term flood risk management. One of the most widely used model types is based on point processes. Despite the widespread use of such models, whether their known simplifications in describing the space-time structure of rainfall will affect the accuracy of flood estimation has not been quantified. In this study, we quantify the biases introduced by the rainfall model limitations to flood estimates intwo medium-sized river catchments (717 km2and 844 km2) in the South East of the UK. To achieve this, we used nine years of hourly radar rainfall data, a dense network of hourly rain gauges, a spatial-temporal rainfall stochastic model based on point processes, and a fully distributed hydrological model. We modelled the corresponding catchment water dynamics using observed and simulated hourly rainfall and then assessed whether the errors introduced by the stochastic model will propagate in the river flow dynamics. Our results show that the stochastic rainfall model properly captures the point-scale rainfall statistics, including point extremes and the cross-site spatial correlations. However, the model results in a bias on extremes of areal statistics, including an overestimation of the areal reduction factor, extreme areal mean precipitation, and the areal fraction of rain (wet area ratio). Using this as input for continuous hydrological simulations, we find that the flow duration curves are well preserved, particularly in the high flow seasons (relative bias is less than 7%). The model also reproduces well the flood frequency curves at a daily scale with an averaged relative bias of 0.36-16.9% at 10-year return levels, confirming its ability to infer the long-term flood risk for medium-sized catchments. However, the summer-season hourly peak discharge is highly overestimated with a relative bias of over 163.5% at the same return level. The overestimation in summer hourly peak discharge is3 explained by the

Journal article

Zhang Z, Paschalis A, Mijic A, 2021, Planning London’s green spaces in an integrated water management approach to enhance future resilience in urban stormwater control, Journal of Hydrology, Vol: 597, ISSN: 0022-1694

Vegetation, as a fundamental element of urban green infrastructure, plays a vital role in mitigating urban flooding. Green infrastructure performance in mitigating floods depends on plant responses to meteorological forcing. This puts urban green infrastructure in risk under a changing climate. In this study, the resilience and efficiency of London’s green infrastructure under climate change is evaluated. The coupled water and carbon dynamics were evaluated using a mechanistic ecohydrological model forced with the new generation of 2018 UK Climate Projections (UKCP18).It was found that despite overall reductions of runoff production in London under climate change in winter/autumn, current urban green infrastructure in London can lose its efficiency due to the elevated levels of plant water stress unless it operates in an integrated manner with the traditional grey infrastructure drainage system. Plant water stress induced mostly by changes in climate is expected to limit vegetation performance during the end of growing seasons. The negative effects of varying climatic factors on vegetation dynamics can only be partially alleviated by the positive effects of the elevated CO2 concentration level, and are highly uncertain due to the large uncertainty of climate projections.

Journal article

Paschalis A, Chakraborty TC, Fatichi S, Meili N, Manoli Get al., 2021, Urban forests as main regulator of the evaporative cooling effect in cities, AGU Advances, Vol: 2, Pages: 1-14, ISSN: 2576-604X

Higher temperatures in urban areas expose a large fraction of the human population to potentially dangerous heat stress. Green spaces are promoted worldwide as local and city-scale cooling strategies but the amount, type, and functioning of vegetation in cities lack quantification and their interaction with urban climate in different settings remains a matter of debate. Here we use state-of-the-art remote sensing data from 145 city clusters to disentangle the drivers of surface urban heat islands (SUHI) intensity and quantify urban-rural differences in vegetation cover, species composition, and evaporative cooling. We show that nighttime SUHIs are affected mostly by abiotic factors, while daytime SUHIs are highly correlated with vegetation characteristics and the wetness of the background climate. Magnitude and seasonality of daytime SUHIs are controlled by urban-rural differences in plant transpiration and leaf area, which explain the dependence of SUHIs on wetness conditions. Leaf area differences are caused primarily by changes in vegetation type and a loss of in-city forested areas, highlighting the importance of maintaining “natural reserves” as a sustainable heat mitigation policy.

Journal article

Dobson B, Jovanovic T, Chen Y, Paschalis A, Butler A, Mijic Aet al., 2021, Integrated modelling to support analysis of COVID-19 impacts on London's water system and in-river water quality, Frontiers in Water, Vol: 3, Pages: 1-18, ISSN: 2624-9375

Due to the COVID-19 pandemic, citizens of the United Kingdom were required to stay at home for many months in 2020. In the weeks before and months following lockdown, including when it was not being enforced, citizens were advised to stay at home where possible. As a result, in a megacity such as London, where long-distance commuting is common, spatial and temporal changes to patterns of water demand are inevitable. This, in turn, may change where people’s waste is treated and ultimately impact the in-river quality of effluent receiving waters. To assess large scale impacts, such as COVID-19, at the city scale, an integrated modelling approach that captures everything between households and rivers is needed. A framework to achieve this is presented in this study and used to explore changes in water use and the associated impacts on wastewater treatment and in-river quality as a result of government and societal responses to COVID-19. Our modelling results revealed significant changes to household water consumption under a range of impact scenarios, however, they only showed significant impacts on pollutant concentrations in household wastewater were in central London. Pollutant concentrations in rivers simulated by the model were most sensitive in the tributaries of the River Thames, highlighting the vulnerability of smaller rivers and the important role that they play in diluting pollution. Modelled ammonia and phosphates were found to be the pollutants that rivers were most sensitive to because their main source in urban rivers is domestic wastewater that was significantly altered during the imposed mobility restrictions. A model evaluation showed that we can accurately validate individual model components (i.e., water demand generator) and 30emphasised need for continuous water quality measurements. Ultimately, the work provides a basis for further developments of water systems integration approaches to project changes under never-before seen scenarios.

Journal article

Moustakis Y, Papalexiou SM, Onof CJ, Paschalis Aet al., 2021, Seasonality, intensity, and duration of rainfall extremes change in a warmer climate, Earth's Future, Vol: 9, Pages: 1-15, ISSN: 2328-4277

Precipitation extremes are expected to intensify under climate change with consequent impacts in flooding and ecosystem functioning. Here we use station data and high‐resolution simulations from the WRF convection permitting climate model (∼4 km, 1 h) over the US to assess future changes in hourly precipitation extremes. It is demonstrated that hourly precipitation extremes and storm depths are expected to intensify under climate change and what is now a 20‐year rainfall will become a 7‐year rainfall on average for ∼ 75% of gridpoints over the US. This intensification is mostly expressed as an increase in rainfall tail heaviness. Statistically significant changes in the seasonality and duration of rainfall extremes are also exhibited over ∼ 95% of the domain. Our results suggest more non‐linear future precipitation extremes with shorter spell duration that are distributed more uniformly throughout the year.

Journal article

Chen Y, Paschalis A, Kendon E, Kim D, Onof Cet al., 2021, Changing spatial structure of summer heavy rainfall, using convection‐permitting ensemble, Geophysical Research Letters, Vol: 48, ISSN: 0094-8276

Subdaily rainfall extremes have been found to intensify, both from observations and climate model simulations, but much uncertainty remains regarding future changes in the spatial structure of rainfall events. Here, future changes in the characteristics of heavy summer rainfall are analyzed by using two sets (1980–2000, 2060–2080) of 12‐member 20‐year‐long convection‐permitting ensemble simulations (2.2 km, hourly) over the UK. We investigated how the peak intensity, spatial coverage and the speed of rainfall events will change and how those changes jointly affect hourly extremes at different spatial scales. We found that in addition to the intensification of heavy rainfall events, the spatial extent tends to increase in all three subregions, and by up to 49.3% in the North‐West. These changes act to exacerbate intensity increases in extremes for most of spatial scales (North: 30.2%–34.0%, South: 25.8%). The increase in areal extremes is particularly pronounced for catchments with sizes 20–500 km2.

Journal article

Moustakis I, Onof CJ, Paschalis A, 2020, Atmospheric convection, dynamics and topography shape the scaling pattern of hourly rainfall extremes with temperature globally, Communications Earth & Environment, Vol: 1, Pages: 1-9, ISSN: 2662-4435

Precipitation extremes (PEx) are expected to increase as ground temperature rises with a rate similarto the air's water holding capacity 7%=K (Clausius-Clapeyron; CC). Recent studies have been inconclusive on the robustness and global consistency of this behavior. Here, we use hourly weatherstations, 40 years of climate reanalysis and two convection permitting models to unravel the globalpattern of PEx scaling with temperature at the hourly scale for the rst time and identify hotspotsof divergence from thermodynamical expectations. We show that in high- and mid-latitudes PExclosely follows a CC scaling, while divergence occurs over the tropics and subtropics. Local features of atmospheric convection, larger-scale dynamics and orography, affect the dependence of PEx on surfacetemperature.

Journal article

Paschalis A, Fatichi S, Zscheischler J, Ciais P, Bahn M, Boysen L, Chang J, De Kauwe M, Estiarte M, Goll D, Hanson PJ, Harper AB, Hou E, Kigel J, Knapp AK, Larsen KS, Li W, Lienert S, Luo Y, Meir P, Nabel JEMS, Ogaya R, Parolari AJ, Peng C, Peñuelas J, Pongratz J, Rambal S, Schmidt IK, Shi H, Sternberg M, Tian H, Tschumi E, Ukkola A, Vicca S, Viovy N, Wang Y-P, Wang Z, Williams K, Wu D, Zhu Qet al., 2020, Rainfall-manipulation experiments as simulated by terrestrial biosphere models: where do we stand?, Global Change Biology, Vol: 26, Pages: 3336-3355, ISSN: 1354-1013

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of ten terrestrial biosphere models to reproduce observed sensitivity of ecosystem productivity to rainfall changes at ten sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are: (a) Inter-model variation is generally large and model agreement varies with time scales. In severely water limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent gross primary productivity. In more mesic sites model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) time scales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress i

Journal article

Fatichi S, Manzoni S, Or D, Paschalis Aet al., 2019, A mechanistic model of microbially mediated soil biogeochemical processes: a reality check, Global Biogeochemical Cycles: an international journal of global change, Vol: 33, Pages: 620-648, ISSN: 0886-6236

Present gaps in the representation of key soil biogeochemical processes such as the partitioning of soil organic carbon (SOC) among functional components, microbial biomass and diversity, and the coupling of carbon and nutrient cycles present a challenge to improving the reliability of projected soil carbon dynamics. We introduce a new soil biogeochemistry module linked with a well‐tested terrestrial biosphere model T&C. The module explicitly distinguishes functional SOC components. Extracellular enzymes and microbial pools are differentiated based on the functional roles of bacteria, saprotrophic, and mycorrhizal fungi. Soil macrofauna is also represented. The model resolves the cycles of nitrogen, phosphorus, and potassium. Model simulations for 20 sites compared favorably with global patterns of litter and soil stoichiometry, microbial and macrofaunal biomass relations with soil organic carbon, soil respiration and nutrient mineralization rates. Long‐term responses to bare fallow and nitrogen addition experiments were also in agreement with observations. Some discrepancies between predictions and observations are appreciable in the response to litter manipulation. Upon successful model reproduction of observed general trends, we assessed patterns associated with the carbon cycle that were challenging to address empirically. Despite large site‐to‐site variability, fine root, fungal, bacteria, and macrofaunal respiration account for 33%, 40%, 24% and 3% on average of total belowground respiration, respectively. Simulated root exudation and carbon export to mycorrhizal fungi represent on average about 13% of plant net primary productivity (NPP). These results offer mechanistic and general estimates of microbial biomass and its contribution to respiration fluxes and to soil organic matter dynamics.

Journal article

Paschalis A, Fatichi S, Pappas C, Or Det al., 2018, Covariation of vegetation and climate constrains present and future T/ET variability, Environmental Research Letters, Vol: 13, Pages: 1-11, ISSN: 1748-9326

The reliable partitioning of the terrestrial latent heat flux into evaporation (E) and transpiration (T) is important for linking carbon and water cycles and for better understanding ecosystem functioning at local, regional and global scales. Previous research revealed that the transpiration-to-evapotranspiration ratio (T/ET) is well constrained across ecosystems and is nearly independent of vegetation characteristics and climate. Here we investigated the reasons for such a global constancy in present-day T/ET by jointly analysing observations and process-based model simulations. Using this framework, we also quantified how the ratio T/ET could be influenced by changing climate. For present conditions, we found that the various components of land surface evaporation (bare soil evaporation, below canopy soil evaporation, evaporation from interception), and their respective ratios to plant transpiration, depend largely on local climate and equilibrium vegetation properties. The systematic covariation between local vegetation characteristics and climate, resulted in a globally constrained value of T/ET = ~70 ± 9% for undisturbed ecosystems, nearly independent of specific climate and vegetation attributes. Moreover, changes in precipitation amounts and patterns, increasing air temperatures, atmospheric CO2 concentration, and specific leaf area (the ratio of leaf area per leaf mass) was found to affect T/ET in various manners. However, even extreme changes in the aforementioned factors did not significantly modify T/ET.

Journal article

Wu D, Ciais P, Viovy N, Knapp AK, Wilcox K, Bahn M, Smith BD, Vicca S, Fatichi S, Zscheischler J, He Y, Li X, Ito A, Arneth A, Harper A, Ukkola A, Paschalis A, Poulter B, Peng C, Ricciuto D, Reinthaler D, Chen G, Tian H, Genet H, Mao J, Ingrisch K, Schmitt M, Meir P, Zhu Q, Hasibeder R, Sippel S, Dangal SRS, Sitch S, Shi X, Wang Y, Luo Y, Liu Y, Piao Set al., 2018, Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites, Biogeosciences, Vol: 15, Pages: 3421-3437, ISSN: 1726-4170

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our resu

Journal article

Peleg N, Marra F, Fatichi S, Paschalis A, Molnar P, Burlando Pet al., 2018, Spatial variability of extreme rainfall at radar subpixel scale, JOURNAL OF HYDROLOGY, Vol: 556, Pages: 922-933, ISSN: 0022-1694

Journal article

Peleg N, Fatichi S, Paschalis A, Molnar P, Burlando Pet al., 2017, An advanced stochastic weather generator for simulating 2-D high-resolution climate variables, Journal of Advances in Modeling Earth Systems, Vol: 9, Pages: 1595-1627, ISSN: 1942-2466

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Journal article

Paschalis A, Molnar P, Fatichi S, Burlando Pet al., 2017, Stochastic modelling of space-time precipitation fields the streap model, Pages: 97-100

In this study, we introduce a new space-time precipitation stochastic model. The aim of the model is the parsimonious simulation of all of the major structural characteristics of precipitation. Its hierarchical structure is based on a three stage simulation process of (a) the storm arrival process; (b) the evolution of wet area and mean intensity (bivariate stochastic process); and (c) of spatial fields by the latent Gaussian process correlated in space and time. The model is validated for one of the most challenging areas in the European Alps and the results are satisfactory for a wide range of spatial and temporal scales.

Conference paper

Fatichi S, Leuzinger S, Paschalis A, Langley JA, Barraclough AD, Hovenden MJet al., 2016, Partitioning direct and indirect effects reveals the response of water-limited ecosystems to elevated CO2, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 113, Pages: 12757-12762, ISSN: 0027-8424

Journal article

Kianfar B, Fatichi S, Paschalis A, Maurer M, Molnar Pet al., 2016, Climate change and uncertainty in high-resolution rainfall extremes

<jats:p>Abstract. A methodology to analyze the impact of climate change on rainfall extremes with a high temporal resolution is presented. It is based on a rainfall stochastic simulator which consists of a point process model for the daily scale (Neymann-Scott Rectangular Pulse Model) and a nested disaggregation scheme for the 10-min rainfall scale (Multiplicative Random Cascade Model). Climate change signals are included as Factors of Change applied to key statistics (first–third order moments, correlation and intermittency) as simulated with ten GCM-RCM model chains of the ENSEMBLES Project. The stochastic simulator was calibrated with data from 22 meteorological stations in Switzerland, and used to analyze rainfall extremes from 30-yr long realizations for the current climate and two future climate periods (mid-Century and end-of-Century). The stochastic simulator reproduces first and higher-order statistics of precipitation very well for temporal scales from 10-min to 24-hr, including annual maxima for a range of return periods relevant for urban hydrology. The internal climate variability (stochasticity) in rainfall extremes can be directly quantified using simulations, and is very high. Despite the imposed climate change signals, the distributions of annual maxima for the current and future climates largely overlap in most climate model chains. There are relatively few cases where the mean future extremes lie outside of the 10–90 % uncertainty bounds of the current climate, and in fact both increases and decreases are found in simulations. The rainfall stochastic simulator can be improved in the future by including the relation between extreme rainfall intensity and air temperature in the parametrisation. We conclude that the climate change signal generated by climate models has a low signal-to-noise ratio in rainfall extremes at high resolutions at the station level and predictions of change are therefore highly uncertain. At the same

Journal article

Paschalis A, Katul GG, Fatichi S, Palmroth S, Way Det al., 2016, On the variability of the ecosystem response to elevated atmospheric CO2 across spatial and temporal scales at the Duke Forest FACE experiment, Agricultural and Forest Meteorology, Vol: 232, Pages: 367-383, ISSN: 0168-1923

While the significance of elevated atmospheric CO2 concentration on instantaneous leaf-level processes such as photosynthesis and transpiration is rarely disputed, its integrated effect at ecosystem level and at long-time scales remains a subject of debate. In part, the uncertainty stems from the inherent leaf-to-leaf variability in gas exchange rates. By combining 10 years of leaf gas exchange measurements collected during the Duke Forest Free Air CO2 Enrichment (FACE) experiment and three different leaf-scale stomatal conductance models, the leaf-to-leaf variability in photosynthetic and stomatal conductance properties is examined. How this variability is then reflected in ecosystem water vapor and carbon dioxide fluxes is explored by scaling up the leaf-level process to the canopy using model calculations. The main results are: (a) the space-time variability of the photosynthesis and stomatal conductance response is considerable as expected. (b) Variability of the calculated leaf level fluxes is dependent on both the meteorological drivers and differences in leaf age, position within the canopy, nitrogen and CO2 fertilization, which can be accommodated in model parameters. (c) Meteorological variability is playing the dominant role at short temporal scales while parameter variability is significant at longer temporal scales. (d) Leaf level results do not necessarily translate to similar ecosystem level responses due to indirect effects and other compensatory mechanisms related to long-term vegetation dynamics and ecosystem water balance.

Journal article

Fatichi S, Ivanov VY, Paschalis A, Peleg N, Molnar P, Rimkus S, Kim J, Burlando P, Caporali Eet al., 2016, Uncertainty partition challenges the predictability of vital details of climate change, EARTHS FUTURE, Vol: 4, Pages: 240-251, ISSN: 2328-4277

Journal article

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