Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000-2009, 2046-2065 and 2081-2100, using the period of 1962-1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000-2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scale

Modeling the role of climate change on small-scale vegetation patterns in a Mediterranean basin using a Cellular Automata model

Predicting vegetation response in regions of ecotone transition under a changing climate is a among grand challenges in ecohydrology. In a small basin (1.3 sq km) in Sicily, Italy, where north-facing slopes are characterized by Quercus (tree), and south-facing slopes by Opuntia ficus-indaca (evergreen perennial species drought tolerant) and grasses we use an ecohydrological Cellular-Automaton model (CATGraSS) of vegetation coexistence driven by rainfall and solar radiation with downscaled future climate to examine the role of climate change on vegetation patterns. In the model, each cell can hold a single plant type or can be bare soil. Plant competition is modeled explicitly by keeping track of mortality and establishment of plants, both calculated probabilistically based on soil moisture stress. Topographic influence on incoming shortwave radiation is treated explicitly, which leads to spatial variations in potential evapotranspiration and resulting soil moisture and plant distribution. The influence of the soil thickness on the vegetation distribution is also introduced. The model is calibrated first using a representation of the current climate as a forcing and comparing the vegetation obtained from the model with the actual vegetation through statistical techniques.. The calibrated model is then forced with future climate scenarios generated using a stochastic downscaling technique based on the weather generator, AWE-GEN. This methodology allows for the downscaling of an ensemble of climate model outputs deriving the frequency distribution functions of factors of change for several statistics of temperature and precipitation from outputs of General Circulation Models. The stochastic downscaling is carried out using simulations of twelve General Circulation Models adopted in the IPCC 4AR, A1B emission scenario, for the future periods of 2046-2065 and 2081-2100. A high sensitivity of the vegetation distribution to variation of rainfall and temperature has been observed. The simulations suggest that the observed vegetation pattern can exist only in the current climate while the changes in the future storm characteristics could lead to a dramatic reorganization of the plant composition based mainly on the topography. Moreover the model analysis underscores the importance of solar irradiance in determining vegetation composition over complex terrain

Using a physically-based model, tRIBS-Erosion, for investigating the effects of climate change in semi-arid headwater basins.

Soil erosion due to rainfall detachment and flow entrainment of soil particles is a physical process responsible for a continuous evolution of landscapes. The rate and spatial distribution of this phenomenon depend on several factors such as climate, hydrologic regime, geomorphic characteristics, and vegetation of a basin. Many studies have demonstrated that climate-erosion linkage in particular influences basin sediment yield and landscape morphology. Although soil erosion rates are expected to change in response to climate, these changes can be highly non-linear and thus require mechanistic understanding of underlying causes. In this study, an integrated geomorphic component of the physically-based, spatially distributed hydrological model, tRIBS, the TIN-based Real-time Integrated Basin Simulator, is used to analyze the sensitivity of semi-arid headwater basins to climate change. Downscaled outputs of global circulation models are used to inform a stochastic weather generator that produces an ensemble of climate scenarios for an area in the Southwest U.S. The ensemble is used as input to the integrated model that is applied to different headwater basins of the Walnut Gulch Experimental Watershed to understand basin response to climate change in terms of runoff and sediment yield. Through a model application to multiple catchments, a scaling relationship between specific sediment yield and drainage basin area is also addressed and probabilistic inferences on future changes in catchment runoff and yield are drawn. Geomorphological differences among catchments do not influence specific changes in runoff and sediment transport that are mostly determined by precipitation changes. Despite a large uncertainty dictated by climate change projections and stochastic variability, sediment transport is predicted to decrease despite a non-negligible possibility of larger runoff rates

Covariation of vegetation and climate constrains present and future T/ET variability

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

Persistent decay of fresh xylem hydraulic conductivity varies with pressure gradient and marks plant responses to injury

Defining plant hydraulic traits is central to the quantification of ecohydrological processes ranging from land-atmosphere interactions, to tree mortality, and water-carbon budgets. A key plant trait is the xylem specific hydraulic conductivity (Kx ), that describes the plant's vascular system capacity to transport water. While xylem's vessels and tracheids are dead upon maturity, the xylem is neither inert nor deadwood, various components of the sapwood and surrounding tissue remaining alive and functional. Moreover, the established definition of Kx assumes linear relations between water flux and pressure gradient by tacitly considering the xylem as a "passive conduit". Here we reexamine this notion of an inert xylem by systematically characterizing xylem flow in several woody plants using Kx measurements under constant and cyclic pressure gradients. Results show a temporal and pressure gradient dependence of Kx . Additionally, microscopic features in "living branches" are irreversibly modified upon drying of the xylem thus differentiating the macroscopic definition of Kx for living and dead xylem. The findings highlight the picture of the xylem as a complex and delicate conductive system whose hydraulic behavior transcends a passive gradient-based flow. The study sheds new light on xylem conceptualization, conductivity measurement protocols, in situ long-distance water transport, and ecosystem modeling. This article is protected by copyright. All rights reserved

An ecohydrological journey of 4500 years reveals a stable but threatened precipitation–groundwater recharge relation around Jerusalem

Groundwater is a key water resource in semiarid and seasonally dry regions around the world, which is replenished by intermittent precipitation events and mediated by vegetation, soil, and regolith properties. Here, a climate reconstruction of 4500 years for the Jerusalem region was used to determine the relation between climate, vegetation, and groundwater recharge. Despite changes in air temperature and vegetation characteristics, simulated recharge remained linearly related to precipitation over the entire analyzed period, with drier decades having lower rates of recharge for a given annual precipitation due to soil memory effects. We show that in recent decades, the lack of changes in the precipitation–groundwater recharge relation results from the compensating responses of vegetation to increasing CO2, i.e., increased leaf area and reduced stomatal conductance. This multicentury relation is expected to be modified by climate change, with changes up to −20% in recharge for unchanged precipitation, potentially jeopardizing water resource availability

Seasonal hysteresis of surface urban heat islands

Temporal dynamics of urban warming have been extensively studied at the diurnal scale, but the impact of background climate on the observed seasonality of surface urban heat islands (SUHIs) remains largely unexplored. On seasonal time scales, the intensity of urban–rural surface temperature differences (ΔTs) exhibits distinctive hysteretic cycles whose shape and looping direction vary across climatic zones. These observations highlight possible delays underlying the dynamics of the coupled urban–biosphere system. However, a general argument explaining the observed hysteretic patterns remains elusive. A coarse-grained model of SUHI coupled with a stochastic soil water balance is developed to demonstrate that the time lags between radiation forcing, air temperature, and rainfall generate a rate-dependent hysteresis, explaining the observed seasonal variations of ΔTs. If solar radiation is in phase with water availability, summer conditions cause strong SUHI intensities due to high rural evaporative cooling. Conversely, cities in seasonally dry regions where evapotranspiration is out of phase with radiation show a summertime oasis effect controlled by background climate and vegetation properties. These seasonal patterns of warming and cooling have significant implications for heat mitigation strategies as urban green spaces can reduce ΔTs during summertime, while potentially negative effects of albedo management during winter are mitigated by the seasonality of solar radiation

Dry-Season Greening and Water Stress in Amazonia: The Role of Modeling Leaf Phenology

Large uncertainties on the sensitivity of Amazon forests to drought exist. Even though water stress should suppress photosynthesis and enhance tree mortality, a green‐up has been often observed during the dry season. This interplay between climatic forcing and forest phenology is poorly understood and inadequately represented in most of existing dynamic global vegetation models calling for an improved description of the Amazon seasonal dynamics. Recent findings on tropical leaf phenology are incorporated in the state‐of‐the‐art eco‐hydrological model Thetys & Chloris. The new model accounts for a mechanistic light‐controlled leaf development, synchronized dry‐season litterfall, and an age‐dependent leaf photosynthetic capacity. Simulation results from 32 sites in the Amazon basin over a 15‐year period successfully mimic the seasonality of gross primary productivity; evapotranspiration (ET); as well as leaf area index, leaf age, and leaf productivity. Representation of tropical leaf phenology reproduces the observed dry‐season greening, reduces simulated gross primary productivity, and does not alter ET, when compared with simulations without phenology. Tolerance to dry periods, with the exception of major drought events, is simulated by the model. Deep roots rather than leaf area index regulation mechanisms control the response to short‐term droughts, but legacy effects can exacerbate multiyear water stress. Our results provide a novel mechanistic approach to model leaf phenology and flux seasonality in the tropics, reconciling the generally observed dry‐season greening, ET seasonality, and decreased carbon uptake during severe droughts

On the uncertainty induced by pedotransfer functions in terrestrial biosphere modeling

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

Insensitivity of ecosystem productivity to predicted changes in fine‐scale rainfall variability

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