About

Amilcare Porporato is the Thomas J. Wu '94 Professor of Civil and Environmental Engineering at Princeton University and an associated faculty member at the High Meadows Environmental Institute. He holds a PhD from the Polytechnic of Milan, Italy, earned in 1996, and a Master of Science in Civil Engineering from the same institution. His research focuses on the quantitative description and prediction of the complex dynamics of the terrestrial water cycle, with particular interest in the impact of the hydrologic cycle on the temporal and spatial variability of ecosystem processes, including energy, carbon, and nutrient cycles. Dr. Porporato employs both theoretical and experimental approaches to isolate and describe the dominant dynamical components of physical and biological interactions within these systems. His specific research areas include soil moisture-microbe-plant dynamics, mathematical modeling of biogeochemical cycles, soil-atmosphere interactions, and the sustainable use of soil and water resources, especially in semi-arid ecosystems, both natural and agricultural. His interdisciplinary research methods draw from fluid mechanics, soil physics, plant physiology, statistical physics, nonlinear dynamics, non-equilibrium thermodynamics, and complex system science. Dr. Porporato has been recognized as a Highly Cited Researcher by Web of Science, received the Hydrologic Sciences Award from the American Geophysical Union, and was awarded the Inaugural Landolt Chair in Sustainable Development and Innovation at EPFL, Switzerland.

Research topics

• Environmental science
• Geology
• Ecology
• Geography
• Biology
• Chemistry
• Natural resource economics
• Soil science
• Atmospheric sciences
• Economics
• Meteorology
• Business
• Earth science
• Climatology
• Agroforestry
• Geochemistry
• Environmental resource management
• Water resource management
• Cartography
• Astrobiology
• Geomorphology
• Environmental chemistry

Selected publications

• Ecohydrological Controls on Moist Convection and Long-Term Rainfall Feedback

  arXiv (Cornell University) · 2026-04-09

  preprintOpen accessSenior author

  To elucidate how land surface state and soil moisture dynamics regulate moist convection, and how convective rainfall subsequently reshapes surface and root-zone hydrology, we develop a stochastic dynamical model that couples soil moisture, vegetation hydraulics, atmospheric boundary layer evolution, and convective available potential energy (CAPE). We show that CAPE depends not only on the free-tropospheric environment but also on soil moisture, through its control of surface fluxes, boundary-layer growth, and the timing of the intersection between the atmospheric boundary layer and the lifting condensation level (LCL). Soil texture and plant properties strongly modulate convective potential during dry-down. Loamy sand favors convection at relatively high soil moisture and maintains the largest CAPE at the time of LCL-ABL crossing across drying conditions. In contrast, sandy soils exhibit high CAPE when wet but lose convective potential rapidly as they dry. As matric potential becomes more negative, convection is increasingly suppressed in finer, loamy clay textures. Plant functional type further shapes dry-down dynamics: water-use-maximizing strategies can enhance dry persistence via stomatal closure during drying, whereas more conservative strategies can sustain convection for longer periods. On longer timescales, stochastic rainfall forcing with CAPE-dependent precipitation intensity produces persistent wet and dry soil moisture regimes, with switching times that depend on soil hydraulic properties, plant physiological traits, and atmospheric conditions.

  PublisherDOI

• Scaling of Rainfall Intensity and Frequency with Rising Temperatures

  2026-03-14

  articleOpen accessSenior authorCorresponding

  Global warming is projected to intensify the hydrological cycle, amplifying risks to ecosystems and society. While extreme rainfall appears to exhibit stronger sensitivity to global warming compared to mean rainfall rates, a unifying physical mechanism​ capable of explaining this systematic divergence has remained elusive. Here, we integrate theory and data from a global network of nearly 50,000 rain-gauge stations to unravel the rainfall intensity and frequency response to rising temperatures. We show that the distributions of wet-day rainfall depth exhibit self-similar shapes across diverse geographical regions and time periods. Combined with the temperature response of rainfall frequency, this consistently links mean and extreme precipitation at both local and global scales. We find that the most probable change in rainfall intensity follows Clausius-Clapeyron (CC) scaling with variations shaped by a fundamental hydrological constraint. This behavior reflects a dynamic intensification of updrafts in space and time, which produces localized heavy precipitation events enhancing atmospheric moisture depletion and hydrologic losses through runoff and percolation. The resulting reduction in evaporative fluxes slows the replenishment of atmospheric moisture, giving rise to the observed trade-off between rainfall frequency and intensity. These robust scaling laws for rainfall shifts with temperature are essential for climate projection and adaptation planning.

  PublisherDOI

• Small-System Group: Thermodynamics as a Complete Self-Similarity Limit

  arXiv (Cornell University) · 2026-04-14

  preprintOpen access1st authorCorresponding

  We revisit the Rayleigh--Riabouchinsky paradox in dimensional analysis by making explicit the bridge between thermodynamics and the mechanical interpretation of temperature. Boltzmann's constant $k_B$ acts as a dimensional unifier, leading to an augmented $Π$-theorem with an additional dimensionless group that encodes system size. In the macroscopic thermodynamic limit this small-system group, $Π_B = k_B/(c\,\ell^3)$ -- the inverse heat capacity of a control volume of size $\ell^3$ in units of $k_B$ -- becomes irrelevant as the response becomes self-similar with respect to it, recovering Rayleigh's formulation. Under suitable conditions, macroscopic limits make the fluctuations of the observables of interest negligible compared to their expected values, hence the state of a system is characterized by a reduced set of parameters. We thus recast thermodynamics as the complete-similarity limit of statistical mechanics with respect to $Π_B$, which also controls thermodynamic fluctuations. We also discuss second-order phase transitions from the viewpoint of incomplete similarity.

  PublisherDOI

• Ecohydrological Controls on Moist Convection and Long-Term Rainfall Feedback

  arXiv (Cornell University) · 2026-04-09

  articleOpen accessSenior author

  To elucidate how land surface state and soil moisture dynamics regulate moist convection, and how convective rainfall subsequently reshapes surface and root-zone hydrology, we develop a stochastic dynamical model that couples soil moisture, vegetation hydraulics, atmospheric boundary layer evolution, and convective available potential energy (CAPE). We show that CAPE depends not only on the free-tropospheric environment but also on soil moisture, through its control of surface fluxes, boundary-layer growth, and the timing of the intersection between the atmospheric boundary layer and the lifting condensation level (LCL). Soil texture and plant properties strongly modulate convective potential during dry-down. Loamy sand favors convection at relatively high soil moisture and maintains the largest CAPE at the time of LCL-ABL crossing across drying conditions. In contrast, sandy soils exhibit high CAPE when wet but lose convective potential rapidly as they dry. As matric potential becomes more negative, convection is increasingly suppressed in finer, loamy clay textures. Plant functional type further shapes dry-down dynamics: water-use-maximizing strategies can enhance dry persistence via stomatal closure during drying, whereas more conservative strategies can sustain convection for longer periods. On longer timescales, stochastic rainfall forcing with CAPE-dependent precipitation intensity produces persistent wet and dry soil moisture regimes, with switching times that depend on soil hydraulic properties, plant physiological traits, and atmospheric conditions.

  PublisherOA PDF

• EcoHydrology, Thermodynamics, and Microbial Ecology at the onset of soil syntrophy

  2026-03-14

  articleOpen access1st authorCorresponding

  Syntrophy is metabolic cross-feeding in which an upstream organism can oxidize a substrate only because a partner continuously removes inhibitory products (often H2), making the overall reaction energetically favorable. In soils, moisture regulates anaerobic microbial interactions by shaping oxygen availability and gas diffusivity, while fermentation produces reduced intermediates, including volatile fatty acids (VFAs) such as butyrate and propionate, whose oxidation is endergonic under standard conditions and becomes feasible only when hydrogen is maintained sufficiently low by hydrogenotrophic methanogens. Here we present a minimalist predator–prey model that captures the key feedbacks among moisture, hydrogen dynamics, and methanogen biomass. Moisture modulate hydrogen production, leakage, and methanogenic growth, shifting the system between a hydrogen-accumulating, methanogen-free regime and a syntrophic coexistence regime in which methanogens depress hydrogen below the threshold required for VFA oxidation to become exergonic. The resulting moisture-driven transition is a transcritical bifurcation governed by a moisture-dependent methanogen reproduction number, providing a compact link between hydrologic variability and the onset and collapse of syntrophy in soils.

  PublisherDOI

• Atmospheric Boundary Layer Control on Forest Thermal Properties

  Global Change Biology · 2026-04-01

  articleOpen accessSenior author

  ABSTRACT Forest canopy, air temperatures and air humidity (, , and ) play a central rol in regulating energy and gas exchange between vegetation and the atmosphere. Although often treated as independent drivers of canopy processes, and are dynamically coupled to via surface energy fluxes and atmospheric boundary layer (ABL) development. We investigated how plant physiology mediates this coupling. Using data from a tropical ecosystem, we studied a process‐based forest model dynamically coupled with an ABL growth model to simulate diurnal interactions between the canopy and the atmosphere. We systematically varied plant traits related to water use and thermal regulation to assess their effects on coupling and feedback. We focused on three metrics: the slope of the relationship, the peak of reached during the day and the lag between the maximum and , indicating hysteresis. Conservative water use, by reducing transpiration, leads to greater canopy warming, which intensifies sensible heat flux and accelerates ABL growth. This, in turn, raises near‐surface air temperature and vapor pressure deficit (VPD), amplifying thermal and water stress. In contrast, greater water use enhances evaporative cooling and slows ABL development, thereby moderating these feedback. Surprisingly, the slope of the relationship is quite insensitive to plant water‐use syndromes. This insight extends beyond modeling. Empirical studies often treat and VPD as independent drivers of transpiration, photosynthesis, or stomatal conductance. Our results challenge this assumption, showing that these variables are influenced by plant function itself. is not a passive outcome but an active mediator of energy, water, and carbon exchange, regulated by a feedback loop involving leaf physiology and atmospheric dynamics. Studies using or the relationship—whether from remote sensing or field data—as a proxy for forest stress or function, must account for this coupling.

  PublisherDOI

• Small-System Group: Thermodynamics as a Complete Self-Similarity Limit

  arXiv (Cornell University) · 2026-04-14

  articleOpen access1st authorCorresponding

  We revisit the Rayleigh--Riabouchinsky paradox in dimensional analysis by making explicit the bridge between thermodynamics and the mechanical interpretation of temperature. Boltzmann's constant $k_B$ acts as a dimensional unifier, leading to an augmented $Π$-theorem with an additional dimensionless group that encodes system size. In the macroscopic thermodynamic limit this small-system group, $Π_B = k_B/(c\,\ell^3)$ -- the inverse heat capacity of a control volume of size $\ell^3$ in units of $k_B$ -- becomes irrelevant as the response becomes self-similar with respect to it, recovering Rayleigh's formulation. Under suitable conditions, macroscopic limits make the fluctuations of the observables of interest negligible compared to their expected values, hence the state of a system is characterized by a reduced set of parameters. We thus recast thermodynamics as the complete-similarity limit of statistical mechanics with respect to $Π_B$, which also controls thermodynamic fluctuations. We also discuss second-order phase transitions from the viewpoint of incomplete similarity.

  PublisherOA PDF

• The Role of Land-Surface Dynamics in Climate Persistence and Convective Extremes

  2026-03-14

  articleOpen accessSenior authorCorresponding

  The properties governing atmospheric convection, which can produce heavy rainfall and severe weather events, depend on both land-surface characteristics and atmospheric conditions. This work develops a stochastic, coupled plant–soil–atmosphere model that treats atmospheric drivers of moist convection, such as convective available potential energy (CAPE), as functions of the soil–vegetation surface. Further, we link trajectories of these atmospheric and surface variables, including rainfall intensity, to changes in functional plant type (i.e., response to drought stress) and soil type. This enables the realization of steady-state probability distributions of relevant ecohydrological quantities, including soil moisture, plant water potential, and CAPE. From this dynamical systems perspective, the probability of rainfall is conditioned on the terrestrial surface state. Therefore, the wet–dry switching that influences climatic persistence in convection-dominated regions can be directly related to soil moisture. This formulation provides a framework for understanding how very large CAPE and intense rainfall can emerge under specific combinations of antecedent soil moisture, land-surface fluxes, and free-atmospheric conditions.

  PublisherDOI

• Scaling of Rainfall Intensity and Frequency with Rising Temperatures

  ArXiv.org · 2026-01-10

  articleOpen accessSenior author

  Global warming is projected to intensify the hydrological cycle, amplifying risks to ecosystems and society. While extreme rainfall appears to exhibit stronger sensitivity to global warming compared to mean rainfall rates, a unifying physical mechanism capable of explaining this systematic divergence has remained elusive. Here, we integrate theory and data from a global network of nearly 50,000 rain-gauge stations to unravel the rainfall intensity and frequency response to rising temperatures. We show that the distributions of wet-day rainfall depth exhibit self-similar shapes across diverse geographical regions and time periods. Combined with the temperature response of rainfall frequency, this consistently links mean and extreme precipitation at both local and global scales. We find that the most probable change in rainfall intensity follows Clausius-Clapeyron (CC) scaling with variations shaped by a fundamental hydrological constraint. This behavior reflects a dynamic intensification of updrafts in space and time, which produces localized heavy precipitation events enhancing atmospheric moisture depletion and hydrologic losses through runoff and percolation. The resulting reduction in evaporative fluxes slows the replenishment of atmospheric moisture, giving rise to the observed trade-off between rainfall frequency and intensity. These robust scaling laws for rainfall shifts with temperature are essential for climate projection and adaptation planning.

  PublisherOA PDF

• Scaling of Rainfall Intensity and Frequency with Rising Temperatures

  arXiv (Cornell University) · 2026-01-10

  preprintOpen accessSenior author

  Global warming is projected to intensify the hydrological cycle, amplifying risks to ecosystems and society. While extreme rainfall appears to exhibit stronger sensitivity to global warming compared to mean rainfall rates, a unifying physical mechanism capable of explaining this systematic divergence has remained elusive. Here, we integrate theory and data from a global network of nearly 50,000 rain-gauge stations to unravel the rainfall intensity and frequency response to rising temperatures. We show that the distributions of wet-day rainfall depth exhibit self-similar shapes across diverse geographical regions and time periods. Combined with the temperature response of rainfall frequency, this consistently links mean and extreme precipitation at both local and global scales. We find that the most probable change in rainfall intensity follows Clausius-Clapeyron (CC) scaling with variations shaped by a fundamental hydrological constraint. This behavior reflects a dynamic intensification of updrafts in space and time, which produces localized heavy precipitation events enhancing atmospheric moisture depletion and hydrologic losses through runoff and percolation. The resulting reduction in evaporative fluxes slows the replenishment of atmospheric moisture, giving rise to the observed trade-off between rainfall frequency and intensity. These robust scaling laws for rainfall shifts with temperature are essential for climate projection and adaptation planning.

  PublisherDOI

Recent grants

• Collaborative Research: Controls over C sequestration: physiology vs. physics

  NSF · $97k · 2012–2016

• Local and nonlocal topographic controls on landscape ecohydrology

  NSF · $128k · 2017–2018

• RAPID Proposal: Merging Monsoon, Snowmelt and Post-flood Ground Information for a Multivariate Estimation and Prediction of Flood Risk for the Indus River, Pakistan

  NSF · $45k · 2011–2012

• Sustainable use of water and soils in seasonally-dry regions: exploring the continuum between natural and intensively-managed ecosystems

  NSF · $453k · 2010–2015

• IGERT: Training Program in Wireless Intelligent Sensor Networks (WISeNet)

  NSF · $3.1M · 2011–2018

Frequent coauthors

• Gabriel G. Katul

  Duke University

  102 shared

• Luca Ridolfi

  Polytechnic University of Turin

  94 shared

• I. Rodriguez‐Iturbe

  90 shared

• Stefano Manzoni

  Stockholm University

  80 shared

• Salvatore Calabrese

  Texas A&M University

  57 shared

• Paolo D’Odorico

  University of California, Berkeley

  53 shared

• Giulia Vico

  51 shared

• Edoardo Daly

  49 shared

Awards & honors

• Highly Cited Researcher, Web of Science
• Hydrologic Sciences Award, AGU
• Borland Lecture – Hydrology Days
• American Geophysical Union (AGU) Fellow
• Inaugural Landolt Chair in Sustainable Development and Innov…