Observational constraints on the chemistry of isoprene nitrates over the eastern United States

The formation of organic nitrates during the oxidation of the biogenic hydrocarbon isoprene can strongly affect boundary layer concentrations of ozone and nitrogen oxides (NOx = NO + NO2). We constrain uncertainties in the chemistry of these isoprene nitrates using chemical transport model simulations in conjunction with observations over the eastern United States from the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) field campaign during summer 2004. The model best captures the observed boundary layer concentrations of organic nitrates and their correlation with ozone using a 4% yield of isoprene nitrate production from the reaction of isoprene hydroxyperoxy radicals with NO, a recycling of 40% NOx when isoprene nitrates react with OH and ozone, and a fast dry deposition rate of isoprene nitrates. Simulated boundary layer concentrations are only weakly sensitive to the rate of photochemical loss of the isoprene nitrates. An 8% yield of isoprene nitrates degrades agreement with the observations somewhat, but concentrations are still within 50% of observations and thus cannot be ruled out by this study. Our results indicate that complete recycling of NOx from the reactions of isoprene nitrates and slow rates of isoprene nitrate deposition are incompatible with the observations. We find that ∼50% of the isoprene nitrate production in the model occurs via reactions of isoprene (or its oxidation products) with the NO3 radical, but note that the isoprene nitrate yield from this pathway is highly uncertain. Using recent estimates of rapid reaction rates with ozone, 20–24% of isoprene nitrates are lost via this pathway, implying that ozonolysis is an important loss process for isoprene nitrates. Isoprene nitrates are shown to have a major impact on the nitrogen oxide (NOx = NO + NO2) budget in the summertime U.S. continental boundary layer, consuming 15–19% of the emitted NOx, of which 4–6% is recycled back to NOx and the remainder is exported as isoprene nitrates (2–3%) or deposited (8–10%). Our constraints on reaction rates, branching ratios, and deposition rates need to be confirmed through further laboratory and field measurements. The model systematically underestimates free tropospheric concentrations of organic nitrates, indicating a need for future investigation of the processes controlling the observed distribution

Converging Currents in Climate-Relevant Conservation: Water, Infrastructure, and Institutions

Ecologists and economists have long talked past each other, but climate change presents similar threats to both groups. Water may serve as the best means of finding a common cause and building a new vision of ecological and economic sustainability, especially in the developing world

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope-scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid-level water, energy, and biogeochemical fluxes. In contrast to the one-dimensional (1-D), 2- to 3-m deep, and free-draining soil hydrology in most ESM land models, we hypothesize that 3-D, lateral ridge-to-valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions. Plain Language Summary Hillslopes are key landscape features that organize water availability on land. Valley bottoms are wetter than hilltops, and sun-facing slopes are warmer and drier than shaded ones. This hydrologic organization leads to systematic differences in soil and vegetation between valleys and hilltops, and between sunny and shady slopes. Although these patterns are fundamental to understanding the structures and functions of water and terrestrial ecosystems, they are too fine grained to be represented in global-scale Earth System Models. Here we bring together Critical Zone scientists who study the interplay of vegetation, the porous upper layer of the continental crust from vegetation to bedrock, and moisture dynamics deep into the weathered bedrock underlying hillslopes and Earth System Model scientists who develop global models, to ask: Do hillslope-scale processes matter to predicting global change? The answers will help scientists understand where and why hillslopes matter, and to better predict how terrestrial ecosystems, including societies, may affect and be affected by our rapidly changing planet.National Science Foundation [NSF-EAR-1528298, NSF-EAR-0753521]6 month embargo; published online: 27 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐mdeep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application

Adaptive Management of Riverine Socio-ecological Systems

If ongoing change in ecosystems and society can render inflexible policies obsolete, then management must dynamically adapt as a counter to perennial uncertainty. This chapter describes a general synthesis of how to make decision-making more adaptive and then explores the barriers to learning in management. We then describe how one such process, known as adaptive management (AM), has been applied in different river basins, on which basis we discuss AM’s strengths and limitations in various resource management contexts

SPEAR: The Next Generation GFDL Modeling System for Seasonal to Multidecadal Prediction and Projection

We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL—the AM4 atmosphere model, MOM6 ocean code, LM4 land model, and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0° (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1° to 0.25°. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM4 models but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM4 models

The Macroecology of Sustainability

Global consumption rates of vital resources suggest that we have surpassed the capacity of the Earth to sustain current levels, much less future trajectories of growth in human population and economy