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DOE OSTI2021

Projecting climate change in South America using variable‐resolution Community Earth System Model: An application to Chile

Abstract We introduce variable‐resolution enabled Community Earth System Model (VR‐CESM) results simulating historical and future climate conditions at 28 km over South America and 14 km over the Andes. Three 30‐year simulations are performed: a historic (1985–2014), a near future (2030–2059), and an end‐century (2070–2099) simulation under the RCP8.5 scenario. Historic results compare favourably to several temperature and precipitation reanalysis products, though local biases are present, particularly during austral summer. Future simulations highlight broad warming patterns (+3–6°C by end‐century) and heterogeneous precipitation responses across South America that qualitatively agree with prior modelling efforts. Our results reveal that the interaction between temperature and precipitation changes produce shifts in several Köppen–Geiger climates. Notable changes include the near‐elimination of the Andean Tundra or Alpine climates, a 15% decrease in Tropical Rainforests and a Tropical Savannah expansion of 20%. To provide a regionally focused analysis of projected climate change and to illustrate the benefits of variable resolution modelling, we analyse changes in the magnitude and trend in seasonal and daily temperature and precipitation in Chile. We also examined several metrics [e.g., snow water equivalent (SWE), temperatures on wet days, and days below 0°C] to evaluate potential impacts of climate change on the Chilean cryosphere between the end‐of‐century and historic periods, finding wide‐ranging indications of cryospheric decline. These changes are interpreted through reductions in the timing (1–2.5 months earlier peak SWE) and magnitude (200–1,000 mm SWE decreases) of water stored as snow in the Andes, a 10–30% decrease in number of cool season wet days with temperatures below 1°C, and 50–200 fewer days (annually) with minimum temperatures below 0°C. Our aim in producing a high‐resolution dataset of climate projections from VR‐CESM is to support analyses of climate change throughout South America but especially in vulnerable montane regions and to provide additional results for comparison with previous, ongoing, and upcoming modelling efforts.

variable-resolution global climate models↗

NASA NTRS1988

Step-wise extinctions at the Cretaceous-Tertiary boundary and their climatic implications

A comparative study of planktonic foraminifera and radiolarian assemblages from the Cretaceous-Tertiary (K-T) boundary section of the Beloc Formation in the southern Peninsula of Haiti, and the lowermost Danian sequence of the Micara Formation in southern Cuba reveals a remarkable pattern of step-wise extinctions. This pattern is consistent in both places despite the widely different lithologies of the two formations. Because of a step-wise extinction and the delayed disappearance of taxa known to be more representative of cooler water realms, it is inferred that a cooling trend which characterized the close of the Maastrichtian and the onset of the Tertiary had the major adverse effect on the existing biota. Although repetitive lithologic and faunal fluctuations throughout the Maastrichtian sediments found at Deep Sea Drilling Project (DSDP) site 146/149 in the Caribbean Sea indicate variations reminiscent of known climatically induced cycles in the Cenozoic, rapid biotic succession appears to have taken place during a crisis period of a duration greater than 2 mission years. Widespread and abundant volcanic activities recorded in the Caribbean area during the crisis period gives further credence to earlier contention that intense volcanism may have played a major role in exhacerbating pre-existing climatic conditions during that time.

Maurrasse, Florentin J-M. R.↗

DOE OSTI2025

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗

DOE OSTI2022

Effect of the Quasi-Biennial Oscillation on the Madden Julian Oscillation Teleconnections in the Southern Hemisphere

The Madden Julian Oscillation (MJO) is the main source of intraseasonal variability in the tropics. MJO modulates rainfall in remote areas in the Southern Hemisphere by exciting tropical and extratropical wave trains. We use newly released reanalysis data to analyze how the Quasi-Biennial Oscillation (QBO) can influence the MJO's effects over the Southern Hemisphere, focusing on precipitation anomalies over South America. The anomalies in the intensity of the South Atlantic Convergence Zone (SACZ) and precipitation over Southeastern South America during MJO phases 1 and 4 are intensified during the easterly QBO. The extratropical wave train excited by the anomalous convection over the maritime continent during MJO phase 4 is affected by the QBO, with a stronger, better-defined pattern during westerly QBO. The conclusions are supported by a perturbation experiment of a case study, conducted using a high-top atmospheric global climate model where the QBO and MJO are controlled.

58 GEOSCIENCES↗

DOE OSTI2021

Viral community analysis in a marine oxygen minimum zone indicates increased potential for viral manipulation of microbial physiological state

Microbial communities in oxygen minimum zones (OMZs) are known to have significant impacts on global biogeochemical cycles, but viral influence on microbial processes in these regions are much less studied. Here we provide baseline ecological patterns using microscopy and viral metagenomics from the Eastern Tropical North Pacific (ETNP) OMZ region that enhance our understanding of viruses in these climate-critical systems. While extracellular viral abundance decreased below the oxycline, viral diversity and lytic infection frequency remained high within the OMZ, demonstrating that viral influences on microbial communities were still substantial without the detectable presence of oxygen. Viral community composition was strongly related to oxygen concentration, with viral populations in low-oxygen portions of the water column being distinct from their surface layer counterparts. However, this divergence was not accompanied by the expected differences in viral-encoded auxiliary metabolic genes (AMGs) relating to nitrogen and sulfur metabolisms that are known to be performed by microbial communities in these low-oxygen and anoxic regions. Instead, several abundant AMGs were identified in the oxycline and OMZ that may modulate host responses to low-oxygen stress. We hypothesize that this is due to selection for viral-encoded genes that influence host survivability rather than modulating host metabolic reactions within the ETNP OMZ. Together, this study shows that viruses are not only diverse throughout the water column in the ETNP, including the OMZ, but their infection of microorganisms has the potential to alter host physiological state within these biogeochemically important regions of the ocean.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage

Buildings with solar photovoltaic (PV) generation and a stationary battery energy storage system (BESS) may self-sustain an uninterrupted full-level electricity supply during power outages. The duration of off-grid operation is dependent on the time of the power fault and the capabilities of the home energy management system (HEMS). In this paper, building resilience is quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year. An evaluation method is proposed and exercised on a reference house in California climate zone 9 for which the detailed electricity usage is simulated using the EnergyPlus software. The influence of factors such as energy use behavioral patterns, energy storage capacity from the BESS, and an electric vehicle (EV) battery on the building resilience is evaluated. Varying combinations of energy storage and controllable loads are studied for optimally improved resilience based on user preferences. It is shown that for the target home and region with a solar PV system of 7.2 kW, a BESS with a capacity of 11 kWh, and an EV with a battery of 80 kWh permanently connected to the home, off-grid self-sustained full operation is guaranteed for at least 72 h.

14 SOLAR ENERGY↗

DOE OSTI2024

Datasets for Widespread Residential Space Heating Electrification in Texas

In this experiment, we explore long term patterns in electricity demand driven by the dual effects of full electrification of space heating in Texas (by adoption of electric heat pumps), and climate change. We use a predictive model of electricity demand, climate projections, and an open source nodal power system (DC Optimal Power Flow) model of the Electric Reliability Council of Texas (ERCOT) system. Heat pumps are a more energy efficient way of providing space heating and cooling in homes. We attempt to exhaustively investigate the impacts of full residential space heating electrification by adoption of heat pumps for the segment of Texas households that currently rely on fossil fuels (about 40%), while simultaneously incorporating climate change meteorological variables. We explore a range of scenarios of heat pump efficiency and climate uncertainty over a long period of future years (2020-2099). In total, the simulation experiment generates 1,280 simulation years of hourly data. We report and analyze results in form of impacts on residential load, total load, peak load, seasonality of peaking, and reliability measured by occurrence and frequency of loss of load events. While the experiment is for ERCOT, the insights and approach can be applied to other regions. The results from the analysis can inform system planners on a range of potential capacity requirements/ reliability implications and/or risks of full space heating electrification via the adoption of electric heat pumps, given the uncertainty in the scenarios/ climate futures. The dataset includes model output for residential, non residential and total load, and the results from the GO ERCOT model runs for 4 RCP Scenarios (RCP 4.5 Cooler, RCP 4.5 Hotter, RCP 8.5 Cooler, RCP 8.5 Hotter), 4 Heating electrification Scenarios (Base , Standard Efficiency HP, High Efficiency HP, Ultra-High Efficiency HP) over 80 years (2020-2099). The metrological variables at BA scale were weighted weighted using population projections consistent with the SSP3 scenario.

Climate Change↗

DOE OSTI2019

Mercury reallocation in thawing subarctic peatlands

Warming Arctic temperatures have led to permafrost thaw that threatens to release previously sequestered mercury (Hg) back into the environment. Mobilisation of Hg in permafrost waters is of concern, as Hg methylation produced under water-saturated conditions results in the neurotoxin, methyl Hg (MeHg). Thawing permafrost may enhance Hg export, but the magnitude and mechanisms of this mobilisation within Arctic ecosystems remain poorly understood. Such uncertainty limits prognostic modelling of Hg mobilisation and impedes a comprehensive assessment of its threat to Arctic ecosystems and peoples. Here, we address this knowledge gap through an assessment of Hg dynamics across a well-studied permafrost thaw sequence at the peak of the growing season in biologically active peat overlying permafrost, quantifying total gaseous mercury (TGM) fluxes, total mercury (Hg Tot ) in the active layer peat, porewater MeHg concentrations, and identifying microbes with the potential to methylate Hg. During the initial thaw, TGM is liberated, likely by photoreduction from permafrost where it was previously stored for decades to centuries. As thawing proceeds, TGM is largely driven by hydrologic changes as evidenced by Hg accumulation in water-logged, organic-rich peat sediments in fen sites. MeHg in porewaters increase across the thaw gradient, a pattern coincident with increases in the relative abundance of microbes possibly containing genes allowing for methylation of ionic Hg. Findings suggest that under changing climate, frozen, well-drained habitats will thaw and collapse into saturated landscapes, increasing the production of MeHg and providing a significant source of the toxic, bioaccumulative contaminant.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Updates of MERRA-2 Data and Services at NASA GES DISC

Over40 years of NASA climate reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) are available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition to being used in traditional weather and climate research, MERRA-2 is also widely used in application studies of, e.g., wind and solar energy, air quality and health, food and drought, and heat waves. Two new MERRA-2 datasets were recently added at the GES DISC: (1) climate statistics derived fromMERRA-2 daily data to assist in the analysis of extreme temperature and precipitation events and of large-scale meteorological patterns from 1980 to the present and (2) gridded satellite and conventional observations processed in the MERRA-2 system, along with key statistics derived from the data assimilation, to help better understand how the quality of observations directly affect there analysis data. The GES DISC focuses its efforts on continually improving existing data services and to develop new data tools to satisfy various user communities. The newly added features include the following: Time series service: This is a new service for MERRA-2 data, which enables the easy and fast access of long-term hourly or daily time series at a location for popular parameters. The data is saved in a single le in Ascii format with a user- friendly structure. New analytic functions in the subsetter interface: Options for downloading daily minimum and maximum values have been added into the subsetter interface, in addition to the existing daily mean option, for all MERRA-2 and MERRA sub-daily products. Data format conversion to GeoTIFF has been implemented. New variables in Giovanni: Most monthly variables have been integrated into Giovanni, GESDISC’s online visualization and analysis tool. Due to the large data volume, hourly variables were selected based on user requests. More online information: New MERRA-2 documentation has been added: Data How-To, Data in Action, and FAQ. This presentation overviews two new MERRA-2 datasets and illustrates the new features of data services through a number of case studies. MERRA-2 data and services can be found at: https://disc.gsfc.gov/datasets?

Data management↗

NASA NTRSDate not supplied

The Surface Albedo of Sea Ice in CMIP6 and the Implications for the Surface Albedo Feedback

The Arctic has experienced rapid sea ice loss and a substantial decline in surface albedo, significantly impacting its radiation budget. Climate models from the Coupled Model Intercomparison Project (CMIP6) reproduce these changes. However, inconsistencies remain among models regarding the magnitude, spatial distribution, and seasonal patterns of Arctic surface albedo evolution. This study investigates these discrepancies by comparing model outputs with observation from the Clouds and the Earth's Radiant Energy System (CERES). We develop a decomposition method to assess the contributions of sea ice albedo, sea ice concentration, and sea ice extent to Arctic surface albedo. Over land, differences in snow cover account for the substantial inter-model spread in surface albedo, while over the ocean, sea ice albedo, concentration, and extent all contribute. Comparisons between CMIP6 and the Atmospheric Model Intercomparison Project (AMIP) simulations, which use identically prescribed sea ice concentrations, reveals considerable inter-model spread in Arctic Ocean surface albedo due to differences in sea ice albedo. Applying the decomposition method to projections shows that models predicting larger decreases in sea ice concentration and extent, especially in the Central Arctic, exhibit lower surface albedo and stronger sea ice albedo feedback. Beyond 2050, Arctic Ocean surface albedo decline is mainly influenced by sea ice extent indicating that the retreat of the ice edge is the most important process to constrain the surface albedo feedback. This study provides insights into factors contributing to the spread and changes in Arctic surface albedo and the associated sea ice albedo feedback.

Patrick C Taylor↗

DOE OSTI2017

Thermodynamic and dynamic contributions to future changes in summer precipitation over Northeast Asia and Korea: a multi-RCM study

This study examines future changes in precipitation over Northeast Asia and Korea using five regional climate model (RCM) simulations driven by single global climate model (GCM) under two representative concentration pathway (RCP) emission scenarios. Focusing on summer season (June–July–August) when heavy rains dominate in this region, future changes in precipitation and associated variables including temperature, moisture, and winds are analyzed by comparing future conditions (2071–2100) with a present climate (1981–2005). Here, physical mechanisms are examined by analyzing moisture flux convergence at 850 hPa level, which is found to have a close relationship to precipitation and by assessing contribution of thermodynamic effect (TH, moisture increase due to warming) and dynamic effect (DY, atmospheric circulation change) to changes in the moisture flux convergence. Overall background warming and moistening are projected over the Northeast Asia with a good inter-RCM agreement, indicating dominant influence of the driving GCM. Also, RCMs consistently project increases in the frequency of heavy rains and the intensification of extreme precipitation over South Korea. Analysis of moisture flux convergence reveals competing impacts between TH and DY. The TH effect contributes to the overall increases in mean precipitation over Northeast Asia and in extreme precipitation over South Korea, irrespective of models and scenarios. However, DY effect is found to induce local-scale precipitation decreases over the central part of the Korean Peninsula with large inter-RCM and inter-scenario differences. Composite analysis of daily anomaly synoptic patterns indicates that extreme precipitation events are mainly associated with the southwest to northeast evolution of large-scale low-pressure system in both present and future climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Regional patterns of postwildfire streamflow response in the Western United States: The importance of scale‐specific connectivity

Abstract Wildfires can impact streamflow by modifying net precipitation, infiltration, evapotranspiration, snowmelt, and hillslope run‐off pathways. Regional differences in fire trends and postwildfire streamflow responses across the conterminous United States have spurred concerns about the impact on streamflow in forests that serve as water resource areas. This is notably the case for the Western United States, where fire activity and burn severity have increased in conjunction with climate change and increased forest density due to human fire suppression. In this review, we discuss the effects of wildfire on hydrological processes with a special focus on regional differences in postwildfire streamflow responses in forests. Postwildfire peak flows and annual water yields are generally higher in regions with a Mediterranean or semi‐arid climate (Southern California and the Southwest) compared to the highlands (Rocky Mountains and the Pacific Northwest), where fire‐induced changes in hydraulic connectivity along the hillslope results in the delivery of more water, more rapidly to streams. No clear streamflow response patterns have been identified in the humid subtropical Southeastern United States, where most fires are prescribed fires with a low burn severity, and more research is needed in that region. Improved assessment of postwildfire streamflow relies on quantitative spatial knowledge of landscape variables such as prestorm soil moisture, burn severity and correlations with soil surface sealing, water repellency, and ash deposition. The latest studies furthermore emphasize that understanding the effects of hydrological processes on postwildfire dynamic hydraulic connectivity, notably at the hillslope and watershed scales, and the relationship between overlapping disturbances including those other than wildfire is necessary for the development of risk assessment tools.

Hallema, Dennis W.↗

DOE OSTI2017

The Changing Character of Twenty-First-Century Precipitation over the Western United States in the Variable-Resolution CESM

Abstract The changing characters of precipitation frequency and intensity have been comprehensively investigated from the recent historical period to the end of the twenty-first century over the western United States. Variable-resolution Community Earth System Model (VR-CESM) ensemble simulations are applied with a fine grid resolution of ~0.25° over the study area. Simulations are forced with prescribed sea surface temperatures, sea ice extent, and greenhouse gas concentrations from the representative concentration pathway 8.5 (RCP8.5) scenario. VR-CESM is shown to be effective at accurately capturing the spatial patterns of the historical precipitation climatology. The results of VR-CESM output provide significantly regional details with crucial enhancement of precipitation representations over complex terrain. In the Intermountain West and U.S. Southwest, a statistically significant increase in mean precipitation and rainy days through midcentury is observed, although this trend is tempered by the end of the century in response to a decrease in relative humidity. Over the Pacific Northwest, extreme precipitation events are observed to increase significantly as a result of increased cool season integrated vapor transport associated with a moistening of the cool seasons and drying through the warm seasons. In particular, extreme precipitation in this region appears to increase more rapidly than would be predicted by the Clausius–Clapeyron relationship. No clear climate signal emerges in mean precipitation or extreme events in the majority of California, where the precipitation climatology is attributed to large interannual variabilities that are tied closely to ENSO patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Role of CO 2 , climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

We examined the net terrestrial carbon flux to the atmosphere (F TA ) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global F TA amplitude increase (19 ± 8%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56%, -3 ± 74 and 20 ± 30% to rising CO 2 , climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO 2 fertilization is the strongest control -with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global < i > F TA : some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between < i > F TA amplitude increase and increase in land carbon sink ( < i > R 2 Combining double low line 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO 2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Dynamic Amplification of Subtropical Extreme Precipitation in a Warming Climate

Projected precipitation changes in a warming climate vary considerably, spatially, and between intensities. The changes can be greater or less than the ~7% K -1 Clausius-Clapeyron (CC) prediction, owing to dynamic effects. Using two global-climate-model large ensembles, we quantify the dynamically induced changes to precipitation extremes from the present (1996–2005) to late-21st-century (2071–2080) climates, as a function of recurrence interval, focusing on the subtropics. We separate non-CC changes into a term proportional to the present-day vertical-velocity spatial pattern (i.e., an amplification or damping thereof by a constant factor) and a residual. The amplitude term varies with recurrence interval, approximately canceling (doubling) CC for moderate (large) extremes, increasing precipitation variability. Contrastingly, the residual is quasi-uniform across recurrence intervals but spatially heterogeneous, weakening extremes over dry zones. This residual may be related to Hadley cell expansion, although this explanation is insufficient to explain many features, and other possible mechanisms are discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Changes in Precipitation From North Atlantic Tropical Cyclones Under RCP Scenarios in the Variable-Resolution Community Atmosphere Model

Decreasing climate models' grid spacing improves the representation of tropical cyclones at decadal time scales. In this study, a variable-resolution (VR) version of the Community Atmosphere Model 5 (CAM5-VR) is utilized to study North Atlantic tropical cyclone climatology in ensemble historical climate simulations and under two Representative Concentration Pathway (RCP) projections (RCP4.5 and RCP8.5). Basin-wide tropical cyclone counts decrease in the RCP simulations, although landfalling storm counts do not show as straightforward of a pattern, especially when focusing on regional changes. Lifetime maximum intensity metrics suggest that tropical cyclones increase in strength in the RCP ensembles. However, despite increases in tropical cyclone-related precipitation rates and the amount of precipitation produced per storm with warming, the annual average Rx5day from tropical cyclones over the eastern United States decreases due to less landfalling storms. This work is part of a continued effort to quantify how tropical cyclone-induced hazards may change in future climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Response patterns of simulated corn yield and soil nitrous oxide emission to precipitation change

Abstract Background Precipitation plays an important role in crop production and soil greenhouse gas emissions. However, how crop yield and soil nitrous oxide (N 2 O) emission respond to precipitation change, particularly with different background precipitations (dry, normal, and wet years), has not been well investigated. In this study, we examined the impacts of precipitation changes on corn yield and soil N 2 O emission using a long-term (1981–2020, 40 years) climate dataset as well as seven manipulated precipitation treatments with different background precipitations using the DeNitrification-DeComposition (DNDC) model. Results Results showed large variations of corn yield and precipitation but small variation of soil N 2 O emission among 40 years. Both corn yield and soil N 2 O emission showed near linear relationships with precipitation based on the long-term precipitation data, but with different response patters of corn yield and soil N 2 O emission to precipitation manipulations. Corn yield showed a positive linear response to precipitation manipulations in the dry year, but no response to increases in precipitation in the normal year, and a trend of decrease in the wet year. The extreme drought treatments reduced corn yield sharply in both normal and wet years. In contrast, soil N 2 O emission mostly responded linearly to precipitation manipulations. Decreases in precipitation in the dry year reduced more soil N 2 O emission than those in the normal and wet years, while increases in precipitation increased more soil N 2 O emission in the normal and wet years than in the dry year. Conclusions This study revealed different response patterns of corn yield and soil N 2 O emission to precipitation and highlights that mitigation strategy for soil N 2 O emission reduction should consider different background climate conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

Uncertainty in Model Predictions of Vibrio Vulnificus Response to Climate Variability and Change: A Chesapeake Bay Case Study

The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4 C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.

model predictions↗