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At least 1,369 records · Page 76

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Variability↗

Relating Paleoclimate Data and Past Temperature Gradients: Some Suggestive Rules

Understanding tropical sensitivity is perhaps the major concern confronting researchers, for both past and future climate change issues. Tropical data has been beset by contradictions, and many techniques applicable to the extratropics are either unavailable or fraught with uncertainty when applied at low latitudes. Paleoclimate data, if interpreted within the context of the latitudinal temperature gradient data they imply, can be used to estimate what happened to tropical temperatures in the past, and provide a first guess for what might happen in the future. The approach is made possible by the modeling result that atmospheric dynamical changes, and the climate impacts they produce, respond primarily to temperature gradient changes. Here we review some "rules" obtained from GCM (General Circulation Model) experiments with different sea surface temperature gradients and different forcing, that can be used to relate paleoclimate reconstructions to the likely temperature gradient changes they suggest.

Rind, David↗

Modeling Climate-Water Impacts on Electricity Sector Capacity Expansion: Preprint

Climate change has the potential to exacerbate water availability concerns for thermal power plant cooling, which is responsible for 41% of U.S. water withdrawals. This analysis describes an initial link between climate, water, and electricity systems using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS) electricity system capacity expansion model. Average surface water projections from Coupled Model Intercomparison Project 3 (CMIP3) data are applied to surface water rights available to new generating capacity in ReEDS, and electric sector growth is compared with and without climate-influenced water rights. The mean climate projection has only a small impact on national or regional capacity growth and water use because most regions have sufficient unappropriated or previously retired water rights to offset climate impacts. Climate impacts are notable in southwestern states that purchase fewer water rights and obtain a greater share from wastewater and other higher-cost water resources. The electric sector climate impacts demonstrated herein establish a methodology to be later exercised with more extreme climate scenarios and a more rigorous representation of legal and physical water availability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Terrestrial Ecosystem Science (Flyer 2020)

A significant fraction of the carbon dioxide (CO 2 ) released to the atmosphere during energy production is taken up by terrestrial ecosystems. This carbon “sink” represents an important but poorly characterized buffer for offsetting the greenhouse gas effects of anthropogenic CO 2 emissions. Also unclear are the effects of related processes such as nutrient, water, and energy cycling—in addition to climate variability and change— on that uptake. Resolving the terrestrial biosphere’s role in the global carbon cycle is consequently a high priority for the Terrestrial Ecosystem Science (TES) program within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER). Understanding the mechanisms and dynamics of ecosystem processes in the face of a changing climate is also essential for improving the representation of terrestrial ecosystems and climate feedbacks in Earth system models (ESMs). TES supports research to advance fundamental understanding of terrestrial ecosystems and their roles in a changing climate.

54 ENVIRONMENTAL SCIENCES↗

Environmental Thermodynamic Effects on Future Changes of Mesoscale Convective Systems and Isolated Deep Convection Over the US: A Case Study

Mesoscale convective systems (MCSs) and isolated deep convection (IDC) significantly influence local weather conditions and the hydrological cycle across the United States. Their future changes under warming is critical to the society. However, the exact impacts of thermodynamic environmental changes on them are difficult to resolve using climate model simulations which integrate both dynamic and thermodynamic factors. This study explores a theoretical modeling approach to isolate environmental thermodynamic effects on their future changes through a case study. For a 50-day period during the 2020 summer, a pair of convection-permitting model simulations indicate contrasting changes in MCSs and IDC between inland and coastal regions under pseudo global warming. Driven by the thermodynamic environments of these simulations, a single-column parcel model indicates a decrease in the frequency of IDC occurrences, along with increases in duration and precipitation amount under warming, attributable to rising most unstable convective available potential energy (MUCAPE), convective inhibition (MUCIN), and precipitable water (PW). A multi-column parcel model reveals contrasting changes in the frequency and mean area of MCSs between inland and coastal regions, underscoring the increase in mean MUCIN over inland regions and increases in mean MUCAPE and PW over coastal regions. The increase in mean MCS area over inland regions is linked to the interplay between accelerated gust fronts and enhanced subsidence strength, which is further traced to the unchanged mean MUCIN but increased mean MUCAPE in large-scale environments. In conclusion, these case study results suggest a major role of thermodynamic environmental changes in controlling characteristics of MCSs and IDC under warming.

Mesoscale convective system↗

Climate change, malaria and neglected tropical diseases: a scoping review

Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

60 APPLIED LIFE SCIENCES↗

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decompose the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2 -/non-CO 2 -forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.

54 ENVIRONMENTAL SCIENCES↗

Harmonization of Land-Use Scenarios for the Period 1500-2100: 600 Years of Global Gridded Annual Land-Use Transitions, Wood Harvest, and Resulting Secondary Lands

In preparation for the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the international community is developing new advanced Earth System Models (ESM) to assess the combined effects of human activities (e.g. land use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being provided by four Integrated Assessment Model (IAM) teams to be used as input to the ESMs for future carbon-climate projections (Moss et al., 2010). The diversity of approaches and requirements among IAMs and ESMs for tracking land-use change, along with the dependence of model projections on land-use history, presents a challenge for effectively passing data between these communities and for smoothly transitioning from the historical estimates to future projections. Here, a harmonized set of land-use scenarios are presented that smoothly connects historical reconstructions of land use with future projections, in the format required by ESMs.

09 BIOMASS FUELS↗

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.

Moore, Berrien, III↗

Climate‐driven changes to the spatio‐temporal distribution of the parasitic nematode, Haemonchus contortus, in sheep in Europe

Abstract Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio‐temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q 0 , adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan‐European spatio‐temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q 0 simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within‐host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q 0 simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2–3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary control strategies, and potentially drive local adaptation to climate change in parasite populations.

Rose, Hannah↗

CFCI3 (CFC-11): UV Absorption Spectrum Temperature Dependence Measurements and the Impact on Atmospheric Lifetime and Uncertainty

CFCl3 (CFC-11) is both an atmospheric ozone-depleting and potent greenhouse gas that is removed primarily via stratospheric UV photolysis. Uncertainty in the temperature dependence of its UV absorption spectrum is a significant contributing factor to the overall uncertainty in its global lifetime and, thus, model calculations of stratospheric ozone recovery and climate change. In this work, the CFC-11 UV absorption spectrum was measured over a range of wavelength (184.95 - 230 nm) and temperature (216 - 296 K). We report a spectrum temperature dependence that is less than currently recommended for use in atmospheric models. The impact on its atmospheric lifetime was quantified using a 2-D model and the spectrum parameterization developed in this work. The obtained global annually averaged lifetime was 58.1 +- 0.7 years (2 sigma uncertainty due solely to the spectrum uncertainty). The lifetime is slightly reduced and the uncertainty significantly reduced from that obtained using current spectrum recommendations

photolysis↗

Spatial Heterogeneity in Ecologically Important Climate Variables at Coarse and Fine Scales in a High-Snow Mountain Landscape

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (~20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change.

54 ENVIRONMENTAL SCIENCES↗

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗

Climate Change Projections in CESM1(CAM5) Compared to CCSM4

Future climate change projections for phase 5 of the Coupled Model Intercomparison Project (CMIP5) are introduced for the Community Earth System Model version 1 that includes the Community Atmospheric Model version 5 [CESM1(CAM5)]. These findings are compared to the Community Climate System Model, version 4 (CCSM4) and include simulations using the representative concentration pathway (RCP) mitigation scenarios, and extensions for those scenarios beyond 2100 to 2300. Equilibrium climate sensitivity of CESM1(CAM5) is 4.10°C, which is higher than the CCSM4 value of 3.20°C. The transient climate response is 2.33°C, compared to the CCSM4 value of 1.73°C. Thus, even though CESM1(CAM5) includes both the direct and indirect effects of aerosols (CCSM4 had only the direct effect), the overall climate system response including forcing and feedbacks is greater in CESM1(CAM5) compared to CCSM4. The Atlantic Ocean meridional overturning circulation (AMOC) in CESM1(CAM5) weakens considerably in the twenty-first century in all the RCP scenarios, and recovers more slowly in the lower forcing scenarios. The total aerosol optical depth (AOD) changes from ~0.12 in 2006 to ~0.10 in 2100, compared to a preindustrial 1850 value of 0.08, so there is less negative forcing (a net positive forcing) from that source during the twenty-first century. As a result, the change from 2006 to 2100 in aerosol direct forcing in CESM1(CAM5) contributes to greater twenty-first century warming relative to CCSM4. There is greater Arctic warming and sea ice loss in CESM1(CAM5), with an ice-free summer Arctic occurring by about 2060 in RCP8.5 (2040s in September) as opposed to about 2100 in CCSM4 (2060s in September).

54 ENVIRONMENTAL SCIENCES↗

Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information

Long-term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small-scale historical hydrological data with large-scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long-term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developed framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site-specific watershed reactive transport models to predict how climate-induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services.

58 GEOSCIENCES↗

The Impact of CCS Readiness on the Evolution of China's Electric Power Sector

In this study, GCAM-China is exercised to examine the impact of CCS availability on the projected evolution of China’s electric power sector under the Paris Increased Ambition policy scenario developed by Fawcett et al. based on the Intended Nationally Determined Contributions (INDCs) submitted under the COP-21 Paris Agreement. This policy scenario provides a backdrop for understanding China’s electric generation mix over the coming century under several CCS availability scenarios: CCS is fully available for commercial-scale deployment by 2025; by 2050; by 2075; and CCS is unavailable for use in meeting the modelled mitigation targets through 2100. Without having CCS available, the Chinese electric power sector turns to significant use of nuclear, wind, and solar to meet growing demands and emissions targets, at a cost. Should large-scale CCS deployment be delayed in China by 25 years, the modeled per-ton cost of climate change mitigation is projected to be roughly $420/tC (2010 US dollars) by 2050, relative to $360/tC in the case in which CCS is available to deploy by 2025, a 16% increase. Once CCS is available for commercial use, mitigation costs for the two cases converge, equilibrating by 2085. However, should CCS be entirely unavailable to deploy in China, the mitigation cost spread, compared to the 2025 case, doubles by 2075 ($580/tC and $1130/tC respectively), and triples by 2100 ($1050/tC vs. $3200/tC). However, while delays in CCS availability may have short-term impacts on China’s overall per-ton cost of meeting the emissions reduction target evaluated here, as well as total mitigation costs, the carbon price is likely to approach the price path associated with the full CCS availability case within a decade of CCS deployment. Having CCS available before the end of the century, even under the delays examined here, could reduce the total amount of nuclear and renewable energy that must deploy, reducing the overall cost of meeting the emissions mitigation targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Monitoring and modeling hydrologic conditions in Ukraine for hydropower generation

Study region: The Dnieper and Dniester Rivers of Ukraine. Study focus: The ongoing conflict in Ukraine has caused disruptions to electricity generation, of which hydroelectric sources contribute approximately 9 % to the country’s needs. With the takeover of the Zaporizhzhia nuclear power plant by enemy forces, the loss of the Kakhovka hydroelectric dam, and the future impacts of the conflict on electricity generation unclear, it may be valuable for the Ukrainian government to better understand how it could leverage hydroelectric power sources in the near future. Unfortunately, measurements of river discharge throughout Ukraine ceased data collection in the late 1980’s to early 1990’s. To address this data gap, we developed a protocol that combined satellite-based time-series measurements of river width at seven locations throughout Ukraine from 2013 to 2023 with reanalysis data, climate-model predictions, and hydrologic models to both provide a means of monitoring a proxy for near-real-time discharge and also predict near-term (i.e., 2023–2030) hydrologic patterns for the region. New hydrological insights for the region: We ran new algorithms on 144 WorldView-2 and WorldView-3 satellite images to map rivers and extract width, one of which was validated against river gauge data located along the same river but in a neighboring country. Hydrologic models using two climate scenarios found minimal change in annual discharge at all sites, but magnitude and timing of peak discharge showed a moderate trend. The results suggest that hydropower is underutilized in Ukraine.

13 HYDRO ENERGY↗

Last Century Warming Over the Canadian Atlantic Shelves Linked to Weak Atlantic Meridional Overturning Circulation

We report the Atlantic meridional overturning circulation (AMOC) is a key component of the global climate system. Recent studies suggested a twentieth-century weakening of the AMOC of unprecedented amplitude (~15%) over the last millennium. Here we present a record of δ 18 O in benthic foraminifera from sediment cores retrieved from the Laurentian Channel and demonstrate that the δ 18 O trend is linked to the strength of the AMOC. In this 100-year record, the AMOC signal decreased steadily to reach its minimum value in the late 1970s, where the weakest AMOC signal then remains constant until 2000. We also present a longer δ 18 O record of 1,500 years and highlight the uniqueness of the last century δ 18 O trend. Moreover, the Little Ice Age period is characterized by statistically heavier δ 18 O, suggesting a relatively weak AMOC. Lastly, implications for understanding the mechanisms driving the intensity of AMOC under global warming and high-latitude freshwater input are discussed.

58 GEOSCIENCES↗