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At least 1,675 records · Page 93

Predicted slowdown in the rate of Atlantic sea ice loss

Abstract Coupled climate models initialized from historical climate states and subject to anthropogenic forcings can produce skillful decadal predictions of sea surface temperature change in the subpolar North Atlantic. The skill derives largely from initialization, which improves the representation of slow changes in ocean circulation and associated poleward heat transport. We show that skillful predictions of decadal trends in Arctic winter sea ice extent are also possible, particularly in the Atlantic sector. External radiative forcing contributes to the skill of retrospective decadal sea ice predictions, but the spatial and temporal accuracy is greatly enhanced by the more realistic representation of ocean heat transport anomalies afforded by initialization. Recent forecasts indicate that a spin‐down of the thermohaline circulation that began near the turn of the century will continue, and this will result in near‐neutral decadal trends in Atlantic winter sea ice extent in the coming years, with decadal growth in select regions.

Yeager, Stephen G.↗

Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors

Differences in simulations of tropical marine low-cloud cover (LCC) feedback are sources of significant spread in temperature responses of climate models to anthropogenic forcing. Here we show that in models the feedback is mainly driven by three large-scale changes—a strengthening tropical inversion, increasing surface latent heat flux, and an increasing vertical moisture gradient. Variations in the LCC response to these changes alone account for most of the spread in model-projected 21st century LCC changes. A methodology is devised to constrain the LCC response observationally using sea surface temperature (SST) as a surrogate for the latent heat flux and moisture gradient. In models where the current climate's LCC sensitivities to inversion strength and SST variations are consistent with observed, LCC decreases systematically, which would increase absorption of solar radiation. These results support a positive LCC feedback. Finally, correcting biases in the sensitivities will be an important step toward more credible simulation of cloud feedbacks.

58 GEOSCIENCES↗

A regional (land–ocean) comparison of the seasonal to decadal variability of the Northern Hemisphere jet stream 1871–2011

Seasonal to decadal variations in Northern Hemisphere jet stream latitude and speed over land (Eurasia, North America) and oceanic (North Atlantic, North Pacific) regions are presented for the period 1871–2011 from the Twentieth Century Reanalysis dataset. Significant regional differences are seen on seasonal to decadal timescales. Seasonally, the jet latitude range is lower over the oceans compared to land, reduced from 20° over Eurasia to 10° over the North Atlantic where the ocean meridional heat transport is greatest. The mean jet latitude range is at a minimum in winter (DJF), particularly along the western boundary of the North Pacific and North Atlantic, where the land-sea contrast and SST gradients are strongest. The 141-year trends in jet latitude and speed show differences on a regional basis. The North Atlantic has significant increasing jet latitude trends in all seasons, up to 3° in winter. Eurasia has significant increasing trends in winter and summer, however, no increase is seen across the North Pacific or North America. Jet speed shows significant increases evident in winter (up to 4.7 ms –1 ), spring and autumn over the North Atlantic, Eurasia and North America however, over the North Pacific no increase is observed. Long term trends are generally overlaid by multidecadal variability, particularly evident in the North Pacific, where 20-year variability in jet latitude and jet speed are seen, associated with the Pacific Decadal Oscillation which explains 50% of the winter variance in jet latitude since 1940. The results highlight that northern hemisphere jet variability and trends differ on a regional basis (North Atlantic, North Pacific, Eurasia and North America) on seasonal to decadal timescales, suggesting that different mechanisms are influencing the jet latitude and speed. This is important from a climate modelling perspective and for climate predictions in the near and longer term.

54 ENVIRONMENTAL SCIENCES↗

Land-use transition for bioenergy and climate stabilization: model comparison of drivers, impacts and interactions with other land use based mitigation options

This study is a model comparison assessing the drivers and impacts of bioenergy production on the global land system and the interaction with other land use based mitigation options in the context of the EMF 27 project. We compare and evaluate results from three integrated assessment models (GCAM, IMAGE, and ReMIND/MAgPIE). All three models project that dedicated bioenergy crops and biomass residues are a potentially important and cost-effective component of the energy system. But bioenergy deployment levels and feedstock composition vary notably across models as do the implications for land-use and greenhouse gas emissions and the interaction with other land use based mitigation measures. Despite numerous model differences, we identify a few that are likely contributing to differences in land-use and emissions attributable to energy crop deployment.

Popp, Alexander↗

Mapping ecoregions under climate change: a case study from the biological ‘crossroads’ of three continents, Turkey

Context: Besides climate change vulnerability, most ecosystems are under threat from a history of improper land-use and conservation policies, yet there is little existing long-term ecological research infrastructure in Turkey. In regions with no ecological networks across large landscapes, ecoregion concept offers opportunities for characterizing the landscape under changing climate.Objectives: Aim is to develop contemporary and future quantitative ecoregions for Turkey based on climate model outputs, to identify climate change-sensitive areas of biodiversity and conservation significance, and to provide a framework for a comprehensive ecological observatory network design.Methods: Using Multivariate Spatio-Temporal Clustering and climate data contemporary and projected future distributions of Turkey’s ecoregions are delineated at several division levels.Results: Turkey’s contemporary ecoregions generally show a northward shift by the end of this century and the lengthening of the growing season across the country, especially eastward and northward. The increase in growing season length, along with the shift in precipitation seasonality and increasing growing season precipitation, shape future conditions within the climate change-sensitive areas. Apart from transboundary ecological and socioeconomic significance, these potentially vulnerable ecosystems also constitute the majority of Turkey’s biodiversity hotspots.Conclusions: Our study marks the first ‘ecoregionalization’ study for Turkey based on both contemporary and future climate scenarios. For countries like Turkey, where large-scale ecological networks have not been established, using such quantitative methodology for delineation of optimal ecoclimatic regions, and for mapping environments at risk from climate change provides an invaluable perspective for conservation planning strategies, and a framework for a comprehensive ecological observatory network design.

54 ENVIRONMENTAL SCIENCES↗

Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land

Recent progress in satellite observations has provided unprecedented opportunities to monitor vegetation activity at global scale. However, a major challenge in fully utilizing remotely sensed data to constrain land surface models (LSMs) lies in inconsistencies between simulated and observed quantities. For example, gross primary productivity (GPP) and transpiration (T) that traditional LSMs simulate are not directly measurable from space, although they can be inferred from spaceborne observations using assumptions that are inconsistent with those LSMs. In comparison, canopy reflectance and fluorescence spectra that satellites can detect are not modeled by traditional LSMs. To bridge these quantities, we presented an overview of the next generation land model developed within the Climate Modeling Alliance (CliMA), and simulated global GPP, T, and hyperspectral canopy radiative transfer (RT; 400–2,500 nm for reflectance, 640–850 nm for fluorescence) at hourly time step and 1° spatial resolution using CliMA Land. CliMA Land predicts vegetation indices and outgoing radiances, including solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near infrared reflectance of vegetation (NIRv) for any given sun-sensor geometry. The spatial patterns of modeled GPP, T, SIF, NDVI, EVI, and NIRv correlate significantly with existing data-driven products (mean R 2 = 0.777 for 9 products). CliMA Land would be also useful in high temporal resolution simulations, for example, providing insights into when GPP, SIF, and NIRv diverge.

54 ENVIRONMENTAL SCIENCES↗

Climate policy models need to get real about people — here’s how

Here, to predict how society and political systems might actually respond to warming, upgrade integrated assessment models. Political support for decarbonizing the global economy is at an all-time high. The good news is that about two-thirds of carbon emissions come from countries that have committed to reach ‘net zero’ by mid-century — they aim to cut their greenhouse-gas outputs and capture as much as they emit. The bad news? The computer models that analysts use to assess routes to achieve such goals are missing a crucial factor: politics.

Peng, Wei↗

Precipitation trends determine future occurrences of compound hot–dry events

Compound hot–dry events—co-occurring hot and dry extremes—frequently cause damages to human and natural systems, often exceeding separate impacts from heatwaves and droughts. Strong increases in the occurrence of these events are projected with warming, but associated uncertainties remain large and poorly understood. Here, using climate model large ensembles, we show that mean precipitation trends exclusively modulate the future occurrence of compound hot–dry events over land. This occurs because local warming will be large enough that future droughts will always coincide with at least moderately hot extremes, even in a 2°C warmer world. By contrast, precipitation trends are often weak and equivocal in sign, depending on the model, region and internal climate variability. Therefore, constraining regional precipitation trends will also constrain future compound hot–dry events. These results help to assess future frequencies of other compound extremes characterized by strongly different trends in the drivers.

54 ENVIRONMENTAL SCIENCES↗

Climate change drives reduced biocontrol of the invasive spongy moth

The effects of climate change on forest-defoliating insects are poorly understood, but could severely reduce forest productivity, biodiversity and timber production. For decades following its introduction in 1869, the spongy moth ( Lymantria dispar ) severely defoliated North American forests, but the introduction of the fungal pathogen Entomophaga maimaiga in 1989 suppressed spongy moth defoliation for 27 years. E. maimaiga , however, needs cool, moist conditions, whereas climate change is bringing hot, dry conditions to the range of the insect. Here, in this work, we use an empirically verified eco-climate model to project that climate change will sharply reduce E. maimaiga infection rates, thereby increasing spongy moth defoliation. Recent rebounds in defoliation are consistent with our projections. Our work demonstrates that the effects of climate change on species interactions can have important consequences for natural ecosystems.

climate-change ecology↗

Transforming How Climate System Models are Used: A Global, Multi-Resolution Approach to Regional Ocean Modeling

We review the results obtained under grant support. Details are given in the publications listed at the end of the review. We also provide lists of the personnel funded by the grant and of other collaborators on grant-related research and of the talks delivered, also under grant related research. We collaborated closely with geophysicists at the Los Alamos National Laboratory and the National Center for Atmospheric Research; especially noteworthy is our collaboration with Todd Ringler of LANL who was an active partner on much of our work.

54 ENVIRONMENTAL SCIENCES↗

Improving representation of drought stress and fire emissions in climate carbon models: measurements and modeling with a focus on the western USA

The objective of the proposed research was to collect data and develop models to improve our understanding of the role of drought and fire impacts on the terrestrial carbon cycle in the western US, including impacts associated with urban systems as they impacted regional carbon cycles. Using data we collected and a synthesis of other measurements, we developed new ways (a) to evaluate the representation of drought stress and fire emissions in the Community Land Model, (b) to model net ecosystem exchange combining ground level atmospheric observations with boundary layer theory, (c) to model upstream impacts of fire and fossil fuel emissions on atmospheric carbon dioxide observations, and (d) to model carbon dioxide observations within urban systems and at the urban-wildland interfaces of forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Diagnosis of convective organization and cold pools using ARM datasets and evaluation of a unified convection parameterization (UNICON)

Tropical thunderstorms often cluster together. Studies have suggested that the degree to which the tropical thunderstorms are clustered impacts Earth's energy balance and water cycle, as well as extreme precipitation events. However, the processes controlling the spatial distribution of the thunderstorms are poorly understood and are not properly represented in most computer models for weather and climate prediction. Under the goals of better understanding how convection organizes at the mesoscale and advancing the representation of mesoscale convective organization in global climate models, we i) objectively quantified the degrees of convective organization and diagnosed cold pool processes using ARM field campaign observations, ii) examined the organization processes in storm-resolving model simulations, and iii) evaluated the impacts of mesoscale convective organization in global model simulations. The project yielded a firm reference against which the global model representation of mesoscale convective organization and cold pools can be evaluated against and shed new light into the role of parameterized convective organization in the global model simulation of the basic state and variability. Our results revealed two distinct phases of convective clustering during the two-day rain episodes (Cheng et al. 2018) and a new mechanism through which vertical wind shear in the low-troposphere can aid convective organization over tropical oceans (Cheng et al. 2020). It was demonstrated that the interactive representation of cold pools and mesoscale convective organization is key for global models to successfully simulate both the mean state and intraseasonal variability in the tropics (Ahn et al. 2019; 2020).

54 ENVIRONMENTAL SCIENCES↗