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At least 793 records · Page 44

The impacts of warming on rapidly retreating high-altitude, low-latitude glaciers and ice core-derived climate records

Alpine glaciers in the low- and mid-latitudes respond more quickly than large polar ice sheets to changes in temperature, precipitation, cloudiness, humidity, and radiation. Many high-altitude glaciers are monitored by ground observations, aerial photography, and satellite-borne sensors. Regardless of latitude and elevation, nearly all nonpolar glaciers and ice caps are undergoing mass loss, which compromises the records of past climate preserved within them. Almost without exception, the retreat of these ice fields is persistent, and a very important driver is the recent warming of the tropical troposphere and oceans. Here we present data on the decrease in the surface area of four glaciers from low- to mid-latitude mountainous regions: the Andes of Peru and northern Bolivia, equatorial east Africa, equatorial Papua, Indonesia, and the western Tibetan Plateau. Climate records based on oxygen isotopic ratios (δ18O) measured in ice cores drilled from several glaciers in these regions reveal that the records from elevations below ~6000 m above sea level have been substantially modified by seasonal melting and the movement of meltwater through porous upper firn layers. Fortunately, δ18O records recovered from higher altitude sites still contain well-preserved seasonal variations to the surface; however, the projected increase in the rate of atmospheric warming implies that climate records from higher elevation glaciers will eventually also be degraded. A long-term ice core collection program on the Quelccaya ice cap in Peru, Earth's largest tropical ice cap, illustrates that the deterioration of its climate record is concomitant with the increase in mid-troposphere temperatures. The melting ice and resulting growth of proglacial lakes presents an imminent hazard to nearby communities. The accelerating melting of glaciers, if sustained, ensures the eventual loss of unique and irreplaceable climate histories, as well as profound economic, agricultural, and cultural impacts on local communities.

Low-latitude glaciers↗

Evolution of Tropical Cyclone Properties Across the Development Cycle of the GISS-E3 Global Climate Model

The next-generation global climate model from the NASA Goddard Institute for Space Studies, GISS-E3, contains many improvements to resolution and physics that allow for improved representation of tropical cyclones (TCs) in the model. This study examines the properties of TCs in two different versions of E3 at different points in its development cycle, run for 20 years at 0.5 degree resolution, and compares these TCs with observations, the previous generation GISS model, E2, and other climate models. E3 shares many TC biases common to global climate models, such as having too few tropical cyclones, but is much improved from E2. E3 produces strong enough TCs that observation-based wind speed thresholds can now be used to detect and track them, and some storms now reach hurricane intensity; neither of these was true of E2. Model development between the first and second versions of E3 further increased the number and intensity of TCs and reduced TC count biases globally and in most regions. One-year sensitivity tests to changes in various microphysical and dynamical tuning parameters are also examined. Increasing the entrainment rate for the more strongly-entraining plume in the convection scheme increases the number of TCs (though also affecting other climate variables, and in some cases increasing biases). Variations in divergence damping did not have a strong effect on simulated TC properties, contrary to expectations based on previous studies. Overall, the improvements in E3 make it more credible for studies of TC activity and its relationship to climate.

Tropical Cyclones↗

Temporal and Spatial Distribution of Health, Labor, and Crop Benefits of Climate Change Mitigation in the United States

Societal benefits from climate change mitigation accrue via multiple pathways. We examine the US impacts of emission changes on several factors that are affected by both climate and air quality responses. Nationwide benefits through midcentury stem primarily from air quality improvements, which are realized rapidly, and include human health, labor productivity, and crop yield benefits. Benefits from reduced heat exposure become large around 2060, thereafter often dominating over those from improved air quality. Monetized benefits are in the tens of trillions of dollars for avoided deaths and tens of billions for labor productivity and crop yield increases and reduced hospital expenditures. Total monetized benefits this century are dominated by health and are much larger than in previous analyses due to improved understanding of the human health impacts of exposure to both heat and air pollution. Benefit–cost ratios are therefore much larger than in prior studies, especially those that neglected clean air benefits. Specifically, benefits from clean air exceed costs in the first decade, whereas benefits from climate alone exceed costs in the latter half of the century. Furthermore, monetized US benefits largely stem from US emissions reductions. Increased emphasis on the localized, near-term air quality–related impacts would better align policies with societal benefits and, by reducing the mismatch between perception of climate as a risk distant in space and time and the need for rapid action to mitigate long-term climate change, might help increase acceptance of mitigation policies.

climate change↗

Climate Data Record Derived from Hyperspectral Sounders on AQUA, S-NPP and NOAA 20

Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. It eliminates or reduces the errors due to inconsistent L2 algorithms. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

climate data record↗

LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2

The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5°C) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new CESM2 schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time-step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed-phase clouds, which leads to an increase in cloud ice content and a weaker shortwave cloud feedback over mid-to-high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate-calibrated CESM2 (PaleoCalibr), which simulates well the observed twentieth century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (∼4°C) and a 20% weaker aerosol-cloud interaction than CESM2. PaleoCalibr represents a physically more consistent treatment of cloud microphysics than CESM2 and is a valuable tool in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

equilibrium climate sensitivity↗

Quantifying the Influence of Mechanistic Representation of Particle Dry Deposition on Historical Changes in Aerosol-Climate Interactions

Dry deposition removes short-lived climate forcers and their precursors from the atmosphere. The aerosol dry deposition schemes in many global climate models have been untouched for decades. Previous work hints that aerosol dry deposition is an uncertainty with respect to aerosol impacts on climate change. Here we demonstrate the impact of a more mechanistic aerosol dry deposition parameterization on the historical aerosol direct and cloud albedo effects using the NASA GISS global chemistry-climate model. We investigate two aerosol configurations – a “bulk” mass-based scheme and a modal scheme that more explicitly represents internal mixing and microphysics – of the global model. Both configurations show ~20% larger historical increases in non-dust aerosols globally with more mechanistic dry deposition. Changes to particle dry deposition, which are strongly a function of particle diameter, have a greater influence on the cloud albedo effect (up to 0.1 W m-2) when aerosols are more explicitly resolved in the modal scheme. On the other hand, impacts on the direct aerosol effect are small for both model configurations. In both aerosol configurations, the global climate effects are relatively insensitive to uncertainty in the strength of the uptake to dry deposition as suggested by (limited) measurements. In general, the low number of aerosol flux measurements and strong variability across existing observations challenge confidence in our understanding of dry depositional processes and changes with environmental conditions. Nonetheless, our work suggests that changes in dry deposition may be important for accurately estimating increases in aerosol abundances over the historical period, which is key for correct inferences about how cooling from aerosols has offset warming from greenhouse gases.

Dry deposition↗

Global Nitrogen Needs to Improve Wheat Yield Under Climate Change

Increasing global food demand will require more food production without further exceeding the planetary boundaries, while at the same time adapting to climate change. We used an ensemble of wheat simulation models, with improved yield traits from the highest-yielding wheat genotypes to quantify potential yield gains and associated N requirements. This was explored for current and climate change scenarios across representative sites of major world wheat producing regions. The improved yield traits increased yield by 16% with current N fertilizer applications under both current climate and mid-century climate change scenarios. To achieve the full yield potential, a 52% increase in global average yield under a mid-century high warming climate scenario (RCP8.5), fertilizer use would need to increase fourfold over current use, which would unavoidably lead to higher environmental impacts from wheat production. Our results show the need to improve soil N availability and N use efficiency, along with yield potential.

Nitrogen↗

The Economics of Farming Expansion in the Brazilian Cerrado Under Possible Effects of Climate Change

This analysis assesses the financial viability of legally investing in native Cerrado vegetation deforestation for crop production, considering climate change. The study uses data from twelve different crop models based on three different climate models to predict potential future crop yields in cleared land for growing soy and maize. The outcomes show that in many micro-regions, investments in clearing land for crop production would destroy economic value, that is, generate a negative net present value because of low/negative and volatile cashflows driven primarily by future yields as affected by climate. Our analysis was carried out based on present agricultural practices and technology. As climate changes, farmers may adapt their practices, which can lead to more resilient and productive crops, or grow different crops, which could provide better returns on investment in clearing land than the ones resulting from our analysis. Despite various uncertainties, farmers, policy makers and financial institutions should be aware of the climatic and financial risks associated with land clearing in Brazil, mainly in micro-regions in which all scenarios resulted in negative outcomes in the investment analysis.

agricultural expansion↗

Performance Considerations for Ground Source Heat Pumps in Cold Climates: Preprint

Remote, cold climates present challenges to finding safe and affordable options to heat homes. In Alaska, residential ground source heat pumps (GSHPs) have been gaining in popularity to fill this gap. However, there is little research on their long-term performance or effect on soil temperatures. The extended heating season and cold soils of Alaska provide a harsh testing ground for GSHPs, even those designed and marketed for colder climates. The large and unbalanced heating load of cold climates creates a challenging environment for GSHPs. In 2013 the Cold Climate Housing Research Center (CCHRC) installed a GSHP at its Research and Testing Facility (RTF) in Fairbanks, Alaska. The heat pump replaced an oil-fired condensing boiler heating a 464 m2 office space via an in-floor hydronic radiant heating system. The ground heat exchanger (GHE) was installed in moisture-rich silty soils underlain with permafrost near 0°C. The intent of the installation was to observe and monitor the system over a 10-year period in order to develop a better understanding of the performance of GSHPs in sites with permafrost and to help inform future design. As of this writing, the heat pump system has been running for seven heating seasons. The efficiency in those seven heating seasons has been variable with ups and downs that have been difficult to explain. This paper seeks to understand the variability in performance as well as make recommendations for GSHP use in other cold climates.

cold climate↗

Cold-Climate Packaged Heat Pumps - Resistance is Futile

The U.S. currently has a large market for room/zonal space conditioning equipment focused primarily on cooling, namely packaged terminal air conditioners (PTACs), packaged terminal heat pumps (PTHPs), and room air conditioners. This equipment largely relies on electric resistance for heating, particularly when outdoor temperatures fall to 40°F or below, presenting a compelling opportunity for energy savings and carbon reductions from reverse cycle heating. This paper provides an overview of cold climate packaged heat pump technologies in the market capable of high output down to outdoor temperatures of 5°F and identifies the technological and market barriers to adoption. For state-of-the-art cold climate packaged heat pumps sold in the retrofit market, defrost meltwater management is the principal barrier to implementation. An energy use analysis is conducted on state-of-the-art cold climate packaged heat pumps for heating and cooling loads by building vintage and climate zone. Potential solutions to defrost meltwater are proposed and modeled for their impact on heating energy efficiency. A national impact assessment estimates the aggregate energy savings and carbon reductions if cold climate packaged heat pumps were to replace existing PTACs and PTHPs in the U.S. building stock. A national, two-track approach is proposed for increasing market adoption in the replacement and new construction markets.

ACEEE Summer Study, cold climate, heat pumps, ccph↗

Air Source Heat Pumps in Very Cold Climates

Air source heat pumps (ASHPs) in heating mode use a refrigeration cycle to remove heat from the outside air and transfer it into a building. Therefore, ASHPs have the potential to save energy compared to conventional heat sources that create the heat as opposed to transferring it from outside. Many cold climate ASHPs available on the market today can operate at outside temperatures of -25 degrees C (-13 degrees F) or even lower. As a result of technological advances and other factors, there is growing interest in ASHPs in cold climates, including very cold regions such as Alaska. However, guidance on the selection, installation, and operation of ASHPs in these very cold climates is limited, as significant data gaps exist regarding the performance of ASHPs in very cold environments. To address these data gaps and guide future innovations, our research team has studied the field performance of several ASHP installations in Alaska and done lab evaluations of several ASHP models using a cold chamber. While a cold chamber cannot fully reflect field conditions, it allowed for changing one variable at a time and gaining additional understanding of the behavior of ASHPs that would be difficult to gain from field studies only. This study focused on two main variables: the temperature in the chamber (representing the outdoor temperature) and the level of thermal loading of the ASHP. The results from the field as well as the lab show that ASHPs can operate with relatively high efficiency even in very cold climates if used in appropriate situations and in an appropriate way. It was found that not only the outside temperature, but also the level of thermal loading is a significant factor affecting the ASHP efficiency and needs to be carefully considered when sizing and operating ASHPs in very cold climates.

air source heat pump↗

Internal Climate Variability Obscures Future Freezing Rain Changes Despite Global Warming Trend

Abstract Although numerous studies have projected changes in freezing rain under future climate conditions, the internal variability of freezing rain remains poorly quantified. Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. By employing multivariate quantile mapping, we decompose the projected freezing rain trend into contributions from changes in temperature, relative humidity, and precipitation, which helps separate the forced response from internal climate variability. Our finding reveals a notable decrease in freezing rain occurrence in most areas. Despite a substantial temperature increase, internal variability overshadows climate forcing across a large portion of the eastern United States until about 2050. This insight has implications for practitioners, suggesting that the observed freezing rain frequency climatology continues to provide a relevant baseline for decision‐making in the near term. However, longer‐term design and adaptation plans should consider the projected changes in these regions.

Zhuang, Haoyu (Richard) [Department of Atmospheric↗

Interactions Between Climate Mean and Variability Drive Future Agroecosystem Vulnerability

ABSTRACT Agriculture is crucial for global food supply and dominates the Earth's land surface. It is unknown, however, how slow but relentless changes in climate mean state, versus random extreme conditions arising from changing variability , will affect agroecosystems' carbon fluxes, energy fluxes, and crop production. We used an advanced weather generator to partition changes in mean climate state versus variability for both temperature and precipitation, producing forcing data to drive factorial‐design simulations of US Midwest agricultural regions in the Energy Exascale Earth System Model. We found that an increase in temperature mean lowers stored carbon, plant productivity, and crop yield, and tends to convert agroecosystems from a carbon sink to a source, as expected; it also can cause local to regional cooling in the earth system model through its effects on the Bowen Ratio. The combined effect of mean and variability changes on carbon fluxes and pools was nonlinear, that is, greater than each individual case. For instance, gross primary production reduces by 9%, 1%, and 13% due to change in mean temperature, change in temperature variability, and change in both temperature mean and variability, respectively. Overall, the scenario with change in both temperature and precipitation means leads to the largest reduction in carbon fluxes (−16% gross primary production), carbon pools (−35% vegetation carbon), and crop yields (−33% and −22% median reduction in yield for corn and soybean, respectively). By unambiguously parsing the effects of changing climate mean versus variability and quantifying their nonadditive impacts, this study lays a foundation for more robust understanding and prediction of agroecosystems' vulnerability to 21st‐century climate change.

54 ENVIRONMENTAL SCIENCES↗

Mind the gaps! Climate scientists should heed lessons in collaborative storytelling from William Shakespeare

Abstract To co‐produce locally relevant climate knowledge, climate scientists are engaging in new collaborations—with stakeholders and with scholars in the humanities, arts, and social sciences. In our work as a Shakespeare scholar‐turned‐public‐humanist and a climate scientist, we have created a methodology that allows researchers and communities to co‐produce knowledge by co‐producing narratives. We combine principles from emerging climate “storylines” research with collaborative storytelling inspired by William Shakespeare's plays and theatrical practices. Shakespeare's plays spark collaborations and interpretations, in part, because of how Shakespeare leaves gaps in the narrative. These gaps allow others to enter as collaborators, creating a “cognitive ecology” that fosters knowledge and action among all engaged. Integrating these methods into climate storyline‐making offers a radical paradigm: it upends the scientist's role as the focal storyteller and expert, and fosters, instead, partnership, equity, and a co‐exploration of multiple uncertainties. It is time for researchers to cede control to a cognitive ecology of collaborative action. This article is categorized under: Trans‐Disciplinary Perspectives > Humanities and the Creative Arts

54 ENVIRONMENTAL SCIENCES↗

A new spatially distributed added value index for regional climate models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles

The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.

54 ENVIRONMENTAL SCIENCES↗

Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble

The CORDEX-CORE initiative was developed with the aim of producing homogeneous regional climate model (RCM) projections over domains world wide. In its first phase, two RCMs were run at 0.22° resolution downscaling 3 global climate models (GCMs) from the CMIP5 program for 9 CORDEX domains and two climate scenarios, the RCP2.6 and RCP8.5. The CORDEX-CORE simulations along with the CMIP5 GCM ensemble and the most recently produced CMIP6 GCM ensemble are analyzed, with focus on several temperature, heat, wet and dry hazard indicators for present day and mid-century and far future time slices. The CORDEX-CORE ensemble shows a better performance than the driving GCMs for several hazard indices due to its higher spatial resolution. For the far future time slice the 3 ensembles project an increase in all temperature and heat indices analyzed under the RCP8.5 scenario. The largest increases are always shown by the CMIP6 ensemble, except for Tx > 35 °C, for which the CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected to increase by the RCM ensemble over the la Plata basin in South America, the Congo basin in Africa, east North America, north east Europe, India and Indochina, regions where a better performance is obtained, whereas the GCM ensembles show small or negligible signals. Furthermore, compound hazard hotspots based on heat, drought and wet indicators are detected in each continent worldwide in region like Central America, the Amazon, the Mediterranean, South Africa and Australia, where a linear relation is shown between the heatwave and drought change signal, and region like Arabian peninsula, the central and south east Africa region (SEAF), the north west America (NWN), south east Asia, India, China and central and northern European regions (WCE, NEU) where the same linear relation is found for extreme precipitation and HW increases. Although still limited, the CORDEX-CORE initiative was able to produce high resolution climate projections with almost global coverage and can provide an important resource for impact assessment and climate service activities.

54 ENVIRONMENTAL SCIENCES↗

Toward indicators of the performance of US infrastructures under climate change risks

Built infrastructures are increasingly disrupted by climate-related extreme events. Being able to monitor what climate change implies for US infrastructures is of considerable importance to all levels of decision-makers. A capacity to develop cross-cutting, widely applicable indicators for more than a dozen different kinds of infrastructure, however, is severely limited at present. The development of such indicators must be considered an ongoing activity that will require expansion and refinement. A number of recent consensus reports suggest four priorities for indicators that portray the impacts of climate change, climate-related extreme events, and other driving forces on infrastructure. These are changes in the reliability of infrastructure services and the implications for costs; changes in the resilience of infrastructures to climate and other stresses; impacts due to the interdependencies of infrastructures; and ongoing adaptation in infrastructures.

adaptation, indicators, infrastructure↗

Climate science to inform adaptation policy: Heat waves over India in the 1.5°C and 2°C warmer worlds

Developing a better scientific understanding of anthropogenic climate change and climate variability, especially the prediction/projection of climate futures with useful temporal and geographical resolution and quantified uncertainties, and using that knowledge to inform adaptation planning and action will become crucially important in the coming years. Generating such policy-relevant knowledge may be particularly important for developing countries such as India. It is with this backdrop that, in this paper, we analyze future heat waves in India by using observations and a large number of model simulations of historical, + 1.5 °C, and + 2.0 °C warmer worlds. In both the future scenarios, there is an increased probability of heat waves during June and July when the Indian monsoon is in full swing and humidity is high, which makes the heat events even more of a health risk. While the highest temperatures in heat waves may not increase much in future climates, the duration and areal extent of the heat waves will most likely increase, leading to the emergence of new heat wave-prone zones in India. The results indicate that the joint frequencies of the longest duration and large area events could be nearly threefold greater in the + 1.5 °C and fivefold greater in the + 2.0 °C future scenarios compared to historical simulations. Thus, overall, the study indicates a substantial increase in the risk of heat events that typically elicit warnings from forecasters. The likely widespread and persistent nature of heat wave events in the future, as revealed by this study, will require planning and adaptation measures beyond the short-term disaster planning frameworks currently in place. Exploring what these measures might look like is beyond the scope of this study, but it underlines the importance of developing climate knowledge with high temporal and geographical resolution capable of informing adaptation policy and planning.

+1.5 °C and +2.0 °C↗