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At least 541 records · Page 30
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NASA NTRS2022

Measuring, mapping, and anticipating climate gentrification in Florida: Miami and Tampa case studies

This article introduces an experimental methodology to identify proxy indicators that are conceptually consistent with the processes of Climate Gentrification (“CG”), in which a change in demand preferences among consumers and investors drives the increased consumption for real estate, in part, on lower measures of physical risk from climate change. Evaluated through case studies in the state of Florida, this article builds on the integration of multiple datasets concerning rental properties, evictions, and socioeconomic data, as well as environmental risk indices to build a Climate Gentrification Risk Index (CGRI). In the Miami case study, we find that the CGRI identifies a hotly contested neighborhood that is already known to be in a state of transition consistent with the processes of CG. In the Tampa case, the index highlights a district that exhibits strong metrics for the future accelerated occurrence of CG. Our findings suggest that transitional land uses and flexible zoning in low-exposure areas are key elements for attracting new development consistent with CG and offer insight into the challenges that local governments face understanding the types and rates of change that may be catalyzed in the broader urban processes of public and private sector climate adaptation in the built environment.

Climate change↗
NASA NTRS1995

Possible role of oceanic heat transport in early Eocene climate

Increased oceanic heat transport has often been cited as a means of maintaining warm high-latitude surface temperatures in many intervals of the geologic past, including the early Eocene. Although the excess amount of oceanic heat transport required by warm high latitude sea surface temperatures can be calculated empirically, determining how additional oceanic heat transport would take place has yet to be accomplished. That the mechanisms of enhanced poleward oceanic heat transport remain undefined in paleoclimate reconstructions is an important point that is often overlooked. Using early Eocene climate as an example, we consider various ways to produce enhanced poleward heat transport and latitudinal energy redistribution of the sign and magnitude required by interpreted early Eocene conditions. Our interpolation of early Eocene paleotemperature data indicate that an approximately 30% increase in poleward heat transport would be required to maintain Eocene high-latitude temperatures. This increased heat transport appears difficult to accomplish by any means of ocean circulation if we use present ocean circulation characteristics to evaluate early Eocene rates. Either oceanic processes were very different from those of the present to produce the early Eocene climate conditions or oceanic heat transport was not the primary cause of that climate. We believe that atmospheric processes, with contributions from other factors, such as clouds, were the most likely primary cause of early Eocene climate.

NASA Discipline Number 52-30↗
NASA NTRS1992

Modelling the Phanerozoic carbon cycle and climate: constraints from the 87Sr/86Sr isotopic ratio of seawater

A numerical model describing the coupled evolution of the biogeochemical cycles of carbon, sulfur, calcium, magnesium, phosphorus, and strontium has been developed to describe the long-term changes of atmospheric carbon dioxide and climate during the Phanerozoic. The emphasis is on the effects of coupling the cycles of carbon and strontium. Various interpretations of the observed Phanerozoic history of the seawater 87Sr/86Sr ratio are investigated with the model. More specifically, the abilities of continental weathering, volcanism, and surface lithology in generating that signal are tested and compared. It is suggested that the observed fluctuations are mostly due to a changing weatherability over time. It is shown that such a conclusion is very important for the modelling of the carbon cycle. Indeed, it implies that the conventional belief that the evolution of atmospheric carbon dioxide and climate on a long time scale is governed by the balance between the volcanic input of CO2 and the rate of silicate weathering is not true. Rather carbon exchanges between the mantle and the exogenic system are likely to have played a key role too. Further, the increase of the global weathering rates with increasing surface temperature and/or atmospheric CO2 pressure usually postulated in long-term carbon cycle and climate modelling is also inconsistent with the new model. Other factors appear to have modulated the weatherability of the continents through time, such as mountain building and the existence of glaciers and ice sheets. Based on these observations, a history of atmospheric carbon dioxide and climate during Phanerozoic time, consistent with the strontium isotopic data, is reconstructed with the model and is shown to be compatible with paleoclimatic indicators, such as the timing of glaciation and the estimates of Cretaceous paleotemperatures.

NASA Discipline Number 52-30↗
NASA NTRS2002

Reducing uncertainty about carbon dioxide as a climate driver

The lack of an adequate ancient analogue for future climates means that we ultimately must use and trust climate models, evaluated against modern observation and our best geologic records of warm and cold climates of the past. Armed with an elevated confidence in the models, we will then be able to make reliable predictions of the Earth's response to our risky experiment with the climate system.

Climate↗
NASA NTRS2005

AIRS radiometric calibration validation for climate research

Climate research using data from satellite based radiometers makes extreme demands on the traceability and stability of the radiometric calibration. The selection of a cooled grating array spectrometer for the Atmospheric Infrared Sounder, AIRS, is key, but does not ensured that AIRS data will be of climate quality. Additional design features, plus additional pre-launch testing, and extensive on-orbit calibration subsystem monitoring beyond what would suffice for application of the data to weather forecasting were required to ensure the radiometric data quality required for climate research. Validation that climate data quality are being generated makes use of the sea surface skin temperatures (SST and (obs-calc).

calibration↗
NASA NTRS2012

Likelihood-Based Climate Model Evaluation

Climate models are deterministic, mathematical descriptions of the physics of climate. Confidence in predictions of future climate is increased if the physics are verifiably correct. A necessary, (but not sufficient) condition is that past and present climate be simulated well. Quantify the likelihood that a (summary statistic computed from a) set of observations arises from a physical system with the characteristics captured by a model generated time series. Given a prior on models, we can go further: posterior distribution of model given observations.

climate models↗
NASA NTRS2012

Global Air Quality and Health Co-benefits of Mitigating Near-term Climate Change Through Methane and Black Carbon Emission Controls

Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM < or = 2.5 microns in aerodynamic diameter; PM2.5), are associated with premature mortality and they disrupt global and regional climate. Objectives: We examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20-40 years. Methods: We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5‑ and ozone-related deaths using epidemiologically derived concentration-response functions. Results: We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23-34% and 7-17% and avoid 0.6-4.4 and 0.04-0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration-response function. Conclusions: In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

air quality↗
NASA NTRS2013

Global and Regional Temperature-change Potentials for Near-term Climate Forcers

We examine the climate effects of the emissions of near-term climate forcers (NTCFs) from 4 continental regions (East Asia, Europe, North America and South Asia) using results from the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model simulations. We address 3 aerosol species (sulphate, particulate organic matter and black carbon) and 4 ozone precursors (methane, reactive nitrogen oxides (NOx), volatile organic compounds and carbon monoxide). We calculate the global climate metrics: global warming potentials (GWPs) and global temperature change potentials (GTPs). For the aerosols these metrics are simply time-dependent scalings of the equilibrium radiative forcings. The GTPs decrease more rapidly with time than the GWPs. The aerosol forcings and hence climate metrics have only a modest dependence on emission region. The metrics for ozone precursors include the effects on the methane lifetime. The impacts via methane are particularly important for the 20 yr GTPs. Emissions of NOx and VOCs from South Asia have GWPs and GTPs of higher magnitude than from the other Northern Hemisphere regions. The analysis is further extended by examining the temperature-change impacts in 4 latitude bands, and calculating absolute regional temperature-change potentials (ARTPs). The latitudinal pattern of the temperature response does not directly follow the pattern of the diagnosed radiative forcing. We find that temperatures in the Arctic latitudes appear to be particularly sensitive to BC emissions from South Asia. The northern mid-latitude temperature response to northern mid-latitude emissions is approximately twice as large as the global average response for aerosol emission, and about 20-30% larger than the global average for methane, VOC and CO emissions.

North America↗
NASA NTRS2013

Evaluation of Aerosol Mixing State Classes in the GISS Modele-matrix Climate Model Using Single-particle Mass Spectrometry Measurements

Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 micron, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 micron contain large fractions of organic material, internally-mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.

climate models↗
NASA NTRS2013

Tropospheric Ozone Changes, Radiative Forcing and Attribution to Emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410 mW m−2. The model range of pre-industrial to present-day changes in O3 produces a spread (+/-1 standard deviation) in RFs of +/-17%. Three different radiation schemes were used - we find differences in RFs between schemes (for the same ozone fields) of +/-10 percent. Applying two different tropopause definitions gives differences in RFs of +/-3 percent. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of +/-30 percent for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44+/-12 percent), nitrogen oxides (31 +/- 9 percent), carbon monoxide (15 +/- 3 percent) and non-methane volatile organic compounds (9 +/- 2 percent); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m(−2) DU(−1), a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m(−2); relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF.

climate change↗
NASA NTRS2013

Projected Climate Impacts to South African Maize and Wheat Production in 2055: A Comparison of Empirical and Mechanistic Modeling Approaches

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were 3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EMMM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EMMM comparisons to provide a fuller picture of crop-climate response uncertainties.

DSSAT↗
NASA NTRS2013

Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma) have been extensively studied.Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-mode data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS), support previous work suggesting that ESS is greater than Climate Sensitivity (CS), and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.

mathematical models↗
NASA NTRS2013

Linking Climate to Incidence of Zoonotic Cutaneous Leishmaniasis (L. major) in Pre-Saharan North Africa

Shifts in surface climate may have changed the dynamic of zoonotic cutaneous leishmaniasis (ZCL) in the pre-Saharan zones of North Africa. Caused by Leishmania major, this form multiplies in the body of rodents serving as reservoirs of the disease. The parasite is then transmitted to human hosts by the bite of a Phlebotomine sand fly (Diptera: Psychodidae) that was previously fed by biting an infected reservoir. We examine the seasonal and interannual dynamics of the incidence of this ZCL as a function of surface climate indicators in two regions covering a large area of the semi-arid Pre-Saharan North Africa. Results suggest that in this area, changes in climate may have initiated a trophic cascade that resulted in an increase in ZCL incidence. We find the correlation between the rainy season precipitation and the same year Normalized Difference Vegetation Index (NDVI) to be strong for both regions while the number of cases of ZCL incidence lags the precipitation and NDVI by 2 years. The zoonotic cutaneous leishmaniasis seasonal dynamic appears to be controlled by minimum temperatures and presents a 2-month lag between the reported infection date and the presumed date when the infection actually occurred. The decadal increase in the number of ZCL occurrence in the region suggests that changes in climate increased minimum temperatures sufficiently and created conditions suitable for endemicity that did not previously exist. We also find that temperatures above a critical range suppress ZCL incidence by limiting the vector's reproductive activity.

NDIV↗
NASA NTRS2015

Geocuration Lessons Learned from the Climate Data Initiative Project

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. This presentation will introduce the concept of geocuration, which we define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium. We also present the Climate Data Initiative (CDI) project as an prototypical example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate change preparedness. The geocuration process used in the CDI project, key lessons learned, and suggestions to improve similar geocuration efforts in the future will be part of this presentation.

climate↗
NASA NTRS2014

Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

crop-model ensembles↗
NASA NTRS2015

Volcanic Eruptions and Climate

Volcanic eruptions represent some of the most climatically important and societally disruptive short-term events in human history. Large eruptions inject ash, dust, sulfurous gases (e.g. SO2, H2S), halogens (e.g. Hcl and Hbr), and water vapor into the Earth's atmosphere. Sulfurous emissions principally interact with the climate by converting into sulfate aerosols that reduce incoming solar radiation, warming the stratosphere and altering ozone creation, reducing global mean surface temperature, and suppressing the hydrological cycle. In this issue, we focus on the history, processes, and consequences of these large eruptions that inject enough material into the stratosphere to significantly affect the climate system. In terms of the changes wrought on the energy balance of the Earth System, these transient events can temporarily have a radiative forcing magnitude larger than the range of solar, greenhouse gas, and land use variability over the last millennium. In simulations as well as modern and paleoclimate observations, volcanic eruptions cause large inter-annual to decadal-scale changes in climate. Active debates persist concerning their role in longer-term (multi-decadal to centennial) modification of the Earth System, however.

Volcanoes↗
NASA NTRS2015

The AgMIP Coordinated Global and Regional Assessments (CGRA) of Climate Change Impacts on Agriculture and Food Security

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to construct a protocol-based framework enabling regional assessments (led by regional experts and modelers) that can provide consistent inputs to global economic and integrated assessment models. These global models can then relay important global-level information that drive regional decision-making and outcomes throughout an interconnected agricultural system. AgMIPs community of nearly 800 climate, crop, livestock, economics, and IT experts has improved the state-of-the-art through model intercomparisons, validation exercises, regional integrated assessments, and the launch of AgMIP programs on all six arable continents. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) of climate change impacts on agriculture and food security to link global and regional crop and economic models using a protocol-based framework. The CGRA protocols are being developed to utilize historical observations, climate projections, and RCPsSSPs from CMIP5 (and potentially CMIP6), and will examine stakeholder-driven agricultural development and adaptation scenarios to provide cutting-edge assessments of climate changes impact on agriculture and food security. These protocols will build on the foundation of established protocols from AgMIPs 30+ activities, and will emphasize the use of multiple models, scenarios, and scales to enable an accurate assessment of related uncertainties. The CGRA is also designed to provide the outputs necessary to feed into integrated assessment models (IAMs), nutrition and food security assessments, nitrogen and carbon cycle models, and additional impact-sector assessments (e.g., water resources, land-use, biomes, urban areas). This presentation will describe the current status of CGRA planning and initial prototype experiments to demonstrate key aspects of the protocols before wider implementation ahead of the IPCC Sixth Assessment Report.

models↗
NASA NTRS2015

Climate Change and Fetal Health: The Impacts of Exposure to Extreme Temperatures in New York City

Background: Climate change is projected to increase the frequency, intensity, and duration of heat waves while reducing cold extremes, yet few studies have examined the relationship between temperature and fetal health. Objectives: We estimate the impacts of extreme temperatures on birth weight and gestational age in Manhattan, a borough in New York City, and explore differences by socioeconomic status (SES). Methods: We combine average daily temperature from 1985 to 2010 with birth certificate data in Manhattan for the same time period. We then generate 33 downscaled climate model time series to project impacts on fetal health. Results: We find exposure to an extra day where average temperature 25 F and 85 F during pregnancy is associated with a 1.8 and 1.7 g (respectively) reduction in birth weight, but the impact varies by SES, particularly for extreme heat, where teen mothers seem most vulnerable. We find no meaningful, significant effect on gestational age. Using projections of temperature from these climate models, we project average net reductions in birth weight in the 2070- 2099 period of 4.6 g in the business-as-usual scenario. Conclusions: Results suggest that increasing heat events from climate change could adversely impact birth weight and vary by SES.

climate change↗