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At least 361 records · Page 20

NASA’s Role in Putting Earth Science Information to Use in Decision-Making

The demand for decision-relevant climate information is continually growing, both because of the severity and intensity of climate change impacts and because of the growing recognition that people can take actions today that will mitigate the risk from future climate impacts. Agencies across the federal government are responding to this need by working together to support the Nation in becoming more resilient to climate change. NASA Earth Science has been a key engine of understanding global climate change and how it impacts people around the world. Additionally, for over two decades, the Agency has worked, via partnerships, to connect NASA Earth Science knowledge with decision support needs, often taking a service-oriented approach by working with boundary organizations and climate service providers. In this presentation, we describe NASA’s unique role in enabling new and practical uses of Earth science information, and how the Agency supports public and private sector partners. We highlight several key examples of NASA projects and activities that support local to regional climate resilience efforts. In addition, we discuss how NASA’s new Earth Information Center, a partnership among several federal agencies, enables in-person and virtual visitors to see how our planet is changing in ways that affect their lives and livelihoods. Lastly, we discuss plans for how NASA Earth Science will continue to help build a more climate resilient future.

earth science↗

Impacts of Interannual Climate Variability on Agricultural and Marine Ecosystems

The El Nino - Southern Oscillation (ENSO) is the dominant mode of global interannual climate variability, and seems to be the only mode for which current prediction methods are more skillful than climatology or persistence. The Zebiak and Cane intermediate coupled ocean-atmosphere model has been in use for ENSO prediction for more than a decade, with notable success. However, the sole dependence of its original initialization scheme and the improved initialization on wind fields derived from merchant ship observations proved to be a liability during 1997/1998 El Nino event: the deficiencies of wind observations prevented the oceanic component of the model from reaching the realistic state during the year prior to the event, and the forecast failed. Our work on the project was concentrated on the use of satellite data for improving various stages of ENSO prediction technology: model initialization, bias correction, and data assimilation. Close collaboration with other teams of the IDS project was maintained throughout.

Cane, M. A.↗

Climatic Effect of Impacts on the Ocean

Impact-generated spherule layers provide information pertinent to the environmental consequences of very large impacts on Earth. The spherules are condensed from high velocity impact ejecta ballistically distributed worldwide. These ejecta comprise material from both the impacting body and the target. Much of this material was vaporized or atomized (in the sense of small droplets of fluid, although doubtless some of the vapor species were atomic) in the impact event, cooled and condensed, and then was re-melted or partially evaporated again on re-entry into the atmosphere far from the crater. The energy deposited in the atmosphere by the re-entering ejecta heat the stratosphere where the particles stop to the temperature of hot lava, and thermal radiation from the superheated stratosphere heats the lower atmosphere, any land surfaces, and the evaporate the surface of the ocean; how hot the atmosphere gets and how much water gets evaporated depends on the scale of the impact. The molten or solid raindrops and hailstones eventually fell out of the atmosphere and onto land or into the ocean over the course of hours and days to pile up as spherule beds, and later the finer dust falls out over months and years.

Zahnle, K. J.↗

Fire Influences on Atmospheric Composition, Air Quality, and Climate

Fires impact atmospheric composition through their emissions, which range from long-lived gases to short-lived gases and aerosols. Effects are typically larger in the tropics and boreal regions but can also be substantial in highly populated areas in the northern mid-latitudes. In all regions, fire can impact air quality and health. Similarly, its effect on large-scale atmospheric processes, including regional and global atmospheric chemistry and climate forcing, can be substantial, but this remains largely unexplored. The impacts are primarily realised in the boundary layer and lower free troposphere but can also be noticeable in upper troposphere/lower stratosphere (UT/LS) region, for the most intense fires. In this review, we summarise the recent literature on findings related to fire impact on atmospheric composition, air quality and climate. We explore both observational and modelling approaches and present information on key regions and on the globe as a whole. We also discuss the current and future directions in this area of research, focusing on the major advances in emission estimates, the emerging efforts to include fire as a component in Earth system modelling and the use of modelling to assess health impacts of fire emissions.

Air quality↗

Compound Heat and Moisture Extreme Impacts on Global Crop Yields Under Climate Change

Extreme heat, drought and moisture excess are increasingly co-occurring within a single growing season, impacting crop yields in global breadbasket regions. In this Review, we synthesize understanding of compound heat and moisture extremes, their impacts on global crop yields and implications for adaptation. Heat and moisture extremes and their impacts become compounded through crop-physiological interactions, heat–moisture couplings in the climate system and crop–atmosphere interactions. Since around 2000, these compound extremes, and hot droughts in particular, have been linked to especially poor harvests (up to 30% yield losses) in regions such as India, Ethiopia, the USA, Europe and Russia. However, in some cases, combinations of crop stresses might generate compensating effects. Compound extremes are projected to increase in frequency and amplitude in the future, but, owing to the biophysical interdependence among temperature, water and crop physiology, the net yield effects of such future compound extremes remain uncertain. Accordingly, compound extremes will necessitate comprehensive agricultural adaptation strategies geared towards multi-stress resilience, as adaptations that work for single climate stresses could be maladaptive under combined stresses. An integrated understanding of heat and water in soil–plant–atmosphere dynamics is urgently needed to understand risks and suitably adapt cropping systems to compounding climate impacts.

Agroecology↗

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗

Global Assessment of Drought Characteristics in the Anthropocene

Contemporary understanding of the impacts of climate change on global drought characteristics (e.g., intensities, extents) is still limited and not well understood. This knowledge is critical because projected changes in climate are expected to impact on future water availability as well as influence decisions on how water resources are allocated. The main aim of this study is to improve understanding of drought characteristics (extents and duration) in the Anthropocene where rapid changes in the environment are caused by the composite influence of human activities and climate change. Multi-scale earth observation data (1980 - 2020) and the Coupled Model Intercomparison Project Phase 6 climate models, which incorporate the Shared Socioeconomic Pathways (2040 - 2070 and 2070 - 2100) are used to assess these characteristics as well as identify climatic hotspots where changes in drought characteristics could drive groundwater hydrology. Results show that towards the end of the 21st century, global land areas under drought will significantly decrease but their durations will not. Generally, there is evidence of significant decline in the proportion of areas that will experience various drought intensities (moderate, severe and extreme drought) in the future and for each category, drought affected areas will not reach 30% on average. Moreover, some regions are potential hotspots of climate–groundwater interactions where drought events could directly impact on groundwater. This is because of the varying degree of strong correlations (positive and negative) between climate and groundwater data in some areas (e.g., Australia, Europe, Southern Africa, Asia). The relatively strong negative correlations in some of these hotspots are indicative of the presence of considerable lags, that could be caused by aridity as well as human groundwater footprints.

Christopher E Ndehedehe↗

The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)

Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.

James A Franke↗

Climate change signal in global agriculture emerges earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern first surveyed in a harmonized multi-model effort in 2014. We report here on new 21st-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean, and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5 to -6% (SSP126) and +1 to -24% (SSP585) — explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9 shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts — when the change signal emerges from the noise — consistently occurs earlier in the new projections for several main producing regions before 2040. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

climate change↗

Solar Spectral Irradiance and Climate

Spectrally resolved solar irradiance is recognized as being increasingly important to improving our understanding of the manner in which the Sun influences climate. There is strong empirical evidence linking total solar irradiance to surface temperature trends - even though the Sun has likely made only a small contribution to the last half-century's global temperature anomaly - but the amplitudes cannot be explained by direct solar heating alone. The wavelength and height dependence of solar radiation deposition, for example, ozone absorption in the stratosphere, absorption in the ocean mixed layer, and water vapor absorption in the lower troposphere, contribute to the "top-down" and "bottom-up" mechanisms that have been proposed as possible amplifiers of the solar signal. New observations and models of solar spectral irradiance are needed to study these processes and to quantify their impacts on climate. Some of the most recent observations of solar spectral variability from the mid-ultraviolet to the near-infrared have revealed some unexpected behavior that was not anticipated prior to their measurement, based on an understanding from model reconstructions. The atmospheric response to the observed spectral variability, as quantified in climate model simulations, have revealed similarly surprising and in some cases, conflicting results. This talk will provide an overview on the state of our understanding of the spectrally resolved solar irradiance, its variability over many time scales, potential climate impacts, and finally, a discussion on what is required for improving our understanding of Sun-climate connections, including a look forward to future observations.

Pilewskie, P.↗

Modeling Impacts of Dust Mineralogy on Fast Climate Response

Mineralogical composition drives dust impacts on Earth's climate systems. However, most climate models still use homogeneous dust, without accounting for the temporal and spatial variation in mineralogy. To quantify the radiative impact of resolving dust mineralogy on Earth's climate, we implement and simulate the distribution of dust minerals (i.e., illite, kaolinite, smectite, hematite, calcite, feldspar, quartz, and gypsum) from Claquin et al. (1999) (C1999) and activate their interaction with radiation in the GFDL AM4.0 model. Resolving mineralogy reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite volume content of 2.7 % (HD27). The reduction in dust absorption results in improved agreement with observation-based single-scattering albedo (SSA), radiative fluxes from CERES (the Clouds and the Earth's Radiant Energy System), and land surface temperature from the CRU (Climatic Research Unit) compared to the baseline HD27 model version. It also results in distinct radiative impacts on Earth's climate over North Africa. Over the 19-year (from 2001 to 2019) modeled period during JJA (June–July–August), the reduction in dust absorption in AM4.0 leads to a reduction of over 50 % in net downward radiation across the Sahara and approximately 20 % over the Sahel at the top of the atmosphere (TOA) compared to the baseline HD27 model version. The reduced dust absorption weakens the atmospheric warming effect of dust aerosols and leads to an alteration in land surface temperature, resulting in a decrease of 0.66 K over the Sahara and an increase of 0.7 K over the Sahel. The less warming in the atmosphere suppresses ascent and weakens the monsoon inflow from the Gulf of Guinea. This brings less moisture to the Sahel, which combined with decreased ascent induces a reduction of precipitation. To isolate the effect of reduced absorption compared to resolving spatial and temporal mineralogy, we carry out a simulation where the hematite volume content of homogeneous dust is reduced from 2.7 % to 0.9 % (HD09). The dust absorption (e.g., single-scattering albedo) of HD09 is comparable to that of the mineralogically speciated model on a global mean scale, albeit with a lower spatial variation that arises solely from particle size. Comparison of the two models indicates that the spatial inhomogeneity in dust absorption resulting from resolving mineralogy does not have significant impacts on Earth's radiation and climate, provided there is a similar level of dust absorption on a global mean scale before and after resolving dust mineralogy. However, uncertainties related to emission and distribution of minerals may blur the advantages of resolving minerals to study their impact on radiation, cloud properties, ocean biogeochemistry, air quality, and photochemistry. On the other hand, lumping together clay minerals (i.e., illite, kaolinite, and smectite), but excluding externally mixed hematite and gypsum, appears to provide both computational efficiency and relative accuracy. Nevertheless, for specific research, it may be necessary to fully resolve mineralogy to achieve accuracy.

Soil dust↗

Sensible Heat Has Significantly Affected the Global Hydrological Cycle Over the Historical Period

Globally, latent heating associated with a change in precipitation is balanced by changes to atmospheric radiative cooling and sensible heat fluxes. Both components can be altered by climate forcing mechanisms and through climate feedbacks, but the impacts of climate forcing and feedbacks on sensible heat fluxes have received much less attention. Here we show, using a range of climate modelling results, that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since preindustrial time, because the radiative impact of forcings and feedbacks approximately compensate. The model results show a dissimilar influence on sensible heat and precipitation from various drivers of climate change. Due to its strong atmospheric absorption, black carbon is found to influence the sensible heat very differently compared to other aerosols and greenhouse gases. Our results indicate that this is likely caused by differences in the impact on the lower tropospheric stability.

Myhre, G.↗

Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

Freduah, Bright S.↗

Improving Decision-Making Activities for Meningitis and Malaria

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

parasitic diseases↗

Machine-Learning Reveals Climate Forcing From Aerosols is Dominated by Increased Cloud Cover

Aerosol-cloud interactions have a potentially large impact on climate, but are poorly quantified and thus contribute a significant and long-standing uncertainty in climate projections. The impacts derived from climate models are poorly constrained by observations, because retrieving robust large-scale signals of aerosol-cloud interactions are frequently hampered by the considerable noise associated with meteorological co-variability. The Iceland-Holuhraun effusive eruption in 2014 resulted in a massive aerosol plume in an otherwise near-pristine environment and thus provided an ideal natural experiment to quantify cloud responses to aerosol perturbations. Here we disentangle significant signals from the noise of meteorological co-variability using a satellite-based machine-learning approach. Our analysis shows that aerosols from the eruption increased cloud cover by approximately 10%, and this appears to be the leading cause of climate forcing, rather than cloud brightening as previously thought. We find that volcanic aerosols do brighten clouds by reducing droplet size, but this has a significantly smaller radiative impact than changes in cloud fraction. These results add substantial observational constraints on the cooling impact of aerosols. Such constraints are critical for improving climate models, which still inadequately represent the complex macro-physical and micro-physical impacts of aerosol-cloud interactions.

Aerosols↗

Insights Into the Size-Resolved Dust Emission From Field Measurements in the Moroccan Sahara

The particle size distribution (PSD) of mineral dust has a strong effect on the impacts of dust on climate. However, our understanding of the emitted dust PSD, including its variability and the fraction of super-coarse dust (diameter >10 µm), remains limited. Here, we provide new insights into the size-resolved dust emission process based on a field campaign performed in the Moroccan Sahara in September 2019 in the context of the FRontiers in dust minerAloGical coMposition and its Effects upoN climaTe (FRAGMENT) project. The obtained dust concentration and diffusive flux PSDs show significant dependencies upon the friction velocity (u*), wind direction and type of event (regular events versus haboob events). For instance, the number fraction of sub-micrometre particles increases with u*, along with a large decrease in the mass fraction of super-coarse dust. We identify dry deposition, which is modulated by u* and fetch length, as a potential cause for this PSD variability. Using a resistance model constrained with field observations to estimate the dry deposition flux and thereby also the emitted dust flux, we show that deposition could represent up to ∼90 % of the emission of super-coarse particles (>10 µm) and up to ∼65 % of the emission of particles as small as ∼5 µm in diameter. Importantly, removing the deposition component significantly reduces the variability with u* in the PSD of the emitted dust flux compared with the diffusive flux, particularly for super-coarse dust. The differences between regular and haboob event concentration and diffusive flux PSDs are suspected to result from a smaller and variable dust source fetch during the haboob events, and/or an increased resistance of soil aggregates to fragmentation associated with the observed increase in relative humidity along the haboob outflow. Finally, compared to the invariant emitted dust flux PSD estimated based on brittle fragmentation theory, we obtain a substantially higher proportion of super-micrometre particles in the dust flux. Overall, our results suggest that dry deposition needs to be adequately considered to estimate the emitted PSD, even in studies limited to the fine and coarse size ranges (<10 µm).

particle size distribution↗