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NASA NTRS2019

20,000 Years of Societal Vulnerability and Adaptation to Climate Change in Southwest Asia

The Fertile Crescent, its hilly flanks and surrounding drylands has been a critical region for studying how climate has influenced societal change, and this review focuses on the region over the last 20,000 years. The complex social, economic, and environmental landscapes in the region today are not new phenomena and understanding their interactions requires a nuanced, multidisciplinary understanding of the past. This review builds on a history of collaboration between the social and natural palaeoscience disciplines. We provide a multidisciplinary, multiscalar perspective on the relevance of past climate, environmental, and archaeological research in assessing present day vulnerabilities and risks for the populations of southwest Asia. We discuss the complexity of palaeoclimatic data interpretation, particularly in relation to hydrology, and provide an overview of key time periods of palaeoclimatic interest. We discuss the critical role that vegetation plays in the human–climate–environment nexus and discuss the implications of the available palaeoclimate and archaeological data, and their interpretation, for palaeonarratives of the region, both climatically and socially. We also provide an overview of how modelling can improve our understanding of past climate impacts and associated change in risk to societies. We conclude by looking to future work, and identify themes of “scale” and “seasonality” as still requiring further focus. We suggest that by appreciating a given locale's place in the regional hydroscape, be it an archaeological site or palaeoenvironmental archive, more robust links to climate can be made where appropriate and interpretations drawn will demand the resolution of factors acting across multiple scales.

Levant↗

NASA NTRS2019

Mineralogical Signatures of Cold and Icy Climates on Ancient and Modern Mars

Liquid water was abundant on early Mars, but whether the climate was warm and wet or cold and icy with punctuated periods of melting is still poorly understood. Modern climate models for Mars tend to predict a colder, icier early climate than previously imagined [e.g., 1]. However, any model for the early climate on Mars must be reconciled with the chemical record. We currently do not understand how alteration mineralogy formed in snow and ice dominated conditions compares to that of warmer climates, and it is unclear whether cold climate weathering could form all or any of the aqueous alteration phases expressed on early martian surfaces [2]. To help resolve this knowledge gap, we synthesize results from glacial Mars analog sites at the Three Sisters, Oregon and mafic regions of the Antarctic ice sheet, and compare them to the surface mineralogy of Mars. These sites provide the opportunity to investigate weathering in environments analogous to glacial environments on Mars throughout geologic time, including snowpacks or smaller wet-based or polythermal glaciers [3, 4] as well as the proposed extensive ice sheets of the late Noachian icy highlands model

Scudder, N. A.↗

NASA NTRS2019

The Missing Economic Risks in Assessments of Climate Change Impacts

Economic assessments of the potential future risks of climate change have been omitting or grossly underestimating many of the most serious consequences for lives and livelihoods because these risks are difficult to quantify precisely and lie outside of human experience. Political and business leaders need to understand the scale of these ‘missing risks’ because they could have drastic and potentially catastrophic impacts on citizens, communities and companies. Scientists are growing in confidence about the evidence for the largest potential impacts of climate change and the rising probability that major thresholds in the Earth’s climate system will be breached as global mean surface temperature rises, particularly if warming exceeds 2°C above the pre-industrial level. These impacts include: (1) Destabilisation of ice sheets and glaciers and consequent sea level rise. (2) Stronger tropical cyclones. (3) Extreme heat impacts. (4) More frequent and intense floods and droughts. (5) Disruptions to oceanic and atmospheric circulation. (6) Destruction of biodiversity and collapse of ecosystems. Many of these impacts will grow and occur concurrently across the world as global temperature climbs. Some of these impacts involve thresholds in the climate system beyond which major impacts accelerate, or become irreversible and unstoppable. When a threshold is breached, it might cause one or more other thresholds to be exceeded as well, leading to a cascade of impacts. Many of these impacts could exceed the capacity of human populations to adapt, and would significantly affect and disrupt the lives and livelihoods of hundreds of millions, if not billions, of people worldwide. These impacts would also undermine economic growth and development, exacerbate poverty and destabilise communities. Economic assessments fail to take account of the potential for large concurrent impacts across the world that would cause mass migration, displacement and conflict, with huge loss of life. Economic assessments that are expressed solely in terms of effects on output (e.g. gross domestic product), or that only extrapolate from past experience, or that use inappropriate discounting, do not provide a clear indication of the potential risks to lives and livelihoods. It is likely that there are additional risks that we are not yet anticipating simply because scientists have not yet detected their possibility, as we have entered a period of climate change that is unprecedented in human history. Some advances are being made in improving economic assessments of climate change impacts but much more progress is required if assessments are to offer reliable guidance for political and business leaders on the biggest risks. The lack of firm quantifications is not a reason to ignore these risks, and when the missing risks are taken into account, the case for strong and urgent action to reduce greenhouse gas emissions becomes even more compelling.

DeFries, Ruth↗

NASA NTRS2018

The Present and Future of Secondary Organic Aerosol Direct Forcing on Climate

Secondary organic aerosols (SOA), a subset of organic aerosols that are chemically produced in the atmosphere, are included in climate modeling calculations using very simple parameterizations. Estimates on their shortwave forcing on climate span almost two orders of magnitude, being potentially comparable to sulfate direct forcing. In the longwave, a neglected part of the spectrum when it comes to SOA, the direct SOA forcing could exceed that of sulfate and black carbon, although in absolute values it is much weaker than the shortwave forcing. Critical for these estimates is the vertical distribution of the climate active agents, pointing to SOA temperature-dependent volatility. Over the last few years, research also revealed the highly oxidized character of organic aerosol and its chemical aging in the atmosphere that partially leads to the formation of brown carbon, an absorbing form of organic aerosol. This review summarizes critical advances in the understanding of SOA behavior and properties relevant to direct climate forcing and puts them in perspective with regard to primary organic aerosol and brown carbon. These findings also demonstrate an emerging dynamic picture of organic aerosol that has not yet been integrated in climate modeling. The challenges for the coming years in order to reduce uncertainties in the direct organic aerosol climate impact are discussed. High priority for future model development should be given to the dynamic link between “white” and “brown” organic aerosol and between primary and secondary organic aerosol. The SOA temperature-dependent volatility parameterizations and wavelength-dependent refractive index should be also included.

Kostas Tsigaridis↗

NASA NTRS2020

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗

NASA NTRSDate not supplied

Influence of regional anthropogenic changes over Nile region on the climate system during the late Holocene (~2500 years before present)

The societal impacts of climate change during the late Holocene leads to regional anthropogenic changes over the Nile region floodplain and could have acted in tandem with natural factors like major volcanic eruptions on the regional climate system to magnify the local climatic impacts. This study aims to explore and investigate the sensitivity of climatic changes to the regional anthropogenic changes due to various factors over the Nile river floodplains during the late-Holocene (2.5K years before present). The GISS ModelE Earth system model will be used to simulate the various scenarios of regional increasing/decreasing river fraction, changes in vegetation type and cover, along with changes in land surface type against the no-changes scenario in absence of volcanic eruptions. The spatial coverage of the Nile river basin is estimated using the GIS shapefile based on elevation data from Shuttle Radar Topography Mission (SRTM) at 3 Arc-seconds (approx. 90-meter) horizontal resolution. The extent of flooding in the model grid (2.0°x2.5° in latitude and longitude) is estimated using the existing high-resolution (0.125°x0.125°) gridded topographic elevation information and mapped over the Nile river floodplains. This study also focuses on evaluating the NASA GISS ModelE for resolving the climate feedbacks and response on climate system due to anthropogenic changes and volcanic eruptions. It is also aimed to analyze and quantify the impact of various anthropogenic factors over the African monsoon system and rainfall over the region, which feeds the Nile River.

Anthropogenic changes↗

NASA NTRS2017

Educational and Scientific Applications of Climate Model Diagnostic Analyzer

Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA technology and infrastructure have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences in 2014, 2015, and 2016. In the summer school, the students work on group research projects where CMDA provide datasets, analysis tools, and provenance support utility tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each of the science use cases is described in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered, an analysis result such as output plots and data files, and a link to the corresponding analysis service call with all the input arguments filled.

Bao, Qihao↗

NASA NTRS2022

Investigating Stable Oxygen and Carbon Isotopic Variability in Speleothem Records Over the Last Millennium Using Multiple Isotope-Enabled Climate Models

The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISS-E2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

isotope-enabled simulations↗

NASA NTRS2022

Compound Effects of Climate Change on Future Transboundary Water Issues in the Middle East

The Middle East is one of the world’s most vulnerable areas to climate change, which has exacerbated environmental, agricultural, water conflict, and public health issues in the region. Here we analyze the latest climate model projections of precipitation and temperature for the very high emissions scenario, SSP5-8.5,to detect potential future changes in this region. A baseline period (1981-2010) is compared with the middle(2040-2069) and end (2070-2099) of the 21stcentury. The results, representing the worst-case scenario, identify the Tigris-Euphrates headwaters as the hotspot of future compounding effects of climate change in the Middle East. Those effects result from the coincidence of elevated temperature, reduced precipitation, and enhanced interannual variability of precipitation. The hotspot overlays the location of the Southeastern Anatolia Project (in Turkish, GAP) irrigation initiative. In this climate context, risks to GAP viability and downstream water security, and associated potential for water-related conflicts and migration are considerable and demand a reconsideration of the risk-benefit assessment of GAP. This need has become more urgent after the recent widespread and deadly climate-related conflicts and wildfires in summer 2021 across the Middle East that further underlined vulnerability of the region to climate extremes.

Tigris-Euphrates headwater↗

NASA NTRS2022

The Influence of Recent and Future Climate Change on Spring Arctic Cyclones

In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global climate reconstructions and projections to examine how recent and future climatic changes alter cyclone behavior. Results suggest that recent climate change has not yet had an appreciable effect on Arctic cyclone characteristics. However, future sea ice loss and increasing surface temperatures drive large increases in the near-surface temperature gradient, sensible and latent heat fluxes, and convection during cyclones. The future climate can alter cyclone trajectories and increase and prolong intensity with greatly augmented wind speeds, temperatures, and precipitation. Such changes in cyclone characteristics could exacerbate sea ice loss and Arctic warming through positive feedbacks. The increasing extreme nature of these weather events has implications for local ecosystems, communities, and socio-economic activities.

Chelsea L Parker↗

NASA NTRSDate not supplied

Introduction to our COSPAR-Sponsored Session: Space-Observation Contributions Supporting Climate Action

• The challenge for us at COSPAR in putting this program together was that we are primarily a scientifically oriented organization. “Climate Action,” as it is often expressed publicly, tends to be the domain of “activists.” As scientists, on the other hand, to retain our credibility – and for the contributions we make to continue carrying the weight of scientific truth – it is critical that we remain even-handed in our analysis and our reporting of results. • COSPAR is the Committee on Space Research, and fortunately, much of what we observe from space bears objectively on the attributes of the Earth System and how it is evolving. We can measure from space changes in the cryosphere, in the oceans, the land surface and the atmosphere, frequently, on a global scale, to a degree that is generally not possible any other way. And we have been making such observations, in increasing detail, scope, and precision, for about 60 years. • These data help us characterize the current state and identify patterns of change in the Earth System that allow us to infer processes and to improve climate models. With modeling we can test and refine our inferences, and make some predictions. The results can then inform policy and decision-makers, the public in general, as well as those taking direct action. • So, for today’s session we have invited 7 15-minute presentations spanning a broad range of climate-related topics, covering observations from space that can inform climate-related decision-making – from sea-ice extent and sea-level rise, to land surface properties and land-based water resources, to interactions between land or water surfaces and the atmosphere, to severe events in the atmosphere itself. • We begin with an overview of the observations contributed by one of the premier space agencies, given by NASA Chief Scientist and Senior Climate Advisor Dr. Kate Calvin, which will be followed by talks on what we are learning about specific attributes of the Earth System from space-based measurements that can inform climate-related policy and action.

Ralph Kahn↗

NASA NTRS2022

Climate Change-Induced Peatland Drying in Southeast Asia

When organic peat soils are sufficiently dry, they become flammable. In Southeast Asian peatlands, widespread deforestation and associated drainage create dry conditions that, when coupled with El Niño-driven drought, result in catastrophic fire events that release large amounts of carbon and deadly smoke to the atmosphere. While the effects of anthropogenic degradation on peat moisture and fire risk have been extensively demonstrated, climate change impacts to peat flammability are poorly understood. These impacts are likely to be mediated primarily through changes in soil moisture. Here, we used neural networks (trained on data from the NASA Soil Moisture Active Passive satellite) to model soil moisture as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985–2005 and 2040–2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts in 2015 and 2019. Based on previous studies, such reductions may be expected to accelerate peat carbon emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.

VIIRS↗

NASA NTRS2024

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↗

NASA NTRS2024

How Can Future Climate Change Affect the Corn Production System in Nebraska, USA?

The increasing temperatures and changing precipitation patterns have affected both crop yields and water requirements challenging agricultural systems in sustaining high crop yields and ensuring water and food security. In the present study, we evaluated the impact of climate change on the corn production under irrigated and rainfed cropping systems in Nebraska considering four climate zones until 2100 as a case study for the US Corn Belt. Additionally, suggests ways to reduce the impact of climate change on corn yield and water resources. Five global circulation model datasets from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) interconnected to Shared Socioeconomic Pathways (SSPs), were selected. Three future periods: near (2020–2039), mid (2040–2069), and far future (2070–2100) under SSP226, SSP370, and SSP585 scenarios were used to predict the climate changes, crop cycle length, crop yield, and crop water requirement. Additionally, we input annual CO2 concentration scenarios for each SSP scenario to model changes from 2015 to 2100 using the CERES-Maize model. Temperatures are forecasted to rise, precipitation to decline, and crop cycle length to decrease, particularly for SSP370 (up to 49% yield decrease) and SSP585 (up to 67% yield decrease) by 2070–2100. Yields are expected to decline across all scenarios and periods for irrigated and rainfed fields due to the reduction in crop cycle length. Crop water demand is projected to increase, with rainfed systems facing heightened impact due to reduced precipitation. Addressing climate change in Nebraska requires actions like developing new corn varieties to longer the crop season, transitioning to efficient irrigation systems, improving irrigation management for water and food security, and reducing the risk of conflicts over its use. These results open possibilities for discussion about the actions that can be taken to cope with climate change and guarantee water and food security in the US Corn Belt.

CMIP6↗

NASA NTRS2013

Climate Forcing Growth Rates: Doubling Down on Our Faustian Bargain

Rahmstorf et al 's (2012) conclusion that observed climate change is comparable to projections, and in some cases exceeds projections, allows further inferences if we can quantify changing climate forcings and compare those with projections. The largest climate forcing is caused by well-mixed long-lived greenhouse gases. Here we illustrate trends of these gases and their climate forcings, and we discuss implications. We focus on quantities that are accurately measured, and we include comparison with fixed scenarios, which helps reduce common misimpressions about how climate forcings are changing. Annual fossil fuel CO2 emissions have shot up in the past decade at about 3/yr, double the rate of the prior three decades (figure 1). The growth rate falls above the range of the IPCC (2001) 'Marker' scenarios, although emissions are still within the entire range considered by the IPCC SRES (2000). The surge in emissions is due to increased coal use (blue curve in figure 1), which now accounts for more than 40 of fossil fuel CO2 emissions.

climate↗

NASA NTRS2021

Strong Regional Influence of Climatic Forcing Datasets on Global Crop Model Ensembles

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Agricultural Model Intercomparison and Improvement↗

NASA NTRS2022

Unique NISTAR-Based Climate GCM Diagnostics of the Earth’s Planetary Albedo and Spectral Absorption Through Longitudinal Data Slicing

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation permit a unique model/data comparison perspective that is not readily available from other satellite data. The key factor is the unique Lissajous orbital viewing geometry from the Lagrangian L1 point, which enables a continuous view of Earth’s sunlit hemisphere. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) is the DSCOVR Mission energy budget instrument, which views the reflected and emitted radiation of the Earth’s sunlit hemisphere by means of single pixel active cavity full-spectrum (Band-A, 0.2–100 μm) and filtered solar wavelength (Band-B, 0.2–4.0 μm; and Band-C, 0.7–4.0 μm) radiometer measurements. An additional solar wavelength photodiode channel (0.3–1.1 μm) provides a calibration reference. The objective of this study is the assessment of climate GCM performance via direct model/data comparisons. Such comparisons are difficult due to quasi-chaotic natural variability present in real-world observational data and in climate GCM simulations. This is where the unique DSCOVR viewing geometry makes possible the longitudinal data slicing methodology for more direct model/data comparison. The key point of the longitudinal slicing approach is that data integration over the entire sunlit hemisphere eliminates the quasi-chaotic meteorological weather-scale noise, while preserving intra-seasonal and planetary-scale variability. The rotation of the Earth that retrieves this climate-style, large-scale longitudinal and seasonal variability. The hemispheric averaging is accomplished automatically in NISTAR measurements with its single-pixel view of the Earth. For climate GCMs, this requires implementing the Sunlit Hemisphere Sampling (SHS) scheme to operate on the GCM run-time output data, utilizing the DSCOVR Satellite Ephemeris data to assure precise viewing geometry between NISTAR measurements and GCM output data, while averaging out the meteorological weather noise. However, GCM generated data are radiative fluxes, while NISTAR (and EPIC) measurements are near-backscattered radiances. Conversing NISTSR measurements into radiative fluxes cannot be accomplished using NISTAR data alone, even with detailed support from conventional satellite data. But the identical viewing geometry of Earth’s sunlit hemisphere, and synergistic analyses of EPIC data make it feasible for this conversion of NISTAR near-backscatter radiances into radiative fluxes.

deep space climate observatory↗

NASA NTRS2022

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↗