Search NASA⌕ Search

SEARCH · Search NASA

Results for “Climate Projections”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Warming but not elevated CO 2 depletes soil organic carbon in a temperate rice paddy

In this article, global climate change has the potential to alter soil organic carbon (SOC) stocks in rice paddies, because increases in temperature and atmospheric carbon dioxide concentration ([CO 2 ]) both influence the primary input (i.e., net primary production, NPP) and output (i.e. heterotrophic respiration) of carbon (C). We used two types of open-top chambers representing present conditions (+0°C, +0 ppm CO 2 ) and projected climate change conditions (+2°C, +200 ppm CO 2 ) to investigate the net effect of climate change on SOC stock in rice paddy. Additional chambers with elevated temperature only (+2°C, +0 ppm CO 2 ) allowed us to quantify the individual effects of temperature and [CO 2 ]. We calculated changes in SOC stock using net ecosystem C balance (NECB) analysis (i.e., the balance between C inputs and outputs). Compared to present conditions, projected climate change did not change grain yield due to a trade-off between the effects of warming and [CO 2 ] on grain yield components. NPP during the fallow season significantly decreased under combined warming and CO 2 , as the impact of warming outweighed that of elevated [CO 2 ]. However, rice NPP remained unchanged during the cropping season. Warming plus elevated CO 2 increased SOC mineralization by 157–429 %, particularly through warming-induced soil CO 2 emission during the fallow season. Consequently, climate change conditions decreased (119–271 %) NECB values compared to present conditions, primarily through the response to warming. Our findings demonstrate that rice paddies represent positive feedback on climate change, because accelerated C release from warmed soils will override C gains from NPP under elevated CO 2 . Reducing SOC depletion in rice paddy agriculture under a changing climate therefore requires conservative soil management practices during the fallow season.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Preliminary Error Budget for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements. The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those in the IPCC Report. A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO Project will implement a spaceborne earth observation mission designed to provide rigorous SI traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables, including: 1) Surface temperature and atmospheric temperature profile 2) Atmospheric water vapor profile 3) Far infrared water vapor greenhouse 4) Aerosol properties and anthropogenic aerosol direct radiative forcing 5) Total and spectral solar irradiance 6) Broadband reflected and emitted radiative fluxes 7) Cloud properties 8) Surface albedo There are two methods the CLARREO mission will rely on to achieve these critical decadal change benchmarks: direct and reference inter-calibration. A quantitative analysis of the strengths and weaknesses of the two methods has led to the recommended CLARREO mission approach. The project consists of two satellites launched into 90-degree, precessing orbits separated by 90 degrees. The instrument suite receiver on each spacecraft includes one emitted infrared spectrometer, two reflected solar spectrometers: dividing the spectrum from ultraviolet through near infrared, and one global navigation receiver for radio occultation. The measurements will be acquired for a period of three years minimum, with a five-year lifetime goal, enabling follow-on missions to extend the climate record over the decades needed to understand climate change. The current work concentrates on the reflected solar instrument giving an overview of its design and calibration approach. The calibration description includes the approach to achieving an SI-traceable system on orbit. The calibration overview is followed by a preliminary error budget based on techniques currently in place at the National Institute of Standards and Technology (NIST).

Thome, Kurtis↗
DOE OSTI2025

Early Stages in the Lifecycle of Polar Liquid-Bearing Clouds

Stratiform liquid-bearing clouds are ubiquitous over the polar regions, where they are predominantly mixed-phase. These polar clouds induce substantial radiative forcing on the surface and continuously modify the atmospheric thermodynamic budget, with direct implications for the polar ice pack resilience. However, the physical representation of these clouds is still a major challenge for climate models. A significant part of polar liquid-bearing cloud lifecycle is often manifested in a quasi-steady self-sustaining, persistent, and turbulent state, which is driven by longwave cloud radiative cooling and can last for multiple days. This self-sustaining cloud lifecycle stage has been thoroughly investigated in numerous studies, though some of its aspects such as precipitation still lack robust quantification and evaluation. The preceding cloud lifecycle stages, which may last up to several hours, have nonetheless remained widely overlooked. These preceding stages initiate at cloud formation, often in a stable and non-turbulent atmospheric layer and serve as a key junction between cloud persistence and cloud dissipation. These two contrasting cloud lifecycle trajectories pose the question if general circulation models (GCMs) can capture the full lifecycle accurately for the real physical reasons, a necessary condition to improve our confidence in climate projections given the changing polar climate. The purpose of this project was to improve the characterization and understanding of these early stages in the lifecycle of polar stratiform liquid-bearing cloud and to aid their representation in GCMs. This research relied on measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign, as well as the observations from the ARM West Antarctic Radiation Experiment (AWARE) and the permanent ARM site at Utqiagvik, North Slope of Alaska (NSA).

58 GEOSCIENCES↗
NASA NTRS2005

Projected Regional Climate in 2025 Due to Urban Growth

By 2025, 60 to 80 percent of the world s population will live in urban environments. Additionally, the following facts published by the United Nations further illustrates how cities will evolve in the future. Urban areas in the developing world are growing very rapidly. The urban growth rate will continue to be particularly rapid in the urban areas of less developed regions, averaging 2.4 per cent per year during 2000-2030, consistent with a doubling time of 29 years. The urbanization process will continue worldwide. The concentration of population in cities is expected to continue so that, by 2030, 84 percent of the inhabitants of more developed countries will be urban dwellers. Urbanization impacts the whole hierarchy of human settlements. In 2000,24.8 per cent of the world population lived in urban settlements with fewer than 500,000 inhabitants and by 2015 that proportion will likely rise to 27.1 per cent.

Shepherd, J. Marshall↗
NASA NTRS2014

Reply to Comment by Laprise on 'the Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: a Case Study over the Continental U.S. Using the GISS-ModelE2 and WRF Models'

In his comment, Laprise raises several points that we agree merit consideration. His primary critique is that our study [Racherla et al., 2012] tested the ability of the WRF regional climate model to reproduce historical temperature and precipitation change relative to the driving global climate model (GCM) using only a single simulation rather than an ensemble. He asserts that the observed changes are smaller than the internal variability in the climate system (i.e., not statistically significant) and that thus a single simulation should not necessarily be able to capture the observations. Laprise points out that the statistical signal is reduced for a multi-decadal trend such as the one we analyzed in comparison with mean climatology and cites two studies showing that for particular climate parameters it can take any years for a signal to be discerned over internal variability. He states that The results of theexperiment as designed were strongly influenced by the presence of internal variability and sampling errors,which masked the rather small climate changes that may have occurred as a consequence of changes inforcing during the period considered. While Laprise discusses statistics in general terms at some length, for the actual climate trends examined in our study, he offers no evidence that the forced signal was smallcompared with internal variability. The two studies he cites [de Ela et al., 2013; Maraun, 2013] do not provide convincing evidence as they concern climate variables averaged over different times and areas. One in fact examines extreme precipitation events, which by definition are rare and thus have a lower significance level. We accept the general point that it is important to consider internal variability, and as noted in our paper we agree that an ensemble of simulations is in principle an optimal, though computationally expensive, approach. While we did not present the statistical significance of the observations in our original paper, we have now evaluated those for the regional temperature trends used in our study to evaluate the added value of WRF and thus can analyze data as to the magnitude of the trends with respect to internal variability.

climate↗
NASA NTRS2013

Reducing Spread in Climate Model Projections of a September Ice-Free Arctic

This paper addresses the specter of a September ice-free Arctic in the 21st century using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that large spread in the projected timing of the September ice-free Arctic in 30 CMIP5 models is associated at least as much with different atmospheric model components as with initial conditions. Here we reduce the spread in the timing of an ice-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea ice climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea ice conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September ice extent will drop to approx. 1.7 million sq km in the mid 2040s and reach the ice-free state (defined as 1 million sq km) in 2054-2058. Under a medium-mitigation scenario, both approaches project a decrease to approx.1.7 million sq km in the early 2060s, followed by a leveling off in the ice extent.

simulation↗
NASA NTRS2023

The Regional Aerosol Model Intercomparison Project (RAMIP)

Changes in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from −0.3 to −1.5 W m−2. Both of these sources of uncertainty are exacerbated on regional scales. The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change. RAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality.

anthropogenic aerosol emissions↗
NASA NTRS2013

Multi-model Mean Nitrogen and Sulfur Deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Evaluation Historical and Projected Changes

We present multi-model global datasets of nitrogen and sulfate deposition covering time periods from 1850 to 2100, calculated within the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The computed deposition fluxes are compared to surface wet deposition and ice-core measurements. We use a new dataset of wet deposition for 2000-2002 based on critical assessment of the quality of existing regional network data. We show that for present-day (year 2000 ACCMIP time-slice), the ACCMIP results perform similarly to previously published multi-model assessments. For this time slice, we find a multi-model mean deposition of 50 Tg(N) yr1 from nitrogen oxide emissions, 60 Tg(N) yr1 from ammonia emissions, and 83 Tg(S) yr1 from sulfur emissions. The analysis of changes between 1980 and 2000 indicates significant differences between model and measurements over the United States but less so over Europe. This difference points towards misrepresentation of 1980 NH3 emissions over North America. Based on ice-core records, the 1850 deposition fluxes agree well with Greenland ice cores but the change between 1850 and 2000 seems to be overestimated in the Northern Hemisphere for both nitrogen and sulfur species. Using the Representative Concentration Pathways to define the projected climate and atmospheric chemistry related emissions and concentrations, we find large regional nitrogen deposition increases in 2100 in Latin America, Africa and parts of Asia under some of the scenarios considered. Increases in South Asia are especially large, and are seen in all scenarios, with 2100 values more than double 2000 in some scenarios and reaching 1300 mg(N) m2 yr1 averaged over regional to continental scale regions in RCP 2.6 and 8.5, 3050 larger than the values in any region currently (2000). The new ACCMIP deposition dataset provides novel, consistent and evaluated global gridded deposition fields for use in a wide range of climate and ecological studies.

Lamarque, J.-F.↗
NASA NTRS2013

Multi-Model Mean Nitrogen and Sulfur Deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Evaluation of Historical and Projected Future Changes

We present multi-model global datasets of nitrogen and sulfate deposition covering time periods from 1850 to 2100, calculated within the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The computed deposition fluxes are compared to surface wet deposition and ice core measurements.We use a new dataset of wet deposition for 2000-2002 based on critical assessment of the quality of existing regional network data. We show that for present day (year 2000 ACCMIP time slice), the ACCMIP results perform similarly to previously published multi-model assessments. For this time slice, we find a multimodel mean deposition of approximately 50 Tg(N) yr−1 from nitrogen oxide emissions, 60 Tg(N) yr−1 from ammonia emissions, and 83 Tg(S) yr−1 from sulfur emissions. The analysis of changes between 1980 and 2000 indicates significant differences between model and measurements over the United States but less so over Europe. This difference points towards a potential misrepresentation of 1980 NH3 emissions over North America. Based on ice core records, the 1850 deposition fluxes agree well with Greenland ice cores, but the change between 1850 and 2000 seems to be overestimated in the Northern Hemisphere for both nitrogen and sulfur species. Using the Representative Concentration Pathways (RCPs) to define the projected climate and atmospheric chemistry related emissions and concentrations, we find large regional nitrogen deposition increases in 2100 in Latin America, Africa and parts of Asia under some of the scenarios considered. Increases in South Asia are especially large, and are seen in all scenarios, with 2100 values more than double their 2000 counterpart in some scenarios and reaching >1300 mg(N)m−2 yr−1 averaged over regional to continental-scale regions in RCP 2.6 and 8.5, 30-50% larger than the values in any region currently (circa 2000). However, sulfur deposition rates in 2100 are in all regions lower than in 2000 in all the RCPs. The new ACCMIP multimodel deposition dataset provides state-of-the-science, consistent and evaluated time slice (spanning 1850-2100) global gridded deposition fields for use in a wide range of climate and ecological studies.

Lamarque, J.-F.↗
NASA NTRS2018

The PMIP4 Contribution to CMIP6 - Part 1: Overview and Over-Arching Analysis Plan

This paper is the first of a series of four GMD (Geoscientific Model Development) papers on the PMIP4-CMIP6 (Paleoclimate Modelling Intercomparison Project - Phase 4 -- Coupled Model Intercomparison Project - Phase 6) experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) - Phase 2, detailed in Haywood et al. (2016). The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21,000 years ago (lgm); the Last Interglacial, 127,000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs.

climate↗
NASA NTRS2010

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Sandford, Stephen P.↗
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↗
NASA NTRS2017

Synergy Between Land Use and Climate Change Increases Future Fire Risk in Amazon Forests

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

Le Page, Yannick↗
NASA NTRS2021

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗
NASA NTRS2013

The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

humidity↗
NASA NTRSDate not supplied

Importance of Radiative Transfer Models in Atmospheric Remote Sensing

Radiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability. RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications. Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections. Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics. This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these

Isaac Moradi↗
DOE OSTI2025

CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US

This dataset presents a suite of downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled dynamically using Regional Climate Model version 4 (RegCM4). Each ensemble member covers the 1980-2019 baseline and 2020-2059 near-future periods under the high-end (SSP585) emission scenario. This dataset is formulated to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details on this dataset, please refer to Kao et al. (2022) and Rastogi et al. (2022).

13 HYDRO ENERGY↗