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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Refined Understanding of the Ice Cloud Longwave Scattering Effects in Climate Model

Abstract Because longwave (LW) absorption by greenhouse gases and clouds is more significant than the LW scattering effect by clouds, most climate models neglect cloud LW scattering to save computational costs. Ignoring cloud LW scattering directly overestimates outgoing longwave radiation (OLR). This study included ice‐cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully‐coupled simulations, prescribed sea surface temperature simulations, and offline radiative transfer calculations to comprehensively assess the impact of ice‐cloud LW scattering on global climate simulation. The instantaneous effect due to ice‐cloud LW scattering reduces the OLR by ∼1 W/m 2 on the global average and 2 W/m 2 on the tropical average. Tropospheric warming and high cloud amount reduction act to partially compensate for such instantaneous OLR reduction caused by the inclusion of LW scattering. When the simulation reaches the equilibrium, the surface warms by 0.66 K on average with respect to the simulation without LW scattering, with the Arctic surface temperature differences more than twice as large as that of the global mean. The impact of including LW scattering on the simulated climate change in response to 4 × CO 2 is also assessed. While including the cloud LW scattering does not significantly modify radiative forcing and total radiative feedback under such a scenario, it results in a 10% more positive cloud feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cloud Radiative Effects on MJO Development in DYNAMO

Observed Madden-Julian Oscillation (MJO) events are examined with the aid of regional model simulations to understand the role of cloud radiative effects in the MJO development. The importance of this role is demonstrated by the absence of MJO in the model simulations that contain no cloud radiative effects. Comparisons of model simulations with and without the cloud radiative effects and observation help identify the major processes arising from those effects. Those processes develop essentially from heating in the upper-troposphere due to shortwave absorption within anvil clouds in the upper troposphere and the convergence of longwave radiation in the middle-upper troposphere, with a peak at 300-hPa, during deep convection. First, that heating adds extra buoyancy and accelerates the rising motion in the upper troposphere in deep convection. The vertical acceleration in the upper troposphere creates a vacuum effect and demands for more deep convection to develop. Second, in response to that demand and required by mass balance arises the large-scale horizontal and vertical mass, moisture, and energy convergence. It strengthens deep convection and, with the feedback from continuing cloud radiative effect, creates conditions that can perpetuate deep convection and MJO development. That perpetuation does not occur however because those processes arising from the cloud radiative heating in the upper troposphere stabilize the troposphere till it supports no further deep convection. Weakening deep convection reduces cloud radiative effects. The subsequent reduction of the vacuum effect in the upper troposphere diminishes deep convection completing an MJO cycle. These results advance our understanding of the development of the MJO in the radiative-convective system over warm waters in the tropics. They show that while the embryo of intraseasonal oscillation may exist in the system its growth/development is largely dependent on cloud radiative effects and feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Summertime low clouds mediate the impact of the large-scale circulation on Arctic sea ice

The rapid Arctic sea ice retreat in the early 21 st century is believed to be driven by several dynamic and thermodynamic feedbacks, such as ice-albedo feedback and water vapor feedback. However, the role of clouds in these feedbacks remains unclear since the causality between clouds and these processes is complex. Here, we use NASA CERES satellite products and NCAR CESM model simulations to suggest that summertime low clouds have played an important role in driving sea ice melt by amplifying the adiabatic warming induced by a stronger anticyclonic circulation aloft. The upper-level high pressure regulates low clouds through stronger downward motion and increasing lower troposphere relative humidity. The increased low clouds favor more sea ice melt via emitting stronger longwave radiation. Then decreased surface albedo triggers a positive ice-albedo feedback, which further enhances sea ice melt. Considering the importance of summertime low clouds, accurate simulation of this process is a prerequisite for climate models to produce reliable future projections of Arctic sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part II: Aerosol–Meteorology–Cloud Interaction

Aerosol effects on micro/macrophysical properties of marine stratocumulus clouds over the western North Atlantic Ocean (WNAO) are investigated using in situ measurements and large-eddy simulations (LES) for two cold-air outbreak (CAO) cases (28 February and 1 March 2020) during the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). The LES is able to reproduce the vertical profiles of liquid water content (LWC), effective radius r eff and cloud droplet number concentration N c from fast cloud droplet probe (FCDP) in situ measurements for both cases. Furthermore, we show that aerosols affect cloud properties (N c , r eff , and LWC) via the prescribed bulk hygroscopicity of aerosols ($\bar{κ}$) and aerosol size distribution characteristics. N c , r eff , and liquid water path (LWP) are positively correlated to $\bar{κ}$ and aerosol number concentration (N a ) while cloud fractional cover (CFC) is insensitive to $\bar{κ}$ and aerosol size distributions for the two cases. The realistic changes to aerosol size distribution (number concentration, width, and the geometrical diameter) with the same meteorology state allow us to investigate aerosol effects on cloud properties without meteorological feedback. We also use the LES results to evaluate cloud properties from two reanalysis products, ERA5 and MERRA-2. Compared to LES, the ERA5 is able to capture the time evolution of LWP and total cloud coverage within the study domain during both CAO cases while MERRA-2 underestimates them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Exploring Sources of Surface Bias in HRRR Using New York State Mesonet

In recent years, there has been increasing demand for applications of short-term forecasting of renewable energy potential and assessments of the likelihood of extreme weather events using the High-Resolution Rapid Refresh (HRRR) model. Examining the biases in the newest version of HRRR is necessary to promote further model development. Using data from one of the most comprehensive and dense monitoring networks, New York State Mesonet (NYSM), we evaluate the HRRR version 3 meteorological fields for an entire year. In this work, the land-atmosphere-cloud coupling system is evaluated as an integrated whole. We investigate the physical processes influencing the soil hydrological balance and the thermodynamic interactions, from surface fluxes up to the level of boundary layer convection from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2 m temperature and humidity biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme nocturnal cold bias in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inaccurate representation of energy partition and soil hydrological process across different land use types as well as a hydrological bias in describing spring snowmelt are identified as the main source of the land-surface-induced bias. A feedback loop linking cloud presence, flux changes, and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

When Will MISR Detect Rising High Clouds?

It is predicted by both theory and models that high-altitude clouds will occur higher in the atmosphere as a result of climate warming. This produces a positive longwave feedback and has a substantial impact on the Earth's response to warming. This effect is well established by theory, but is poorly constrained by observations, and there is large spread in the feedback strength between climate models. For this study, we use the NASA Multi-angle Imaging SpectroRadiometer (MISR) to examine changes in Cloud-Top-Height (CTH). MISR uses a stereo-imaging technique to determine CTH. This approach is geometric in nature and insensitive to instrument calibration and therefore is well suited for trend analysis and studies of variability on long time scales. In this article we show that the current MISR record does have an increase in CTH for high-altitude cloud over Southern Hemisphere (SH) oceans but not over Tropical or the Northern Hemisphere (NH) oceans. We use climate model simulations to estimate when MISR might be expected to detect trends in CTH, that include the NH. The analysis suggests that according to the models used in this study MISR should detect changes over the SH ocean earlier than the NH, and if the model predictions are correct should be capable of detecting a trend over the Tropics and NH very soon (3–10 years). This result highlights the potential value of a follow-on mission to MISR, which no longer maintains a fixed equator crossing time and is unlikely to be making observations for another 10 years.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

Abstract In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston’s proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Optimizing DOE Opportunities to Research Land–Atmosphere Interactions in the U.S. Southeast (Workshop Report)

The southeastern United States (Southeast), with its complex and varied environments, is an area of tremendous economic, ecological, and societal importance to the country. The region is characterized by heterogeneous landscapes (i.e., geology and soil type) and a long history of human land use coupled with a warm temperature regime and high precipitation. As a result, soil erosion and deposition are pronounced, vegetation recovery is rapid, and human modification is extensive across the region. To better understand land–atmosphere interactions in this important and complex region, research communities supported by the U.S. Department of Energy’s Biological and Environmental Research (BER) program identified the Southeast as a priority region of interest. In fall 2024, the third Atmospheric Radiation Measurement Mobile Facility (AMF3), one of three mobile monitoring facilities designed to collect atmospheric and climate data from undersampled regions around the world, will begin operations in northwestern Alabama’s Bankhead National Forest (BNF). The AMF3-BNF 5-year deployment, from 2024–2029, will monitor the effects of feedbacks among aerosols, clouds, and precipitation on plant physiology and canopy-scale fluxes. It will also focus on scale aggregation to resolve the role of local forcing on larger-scale processes. To enable broader AMF3 involvement by the science community, the BER Environmental System Science (ESS) program organized the Southeast Land– Atmosphere Research Opportunities (SELARO) workshop in August 2023. The purpose was to identify gaps in scientific understanding of terrestrial processes in the Southeast (defined as states bounded by the Gulf of Mexico to the south, the Atlantic Ocean to east, the Mississippi River to the west, and extending through Tennessee and North Carolina to the north) and explore opportunities to use the AMF3-BNF deployment to coordinate and leverage research efforts across the region. Many parts of the Southeast have experienced repeated anthropogenic forcings. Farming, hunting, burning, and settlement of the region by Indigenous Peoples first shaped the distribution of plant communities, which in turn influenced European colonization patterns. Timber harvesting was common during the expansion of European settlements, and production forestry continues today. Agricultural production was extensive and then waned through the 20th century, creating a period of afforestation following agricultural abandonment. Today, many formerly agricultural landscapes are undergoing rapid urbanization and suburbanization. Overlying these patterns of anthropogenic land use are frequent disturbances from hurricanes, tornadoes, wildfires, drought, flooding, ice storms, and the occasional blizzard. An additional characteristic of the Southeast is its overall landscape complexity. Unlike the western United States, where broad expanses may share similar characteristics, Southeast topography, drainage patterns, vegetation, and development patterns vary widely across relatively small spatial scales (<1 km). This is due to the region’s underlying geology and soil development, species biodiversity patterns, and land ownership and use coupled with strong forces of erosion, weathering, and rapid plant growth in the warm, wet climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Simulating Marine Stratocumulus Clouds using Lagrangian Superdroplet Method in ERF

This study investigates the simulation of marine stratocumulus (stratoCu) clouds – common in many offshore and coastal wind energy regions - using Lagrangian Superdroplet Method (SDM) implemented in Energy Research and Forecasting (ERF) model. Developed by the Wind Energy Technologies Office (WETO), ERF is a high-resolution atmospheric modeling tool that relies on traditional bulk microphysics schemes. Under an LLNL-led Laboratory Directed Research and Development (LDRD) project, SDM was integrated into ERF to improve cloud process fidelity by explicitly tracking individual “superdroplets”. This enables a realistic representation of the droplet size spectrum, cloud-atmosphere interactions, and potential feedbacks from wind plants on atmospheric flow and cloud structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Coupled Climate Simulations With E3SM‐MMF

Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO 2 experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections.

E3SM↗
DOE OSTI2024

The Role of Cloud Radiative Effects in the Propagating Southern Annular Mode

Abstract The Southern Annular Mode (SAM) is the most dominant natural mode of variability in the mid‐latitudes of the Southern Hemisphere (SH). However, both the sign and magnitude of the feedbacks from the diabatic processes, especially those associated with clouds, onto the SAM remain elusive. By applying the cloud locking technique to the Energy Exascale Earth System Model (E3SM) atmosphere model, this study isolates the positive feedback from the cloud radiative effect (CRE) to the SAM. Feedback analysis based on a wave activity‐zonal momentum interaction framework corroborates this weak but positive feedback. While the magnitude of the CRE feedback appears to be secondary compared to the feedbacks from the dry and other diabatic processes, the indirect CRE effects through the interaction with other dynamical and thermodynamical processes appear to play as important a role as the direct CRE in the life cycle of the SAM. The cross‐EOF analysis further reveals the obstructive effect of the interactive CRE on the propagation mode of the SH zonal wind directly through the CRE wave source and/or indirectly through modulating other diabatic processes. As a result, the propagation mode becomes more persistent and the SAM it represents becomes more predictable when the interactive CRE is disabled by cloud locking. Future efforts on inter‐model comparisons of CRE‐denial experiments are important to build consensus on the dynamical feedback of CRE.

58 GEOSCIENCES↗
DOE OSTI2024

Influence of open ocean biogeochemistry on aerosol and clouds: Recent findings and perspectives

Aerosols and clouds are key components of the marine atmosphere, impacting the Earth’s radiative budget with a net cooling effect over the industrial era that counterbalances greenhouse gas warming, yet with an uncertain amplitude. Here we report recent advances in our understanding of how open ocean aerosol sources are modulated by ocean biogeochemistry and how they, in turn, shape cloud coverage and properties. We organize these findings in successive steps from ocean biogeochemical processes to particle formation by nucleation and sea spray emissions, further particle growth by condensation of gases, the potential to act as cloud condensation nuclei or ice nucleating particles, and finally, their effects on cloud formation, optical properties, and life cycle. We discuss how these processes may be impacted in a warming climate and the potential for ocean biogeochemistry—climate feedbacks through aerosols and clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Strength of Coupling to the Southern Ocean Modulates Tropical Eastern Pacific Variability and Forced Response

Despite rising global-mean temperatures, large parts of the Southern Ocean and tropical eastern Pacific Ocean have cooled during the satellite era. These regions may be linked by teleconnections, with Southern Ocean cooling contributing to tropical eastern Pacific cooling. We demonstrate that, on average, state-of-the-art Earth system models (ESMs) underestimate the magnitude of interaction between the Southern Ocean and tropical eastern Pacific Ocean. The strength of the teleconnection is shown to be mediated by the magnitude of the positive cloud–sea surface temperature (SST) feedback in the subtropical eastern Pacific Ocean and the strength of the wind–evaporation–SST (WES) feedback. We link excessive precipitation in the tropical Pacific south of the equator to the strength of the Southern Ocean–eastern Pacific teleconnection. This model bias, known as the double intertropical convergence zone (ITCZ), is shown to be related to erroneous convection south of the equator, weakened cross-equatorial trade winds, and unfavorable meteorological conditions for marine boundary layer subtropical clouds. We postulate there is a two-way interaction, in which a double-ITCZ occurs with weaker cloud–SST and WES feedbacks, which in turn impact local SSTs and amplify the double-ITCZ. Models with a stronger Southern Ocean to tropical Pacific teleconnection tend to exhibit more multidecadal variability in the Walker circulation, ITCZ, and west–east equatorial SST gradient, as well as greater delayed warming in the tropical eastern Pacific Ocean resulting from delayed Southern Ocean warming under greenhouse gas forcing. These results provide insight into why ESMs struggle to replicate observed tropical Pacific temperature trend patterns and point to ITCZ location as a key target for improvement in future model development.

Climate change↗
DOE OSTI2024

Baselining the Indirect Effect by Improving Quantification of Sea Spray and Marine Sources at Ascension Island (Final Report)

Oceans cover two-thirds of the Earth and understanding the interactions of aerosols with clouds in these large marine regions requires quantifying the man-made contributions to the budget of cloud-drop forming particles (known as cloud condensation nuclei, or CCN) relative to the non-manmade “baseline” conditions and understanding the meteorology of boundary layer clouds. Modeling studies have shown substantial uncertainties and sensitivities to natural marine CCN sources, meaning that to reduce uncertainties in indirect effects we must be able to better quantify the CCN budget in ocean regions. While models provide important constraints on these uncertainties, actually reducing uncertainties requires substantial observations in open-ocean and coastal regions in order to establish the baseline on which manmade emissions are added. The tropical South Atlantic Ocean is one of the least-sampled regions of the planet, making the comprehensive measurements of the Department of Energy Atmospheric Radiation Measurement Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign provides the longest record of aerosol size distribution measurements from a differential mobility analyzer in a cloud-influenced marine location in the ARM database, with 17 months of ground-based aerosol size distribution measurements. This project addressed the research topic of Aerosol-Cloud Interactions (ACI) by supporting three publications from the LASIC measurements: 1. The ARM measurements were combined with a new value-added technique that was pioneered by the Russell group for quantifying sea salt. This quantification of sea salt uses supermicron scattering measurements for retrieving reasonable sea spray mass concentrations, providing the best-available, observationally-constrained estimate of the sea spray mode properties when supermicron size distribution measurements are not available. 2. The fitted modes of the distribution were used to investigate the signatures of cloud processing for very clean to very smoky aerosol conditions, revealing not only differences in the particles that activate in clouds but also in the mechanisms that control that droplet formation process. In clean air, the size required to form a cloud droplet is influenced by the number of particles, as well as how quickly particles take up water during growth in cloud. 3. Building on this aerosol characterization, cloud and meteorological conditions were used to evaluate aerosol-related changes in cloud albedo and optical depth. We introduced a new method of decomposing the impact of aerosols on clouds known as the Twomey effect by incorporating retrieved supersaturation from two independent sets of observations to constrain the feedback of aerosol particles on cloud properties. The method quantifies the reduction of the Twomey effect at high aerosol concentrations, which has never been explained quantitatively by observations. In addition, the results provide the first direct validation for the conditions observed in the tropical South Atlantic of a parcel-based approach that is embedded in many climate models. Together these findings illustrate how ARM extended field campaigns in stratocumulus-covered regions can be used to constrain ACI processes with direct observations, providing specific radiative effects without models. By making such process-specific constraints available to improve ACI in global climate models, ARM observations play a key role in supporting model development.

58 GEOSCIENCES↗
DOE OSTI2023

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Significance of the organic aerosol driven climate feedback in the boreal area

Aerosol particles cool the climate by scattering solar radiation and by acting as cloud condensation nuclei. Higher temperatures resulting from increased greenhouse gas levels have been suggested to lead to increased biogenic secondary organic aerosol and cloud condensation nuclei concentrations creating a negative climate feedback mechanism. Here, we present direct observations on this feedback mechanism utilizing collocated long term aerosol chemical composition measurements and remote sensing observations on aerosol and cloud properties. Summer time organic aerosol loadings showed a clear increase with temperature, with simultaneous increase in cloud condensation nuclei concentration in a boreal forest environment. Remote sensing observations revealed a change in cloud properties with an increase in cloud reflectivity in concert with increasing organic aerosol loadings in the area. The results provide direct observational evidence on the significance of this negative climate feedback mechanism.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Role of the Terrestrial Biosphere in Atmospheric Chemistry and Climate

The terrestrial biosphere–atmosphere interface provides a key chemical, biological, and physical lower boundary for the atmosphere. The presence of vegetation itself modifies the physical boundary, or the biogeophysical aspects of the system, by controlling important climate drivers such as soil moisture, light environment, and temperature. The leaf surface area of the terrestrial biosphere provides additional surface area for emissions, and it can be up to 55% of the total Earth’s surface area during the boreal summer. Vegetation also influences the biogeochemical aspects of the system by emitting a broad suite of reactive trace gases such as biogenic volatile organic compound (BVOC) emissions and climate-relevant primary biological aerosol particles (PBAP). Many of these emissions are a function of meteorological and climatological conditions at the surface, including temperature, light environment, soil moisture, and winds. Once emitted, they can be processed in the troposphere through a suite of chemical reactions. BVOC can contribute to the formation of ozone and secondary organic aerosols (SOA), and PBAP can rupture to form smaller particles with climatic relevance. These emissions and subsequent aerosol products can influence atmospheric processes that affect the surface climate, such as the attenuation of radiation, the formation of greenhouse gases such as ozone that can feedback to surface air temperature, and the alteration of clouds and subsequent precipitation. These atmospheric changes can then feedback to the land surface and emissions themselves, creating positive or negative feedback loops that can dampen or amplify the emission response. For the dominant BVOC isoprene, the feedback response to temperature can be positive or negative depending on ambient temperatures that drive isoprene emissions. The feedback response to soil moisture and precipitation can be positive, negative, or uncoupled depending on the moisture content of the soil and the total atmospheric aerosol loading. For light, the isoprene response can be positive or negative depending on the role of diffuse light. Overall, these feedbacks highlight the dynamical response of the biosphere to changing atmospheric conditions across a range of time scales, from minutes for trace gases and aerosols, to months for phenological changes, to years for land cover and land use change. Here, the dynamic aspect of this system requires us to understand, simulate, and predict the complex feedbacks between the biosphere and atmosphere and understand their role in the simulation and understanding of climate and global change. From the observational perspective, these feedbacks are challenging to identify in observations, and predictive modeling tools provide a crucial link for understanding how these feedbacks will change under warming climate scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

CERESMIP: a climate modeling protocol to investigate recent trends in the Earth's Energy Imbalance

The Clouds and the Earth's Radiant Energy System (CERES) project has now produced over two decades of observed data on the Earth's Energy Imbalance (EEI) and has revealed substantive trends in both the reflected shortwave and outgoing longwave top-of-atmosphere radiation components. Available climate model simulations suggest that these trends are incompatible with purely internal variability, but that the full magnitude and breakdown of the trends are outside of the model ranges. Unfortunately, the Coupled Model Intercomparison Project (Phase 6) (CMIP6) protocol only uses observed forcings to 2014 (and Shared Socioeconomic Pathways (SSP) projections thereafter), and furthermore, many of the ‘observed' drivers have been updated substantially since the CMIP6 inputs were defined. Most notably, the sea surface temperature (SST) estimates have been revised and now show up to 50% greater trends since 1979, particularly in the southern hemisphere. Additionally, estimates of short-lived aerosol and gas-phase emissions have been substantially updated. These revisions will likely have material impacts on the model-simulated EEI. We therefore propose a new, relatively low-cost, model intercomparison, CERESMIP, that would target the CERES period (2000-present), with updated forcings to at least the end of 2021. The focus will be on atmosphere-only simulations, using updated SST, forcings and emissions from 1990 to 2021. The key metrics of interest will be the EEI and atmospheric feedbacks, and so the analysis will benefit from output from satellite cloud observation simulators. The Tier 1 request would consist only of an ensemble of AMIP-style simulations, while the Tier 2 request would encompass uncertainties in the applied forcing, atmospheric composition, single and all-but-one forcing responses. We present some preliminary results and invite participation from a wide group of models.

54 ENVIRONMENTAL SCIENCES↗