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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of Model Summertime Boundary Layer Cloud Development over Complex Terrain in New York State

Weather forecasting over complex terrain with diverse land cover is challenging. Utilizing the high-resolution observations from New York State Mesonet (NYSM), we are able to evaluate the surface processes of the Weather Research Forecast (WRF) Model in a detailed, scale-dependent manner. Here, in the study, possible impacts of land–atmosphere interaction on surface meteorology and boundary layer cloud development are investigated with different model resolutions, land surface models (LSMs), and planetary boundary layer (PBL) physical parameterizations. The High-Resolution Rapid Refresh, version 3 (HRRR), forecasting model is used as a reference for the sensitivity evaluation. Results show that over complex terrain, the high-resolution simulations (1 km × 60 vertical levels) generally perform better compared to low-resolution (3 km × 50 levels) in both surface meteorology and cloud fields. LSMs play a more important role in surface meteorology compared to PBL schemes. The NoahMP land surface model exhibits daytime warmer and drier biases compared to the Rapid Update Cycle (RUC) due to better prediction of the Bowen ratio in RUC. The PBL schemes would affect the convective strength in the boundary layer. The Shin–Hong (SH) scale-aware scheme tends to produce the strongest convective strength in the PBL, while the ACM2 PBL scheme rarely resolved convection even at 1-km resolution. By considering the radiation effect of subgrid-scale (SGS) clouds, the Mellor–Yamada–Nakanishi–Niino eddy diffusivity mass flux (MYNN-EDMF) predicted the highest cloud coverage and lowest surface solar radiation bias. The configuration of SGS clouds in MYNN-EDMF would not only significantly reduce shortwave radiation bias, but also affect the convection behaviors through land surface–cloud–radiation interaction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effect of data assimilation in the Polar WRF with 3DVAR on the prediction of radiation, heat flux, cloud, and near surface atmospheric variables over Svalbard

Although the Polar Weather Research and Forecasting (PWRF) model has been developed for polar environments, simulations of atmospheric states in the polar region still have large uncertainties. Therefore, the effects of data assimilation (DA) to improve forecasts in the polar region were investigated for September 2017 using PWRF and the three-dimensional variational (3DVAR) DA method. The experiments without DA and those with DA assimilating only conventional observations and both conventional observations and satellite radiance data were performed. The forecasts from all experiments both without and with DA underestimated (overestimated) the downward longwave (shortwave) radiation flux due to the underestimation of the amount of Arctic clouds. When satellite radiance data (i.e., the Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS)) were assimilated in addition to conventional observations in the PWRF, the distribution and amount of water vapor became closer to observations, which improves cloud liquid water forecasts. Therefore, when both conventional observations and radiance data were assimilated, the 25–30 h forecast errors of the downward longwave and shortwave radiation fluxes and sensible and latent heat fluxes decreased by 12.7%, 8.1%, 3.2%, and 7.8% with the WSM5 scheme and by 17.1%, 4.7%, 2.5%, and 3.1% with the 2-moment Morrison scheme, respectively, compared to those in the experiments without DA. The forecast errors of the 10 m wind and 2 m temperature with DA were smaller than those without DA at most observation stations. Therefore, the uncertainties of the Arctic forecasts in the PWRF decreased when using DA. To further improve Arctic forecasts, the assimilation of various additional satellite data is necessary.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

Abstract. Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Sensitivity of Anthropogenic Cloud Droplet Number Change to Preindustrial Emission Inventories and Physics Parameterizations

Understanding the preindustrial (PI) to present-day (PD) change in cloud droplet number concentration (ΔNd) is important to constrain the anthropogenic influence on clouds and aid future model projections. Perturbed parameter ensemble simulations of PI and PD conditions in the Energy Exascale Earth System Model (E3SMv3) reveal two locations with consistent negative ΔNd signal across parameter space–the Southeastern US and the United Kingdom–despite a trend of positive ΔNd globally from increased fossil fuel consumption. These negative ΔNd signals are driven by higher anthropogenic biofuel emissions in the PI. By varying the PI aerosol mass and/or number emissions across these data sets' uncertainty ranges, we can change the magnitude and sign of ΔNd and the effective radiative forcing from aerosol-cloud interactions (ERFaci) regionally and globally, with near-zero ΔNd leading to near-zero ERFaci. These results highlight the need to constrain PI emission uncertainty to better understand Earth system responses to aerosol-cloud interactions.

Brown, Hunter Y. [University of Wyoming, Laramie, ↗
DOE OSTI2025

Global quantification of the dispersion effect with POLDER satellite data

Increased aerosols can modify the shape of the cloud Particle Size Distribution (PSD), thereby influencing the radiative properties of clouds, known as the Dispersion Effect (DE). However, a global, observation-based quantification of its impact on Aerosol-Cloud Interactions (ACI) is lacking, leading to DE being typically ignored in satellite-based estimates of ACI forcing. Here we propose a physics-based method that combines polarimetric satellite data on cloud PSD to achieve global observational quantification of DE’s impact on ACI in liquid-phase stratiform clouds. Globally, DE offsets ACI changes induced by droplet number concentration variation and liquid water path adjustment by 7% and −1.4%, respectively. Furthermore, a parameterization based on the global dataset of PSD shape parameters is developed to improve DE estimation in large-scale models. Both the quantification and parameterization enhance our understanding of DE and facilitate the inclusion of this non-negligible impact of DE on ACI in estimating aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Pluminate: Quantifying aerosol injection behavior from simulation, experimentation and observations

Marine aerosol injections are a key component in further understanding of both the potentials of deliberate injection for marine cloud brightening (MCB), a potential climate intervention (CI) strategy, and key aerosol-cloud interaction behaviors that currently form the largest uncertainty in global climate model (GCM) predictions of our climate. Since the rate of spread of aerosols in a marine environment directly translates to the effectiveness and ability of aerosol injections in impacting cloud radiative forcing, it is crucial to understand the spatial and temporal extent of injected-aerosol effects following direct injection into marine environments. The ubiquity of ship-injected aerosol tracks from satellite imagery renders observational validation of new parameterizations possible in 2D, however, 3D compatible data is more scarce, and necessary for the development of subgrid scale parameterizations of aerosol-cloud interactions in GCMs. This report introduces two novel parameterizations of atmospheric aerosol injection behavior suitable for both 3D (GCM-compatible) and 2D (observation-related) modeling. Their applicability is highlighted using a wealth of different observational data: small and larger scale salt-aerosol injection experiments conducted at SNL, 3D large eddy simulations of ship-injected aerosol tracks and 2D satellite images of ship tracks. The power of experimental data in enhancing knowledge of aerosol-cloud interactions is in particular emphasized by studying key aerosol microphysical and optical properties as observed through their mixing in cloud-like environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

QBO deepens MJO convection

Abstract The underlying mechanism that couples the Quasi-Biennial Oscillation (QBO) and the Madden-Julian oscillation (MJO) has remained elusive, challenging our understanding of both phenomena. A popular hypothesis about the QBO-MJO connection is that the vertical extent of MJO convection is strongly modulated by the QBO. However, this hypothesis has not been verified observationally. Here we show that the cloud-top pressure and brightness temperature of deep convection and anvil clouds are systematically lower in the easterly QBO (EQBO) winters than in the westerly QBO (WQBO) winters, indicating that the vertical growth of deep convective systems within MJO envelopes is facilitated by the EQBO mean state. Moreover, the deeper clouds during EQBO winters are more effective at reducing longwave radiation escaping to space and thereby enhancing longwave cloud-radiative feedback within MJO envelopes. Our results provide robust observational evidence of the enhanced MJO activity during EQBO winters by mean state changes induced by the QBO.

Jin, Daeho (ORCID:0000000343894393)↗
DOE OSTI2023

Influences of cloud vertical overlapping on the calculated cloud albedo and their validation with satellite observations

Cloud albedo is expected to influence cloud radiative forcing in addition to cloud fraction, and inadequate description of the cloud overlapping effects on the cloud fraction may influence the simulated cloud fraction, and thus the relative cloud radiative forcing (RCRF) and cloud albedo. In this study, we first present a new formula by extending that presented previously in Liu et al. (2011) to consider multilayer clouds directly in the relationship between cloud albedo, cloud fraction and RCRF, and then quantitatively evaluate the effects of different cloud vertical overlapping structures, represented by the decorrelation length scales (L cf ), on the simulated cloud albedos. We use the BCC_AGCM2.0_CUACE/Aero model with simultaneous validation by observations from the Clouds and the Earth's Radiation Energy System (CERES) satellite. When L cf < 4 km (i.e., the cloud overlap is closer to the random overlap), the simulated cloud albedos are generally in good agreement with the satellite-based albedos for December– February and June–August; when L cf ≥ 4 km (i.e., the cloud vertical overlap is closer to the maximum overlap), the difference between simulated and observed cloud albedos became larger, due mainly to significant differences in cloud fractions and RCRF. Further quantitative analysis shows that the relative Euclidean distance, which represents the degree of overall model–observation disagreement, increases with the L cf for all three variables (cloud albedo, cloud fraction and RCRF), indicating the importance of cloud vertical overlapping in determining the accuracy of the calculated cloud albedo for multilayer clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Early Career Research Program Annual Progress Report: Using ARM Data and Multiscale Models to Advance the Understanding of Liquid-Phase Cloud Response to Aerosol Perturbation over Ocean and Land

This project aims to study the response of liquid-phase clouds to aerosol perturbation and reduce the related uncertainty in the DOE Earth system model. Specific objectives include: Objective 1: Quantify the aerosol indirect effect on liquid-phase clouds using ARM observations and satellite retrievals while constraining the confounding large-scale conditions; Objective 2: Harness LES case studies, untangle the confounding meteorological impacts on the observed aerosol indirect effect, and identify key cloud processes controlling the net radiative forcing of aerosol-cloud interactions at different spatiotemporal scales; Objective 3: Evaluate the aerosol indirect effect on liquid-phase clouds with process-level understanding in E3SM multiscale model configurations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Strategizing emission cuts in China to mitigate short-term warming from clean air policies

Aerosol-cloud interactions remain one of the largest sources of uncertainty in estimates of anthropogenic climate forcing. Reducing aerosols to achieve air quality improvement and climate goals can cause unintended warming due to the weakening of aerosol cooling. Here we investigate the climate impacts of spatially optimized sulfur dioxide (SO 2 ) emission reduction under a carbon-neutral pathway in China. We find that targeting reduction in highly polluted regions in China significantly suppresses the rise in effective radiative forcing due to aerosol-cloud interactions (ERF aci ) during 2020–2060. Owing to the nonlinear aerosol-cloud interaction, the optimized emission reduction strategy limits the regional average increase in ERF aci of more than 0.89 W m −2 to less than 0.13 W m −2 in the short-term future during 2020–2040 and weakens the ERF aci increase by two-thirds in 2060 over China. These findings demonstrate the critical role of targeted emission control in mitigating short-term climate risks while pursuing air quality goals.

Zhu, Yitong [Nanjing Univ. of Information Science ↗
DOE OSTI2025

Enhanced mid-latitude warming due to poleward shift of sea salt aerosols in a warmer future

Natural aerosols provide large uncertainties regarding the quantification of the climate effects of aerosols, especially those related to aerosol-cloud interactions. Advancing research on the interaction of natural aerosols and climate can provide a better assessment of the climate impacts of anthropogenic activities. Furthermore, as one of the most dominant natural aerosols, sea salt has the highest proportion of mass in natural aerosols. Sea salt can be regarded as a purely scattering aerosol, causing a negative radiative effect by scattering shortwave solar radiation and acting as cloud condensation nuclei (CCN) through aerosol-cloud interactions. Future climate change will influence sea salt distribution, thus modifying the radiative effects of sea salt, which will further affect the climate. However, few previous studies have explored the interactions between sea salt changes under warming scenarios and climate change.

Yang, Yang [Nanjing Univ. of Information Science a↗
DOE OSTI2025

Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages

The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Fall and Rise of the Global Climate Model

Abstract Global models are an essential tool for climate projections, but conventional coarse‐resolution atmospheric general circulation models suffer from errors both in their parameterized cloud physics and in their representation of climatically important circulation features. A notable recent study by Terai et al. (2020, https://doi.org/10.1029/2020ms002274) documents a global model capable of reproducing the regime‐based effect of aerosols on cloud liquid water path expected from observational evidence. This may represent a significant advance in cloud process fidelity in global models. Such models can be expected to give a better estimate of the effective radiative forcing of the climate. If this advance in cloud process representation can be matched by advances in the representation of circulation features such as monsoons, then such models may also be able to navigate the complex tangle between spatially heterogeneous aerosol–cloud interactions and regional circulation patterns. This tight link between aerosol and circulation results in anthropogenic perturbations of climate variables of societal importance, such as regional rainfall distributions. Upcoming global models with km‐scale resolution may improve the regional circulation and be able to take advantage of the Terai et al. (2020, https://doi.org/10.1029/2020ms002274) improvement in cloud physics. If so, an era of significantly improved regional climate projection capabilities may soon dawn. If not, then the improvement in cloud physics might spur intensified efforts on problems in model dynamics. Either way, based on the rapid changes in aerosol emissions in the near future, learning to make reliable projections based on biased models is a skill that will not go out of style.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Enhancing Convection Parameterization for Next Generation E3SM (Final Technical Report)

This technical report summarizes the achievements during the project period. The general goal of the project is to enhance the representation of atmospheric deep convection in the DOE global climate model E3SM. By implementing a stochastic convection scheme into E3SM, we improved the simulation of precipitation intensity and frequency. As a result, it has a profound impact on the simulation of other fields in the model, including aerosol scavenging by precipitation and aerosol radiative effects. We also implemented a convective cloud microphysics scheme into E3SMv2 to represent more accurately the interaction between convection and grid-scale clouds. An extensive analysis of model simulations as part of the Next Generation Development (NGD) convection scheme assessment project found that including the convective microphysics scheme improved the simulation of Madden-Julian oscillations (MJO) in the model. To make convective parameterization schemes more scale-aware as the GCM resolution increases, we analyzed the output from cloud-resolving model (CRM) simulations of both organized and unorganized convection by coarse-graining the CRM data to different GCM resolutions. Using a novel approach to modify the convective closure, we demonstrated that the convection scheme used in E3SM (ZM scheme) can be made scale-aware.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Optimizing energy yield of monolithic perovskite/silicon tandem solar cells in real-world Conditions: The impact of luminescent coupling

Efficient light management is key to maximizing power conversion efficiency (PCE) in monolithic perovskite/silicon tandem solar cells. Achieving peak efficiency requires closely matched current generation in all junctions, especially in integrated configurations. However, real-world conditions vary significantly due to factors such as sunlight spectrum, diffuse-to-direct sunlight ratio, angular distribution of light, subcell temperature coefficients, and ground reflection. This study introduces a comprehensive optical and device simulation to optimize perovskite/silicon tandem cells, considering experimental luminescent coupling (LC) efficiency and its dependence on working conditions, alongside variations in radiative recombination, effect of temperature on absorptivity spectra, and cloud cover. Our results show potential energy yield improvements of up to 1.4 % with LC, based on current perovskite radiative recombination records, and up to 4 % with direct bandgap materials. Although radiative recombination's dependence on excitation intensity reduces output power and requires thicker absorbers, LC compensates for these losses. LC also lowers the optimized bandgap for the perovskite top cell from 1.72 eV to 1.64–1.68 eV, or even lower in regions with redshifted irradiance. Additionally, optimization revealed that thinner silicon bottom cells require a higher perovskite top cell bandgap, impacting the balance between fabrication cost and cell stability.

14 SOLAR ENERGY↗
DOE OSTI2022

Influence of Aerosol Embedded in Shallow Cumulus Cloud Fields on the Surface Solar Irradiance

Ubiquitous shallow cumulus clouds are associated with complex variability in surface solar irradiance (SSI). Aerosol embedded in the cloud field typically has a much smaller overall radiative effect, but can significantly perturb the shape of the SSI probability density function (PDF). These perturbations have important implications for several applications that utilize SSI, but are poorly quantified and are the subject of this study. Multiple cases of shallow cumulus cloud fields with embedded aerosol are simulated at the Southern Great Plains Atmospheric Observatory using large eddy simulation (LES). The LES-derived cloud and aerosol fields are then ingested into Monte Carlo three-dimensional (3D) radiative transfer to simulate SSI. We find a variety of perturbations to the SSI PDF that depend on aerosol presence and optical properties. The processes leading to these perturbations include extinction of the direct beam that often increases from the clear-sky region toward cloud edge due to aerosol hygroscopic growth, and scattering of radiation by aerosol into cloud shadows. The ability to predict the SSI PDF in the presence of aerosol is assessed by adding three representative aerosol optical properties into an existing machine learning framework. We show that machine learning accurately predicts the SSI PDF across a wide range of conditions with negligible computational expense. Importance metrics reveal the relatively high influence of aerosol optical properties in making the predictions. These new findings highlight the important role that aerosol plays in SSI variability for highly 3D cloud-aerosol environments and provides a computationally efficient route forward for its simulation.

3D radiative transfer↗
DOE OSTI2022

Cloud adjustments from large-scale smoke–circulation interactions strongly modulate the southeastern Atlantic stratocumulus-to-cumulus transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (~1–2 K) and greatly enhanced moisture (>2 g kg -1 ) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Seasonality and Albedo Dependence of Cloud Radiative Forcing in the Upper Colorado River Basin

Mountains create and enhance their own clouds, which both scatter and absorb shortwave radiation from the sun and absorb and re-emit land surface and atmospheric longwave radiation. However, the impacts of clouds on the surface radiation balance in high elevation snowy mountain terrain are poorly explored. In this study, we use data collected by the SAIL field campaign and partner organizations in the upper elevations (2,880 m.a.s.l) of the Upper Colorado River Basin (UCRB) over a 21-month period from September 2021 to June 2023 to estimate Cloud Radiative Forcing (CRF) in the shortwave, longwave, and the net effect. Longwave warming effects dominate during the winter when snow albedos are high (0.8–0.9) and the background atmospheric precipitable water vapor is low (<0.5 cm), yielding a maximum monthly average net CRF of +34.7 W·m -2 , meaning that clouds increase the net radiation relative to clear skies during this time period. The sign of net CRF switches in the warm season as snow recedes, sun-angles increase, and the North American monsoon arrives, yielding a minimum monthly average net CRF of -47.6 W·m -2 with hourly minima of -600 W·m -2 . The sign of net CRF is typically positive, even at solar noon, when the surface is snow covered, except for a brief period over melting, low-albedo snow (0.5–0.6) impacted by dust impurities. Sensitivity tests elucidate the role of the surface albedo on the net CRF. The results suggest that net CRF will increase in magnitude and lead to a more persistent cooling effect on the surface net radiation budget as the snow cover declines.

54 ENVIRONMENTAL SCIENCES↗