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At least 55 records · Page 3

On the Prediction of Aerosol-Cloud Interactions Within a Data-Driven Framework

Aerosol-cloud interactions (ACI) pose the largest uncertainty for climate projection. Among many challenges of understanding ACI, the question of whether ACI can be deterministically predicted has not been explicitly answered. Here we attempt to answer this question by predicting cloud droplet number concentration N c from aerosol number concentration N a and ambient conditions using a data-driven framework. We use aerosol properties, vertical velocity fluctuations, and meteorological states from the ACTIVATE field observations (2020–2022) as predictors to estimate N c . We show that the campaign-wide N c can be successfully predicted using machine learning models despite the strongly nonlinear and multi-scale nature of ACI. However, the observation-trained machine learning model fails to predict N c in individual cases while it successfully predicts N c of randomly selected data points that cover a broad spatiotemporal scale. This suggests that, within a data-driven framework, the N c prediction is uncertain at fine spatiotemporal scales.

54 ENVIRONMENTAL SCIENCES↗

Aerosol effective radiative forcing increases Earth’s energy imbalance in recent decades

Earth’s energy imbalance (EEI), a key driver of climate change, has risen markedly over the last two decades. Greenhouse gas forcing, aerosol forcing, and cloud feedback all contribute to this increase. However, the role of aerosol forcing, particularly effective radiative forcing through aerosol-cloud interactions (ERF ACI ), remains highly uncertain and closely intertwined with cloud feedback. Here, we estimate shortwave ERF ACI using satellite observations and show its importance as a contributor to the EEI increase between 2003 and 2023. ERF ACI exhibits a significant increasing trend of 0.33 Wm −2 /decade averaged over oceans between 60°S and 60°N. The increasing trend of ERF ACI stems from a global decline in cloud droplet number concentration driven by decreasing anthropogenic aerosol emissions. It is of similar magnitude as the combined instantaneous forcing trend from greenhouse gases and aerosol-radiation interactions. Our results may reduce the gap between the simulated and observed shortwave contribution to EEI trends while implying a weak shortwave cloud feedback. They also suggest a stronger aerosol forcing than the multi-model mean.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗

Advancing the quantification of aerosol-cloud interactions with the CALIPSO-CloudSat-Aqua/MODIS record

Aerosol-cloud-precipitation interactions are assessed over the non-polar ocean using more than 11 years of combined Aqua-MODIS, CALIPSO-CALIOP, and CloudSat products. The analysis first shows the benefit of incorporating vertically resolved aerosol extinction coefficient (σext) in aerosol-cloud interactions (ACI) assessments, demonstrating that: σext vertically collocated with the cloud layer () correlates best with cloud droplet number concentration (Nd), column-integrated aerosol optical depth (AOD) cannot explain the Nd variability in the extratropics, and the S-shape of the AOD-Nd relationship reported in previous studies is not replicated when using instead of AOD, with a Nd- linearity more consistent with in-situ studies over the ocean. ACI metric, estimated as the log-scale regression between CALIOP and MODIS Nd reveals that the eastern Pacific is the region with the strongest ACI, followed by the Southern Ocean. The susceptibility of clouds to changes in their liquid water path (LWP) and frequency of precipitation followed a 2-step calculation by combining the Nd- regression (ACI) with the regression between these macrophysical variables and Nd. LWP susceptibility is negative (LWP decreases with aerosol loading) and statistically significant over the eastern Pacific, eastern Atlantic, and extratropics. In contrast, vast areas of the tropical and subtropical ocean feature negligible changes in LWP with aerosol. Precipitation frequency susceptibility is negative, but the values are only significant over the coastal eastern Pacific and Atlantic. The findings suggest that previous modeling assessments relying on AOD may need to be revisited by taking advantage of the synergy between passive and active sensors.

Li, Zhujun↗

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.

54 ENVIRONMENTAL SCIENCES↗

Low- to Mid-Latitude X-Ray Emission from Jupiter

The Chandra X-ray Observatory (CXO) observed Jupiter during the period 2003 February 24-26 for approx.40 hours (4 Jupiter rotations), using both the spectroscopy array of the Advanced CCD Imaging Spectrometer (ACIS-S) and the imaging array of the High-Resolution Camera (HRC-I). Two ACIS-S exposures, each approx.8.5 hr long, were separated by an HRC-I exposure of approx.20 hr. The low- to mid-latitude non-auroral disk X-ray emission is much more spatially uniform than the auroral emission. However, the low- to mid-latitude X-ray count rate shows a small but statistically significant hour angle dependence, and is higher in regions of relatively low surface magnetic field strength, confirming ROSAT results. In addition, the spectrum from the low surface field region shows an enhancement in the energy band 1.14- 1.38 keV, perhaps partly due to line emission from that region. Correlation of surface magnetic field strength with count rate is not found for the 2000 December HRC-I data, at a time when solar activity was high. The low- to mid-latitude disk X-ray count rate observed by the HRC-I in the 2003 February observation is about 50% of that observed in 2000 December, roughly consistent with a decrease in the solar activity index (F10.7 cm flux) by a similar amount over the same time period. The low- to mid-latitude X-ray emission does not show any oscillations similar to the -45 minute oscillations sometimes seen from the northern auroral zone. The temporal variation in Jupiter's non-auroral X-ray emission exhibits similarities to variations in solar X-ray flux observed by GOES and TIMED/SEE. The two ACIS-S 0.3-2 keV low- to mid-latitude X-ray spectra are harder than the auroral spectrum, and are different from each other at energies above 0.7 keV, showing variability in Jupiter s non-auroral X-ray emission on a time scale of a day. The 0.3-2.0 keV X-ray power emitted at low- to mid-latitudes is 0.21 GW and 0.39 GW for the first and second ACIS-S exposures, respectively. We suggest that X-ray emission from Jupiter's disk may be largely generated by solar X-rays resonantly and fluorescently scattered in its upper atmosphere, especially at times of high incident solar X-ray flux. However, the correlation of higher count rate with low surface magnetic-field strength indicates the presence of some secondary component, possibly ion precipitation from radiation belts closer to the planet than elsewhere at low- to mid-latitudes.

Bhardwaj, Anil↗

Low- to Middle-Latitude X-Ray Emission from Jupiter

The Chandra X-ray Observatory (CXO) observed Jupiter during the period 24-26 February 2003 for approx. 40 hours (4 Jupiter rotations), using both the spectroscopy array of the Advanced CCD Imaging Spectrometer (ACIS-S) and the imaging array of the High-Resolution Camera (HRC-I). Two ACIS-S exposures, each -8.5 hours long, were separated by an HRC-I exposure of approx. 20 hours. The low- to middle-latitude nonauroral disk X-ray emission is much more spatially uniform than the auroral emission. However, the low- to middle-latitude X-ray count rate shows a small but statistically significant hour angle dependence and depends on surface magnetic field strength. In addition, the X-ray spectra from regions corresponding to 3-5 gauss and 5-7 gauss surface fields show significant differences in the energy band 1.26-1.38 keV, perhaps partly due to line emission occurring in the 3-5 gauss region but not the 5-7 gauss region. A similar correlation of surface magnetic field strength with count rate is found for the 18 December 2000 HRC-I data, at a time when solar activity was high. The low- to middle-latitude disk X-ray count rate observed by the HRC-I in the February 2003 observation is about 50% of that observed in December 2000, roughly consistent with a decrease in the solar activity index (F10.7 cm flux) by a similar amount over the same time period. The low- to middle-latitude X-ray emission does not show any oscillations similar to the approx. 45 min oscillations sometimes seen from the northern auroral zone. The temporal variation in Jupiter's nonauroral X-ray emission exhibits similarities to variations in solar X-ray flux observed by GOES and TIMED/SEE. The two ACIS-S 0.3-2.0 keV low- to middle-latitude X-ray spectra are harder than the auroral spectrum and are different from each other at energies above 0.7 keV, showing variability in Jupiter's nonauroral X-ray emission on a timescale of a day. The 0.3-2.0 keV X-ray power emitted at low to middle latitudes is 0.21 GW and 0.39 GW for the first and second ACIS-S exposures, respectively. We suggest that X-ray emission from Jupiter's disk may be largely generated by the scattering and fluorescence of solar X rays in its upper atmosphere, especially at times of high incident solar X-ray flux. However, the dependence of count rate on surface magnetic-field strength may indicate the presence of some secondary component, possibly ion precipitation from radiation belts close to the planet.

Bhardwaj, Anil↗

Aerosol-Cloud Interaction Determined by Both in Situ and Satellite Data Over a Northern High-Latitude Site

The first aerosol indirect effect over a clean, northern high-latitude site was investigated by determining the aerosol cloud interaction (ACI) using three different approaches; ground-based in situ measurements, combined ground-based in situ measurements 5 and satellite retrievals and using only satellite retrievals. The obtained values of ACI were highest for in situ ground-based data, clearly lower for combined ground-based and satellite data, and lowest for data relying solely on satellite retrievals. One of the key findings of this study was the high sensitivity of ACI to the definition of the aerosol burden. We showed that at least a part of the variability in ACI can be explained by 10 how different investigators have related dierent cloud properties to "aerosol burden".

Lihavainen, H.↗

Real Time Space Weather Support for Chandra X-Ray Observatory Operations

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ( soft , 100 500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth s magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA s Space Weather Prediction Center. This presentation describes the radiation mitigation strategies to minimize the proton damage in the ACIS CCD detectors and the importance of real-time data sources that are used to protect the ACIS detector system from space weather events.

O'Dell, Stephen L.↗

Modeling Contamination Migration on the Chandra X-ray Observatory II

During its first 14 years of operation, the cold (about ‐60degC) optical blocking filter of the Advanced CCD Imaging Spectrometer (ACIS), aboard the Chandra X‐ray Observatory, has accumulated a growing layer of molecular contamination that attenuates low‐energy x rays. Over the past few years, the accumulation rate, spatial distribution, and composition may have changed, perhaps partially related to changes in the operating temperature of the ACIS housing. This evolution of the accumulation of the molecular contamination has motivated further analysis of contamination migration on the Chandra X‐ray Observatory, particularly within and near the ACIS cavity. To this end, the current study employs a higher‐fidelity geometric model of the ACIS cavity, detailed thermal modeling based upon monitored temperature data, and an accordingly refined model of the molecular transport.

O'Dell, Stephen L.↗

Modeling Contamination Migration on the Chandra X-ray Observatory II

During its first 14 years of operation, the cold (about ‐60degC) optical blocking filter of the Advanced CCD Imaging Spectrometer (ACIS), aboard the Chandra X‐ray Observatory, has accumulated a growing layer of molecular contamination that attenuates low‐energy x rays. Over the past few years, the accumulation rate, spatial distribution, and composition may have changed, perhaps partially related to changes in the operating temperature of the ACIS housing. This evolution of the accumulation of the molecular contamination has motivated further analysis of contamination migration on the Chandra X‐ray Observatory, particularly within and near the ACIS cavity. To this end, the current study employs a higher‐fidelity geometric model of the ACIS cavity, detailed thermal modeling based upon monitored temperature data, and an accordingly refined model of the molecular transport.

O'Dell, Steve↗

Aircraft-Measured Indirect Cloud Effects from Biomass Burning Smoke in the Arctic and Subarctic

The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300% over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were approx. 40- 60% smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq)/ and various biomass burning tracers (BBt/ across the multi-campaign data set, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACIs, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be approx. 0.16 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/cu m and very high aerosol concentrations (2000- 3000/ cu cm in the most polluted clouds, the estimated ACI value was only 0.05. In this case, competition for water vapor by the high concentration of cloud condensation nuclei (CCN) strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease local summertime short-wave radiative flux by between 2 and 4 W/sq m or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic.We lastly explore evidence suggesting that numerous northern-latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei.

cloud microphysics↗

Aircraft-Measured Indirect Cloud Effects from Biomass Burning Smoke in the Arctic and Subarctic

The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300 over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were 50 smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq))/ and various biomass burning tracers (BBt/ across the multi-campaign dataset, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACI, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be 0.12 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/ cu m) and very high aerosol concentrations (2000-3000 cu m) in the most polluted clouds, the estimated ACI value was only 0.06. In this case, competition for water vapor by the high concentration of CCN strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease shortwave radiative flux by 2 and 4 W/sq or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic. We lastly show evidence to suggest that numerous northern latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei. However, the influence of background particles on smoke-driven indirect effects is currently unclear.

Arctic↗

X-Ray Imaging Observations of the High-Mass γ-Ray Binary HESS J0632+057

The Chandra X-ray Observatory (CXO)imaged the high-massγ-ray binary (HMGB) HESS8J0632+057 with the Advanced CCD Imaging Spectrometer (ACIS). We analyzed the CXO data to-9gether with 967 ks of archival imaging Swift-XRT observations. On arcsecond scales we find a hint10of asymmetric extended emission. On arcminute scales, there is a region of extended emission (“the11blob”) which is located≈5.5′east of the binary. The blob is seen in both the CXO-ACIS and the12Swift-XRT images but it does not have a counterpart in the radio, NIR, IR, or optical images. The13ACIS spectrum of the blob fits either an absorbed power-law model with Γ'2.6, or a thermal plasma14model withkT'3 keV. Since the blob’s NH is significantly larger than that of the binary we conclude15that the blob and binary are not directly related. The somewhat larger very deep XRT image suggests16that the binary may be located within a shell (or cavity). The four ACIS spectra taken within the∼2017day interval near the light curve minimum suggests that the NH is varying on timescales of days, pos-18sibly due to the inhomogenous circumbinary environment. The XRT spectra extracted from the wider19orbital phase intervals support significant changes in NH near the light curve maximum/minimum,20which may be responsible for the substantial systematic residuals seen near 1 keV, and provide tenta-21tive evidence for a Fe line at 6.4 keV. We find no significant periodic signal in the ACIS data up to 0.156 Hz.

O Kargaltsev↗

Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models

The radiative forcing of anthropogenic aerosols associated with aerosol–cloud interactions (RF(sub aci)) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RF(sub aci), is generally simplified in climate models. Here we employ outputs from long-term (30-years) simulations of a global size-resolved (sectional) aerosol microphysics model and a machine-learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS-ModelE2.1 with a mass-based One-Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS-ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RF(sub aci) from −1.46 W⋅m(exp −2) to −1.11 W⋅m(exp −2). This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RF(sub aci) without compromising their computing efficiency.

Radiative forcing↗

Science and Science-Enabling Activities of the SHERLOC and WATSON Imaging Systems in Jezero Crater, Mars

During its first year of operation, the Perseverance rover explored the cratered and fractured floor of Jezero crater on Mars. Here, we report the use of the Scanning Habitability Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) imaging system that includes two high-resolution cameras, the Autofocus and Contextual Imager (ACI) and Wide Angle Topographic Sensor for Operations and eNgineering (WATSON). ACI is a fixed focus gray scale imager with a resolution of 10.1 μm/pixel whereas WATSON is a variable field of view, variable focus imager capable of resolution down to 14 μm/pixel. WATSON is a reflight of the MArs Hand Lens Imager (MAHLI) imager and has similar capabilities. During first-time activities, WATSON was used to support both science and engineering operations related to sample and abrasion patch assessment and sample collection and caching. WATSON also documented the deployment of the Ingenuity helicopter. The Crater Floor Campaign identified two primary rock units, the Máaz formation and the Séítah formation, which have been interpreted as lava flows and an olivine cumulate, respectively. Interpretation of rock textures with WATSON and ACI images was limited to abraded surfaces because unmodified outcrop surfaces (herein termed “natural surfaces”) show high degrees of dust covering, wind abrasion, and coating by secondary mineral products. WATSON and ACI images support the hypothesis that the material of both the Máaz and Séítah formations consists of largely aqueously altered mafic materials with varying igneous origins.

WATSON↗

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

Radiative Forcing of Nitrate Aerosols From 1975 to 2010 as Simulated by MOSAIC Module in CESM2-MAM4

In this work, we incorporate the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model Version 6 with interactive chemistry (CAM6-chem), and couple it with the four mode version of the Modal Aerosol Module (MAM4). The MOSAIC module is used to simulate the thermodynamics of the gas-aerosol mass exchange, with a special focus on simulating nitrate aerosol. By comparing against ground and satellite observations, we found that the MOSAIC/MAM4 scheme performs reasonably well in simulating spatiotemporal distributions of aerosols, including nitrate aerosol. We conducted a series of model experiments with and without nitrate aerosols, and examined the radiative effect (RE) associated with nitrate aerosols in 1975, 2000, and 2010, and accessed the radiative forcing (RF) of nitrate aerosols between the present day and pre-industrial periods. Comparing with the nitrate aerosol RE, we predicted relatively small RF of anthropogenic nitrate aerosol from aerosol-radiation interactions (RF ari : -0.014 W m -2 ) and large RF from aerosol-cloud interactions (RF aci : -0.219 W m -2 ). Regional signatures of nitrate RE/RF are noticeable and important: for instance, very small changes in RE ari in Europe and USA, but 2.8–3 times increases in RE ari in India and China from 1975 to 2010, while RE aci /RF aci in China is a warming effect due to the competing effect between sulfate and nitrate aerosols as cloud condensation nuclei.

54 ENVIRONMENTAL SCIENCES↗

The Amazon River‐Breeze Circulation Limits Detection of Aerosol‐Cloud Interactions in Warm Clouds

Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration ($N_d$) compared to adjacent land clouds. Thus, clouds above the river may appear polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that $N_d$ is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact $N_d$ as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.

Aerosol-Cloud Interactions↗