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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Case Studies of Aerosol Remote Sensing in the Vicinity of Clouds

Studying the spatial variability of aerosol properties in the vicinity of clouds is essential to our ability to determine aerosol direct and indirect effects on climate. In this paper, we describe aerosol observations collected near cloud edges by an airborne Sun photometer over dark ocean waters. Focusing on case studies of aerosol measurements near eight cloud edges within a dissipating stratiform cloud deck, we compare the airborne Sun photometer observations to retrievals of aerosol properties using the standard Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol algorithm applied to 500-m-resolution MODIS spectral reflectances. We find a persistent, spectrally neutral increase in the Sun photometer-derived aerosol optical depth (AOD) of up to 10% (0.015) in the 2-km distances closest to the edges of several distinct clouds. At midvisible wavelengths, the MODIS AOD retrievals show similar increases toward cloud edges, although a larger increase in AOD is found in the MODIS along-scan direction. At shortwave infrared (SWIR) wavelengths (1240-2130 nm), the MODIS-derived AOD increases near cloud edges are of the order of 0.03 and as such three times as large as the Sun photometer-derived values. Hence, in contrast to recently discussed bluing of aerosols near cloud edges, i.e., a preferential apparent increase in the visible reflectances of clear-sky pixels due to 3-D radiative transfer effects in the vicinity of clouds, we find a reddening of aerosols in the MODIS 500-m-resolution aerosol retrievals near clouds. This reddening in our study can be traced to larger absolute increases in SWIR reflectances when compared to visible reflectances near clouds, which in turn seem to stem from larger electronic cross talk in the MODIS SWIR bands (5-7). We note that the lack of bluing in our MODIS observations is likely due to the small geometric and optical thicknesses of the clouds considered.

Redemann, Jens↗
NASA NTRS2014

Combined Dust Detection Algorithm by Using MODIS Infrared Channels over East Asia

A new dust detection algorithm is developed by combining the results of multiple dust detectionmethods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTDmethods have limitations in identifying the offset values of the BTDto discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10 × 10 pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia.

East Asia↗
NASA NTRS2014

Detecting Super-Thin Clouds With Polarized Light

We report a novel method for detecting cloud particles in the atmosphere. Solar radiation backscattered from clouds is studied with both satellite data and a radiative transfer model. A distinct feature is found in the angle of linear polarization of solar radiation that is backscattered from clouds. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when clouds are present, this electric field can rotate significantly away from the parallel direction. Model results demonstrate that this polarization feature can be used to detect super-thin cirrus clouds having an optical depth of only ~0.06 and super-thin liquid water clouds having an optical depth of only ~0.01. Such clouds are too thin to be sensed using any current passive satellite instruments.

Sun, Wenbo↗
NASA NTRS2013

Sensitivity of Downward Longwave Surface Radiation to Moisture and Cloud Changes in a High-elevation Region

Several studies have suggested enhanced rates of warming in high-elevation regions since the latter half of the twentieth century. One of the potential reasons why enhanced rates of warming might occur at high elevations is the nonlinear relationship between downward longwave radiation (DLR) and specific humidity (q). Using ground-based observations at a high-elevation site in southwestern Colorado and coincident satellite-borne cloud retrievals, the sensitivity of DLR to changes in q and cloud properties is examined and quantified using a neural network method. It is also used to explore how the sensitivity of DLR to q (dDLR/dq) is affected by cloud properties. When binned by season, dDLR/dq is maximum in winter and minimum in summer for both clear and cloudy skies. However, the cloudy-sky sensitivities are smaller, primarily because (1) for both clear and cloudy skies dDLR/dq is proportional to 1/q, for q>0.5 g/kg, and (2) the seasonal values of q are on average larger in the cloudy-sky cases than in clear-sky cases. For a given value of q, dDLR/dq is slightly reduced in the presence of clouds and this reduction increases as q increases. In addition, DLR is found to be more sensitive to changes in cloud fraction when cloud fraction is large. In the limit of overcast skies, DLR sensitivity to optical thickness decreases as clouds become more opaque. These results are based on only one high-elevation site, so the conclusions here need to be tested at other high-elevation locations.

cloud physics↗
NASA NTRS2014

Extending 3D Near-Cloud Corrections from Shorter to Longer Wavelengths

Satellite observations have shown a positive correlation between cloud amount and aerosol optical thickness (AOT) that can be explained by the humidification of aerosols near clouds, and/or by cloud contamination by sub-pixel size clouds and the cloud adjacency effect. The last effect may substantially increase reflected radiation in cloud-free columns, leading to overestimates in the retrieved AOT. For clear-sky areas near boundary layer clouds the main contribution to the enhancement of clear sky reflectance at shorter wavelengths comes from the radiation scattered into clear areas by clouds and then scattered to the sensor by air molecules. Because of the wavelength dependence of air molecule scattering, this process leads to a larger reflectance increase at shorter wavelengths, and can be corrected using a simple two-layer model. However, correcting only for molecular scattering skews spectral properties of the retrieved AOT. Kassianov and Ovtchinnikov proposed a technique that uses spectral reflectance ratios to retrieve AOT in the vicinity of clouds; they assumed that the cloud adjacency effect influences the spectral ratio between reflectances at two wavelengths less than it influences the reflectances themselves. This paper combines the two approaches: It assumes that the 3D correction for the shortest wavelength is known with some uncertainties, and then it estimates the 3D correction for longer wavelengths using a modified ratio method. The new approach is tested with 3D radiances simulated for 26 cumulus fields from Large-Eddy Simulations, supplemented with 40 aerosol profiles. The results showed that (i) for a variety of cumulus cloud scenes and aerosol profiles over ocean the 3D correction due to cloud adjacency effect can be extended from shorter to longer wavelengths and (ii) the 3D corrections for longer wavelengths are not very sensitive to unbiased random uncertainties in the 3D corrections at shorter wavelengths.

aerosol optical depth↗
NASA NTRS2014

Retrieval of Aerosol Optical Properties under Thin Cirrus from MODIS

Retrieval of aerosol optical properties using shortwave bands from passive satellite sensors, such as MODIS, is typically limited to cloud-free areas. However, if the clouds are thin enough (i.e. thin cirrus) such that the satellite-observed reflectance contains signals under the cirrus layer, and if the optical properties of this cirrus layer are known, the TOA reflectance can be corrected for the cirrus layer to be used for retrieving aerosol optical properties. To this end, we first correct the TOA reflectances in the aerosol bands (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 micron for ocean algorithm and 0.412, 0.47, and 0.65 micron for deep blue algorithm) for the effects of thin cirrus using 1.38 micron reflectance and conversion factors that convert cirrus reflectance in 1.38 micron band to those in aerosol bands. It was found that the conversion factors can be calculated by using relationships between reflectances in 1.38 micron band and minimum reflectances in the aerosol bands (Gao et al., 2002). Refer to the example in the figure. Then, the cirrus-corrected reflectance can be calculated by subtracting the cirrus reflectance from the TOA reflectance in the optically thin case. A sensitivity study suggested that cloudy-sky TOA reflectances can be calculated with small errors in the form of simple linear addition of cirrus-only reflectances and clear-sky reflectances. In this study, we correct the cirrus signals up to TOA reflectance at 1.38 micron of 0.05 where the simple linear addition is valid without extensive radiative transfer simulations. When each scene passes the set of tests shown in the flowchart, the scene is corrected for cirrus contamination and passed into aerosol retrieval algorithms.

MODIS↗
NASA NTRS2014

A Regional CO2 Observing System Simulation Experiment for the ASCENDS Satellite Mission

Top-down estimates of the spatiotemporal variations in emissions and uptake of CO2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO2 measurement platforms. In particular, the planned NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO2 fluxes, we use a portable library of footprints (surface influence functions) generated by the WRF-STILT Lagrangian transport model in a regional Bayesian synthesis inversion. The regional Lagrangian framework is well suited to make use of ASCENDS observations to constrain fluxes at high resolution, in this case at 1 degree latitude x 1 degree longitude and weekly for North America. We consider random measurement errors only, modeled as a function of mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the 1 degree x 1 degree, weekly scale, the largest uncertainty reductions, on the order of 50 percent, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large. Uncertainty reductions are smaller for a 1.57 micron candidate wavelength than for a 2.05 micron wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual, biome scale range from 40 percent to 75 percent across our four instrument design cases, and from 65 percent to 85 percent for the continent as a whole. Our uncertainty reductions at various scales are substantially smaller than those from a global ASCENDS inversion on a coarser grid, demonstrating how quantitative results can depend on inversion methodology. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr-1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.

remote sensing↗
NASA NTRS2014

Far-Reaching Impacts of African Dust- A Calipso Perspective

African dust can transport across the tropical Atlantic and reach the Amazon basin, exerting far-reaching impacts on climate in downwind regions. The transported dust influences the surface-atmosphere interactions and cloud and precipitation processes through perturbing the surface radiative budget and atmospheric radiative heating and acting as cloud condensation nuclei and ice nuclei. Dust also influences biogeochemical cycle and climate through providing nutrients vital to the productivity of ocean biomass and Amazon forests. Assessing these climate impacts relies on an accurate quantification of dust transport and deposition. Currently model simulations show extremely large diversity, which calls for a need of observational constraints. Kaufman et al. (2005) estimated from MODIS aerosol measurements that about 144 Tg of dust is deposited into the tropical Atlantic and 50 Tg of dust into the Amazon in 2001. This estimated dust import to Amazon is a factor of 3-4 higher than other observations and models. However, several studies have argued that the oversimplified characterization of dust vertical profile in the study would have introduced large uncertainty and very likely a high bias. In this study we quantify the trans-Atlantic dust transport and deposition by using 7 years (2007-2013) observations from CALIPSO lidar. CALIPSO acquires high-resolution aerosol extinction and depolarization profiles in both cloud-free and above-cloud conditions. The unique CALIPSO capability of profiling aerosols above clouds offers an unprecedented opportunity of examining uncertainties associated with the use of MODIS clear-sky data. Dust is separated from other types of aerosols using the depolarization measurements. We estimated that on the basis of 7-year average, 118142 Tg of dust is deposited into the tropical Atlantic and 3860 Tg of dust into the Amazon basin. Substantial interannual variations are observed during the period, with the maximum to minimum ratio of about 1.6 and 2.5 for the deposition to the tropical Atlantic and Amazon, respectively. The MODIS-based estimates appear to fall within the range of CALIPSO-based estimates; and the difference between MODIS and CALIPSO estimates can be largely attributed to the interannual variability, which is corroborated by long-term surface dust concentration observations in the tropical Atlantic. Considering that CALIPSO generally tends to underestimate the aerosol loading, our estimate is likely to represent a low bound for the dust transport and deposition estimate. The finding suggests that models have substantial biases and considerable effort is needed to improve model simulations of dust cycle.

dust↗
NASA NTRS2014

Detecting Super-Thin Clouds with Polarized Sunlight

We report a novel method for detecting cloud particles in the atmosphere. Solar radiation backscattered from clouds is studied with both satellite data and a radiative transfer model. A distinct feature is found in the angle of linear polarization of solar radiation that is backscattered from clouds. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when clouds are present, this electric field can rotate significantly away from the parallel direction. Model results demonstrate that this polarization feature can be used to detect super-thin cirrus clouds having an optical depth of only ~0.06 and super-thin liquid water clouds having an optical depth of only ~0.01. Such clouds are too thin to be sensed using any current passive satellite instruments.

Aerosols and particles↗
NASA NTRS2014

Method for Ground-to-Space Laser Calibration System

The present invention comprises an approach for calibrating the sensitivity to polarization, optics degradation, spectral and stray light response functions of instruments on orbit. The concept is based on using an accurate ground-based laser system, Ground-to-Space Laser Calibration (GSLC), transmitting laser light to instrument on orbit during nighttime substantially clear-sky conditions. To minimize atmospheric contribution to the calibration uncertainty the calibration cycles should be performed in short time intervals, and all required measurements are designed to be relative. The calibration cycles involve ground operations with laser beam polarization and wavelength changes.

Lukashin, Constantine↗
NASA NTRS2014

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

surface concentration↗
NASA NTRS2015

Method for Ground-to-Satellite Laser Calibration System

The present invention comprises an approach for calibrating the sensitivity to polarization, optics degradation, spectral and stray light response functions of instruments on orbit. The concept is based on using an accurate ground-based laser system, Ground-to-Space Laser Calibration (GSLC), transmitting laser light to instrument on orbit during nighttime substantially clear-sky conditions. To minimize atmospheric contribution to the calibration uncertainty the calibration cycles should be performed in short time intervals, and all required measurements are designed to be relative. The calibration cycles involve ground operations with laser beam polarization and wavelength changes.

Lukashin, Constantine↗
NASA NTRS2015

Next-Generation Angular Distribution Models for Top-of-Atmosphere Radiative Flux Calculation from the CERES Instruments: Methodology

The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance, radiative effects of clouds and aerosols, and climate feedback. The Clouds and the Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation ADMs that are developed for Terra and Aqua using all available CERES rotating azimuth plane radiance measurements. Coincident cloud and aerosol retrievals, and radiance measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from Goddard Earth Observing System (GEOS) data assimilation version 5.4.1 are used to define scene type. CERES radiance measurements are stratified by scene type and by other parameters that are important for determining the anisotropy of the given scene type. Anisotropic factors are then defined either for discrete intervals of relevant parameters or as a continuous functions of combined parameters, depending on the scene type. Significant differences between the ADMs described in this paper and the existing ADMs are over clear-sky scene types and polar scene types. Over clear ocean, we developed a set of shortwave (SW) ADMs that explicitly account for aerosols. Over clear land, the SW ADMs are developed for every 1 latitude1 longitude region for every calendar month using a kernel-based bidirectional reflectance model. Over clear Antarctic scenes, SW ADMs are developed by accounting the effects of sastrugi on anisotropy. Over sea ice, a sea-ice brightness index is used to classify the scene type. Under cloudy conditions over all surface types, the longwave (LW) and window (WN) ADMs are developed by combining surface and cloud-top temperature, surface and cloud emissivity, cloud fraction, and precipitable water. Compared to the existing ADMs, the new ADMs change the monthly mean instantaneous fluxes by up to 5Wm(exp -2) on a regional scale of 1 deg. latitude x 1 deg. longitude, but the flux changes are less than 0.5Wm(exp -2) on a global scale.

Su, W.↗
NASA NTRS2015

Assimilation of Precipitation Measurement Missions Microwave Radiance Observations With GEOS-5

The Global Precipitation Mission (GPM) Core Observatory satellite was launched in February, 2014. The GPM Microwave Imager (GMI) is a conically scanning radiometer measuring 13 channels ranging from 10 to 183 GHz and sampling between 65 S 65 N. This instrument is a successor to the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), which has observed 9 channels at frequencies ranging 10 to 85 GHz between 40 S 40 N since 1997. This presentation outlines the base procedures developed to assimilate GMI and TMI radiances in clear-sky conditions, including quality control methods, thinning decisions, and the estimation of, observation errors. This presentation also shows the impact of these observations when they are incorporated into the GEOS-5 atmospheric data assimilation system.

GPM/GMI↗
NASA NTRS2016

Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

polar-orbiting↗
NASA NTRS2016

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

MAIAC↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11084-DND

The solar radiation must be considered as the primary factor when we study the climatic system because it provides almost all energy that drives the climatic system and most atmospheric phenomena. The solar radiation at the TOA is partially transferred, transformed into other forms of energy that are eventually dissipated by the general circulation of the atmosphere and oceans, and partially used in chemical and biological processes. The absorption of solar energy in the atmosphere (Acol) plays a key role in the climate system, not only because it affects the amount of solar energy absorbed by the Earth system, but also because it changes the vertical distribution of absorbed energy, which in turn impacts surface evaporation, atmospheric convection and precipitation. To investigate Acol, we have collected the collocated satellite-surface observations over the 35 selected BSRN surface sites during the period 2000-2004. The surface radiation budgets are averaged from the BSRN Shortwave (SW) observations over a 1-hour interval centered at the time of the NASA Terra and Aqua satellites overpass, and the TOA radiation budgets are averaged from the closest FOV satellite data to the BSRN stations. Then the atmospheric column SW absorption will be inferred from the satellite TOA albedo and BSRN surface absorption (through the estimated surface albedo). Monthly means of Acol, TOA albedo, and surface absorption have been calculated under both clear- and all-sky conditions over the 35 selected BSRN sites which represent different climate regimes. To evaluate the GCM simulations, we have collected the ECHAM5-HAM simulated surface, TOA and atmospheric radiation budgets by researchers at ETH Zurich and compared those simulations with observations. The preliminary comparisons have shown that the ECHAM5 simulated clear-sky surface absorption, TOA albedo, and ACOL agree very well (1-3%) with observations. Under all-sky conditions, they have strong correlations with CERES-derived cloud fraction. The simulated surface absorption is lower and TOA albedo is higher than those under clear skies, but ACOL does not increase too much. However, there are relatively large differences over some regions and months. A further study is needed.

X. Dong↗
DOE OSTI2026

E3SMv3 ‘Nephele’ Perturbed Parameter Ensemble Value-Added Product for ENA, SGP, NSA, and Global Means

Processed output from the E3SMv3 Nephele perturbed parameter ensemble (PPE). This product contains global means of present-day (using 2010 aerosol forcings) and preindustrial (using 1850 aerosol forcings) monthly and daily global-mean quantities, as well as hourly mean quantities at the E3SMv3 model grid cell closest to the ENA, SGP, and NSA ARM sites. In this PPE, the E3SMv3 model was run for 27 months in an atmosphere-only configuration with free tropospheric winds nudged to reanalysis. Each ensemble member represents a unique combination of 25 model parameter values (in the microphysics, convective microphysics, and aerosol schemes) that were perturbed randomly and simultaneously. The E3SMv3 default configuration is included as member 0. See https://doi.org/10.22541/essoar.174907165.57104591/v1 (in review) for more information on the Nephele PPE and the perturbed parameters.

Model atmospheric temperature↗