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

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assessing the WRF-Solar Model Performance Using Satellite-Derived Irradiance from the National Solar Radiation Database

Abstract WRF-Solar is a numerical weather prediction model specifically designed to meet the increasing demand for accurate solar irradiance forecasting. The model provides flexibility in the representation of the aerosol–cloud–radiation processes. This flexibility can be argued to make it more difficult to improve the model’s performance because of the necessity of inspecting different configurations. To alleviate this situation, WRF-Solar has a reference configuration to use as a benchmark in sensitivity experiments. However, the scarcity of high-quality ground observations is a handicap to accurately quantify the model performance. An alternative to ground observations are satellite irradiance retrievals. Herein we analyze the adequacy of the National Solar Radiation Database (NSRDB) to validate the WRF-Solar performance using high-quality global horizontal irradiance (GHI) observations across the contiguous United States (CONUS). Based on the sufficient performance of NSRDB, we further analyze the WRF-Solar forecast errors across the CONUS, the growth of the forecasting errors as a function of the lead time, and sensitivities to the grid spacing and the representation of the radiative effects of unresolved clouds. Our results based on WRF-Solar forecasts spanning 2018 reveal a 7% median degradation of the mean absolute error (MAE) from the first to the second daytime period. Reducing the grid spacing from 9 to 3 km leads to a 4% improvement in the MAE, whereas activating the radiative effects of unresolved clouds is desirable over most of the CONUS even at 3 km of grid spacing. A systematic overestimation of the GHI is found. These results illustrate the potential of GHI retrievals to contribute to increasing the WRF-Solar performance.

14 SOLAR ENERGY↗
NASA NTRS2008

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. The following is presented in this report: (1) a brief review of the GCE model and its applications on the impact of aerosols on deep precipitation processes, (2) the Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) a discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗
NASA NTRS2010

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.

Tao, Wei-Kuo↗
NASA NTRS2010

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the ph ysical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

Tao, Wei-Kuo↗
DOE OSTI2025

Improving vertical detail in simulated temperature and humidity data using machine learning

Atmospheric models used for weather forecasting and climate predictions discretise the atmosphere onto a vertical grid. There are however atmospheric phenomena that occur on scales smaller than the thickness of those model layers. The formation of low-level clouds due to temperature inversions is an example. This leads to atmospheric models underestimating, or even missing, these clouds and their radiative effects. Using radiosonde observations as training data, a machine learning model is used to improve the vertical detail of modelled profiles of temperature and specific humidity. In addition, a physics-informed machine learning model is developed and compared to the traditional approach; showing improvements in the cloud fraction profiles calculated from its predictions. The vertically enhanced profiles also improve the representation of layers of convective inhibition and anomalous refractivity gradients. This work facilitates targeted improvements to the representation of certain atmospheric processes without the burden of increased memory and computational cost from increasing vertical resolution throughout the whole model.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Accuracy of the Independent Pixel Approximation at Absorbing Wavelengths

In order to correctly interpret shortwave cloud radiation measured by satellites and ground-based radiometers, or by two aircraft flying above and below clouds, we need to better understand interactions between inhomogeneous clouds and solar radiation. The discrepancies between shortwave absorption inferred from measurements and predicted by models, between cloud optical depths estimated from satellites and ground measurements, between single scattering albedo retrieved from in situ radiation measurements and computed from measured droplet size distribution, among others, are strongly affected by cloud horizontal inhomogeneity. Net horizontal photon transport (i. e., horizontal fluxes) are a direct consequence of the inhomoqeneity in cloud structure. Horizontal fluxes and their effect on the accuracy of the pixel-by-pixel one-dimensional (1 D) radiative transfer calculations has recently undergone close scrutiny for conservative scattering. However, the properties and magnitude of horizontal fluxes in absorbing wavelengths are still poorly understood. As far as we are aware, only Ackerman and Cox and Titov discussed correlations between horizontal fluxes at absorbing wavelengths, though these were far from comprehensive. This paper partly fills this gap. We discuss here of whether the accuracy of the Independent Pixel Approximation (IPA), a 1 D radiative transfer approximation for each pixel, is a better model for multiple scattering at conservative or at absorbing wavelengths. Issues addressed here are: (1) dependence of net horizontal fluxes on single scattering albedo; (2) connection between pixel-by-pixel accuracy of the IPA and horizontal fluxes and (3) radiative smoothing and horizontal fluxes at absorbing wavelengths. In contrast to the traditional understanding of IPA, we study IPA accuracies not only for reflectance but also for transmittance and absorptance at both conservative and absorbing wavelengths. In spite of the apparent similarity between the three processes, dependence of IPA accuracies on single-scattering albedo is completely different. As a result, cloud optical properties retrieved from high resolution satellite images and ground-based measurements using IPA at absorbing channels will have different accuracies.

Marchak, Alexander↗
DOE OSTI2022

Evidence for Secondary Ice Production in Southern Ocean Maritime Boundary Layer Clouds

Abstract Maritime boundary‐layer clouds over the Southern Ocean (SO) have a large shortwave radiative effect. Yet, climate models have difficulties in representing these clouds and, especially, their phase in this observationally sparse region. This study aims to increase the knowledge of SO cloud phase by presenting in‐situ cloud microphysical observations from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES). We investigate the occurrence of ice in summertime marine stratocumulus and cumulus clouds in the temperature range between 6 and −25°C. Our observations show that in ice‐containing clouds, maximum ice number concentrations of up to several hundreds per liter were found. The observed ice crystal concentrations were on average one to two orders of magnitude higher than the simultaneously measured ice nucleating particle (INP) concentrations in the temperature range below −10°C and up to five orders of magnitude higher than estimated INP concentrations in the temperature range above −10°C. These results highlight the importance of secondary ice production (SIP) in SO summertime marine boundary‐layer clouds. Evidence for rime splintering was found in the Hallett‐Mossop (HM) temperature range but the exact SIP mechanism active at lower temperatures remains unclear. Finally, instrument simulators were used to assess simulated co‐located cloud ice concentrations and the role of modeled HM rime‐splintering. We found that CAM6 is deficient in simulating number concentrations across the HM temperature range with little sensitivity to the model HM process, which is inconsistent with the aforementioned observational evidence of highly active SIP processes in SO low‐level clouds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES- Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
DOE OSTI2020

Contrasting aerosol effects on longwave cloud forcing in South East Asia and Amazon simulated with Community Atmosphere Model version 5.3

Aerosols modify cloud microphysical and radiative properties and thus impact the shortwave (SW) and longwave cloud forcing (LWCF). This study first reports the finding of contrasting aerosol effects on LWCF in South East Asia and Amazon in the Community Atmosphere Model version 5.3 (CAM5.3), which corresponds to the sum of LW indirect and semi-direct effects investigated in Ghan et al., (2012). A series of numerical experiments is conducted to decompose the complex aerosol effects on LWCF. Our analysis indicates that the cooling (negative aerosol effects on LWCF) in Amazon is due mainly to the aerosol effects on warm clouds and the inhibition of vertical motion by the aerosol-induced radiative cooling. In contrast, the warming (positive aerosol effects on LWCF) in South East Asia is due mainly to the aerosol effect on homogeneous freezing, thus reducing the ice particle size and prolonging the existence of ice cloud. Our results emphasize that a comprehensive analysis of integrated aerosol effects on both warm and ice clouds is necessary for better understanding the aerosol effects on LWCF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Final Technical Report

Southern Africa is the world’s largest emitter of biomass burning aerosols. Their westward transport over the remote southeast Atlantic ocean colocates some of the largest atmospheric loadings of absorbing aerosol with the least examined of the Earth’s major subtropical stratocumulus decks. Global aerosol model results highlight that the largest positive top-ofatmosphere forcing in the world occurs in the southeast Atlantic, but this region exhibits large differences in magnitude and sign between reputable models, in part because of high variability in the underlying model cloud distributions. Many uncertainties contribute to the highly variable model radiation fields: the aging of the shortwave-absorbing aerosol during transport, how much of the aerosol mixes into the cloudy boundary layer, and how the low clouds adjust to smokeradiation and smoke-cloud interactions. In addition, the ability of the biomass burning aerosol to absorb shortwave radiation is known to vary seasonally as the fuel type on land changes. LASIC (Layered Atlantic Smoke Interactions with Clouds) is a strategy to improve our understanding of aged carbonaceous aerosol, its seasonal evolution, and the mechanisms by which clouds adjust to the presence of the aerosol. The observational strategy centers on deploying the AMF1 cloud, aerosol, and atmospheric profiling instrumentation to Ascension Island, located within the trade-wind shallow cumulus regime (14.50W, 80S) 3000 km offshore of continental Africa. The location is within the latitude zone of the maximum outflow of aerosol, with the deepening boundary layer known to entrain free-tropospheric smoke. The primary activities for LASIC are: 1) to improve current knowledge on aged biomass burning aerosol and its radiative properties as a function of the seasonal cycle; 2) to use surface-based remote sensing to sensitively interrogate the atmosphere for the relative vertical location of aerosol and clouds; 3) to improve our understanding of the cloud adjustments to the presence of shortwave-absorbing aerosol within the vertical column, both through aerosol-radiation and through aerosol-cloud interactions; 4) to aid low cloud parameterization efforts for climate models. The measurements span June 1, 2016 - October 31, 2017, encompassing two July-October biomass burning seasons. The August-September, 2016, months include an Intensive Observing Period (IOP) with 8x/daily radiosondes. In 2017, from 16 August through 7 September, the UK FAAM Bae- 146 plane was deployed from Ascension, providing complementary data on the atmosphere’s vertical structure as part of the CLARIFY project, with similar scientific goals. The NASA ORACLES aircraft campaign, sharing similar objectives to LASIC, deployed from Namibia in September, 2016, and Sao Tome in August, 2017. The latter included a suitcase flight to Ascension spanning August 18-21. In 2017 a CAPS-SSA instrument belonging to Aerodyne was brought to Ascension, gathering data primarily for August, towards providing a second, independent measurement of aerosol absorption. Ascension Island is also an AERONET site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cloud radiative effect dominates variabilities of surface energy budget in the dark Arctic

Climate models simulate a wide range of temperatures in the Arctic. Here we investigate one of the main drivers of changes in surface temperature: the net surface heat flux in the models. We show that in the winter months of the dark Arctic, there is a more than two-fold difference in the net surface heat fluxes among the models, and this difference is dominated by the downward infrared radiation from clouds. Owing to the small amount of water vapor in the winter Arctic, infrared radiation from clouds transmits more easily to the surface in the Arctic than at other latitudes, resulting in large cloud radiative effect at the surface. The dominant role of the cloud effect is also found in the transient variability of the net surface heat flux. Results demonstrate that accurate simulation of clouds is crucial for determining the net surface heat flux, which in turn affects surface temperature and sea ice properties in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.↗
NASA NTRS1991

Sea ice - atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

In the past six months, work has continued on energy flux sensitivity studies, ice surface temperature retrievals, corrections to Advanced Very High Resolution Radiometer (AVHRR) thermal infrared data, modelling of cloud fraction retrievals, and radiation climatologies. We tentatively conclude that the SSM/I may not provide accurate enough estimates of ice concentration and type to improve our shorter term energy flux estimates. SSM/I derived parameters may still be applicable in longer term climatological flux characterizations. We hold promise for a system coupling observation to a ice deformation model. Such a model may provide information on ice distribution which can be used in energy flux calculations. Considerable variation was found in modelled energy flux estimates when bulk transfer coefficients are modulated by lead fetch. It is still unclear what the optimum formulation is and this will be the subject of further work. Data sets for ice surface temperature retrievals were assembled and preliminary data analysis was started. Finally, construction of a conceptual framework for further modelling of the Arctic radiation flux climatology was started.

Steffen, Konrad↗
NASA NTRS2006

First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm

We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds.

Joiner, Joanna↗
DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Longwave cloud radiative forcing at the surface from ISCCP-C1 data

A method for deriving one component of the total cloud forcing picture, namely, the LW cloud forcing at the surface, is presented. The method is based on a validated radiative transfer technique and utilizes meteorological data available from the International Satellite Cloud Climatology Project. The radiative transfer model used was validated earlier and the TOVS-derived temperature and water vapor data used were generally reasonable. On a monthly-average basis, random error was estimated to be in the 5-10 W/sq m range, but biases as large as 10-20 W/sq m can occur in some regions. The lack of information on cloud-base heights were found to be the largest source of errors in the models and the meteorological data.

Gupta, Shashi K.↗
DOE OSTI2020

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗