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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Climate Sensitivity and the Direct Effect of Carbon Dioxide in a Limited-Area Cloud-Resolving Model

Even in a small domain, it can be prohibitively expensive to run cloud-resolving greenhouse gas warming experiments due to the long equilibration time. Here, a technique is introduced that reduces the computational cost of these experiments by an order of magnitude: instead of fixing the carbon dioxide concentration and equilibrating the sea surface temperature (SST), this technique fixes the SST and equilibrates the carbon dioxide concentration. Using this approach in a cloud-resolving model of radiative–convective equilibrium (RCE), the equilibrated SST is obtained as a continuous function of carbon dioxide concentrations spanning 1 ppmv to nearly 10 000 ppmv, revealing a dramatic increase in equilibrium climate sensitivity (ECS) at higher temperatures. This increase in ECS is due to both an increase in forcing and a decrease in the feedback parameter. In addition, the technique is used to obtain the direct effects of carbon dioxide (i.e., the rapid adjustments) over a wide range of SSTs. Overall, the direct effect of carbon dioxide offsets a quarter of the increase in precipitation from warming, reduces the shallow cloud fraction by a small amount, and has no impact on convective available potential energy (CAPE).

Romps, David M.↗
NASA NTRS2018

Weak Hydrological Sensitivity to Temperature Change over Land, Independent of Climate Forcing

We present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from ten climate models, we show how modeled global mean precipitation increases by 2-3% per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature-driven (slow) ocean HS of 3-5%/K, while the slow land HS is only 0-2%/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. We identify a particular need for model investigations and observational constraints on convective precipitation in the Arctic, and large-scale precipitation around the Equator.

Samset, B. H.↗
NASA NTRS1985

Cloud optical thickness feedbacks in the CO2 climate problem

A radiative-convective equilibrium model is developed and applied to study cloud optical thickness feedbacks in the CO2 climate problem. The basic hypothesis is that in the warmer and moister CO2-rich atmosphere, cloud liquid water content will generally be larger than at present, so that cloud optical thickness will be larger too. For clouds other than thin cirrus, the result is to increase the albedo more than to increase the greenhouse effect. Thus the sign of the feedback is negative: cloud optical properties alter in such a way as to reduce the surface and tropospheric warming caused by the addition of CO2. This negative feedback can be substantial. When observational estimates of the temperature dependence of cloud liquid water content are employed in the model, the surface temperature change due to doubling CO2 is reduced by about one half.

Somerville, R. C. J.↗
NASA NTRS2004

Characterization of Individual Aerosol Particles Associated with Clouds (CRYSTAL-FACE)

The aim of our research was to obtain data on the chemical and physical properties of individual aerosol particles from near the bottoms and tops of the deep convective systems that lead to the generation of tropical cirrus clouds and to provide insights into the particles that serve as CCN or IN. We used analytical transmission electron microscopy (ATEM), including energy-dispersive X-ray spectrometry (EDS) and electron energy-loss spectroscopy (EELS), and field-emission electron microscopy (FESEM) to compare the compositions, concentrations, size distributions, shapes, surface coatings, and degrees of aggregation of individual particles from cloud bases and the anvils near the tropopause. Aggregates of sea salt and mineral dust, ammonium sulfate, and soot particles are abundant in in-cloud samples. Cirrus samples contain many H2SO4 droplets, but acidic sulfate particles are rare at the cloud bases. H2SO4 probably formed at higher altitudes through oxidation of SO2 in cloud droplets. The relatively high extent of ammoniation in the upper troposphere in-cloud samples appears to have resulted from vertical transport by strong convection. The morphology of H2SO4 droplets indicates that they had been at least yartiy ammoniated at the time of collection. They are internally mixed with organic materials, metal sulfates, and solid particles of various compositions. Ammoniation and internal mixing of result in freezing at higher temperature than in pure H2SO4 aerosols. K- and S-bearing organic particles and Si-Al-rich particles are common throughout. Sea salt and mineral dust were incorporated into the convective systems from the cloud bases and worked as ice nuclei while being vertically transported. The nonsulfate particles originated from the lower troposphere and were transported to the upper troposphere and lower stratosphere.

Buseck, Peter R.↗
DOE OSTI2024

Linear Time-Invariant Models of a Large Cumulus Ensemble

Abstract Methods in system identification are used to obtain linear time-invariant state-space models that describe how horizontal averages of temperature and humidity of a large cumulus ensemble evolve with time under small forcing. The cumulus ensemble studied here is simulated with cloud-system-resolving models in radiative–convective equilibrium. The identified models extend steady-state linear response functions used in past studies and provide accurate descriptions of the transfer function, the noise model, and the behavior of cumulus convection when coupled with two-dimensional gravity waves. A novel procedure is developed to convert the state-space models into an interpretable form, which is used to elucidate and quantify memory in cumulus convection. The linear problem studied here serves as a useful reference point for more general efforts to obtain data-driven and interpretable parameterizations of cumulus convection.

Meteorology & Atmospheric Sciences↗
DOE OSTI2026

Pinned Clouds over Industrial Sources of Heat during TRACER

An analysis of stereo-camera data from the Tracking Aerosol Convection Interactions Experiment (TRACER) campaign in Houston, Texas, reveals the existence of pinned clouds sitting atop industrial heat sources. These are not plumes of vapor and condensate emanating from stacks: The pinned shallow cumuli have cloud bases at about the lifting condensation of near-surface air. On many mornings, the pinned clouds are the only shallow cumuli in the field of view of the stereo cameras, persisting by themselves for at least an hour. On those mornings, the lower atmosphere straddles the boundary between stable and unstable, and the waste heat from industrial facilities is able to pin moist convection overhead. When solar heating of the surface becomes sufficient later in the morning, those mornings transition to having widespread shallow moist convection. Occurring within the field of view of the stereo cameras and other TRACER instruments, these pinned clouds represent steady plume-like moist convection triggered by known heat sources in a well-characterized atmosphere, making them a rich target for further study. Significance Statement This article introduces steady-state cumulus clouds observed during the Tracking Aerosol Convection Interactions Experiment (TRACER) campaign that were pinned to industrial heat sources. These pinned clouds were present in the early morning only when conditions were primed for moist convection, but for which there was not yet enough solar heating to trigger widespread convection. They persist in a statistical steady state and therefore provide a natural setting to explore the mechanisms controlling convective dynamics, which play a central role in Earth’s atmospheric circulation and radiative balance.

Atmosphere↗
DOE OSTI2025

TRACER-iso Field Campaign Report

The TRACER-iso project took place from June 1 to September 30, 2022, as part of the intensive operational period (IOP) of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s TRacking Aerosol Convection interactions ExpeRiment (TRACER) at the main project site at the La Porte, Texas, municipal airport. The project sought to use measurements of the stable isotopic composition of water vapor to better understand cloud-aerosol interactions in deep convection in a polluted urban setting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Water vapor isotopic composition during TRACER IOP

The TRACER-Iso project took place from June 1 to September 30, 2022 as part of the intensive observation period (IOP) of the Tracking Aerosol Convection Interactions (TRACER) project at the main project site at the La Porte, Texas, municipal airport. The project sought to use measurements of the stable isotopic composition of water vapor to better understand cloud-aerosol interactions in deep convection in a polluted urban setting. Water vapor isotopologue and humidity measurements were determined using a Picarro L2130 Water Vapor Isotope Analyzer. The instrument was deployed in the guest van and consists of three main components: a water vapor isotope analyzer, and a Los Gatos Research Water Vapor Isotope Standard Source (WVISS), and a Los Gatos Research Dry Air Source. Ambient air samples were collected through an inlet located about one meter above roof of the shipping container. Samples were then delivered to the analyzer through teflon tubing by use of an external pump to minimize the transport time between the inlet and analyzer. The inlet tubing was surrounded by a Briskheat heat trace and insulating material to ensure ambient air samples did not fall below the dew point and result in condensation. The analyzer uses cavity ringdown spectroscopy to report isotopic ratios of ambient air samples at a frequency of 1 Hz. The calibration unit of the instrument was used in conjunction with the dry air source to periodically measure the δ values of standard waters. It uses a nebulizer to push small water droplets into a hot chamber that vaporizes the water without fractionation. This vapor was then transported to the analyzer using a built-in compressor and the dry air source, which allows each standard with known δ values to be measured at a wide range of humidity values for post-measurement calibration of ambient air samples. There are multiple sources of uncertainty introduced at different stages during the data collection and processing. These include (1) instrument precision, (2) uncertainty in the secondary standards, (3) humidity-correction uncertainty, and (4) VSMOW-SLAP calibration uncertainty. Uncertainty from each step is propagated in quadrature to calculate a total uncertainty of each isotopologue. Uncertainty was determined to be 2.3‰ for δD and 0.4‰ for δ18O.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Tao, W. K.↗
NASA NTRS1995

Lidar measurements of boundary layers, aerosol scattering and clouds during project FIFE

A detailed account of progress achieved under this grant funding is contained in five journal papers. The titles of these papers are: The calculation of area-averaged vertical profiles of the horizontal wind velocity using volume imaging lidar data; Volume imaging lidar observation of the convective structure surrounding the flight path of an instrumented aircraft; Convective boundary layer mean depths, cloud base altitudes, cloud top altitudes, cloud coverages, and cloud shadows obtained from Volume Imaging Lidar data; An accuracy analysis of the wind profiles calculated from Volume Imaging Lidar data; and Calculation of divergence and vertical motion from volume-imaging lidar data. Copies of these papers form the body of this report.

Eloranta, Edwin W.↗
NASA NTRS2017

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

MAIAC AO↗
NASA NTRS2016

The Response of Phanerozoic Surface Temperature to Variations in Atmospheric Oxygen Concentration

Recently, Poulsen et al. (2015) suggested that O2 has played a major role in climate forcing during the Phanerozoic. Specifically, they argued that decreased O2 levels during the Cenomanian stage of the middle Cretaceous (94–100 Ma) could help explain the extremely warm climate during that time. The postulated warming mechanism involves decreased Rayleigh scattering by a thinner atmosphere, which reduces the planetary albedo and allows greater surface warming. This warming effect is then amplified by cloud feedbacks within their 3-D climate model. This increase in shortwave surface forcing, in their calculations, exceeds any decrease in the greenhouse effect caused by decreased O2. Here we use a 1-D radiative-convective climate model (with no cloud feedback) to check their results. We also include a self-consistent calculation of the change in atmospheric ozone and its effect on climate. Our results are opposite to those of Poulsen et al.: we find that the climate warms by 1.4 K at 35% O2 concentrations as a result of increased pressure broadening of CO2 and H2O absorption lines and cools by 0.8 K at 10% O2 as a result of decreased pressure broadening. The surface temperature changes are only about 1 K either way, though, for reasonable variations in Phanerozoic O2 concentrations (10%–35% by volume). Hence, it seems unlikely that changes in atmospheric O2 account for the warm climate of the Cenomanian. Other factors, such as a higher-than-expected sensitivity of climate to increased CO2 concentrations, may be required to obtain agreement with the paleoclimate data.

Atmospheric O2 levels↗
NASA NTRS2016

Simplified ISCCP Cloud Regimes for Evaluating Cloudiness in CMIP5 Models

We take advantage of the ISCCP simulator implemented in many CMIP5 models, in order to introduce a credible method to compare model cloud output with corresponding ISCCP observations based on the cloud regime (CR) concept. A novel simplified CR derivation method is introduced that exploits the co-variations of three variables, cloud optical thickness, cloud top pressure and cloud fraction (, pc, CF). Following evaluation criteria established in a previous paper of ours, we assess model cloud simulation performance based on how well the simplified CRs are simulated in terms of similarity of centroids, global values and map correlations of relative frequency-of-occurrence (RFO), and long term total clouds amounts (as opposed to average instantaneous cloud fractions). Mirroring prior results, modeled clouds tend to be too thick optically and not as extensive as in observations. Averaging across models does not help in this or other evaluation aspects, except for cloud geographical locations. A good model for one criterion is usually found to be also a good performer for other criteria despite plenty of exceptions for the criterion of centroid similarity. On the other hand, CRs that include convectively generated high-altitude clouds are not as well simulated here compared to the previous study, but other regimes containing low clouds with high CF improve. Models that have previously performed well distinguish themselves again here, but improvements from other models are also found. The simplified cloud evaluation method thus proves to be more forgiving while still good enough to reveal model weaknesses.

global climate models↗
NASA NTRS2010

Mechanisms of Diurnal Precipitation over the United States Great Plains: A Cloud-Resolving Model Simulation

The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.

Lee, M.-I.↗
DOE OSTI2021

Investigating the Causes and Impacts of Convective Aggregation in a High Resolution Atmospheric GCM

Abstract A ∼50 km resolution atmospheric general circulation model (GCM) is used to investigate the impact of radiative interactions on spatial organization of convection, the model's mean state, and extreme precipitation events in the presence of realistic boundary conditions. Mechanism‐denial experiments are performed in which synoptic‐scale feedbacks between radiation and dynamics are suppressed by overwriting the model‐generated atmospheric radiative cooling rates with its monthly varying climatological values. When synoptic‐scale radiative interactions are disabled, the annual mean circulation and precipitation remain almost unchanged, however tropical convection becomes less aggregated, with an increase in cloud fraction and relative humidity in the free troposphere but a decrease in both variables in the boundary layer. Changes in cloud fraction and relative humidity in the boundary layer exhibit more sensitivity to the presence of radiative interactions than variations in the degree of aggregation. The less aggregated state is associated with a decrease in the frequency of extreme precipitation events, coincident with a decrease in the dynamical contribution to the magnitude of extreme precipitation. At regional scales, the spatial contrast in radiative cooling between dry and moist regions diminishes when radiative interactions are suppressed, reducing the upgradient transport of energy, degree of aggregation, and frequency of extreme precipitation events. However, the mean width of the tropical rain belt remains almost unaffected when radiative interactions are disabled. These results offer insights into how radiation‐circulation coupling affects the spatial organization of convection, distributions of clouds and humidity, and weather extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

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

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

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

The Airborne Cloud-Aerosol Transport System: Overview and Description of the Instrument and Retrival Algorithms - Part I

The Airborne Cloud-Aerosol Transport System (ACATS) is a multi-channel Doppler lidar system recently developed at NASA Goddard Space Flight Center (GSFC). A unique aspect of the multi-channel Doppler lidar concept such as ACATS is that it is also, by its very nature, a high spectral resolution lidar (HSRL). Both the particulate and molecular scattered signal can be directly and unambiguously measured, allowing for direct retrievals of particulate extinction. ACATS is therefore capable of simultaneously resolving the backscatterextinction properties and motion of a particle from a high altitude aircraft. ACATS has flown on the NASA ER-2 during test flights over California in June 2012 and science flights during the Wallops Airborne Vegetation Experiment (WAVE) in September 2012. This paper provides an overview of the ACATS method and instrument design, describes the ACATS retrieval algorithms for cloud and aerosol properties, and demonstrates the data products that will be derived from the ACATS data using initial results from the WAVE project. The HSRL retrieval algorithms developed for ACATS have direct application to future spaceborne missions such as the Cloud-Aerosol Transport System (CATS) to be installed on the International Space Station (ISS). Furthermore, the direct extinction and particle wind velocity retrieved from the ACATS data can be used for science applications such 27 as dust or smoke transport and convective outflow in anvil cirrus clouds.

HSRL↗