In the OSTI Collections: Clouds, Sunlight, and Radiant Heat

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Article Acknowledgement:
Dr. William N. Watson, Physicist
DOE Office of Scientific and Technical Information

 

Clouds and other aerosols

More about clouds

Plans for further investigations

References

Reports available through OSTI's SciTech Connect

Additional references

 

 

The sun radiates electromagnetic waves of every frequency into the space around it—much of it visible light, but also the higher frequencies of ultraviolet light, x-rays, and gamma rays, as well as the lower frequencies of infrared light, microwaves, and radio waves.  A small portion of all this radiation is intercepted by the earth.  The earth's atmosphere absorbs much of the short, higher frequency radiation beyond the far ultraviolet and a great deal of the long, lower frequency waves, but is somewhat transparent to infrared light and quite transparent to a broad range of microwave and radio frequencies and to visible light.[Wikipedia]  Radiation that the earth gets from the sun provides energy that plants photosynthesize food with, that eyes see with, and that the earth's weather is driven by. 

 

Meteorologists know enough about how electromagnetic radiation affects weather to compute detailed short-term forecasts and make some large-scale long-range predictions.  However, useful detailed prediction of climatic trends has required more information about the effects of these rays.  Some of the most significant information that was still missing in the late 1980s was how electromagnetic radiation affects, and is affected by, clouds.  To different degrees, different kinds of clouds reflect, transmit, scatter, or absorb the spectrum of frequencies they receive from the sun and the infrared light they get from the earth when its surface is warmed by the sun's rays.  The question was, what are the details of how all this electromagnetic radiation and the different kinds of clouds affect each other?  Find out, and you can better determine the course of the earth's climate. 

 

Because clouds can't be appropriately scaled down enough to get this kind of information from laboratory experiments, the Atmospheric Radiation Measurement (ARM) program was established to set up special monitoring stations to observe features of the atmosphere beyond the ones normally tracked to derive shorter-range forecasts.  Since the first of these research stations was dedicated in 1993, the program has collected huge amounts of numeric data to reduce the uncertainties in climate projections—enough to make a larger contribution of numeric data sets to the U. S. Department of Energy's Data Explorer than any other research program makes.  Reports about research based on this data also appear frequently, as can be seen by checking SciTech Connect for reports catalogued with the acronym "ARM". 

 

One of the earliest reports[SciTech Connect] described what the program's measuring instruments needed to support: 

"the measurement of key aspects of the radiation field under a range of climatologically significant meteorological conditions sufficient to constrain detailed radiative calculations;

"detailed studies of atmospheric trace gas, aerosol, and water-vapor distributions;

"detailed studies of meteorological variables, including cloud type and distribution, wind field, temperature, etc.;

"measurement of large-scale vertical velocities; and

"measurement of critical microphysical properties of clouds." 

 

To support these measurements in turn required "near real-time processing of data and execution of models" and "state-of-the-art calibration methods, including on-site calibration at facilities explicitly designed to support the measurement systems and redundant measurement suites providing near real-time evaluation of instrument performance".  A later report[SciTech Connect]describes how the ARM program's main scientific questions were described a few years after it started:
 

  1. "What are the direct effects of temperature and atmospheric constituents, particularly clouds, water vapor and aerosols on the radiative flow of energy through the atmosphere and across the Earth's surface?

  2. What is the nature of the variability of radiation and the radiative properties of the atmosphere on climatically relevant space and time scales?

  3. What are the primary interactions among the various dynamic, thermodynamic and radiative processes that determine the radiative properties of an atmospheric column, including clouds and the underlying surface?

  4. How do radiative processes interact with dynamical and hydrologic processes to produce cloud feedbacks that regulate climate change?"

That report goes on to tell how

 

"During its formative years, the program focused on site development, instrument development and procurement, and technique development both in atmospheric retrievals and model evaluation. Rapid and substantive progress in all these areas produced data streams and analyses that translated into new insights into physical processes in the atmosphere and improved modeling of these processes. This in turn fostered evaluations of current climate model parameterizations and development of new parameterizations. As a result, the current ARM Program emphasis is on understanding and modeling fundamental cloud and radiation process and parameterization development and testing for climate models."

While much has been learned since then about how clouds interact with electromagnetic waves, much remains to be understood.  The newest reports from the program provide a look at researchers' most recent findings and their current questions. 

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Clouds and other aerosols

 

Perhaps aerosol sprays are the most familiar suspensions of solid or liquid particles in a gas that are commonly referred to as aerosols, but many natural aerosols also exist, including the particles that water droplets in clouds condense on.[Wikipedia]  (Indeed, clouds themselves are aerosols by this definition, but climatology reports typically use the term "aerosol" for suspensions other than clouds.)  The aerosols that cloud droplets condense on, and the updrafts at the bases of clouds, both affect the flow of electromagnetic radiation from the sun to the earth and from the earth into outer space—particularly the difference between these energy flows, which is known as "radiative forcing" or "climate forcing"[Wikipedia].  Earlier measurement techniques couldn't distinguish the separate effects of the updrafts and the solid particles, however, so quantifying the effects had been greatly impeded.  Beginnings of a way to disentangle the two effects has come with the use of weather satellites that orbit the earth's poles and estimate the updraft velocity and number of cloud droplets at the bases of clouds.  The estimation method, and how the estimates are used, are described in the report "Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings"[SciTech Connect]. 

 

 

Figure 1.  Application of the methodology described in the report "Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings"[SciTech Connect] to the Houston area. The retrieval is done with the Visible/Infrared Imager Radiometer Suite[Wikipedia] aboard the Suomi NPP satellite[Wikipedia] for a regular grid of 75 pixels x 75 pixels having 375-meter resolution per pixel. The numbers in each area are, top: cloud condensation nuclei per cubic centimeter, middle: cloud-base supersaturation in percent, bottom: cloud base temperature in degrees Celsius. Unstable clean tropical air mass flows northward (upward in the image) from the Gulf of Mexico. The Houston urban effect is clearly visible by more than tripling the cloud condensation nuclei concentrations over Houston while reducing cloud-base supersaturation to less than half. This represents an even much larger factor in enhancing cloud condensation nuclei concentrations for the same cloud-base supersaturation. A smaller effect is seen over the urban and industrial areas to the east of Houston. The color composite is red, green, and blue for the visible reflectance, 3.7-micrometer solar reflectance, and thermal temperature, respectively. The Houston bay and beltways are marked by white lines.  (After "Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings"[SciTech Connect], p. 15.)

 

Reducing other uncertainties in the solid-particle properties of clouds was also the purpose of data analyses described in "Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions"[SciTech Connect].  The particular data to be analyzed was about tiny ice crystals, since many clouds form when water droplets condense onto them.  Since the clouds' physical properties depend heavily on the ice crystals' shapes, a great deal of information about the shapes and related quantities was gathered into databases.  The researchers also investigated how aerosols other than clouds affect clouds' properties at varying locations, environments, and air and surface conditions. 

 

Figure 2.  Images of ice-crystal cloud particles exemplifying the 11 categories into which an algorithm sorts them by shape:  (a) small quasi-sphere (SQS), (b) medium quasi-sphere (MQS), (c) large quasi-sphere (LQS), (d) column (COL), (e) plate (PLT), (f) bullet rosette (BR), (g) aggregates of bullet rosettes (ABRs), (h) aggregates of columns (ACs), (i) aggregates of plates (APs), (j) capped column (CC), and (k) unclassified (UC).  (After "Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions"[SciTech Connect], p. 23.) 

 

In another project[SciTech Connect], researchers at the Scripps Institution of Oceanography and Pacific Northwest National Laboratory used new observations of certain arctic phenomena to improve mathematical models of how the earth's climate may respond to increases in greenhouse gases, which absorb and emit infrared radiation[Wikipedia].  One of the largest sources of aerosol particles had been unaccounted for in earlier mathematical models:  the "frost flowers" that form on newly frozen arctic sea ice[Wikipedia].  In winter winds of about 22 miles per hour (10 meters per second), about a million aerosol particles are produced every second per square meter of frost flower surface, but this particle flux is "highly localized to new sea ice regions and strongly dependent on wind speed".  The researchers' new model has been used to quantify potential effects of this source of aerosol, including radiative forcing, and to investigate how to better predict the way aerosols, clouds, and climate will interact to produce climate change at regional scales in response to radiative forcing produced by human activity.  As their report states, accounting for such effects is important because "[t]he Arctic is Earth's most sensitive region to changes in the atmospheric composition of greenhouse gases, exhibiting nearly twice the global mean surface warming in response to industrial-era anthropogenic emissions".  The report includes brief descriptions of the effects found in certain scenarios. 

 

Part of the project reported in "Characterization of 3D Cirrus Cloud and Radiation Fields Using ARS/AIRS/MODIS data and its Application to Climate Model"[SciTech Connect] involved adding details to existing mathematical models about ice microphysics and associated phenomena.  Clouds with a given ice water content reflect more sunlight, the smaller their cloud particles are, and the cloud particles' sizes are determined by diffusion, collision, and ice crystals' shapes.  Running models that include all the details of how cloud particles form is impractical even on today's most powerful supercomputers, so the modelers reduced their additions to information about effective average ice crystal sizes based on observational data.  For one model, the researchers also described solar and infrared radiation in more detail—not by specifying the radiation's intensity at each specific frequency, but in terms of a few specific frequency bands.  This model was also enhanced with details about the way light of 60 different wavelengths is scattered by 18 different aerosol types:  maritime, continental, urban, insoluble, water-soluble, black-carbon soot, five different sizes of mineral dust, mineral dust in four different modes, sea salt in accumulation mode and coarse mode, and sulfate droplets.  To study how cloud condensation nuclei may increase clouds' reflection of solar radiation, the researchers also analyzed satellite-captured scenes containing heavy dust events and ice clouds covering the planet's regions of frequent dust outbreaks and long-range dust transportation.  Their findings that smaller cloud particle sizes always characterized regions with larger dust aerosol optical depth were consistent with a hypothesis[Wikipedia] first published by atmospheric scientist Sean Twomey. 

 

A different project, described in "Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements"[SciTech Connect], aimed to assimilate ARM measurements with other satellite and radar data for reanalysis of weather observed in a selected time period, and to provide a comprehensive data assimilation system that could represent land and weather variables, solid or liquid water in the air (aka hydrometeors[Wikipedia]), and aerosol concentrations and size distributions in a volume of space over a time interval.  The goal was to produce accurate, consistent, and comprehensive data sets to describe initial states for mathematical models that resolve individual clouds and for models that describe single columnar volumes of the atmosphere.  The project achieved these goals and several others, as described in the report. 

 

Figure 3.  Top:  infrared image from the Geostationary Operational Environmental Satellite (GOES)[Wikipedia] (left) and a reflectivity map from NEXRAD[Wikipedia] weather radar (right) for the Southern Great Plains site[ARM] of the Atmospheric Radiation Measurement program, both taken near 0300 Coordinated Universal Time[Wikipedia], on June 14, 2007.  Bottom:  otherwise-identical mathematical models of the same event's radar reflectivity at 0300 Coordinated Universal Time, both based on conventional and satellite data but differing in whether additional data from site observations was (left) or was not (right) also assimilated.  (From "Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements"[SciTech Connect], pp. 6 and 7 of 15.) 

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More about clouds


A measurement of any quantity generally results in a figure that represents the actual quantity combined with some extraneous influence, so that the measurement ends up being at least slightly off.  If the extraneous influences on a set of quantities vary randomly, multiple measurements of the same quantities will give varying results.  The measurements, plus any information about the extraneous influences, are the only data from which the most likely values of the actual quantities can be inferred.  Using this data more completely, and adding information from measurements of related quantities, were the keys to the improvements in accuracy reported in "Development of Integrated ASR Model Forcing Data and Their Applications to Improve CAM"[SciTech Connect].  The "ASR" in this title stands for "Atmospheric System Research"[ASR], while "CAM" stands for "Community Atmosphere Model"[Wikipedia], a mathematical model of the atmosphere used by the climate-research community. 

 

Results of using ARM's unique long-term radar observations of clouds to study cloud lifecycle and precipitation features under different weather and climate conditions are briefly described in "Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models"[SciTech Connect].  Here, "MJO" refers to the largest element of the 30-90 day variability in the tropical atmosphere, the Madden-Julian oscillation[Wikipedia]; "AMIE" is an acronym for "ARM MJO Investigation Experiment", which provided data on surface precipitation that was used in the study.  Observations showed differences in rain produced by cumulus[Wikipedia] and stratus [Wikipedia] clouds, both in the structure shown by the composite distributions of radar reflectivity and Doppler velocity[ERAU, UIUC, Wikipedia], and in the number concentrations of small and large raindrops measured by disdrometers[Wikipedia].  A new method of estimating rainfall rates from both types of clouds was developed and found to improve on an earlier method.  The researchers also found that low-level cloud evolutions seem to lead rain from both cumulus and stratus clouds, which then leads the middle- and upper-level clouds. 

 

Several discoveries from an Atmospheric System Research project entitled "ARM Observations for the Development and Evaluation of Models and Parameterizations of Cloudy Boundary Layers" are described in a February 2016 report[SciTech Connect].  Among these are:  

 

  • While earlier simulations of spatial volumes, and their large-scale distributions of low clouds, fine-scale cloud properties, and vertical velocities, assumed for mathematical simplicity that conditions were the same on opposite boundaries of the volume, the simulations were significantly improved with input of more realistic boundary conditions when turbulent fluctuations at the inflow and outflow boundaries are substantially different, such as where terrain or land uses are complex. 

  • Simulations of different cloud variables can't be self-consistent if the simulation assumes that all the variables have the same probability distribution. 

  • Mesoscale[Wikipedia] cloud organizations contribute significantly to turbulent kinetic energy (which is weakly correlated to fluxes beyond a critical scale) but limitedly to momentum and heat transport (apparently dominated by large turbulent eddies)—a result that led the authors to rethink a classic treatment of turbulence in a cloud-topped boundary layer[Wikipedia]. 

  • One scheme for simulating shallow convection gets the vertical structure of various flux profiles qualitatively correct, but it doesn't accurately represent the flux's dependence on cloud microphysics and precipitation. 

  • Limited-area models "possesses a unique capability" to simulate tropical deep convection[Wikipedia], and have the potential to bridge the gap between cloud-resolving models and numerical weather prediction models, but getting consistent, reliable dynamic and cloud fields "remains a challenge". 

  • Simulations of large eddies[Wikipedia] in the atmosphere combined with the Weather Research and Forecasting[Wikipedia] model indicate that (1) the vertical velocity and cloud liquid water content of updrafts tend to be greatest in those updrafts that are influenced by the cooler-air regions (cold pools[NOAA]) induced by shallow cumulus clouds' convection, and (2) higher rain rates correspond to larger cloud cover through upper-level clouds' being sheared off. 

  • In simulations based on six well-documented cases, a computational method based on the rate of mass flow per unit area can account for most of the heat and moisture fluxes under certain conditions, but substantially underestimates vertical heat and moisture fluxes under others, and fails to represent momentum transport in the cloud layer.  

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Plans for further investigations

 

OSTI's services provide access not only to ARM data and data-analysis results, but to plans for upcoming investigations as well.  Five such plans from December 2015 describe efforts to fill various knowledge gaps regarding the interactions of clouds, sunlight, and radiant heat in the earth's weather system. 

 

One big knowledge gap concerns the cloud and aerosol properties over the Southern Ocean[Wikipedia], which are known imprecisely, largely from satellite data.  Measurements of these properties, and of surface radiation fluxes, are to be made with instruments deployed at Macquarie Island[Wikipedia], just 6 degrees north of the Southern Ocean's boundary.  The measurements are to be taken for two years to characterize the measured properties' full seasonal cycle and variability.[SciTech Connect] 

 

Another project plan[SciTech Connect] notes the importance of cumulus-cloud convection, both to electromagnetic radiation in the atmosphere and to the earth's water cycle, over many regions of the world, especially during summer growing seasons "when intense turbulence induced by surface radiation couples the land surface to clouds".  The plan describes how the project is to address present uncertainties about these phenomena: 

 

"Insufficient data to couple cloud properties to inhomogeneities in boundary-layer and aerosol properties make parameters of convective clouds uncertain in current mathematical models.  Measurements to better understand shallow clouds are the object of two spring and late summer observation periods in the vicinity of ARM's Southern Great Plains site[ARM].  While routine aerosol measurements are to be supplemented with measurements of aerosol microphysical properties at the surface, atmospheric turbulence, cloud water content and drop-size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei concentrations are to be measured by ARM's Aerial Facility[ARM].  The measurements, combined with studies of mathematical models, should allow quantification of how shallow clouds are influenced by inhomogeneities of land use, vegetation, soil moisture, convective eddies, and aerosol properties.  Also to be studied are clouds' feedback on aerosol photochemical processes and on radiation reaching the earth's surface along with associated changes in the surface heat, moisture, and momentum fluxes."

 

Another plan[SciTech Connect] describes how measurements of trace gases, and of solar and infrared radiation, are also to be made over the Southern Great Plains site by instruments on a different ARM Aerial Facility aircraft.  The goal of this project is to better understand carbon exchange at the Southern Great Plains site, how carbon dioxide and associated fluxes of water and energy influence differences between incoming and outgoing electromagnetic radiation there, and how greenhouse gases are transported on continental scales.  The aircraft is to carry analyzers for continuous measurement of carbon dioxide, and a 12-flask sampler for analyses of several carbon-cycle gases:  carbon dioxide made with each of three different isotopes of carbon, carbon monoxide, methane, nitrogen dioxide, carbonyl sulfide, and ethane and other trace hydrocarbons. 

 

Oliktok Point, Alaska, part of ARM's North Slope site[ARM], is also where ARM's third Mobile Facility[ARM] is currently stationed.  Measurements obtained there are to be complemented by readings from drones[Wikipedia] to address how temperature and humidity change in transitions between clear and cloudy conditions, how aerosols vary with height at high latitudes, how well remote sensors perform in the Arctic, and how heat and moisture fluxes vary spatially over ice and land surfaces.  According to the published plan for making these measurements[SciTech Connect], understanding of atmospheric conditions at high latitudes, particularly properties related to clouds, aerosols, and radiation, has become very relevant because of observed decreases in polar ice and snow.  The measurements will also allow evaluation of drones' potential for future routine atmospheric measurements at Oliktok Point. 

 

The last of these December 2015 plans[SciTech Connect] describes a project to help "provide a stringent test for global aerosol models" by gathering data about the "least examined of the Earth's major stratocumulus decks", which is over the remote southeast Atlantic Ocean.  This region has the further significance of being where "some of the largest atmospheric loadings of absorbing aerosol" arrive from southern Africa, "the world's largest emitter of biomass-burning (BB) aerosols."  The effect of this on radiative forcing has been uncertain because we lack information about how shortwave-absorbing aerosol ages during transport over the ocean, how much of the aerosol mixes into the cloudy boundary layer, and how the low clouds adjust to interactions of both clouds and radiation with smoke.  Furthermore, the aerosols change seasonally as the biomass burned to produce them changes.  Measurements to redress the gaps in our information are to be taken with ARM's first Mobile Facility[ARM] near Ascension Island[Wikipedia], which is 3000 kilometers from Africa and in the zone of maximum aerosol outflow.  The measurement period is to encompass two July-to-October biomass-burning seasons.  A smaller set of secondary instruments is to be placed upwind on the South Atlantic island of Saint Helena[Wikipedia].  All these observations are to overlap with other complementary ones taken elsewhere by different US and UK agencies, and the collected data is to be combined in a comprehensive modeling effort to understand the distribution of the planet's radiative balance in a region with an important cloud feedback to climate. 

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References

Wikipedia


List of Atmospheric Radiation Measurement data sets available through the DoE Data Explorer

 

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Reports available through OSTI’s SciTech Connect

 

Additional references

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Last updated on Wednesday 27 July 2016