Atmospheric Radiation Measurement Program Site Research Articles

A More Transparent Infrared Window

AbstractThe infrared window region (780–1,250 cm−1, 12.8 to 8.0 μm) is of great importance to Earth's climate due to its high transparency and thermal energy. We present here a new investigation of the transparency of this spectral region based on observations by interferometers of downwelling surface radiance at two DOE Atmospheric Radiation Measurement program sites. We focus on the dominant source of absorption in this region, the water vapor continuum, and derive updated values of spectral absorption coefficients for both the self and foreign continua. Our results show that the self continuum is too strong in the previous version of Mlawer‐Tobin_Clough‐Kneizys‐Davies (MT_CKD) water vapor continuum model, a result that is consistent with other recent analyses, while the foreign continuum is too weak in MT_CKD. In general, the weaker self continuum derived in this study results in an overall increase in atmospheric transparency in the window, although in atmospheres with low amounts of water vapor the transparency may slightly decrease due to the increase in foreign continuum absorption. These continuum changes lead to a significant decrease in downwelling longwave flux at the surface for moist atmospheres and a modest increase in outgoing longwave radiation. The increased fraction of surface‐leaving radiation that escapes to space leads to a notable increase (∼5–10%) in climate feedback, implying that climate simulations that use the new infrared window continuum will show somewhat less warming than before. This study also points out the possibly important role that aerosol absorption may play in the longwave radiative budget.

Regime‐Specific Cloud Vertical Overlap Characteristics From Radar and Lidar Observations at the ARM Sites

AbstractClimate and numerical weather prediction models require assumptions to represent the vertical distribution of subgrid‐scale clouds, which have radiative transfer implications. In this study, nearly 25 years of ground‐based radar and lidar observations of vertical cloud profiles at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site are utilized to derive cloud vertical overlap characteristics from the Cloud Type (CLDTYPE) data product. The cloud vertical overlap characteristics are further separated by cloud regime by considering seven cloud types (i.e., low cloud, congestus, deep convection, altocumulus, altostratus, cirrostratus, and cirrus) as well as periods of shallow cumulus. The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites among other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting.

Coordinated Airborne Studies in the Tropics (CAST)

Abstract The main field activities of the Coordinated Airborne Studies in the Tropics (CAST) campaign took place in the west Pacific during January–February 2014. The field campaign was based in Guam (13.5°N, 144.8°E), using the U.K. Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 atmospheric research aircraft, and was coordinated with the Airborne Tropical Tropopause Experiment (ATTREX) project with an unmanned Global Hawk and the Convective Transport of Active Species in the Tropics (CONTRAST) campaign with a Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical west Pacific, as well as the importance of trace-gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights in the region between 1°S and 14°N and 130° and 155°E. It was used to sample at altitudes below 8 km, with much of the time spent in the marine boundary layer. It measured a range of chemical species and sampled extensively within the region of main inflow into the strong west Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement Program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project, focusing on the design and operation of the west Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on board the Global Hawk in February–March 2015.

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

Abstract The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

MCMC-Based Assessment of the Error Characteristics of a Surface-Based Combined Radar–Passive Microwave Cloud Property Retrieval

AbstractCollocated active and passive remote sensing measurements collected at U.S. Department of Energy Atmospheric Radiation Measurement Program sites enable simultaneous retrieval of cloud and precipitation properties and air motion. Previous studies indicate the parameters of a bimodal cloud particle size distribution can be effectively constrained using a combination of passive microwave radiometer and radar observations; however, aspects of the particle size distribution and particle shape are typically assumed to be known. In addition, many retrievals assume the observation and retrieval error statistics have Gaussian distributions and use least squares minimization techniques to find a solution. In truth, the retrieval error characteristics are largely unknown. Markov chain Monte Carlo (MCMC) methods can be used to produce a robust estimate of the probability distribution of a retrieved quantity that is nonlinearly related to the measurements and that has non-Gaussian error statistics. In this work, an MCMC algorithm is used to explore the error characteristics of cloud property retrievals from surface-based W-band radar and low-frequency microwave radiometer observations for a case of orographic snowfall. In this particular case, it is found that a combination of passive microwave radiometer measurements with radar reflectivity and Doppler velocity is sufficient to constrain the liquid and ice particle size distributions, but only if the width parameter of the assumed gamma particle size distribution and mass–dimensional relationships are specified. If the width parameter and mass–dimensional relationships are allowed to vary realistically, a unique retrieval of the liquid and ice particle size distribution for this orographic snowfall case is rendered far more problematic.

Climatology and Formation of Tropical Midlevel Clouds at the Darwin ARM Site

Abstract A 4-yr climatology of midlevel clouds is presented from vertically pointing cloud lidar and radar measurements at the Atmospheric Radiation Measurement Program (ARM) site at Darwin, Australia. Few studies exist of tropical midlevel clouds using a dataset of this length. Seventy percent of clouds with top heights between 4 and 8 km are less than 2 km thick. These thin layer clouds have a peak in cloud-top temperature around the melting level (0°C) and also a second peak around −12.5°C. The diurnal frequency of thin clouds is highest during the night and reaches a minimum around noon, consistent with variation caused by solar heating. Using a 1.5-yr subset of the observations, the authors found that thin clouds have a high probability of containing supercooled liquid water at low temperatures: ~20% of clouds at −30°C, ~50% of clouds at −20°C, and ~65% of clouds at −10°C contain supercooled liquid water. The authors hypothesize that thin midlevel clouds formed at the melting level are formed differently during active and break monsoon periods and test this over three monsoon seasons. A greater frequency of thin midlevel clouds are likely formed by increased condensation following the latent cooling of melting during active monsoon periods when stratiform precipitation is most frequent. This is supported by the high percentage (65%) of midlevel clouds with preceding stratiform precipitation and the high frequency of stable layers slightly warmer than 0°C. In the break monsoon, a distinct peak in the frequency of stable layers at 0°C matches the peak in thin midlevel cloudiness, consistent with detrainment from convection.

Ground-Based Millimeter- and Submillimeter-Wave Observations of Low Vapor and Liquid Water Contents

Ground-based observations at millimeter (mm) and submillimeter (submm) wavelengths were collected at the atmospheric radiation measurement program site at Barrow, AK, during the Arctic winter by a new 25-channel radiometer. A weighting function analysis is presented to demonstrate the enhanced sensitivity of mm- and submm-wave (50-400 GHz) radiometers to low vapor and liquid water contents with respect to conventional instruments such as the ones operating at centimeter (cm) wavelengths (20-30 GHz). In addition, based on measurements, we carried out a quantitative analysis of mm- and submm-wavelength sensitivity, yielding improvement factors from 1.5 to 69 for precipitable water vapor (PWV) and 3 to 4 for liquid water path (LWP) when compared to 20-30 GHz radiometers. Furthermore, using a simulated data set, we evaluate the effect of hydrometeor scattering: given the conditions occurring during the experiment, the scattering contribution is within the instrumental noise for most, but not all, of the considered channels. With the same data set, we demonstrate that in the dry conditions of the Arctic, a simple linear regression yields satisfactory results when applied on selected mm- and submm-wave channels. For a dual-channel combination, the expected accuracy is ~0.23 (0.007) mm for PWV (LWP), when using mm- and submm-wavelengths, whereas it is 0.37 (0.012) mm using cm-wave channels. When the retrieval is applied to real observations, the accuracy is found in agreement with theoretical expectations.

The Atmospheric Radiation Measurement Program Cloud Profiling Radars: Second-Generation Sampling Strategies, Processing, and Cloud Data Products

Abstract The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates millimeter-wavelength cloud radars in several climatologically distinct regions. The digital signal processors for these radars were recently upgraded and allow for enhancements in the operational parameters running on them. Recent evaluations of millimeter-wavelength cloud radar signal processing performance relative to the range of cloud dynamical and microphysical conditions encountered at the ARM Program sites have indicated that improvements are necessary, including significant improvement in temporal resolution (i.e., less than 1 s for dwell and 2 s for dwell and processing), wider Nyquist velocities, operational dealiasing of the recorded spectra, removal of pulse compression while sampling the boundary layer, and continuous recording of Doppler spectra. A new set of millimeter-wavelength cloud radar operational modes that incorporate these enhancements is presented. A significant change in radar sampling is the introduction of an uneven mode sequence with 50% of the sampling time dedicated to the lower atmosphere, allowing for detailed characterization of boundary layer clouds. The changes in the operational modes have a substantial impact on the postprocessing algorithms that are used to extract cloud information from the radar data. New methods for postprocessing of recorded Doppler spectra are presented that result in more accurate identification of radar clutter (e.g., insects) and extraction of turbulence and microphysical information. Results of recent studies on the error characteristics of derived Doppler moments are included so that uncertainty estimates are now included with the moments. The microscale data product based on the increased temporal resolution of the millimeter-wavelength cloud radars is described. It contains the number of local maxima in each Doppler spectrum, the Doppler moments of the primary peak, uncertainty estimates for the Doppler moments of the primary peak, Doppler moment shape parameters (e.g., skewness and kurtosis), and clear-air clutter flags.

Ensemble single column modeling (ESCM) in the tropical western Pacific: Forcing data sets and uncertainty analysis

Single column models (SCMs) are useful tools for the evaluation of parameterisations of radiative and moist processes used in general circulation models (GCMs). Most SCM studies to date have concentrated on regions where there is a sufficiently dense observational network to derive the required forcing data. This paper describes an ensemble single column modeling (ESCM) approach where the forcing data are derived from numerical weather prediction (NWP) analysis products. To highlight the benefits of the ESCM approach, four forcing data sets were derived for a two year period at the Tropical Western Pacific ARM (Atmospheric Radiation Measurement Program) sites at Manus Island and Nauru. In the first section of the study, the NWP derived forcing data are validated against a range of observations at the tropical sites. In the second section, the sensitivity of two different SCMs to uncertainties in the forcing data sets are analysed. It is shown that despite the inherent uncertainties in the NWP derived forcing data, an ESCM approach is able to identify errors in the SCM physics. This suggests the ESCM approach is useful for testing parameterisations in relatively observation sparse regions, such as the TWP.

A microphysical parameterization for convective clouds in the ECHAM5 climate model: Single‐column model results evaluated at the Oklahoma Atmospheric Radiation Measurement Program site

The microphysical parameterization used for stratiform clouds in the ECHAM5 climate model is now extended for simulations of convective clouds. The performance of the newly implemented parameterization in simulating midlatitude continental summertime convective cloud systems is evaluated in this paper at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site in Oklahoma using the single‐column mode (SCM) of ECHAM5. Three ARM intensive operating periods (IOPs), including two summer ones and a late spring one, are used for the evaluation. Results show that the SCM simulated cloud cover fraction agrees well with observations. The SCM also captures most of the precipitation events. With the new microphysical parameterization, the model performs at least as well as with the original model setup in simulating almost all the fields examined in this study. Significant improvement is shown in the simulations of outgoing longwave radiation and net incoming solar radiation at the top of the atmosphere revealing the feasibility of the new parameterization. Sensitivity studies show that a 10‐fold increase in cloud droplet number concentration significantly increases the simulated liquid water content. More interestingly, this increase in cloud droplet number leads to an increase in the total amount of precipitation in two of the three IOPs.

Cloud Properties Simulated by a Single-Column Model. Part I: Comparison to Cloud Radar Observations of Cirrus Clouds

Abstract This study describes and demonstrates a new method for identifying deficiencies in how cloud processes are represented in large-scale models. Kilometer-scale-resolving cloud radar observations and cloud-resolving model (CRM) simulations were used to evaluate the representation of cirrus clouds in the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model for a 29-day period during June and July 1997 at the Atmospheric Radiation Measurement Program site in Oklahoma. To produce kilometer-scale cirrus statistics from the SCM results, synthetic subgrid-scale (SGS) cloud fields were generated using the SCM’s cloud fraction and hydrometeor content profiles, and the SCM’s cloud overlap and horizontal inhomogeneity assumptions. Three sets of SCM synthetic SGS cloud fields were analyzed. Two NOSNOW sets were produced in which clouds did not include snow; one set used random overlap, the other, maximum/random. In the SNOW set, clouds included snow and random overlap was used. The three sets were sampled in the same way as the cloud-radar-detected cloud fields and the CRM-simulated cloud fields. The mean cirrus cloud occurrence frequency for the SCM NOSNOW cloud fields agrees with the observed value as well as the CRM’s does, while that for SCM SNOW cloud fields is only half that observed. In most aspects, the SCM’s cirrus properties differ significantly from the cloud radar’s and the CRM’s, which generally agree. In comparison, there are too many physically thin SCM NOSNOW cirrus layers (most occupy only a single model layer) and too many physically thick SCM SNOW cirrus layers (most are thicker than 4 km). For the optically thin subset of cirrus layers, 1) the mean, mode, and median ice water path, and layer-mean ice water content (IWC) values for the SCM are significantly larger than the observed and CRM values; 2) the SCM layer-mean IWCs decrease with cloud physical thickness, opposite to the observations and CRM results; and 3) the range of layer-mean effective radii in the SCM thin cirrus is too narrow.

The Radiative, Cloud, and Thermodynamic Properties of the Major Tropical Western Pacific Cloud Regimes

Abstract This study investigates the radiative, cloud, and thermodynamic characteristics of the atmosphere separated into objectively defined cloud regimes in the tropical western Pacific (TWP). A cluster analysis is applied to 2 yr of daytime-only data from the International Satellite Cloud Climatology Project (ISCCP) to identify four major cloud regimes in the TWP region. A variety of data collected at the Department of Energy’s Atmospheric Radiation Measurement Program (ARM) site on Manus Island is then used to identify the main characteristics of the regimes. Those include surface and top-of-the-atmosphere radiative fluxes and cloud properties derived from a suite of ground-based active remote sensors, as well as the temperature and water vapor distribution measured from radiosondes. The major cloud regimes identified in the TWP area are two suppressed regimes—one dominated by the occurrence of mostly shallow clouds, the other by thin cirrus—as well as two convectively active regimes—one exhibiting a large coverage of optically thin cirrus clouds, the other characterized by a large coverage with optically thick clouds. All four of these TWP cloud regimes are shown to exist with varying frequency of occurrence at the ARM site at Manus. It is further shown that the detailed data available at that site can be used to characterize the radiative, cloud, and thermodynamic properties of each of the regimes, demonstrating the potential of the regime separation to facilitate the extrapolation of observations at one location to larger scales. A variety of other potential applications of the regime separation are discussed.

Sensitivity of near infrared total water vapour estimate to calibration errors

Analysis of satellite data to estimate the precipitable water (also called the columnar water vapour) amount often leads to systematic errors in deduced precipitable water (PW). The causes of systematic errors are likely to be instrumental calibration errors rather than variability of atmospheric parameters. We use the MODTRAN 4.0 radiative transfer code to model effects of various calibration errors on the Multi-spectral Thermal Imager (MTI) daytime total water vapour estimate. From the considered sources of calibration errors (spectral band centre error, spectral bandwidth error and radiometric calibration error) the radiometric calibration error has the largest influence on the accuracy of total water vapour estimate. When the radiometric calibration error between 1% and 5% is combined with the estimated spectral band centre error of 1 nm and the bandwidth error of 0.5 nm, the total systematic error of the columnar water vapour estimate is expected to be between 8% and 26%. The accuracy of the retrieved PW using the MTI imagery over the NASA Stennis site and Oklahoma DOE (Department of Energy) ARM (Atmospheric Radiation Measurement program) site is about 17%, well within the estimated range due to calibration errors. A similarity between the MTI and the MODIS (Moderate Resolution Imaging Spectral-Radiometer) bands used for water vapour estimate suggests that a similar error analysis may be valid for the MODIS sensor. However, the narrow band instruments (with bandwidth around 10 nm) are much more sensitive to the band centre calibration error.

Cloud Resolving Modeling of the ARM Summer 1997 IOP: Model Formulation, Results, Uncertainties, and Sensitivities

Abstract A new three-dimensional cloud resolving model (CRM) has been developed to study the statistical properties of cumulus convection. The model was applied to simulate a 28-day evolution of clouds over the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains site during the summer 1997 Intensive Observation Period. The model was forced by the large-scale advective tendencies and surface fluxes derived from the observations. The sensitivity of the results to the domain dimensionality and size, horizontal grid resolution, and parameterization of microphysics has been tested. In addition, the sensitivity to perturbed initial conditions has also been tested using a 20-member ensemble of runs. The model captures rather well the observed temporal evolution of the precipitable water and precipitation rate, although it severely underestimates the shaded cloud fraction possibly because of an inability to account for the lateral advection of clouds over the ARM site. The ensemble runs reveal t...

Full-Time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instruments and Data Processing

Full-Time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instruments and Data Processing

Model Calculations and Interferometer Measurements of Ice-Cloud Characteristics

Abstract This paper investigates the relationship between high–spectral resolution infrared (IR) radiances and the microphysical and macrophysical properties of cirrus clouds. Through use of radiosonde measurements of the atmospheric state at the Department of Energy’s Atmospheric Radiation Measurement Program site, high–spectral resolution IR radiances are calculated by combining trace gas absorption optical depths from a line-by-line radiative transfer model with the discrete ordinate radiative transfer (DISORT) method. The sensitivity of the high–spectral resolution IR radiances to particle size, ice-water path, cloud-top location, cloud thickness, and multilayered cloud conditions is estimated in a multitude of calculations. DISORT calculations and interferometer measurements of cirrus ice cloud between 700 and 1300 cm−1 are compared for three different situations. The measurements were made with the High–Spectral Resolution Interferometer Sounder mounted on a National Aeronautics and Space Administration ER-2 aircraft flying at 20-km altitude during the Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS).

A comparison of Sun photometer derivations of total column water vapor and ozone to standard measures of same at the Southern Great Plains Atmospheric Radiation Measurement site

Total column water vapor measurements made over a 1‐year period by collocated instruments at the Southern Great Plains Atmospheric Radiation Measurement program site in northern Oklahoma are compared. Microwave radiometer measurements were validated in an earlier program with extensive comparisons to balloon sonde measurements. Sun photometry, using the multifilter rotating shadowband radiometer (MFRSR), was the second technique used to derive water vapor using the 940‐nm water band when no clouds were between the radiometer and the sun. Bruegge et al.'s implementation of Reagan et al.'s modified Langley technique was applied in this case. This approach is noteworthy in that it does not rely on a comparison to a standard for calibration. The comparison of 101 one‐half‐hour to two‐hour averages produced a root‐mean‐square difference of 0.18 cm compared to a mean value of 1.49 cm, or about 12%, with the MFRSR showing an overall bias of +0.03 cm relative to the microwave radiometer data. This is a somewhat higher rms error than other results using the modified Langley technique, but the comparison was made over the entire range of water vapor columns experienced in a year of observations. As a by‐product of the water vapor derivation procedure for the MFRSR, ozone column abundance was estimated. Seasonally averaged, these data compare favorably with Dobson measurements from Nashville, Tennessee, which is near the same latitude. A more definitive conclusion regarding the Sun photometer ozone derivation technique requires colocated ozone measurements using an accepted standard approach, however, the technique appears to provide a useful ozone estimate for correcting aerosol optical depth derivations.