Southern Great Plains Site Research Articles

Diagnosis of Community Atmospheric Model 2 (CAM2) in numerical weather forecast configuration at Atmospheric Radiation Measurement sites

The Community Atmospheric Model 2 (CAM2) is run as a short‐term (1–5 days) forecast model initialized with reanalysis data. The intent is to reveal model deficiencies before complex interactions obscure the root error sources. Integrations are carried out for three Atmospheric Radiation Measurement (ARM) Program intensive operational periods (IOPs): June/July 1997, April 1997, and March 2000. The ARM data are used to validate the model in detail for the Southern Great Plains (SGP) site for all the periods and in the tropical west Pacific for the March 2000 period. The model errors establish themselves quickly, and within 3 days the model has evolved into a state distinctly different from the ARM observations. The summer forecasts evince a systematic error in convective rainfall. This error manifests itself in the temperature and moisture profiles after a single diurnal cycle. The same error characteristics are seen in the March 2000 tropical west Pacific forecasts. The model performs well in the spring cases at the SGP. Most of the error is manifested during rainy periods. The ARM cloud radar comparison to the model reveals cloud errors which are consistent with the relative humidity profile errors. The cloud errors are similar to those seen in climatological integrations, but the state variable errors are different. Thus there is the possibility that the some basic parameterization errors are obscured in the climatological integrations. The approach described here will facilitate parameterization experimentation, diagnoses, and validation. One way of reducing cloud feedback uncertainty is to make the physical processes behave in the most realistic manner possible. Paradoxically, perhaps the best way to reduce uncertainty in cloud feedback mechanisms is to evaluate the model processes with realistic forcing before such feedbacks have any significant affect.

Natural variability and sampling errors in solar radiation measurements for model validation over the Atmospheric Radiation Measurement Southern Great Plains region

Ground‐based radiation measurements are frequently used for validating the performance of a model in simulating clouds. Such important questions are often raised as: (1) How well do the measurements represent model grid mean values?; (2) How much of model‐observation differences can be attributed to inherent sampling errors?; and (3) What scale does modeling need to be performed in order to capture the cloud variation? We attempt to address these questions using surface solar irradiance data retrieved from the Geostationary Operational Environmental Satellite (GOES) and measured at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The satellite retrievals are used to mimic ground measurements with various spatial densities and temporal frequencies, from which the sampling errors of the ground observations are quantified and characterized. Most of the differences between point‐specific measurements and area‐mean satellite retrievals originate from ground sampling errors. We quantify these errors for different months, model grid sizes, and integration intervals. In March 2000, for example, the sampling error is 16 W m−2 for instantaneous irradiances averaged over an area of 10 × 10 km2. It increases to 46 and 64 W m−2 if the model grid size is enlarged to 200 × 200 km2 and 400 × 400 km2, respectively. The sampling uncertainties decrease rapidly as the time‐averaging interval increases up to 24 hours and then level off to a relatively small and stable value. Averaging over periods greater than 5 days reduces the error to a magnitude of less than 15 W m−2 over all grid sizes. The sampling error also decreases as the number of ground stations increases inside a grid, but the most substantial reduction occurs as the number of ground sites increases from 1 to 2 or 3 for a grid size of 200 × 200 km2. This means that for computing grid‐mean surface solar irradiance, there is no need for an overly dense network of observation stations.

Advanced retrievals of multilayered cloud properties using multispectral measurements

Current satellite cloud retrievals are usually based on the assumption that all clouds consist of a homogenous single layer despite the frequent occurrence of cloud overlap. As such, cloud overlap will cause large errors in the retrievals of many cloud properties. To address this problem, a multilayered cloud retrieval system (MCRS) is developed by combining satellite visible and infrared radiances and surface microwave radiometer measurements. A two‐layer cloud model was used to simulate ice‐over‐water cloud radiative characteristics. The radiances emanating from the combined low cloud and surface are estimated using the microwave liquid water with an assumption of effective droplet size. These radiances replace the background radiances traditionally used in single‐layer cloud retrievals. The MCRS is applied to data from March through October 2000 over four Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) sites. The results are compared to the available retrievals of ice water path (IWP) from radar data and show that the MCRS clearly produces a more accurate retrieval of ice‐over‐water cloud properties. MCRS yields values of IWP that are closest to those from the radar retrieval. For ice‐over‐water cloud systems, on average, the optical depth and IWP are reduced, from original overestimates, by approximately 30%. The March–October mean cloud effective temperatures from the MCRS are decreased by 10 ± 12 K, which translates to an average height difference of ∼1.4 km. These results indicate that ice‐cloud height derived from traditional single‐layer retrieval is underestimated, and the midlevel ice cloud coverage is over classified. Effective ice crystal particle sizes are increased by only a few percent with the new method. This new physically based technique should be robust and directly applicable when data are available simultaneously from a satellite imager and the appropriate satellite or surface microwave sensor.

Simulations of midlatitude frontal clouds by single‐column and cloud‐resolving models during the Atmospheric Radiation Measurement March 2000 cloud intensive operational period

This study quantitatively evaluates the overall performance of nine single‐column models (SCMs) and four cloud‐resolving models (CRMs) in simulating a strong midlatitude frontal cloud system taken from the spring 2000 Cloud Intensive Observational Period at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The evaluation data are an analysis product of constrained variational analysis of the ARM observations and the cloud data collected from the ARM ground active remote sensors (i.e., cloud radar, lidar, and laser ceilometers) and satellite retrievals. Both the selected SCMs and CRMs can typically capture the bulk characteristics of the frontal system and the frontal precipitation. However, there are significant differences in detailed structures of the frontal clouds. Both CRMs and SCMs overestimate high thin cirrus clouds before the main frontal passage. During the passage of a front with strong upward motion, CRMs underestimate middle and low clouds while SCMs overestimate clouds at the levels above 765 hPa. All CRMs and some SCMs also underestimated the middle clouds after the frontal passage. There are also large differences in the model simulations of cloud condensates owing to differences in parameterizations; however, the differences among intercompared models are smaller in the CRMs than the SCMs. In general, the CRM‐simulated cloud water and ice are comparable with observations, while most SCMs underestimated cloud water. SCMs show huge biases varying from large overestimates to equally large underestimates of cloud ice. Many of these model biases could be traced to the lack of subgrid‐scale dynamical structure in the applied forcing fields and the lack of organized mesoscale hydrometeor advections. Other potential reasons for these model errors are also discussed in the paper.

Aerosol retrievals using rotating shadowband spectroradiometer data

The rotating shadowband spectroradiometer (RSS) is a high‐resolution device that measures the total, direct, and diffuse intensity of sunlight at 1016 different wavelengths. RSS data can be used to retrieve gas amounts and aerosol properties as well as to assess the accuracy of retrievals using data from lower‐spectral resolution instruments, such as the multifilter rotating shadowband radiometer (MFRSR). An algorithm to retrieve aerosol and gas amounts and the aerosol size distribution from RSS data, using the full resolution and using selected wavelengths, has been developed (Gianelli, 2004). The results of the retrievals, applied to RSS data from the southern Great Plains (SGP) site, indicate a number of things about the aerosol size distribution and our ability to retrieve aerosol information accurately. First, we show that the aerosol size distribution at SGP is at least bimodal. The notion that a more complex size distribution can be modeled with an appropriately selected monomodal distribution produces an unacceptable fit to the data once the separation of aerosol extinction from nitrogen dioxide absorption at short wavelengths is taken into consideration. Second, we find that the amount of retrievable aerosol information is limited by the wavelength range of the data. This is exemplified by the indeterminacy of the coarse‐mode effective radius and the interdependence in the retrievals of the fine‐mode effective radius and effective variance. Third, when the fine‐mode effective variance is constrained, an annual cycle in fine‐mode effective radius values emerges from the retrieval results, with a maximum in March and a minimum in September. Conceivably, changes in the effective variance could influence the observed pattern as well. The large margin of error in the coarse‐mode effective radius leads to relatively small error bars for the coarse‐ and fine‐mode optical depths, the fine‐mode effective radius, and ozone, except on those days when the coarse‐mode optical depth is high. Examining the retrieval results for different wavelength combinations of five RSS channels allows us to investigate whether or not the MFRSR channels are optimized to retrieve aerosol information or if a different filter set would increase the robustness of the retrievals. We show that replacing the 670 nm channel with one at either 375 or 1034 nm improves the retrieval accuracy. In particular, retrievals with the 1034 nm channel very closely reproduce the full RSS retrieval results, provided that the NO2 column amount can be determined by other means. The precision of the retrieved values of the fine‐mode effective radius is shown to be strongly sensitive to the precision of measured NO2 amounts; a margin of error in column NO2 of 0.3 Dobson units results in a corresponding margin of error of 0.04 μm in the fine‐mode effective radius. This confirms that aerosol sizes cannot be inferred accurately from optical depth spectra alone if either the amount of NO2 above a site is unknown or an inaccurate value is assumed.

Evaluation of a GCM subgrid cloud‐radiation interaction parameterization using cloud‐resolving model simulations

The mosaic approach of Liang and Wang (1997) for the general circulation model (GCM) parameterization of subgrid cloud‐radiation interactions is evaluated against the validated cloud‐resolving model (CRM) simulation of the Atmospheric Radiation Measurement (ARM) intensive observation period (IOP, June 22–July 17, 1997) at the Southern Great Plains (SGP) site. The CRM‐generated cloud statistics determines the required characteristic structure differences between three primary cloud genera (convective, anvil and stratiform). It is demonstrated that the mosaic approach with the CRM cloud statistics well simulates the CRM domain‐averaged radiative quantities. The result indicates that the mosaic approach of the cloud overlap based on the cloud genera differing in formation mechanisms and of the optical inhomogeneity by cloud water path scaling can capture, respectively, the dominant effects of the cloud geometric association and optical property variability within a GCM grid.

Remote Sensing of Atmospheric Water Vapor Using the Moderate Resolution Imaging Spectroradiometer

Abstract This paper presents first validation results for an algorithm developed for the retrieval of integrated columnar water vapor from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the polar-orbiting Terra and Aqua platforms. The algorithm is based on the absorption of reflected solar radiation by atmospheric water vapor and allows the retrieval of integrated water vapor above cloud-free land surfaces. A comparison of the retrieved water vapor with measurements of the Microwave Water Radiometer at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for a 10-month period in 2002 showed an rms deviation of 1.7 kg m−2 and a bias of 0.6 kg m−2. A comparison with radio soundings in central Europe from July 2002 to April 2003 showed an rms deviation of 2 kg m−2 and a bias of −0.8 kg m−2.

Evaluation of Cirrus Cloud Properties Derived from MODIS Data Using Cloud Properties Derived from Ground-Based Observations Collected at the ARM SGP Site

AbstractThe Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra satellite has been collecting global data since March 2000 and the one on the Aqua satellite since June 2002. In this paper, cirrus cloud properties derived from ground-based remote sensing data are compared with similar cloud properties derived from MODIS data on Terra. To improve the space–time correlation between the satellite and ground-based observations, data from a wind profiler are used to define the cloud advective streamline along which the comparisons are made. In this paper, approximately two dozen cases of cirrus are examined and a statistical approach to the comparison that relaxes the requirement that clouds occur over the ground-based instruments during the overpass instant is explored. The statistical comparison includes 168 cloudy MODIS overpasses of the Southern Great Plains (SGP) region and approximately 300 h of ground-based cirrus observations. The physical and radiative properties of cloud layers are derived from MODIS data separately by the MODIS Atmospheres Team and the Clouds and the Earth’s Radiant Energy System (CERES) Science Team using multiwavelength reflected solar and emitted thermal radiation measurements. Using two ground-based cloud property retrieval algorithms and the two MODIS algorithms, a positive correlation in the effective particle size, the optical thickness, the ice water path, and the cloud-top pressure between the various methods is shown, although sometimes there are significant biases. Classifying the clouds by optical thickness, it is demonstrated that the regionally averaged cloud properties derived from MODIS are similar to those diagnosed from the ground. Because of a conservative approach toward identifying thin cirrus pixels over this region, the area-averaged cloud properties derived from the MODIS Atmospheres MOD06 product tend to be biased slightly toward the optically thicker pixels. This bias tendency has implications for model validation and parameterization development applied to thin cirrus retrieved over SGP-like land surfaces. A persistent bias is also found in the derived cloud tops of thin cirrus with both satellite algorithms reporting cloud top several hundred meters less than that reported by the cloud radar. Overall, however, it is concluded that the MODIS retrieval algorithms characterize with reasonable accuracy the properties of thin cirrus over this region.

AMSU-B Observations of Mixed-Phase Clouds over Land

Abstract Measurements from passive microwave satellite instruments such as the Advanced Microwave Sounding Unit B (AMSU-B) are sensitive to both liquid and ice cloud particles. Radiative transfer modeling is exploited to simulate the response of the AMSU-B instrument to mixed-phase clouds over land. The plane-parallel radiative transfer model employed for the study accounts for scattering and absorption from cloud ice as well as absorption and emission from trace gases and cloud liquid. The radiative effects of mixed-phase clouds on AMSU-B window channels (i.e., 89 and 150 GHz) and water vapor line channels (i.e., 183 ± 1, 3, and 7 GHz) are studied. Sensitivities to noncloud parameters, including surface temperature, surface emissivity, and atmospheric temperature and water vapor profiles, are also quantified. Modeling results indicate that both cloud phases generally have significant radiative effects and that the 150- and 183 ± 7-GHz channels are typically the most sensitive channels to integrated cloud properties (i.e., liquid water path and ice water path). However, results also indicate that AMSU-B measurements alone are probably insufficient for retrieving all mixed-phase cloud properties of interest. These results are supported by comparisons of AMSU-B observations of a mixed-phase cloud over the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site with corresponding calculated clear-sky values.

Comparing ice cloud microphysical properties using CloudNET and Atmospheric Radiation Measurement Program data

A comparison of the microphysical properties of ice clouds, using lidar and radar data, is made for three sites: Cabauw (Netherlands), Atmospheric Radiation Measurement Program Southern Great Plains (ARM‐SGP) site (United States), and Chilbolton (United Kingdom). The effective particle size (Reff), extinction, and ice water content (IWC) are derived and correlated to each other, temperature, radar reflectivity, and depth into the cloud from cloud top (ΔZt). There is no indication for large seasonal differences of the ice microphysical properties; however, the Reff differences observed at the ARM‐SGP site are of the same magnitude as the error. The Chilbolton and Cabauw sites exhibit similar behavior in all cases while the ARM site shows large differences for some relationships, e.g., Reff(T, IWC). Within the sensitivity studies performed, it is not possible to construct a single Reff(T, IWC) parameterization valid at all three sites, and therefore it is not applicable in global models. It is possible to construct a single parameterization of ice water content related to temperature or to radar reflectivity. In all cases, an ice habit and particle size distribution assumption has to be made, resulting in different fits for different habits. When Reff is correlated to ΔZt for different classes of total cloud thicknesses (H), one can define a single parameterization, using parabolic descriptions, valid at the three sites and possibly on a global scale.

Climatology of Warm Boundary Layer Clouds at the ARM SGP Site and Their Comparison to Models

Abstract A 4-yr climatology (1997–2000) of warm boundary layer cloud properties is developed for the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) site. Parameters in the climatology include cloud liquid water path, cloud-base height, and surface solar flux. These parameters are retrieved from measurements produced by a dual-channel microwave radiometer, a millimeter-wave cloud radar, a micropulse lidar, a Belfort ceilometer, shortwave radiometers, and atmospheric temperature profiles amalgamated from multiple sources, including radiosondes. While no significant interannual differences are observed in the datasets, there are diurnal variations with nighttime liquid water paths consistently higher than daytime values. The summer months of June, July, and August have the lowest liquid water paths and the highest cloud-base heights. Model outputs of cloud liquid water paths from the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the Eta Model for 104 model output location time series (MOLTS) stations in the environs of the SGP central facility are compared to observations. The ECMWF and MOLTS median liquid water paths are greater than 3 times the observed values. The MOLTS data show lower liquid water paths in summer, which is consistent with observations, while the ECMWF data exhibit the opposite tendency. A parameterization of normalized cloud forcing that requires only cloud liquid water path and solar zenith angle is developed from the observations. The parameterization, which has a correlation coefficient of 0.81 with the observations, provides estimates of surface solar flux that are comparable to values obtained from explicit radiative transfer calculations based on plane-parallel theory. This parameterization is used to estimate the impact on the surface solar flux of differences in the liquid water paths between models and observations. Overall, there is a low bias of 50% in modeled normalized cloud forcing resulting from the excess liquid water paths in the two models. Splitting the liquid water path into two components, cloud thickness and liquid water content, shows that the higher liquid water paths in the model outputs are primarily a result of higher liquid water contents, although cloud thickness may a play a role, especially for the ECMWF model results.

Characterization of Upper-Troposphere Water Vapor Measurements during AFWEX Using LASE

AbstractWater vapor mass mixing ratio profiles from NASA's Lidar Atmospheric Sensing Experiment (LASE) system acquired during the Atmospheric Radiation Measurement (ARM)–First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX) are used as a reference to characterize upper-troposphere water vapor (UTWV) measured by ground-based Raman lidars, radiosondes, and in situ aircraft sensors over the Department of Energy (DOE) ARM Southern Great Plains (SGP) site in northern Oklahoma. LASE was deployed from the NASA DC-8 aircraft and measured water vapor over the ARM SGP Central Facility (CF) site during seven flights between 27 November and 10 December 2000. Initially, the DOE ARM SGP Cloud and Radiation Testbed (CART) Raman lidar (CARL) UTWV profiles were about 5%–7% wetter than LASE in the upper troposphere, and the Vaisala RS80-H radiosonde profiles were about 10% drier than LASE between 8 and 12 km. Scaling the Vaisala water vapor profiles to match the precipitable water vapor (PWV) measured by the ARM SGP microwave radiometer (MWR) did not change these results significantly. By accounting for an overlap correction of the CARL water vapor profiles and by employing schemes designed to correct the Vaisala RS80-H calibration method and account for the time response of the Vaisala RS80-H water vapor sensor, the average differences between the CARL and Vaisala radiosonde upper-troposphere water vapor profiles are reduced to about 5%, which is within the ARM goal of mean differences of less than 10%. The LASE and DC-8 in situ diode laser hygrometer (DLH) UTWV measurements generally agreed to within about 3%–4%. The DC-8 in situ frost point cryogenic hygrometer and Snow White chilled-mirror measurements were drier than the LASE, Raman lidars, and corrected Vaisala RS80H measurements by about 10%–25% and 10%–15%, respectively. Sippican (formerly VIZ Manufacturing) carbon hygristor radiosondes exhibited large variabilities and poor agreement with the other measurements. PWV derived from the LASE profiles agreed to within about 3% on average with PWV derived from the ARM SGP microwave radiometer. The agreement between the LASE and MWR PWV and the LASE and CARL UTWV measurements supports the hypotheses that MWR measurements of the 22-GHz water vapor line can accurately constrain the total water vapor amount and that the CART Raman lidar, when calibrated using the MWR PWV, can provide an accurate, stable reference for characterizing upper-troposphere water vapor.

The QME AERI LBLRTM: A Closure Experiment for Downwelling High Spectral Resolution Infrared Radiance

Abstract Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994–97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%–8% too strong in the 750–1000 cm−1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100–1300 cm−1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m−2 over a wide range of atmospheric states.

A Simulation Study of Shallow Moist Convection and Its Impact on the Atmospheric Boundary Layer

Abstract By comparing regional model simulations with the observations collected at the southern Great Plains (SGP) site and the tropical western Pacific (TWP) Nauru site of the Atmospheric Radiation Measurement (ARM) project, this paper evaluates the overall performance of a recently developed shallow cumulus parameterization scheme under different meteorological conditions. The scheme is incorporated into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). The simulations indicate that the shallow cumulus scheme can accurately simulate both marine shallow cumuli and the observed diurnal cycle of continental shallow cumuli. Both subgrid cloud properties and the resolved thermodynamic structures and the surface energy budget are well simulated by the model. Using the simulations performed in this study, the authors also investigate the impact of shallow cumuli on the boundary layer structure. The simulations indicate that maritime shallow convection moistens and cools the cloud ...

The diurnal cycle of shallow cumulus clouds over land: A single‐column model intercomparison study

AbstractAn intercomparison study for single‐column models (SCMs) of the diurnal cycle of shallow cumulus convection is reported. The case, based on measurements at the Atmospheric Radiation Measurement program Southern Great Plains site on 21 June 1997, has been used in a large‐eddy simulation intercomparison study before. Results of the SCMs reveal the following general deficiencies: too large values of cloud cover and cloud liquid water, unrealistic thermodynamic profiles, and high amounts of numerical noise. Results are also strongly dependent on vertical resolution.These results are analysed in terms of the behaviour of the different parametrization schemes involved: the convection scheme, the turbulence scheme, and the cloud scheme. In general the behaviour of the SCMs can be grouped in two different classes: one class with too strong mixing by the turbulence scheme, the other class with too strong activity by the convection scheme. The coupling between (subcloud) turbulence and the convection scheme plays a crucial role. Finally, (in part) motivated by these results several models have been successfully updated with new parametrization schemes and/or their present schemes have been successfully modified. © Royal Meteorological Society, 2004. S. Irons's contribution is Crown copyright

Light Scattering by Quasi-Spherical Ice Crystals

Abstract The shapes and single-scattering properties of small, irregular, quasi-spherical ice crystals, with equivalent radii between approximately 8 and 90 μm and size parameters from about 90 to 1000, are studied using two-dimensional images measured by a cloud particle imager in midlatitude cirrus during the 2000 Cloud Intensive Operation Period conducted over the Atmospheric Radiation Measurement program's Southern Great Plains site. A statistical shape analysis of the ice crystal images is carried out to obtain size-dependent relative standard deviations of radius and correlation functions of logradius, which together define the shape statistics of the sample ice crystals. The former describes the overall variation in the lengths of radius vectors defining the particle surface from a given origin, whereas the latter describes correlations of lengths of radius vectors as functions of angular distance between them. The logradius is essentially the natural logarithm of radius. There is no strong depende...

Comparison of cirrus optical depths derived from GOES 8 and surface measurements

Ground‐based passive radiometer measurements are used to validate satellite‐derived cirrus optical depths over the Atmospheric Radiation Measurement Program Southern Great Plains site during March 2000. Optical depths derived from direct beam measurements by a multifilter rotating shadow band radiometer were well correlated with those determined from the Geostationary Operational Environmental Satellite, especially in relatively homogenous cloud fields. Compared to the multifilter rotating shadow band radiometer (MFRSR) results, on average, the satellite retrieval overestimated optical depth by ∼0.67 (29%), even though 75% of the GOES values were within ±1.0 of the MFRSR results. Some of the bias is attributable to cloud inhomogeneities, mismatches in observed clouds, errors in the surface albedo, and possible errors in the ice crystal scattering phase function. The results demonstrate the potential for using MFRSR data, available over many parts of the globe, for validating satellite cloud retrievals in many different surface and atmospheric conditions.

Impact of a revised convective triggering mechanism on Community Atmosphere Model, Version 2, simulations: Results from short‐range weather forecasts

This study implements a revised convective triggering condition in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, Version 2 (CAM2), model to reduce its excessive warm season daytime precipitation over land. The new triggering mechanism introduces a simple dynamic constraint on the initiation of convection that emulates the collective effects of lower level moistening and upward motion of the large‐scale circulation. It requires a positive contribution from the large‐scale advection of temperature and moisture to the existing positive convective available potential energy (CAPE) for model convection to start. In contrast, the original convection triggering function in CAM2 assumes that convection is triggered whenever there is positive CAPE, which results in too frequent warm season convection over land arising from strong diurnal variation of solar radiation. We examine the impact of the new trigger on CAM2 simulations by running the climate model in numerical weather prediction (NWP) mode so that more available observations and high‐frequency NWP analysis data can be used to evaluate model performance. We show that the modified triggering mechanism has led to considerable improvements in the simulation of precipitation, temperature, moisture, clouds, radiations, surface temperature, and surface sensible and latent heat fluxes when compared to the data collected from the Atmospheric Radiation Measurement (ARM) Program at its Southern Great Plains (SGP) site. Similar improvements are also seen over other parts of the globe. In particular, the surface precipitation simulation has been significantly improved over both the continental United States and around the globe; the overestimation of high clouds in the equatorial tropics has been substantially reduced; and the temperature, moisture, and zonal wind are more realistically simulated. Results from this study also show that some systematic errors in the CAM2 climate simulations can be detected in the early stage of model integration. Examples are the extremely overestimated high clouds in the tropics in the vicinity of Intertropical Convergence Zone and the spurious precipitation maximum to the east of the Rockies. This has important implications in studies of these model errors since running the climate model in NWP mode allows us to perform a more in‐depth analysis during a short time period where more observations are available and different model errors from various processes have not compensated for the systematic errors.

In situ aerosol profiles over the Southern Great Plains cloud and radiation test bed site: 2. Effects of mixing height on aerosol properties

The goal of this study was to determine under what meteorological conditions, if any, measurements of aerosol properties made at the Earth's surface are representative of aerosol properties measured within the column of air above the surface. Specifically, this study uses instrumentation from the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site to determine how the observed mixing height (MH) and the degree of mixing affects the vertical variation of aerosol extensive and intensive properties. The MH was estimated by applying the Heffter [1980] technique with a critical lapse rate of 0.001 K m−1 to the available radiosonde data. This estimate was then used to determine whether each vertical aerosol profile flight leg from 59 flights was within or above the atmospheric boundary layer (ABL). Although the aerosol extensive properties, such as light absorption by particles σap, light scattering by particles σsp, and total extinction by particles σext measured within the ABL were highly correlated with the surface measurements (R2 = 0.74, 0.88, and 0.88, respectively), the airborne measurements of σap were systematically lower (slope = 0.77). By contrast, the σsp and σext regression line slopes were 0.99 and 1.00. The aerosol extensive properties measured above the ABL were poorly correlated with surface values and were almost an order of magnitude lower than the simultaneous measurements made within the ABL. Aerosol intensive properties such as the single‐scattering albedo ϖo, the hemispheric backscatter fraction b, and the Ångström exponent å exhibited a similar behavior (R2 = 0.74, 0.61, and 0.55, respectively) but had regression line slopes within the ABL of 0.88, 0.75, and 0.62, respectively. There were no statistically significant correlations between the intensive aerosol properties measured above the ABL and those measured at the surface. Limiting the analysis to well‐mixed days with near‐neutral static stability did not significantly improve the results. Thus the hypothesis that the best agreement between surface measurements and those within the ABL will occur when the atmosphere is well mixed was not supported by this data set.

In situ aerosol profiles over the Southern Great Plains cloud and radiation test bed site: 1. Aerosol optical properties

Aerosol optical properties were measured over the Southern Great Plains (SGP) cloud and radiation test bed site using a light aircraft (Cessna C‐172N). The aircraft flew level legs at altitudes between 500 m and 3500 m several times per week over the course of 2 years in order to obtain a statistically representative data set of in situ aerosol vertical profiles. Instrumentation on the aircraft was similar to that at the surface SGP site so that measurements at the surface and aloft could easily be compared. Measured parameters included total light scattering, backscattering, and absorption, while calculated parameters included single‐scattering albedo, backscatter fraction, and Ångström exponent. Statistical plots of aerosol optical properties and their variation in the lower column (0–4000 m) showed that over the course of the 2 years studied, albedo, backscatter fraction, and Ångström exponent were fairly invariant with altitude (at least up to 1800 m). Despite the vertical consistency the correlation between column average and surface values for single‐scattering albedo, backscatter fraction, and Ångström exponent tended to be quite low, with R2 ranging from 0.3 to 0.6 and linear regression slopes ranging from 0.2 to 0.6. These results suggest that long‐term surface aerosol measurements capture the column aerosol properties but may not be as representative of day‐to‐day variations in the column. Comparison of aerosol optical depth (AOD) calculated from the vertical profiles with other measurements of AOD made at SGP (i.e., by the Cimel Sun photometer and the multifilter rotating shadowband radiometer (MFRSR)) showed fair correlation (R2 ∼ 0.7 Cimel, R2 ∼ 0.8 MFRSR), although the aircraft AODs tend to have a consistent offset of −0.04, even after incorporating a correction for supermicrometer aerosol and stratospheric aerosol.