Southern Great Plains Site Research Articles

Characterization of Vertical Velocity and Drop Size Distribution Parameters in Widespread Precipitation at ARM Facilities

AbstractExtended, high-resolution measurements of vertical air motion and median volume drop diameter D0 in widespread precipitation from three diverse Atmospheric Radiation Measurement Program (ARM) locations [Lamont, Oklahoma, Southern Great Plains site (SGP); Niamey, Niger; and Black Forest, Germany] are presented. The analysis indicates a weak (0–10 cm−1) downward air motion beneath the melting layer for all three regions, a magnitude that is to within the typical uncertainty of the retrieval methods. On average, the hourly estimated standard deviation of the vertical air motion is 0.25 m s−1 with no pronounced vertical structure. Profiles of D0 vary according to region and rainfall rate. The standard deviation of 1-min-averaged D0 profiles for isolated rainfall rate intervals is 0.3–0.4 mm. Additional insights into the form of the raindrop size distribution are provided using available dual-frequency Doppler velocity observations at SGP. The analysis suggests that gamma functions better explain paired velocity observations and radar retrievals for the Oklahoma dataset. This study will be useful in assessing uncertainties introduced in the measurement of precipitation parameters from ground-based and spaceborne remote sensors that are due to small-scale variability.

Retrievals of cloud optical depth and effective radius from Thin-Cloud Rotating Shadowband Radiometer measurements

[1] A Thin-Cloud Rotating Shadowband Radiometer (TCRSR) was developed and deployed in a field test at the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plains site. The TCRSR measures the forward-scattering lobe of the direct solar beam (i.e., the solar aureole) through an optically thin cloud (optical depth < 8). We applied the retrieval algorithm of Min and Duan (2005) to the TCRSR measurements of the solar aureole to derive simultaneously the cloud optical depth (COD) and cloud drop effective radius (DER), subsequently inferring the cloud liquid-water path (LWP). After careful calibration and preprocessing, our results indicate that the TCRSR is able to retrieve simultaneously these three properties for optically thin water clouds. Colocated instruments, such as the MultiFilter Rotating Shadowband Radiometer (MFRSR), atmospheric emitted radiance interferometer (AERI), and Microwave Radiometer (MWR), are used to evaluate our retrieval results. The relative difference between retrieved CODs from the TCRSR and those from the MFRSR is less than 5%. The distribution of retrieved LWPs from the TCRSR is similar to those from the MWR and AERI. The differences between the TCRSR-based retrieved DERs and those from the AERI are apparent in some time periods, and the uncertainties of the DER retrievals are discussed in detail in this article.

Evaluating Weather Research and Forecasting (WRF) Model Predictions of Turbulent Flow Parameters in a Dry Convective Boundary Layer

AbstractWeather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern Great Plains (SGP). The first studied case exhibited a dryline passage during the simulation window, and the second studied case was used to examine the CBL in a post-cold-frontal environment. The model runs were conducted with three boundary layer parameterization schemes (Yonsei University, Mellor–Yamada–Janjić, and asymmetrical convective) commonly employed within the WRF model environment to represent effects of small-scale turbulent transport. A study domain was centered over the Atmospheric Radiation Measurement Program SGP site in Lamont, Oklahoma. Results show that near-surface flow and turbulence parameters are predicted reasonably well with all tested horizontal grid spacings (1, 2, and 4 km) and that value added through refining grid spacing was minimal at best for conditions considered in this study. In accord with this result, it was suggested that the 16-fold increase in computing overhead associated with changing from 4- to 1-km grid spacing was not justified. Therefore, only differences among schemes at 4-km spacing were presented in detail. WRF model predictions generally overestimated the contribution to turbulence generation by mechanical forcing over buoyancy forcing in both studied CBL cases. Nonlocal parameterization schemes were found to match observational data more closely than did the local scheme, although differences among the predictions with all three schemes were relatively small.

The influence of observed cirrus microphysical properties on shortwave radiation: A case study over Oklahoma

[1] The shortwave radiative effect of an ice cloud observed over the Atmospheric Radiation Measurement program's Southern Great Plains site in Oklahoma is investigated. Airborne microphysical data from a cloud particle imager, optical array probes, and forward scattering probes are used to construct vertical profiles of the size and shape distributions of ice crystals. Due to uncertainties associated with measuring the sizes and shapes of small ice crystals with maximum dimensions less than 120 μm, five alternate size-shape distributions are derived and combined with existing databases of wavelength-dependent single-scattering properties of idealized ice crystals to obtain vertical profiles of optical properties. The dependence of the surface and the top-of-the-atmosphere fluxes on these uncertainties is simulated with a radiative transfer model. In addition, surface fluxes are compared against measurements at the surface. It is found that the differences between the modeled and measured fluxes are too large to be explained by uncertainties in the shape and concentrations of small ice crystals. Sensitivity tests suggest that the discrepancies occur because the real optical thickness is larger than that derived from the aircraft profiles most of the time. When the optical thickness was derived based on modeled and measured direct fluxes, the modeled total downward flux agreed well with the measurements. Slightly (less than 10%) reducing the asymmetry parameter, which is possibly associated with the presence of surface roughness, air bubble inclusions or other nonidealities in ice crystals, may further improve the agreement with observations.

Examination of turbulent entrainment-mixing mechanisms using a combined approach

Turbulent entrainment-mixing mechanisms are investigated by applying a combined approach to the aircraft measurements of three drizzling and two nondrizzling stratocumulus clouds collected over the U.S. Department of Energy's Atmospheric Radiation Measurement Southern Great Plains site during the March 2000 cloud Intensive Observation Period. Microphysical analysis shows that the inhomogeneous entrainment-mixing process occurs much more frequently than the homogeneous counterpart, and most cases of the inhomogeneous entrainment-mixing process are close to the extreme scenario, having drastically varying cloud droplet concentration but roughly constant volume-mean radius. It is also found that the inhomogeneous entrainment-mixing process can occur both near the cloud top and in the middle level of a cloud, and in both the nondrizzling clouds and nondrizzling legs in the drizzling clouds. A new dimensionless number, the scale number, is introduced as a dynamical measure for different entrainment-mixing processes, with a larger scale number corresponding to a higher degree of homogeneous entrainment mixing. Further empirical analysis shows that the scale number that separates the homogeneous from the inhomogeneous entrainment-mixing process is around 50, and most legs have smaller scale numbers. Thermodynamic analysis shows that sampling average of filament structures finer than the instrumental spatial resolution also contributes to the dominancemore » of inhomogeneous entrainment-mixing mechanism. The combined microphysical-dynamical-thermodynamic analysis sheds new light on developing parameterization of entrainment-mixing processes and their microphysical and radiative effects in large-scale models.« less

A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data

Atmospheric states from the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the North American Regional Reanalysis (NARR) are compared with data from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site, including the ARM continuous forcing product and Cloud Modeling Best Estimate (CMBE) soundings, during the period 1999–2001 to understand their validity for single-column model (SCM) and cloud-resolving model (CRM) forcing datasets. Cloud fraction, precipitation, and radiation information are also compared to determine what errors exist within these reanalyses. For the atmospheric state, ARM continuous forcing and the reanalyses have good agreement with the CMBE sounding information, with biases generally within 0.5 K for temperature, 0.5 m s−1 for wind, and 5% for relative humidity. Larger disagreements occur in the upper troposphere (p &lt; 300 hPa) for temperature, humidity, and zonal wind, and in the boundary layer (p &gt; 800 hPa) for meridional wind and humidity. In these regions, larger errors may exist in derived forcing products. Significant differences exist for vertical pressure velocity, with the largest biases occurring during the spring upwelling and summer downwelling periods. Although NARR and MERRA share many resemblances to each other, ARM outperforms these reanalyses in terms of correlation with cloud fraction. Because the ARM forcing is constrained by observed precipitation that gives the adequate mass, heat, and moisture budgets, much of the precipitation (specifically during the late spring/early summer) is caused by smaller-scale forcing that is not captured by the reanalyses. While reanalysis-based forcing appears to be feasible for the majority of the year at this location, it may have limited usage during the late spring and early summer, when convection is common at the ARM SGP site. Both NARR and MERRA capture the seasonal variation of cloud fractions (CFs) observed by ARM radar–lidar and Geostationary Operational Environmental Satellite (GOES) with high correlations (0.92–0.78) but with negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows better agreement for both shortwave (SW) and longwave (LW) fluxes except for LW-down (due to a negative bias in water vapor): NARR has significant positive bias for SW-down and negative bias for LW-down under clear-sky and all-sky conditions. The NARR biases result from a combination of too few clouds and a lack of sufficient extinction by aerosols and water vapor in the atmospheric column. The results presented here represent only one location for a limited period, and more comparisons at different locations and longer periods are needed.

Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains central facility

Abstract. We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

A spectral method for retrieving cloud optical thickness and effective radius from surface-based transmittance measurements

Abstract. We introduce a new spectral method for the retrieval of optical thickness and effective radius from cloud transmittance that relies on the spectral slope of the normalized transmittance between 1565 nm and 1634 nm, and on cloud transmittance at a visible wavelength. The standard dual-wavelength technique, which is traditionally used in reflectance-based retrievals, is ill-suited for transmittance because it lacks sensitivity to effective radius, especially for optically thin clouds. Using the spectral slope rather than the transmittance itself enhances the sensitivity of transmittance observations with respect to the effective radius. This is demonstrated by applying it to the moderate spectral resolution observations from the Solar Spectral Flux Radiometer (SSFR) and Shortwave Spectroradiometer (SWS), and by examining the retrieval uncertainties of the standard and the spectral method for data from the DOE ARM Southern Great Plains (SGP) site and a NOAA ship cruise (ICEALOT). The liquid water path (LWP) is derived from the retrieved optical thickness and effective radius, based on two different assumptions about the cloud vertical profile, and compared to the simultaneous observations from a microwave radiometer. Optical thickness and effective radius is also compared to MODIS retrievals. In general, the effective radius uncertainties were much larger for the standard retrieval than for the spectral retrieval, particularly for thin clouds. When defining 2 μm as upper limit for the tolerable uncertainty of the effective radius, the standard method returned only very few valid retrievals for clouds with an optical thickness below 25. For the analyzed ICEALOT data (mean optical thickness 23), the spectral method provided valid retrievals for 84 % of the data (24 % for the standard method). For the SGP data (mean optical thickness 44), both methods provided a high return of 90 % for the spectral method and 78 % for the standard method.

Sky cover from MFRSR observations

Abstract. The diffuse all-sky surface irradiances measured at two nearby wavelengths in the visible spectral range and their modeled clear-sky counterparts are the main components of a new method for estimating the fractional sky cover of different cloud types, including cumuli. The performance of this method is illustrated using 1-min resolution data from a ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR). The MFRSR data are collected at the US Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site during the summer of 2007 and represent 13 days with cumuli. Good agreement is obtained between estimated values of the fractional sky cover and those provided by a well-established independent method based on broadband observations.

Investigating cloud radar sensitivity to optically thin cirrus using collocated Raman lidar observations

[1] The sensitivity of the millimeter cloud radar (MMCR) to optically thin single-layer cirrus at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site is investigated using collocated Raman lidar observations. The sensitivity is characterized in terms of cloud optical depth (OD) and infrared (IR) radiative flux using over three years of coincident Raman lidar and MMCR observations. For cases when the Raman lidar is not fully attenuated (OD < 2.0) the MMCR detects approximately 70% of the total cloud OD with the majority of missed cloud OD occurring near cloud top. If only MMCR observations are used for computing cloudy top-of-the-atmosphere (TOA) IR flux, the missed cloud OD results in TOA flux biases from 0 to over 100 W/m2; however, the most frequently occurring bias is approximately 16 W/m2. This result highlights the importance of combining Raman lidar, or other sensitive cloud lidars that are able to measure cloud extinction directly, with the MMCR in order to accurately characterize the cloud radiative forcing for thin cirrus cases.

Parameterization of Riming Intensity and Its Impact on Ice Fall Speed Using ARM Data

Abstract Riming within mixed-phase clouds can have a large impact on the prediction of clouds and precipitation within weather and climate models. The increase of ice particle fall speed due to riming has not been considered in most general circulation models (GCMs), and many weather models only consider ice particles that are either unrimed or heavily rimed (not a continuum of riming amount). Using the Atmospheric Radiation Measurement (ARM) Program dataset at the Southern Great Plains (SGP) site of the United States, a new parameterization for riming is derived, which includes a diagnosed rimed mass fraction and its impact on the ice particle fall speed. When evaluated against a vertical-pointing Doppler radar for stratiform mixed-phase clouds, the new parameterization produces better ice fall speeds than a conventional parameterization. The new parameterization is tested in the recently developed Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model (AM3) using prescribed sea surface temperature (SST) simulations. Compared with the standard (CTL) simulation, the new parameterization increases ice amount aloft by ∼20%–30% globally, which reduces the global mean outgoing longwave radiation (OLR) by ∼2.8 W m−2 and the top-of-atmosphere (TOA) shortwave absorption by ∼1.5 W m−2. Global mean precipitation is also slightly reduced, especially over the tropics. Overall, the new parameterization produces a comparable climatology with the CTL simulation and it improves the physical basis for using a fall velocity larger than a conventional parameterization in the current AM3.

A Simple Method to Retrieve Cloud Properties from Atmospheric Transmittance and Liquid Water Column Measurements

Abstract A deeper knowledge of the effects and interactions of clouds in the climatic system requires developing both satellite and ground-based methods to assess their optical properties. A simple method based on a parameterized inversion of a radiative transfer model is proposed to estimate the optical depth of thick liquid water clouds from the atmospheric transmittance at 415 nm, solar zenith angle, surface albedo, effective droplet radius, and aerosol load. When concurrent measurements of atmospheric transmittance and liquid water path are available, the effective radius of the droplet size distribution can also be retrieved. The method is compared with a reference algorithm from Min and Harrison, which uses similar data, except aerosol load. When applied to measurements performed at the Southern Great Plains site of the Atmospheric Radiation Measurement Program, the mean bias deviation between the proposed method and the reference method is only −0.08 in units of optical depth, whereas the standard deviation is only 0.46. For the effective droplet radius estimations, the mean bias deviation is −0.13 μm, and the standard deviation is 0.14 μm. Maximum relative deviations are lower than 5% and 8% for cloud optical depth and effective radius, respectively. The effects on these retrievals of the assumed aerosol optical depth and surface albedo are also analyzed.

Surface summertime radiative forcing by shallow cumuli at the Atmospheric Radiation Measurement Southern Great Plains site

[1] Although shallow cumuli are common over large areas of the globe, their impact on the surface cloud radiative forcing (CRF) has not been carefully evaluated. This study addresses this shortcoming by analyzing data collected during conditions with single-layer shallow cumuli over eight summers (2000 through 2007) at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. During periods with clouds, the average shortwave and longwave CRF at the surface are −45.5 W m−2 (out of 612 W m−2 estimated for clear-sky conditions) and +15.9 W m−2 (out of −105.2 W m−2 estimated for clear-sky conditions), respectively. Instances of cloud-induced enhancement of the shortwave irradiance over that estimated for clear skies are observed approximately 20% of the time and are caused by spatial and temporal inhomogeneity of cumuli. Such enhancement is responsible for occurrences of positive shortwave CRF with instantaneous values as large as +75 W m−2. The total amount of shortwave and longwave energy deposited at the surface over a period of time depends nonlinearly on the fractional sky cover, and the largest values of the deposited energy occur for intermediate cloud amounts between 0.4 and 0.6.

Diagnosis of multilayer clouds using photon path length distributions

Photon path length distribution is sensitive to 3‐D cloud structures. A detection method for multilayer clouds has been developed, by utilizing the information of photon path length distribution. The photon path length method estimates photon path length information from the low level, single‐layer cloud structure that can be accurately observed by a millimeter‐wave cloud radar (MMCR) combined with a micropulse lidar (MPL). As multiple scattering within the cloud layers and between layers would substantially enhance the photon path length, the multilayer clouds can be diagnosed by evaluating the estimated photon path information against observed photon path length information from a co‐located rotating shadowband spectrometer (RSS). The measurements of MMCR‐MPL and RSS at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site have been processed for the year 2000. Cases studies illustrate the consistency between MMCR‐MPL detection and the photon path length method under most conditions. However, the photon path length method detected some multilayer clouds that were classified by the MMCR‐MPL as single‐layer clouds. From 1 year statistics at the ARM SGP site, about 27.7% of single‐layer clouds detected by the MMCR‐MPL with solar zenith angle less than 70° and optical depth greater than 10 could be multilayer clouds. It suggests that a substantial portion of single‐layer clouds detected by the MMCR‐MPL could also be influenced by some “missed” clouds or by the 3‐D effects of clouds.

Retrieval of aerosol optical depth in vicinity of broken clouds from reflectance ratios: case study

Abstract. A recently developed reflectance ratio (RR) method for the retrieval of aerosol optical depth (AOD) is evaluated using extensive airborne and ground-based data sets collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS), which took place in June 2007 over the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site. A detailed case study is performed for a field of single-layer shallow cumuli observed on 12 June 2007. The RR method is applied to retrieve the spectral values of AOD from the reflectance ratios measured by the MODIS Airborne Simulator (MAS) for two pairs of wavelengths (660 and 470 nm, 870 and 470 nm) collected at a spatial resolution of 0.05 km. The retrieval is compared with an independent AOD estimate from three ground-based Multi-filter Rotating Shadowband Radiometers (MFRSRs). The interpolation algorithm that is used to project MFRSR point measurements onto the aircraft flight tracks is tested using AOD derived from NASA Langley High Spectral Resolution Lidar (HSRL). The RR AOD estimates are in a good agreement (within 5%) with the MFRSR-derived AOD values for the 660-nm wavelength. The AODs obtained from MAS reflectance ratios overestimate those derived from MFRSR measurements by 15–30% for the 470-nm wavelength and underestimate the 870-nm AOD by the same amount.

Evaluation of the NASA GISS Single-Column Model Simulated Clouds Using Combined Surface and Satellite Observations

Abstract Three years of surface and Geostationary Operational Environmental Satellite (GOES) data from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to evaluate the NASA GISS Single Column Model (SCM) simulated clouds from January 1999 to December 2001. The GOES-derived total cloud fractions for both 0.5° and 2.5° grid boxes are in excellent agreement with surface observations, suggesting that ARM point observations can represent large areal observations. Low (&amp;lt;2 km), middle (2–6 km), and high (&amp;gt;6 km) levels of cloud fractions, however, have negative biases as compared to the ARM results due to multilayer cloud scenes that can either mask lower cloud layers or cause misidentifications of cloud tops. Compared to the ARM observations, the SCM simulated most midlevel clouds, overestimated low clouds (4%), and underestimated total and high clouds by 7% and 15%, respectively. To examine the dependence of the modeled high and low clouds on the large-scale synoptic patterns, variables such as relative humidity (RH) and vertical pressure velocity (omega) from North American Regional Reanalysis (NARR) data are included. The successfully modeled and missed high clouds are primarily associated with a trough and ridge upstream of the ARM SGP, respectively. The PDFs of observed high and low occurrence as a function of RH reveal that high clouds have a Gaussian-like distribution with mode RH values of ∼40%–50%, whereas low clouds have a gammalike distribution with the highest cloud probability occurring at RH ∼75%–85%. The PDFs of modeled low clouds are similar to those observed; however, for high clouds the PDFs are shifted toward higher values of RH. This results in a negative bias for the modeled high clouds because many of the observed clouds occur at RH values below the SCM-specified stratiform parameterization threshold RH of 60%. Despite many similarities between PDFs derived from the NARR and ARM forcing datasets for RH and omega, differences do exist. This warrants further investigation of the forcing and reanalysis datasets.

An assessment of the absolute accuracy of the Atmospheric Infrared Sounder v5 precipitable water vapor product at tropical, midlatitude, and arctic ground‐truth sites: September 2002 through August 2008

The Atmospheric Infrared Sounder (AIRS) is the first of a series of satellite sensors that exploit high spectral resolution and broad spectral coverage of the midinfrared to improve the retrieval accuracy of passive infrared sounding. The AIRS atmospheric retrieval goals are to obtain 1 K accuracy for 1 km layers below 100 mb for temperature and 10% for 2 km layers for water vapor in clear and most cloud conditions. The AIRS total column precipitable water vapor (PWV) is obtained by integrating the vertical profile of water vapor mixing ratio derived from cloud‐cleared radiances. The accuracy goal of the AIRS PWV product is 5%. This paper provides a validation of the AIRS PWV product at three distinct climate sites over the nearly full range of total water amounts observed on Earth (between 0.1 and 6.5 cm). Six years (September 2002 to August 2008) of AIRS v5 retrievals of PWV are evaluated against ground‐based microwave radiometer (MWR) data at three Department of Energy Atmospheric Radiation Measurement program (ARM) sites. The accuracy of the MWR PWV retrieval is estimated to be between 1% and 3%. This study shows that the agreement between the MWR and AIRS retrievals of PWV is within 5% at all three ARM climate sites for most conditions. The notable exceptions are (1) very dry cases (PWV &lt; 1 cm) over the Southern Great Plains (SGP) land site during both daytime and nighttime, where AIRS is too moist by 15%–30% and (2) nighttime observations over the SGP land site for PWV &gt; 1 cm, where AIRS is too dry by about 10%. The moist bias for low water amounts (usually observed during the winter) over land could be a surface emissivity–related error since very little bias is seen at the ARM Arctic site for similar water amounts. The cause of the dry bias at nighttime over land for moderate water amounts is not determined by this study. However, a spatial map of the diurnal bias in monthly AIRS water amount suggests that this effect is related to meteorological conditions in the U. S. Great Plains, which in the summertime is characterized by a moist boundary layer. The diurnal error in AIRS PWV at the SGP site seen with respect to the MWR data are confirmed by PWV amounts derived from a coincident ground‐based GPS receiver.

Mechanisms Affecting the Transition from Shallow to Deep Convection over Land: Inferences from Observations of the Diurnal Cycle Collected at the ARM Southern Great Plains Site

AbstractSummertime observations for 11 yr from the Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site are used to investigate mechanisms controlling the transition from shallow to deep convection over land. It is found that a more humid environment immediately above the boundary layer is present before the start of late afternoon heavy precipitation events. The higher moisture content is brought by wind from the south. Greater boundary layer inhomogeneity in moist static energy, temperature, moisture, and horizontal wind before precipitation begins is correlated to larger rain rates at the initial stage of precipitation. In an examination of afternoon rain statistics, higher relative humidity above the boundary layer is correlated to an earlier onset and longer duration of afternoon precipitation events, whereas greater boundary layer inhomogeneity and atmospheric instability in the 2–4-km layer above the surface are positively correlated to the total rain amount and the maximum rain rate. Although other interpretations may be possible, these observations are consistent with theories for the transition from shallow to deep convection that emphasize the role of a moist lower free troposphere and boundary layer inhomogeneity.

Comparison of measured and modeled outgoing longwave radiation for clear‐sky ocean and land scenes using coincident CERES and AIRS observations

Clear‐sky outgoing longwave radiation (OLR) is computed using the Atmospheric and Environmental Research (AER), Inc., Rapid Radiative Transfer Model (RRTM) for comparison with the observations of the Clouds and the Earth's Radiant Energy System (CERES) for both ocean and land scenes. CERES clear‐sky OLR is in agreement with RRTM model calculations to 0.2% accuracy using best estimate radiosondes (BE) launched coincident with NASA Aqua overpasses at the Atmospheric Radiation Measurement Southern Great Plains (SGP) site and 0.8% using retrieved profiles of temperature, water vapor, ozone, and surface parameters from the Atmospheric Infrared Sounder (AIRS) on the Aqua platform. A partial flux analysis using AIRS radiances implies an accuracy for the RRTM model in the far infrared of 0.4% (about 0.5 W/m2) for wave numbers less than 650 cm−1 (wavelengths greater than 15.4 μm). CERES minus model biases over clear‐sky ocean are similar to previously published results. Ordering the results according to the magnitude of the measured minus model mean bias for nighttime, tropical, ocean gives: +0.57 ± 1.9 W/m2 (Dessler/Fu‐Liou), +0.83 ± 1.5 W/m2 (Huang/MODTRAN5), +1.6 ± 1.6 W/m2 (Moy/RRTM), +3.7 ± 2.1 W/m2 (Dessler/Chou). Comparison of observed minus modeled OLR over land are included in this study. Excluding nonfrozen ocean, a mean difference over land of +2.0 W/m2 for nighttime cases and +1.0 W/m2 for daytime cases is found where the land classes are weighted inversely by their standard error. The nighttime bias is quite consistent across all the land classes. The daytime bias shows less consistency with a tendency toward larger CERES minus AIRS RRTM OLR bias for the land classes with smaller vegetation fraction. Comparison of clear‐sky CERES and AIRS RRTM OLR over cold snow‐/ice‐covered surfaces (mainly in the polar regions) is complicated by the use of the MODIS cloud mask in the identification of the clear CERES footprints used in the comparison. Clear scenes over cold surfaces can be identified more reliably in the daytime, for which the comparison between CERES and AIRS RRTM is better than 1.2 W/m2 indicating good agreement.

CloudSat Studies of Stratiform Precipitation Systems Observed in the Vicinity of the Southern Great Plains Atmospheric Radiation Measurement Site

Abstract The spaceborne W-band (94 GHz) radar on board the CloudSat polar-orbiting satellite offers new opportunities for retrieving parameters of precipitating cloud systems. CloudSat measurements can resolve the vertical cross sections of such systems. The radar brightband features, which are commonly present when observing stratiform precipitating systems, allow the vertical separation of the ice, mixed, and liquid precipitating hydrometeor layers. In this study, the CloudSat data are used to simultaneously retrieve ice water path (IWP) values for ice layers of precipitating systems using absolute radar reflectivity measurements and mean rainfall rates Rm in the liquid hydrometeor layers using the attenuation-based reflectivity gradient method. The retrievals were performed for precipitating events observed in the vicinity of the Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Climate Research Facility. The retrieval results indicated that IWP values in stratiform precipitating systems vary from a few hundreds up to about 10 thousands of grams per meter squared, and the mean rain rates were in a general range between 0.5 and about 12 mm h−1. On average, mean rainfall increases with an increase in ice mass observed above the melting layer; the corresponding mean correlation coefficient is about 0.35, although events with higher correlation as well as those with no appreciable correlation were observed. Horizontal advection, wind shear, and vertical air motions might be some of the reasons for decorrelation between IWP and Rm retrieved for the same vertical atmospheric column. A mean statistical relation between IWP and Rm derived from CloudSat retrievals is in good agreement with the data obtained from multiwavelength ground-based cloud radar measurements at the SGP site.