ARM SGP Site Research Articles

Assessment of Warm and Dry Bias over ARM SGP Site in E3SMv2 and E3SM-MMF

Abstract Many climate models exhibit a dry and warm bias over the central United States during the summer months, including the Energy Exascale Earth System Model (E3SM) and its Multiscale Modeling Framework (MMF) configuration. Understanding the causes of this bias is important to shine a light on this common model error and reduce the uncertainty in future projections. In this study, we use E3SMv2 and E3SM-MMF to assess how parameterized and resolved convection affect temperature and precipitation biases over the Southern Great Plains site of the Atmospheric Radiation Measurement program. Both configurations overestimate near-surface temperature and underestimate precipitation at the ARM SGP site. The bias is associated with a lack of low-level clouds during days without precipitation and too much incoming solar radiation causing the surface to warm. Low-level cloud fraction in E3SM-MMF during the nonprecipitating days is lower in comparison to E3SMv2 and observation, consistent with the larger warm bias. We also find that the underestimated precipitation can be characterized as “too frequent, too weak” in E3SMv2 and “too rare, too intense” in E3SM-MMF. These deficiencies conspire to sustain the warm and dry bias over the central United States.

An Investigation of the Ice Cloud Detection Sensitivity of Cloud Radars Using the Raman Lidar at the ARM SGP Site

The ice cloud detection sensitivity of the millimeter cloud radar (MMCR) and the Ka-band Zenith radar (KAZR) is investigated using a collocated Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains site. Only profiles that are transparent to the RL with ice clouds only are considered in this study. The MMCR underestimates the RL ice cloud optical depth (COD) by 20%. The MMCR detects no ice clouds in 37% of the profiles. These profiles where ice cloud goes undetected by the MMCR typically contain very optically thin clouds, with a mean RL ice COD of 0.03. Higher ice cloud detection sensitivity is found for the KAZR, which underestimates the RL ice COD by 15%. The decrease in the ice COD bias for the KAZR compared to the MMCR is largely due to a decrease in the ice COD bias for the situation where the transparent profiles with ice clouds are detected by both the RL and cloud radar. The climatic net ice cloud radiative effects (CREs) from the RL at the top of the atmosphere (TOA) and the surface are 3.2 W m−2 and −0.6 W m−2, respectively. The ice CREs at the TOA and surface are underestimated for the MMCR by 0.7 W m−2 and 0.16 W m−2 (21% and 29%) and underestimated for the KAZR by 0.6 W m−2 and 0.14 W m−2 (17% and 24%). The ice clouds undetected by the cloud radars led to underestimating the climatic net cloud heating rates below 150 hPa by about 0–0.04 K day−1.

All‐Sky Aerosol Direct Radiative Effects at the ARM SGP Site

AbstractAll‐sky aerosol direct radiative effect (DRE) was estimated for the first time at the Atmospheric Radiation Measurement Southern Great Plains site using multiyear ground‐based observations. The NASA Langley Fu‐Liou radiation model was employed. Observed inputs for the radiation model include aerosol and cloud vertical extinction profile from Raman lidar; spectral aerosol optical depth, single‐scattering albedo, and asymmetry factor from Aerosol Robotic Network; cloud water content profiles from radars; temperature and water vapor profiles from radiosondes; and surface shortwave spectral albedo from radiometers. A cloudy‐sky radiative closure experiment was performed. The relative mean differences between modeled and observed surface downwelling shortwave total fluxes were 6% (7%) for transparent (opaque) cloudy‐skies. The estimated annual mean all‐sky aerosol DRE is −2.130.54 W m−2 at the top of atmosphere (TOA) and −5.950.87 W m−2 at the surface, compared to −3.000.58 W m−2 and −6.851.00 W m−2, respectively, under clear‐sky conditions. The seasonal cycle of all‐sky aerosol DRE is similar to that of the clear‐sky, except with secondary influences of the clouds: The cloud radiative effect is strongest (most negative) in the spring, which reduces the all‐sky aerosol DRE. The relative uncertainties in all‐sky aerosol DRE due to measurement errors are generally comparable to those in clear‐sky conditions except for the aerosol single‐scattering albedo. The TOA all‐sky aerosol DRE relative uncertainty due to aerosol single‐scattering albedo uncertainty is larger than that in clear‐sky, leading to a larger total relative uncertainty. The measurement errors in cloud properties have small effects on the all‐sky aerosol DRE.

A 17-year climatology of temperature inversions above clouds over the ARM SGP site: The roles of cloud radiative effects

Abstract Atmospheric temperature inversions, i.e., temperatures increasing with altitude, modulate both radiative and buoyancy fluxes in the atmosphere. A temperature inversion layer often occurs immediately above a cloud layer that cools radiatively and thereby strengthens the capping temperature inversion. This study aims to investigate the characteristics of temperature inversions above clouds and their relationships with cloud-top radiative cooling. Using a 17-year (January 2001 to December 2017) high-quality and continuous radiosonde dataset collected at the Atmospheric Radiation Measurement Southern Great Plains Central Facility site, key temperature inversion parameters, namely, the occurrence frequency (dp), depth (dz), temperature difference (dT), and gradient (dT/dz), are derived for single- and double-layer clouds (SLC and DLC, respectively). The occurrence frequency of temperature inversions above single-layer clouds decreases dramatically as cloud tops rise from low to high altitudes. When an overlying higher cloud layer is present, the inversion becomes less frequent, shallower, and weaker than without it. This may be because higher clouds weaken the cloud-top radiative cooling of the underneath clouds by enhancing downwelling infrared radiation. This is supported by radiative transfer simulations. There are distinctive seasonal cycles of cloud-top radiative cooling for high clouds that are primarily driven by variations in shortwave heating. Distinctive seasonal cycles of temperature inversions also occurred regardless of the cloud regime (SLC or DLC) and altitude (low or high clouds). They appear to be driven by the seasonal cycle of cloud coverage (i.e., a greater amount of clouds undergoes stronger area-mean radiative cooling) although the shortwave heating seasonal cycle also plays a role for high clouds. Cloud radiative cooling cannot explain the diurnal cycle of temperature inversions.

The Impact of Surface Heterogeneities and Land‐Atmosphere Interactions on Shallow Clouds Over ARM SGP Site

AbstractContinental shallow clouds are an important component of the land‐atmosphere coupled climate system because of their role in modulating energy and water budgets. The parameterization of these clouds in climate models presents a significant challenge. We evaluate the potential impact of subgrid‐scale (for climate models) land‐atmosphere interactions on shallow clouds using nested large‐eddy simulations (LESs). We compare LESs that allow for land‐atmosphere interactions to ones that artificially suppress all or part of them by smoothing out surface heterogeneities in surface heat, moisture and radiation fluxes within the domain. The LES domains are coupled to an interactive land surface model and nested inside a mesoscale domain. Three summertime shallow convection cases over the Department of Energy Atmospheric Radiation Measurement Facility's Southern Great Plains site are examined. A consistent increase in cloud water content is observed in all cases when surface heterogeneities and the land‐atmosphere interactions they induce in the LES domain are removed. By comparing experiments where only surface flux heterogeneities induced by cloud shadows are removed to ones where all surface flux heterogeneities are removed, we find that cloud shading‐induced surface heterogeneities can have a larger impact on shallow convection than static land surface heterogeneities in our cases. Furthermore, the impact of cloud shading on cloud water content and cloud size is found to vary significantly with the solar incidence angle. Our results suggest that the impact of cloud shadows needs to be considered when parameterizing land‐atmosphere interactions in the presence of shallow clouds for regional or global climate models.

Remote sensing of ground-level PM2.5 combining AOD and backscattering profile

Abstract The remote sensing of PM2.5 (particulate matter concentration with aerodynamic diameter d ≤ 2.5 μm) mass concentration is mostly based on the measurements of AOD (aerosol optical depth) that is a common product of satellite and ground instruments which measure spectral radiance. The relationship between surface PM2.5 and column integrated AOD is found associated with vertical and size distribution of aerosols. In this study, a non-linear regression model combining AOD and near surface backscatter for estimation of PM2.5 is developed and tested based on 6 years ground measurements from HUBC (Howard University Beltsville Campus) facility. Overall, the non-linear model explains ~ 60% of the variability in hourly PM2.5. The RMSE (root-mean-square error) is ~ 5.83 μg/m 3 with a corresponding average PM2.5 of 15.43 μg/m 3 . That is a big improvement to the linear model using AOD alone (~ 40% of the variability, RMSE is ~ 7.14 μg/m 3 ). The ceilometer measured near surface backscatter is found to improve the estimation of PM2.5-AOD relationship the most compared to other factors, such as aerosol size indicator, surface temperature, relative humidity, wind speed and pressure especially when AOD is large (AOD ≥ 0.3). As aerosol size indicator, two Angstrom exponents are calculated by AOD at three wavelengths of 415, 500, 860 nm and are found also important to the PM2.5-AOD relationship. In addition to the HUBC site, the model is tested based on the 4 years (2012 to 2015) measurements from ARM SGP site and the nearest EPA site. The results also show the significant role of the ceilometer measured near surface backscatter on improving estimation of PM2.5. This study illustrated the potential of ceilometer on investigation of air pollution. With broad ceilometer network, ground-level particle concentrations can be better determined.

Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

Abstract. The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.

Cloud properties derived from two lidars over the ARM SGP site

Active remote sensors such as lidars or radars can be used with other data to quantify the cloud properties at regional scale and at global scale. Relative to radar, lidar remote sensing is sensitive to very thin and high clouds but has a significant limitation due to signal attenuation in the ability to precisely quantify the properties of clouds with a cloud optical thickness larger than 3. The cloud properties for all levels of clouds are derived and distributions of cloud base height (CBH), top height (CTH), physical cloud thickness (CT), and optical thickness (COT) from local statistics are compared. The goal of this study is (1) to establish a climatology of macrophysical and optical properties for all levels of clouds observed over the ARM SGP site and (2) to estimate the discrepancies between the two remote sensing systems (pulse energy, sampling, resolution, etc.). Our first results tend to show that the MPL, which are the primary ARM lidars, have a distinctly limited range within which all of these cloud properties are detectable, especially cloud top and cloud thickness, but this can include cloud base particularly during summer daytime period. According to the comparisons between RL and MPL, almost 50% of situations show a signal to noise ratio too low (smaller than 3) for the MPL in order to detect clouds higher than 7km during daytime period in summer. Consequently, the MPL-derived annual cycle of cirrus cloud base (top) altitude is biased low, especially for daylight periods, compared with those derived from the RL data, which detects cloud base ranging from 7.5 km in winter to 9.5 km in summer (and tops ranging from 8.6 to 10.5 km). The optically thickest cirrus clouds (COT > 0.3) reach 50% of the total population for the Raman lidar and only 20% for the Micropulse lidar due to the difference of pulse energy and the effect of solar irradiance contamination. A complementary study using the cloud fraction derived from the Micropulse lidar for clouds below 5 km and from the Raman lidar for cloud above 5 km allows for better estimation of the total cloud fraction between the ground and the top of the atmosphere. This study presents the diurnal cycle of cloud fraction for each season in comparisons with Long et al.'s (2006) cloud fraction calculation derived from radiative flux analysis. Copyright © 2011 by the American Geophysical Union.

Retrievals of cloud ice water path by combining ground cloud radar and satellite high‐frequency microwave measurements near the ARM SGP site

A framework to retrieve ice water paths over a broad area by combining observations of surface cloud radar and satellite high‐frequency microwave measurements in a physically consistent way is presented. The surface cloud radar provides the statistics of vertical distribution of ice water content, while the satellite retrievals use those statistics to broaden a point measurement to an areal measurement. This study seeks to improve retrievals by adopting newly available ice microphysical properties from recent in situ observations, and by treating single scattering properties based on discrete dipole approximation simulations of realistic nonspherical ice particles. First, a new radar reflectivity‐ice water content relation is derived using backscattering cross sections calculated from six types of nonspherical ice particles. Ice water content profiles derived from radar reflectivity profiles are then used to calculate brightness temperatures at satellite observing frequencies by a radiative transfer model, which forms an a priori database for a Bayesian ice water path retrieval algorithm. Comparison between the satellite and surface radar retrievals shows that the two agree better for cases with ice water paths greater than 100 g m−2. For lower ice water paths, the difference between satellite and surface radar retrievals becomes large, presumably because of the insensitivity of the microwave scattering to optically thin ice clouds.

The impact of surface albedo on the retrievals of low‐level stratus cloud properties: An updated parameterization

An updated version of Dong et al. (1998, hereinafter referred to as D98) parameterization is developed from a total of 40 hours of data with a broad range of surface albedos (0.1–0.8) during the 2000–2002 winter seasons at the DOE ARM SGP site. The updated parameterization includes the impact of surface albedo on the retrievals of stratus cloud microphysical and radiative properties, and has a significant improvement over D98 when surface albedo is high. Comparing the retrievals, the cloud‐droplet effective radii (re) calculated from the updated parameterization have a higher correlation coefficient (0.733) and lower Root‐Mean‐Square (RMS) error (1.74 μm or 17.4%) than those (0.602, 4.0 μm or 40%) from the D98. The cloud albedos also have a much higher correlation coefficient (0.983) and lower RMS (3%) than those (0.465, 26%) from the D98. The upper limit of surface albedo is 0.3 in applying the D98.

On the seemingly incompatible parcel and globally integrated views of the energetics of triggered atmospheric deep convection over land

AbstractThe energetics of the diurnal cycle of atmospheric deep convection over land remain difficult to understand and simulate accurately with current cumulus parametrizations. Furthermore, a proper formulation has remained elusive owing to seeming incompatibilities between, on the one hand, the parcel view of energetics which relies on such concepts as Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN), and, on the other hand, the globally integrated view, which relies on such concepts as Moist Available Energy (MAE), reference states, and energy conversion terms. While the MAE is intuitively the global counterpart of the parcel‐defined CAPE, there seems to be no global analogue to the parcel‐defined concept of energy barrier attached to CIN. To gain insights into this issue, a new cost function PE is introduced to quantify the amount of positive or negative energy required for a given sounding to undergo an arbitrary adiabatic rearrangement of mass, and which encompasses both the parcel‐defined and global energy concepts as particular cases. The function PE offers a complementary view of the stability and energy characteristics of atmospheric soundings, whose local minima are naturally associated with the reference states of the system.It is established that:(a) MAE is essentially equivalent to CAPE multiplied by a mass conversion factor Mb which scales as the amount of convectively unstable boundary‐layer air. Using the available summer 1997 IOP data from the ARM–SGP site, Mb is found to correlate with CAPE, which suggests the existence of a functional relationship between CAPE and MAE; if further confirmed, this result would considerably simplify the computation of MAE.(b) A global counterpart to the parcel‐defined concept of energy barrier can only be defined if the system considered admits several reference states, and not one as is classically assumed. In that case, energy barriers naturally arise as the amount of energy required to switch from one reference state to another. In the context of triggered deep convection, there must be at least two reference states: a shallow one, which is the actual state (or a slightly modified one if there is boundary layer CAPE), and a deep one associated with the release of MAE/CAPE; the energy barrier separating these two reference states naturally defines a generalized CIN.In the limited context of the above‐mentioned IOP ARM data, it is further shown that:(c) Spatially averaged conditions exhibiting potential instability to deep convection may be associated with individual soundings having widely different stability characteristics, including absolute stability, potential instability, and absolute instability; this suggests that triggered deep convection may not necessarily be the result of a parcel's vertical kinetic energy exceeding its negative buoyancy, but rather from the destruction of convective inhibition (i.e. production of absolute instability) in a local region.(d) A few local soundings exhibit multiple reference states, corresponding roughly to multiple levels of neutral buoyancy. These may allow for convective clouds with cloud‐top heights significantly lower than those classically predicted by the undiluted ascent of a boundary‐layer air parcel up to its highest level of neutral buoyancy, even in the absence of complex entrainment scenarios. Copyright © 2004 Royal Meteorological Society

A high‐resolution oxygen A‐band and water vapor band spectrometer

A prototype high‐resolution oxygen A‐band and water vapor band spectrometer (HAWS) and new theoretical framework have been developed and demonstrated to study the applicability of photon path length statistics in the remote sensing of clouds, aerosols, and water vapor, particularly in addressing current challenges such as the detection of thin layers of clouds and aerosols especially over surfaces with high albedo, reducing retrieval errors due to the presence of non‐spherical particles, and enhancing the vertical resolution of retrieved atmospheric constituents. This work also provides a basis for the application of path length distribution in the development and validation of radiative transfer parameterizations that account for the effects of cloud inhomogeneity. The HAWS successfully achieves an out‐of‐band rejection of better than 10−5, a resolution of better than 0.5 cm−1, and high signal‐to‐noise ratio, which are crucial to retrieval of atmospheric information through high‐resolution spectrometry in the A‐band and water vapor band. A field campaign was conducted to demonstrate the capabilities of HAWS and the new retrieval algorithm at the cloud and radiation testbed at ARM SGP site in Oklahoma, where a comprehensive set of radiometric, passive, and active sensors provide continuous and concurrent measurements of clouds, aerosols, water vapor, and other atmospheric properties. Results show that in the A‐band thick and multiple layer clouds significantly enhance the mean and variance of the photon path length distribution, thin cirrus condition produce relatively small mean distribution and variance, and mean path lengths comparable to or smaller than the solar airmass were associated with clear sky cases at large solar zenith angles. The mean path length and variance in the water vapor band differs from that in the A‐band due to the spatial inhomogeneity of water vapor amounts, particularly in association with cloud layers.

Comparison of cloud top heights derived from MISR stereo and MODIS CO2‐slicing

The EOS‐TERRA MODIS and MISR instruments provide radiances for independent spectral and stereo retrievals of cloud top height (CTH), respectively. Collocated and coincident CTH retrievals were compared against each other and with coincident millimeter‐wavelength cloud radar (MMCR) retrievals over the British Isles and the ARM SGP site. This inter‐comparison suggests close agreement between MMCR, MODIS and MISR when they detect the same CTHs. When MISR detected high clouds, MISR stereo CTH was generally higher than MODIS CO2‐slicing CTH. However, for large areas in most of the 27 scenes studied here, high clouds were detected by MODIS but not by MISR. These high clouds occurred during periods of multi‐layered clouds. Inspection of all off‐nadir MISR radiances during these periods indicated that MISR has sufficient sensitivity to detect these clouds, but not with the innermost 3 MISR cameras used for stereo CTH retrieval.

Satellite remote sensing of land surface temperatures: Application of the atmospheric correction method and split-window technique to data of ARM-SGP site

The performance of algorithms for the satellite remote sensing of land surface temperatures based on an atmospheric correction method and a split-window technique was examined. For this purpose, we employed comprehensive data collected over the Atmospheric Radiation Measurement Program (ARM) Southern Great Plain (SGP) Cloud and Radiation Testbed (CART) site for a number of manually determined clear and mostly clear dates during 1997 and 1999 with cloud coverage of less than 10%. The data sources included brightness temperature data measured by the Advanced Very High Resolution Radiometer (AVHRR) on-board National Oceanic and Atmospheric Administration (NOAA)-12 and NOAA-14, collocated and coincident observed surface temperatures derived from the solar and IR radiation observing system (SIROS) and solar and IR station (SIRS) data, and balloon-borne atmospheric sounding profiles. For the application of the atmospheric correction method, we used the Moderate Resolution Transmittance Model (MODTRAN) 3.7 to compute transmittances and atmospheric radiances. In the present study, comparison of the retrieved surface temperatures with observations obtained at the central and external facility sites over the SGP area shows that the accuracy of the atmospheric correction scheme is closer to the requirement that is acceptable for estimating surface latent heat fluxes than the split-window method.

Comparison of POLDER cloud phase retrievals to active remote sensors measurements at the ARM SGP site

In our present study, cloud boundaries derived from a combination of active remote sensors at the ARM SGP site are compared to POLDER cloud top phase index which is derived from polarimetric measurements using an innovative method. This approach shows the viability of the POLDER phase retrieval algorithm, and also leads to interesting results. In particular, the analysis demonstrates the sensitivity of polarization measurements to ice crystal shape and indicates that occurrence of polycrystalline ice clouds has to be taken into account in order to improve the POLDER phase retrieval algorithm accuracy. Secondly, the results show that a temperature threshold of 240 K could serve for cloud top particle phase classification. Considering the limitations of the analysis, the temperature threshold could be biased high, but not by more than about 5 degrees.