Abstract

Routine in situ observations of the atmosphere taken in flight by commercial aircraft provide atmospheric profiles with greater temporal density and, in many parts of the country, at more locations than the operational radiosonde network. Thousands of daily temperature and wind observations are provided by largely complementary systems, the Airborne Meteorological Data Relay (AMDAR) and the Tropospheric Airborne Meteorological Data Reporting (TAMDAR). All TAMDAR aircraft also measure relative humidity while a subset of AMDAR aircraft are equipped with the Water Vapor Sensing System (WVSS) measure specific humidity. One year of AMDAR/WVSS and TAMDAR observations are evaluated against operational National Weather Service (NWS) radiosondes to characterize the performance of these systems in similar environments. For all observed variables, AMDAR reports showed both smaller average differences and less random differences with respect to radiosondes than the corresponding TAMDAR observations. Observed differences were not necessarily consistent with known radiosonde biases. Since the systems measure different humidity variables, moisture is evaluated in both specific and relative humidity using both aircraft and radiosonde temperatures to derive corresponding moisture variables. Derived moisture performance is improved when aircraft-based temperatures are corrected prior to conversion. AMDAR observations also show greater consistency between different aircraft than TAMDAR observations do. The small variability in coincident WVSS humidity observations indicates that they may prove more reliable than humidity observations from NWS radiosondes.

Abstract

Ceilometer observations of cloud cover are an important component of the automated weather observation network. However, the accuracy of its measurements of cloud amount is impacted by the limited vertical range and areal extent of its observations. A multiyear collocated dataset of observations from a laser ceilometer, a total sky imager (TSI), and a micropulse lidar (MPL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility is used to simulate the observations of operational ceilometers and to analyze the magnitude of the errors associated with ceilometer-based observations of cloud amount. The limited areal coverage of ceilometers results in error when skies are heterogeneous, but these errors are small compared to those caused by the limited vertical range: observations of clear sky or few clouds are often in error as the instrument cannot detect the presence of upper-level clouds. The varying quantities of upper-level clouds mean that errors are diurnally and seasonally dependent, with the greatest error at the SGP site happening in the morning and summer, respectively. Overall, the spatial homogeneity and low base of stratus clouds means that ceilometer-based observations of overcast skies are the most accurate, with a root-mean-square error of cloud fraction in overcast conditions an order of magnitude lower than for the dataset as a whole.

Abstract

The addition of moisture observations via the Water Vapor Sensing System (WVSS) from about 150 aircraft available operationally through the World Meteorological Organization (WMO) Aircraft Meteorological Data Relay (AMDAR) program now provides highly reliable thermodynamic profiles of the troposphere. The nearly 900 profiles available daily provide greater temporal and spatial density than the operational radiosonde network over many parts of the United States. Previous studies comparing WVSS reports with specially collocated radiosondes have documented the quality and consistency of the WVSS observations. These studies, however, have been limited for short periods at a single location. This study expands on the earlier evaluations by using operational U.S. radiosondes from 2015 in a variety of locations, seasons, and climates. Comparison profiles at radiosonde sites were calculated in pressure layers and then interpolated to terrain-following sigma coordinates to account for the differences in elevations of comparison sites and provide a better means of integrating the higher vertical resolution of AMDAR observations taken in the boundary layer. Overall, systematic differences between the WVSS and radiosondes are smallest just above the surface, with the WVSS observations being slightly moister than the radiosondes aloft, with WVSS reports being moister during ascent than descent—possibly the result of small hysteresis effects. Standard deviations averaged 1.3 g kg⁻¹ near the surface over the yearlong period. Differences varied by season and region. Overall, the results indicate that WVSS observations are compatible with radiosonde reports and can be used with high confidence to fill temporal and spatial data gaps.

Abstract

Mobile systems equipped with remote sensing instruments capable of simultaneous profiling of temperature, moisture, and wind at high temporal resolutions can offer insights into atmospheric phenomena that the operational network cannot. Two recently developed systems, the Space Science and Engineering Center (SSEC) Portable Atmospheric Research Center (SPARC) and the Collaborative Lower Atmosphere Profiling System (CLAMPS), have already experienced great success in characterizing a variety of phenomena. Each system contains an Atmospheric Emitted Radiance Interferometer for thermodynamic profiling and a Halo Photonics Stream Line Doppler wind lidar for kinematic profiles. These instruments are augmented with various in situ and remote sensing instruments to provide a comprehensive assessment of the evolution of the lower troposphere at high temporal resolution (5 min or better). While SPARC and CLAMPS can be deployed independently, the common instrument configuration means that joint deployments with well-coordinated data collection and analysis routines are easily facilitated.

In the past several years, SPARC and CLAMPS have participated in numerous field campaigns, which range from mesoscale campaigns that require the rapid deployment and teardown of observing systems to multiweek fixed deployments, providing crucial insights into the behavior of many different atmospheric boundary layer processes while training the next generation of atmospheric scientists. As calls for a nationwide ground-based profiling network continue, SPARC and CLAMPS can play an important role as test beds and prototype nodes for such a network.

Abstract

Temporal changes in stability and shear associated with the development of thunderstorms are quantified using the enhanced temporal resolution of combined Atmospheric Emitted Radiance Interferometer (AERI) thermodynamic profile retrievals and National Oceanic and Atmospheric Administration (NOAA) 404-MHz wind profiler observations. From 1999 to 2003, AERI systems were collocated with NOAA wind profilers at five sites in the southern Great Plains of the United States, creating a near-continuous dataset of atmospheric soundings in both the prestorm and poststorm environments with a temporal resolution of up to 10 min between observations.

Median values for several standard severe weather indices were calculated for tornadic storms and nontornadic supercells. It was found that instability generally increases throughout the preconvective period, reaching a peak roughly 1 h before a tornado forms or a nontornadic supercell forms large hail. Wind shear for both tornadic and nontornadic storms starts to increase roughly 3 h before storm time. However, indices are highly variable between time and space and may not be representative of the environment at large.

Abstract

Atmospheric bores have been shown to have a role in the initiation and maintenance of elevated convection. Previous observational studies of bores have been case studies of more notable events. However, this creates a selection bias toward extraordinary cases, while discussions of the differences between bores that favor convective initiation and maintenance and bores that do not are lacking from the literature. This study attempts to fill that gap by analyzing a high-temporal-resolution thermodynamic profile composite of eight bores observed by multiple platforms during the Plains Elevated Convection at Night (PECAN) campaign in order to assess the impact of bores on the environment. The time–height cross section of the potential temperature composite displays quasi-permanent parcel displacements up to 900 m with the bore passage. Low-level lifting is shown to weaken the capping inversion and reduce convective inhibition (CIN) and the level of free convection (LFC). Additionally, low-level water vapor increases by about 1 g kg⁻¹ in the composite mean. By assessing variability across the eight cases, it is shown that increases in low-level water vapor result in increases to convective available potential energy (CAPE), while drying results in decreased CAPE. Most cases resulted in decreased CIN and LFC height with the bore passage, but only some cases resulted in increased CAPE. This suggests that bores will increase the potential for convective initiation, but future research should be directed toward better understanding cases that result in increased CAPE as those are the types of bores that will increase severity of convection.

Abstract

Observations of thermodynamic and kinematic parameters associated with derivatives of the thermodynamics and wind fields, namely, advection, vorticity, divergence, and deformation, can be obtained by applying Green’s theorem to a network of observing sites. The five nodes that comprise the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) profiling network, spaced 50–80 km apart, are used to obtain measurements of these parameters over a finite region. To demonstrate the applicability of this technique at this location, it is first applied to gridded model output from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model, using profiles from the locations of ARM network sites, so that values calculated from this method can be directly compared to finite difference calculations. Good agreement is found between both approaches as well as between the model and values calculated from the observations. Uncertainties for the observations are obtained via a Monte Carlo process in which the profiles are randomly perturbed in accordance with their known error characteristics. The existing size of the ARM network is well suited to capturing these parameters, with strong correlations to model values and smaller uncertainties than a more closely spaced network, yet it is small enough that it avoids the tendency for advection to go to zero over a large area.

Abstract

Observing thermodynamic profiles within the planetary boundary layer is essential to understanding and predicting atmospheric phenomena because of the significant exchange of sensible and latent heat between the land and atmosphere within that layer. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based infrared spectrometer used to obtain the vertical profiles of temperature and water vapor mixing ratio. Most AERIs are only capable of zenith views, although the Marine AERI (M-AERI) has a design that allows it to view various elevation angles. In this study, we quantify the improvement in the information content and accuracy of the retrieved profiles when nonzenith angles are included, as is common with microwave radiometer profilers. The impacts of the additional scan angles are quantified through both a synthetic study and with M-AERI observations from the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) campaign. The simulation study shows that low elevation angles contain more information content for temperature whereas high elevation angles have more information content for water vapor. Outside of very humid environments, the addition of low elevation angles also results in lower root-mean-square errors when compared with high angles for both temperature and water vapor mixing ratio, although this is primarily a result of averaging multiple observations together to reduce instrument noise. Real-world results from the ACAPEX dataset indicate similar results as were found for the simulation study, although not all predicted benefits are realized because of the small sample size and observational uncertainties.

Abstract

Profiles of atmospheric temperature and water vapor from remotely sensed platforms provide critical observations within the temporal and spatial gaps of the radiosonde network. The 2017 National Academies of Science Decadal Survey highlighted that observations of the planetary boundary layer (PBL) from the current space-based observing system are not of the necessary accuracy or resolution for monitoring and predicting high-impact weather phenomena. One possible solution to improving observations of the PBL is supplementing the existing space-based observing system with a network of ground-based profilers. A synthetic information content study is developed utilizing profiles from the Atmospheric Radiation Measurement (ARM) program sites at the Southern Great Plains (SGP), east North Atlantic (ENA), and North Slope of Alaska (NSA) to assess the benefits, in terms of degrees of freedom (DOF), vertical resolution, and uncertainties, of a synergy between the ground-based Atmospheric Emitted Radiance Interferometer (AERI) with space-based hyperspectral infrared (IR) sounders. A combination of AERI with any of the three polar-orbiting IR sounders: the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), or the Infrared Atmospheric Sounding Interferometer (IASI), results in a DOF increase of 30%–40% in the surface-to-700-hPa layer compared to the space-based instrument alone. Introducing AERI measurements to the observing system also results in significant improvements to vertical resolution and uncertainties in the bottom 1000 m of the atmosphere compared to CrIS measurements alone. A synergy of CrIS and AERI exceeds the 1-km-vertical-resolution goal set by the Decadal Survey in the lowest 1000 m.

Abstract

While fractional entrainment rates for cumulus clouds have typically been derived from airborne observations, this limits the size and scope of available datasets. To increase the number of continental cumulus entrainment rate observations available for study, an algorithm for retrieving them from ground-based remote sensing observations has been developed. This algorithm, called the Entrainment Rate In Cumulus Algorithm (ERICA), uses the suite of instruments at the Southern Great Plains (SGP) site of the U.S. Department of Energy's Atmospheric Radiation Measurement Program (ARM) Climate Research Facility as inputs into a Gauss–Newton optimal estimation scheme, in which an assumed guess of the entrainment rate is iteratively adjusted through intercomparison of modeled cloud attributes to their observed counterparts. The forward model in this algorithm is the explicit mixing parcel model (EMPM), a cloud parcel model that treats entrainment as a series of discrete entrainment events. A quantified value for the uncertainty in the retrieved entrainment rate is also returned as part of the retrieval. Sensitivity testing and information content analysis demonstrate the robust nature of this method for retrieving accurate observations of the entrainment rate without the drawbacks of airborne sampling. Results from a test of ERICA on 3 months of shallow cumulus cloud events show significant variability of the entrainment rate of clouds in a single day and from one day to the next. The mean value of 1.06 km⁻¹ for the entrainment rate in this dataset corresponds well with prior observations and simulations of the entrainment rate in cumulus clouds.