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The 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging from 0 to 2 g kg−1 at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded an RMSE of 1.14 g kg−1 in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales on the order of ten to hundreds of kilometers.

Accurate simulation of planetary boundary layer height (PBLH) is key to greenhouse gas emission estimation, air quality prediction, and weather forecasting. This paper describes an extensive performance assessment of several Weather Research and Forecasting (WRF) Model configurations in which novel observations from ceilometers, surface stations, and a flux tower were used to study their ability to reproduce the PBLH and the impact that the urban heat island (UHI) has on the modeled PBLHs in the greater Washington, D.C., area. In addition, CO2 measurements at two urban towers were compared with tracer transport simulations. The ensemble of models used four PBL parameterizations, two sources of initial and boundary conditions, and one configuration including the building energy parameterization urban canopy model. Results have shown low biases over the whole domain and period for wind speed, wind direction, and temperature, with no drastic differences between meteorological drivers. We find that PBLH errors are mostly positively correlated with sensible heat flux errors and that modeled positive UHI intensities are associated with deeper modeled PBLs over the urban areas. In addition, we find that modeled PBLHs are typically biased low during nighttime for most of the configurations with the exception of those using the MYNN parameterization, and these biases directly translate to tracer biases. Overall, the configurations using the MYNN scheme performed the best, reproducing the PBLH and CO2 molar fractions reasonably well during all hours and thus opening the door to future nighttime inverse modeling.

A network of automated weather stations (AWS) with ceilometers can be used to detect sky conditions, aerosol dispersion, and mixing layer heights, in addition to the routine surface meteorological parameters (temperature, pressure, humidity, etc.). Currently, a dense network of AWSs that observe all of these parameters does not exist in the United States even though networks of them with ceilometers exist. These networks normally use ceilometers for determining only sky conditions. Updating AWS networks to obtain those nonstandard observations with ceilometers, especially mixing layer height, across the United States would provide valuable information for validating and improving weather/climate forecast models. In this respect, an aerosol-based mixing layer height detection method, called the combined-hybrid method, is developed and evaluated for its uncertainty characteristics for application in the United States. Four years of ceilometer data from the National Weather Service Ceilometer Proof of Concept Project taken in temperate, maritime polar, and hot/arid climate regimes are utilized in this evaluation. Overall, the method proved to be a strong candidate for estimating mixing layer heights with ceilometer data, with averaged uncertainties of 237 ± 398 m in all tested climate regimes and 69 ± 250 m when excluding the hot/arid climate regime.

This paper presents a case study of a strong low-level jet (LLJ) that was observed about 20 km off the coast of Ocean City, Maryland, during a measurement campaign in the summer of 2013. Doppler wind lidar observations offshore, together with analyses of 4-km WRF Model data and NARR data, are used to reconstruct the forcing mechanisms that led to the growth and rapid collapse of the jet offshore as well as to differentiate the forcing mechanisms resulting in an LLJ farther inland. It was observed that the LLJ over the mid-Atlantic coastal plain decreased gradually throughout the early morning hours relative to the LLJ along the coastal ocean as a downslope wind moved eastward from the Appalachian Mountains. The forcing of the LLJ was a result of both thermal and mechanical mechanisms linked to the topography, while synoptic forcing from an approaching cold front led to a downslope wind. Data from a wind profiler near Cambridge, Maryland, also showed an LLJ, but forced by different regional conditions, emphasizing the difficulties of inferring wind conditions offshore from onshore observations. The sudden breakdown of the jet offshore appears to have been a result of an interaction with a downslope wind from the Appalachian Mountains. This particular case study highlights the 1) importance of both large-scale and regional forcing, 2) impact that topographical forcing farther inland had on offshore wind, and 3) different responses in the wind profile as a downslope wind moved across the mid-Atlantic region.

The Water Vapor Variability-Satellite/Sondes (WAVES) 2006 field campaign provided a contiguous 5-day period of concentrated high-resolution measurements to examine finescale boundary layer phenomena under the influence of a summertime subtropical high over the mid-Atlantic region that is characterized by complex geography. A holistic analytical approach to low-level wind observations was adopted to identify the low-level flow structures and patterns of evolution on the basis of airmass properties and origination. An analysis of the measurements and the other available observations is consistent with the classic depiction of the daytime boundary layer development but revealed a pronounced diurnal cycle that was categorized into three stages: (i) daytime growth of the convective boundary layer, (ii) flow intensification into a low-level jet regime after dusk, and (iii) interruption by a downslope wind regime after midnight. The use of the field campaign data allows for the differentiation of the latter two flow regimes by their directions with respect to the orientation of the Appalachian Mountains and their airmass origins. Previous studies that have investigated mountain flows and low-level jet circulations have focused on regions with overt geographic prominence, stark gradients, or frequent reoccurrences, whereby such meteorological phenomena exhibit a clear signature and can be easily isolated and diagnosed. The results of this study provide evidence that similar circulation patterns operate in nonclassic locations with milder topography and atmospheric gradients, such as the mid-Atlantic region. The new results have important implications for the understanding of the mountain-forced flows and some air quality problems during the nocturnal period.

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night. To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

Water vapor mixing ratio retrieval using the Howard University Raman lidar is presented with emphasis on three aspects: (i) comparison of the lidar with collocated radiosondes and Raman lidar, (ii) investigation of the relationship between atmospheric state variables and the relative performance of the lidar and sonde (in particular, their poor agreement), and (iii) comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 campaign. Ensemble averaging of water vapor mixing ratio data from 10 nighttime comparisons with Vaisala RS92 radiosondes shows, on average, an agreement within ±10%, up to ∼8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20% over the first 7 km (10% below 4 km). A grid analysis, defined in the temperature–relative humidity space, was developed to characterize the lidar–radiosonde agreement and quantitatively localizes regions of strong and weak correlations as a function of altitude, temperature, or relative humidity. Three main regions of weak correlation emerge: (i) regions of low relative humidity and low temperature, (ii) regions of moderate relative humidity at low temperatures, and (iii) regions of low relative humidity at moderate temperatures. Comparison of Atmospheric Infrared Sounder and Tropospheric Emission Sounder satellite retrievals of moisture with those of Howard University Raman lidar showed a general agreement in the trend, but the satellites miss details in atmospheric structure because of their low resolution. A relative difference of about ±20% is usually found between lidar and satellite measurements for the coincidences available.

One of the important goals of NASA’s Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE) was to further the understanding of the evolution of tropical anvil clouds generated by deep convective systems. An important step toward understanding the radiative properties of convectively generated anvil clouds is to study their life cycle. Observations from ground-based radar, geostationary satellite radiometers, aircraft, and radiosondes during CRYSTAL-FACE provided a comprehensive look at the generation of anvil clouds by convective systems over South Florida during July 2002. This study focused on the relationship between convective rainfall and the evolution of the anvil cloud shield associated with convective systems over South Florida on 23 July 2002, during the CRYSTAL-FACE experiment. Anvil clouds emanating from convective cells grew downwind (to the southwest), reaching their maximum area at all temperature thresholds 1–2 h after the active convective cells collapsed. Radar reflectivity data revealed that precipitation-sized anvil particles extended downwind with the cloud tops. The time lag between maximum rainfall and maximum anvil cloud area increased with system size and rainfall. Observations from airborne radar and analysis of in situ cloud particle size distribution measurements in the anvil region suggested that gravitational size sorting of cloud particles dispersed downshear was a likely mechanism in the evolution of the anvil region. Linear regression analysis suggested a positive trend between this time lag and maximum convective rainfall for this case, as well as between the time lag and maximum system cloud cover. The injection of condensate into the anvil region by large areas of intense cells and dispersal in the upper-level winds was a likely explanation to cause the anvil cloud-top area to grow for 1–2 h after the surface convective rainfall began to weaken. In future work these relationships should be evaluated in differing regimes of shear, stability, or precipitation efficiency, such as over the tropical oceans, in order to generalize the results. The results of this study implied that for these cloud systems, the maximum in latent heating (proportional to rainfall) may precede the peak radiative forcing (related to anvil cloud height and area) by a lead time that was proportional to system size and strength. Mesoscale modeling simulations of convective systems on this day are under way to examine anvil evolution and growth mechanisms.

The NASA Goddard Space Flight Center (GSFC) Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP), which occurred in May and June 2002 in the midwestern part of the United States. The SRL received extensive optical modifications prior to and during the IHOP campaign that added new measurement capabilities and enabled unprecedented daytime water vapor measurements by a Raman lidar system. Improvements were also realized in nighttime upper-tropospheric water vapor measurements. The other new measurements that were added to the SRL for the IHOP deployment included rotational Raman temperature, depolarization, cloud liquid water, and cirrus cloud ice water content. In this first of two parts, the details of the operational configuration of the SRL during IHOP are provided along with a description of the analysis and calibration procedures for water vapor mixing ratio, aerosol depolarization, and cirrus cloud extinction-to-backscatter ratio. For the first time, a Raman water vapor lidar calibration is performed, taking full account of the temperature sensitivity of water vapor and nitrogen Raman scattering. Part II presents case studies that permit the daytime and nighttime error statistics to be quantified.

The NASA GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June 2002 in the midwestern part of the United States. The SRL system configuration and methods of data analysis were described in Part I of this paper. In this second part, comparisons of SRL water vapor measurements and those of Lidar Atmospheric Sensing Experiment (LASE) airborne water vapor lidar and chilled-mirror radiosonde are performed. Two case studies are then presented: one for daytime and one for nighttime. The daytime case study is of a convectively driven boundary layer event and is used to characterize the daytime SRL water vapor random error characteristics. The nighttime case study is of a thunderstorm-generated cirrus cloud case that is studied in its meteorological context. Upper-tropospheric humidification due to precipitation from the cirrus cloud is quantified as is the cirrus cloud optical depth, extinction-to-backscatter ratio, ice water content, cirrus particle size, and both particle and volume depolarization ratios. A stability and back-trajectory analysis is performed to study the origin of wave activity in one of the cloud layers. These unprecedented cirrus cloud measurements are being used in a cirrus cloud modeling study.

Detailed observations of the interactions of a cold front and a dryline over the central United States that led to dramatic undulations in the boundary layer, including an undular bore, are investigated using high-resolution water vapor mixing ratio profiles measured by Raman lidars. The lidar-derived water vapor mixing ratio profiles revealed the complex interaction between a dryline and a cold-frontal system. An elevated, well-mixed, and deep midtropospheric layer, as well as a sharp transition (between 5- and 6-km altitude) to a drier region aloft, was observed. The moisture oscillations due to the undular bore and the mixing of the prefrontal air mass with the cold air at the frontal surface are all well depicted. The enhanced precipitable water vapor and roll clouds, the undulations associated with the bore, the strong vertical circulation and mixing that led to the increase in the depth of the low-level moist layer, and the subsequent lifting of this moist layer by the cold-frontal surface, as well as the feeder flow behind the cold front, are clearly indicated. A synthesis of the Raman lidar–measured water vapor mixing ratio profiles, satellite, radiometer, tower, and Oklahoma Mesonet data indicated that the undular bore was triggered by the approaching cold front and propagated south-southeastward. The observed and calculated bore speeds were in reasonable agreement. Wave-ducting analysis showed that favorable wave-trapping mechanisms existed; a low-level stable layer capped by an inversion, a well-mixed midtropospheric layer, and wind curvature from a low-level jet were found.

Water 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.

Mixed-phase clouds are still poorly understood, though studies have indicated that their parameterization in general circulation models is critical for climate studies. Most of the knowledge of mixed-phase clouds has been gained from in situ measurements, but reliable remote sensing algorithms to study mixed-phase clouds extensively are lacking. A combined active and passive remote sensing approach for studying supercooled altocumulus with ice virga, using multiple remote sensor observations, is presented. Precipitating altocumulus clouds are a common type of mixed-phase clouds, and their easily identifiable structure provides a simple scenario to study mixedphase clouds. First, ice virga is treated as an independent ice cloud, and an existing lidar‐radar algorithm to retrieve ice water content and general effective size profiles is applied. Then, a new iterative approach is used to retrieve supercooled water cloud properties by minimizing the difference between atmospheric emitted radiance interferometer (AERI)‐observed radiances and radiances, calculated using the discrete-ordinate radiative transfer model at 12 selected wavelengths. Case studies demonstrate the capabilities of this approach in retrieving radiatively important microphysical properties to characterize this type of mixed-phase cloud. The good agreement between visible optical depths derived from lidar measurement and those estimated from retrieved liquid water path and effective radius provides a closure test for the accuracy of mainly AERI-based supercooled water cloud retrieval.

Systematic observations of the sizes, shapes, and degrees of riming of ice particles falling at a downwind station of a major mountain barrier are presented. The observational station was equipped to measure ice-particle masses from 1 µg to a few milligrams, and to measure ice-particle dimensions, habits, degrees of riming, and degrees of aggregation. The results are shown to be useful in learning where ice nucleation and growth take place in the cloud system. The present study analyzed dissipating and developing winter orographic storm systems, which are representative of more than 60% of the storms observed over the study region. It suggests that most of the needles and columns observed at the ground may be formed by secondary ice production. Heavy riming was associated with light precipitation, while high precipitation rates were correlated with a high number fraction of aggregate crystals. Aggregation was found to be important in the process of precipitation development and the aggregate mass...

In the winter of 1986, two microwave radiometers were operated side by side at a high-altitude weather observation site in the central Sierra Nevada for the purpose of comparing measurements in a variety of ambient weather conditions. The instruments continuously recorded measurements of vertically integrated water vapor and liquid water during storms affecting the area. One radiometer was designed with a spinning reflector to shed precipitation particles while the other radiometer's reflector was fixed. Temporal records of the data show periods of wet weather contamination for the fixed reflector radiometer. The absence (presence) of these contaminated periods is mainly explained by the difference in the design of the radiometers. These contaminated periods led to larger standard deviation in the data from the fixed-reflector radiometer and lower correlation coefficients between the two instruments. Correlation coefficients of 0.83 for the liquid and 0.68 for the vapor values were found for the ...

The water vapor data measured with airborne and ground-based lidar systems during the International H2O Project (IHOP_2002), which took place in the Southern Great Plains during 13 May–25 June 2002 were investigated. So far, the data collected during IHOP_2002 provide the largest set of state-of-the-art water vapor lidar data measured in a field campaign. In this first of two companion papers, intercomparisons between the scanning Raman lidar (SRL) of the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) and two airborne systems are discussed. There are 9 intercomparisons possible between SRL and the differential absorption lidar (DIAL) of Deutsches Zentrum für Luft- und Raumfahrt (DLR), while there are 10 intercomparisons between SRL and the Lidar Atmospheric Sensing Experiment (LASE) of the NASA Langley Research Center. Mean biases of (−0.30 ± 0.25) g kg−1 or −4.3% ± 3.2% for SRL compared to DLR DIAL (DLR DIAL drier) and (0.16 ± 0.31) g kg−1 or 5.3% ± 5.1% for SRL compared to LASE (LASE wetter) in the height range of 1.3–3.8 km above sea level (450–2950 m above ground level at the SRL site) were found. Putting equal weight on the data reliability of the three instruments, these results yield relative bias values of −4.6%, −0.4%, and +5.0% for DLR DIAL, SRL, and LASE, respectively. Furthermore, measurements of the Snow White (SW) chilled-mirror hygrometer radiosonde were compared with lidar data. For the four comparisons possible between SW radiosondes and SRL, an overall bias of (−0.27 ± 0.30) g kg−1 or −3.2% ± 4.5% of SW compared to SRL (SW drier) again for 1.3–3.8 km above sea level was found. Because it is a challenging effort to reach an accuracy of humidity measurements down to the ∼5% level, the overall results are very satisfactory and confirm the high and stable performance of the instruments and the low noise errors of each profile.