Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert A. Houze, Jr.

2013-11-13

We examined cloud radar data in monsoon climates, using cloud radars at Darwin in the Australian monsoon, on a ship in the Bay of Bengal in the South Asian monsoon, and at Niamey in the West African monsoon. We followed on with a more in-depth study of the continental MCSs over West Africa. We investigated whether the West African anvil clouds connected with squall line MCSs passing over the Niamey ARM site could be simulated in a numerical model by comparing the observed anvil clouds to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model at highmore » resolution using six different ice-phase microphysical schemes. We carried out further simulations with a cloud-resolving model forced by sounding network budgets over the Niamey region and over the northern Australian region. We have devoted some of the effort of this project to examining how well satellite data can determine the global breadth of the anvil cloud measurements obtained at the ARM ground sites. We next considered whether satellite data could be objectively analyzed to so that their large global measurement sets can be systematically related to the ARM measurements. Further differences were detailed between the land and ocean MCS anvil clouds by examining the interior structure of the anvils with the satellite-detected the CloudSat Cloud Profiling Radar (CPR). The satellite survey of anvil clouds in the Indo-Pacific region was continued to determine the role of MCSs in producing the cloud pattern associated with the MJO.« less

Validation of a radiosonde-based cloud layer detection method against a ground-based remote sensing method at multiple ARM sites

NASA Astrophysics Data System (ADS)

Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Cribb, Maureen

2013-01-01

Cloud vertical structure is a key quantity in meteorological and climate studies, but it is also among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP), Tropical Western Pacific (TWP), and North Slope of Alaska (NSA) sites and a shorter-term product for the ARM Mobile Facility (AMF) deployed in Shouxian, Anhui Province, China (AMF-China). The AMF-China site was in operation from 14 May to 28 December 2008; the ARM sites have been collecting data for over 15 years. The Active Remote Sensing of Cloud (ARSCL) value-added product (VAP), which combines data from the 95-GHz W-band ARM Cloud Radar (WACR) and/or the 35-GHz Millimeter Microwave Cloud Radar (MMCR), is used in this study to validate the radiosonde-based cloud layer retrieval method. The performance of the radiosonde-based cloud layer retrieval method applied to data from different climate regimes is evaluated. Overall, cloud layers derived from the ARSCL VAP and radiosonde data agree very well at the SGP and AMF-China sites. At the TWP and NSA sites, the radiosonde tends to detect more cloud layers in the upper troposphere.

Retrieval of Boundary Layer 3D Cloud Properties Using Scanning Cloud Radar and 3D Radiative Transfer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marchand, Roger

Retrievals of cloud optical and microphysical properties for boundary layer clouds, including those widely used by ASR investigators, frequently assume that clouds are sufficiently horizontally homogeneous that scattering and absorption (at all wavelengths) can be treated using one dimensional (1D) radiative transfer, and that differences in the field-of-view of different sensors are unimportant. Unfortunately, most boundary layer clouds are far from horizontally homogeneous, and numerous theoretical and observational studies show that the assumption of horizontal homogeneity leads to significant errors. The introduction of scanning cloud and precipitation radars at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) programmore » sites presents opportunities to move beyond the horizontally homogeneous assumption. The primary objective of this project was to develop a 3D retrieval for warm-phase (liquid only) boundary layer cloud microphysical properties, and to assess errors in current 1D (non-scanning) approaches. Specific research activities also involved examination of the diurnal cycle of hydrometeors as viewed by ARM cloud radar, and continued assessment of precipitation impacts on retrievals of cloud liquid water path using passive microwaves.« less

Validation of CERES-MODIS Arctic cloud properties using CloudSat/CALIPSO and ARM NSA observations

NASA Astrophysics Data System (ADS)

Giannecchini, K.; Dong, X.; Xi, B.; Minnis, P.; Kato, S.

2011-12-01

The traditional passive satellite studies of cloud properties in the Arctic are often affected by the complex surface features present across the region. Nominal visual and thermal contrast exists between Arctic clouds and the snow- and ice-covered surfaces beneath them, which can lead to difficulties in satellite retrievals of cloud properties. However, the addition of active sensors to the A-Train constellation of satellites has increased the availability of validation sources for cloud properties derived from passive sensors in the data-sparse high-latitude regions. In this study, Arctic cloud fraction and cloud heights derived from the NASA CERES team (CERES-MODIS) have been compared with CloudSat/CALIPSO and DOE ARM NSA radar-lidar observations over Barrow, AK, for the two-year period from 2007 to 2008. An Arctic-wide comparison of cloud fraction and height between CERES-MODIS and CloudSat/CALIPSO was then conducted for the same time period. The CERES-MODIS cloud properties, which include cloud fraction and cloud effective heights, were retrieved using the 4-channel VISST (Visible Infrared Solar-Infrared Split-window Technique) [Minnis et al.,1995]. CloudSat/CALIPSO cloud fraction and cloud-base and -top heights were from version RelB1 data products determined by both the 94 GHz radar onboard CloudSat and the lidar on CALIPSO with a vertical resolution of 30 m below 8.2 km and 60 m above. To match the surface and satellite observations/retrievals, the ARM surface observations were averaged into 3-hour intervals centered at the time of the satellite overpass, while satellite observations were averaged within a 3°x3° grid box centered on the Barrow site. The preliminary results have shown that all observed CFs have peaks during April-May and September-October, and dips during winter months (January-February) and summer months (June-July) during the study period of 2007-2008. ARM radar-lidar and CloudSat/CALIPSO show generally good agreement in CF (0.79 vs. 0.74), while CERES-MODIS derived values are much lower (0.60). CERES-MODIS derived cloud effective height (2.7 km) falls between the CloudSat/CALIPSO derived cloud base (0.6 km) and top (6.4 km) and the ARM ceilometers and MMCR derived cloud base (0.9 km) and radar derived cloud top (5.8 km). When extended to the entire Arctic, although the CERES-MODIS and Cloudsat/CALIPSO derived annual mean CFs agree within a few percents, there are significant differences over several regions, and the maximum cloud heights derived from CloudSat/CALIPSO (13.4 km) and CERES-MODIS (10.7 km) show the largest disagreement during early spring.

Fine-scale Horizontal Structure of Arctic Mixed-Phase Clouds.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rambukkange,M.; Verlinde, J.; Elorante, E.

2006-07-10

Recent in situ observations in stratiform clouds suggest that mixed phase regimes, here defined as limited cloud volumes containing both liquid and solid water, are constrained to narrow layers (order 100 m) separating all-liquid and fully glaciated volumes (Hallett and Viddaurre, 2005). The Department of Energy Atmospheric Radiation Measurement Program's (DOE-ARM, Ackerman and Stokes, 2003) North Slope of Alaska (NSA) ARM Climate Research Facility (ACRF) recently started collecting routine measurement of radar Doppler velocity power spectra from the Millimeter Cloud Radar (MMCR). Shupe et al. (2004) showed that Doppler spectra has potential to separate the contributions to the total reflectivitymore » of the liquid and solid water in the radar volume, and thus to investigate further Hallett and Viddaurre's findings. The Mixed-Phase Arctic Cloud Experiment (MPACE) was conducted along the NSA to investigate the properties of Arctic mixed phase clouds (Verlinde et al., 2006). We present surface based remote sensing data from MPACE to discuss the fine-scale structure of the mixed-phase clouds observed during this experiment.« less

AMF3 ARM's Research Facility and MAOS at Oliktok Point Alaska

NASA Astrophysics Data System (ADS)

Helsel, F.; Ivey, M.; Dexheimer, D.; Hardesty, J.; Lucero, D. A.; Roesler, E. L.

2016-12-01

Scientific Infrastructure To Support Atmospheric Science And Aerosol Science For The Department Of Energy's Atmospheric Radiation Measurement Programs Mobile Facility 3 Located At Oliktok Point, Alaska.The Atmospheric Radiation Measurement (ARM) Program's Mobile Facility 3 (AMF3) located at Oliktok Point, Alaska is a U.S. Department of Energy (DOE) site designed to collect data to determine the impact that clouds and aerosols have on solar radiation. The site provides a scientific infrastructure and data archives for the international Arctic research community. The infrastructure at Oliktok is designed to be mobile and it may be relocated in the future to support other ARM science missions. AMF3's present instruments include: scanning precipitation Radar-cloud radar, Raman Lidar, Eddy correlation flux systems, Ceilometer, Balloon sounding system, Atmospheric Emitted Radiance Interferometer (AERI), Micro-pulse Lidar (MPL), Millimeter cloud radar along with all the standard metrological measurements. A Mobile Aerosol Observing System (MAOS) has been added to AMF3 in 2016 more details of the instrumentation at www.arm.gov/sites/amf/mobile-aos. Data from these instruments are placed in the ARM data archives and are available to the international research community. This poster will discuss what instruments are at the ARM Program's AMF3 and highlight the newest addition to AMF3, the Mobile Aerosol Observing System (MAOS).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng, Min; Kollias, Pavlos; Feng, Zhe

The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification ismore » equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.« less

The diurnal cycle of clouds and precipitation at the ARM SGP site: Cloud radar observations and simulations from the multiscale modeling framework

DOE PAGES

Zhao, Wei; Marchand, Roger; Fu, Qiang

2017-07-08

Millimeter Wavelength Cloud Radar (MMCR) data from December 1996 to December 2010, collected at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site, are used to examine the diurnal cycle of hydrometeor occurrence. These data are categorized into clouds (-40 dBZ e ≤ reflectivity < -10 dBZ e), drizzle and light precipitation (-10 dBZ e ≤ reflectivity < 10 dBZ e), and heavy precipitation (reflectivity ≥ 10 dBZ e). The same criteria are implemented for the observation-equivalent reflectivity calculated by feeding outputs from a Multiscale Modeling Framework (MMF) climate model into a radar simulator.more » The MMF model consists of the National Center for Atmospheric Research Community Atmosphere Model with conventional cloud parameterizations replaced by a cloud-resolving model. We find that a radar simulator combined with the simple reflectivity categories can be an effective approach for evaluating diurnal variations in model hydrometeor occurrence. It is shown that the MMF only marginally captures observed increases in the occurrence of boundary layer clouds after sunrise in spring and autumn and does not capture diurnal changes in boundary layer clouds during the summer. Above the boundary layer, the MMF captures reasonably well diurnal variations in the vertical structure of clouds and light and heavy precipitation in the summer but not in the spring.« less

AMF3 ARM's Research Facility at Oliktok Point Alaska

NASA Astrophysics Data System (ADS)

Helsel, F.; Lucero, D. A.; Ivey, M.; Dexheimer, D.; Hardesty, J.; Roesler, E. L.

2015-12-01

Scientific Infrastructure To Support Atmospheric Science And Aerosol Science For The Department Of Energy's Atmospheric Radiation Measurement Programs Mobile Facility 3 Located At Oliktok Point, Alaska.The Atmospheric Radiation Measurement (ARM) Program's Mobile Facility 3 (AMF3) located at Oliktok Point, Alaska is a U.S. Department of Energy (DOE) site. The site provides a scientific infrastructure and data archives for the international Arctic research community. The infrastructure at Oliktok is designed to be mobile and it may be relocated in the future to support other ARM science missions. AMF-3 instruments include: scanning precipitation Radar-cloud radar, Raman Lidar, Eddy correlation flux systems, Ceilometer, Balloon sounding system, Atmospheric Emitted Radiance Interferometer (AERI), Micro-pulse Lidar (MPL), Millimeter cloud radar along with all the standard metrological measurements. Data from these instruments is placed in the ARM data archives and are available to the international research community. This poster will discuss what instruments are at AMF3 and the challenges of powering an Arctic site without the use of grid power.

Boundary Layer Thermodynamics and Cloud Microphysics for a Mixed Stratocumulus and Cumulus Cloud Field Observed during ACE-ENA

NASA Astrophysics Data System (ADS)

Jensen, M. P.; Miller, M. A.; Wang, J.

2017-12-01

The first Intensive Observation Period of the DOE Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) took place from 21 June through 20 July 2017 involving the deployment of the ARM Gulfstream-159 (G-1) aircraft with a suite of in situ cloud and aerosol instrumentation in the vicinity of the ARM Climate Research Facility Eastern North Atlantic (ENA) site on Graciosa Island, Azores. Here we present preliminary analysis of the thermodynamic characteristics of the marine boundary layer and the variability of cloud properties for a mixed cloud field including both stratiform cloud layers and deeper cumulus elements. Analysis combines in situ atmospheric state observations from the G-1 with radiosonde profiles and surface meteorology from the ENA site in order to characterize the thermodynamic structure of the marine boundary layer including the coupling state and stability. Cloud/drizzle droplet size distributions measured in situ are combined with remote sensing observations from a scanning cloud radar, and vertically pointing cloud radar and lidar provide quantification of the macrophysical and microphysical properties of the mixed cloud field.

Machine Learing Applications on a Radar Wind Profiler Deployment During the ARM GoAmazon2014/5 Campaign

NASA Astrophysics Data System (ADS)

Giangrande, S. E.; WANG, D.; Hardin, J. C.; Mitchell, J.

2017-12-01

As part of the 2 year Department of Energy Atmospheric Radiation Measurement (ARM) Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign, the ARM Mobile Facility (AMF) collected a unique set of observations in a region of strong climatic significance near Manacapuru, Brazil. An important example for the beneficial observational record obtained by ARM during this campaign was that of the Radar Wind Profiler (RWP). This dataset has been previously documented for providing critical convective cloud vertical air velocity retrievals and precipitation properties (e.g., calibrated reflectivity factor Z, rainfall rates) under a wide variety of atmospheric conditions. Vertical air motion estimates to within deep convective cores such as those available from this RWP system have been previously identified as critical constraints for ongoing global climate modeling activities and deep convective cloud process studies. As an extended deployment within this `green ocean' region, the RWP site and collocated AMF surface gauge instrumentation experienced a unique hybrid of tropical and continental precipitation conditions, including multiple wet and dry season precipitation regimes, convective and organized stratiform storm dynamics and contributions to rainfall accumulation, pristine aerosol conditions of the locale, as well as the effects of the Manaus, Brazil, mega city pollution plume. For hydrological applications and potential ARM products, machine learning methods developed using this dataset are explored to demonstrate advantages in geophysical retrievals when compared to traditional methods. Emphasis is on performance improvements when providing additional information on storm structure and regime or echo type classifications. Since deep convective cloud dynamic insights (core updraft/downdraft properties) are difficult to obtain directly by conventional radars that also observe radar reflectivity factor profiles similar to RWP systems, we also consider possible machine learning applications to inform on (statistical) proxy convective relationships between observed convective core dynamics and radar microphysical properties that are otherwise not easily related by clear physical process paths using existing radar networks.

AMF3 CloudSat Overpasses Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matrosov, Sergey; Hardin, Joseph; De Boer, Gijs

Synergy between ground-based and satellite radar observations of clouds and precipitation is important for refining the algorithms to retrieve hydrometeor microphysical parameters, improvements in the retrieval accuracy, and better understanding the advantages and limitations of different retrieval approaches. The new dual-frequency (Ka- and W-band, 35 GHz and 94 GHz) fully polarimetric scanning U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility cloud radars (SACRs-2) are advanced sensors aimed to significantly enhance remote sensing capabilities (Kollias et al. 2016). One of these radars was deployed as part of the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska (70.495omore » N, 149.886oW). The National Aeronautics and Space Administration (NASA) CloudSat satellite, which is part of the polar-orbiting A-train satellite constellation, passes over the vicinity of the AMF3 location (typically within 0-7 km depending on a particular overpass) on a descending orbit every 16 days at approximately 13:21 UTC. The nadir pointing W-band CloudSat cloud profiling radar (CPR) provides vertical profiles of reflectivity that are then used for retrievals of hydrometeor parameters (Tanelli et al. 2008). The main objective of the AMF3 CloudSat overpasses intensive operating period (IOP) campaign was to collect approximately collocated in space and time radar data from the SACR-2 and the CloudSat CPR measurements for subsequent joint analysis of radar variables and microphysical retrievals of cloud and precipitation parameters. Providing the reference for the SACR-2 absolute calibration from the well-calibrated CloudSat CPR was another objective of this IOP. The IOP objectives were achieved by conducting seven special SACR-2 scans during the 10.5-min period centered at the exact time of the CloudSat overpass over the AMF3 (~1321 UTC) on six dates of the CloudSat overpasses during the three-month period allocated to this IOP. These six days were March 5 and 21, April 6 and 22, and May 8 and 24.« less

Observing microphysical structures and hydrometeor phase in convection with ARM active sensors

NASA Astrophysics Data System (ADS)

Riihimaki, L.; Comstock, J. M.; Luke, E. P.; Thorsen, T. J.; Fu, Q.

2016-12-01

The existence and distribution of super-cooled liquid water within convective clouds impacts the microphysical processes responsible for cloud radiative and lifetime effects. Yet few observations of cloud phase are available within convection and associated stratiform anvils. Here we identify super-cooled liquid layers within convection and associated stratiform clouds using measured radar Doppler spectra from vertically pointing Ka-band cloud radar and Raman Lidar, capitalizing on the strengths of both instruments. Observations from these sensors are used to show that liquid exists in patches within the cloud, rather than in uniform layers, impacting the growth and formation of ice. While a depolarization lidar like the Raman Lidar is a trusted measurement for identifying super-cooled liquid, the lidar attenuates at an optical depth of around three, limiting its ability to probe the full cloud. The use of the radar Doppler spectra is particularly valuable for this purpose because it allows observations within optically thicker clouds. We demonstrate a new method for identifying super-cooled liquid objectively from the radar Doppler spectra using machine-learning techniques.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schumacher, Courtney

One of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Parsivel2 disdrometers was deployed at the first ARM Mobile Facility (AMF1) T3 site in Manacapuru, Brazil at the beginning of the second Green Ocean Amazon (GoAmazon)2014/15 intensive operational period (IOP2) in September 2014 through the end of the field campaign in December 2015. The Parsivel2 provided one-minute drop-size distribution (DSD) observations that have already been used for a number of applications related to GoAmazon2014/15 science objectives. The first use was the creation of a reflectivity-rain rate (Z-R) relation enabling the calculation of rain rates frommore » the Brazilian Sistema de Protecao da Amazonia (SIPAM) S-band operational radar in Manaus. The radar-derived rainfall is an important constraint for the variational analysis of a large-scale forcing data set, which was recently released for the two IOPs that took place in the 2014 wet and transition seasons, respectively. The SIPAM radar rainfall is also being used to validate a number of cloud-resolving model simulations being run for the campaign. A second use of the Parsivel2 DSDs has been to provide a necessary reference point to calibrate the vertical velocity retrievals from the AMF1 W Band ARM Cloud Radar (WACR) cloud-profiling and ultra-high-frequency (UHF) wind-profiling instruments. Accurate retrievals of in-cloud vertical velocities are important to understand the microphysical and kinematic properties of Amazonian convective clouds and their interaction with the land surface and atmospheric aerosols. Further use of the Parsivel2 DSD observations can be made to better understand precipitation characteristics and their variability during GoAmazon2014/15.« less

Cloud Type Classification (cldtype) Value-Added Product

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flynn, Donna; Shi, Yan; Lim, K-S

The Cloud Type (cldtype) value-added product (VAP) provides an automated cloud type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of clouds are classified into seven cloud types based on predetermined and site-specific thresholds of cloud top, base and thickness. Examples of thresholds for selected U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility sites are provided in Tables 1 and 2. Inputs for the cldtype VAP include lidar and radar cloud boundaries obtained from the Active Remotely Sensed Cloud Location (ARSCL) and Surface Meteorological Systems (MET) data. Rainmore » rates from MET are used to determine when radar signal attenuation precludes accurate cloud detection. Temporal resolution and vertical resolution for cldtype are 1 minute and 30 m respectively and match the resolution of ARSCL. The cldtype classification is an initial step for further categorization of clouds. It was developed for use by the Shallow Cumulus VAP to identify potential periods of interest to the LASSO model and is intended to find clouds of interest for a variety of users.« less

Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations

DOE PAGES

Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas

2015-11-05

In this paper, we evaluate high-level clouds in a cloud resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of cloud occurrence and radar reflectivity compare well with cloud radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level cloud and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level cloud. For ARM9707, persistent large positive biases in high-level cloud are found, which are not sensitivemore » to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level cloud amount, radiation, and high sensitivity of cloud amount to nudging time scale in both convective cases. The high sensitivity of high-level cloud amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful ‘‘tuning’’ parameter for the simulated cloud and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in cloud and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level clouds in super-parameterized global climate models such as the multiscale modeling framework.« less

The occurrence of ice production in slightly supercooled Arctic stratiform clouds as observed by ground-based remote sensors at the ARM NSA site

NASA Astrophysics Data System (ADS)

Zhang, Damao; Wang, Zhien; Luo, Tao; Yin, Yan; Flynn, Connor

2017-03-01

Ice particle formation in slightly supercooled stratiform clouds is not well documented or understood. In this study, 4 years of combined lidar depolarization and radar reflectivity (Ze) measurements are analyzed to distinguish between cold drizzle and ice crystal formations in slightly supercooled Arctic stratiform clouds over the Atmospheric Radiation Measurement Program Climate Research Facility North Slope of Alaska Utqiaġvik ("Barrow") site. Ice particles are detected and statistically shown to be responsible for the strong precipitation in slightly supercooled Arctic stratiform clouds at cloud top temperatures as high as -4°C. For ice precipitating Arctic stratiform clouds, the lidar particulate linear depolarization ratio (δpar_lin) correlates well with radar Ze at each temperature range, but the δpar_lin-Ze relationship varies with temperature ranges. In addition, lidar depolarization and radar Ze observations of ice generation characteristics in Arctic stratiform clouds are consistent with laboratory-measured temperature-dependent ice growth habits.

Comparison of Marine Boundary Layer Cloud Properties From CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

NASA Astrophysics Data System (ADS)

Dong, X.; Xi, B.; Minnis, P.; Sun-Mack, S.

2014-12-01

Marine Boundary Layer (MBL) cloud properties derived for the NASA CERES Project using Terra and Aqua MODIS data are compared with observations taken at DOE ARM Mobile Facility at the Azores site from Jun. 2009 to Dec. 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1-hour interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30×30 km2 grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud-top/base heights (Htop/Hbase) were determined from cloud-top/base temperatures (Ttop/Tbase) using a regional boundary-layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2=0.82 and 0.84, respectively). In general, the cloud-top comparisons agree better than cloud-base comparisons because the CM Tbase and Hbase are secondary product determined from Ttop and Htop. No significant day-night difference was found in the analyses. The comparisons of microphysical properties reveal that, when averaged over a 30x30 km2 area, the CM-retrieved cloud-droplet effective radius (re) is 1.3 µm larger than that from the ARM retrievals (12.8 µm). While the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (τ, 9.6 vs. 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using effective radius retrieved at 2.1-µm channel to calculate LWP can reduce the difference between the CM and ARM from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CM LWP and re retrievals are within the uncertainties of the ARM LWP (~ 20 gm-2) and re (~ 10%) retrievals, however, the 30% difference in τ is significant. Possible reasons contributed to this discrepancy increased sensitivities in τ from both surface retrievals when τ ~ 10 and topography. The τ differences vary with wind direction and are consistent with the island orography.

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulusmore » and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.« less

Clouds, aerosol, and precipitation in the Marine Boundary Layer: An ARM mobile facility deployment

DOE PAGES

Wood, Robert; Luke, Ed; Wyant, Matthew; ...

2014-04-27

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulusmore » and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1-11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging.The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.« less

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) 38 deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) 39 comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric 40 Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is 41 to gain improved understanding of the interactions of clouds, aerosols and precipitation in the 42 marine boundary layer. 43 Graciosa Island straddles the boundary between the subtropics and midlatitudes in the 44 Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and 45 cloudiness conditions. Lowmore » clouds are the dominant cloud type, with stratocumulus and cumulus 46 occurring regularly. Approximately half of all clouds contained precipitation detectable as radar 47 echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1-48 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide 49 range of aerosol conditions was sampled during the deployment consistent with the diversity of 50 sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way 51 interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation 52 and cloud radiative properties while being controlled in part by precipitation scavenging. 53 The data from at Graciosa are being compared with short-range forecasts made a variety 54 of models. A pilot analysis with two climate and two weather forecast models shows that they 55 reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, 56 but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to 57 be a long-term ARM site that became operational in October 2013.« less

StatisticAl Characteristics of Cloud over Beijing, China Obtained FRom Ka band Doppler Radar Observation

NASA Astrophysics Data System (ADS)

LIU, J.; Bi, Y.; Duan, S.; Lu, D.

2017-12-01

It is well-known that cloud characteristics, such as top and base heights and their layering structure of micro-physical parameters, spatial coverage and temporal duration are very important factors influencing both radiation budget and its vertical partitioning as well as hydrological cycle through precipitation data. Also, cloud structure and their statistical distribution and typical values will have respective characteristics with geographical and seasonal variation. Ka band radar is a powerful tool to obtain above parameters around the world, such as ARM cloud radar at the Oklahoma US, Since 2006, Cloudsat is one of NASA's A-Train satellite constellation, continuously observe the cloud structure with global coverage, but only twice a day it monitor clouds over same local site at same local time.By using IAP Ka band Doppler radar which has been operating continuously since early 2013 over the roof of IAP building in Beijing, we obtained the statistical characteristic of clouds, including cloud layering, cloud top and base heights, as well as the thickness of each cloud layer and their distribution, and were analyzed monthly and seasonal and diurnal variation, statistical analysis of cloud reflectivity profiles is also made. The analysis covers both non-precipitating clouds and precipitating clouds. Also, some preliminary comparison of the results with Cloudsat/Calipso products for same period and same area are made.

SGP and TWP (Manus) Ice Cloud Vertical Velocities

DOE Data Explorer

Kalesse, Heike

2013-06-27

Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

Spectral Invariance Principles Observed in Spectral Radiation Measurements of the Transition Zone

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2011-01-01

The main theme for our research is the understanding and closure of the surface spectral shortwave radiation problem in fully 3D cloud situations by combining the new ARM scanning radars, shortwave spectrometers, and microwave radiometers with the arsenal of radiative transfer tools developed by our group. In particular, we define first a large number of cloudy test cases spanning all 3D possibilities not just the customary uniform-overcast ones. Second, for each case, we define a "Best Estimate of Clouds That Affect Shortwave Radiation" using all relevant ARM instruments, notably the new scanning radars, and contribute this to the ARM Archive. Third, we test the ASR-signature radiative transfer model RRTMG_SW for those cases, focusing on the near-IR because of long-standing problems in this spectral region, and work with the developers to improve RRTMG_SW in order to increase its penetration into the modeling community.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Heymsfield

Data was taken with the NASA ER-2 aircraft with the Cloud Radar System and other instruments in conjunction with the DOE ARM CLASIC field campaign. The flights were near the SGP site in north Central Oklahoma and targeted small developing convection. The CRS is a 94 GHz nadir pointing Doppler radar. Also on board the ER-2 was the Cloud Physics Lidar (CPL). Seven science flights were conducted but the weather conditions did not cooperate in that there was neither developing convection, or there was heavy rain.

A Method for the Automatic Detection of Insect Clutter in Doppler-Radar Returns.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luke,E.; Kollias, P.; Johnson, K.

2006-06-12

The accurate detection and removal of insect clutter from millimeter wavelength cloud radar (MMCR) returns is of high importance to boundary layer cloud research (e.g., Geerts et al., 2005). When only radar Doppler moments are available, it is difficult to produce a reliable screening of insect clutter from cloud returns because their distributions overlap. Hence, screening of MMCR insect clutter has historically involved a laborious manual process of cross-referencing radar moments against measurements from other collocated instruments, such as lidar. Our study looks beyond traditional radar moments to ask whether analysis of recorded Doppler spectra can serve as the basismore » for reliable, automatic insect clutter screening. We focus on the MMCR operated by the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) facility in Oklahoma. Here, archiving of full Doppler spectra began in September 2003, and during the warmer months, a pronounced insect presence regularly introduces clutter into boundary layer returns.« less

Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign

DOE PAGES

Giangrande, Scott E.; Collis, Scott; Theisen, Adam K.; ...

2014-09-12

This study presents radar-based precipitation estimates collected during the two-month DOE ARM - NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR, XSAPR) for rainfall estimation products to distances within 100 km of the Oklahoma SGP facility. A dense collection of collocated ARM, NASA GPM and nearby surface Oklahoma Mesonet gauge records are consulted to evaluate potential ARM radar-based hourly rainfall products and campaign optimized methods over individual gauge and areal characterizations. Rainfall products are evaluated against the performance of the regional operational NWSmore » NEXRAD S-band radar polarimetric product. Results indicate that the ARM C-band system may achieve similar point and areal-gauge bias and root mean square (rms) error performance to the NEXRAD standard for the variety of MC3E deep convective events sampled when capitalizing on differential phase measurements. The best campaign rainfall performance was achieved when applying radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The ARM X-band systems only demonstrate solid capabilities as compared to NEXRAD standards for hourly point and areal rainfall accumulations under 10 mm. Here, all methods exhibit a factor of 1.5 to 2.5 reduction in rms errors for areal accumulations over a 15 km2 NASA dense network housing 16 sites having collocated bucket gauges, with the higher error reductions best associated with polarimetric methods.« less

Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giangrande, Scott E.; Collis, Scott; Theisen, Adam K.

This study presents radar-based precipitation estimates collected during the two-month DOE ARM - NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR, XSAPR) for rainfall estimation products to distances within 100 km of the Oklahoma SGP facility. A dense collection of collocated ARM, NASA GPM and nearby surface Oklahoma Mesonet gauge records are consulted to evaluate potential ARM radar-based hourly rainfall products and campaign optimized methods over individual gauge and areal characterizations. Rainfall products are evaluated against the performance of the regional operational NWSmore » NEXRAD S-band radar polarimetric product. Results indicate that the ARM C-band system may achieve similar point and areal-gauge bias and root mean square (rms) error performance to the NEXRAD standard for the variety of MC3E deep convective events sampled when capitalizing on differential phase measurements. The best campaign rainfall performance was achieved when applying radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The ARM X-band systems only demonstrate solid capabilities as compared to NEXRAD standards for hourly point and areal rainfall accumulations under 10 mm. Here, all methods exhibit a factor of 1.5 to 2.5 reduction in rms errors for areal accumulations over a 15 km2 NASA dense network housing 16 sites having collocated bucket gauges, with the higher error reductions best associated with polarimetric methods.« less

Cloud Properties and Radiative Heating Rates for TWP

DOE Data Explorer

Comstock, Jennifer

2013-11-07

A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

Remote sensing data from CLARET: A prototype CART data set

NASA Technical Reports Server (NTRS)

Eberhard, Wynn L.; Uttal, Taneil; Clark, Kurt A.; Cupp, Richard E.; Dutton, Ellsworth G.; Fedor, Leonard, S.; Intrieri, Janet M.; Matrosov, Sergey Y.; Snider, Jack B.; Willis, Ron J.

1992-01-01

The data set containing radiation, meteorological , and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) Program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of the experiment, ARM scientists requested archival of subsets of the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory.

The ARM Climate Research Facility - New Capabilities and the Expected Impacts on Climate Science and Modeling

NASA Astrophysics Data System (ADS)

Voyles, J.; Mather, J. H.

2010-12-01

The ARM Climate Research Facility is a Department of Energy national scientific user facility. Research sites include fixed and mobile facilities, which collect research quality data for climate research. Through the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy’s Office of Science allocated $60 million to the ARM Climate Research Facility for the purchase of instruments and improvement of research sites. With these funds, ARM is in the process of deploying a broad variety of new instruments that will greatly enhance the measurement capabilities of the facility. New instruments being purchased include dual-frequency scanning cloud radars, scanning precipitation radars, Doppler lidars, a mobile Aerosol Observing System and many others. A list of instruments being purchased is available at http://www.arm.gov/about/recovery-act. Orders for all instruments have now been placed and activities are underway to integrate these new systems with our research sites. The overarching goal is to provide instantaneous and statistical measurements of the climate that can be used to advance the physical understanding and predictive performance of climate models. The Recovery Act investments enable the ARM Climate Research Facility to enhance existing and add new measurements, which enable a more complete understanding of the 3-dimensional evolution of cloud processes and related atmospheric properties. Understanding cloud processes are important globally, to reduce climate-modeling uncertainties and help improve our nation’s ability to manage climate impacts. Domer Plot of W-Band Reflectivity

Scientific Infrastructure to Support Atmospheric Science and Aerosol Science for the Department of Energy's Atmospheric Radiation Measurement Programs at Barrow, Alaska.

NASA Astrophysics Data System (ADS)

Lucero, D. A.; Ivey, M.; Helsel, F.; Hardesty, J.; Dexheimer, D.

2015-12-01

Scientific infrastructure to support atmospheric science and aerosol science for the Department of Energy's Atmospheric Radiation Measurement programs at Barrow, Alaska.The Atmospheric Radiation Measurement (ARM) Program's located at Barrow, Alaska is a U.S. Department of Energy (DOE) site. The site provides a scientific infrastructure and data archives for the international Arctic research community. The infrastructure at Barrow has been in place since 1998, with many improvements since then. Barrow instruments include: scanning precipitation Radar-cloud radar, Doppler Lidar, Eddy correlation flux systems, Ceilometer, Manual and state-of-art automatic Balloon sounding systems, Atmospheric Emitted Radiance Interferometer (AERI), Micro-pulse Lidar (MPL), Millimeter cloud radar, High Spectral Resolution Lidar (HSRL) along with all the standard metrological measurements. Data from these instruments is placed in the ARM data archives and are available to the international research community. This poster will discuss what instruments are at Barrow and the challenges of maintaining these instruments in an Arctic site.

Comparison of Marine Boundary Layer Cloud Properties from CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

NASA Technical Reports Server (NTRS)

Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

2014-01-01

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km×30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R(sup 2) = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km× 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 micrometers is 1.3 micrometers larger than that from the ARM retrievals (12.8 micrometers), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm( exp -2) less than its ARM counterpart (114.2 gm( exp-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 micrometers channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from 13.7 to 2.1 gm2. The 10% differences between the ARM and CERES-MODIS LWP and r(sub e) retrievals are within the uncertainties of the ARM LWP (approximately 20gm( exp -2)) and r(sub e) (approximately 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when t is approximately 10 and topography. The t differences vary with wind direction and are consistent with the island orography.Much better agreement in t is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Comparison of marine boundary layer cloud properties from CERES-MODIS Edition 4 and DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

2014-08-01

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km × 30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2 = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km × 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 µm is 1.3 µm larger than that from the ARM retrievals (12.8 µm), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 µm channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CERES-MODIS LWP and re retrievals are within the uncertainties of the ARM LWP ( 20 gm-2) and re ( 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when τ 10 and topography. The τ differences vary with wind direction and are consistent with the island orography. Much better agreement in τ is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Low-cloud characteristics over the tropical western Pacific from ARM observations and CAM5 simulations

DOE PAGES

Chandra, Arunchandra S.; Zhang, Chidong; Klein, Stephen A.; ...

2015-09-10

Here, this study evaluates the ability of the Community Atmospheric Model version 5 (CAM5) to reproduce low clouds observed by the Atmospheric Radiation Measurement (ARM) cloud radar at Manus Island of the tropical western Pacific during the Years of Tropical Convection. Here low clouds are defined as clouds with their tops below the freezing level and bases within the boundary layer. Low-cloud statistics in CAM5 simulations and ARM observations are compared in terms of their general occurrence, mean vertical profiles, fraction of precipitating versus nonprecipitating events, diurnal cycle, and monthly time series. Other types of clouds are included to putmore » the comparison in a broader context. The comparison shows that the model overproduces total clouds and their precipitation fraction but underestimates low clouds in general. The model, however, produces excessive low clouds in a thin layer between 954 and 930 hPa, which coincides with excessive humidity near the top of the mixed layer. This suggests that the erroneously excessive low clouds stem from parameterization of both cloud and turbulence mixing. The model also fails to produce the observed diurnal cycle in low clouds, not exclusively due to the model coarse grid spacing that does not resolve Manus Island. Lastly, this study demonstrates the utility of ARM long-term cloud observations in the tropical western Pacific in verifying low clouds simulated by global climate models, illustrates issues of using ARM observations in model validation, and provides an example of severe model biases in producing observed low clouds in the tropical western Pacific.« less

Clouds, Aerosol, and Precipitation in the Marine Boundary Layer: An ARM Mobile Facility Deployment

NASA Technical Reports Server (NTRS)

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.; Remillard, Jasmine; Kollias, Pavlos; Fletcher, Jennifer; Stemmler, Jayson; de Szoeke, Simone; Yuter, Sandra; Miller, Matthew;

Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling

DOE PAGES

Kalesse, Heike; Szyrmer, Wanda; Kneifel, Stefan; ...

2016-03-09

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyondmore » the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.« less

Phase-partitioning in mixed-phase clouds - An approach to characterize the entire vertical column

NASA Astrophysics Data System (ADS)

Kalesse, H.; Luke, E. P.; Seifert, P.

2017-12-01

The characterization of the entire vertical profile of phase-partitioning in mixed-phase clouds is a challenge which can be addressed by synergistic profiling measurements with ground-based polarization lidars and cloud radars. While lidars are sensitive to small particles and can thus detect supercooled liquid (SCL) layers, cloud radar returns are dominated by larger particles (like ice crystals). The maximum lidar observation height is determined by complete signal attenuation at a penetrated optical depth of about three. In contrast, cloud radars are able to penetrate multiple liquid layers and can thus be used to expand the identification of cloud phase to the entire vertical column beyond the lidar extinction height, if morphological features in the radar Doppler spectrum can be related to the existence of SCL. Relevant spectral signatures such as bimodalities and spectral skewness can be related to cloud phase by training a neural network appropriately in a supervised learning scheme, with lidar measurements functioning as supervisor. The neural network output (prediction of SCL location) derived using cloud radar Doppler spectra can be evaluated with several parameters such as liquid water path (LWP) detected by microwave radiometer (MWR) and (liquid) cloud base detected by ceilometer or Raman lidar. The technique has been previously tested on data from Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) instruments in Barrow, Alaska and is in this study utilized for observations from the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. Comparisons to supercooled-liquid layers as classified by CLOUDNET are provided.

Exploring Stratocumulus Cloud-Top Entrainment Processes and Parameterizations by Using Doppler Cloud Radar Observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albrecht, Bruce; Fang, Ming; Ghate, Virendra

2016-02-01

Observations from an upward-pointing Doppler cloud radar are used to examine cloud-top entrainment processes and parameterizations in a non-precipitating continental stratocumulus cloud deck maintained by time varying surface buoyancy fluxes and cloud-top radiative cooling. Radar and ancillary observations were made at the Atmospheric Radiation Measurement (ARM)’s Southern Great Plains (SGP) site located near Lamont, Oklahoma of unbroken, non-precipitating stratocumulus clouds observed for a 14-hour period starting 0900 Central Standard Time on 25 March 2005. The vertical velocity variance and energy dissipation rate (EDR) terms in a parameterized turbulence kinetic energy (TKE) budget of the entrainment zone are estimated using themore » radar vertical velocity and the radar spectrum width observations from the upward-pointing millimeter cloud radar (MMCR) operating at the SGP site. Hourly averages of the vertical velocity variance term in the TKE entrainment formulation correlates strongly (r=0.72) to the dissipation rate term in the entrainment zone. However, the ratio of the variance term to the dissipation decreases at night due to decoupling of the boundary layer. When the night -time decoupling is accounted for, the correlation between the variance and the EDR term increases (r=0.92). To obtain bulk coefficients for the entrainment parameterizations derived from the TKE budget, independent estimate of entrainment were obtained from an inversion height budget using ARM SGP observations of the local time derivative and the horizontal advection of the cloud-top height. The large-scale vertical velocity at the inversion needed for this budget from EMWF reanalysis. This budget gives a mean entrainment rate for the observing period of 0.76±0.15 cm/s. This mean value is applied to the TKE budget parameterizations to obtain the bulk coefficients needed in these parameterizations. These bulk coefficients are compared with those from previous and are used to in the parameterizations to give hourly estimates of the entrainment rates using the radar derived vertical velocity variance and dissipation rates. Hourly entrainment rates were estimated from a convective velocity w* parameterization depends on the local surface buoyancy fluxes and the calculated radiative flux divergence, parameterization using a bulk coefficient obtained from the mean inversion height budget. The hourly rates from the cloud turbulence estimates and the w* parameterization, which is independent of the radar observations, are compared with the hourly we values from the budget. All show rough agreement with each other and capture the entrainment variability associated with substantial changes in the surface flux and radiative divergence at cloud top. Major uncertainties in the hourly estimates from the height budget and w* are discussed. The results indicate a strong potential for making entrainment rate estimates directly from the radar vertical velocity variance and the EDR measurements—a technique that has distinct advantages over other methods for estimating entrainment rates. Calculations based on the EDR alone can provide high temporal resolution (for averaging intervals as small as 10 minutes) of the entrainment processes and do not require an estimate of the boundary layer depth, which can be difficult to define when the boundary layer is decoupled.« less

Large Scale Ice Water Path and 3-D Ice Water Content

DOE Data Explorer

Liu, Guosheng

2008-01-15

Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.

Architectures for Rainfall Property Estimation From Polarimetric Radar

NASA Astrophysics Data System (ADS)

Collis, S. M.; Giangrande, S. E.; Helmus, J.; Troemel, S.

2014-12-01

Radars that transmit and receive signals in polarizations aligned both horizontal and vertical to the horizon collect a number of measurements. The relation both between these measurements and between measurements and desired microphysical quantities (such as rainfall rate) is complicated due to a number of scattering mechanisms. The result is that there ends up being an intractable number of often incompatible techniques for extracting geophysical insight. This presentation will discuss methods developed by the Atmospheric Measurement Climate (ARM) Research Facility to streamline the creation of application chains for retrieving rainfall properties for the purposes of fine scale model evaluation. By using a Common Data Model (CDM) approach and working in the popular open source Python scientific environment analysis techniques such as Linear Programming (LP) can be bought to bear on the task of retrieving insight from radar signals. This presentation will outline how we have used these techniques to detangle polarimetric phase signals, estimate a three-dimensional precipitation field and then objectively compare to cloud resolving model derived rainfall fields from the NASA/DoE Mid-Latitude Continental Convective Clouds Experiment (MC3E). All techniques show will be available, open source, in the Python-ARM Radar Toolkit (Py-ART).

Evaluation of WRF Model Against Satellite and Field Measurements During ARM March 2000 IOP

NASA Astrophysics Data System (ADS)

Wu, J.; Zhang, M.

2003-12-01

Meso-scale WRF model is employed to simulate the organization of clouds related with the cyclogenesis occurred during March 1-4, 2000 over ARM SGP CART site. Qualitative comparisons of simulated clouds with GOES8 satellite images show that the WRF model can capture the main features of clouds related with the cyclogenesis. The simulated precipitation patterns also match the Radar reflectivity images well. Further evaluation of the simulated features on GCM grid-scale is conducted against ARM field measurements. The evaluation shows that the evolutions of the simulated state fields such as temperature and moisture, the simulated wind fields and the derived large-scale temperature and moisture tendencies closely follow the observed patterns. These results encourages us to use meso-scale WRF model as a tool to verify the performance of GCMs in simulating cloud feedback processes related with the frontal clouds such that we can test and validate the current cloud parameterizations in climate models, and make possible improvements to different components of current cloud parameterizations in GCMs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicoll, Ken A.; O'Connor, E.

Large-scale properties of clouds such as lifetime, optical thickness, and precipitation are all dependent on small-scale cloud microphysical processes. Such processes determine when droplets will grow or shrink, their size, and the number of cloud droplets. Although our understanding of cloud microphysics has vastly improved over the past several decades with the development of remote sensing methods such as lidar and radar, there remain a number of processes that are not well understood, such as the effect of electrical charge on cloud microphysics. To understand the various processes and feedback mechanisms, high-vertical–resolution observations are required. Radiosondes provide an ideal platformmore » for providing routine vertical profiles of in situ measurements at any location (with a vertical resolution of a few meters). Modified meteorological radiosondes have been extensively developed at the University of Reading for measuring cloud properties, to allow measurements beyond the traditional thermodynamic quantities (pressure, temperature and relative humidity) to be obtained cost-effectively. This project aims to investigate a number of cloud processes in which in situ cloud observations from these modified radiosondes can provide information either complementary to or not obtainable by lidar/radar systems. During two intensive operational periods (IOPs) in May and August 2014 during deployment to Hyytiälä, Finland, the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Second ARM Mobile Facility (AMF2) launched a total of 24 instrumented radiosondes through a number of different cloud types ranging from low-level stratiform cloud to cumulonimbus. Twelve balloon flights of an accelerometer turbulence sensor were made, which detected significant turbulence on eleven of these flights. Most of the turbulent episodes encountered were due to convective processes, but several were associated with the transition from troposphere to stratosphere at the tropopause. Similarities in the location of turbulent layers were generally found between the balloon turbulence sensor and the Ka-band radar, but with discrepancies between the orders of magnitude of turbulence detected. The reason for these discrepancies is the subject of future work.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalesse, Heike; Szyrmer, Wanda; Kneifel, Stefan

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyondmore » the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.« less

A 10-Year Climatology of Cloud Cover and Vertical Distribution Derived from Both Surface and GOES Observations Over the DOE ARM SGP Site

NASA Technical Reports Server (NTRS)

Xi, Baike; Dong, Xiquan; Minnis, P.; Khaiyer, M.

2010-01-01

Analysis of a decade of ARM radar-lidar and GOES observations at the SGP site reveal that 0.5 and 4-hr averages of the surface cloud fraction correspond closely to 0.5deg and 2.5deg averages of GOES cloudiness, respectively. The long-term averaged surface and GOES cloud fractions agree to within 0.5%. Cloud frequency increases and cloud amount decreases as the temporal and spatial averaging scales increase. Clouds occurred most often during winter and spring. Single-layered clouds account for 61.5% of the total cloud frequency. There are distinct bimodal vertical distributions of clouds with a lower peak around 1 km and an upper one that varies from 7.5 to 10.8 km between winter and summer, respectively. The frequency of occurrence for nighttime GOES high-cloud tops agree well with the surface observations, but are underestimated during the day.

Insights from modeling and observational evaluation of a precipitating continental cumulus event observed during the MC3E field campaign

DOE PAGES

Mechem, David B.; Giangrande, Scott E.; Wittman, Carly S.; ...

2015-03-13

A case of shallow cumulus and precipitating cumulus congestus sampled at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) supersite is analyzed using a multi-sensor observational approach and numerical simulation. Observations from a new radar suite surrounding the facility are used to characterize the evolving statistical behavior of the precipitating cloud system. This is accomplished using distributions of different measures of cloud geometry and precipitation properties. Large-eddy simulation (LES) with size-resolved (bin) microphysics is employed to determine the forcings most important in producing the salient aspects of the cloud system captured in the radar observations. Our emphasis ismore » on assessing the importance of time-varying vs. steady-state large-scale forcing on the model's ability to reproduce the evolutionary behavior of the cloud system. Additional consideration is given to how the characteristic spatial scale and homogeneity of the forcing imposed on the simulation influences the evolution of cloud system properties. Results indicate that several new scanning radar estimates such as distributions of cloud top are useful to differentiate the value of time-varying (or at least temporally well-matched) forcing on LES solution fidelity.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.

Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riihimaki, Laura D.; Comstock, Jennifer M.; Luke, Edward

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectramore » from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.« less

Life Cycle of Tropical Convection and Anvil in Observations and Models

NASA Astrophysics Data System (ADS)

McFarlane, S. A.; Hagos, S. M.; Comstock, J. M.

2011-12-01

Tropical convective clouds are important elements of the hydrological cycle and produce extensive cirrus anvils that strongly affect the tropical radiative energy balance. To improve simulations of the global water and energy cycles and accurately predict both precipitation and cloud radiative feedbacks, models need to realistically simulate the lifecycle of tropical convection, including the formation and radiative properties of ice anvil clouds. By combining remote sensing datasets from precipitation and cloud radars at the Atmospheric Radiation Measurement (ARM) Darwin site with geostationary satellite data, we can develop observational understanding of the lifetime of convective systems and the links between the properties of convective systems and their associated anvil clouds. The relationships between convection and anvil in model simulations can then be compared to those seen in the observations to identify areas for improvement in the model simulations. We identify and track tropical convective systems in the Tropical Western Pacific using geostationary satellite observations. We present statistics of the tropical convective systems including size, age, and intensity and classify the lifecycle stage of each system as developing, mature, or dissipating. For systems that cross over the ARM Darwin site, information on convective intensity and anvil properties are obtained from the C-Pol precipitation radar and MMCR cloud radar, respectively, and are examined as a function of the system lifecycle. Initial results from applying the convective identification and tracking algorithm to a tropical simulation from the Weather Research and Forecasting (WRF) model run show that the model produces reasonable overall statistics of convective systems, but details of the life cycle (such as diurnal cycle, system tracks) differ from the observations. Further work will focus on the role of atmospheric temperature and moisture profiles in the model's convective life cycle.

The Diurnal Cycle of Clouds and Precipitation at the ARM SGP Site: An Atmospheric State-Based Analysis and Error Decomposition of a Multiscale Modeling Framework Simulation

NASA Astrophysics Data System (ADS)

Zhao, Wei; Marchand, Roger; Fu, Qiang

2017-12-01

Long-term reflectivity data collected by a millimeter cloud radar at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to examine the diurnal cycle of clouds and precipitation and are compared with the diurnal cycle simulated by a Multiscale Modeling Framework (MMF) climate model. The study uses a set of atmospheric states that were created specifically for the SGP and for the purpose of investigating under what synoptic conditions models compare well with observations on a statistical basis (rather than using case studies or seasonal or longer time scale averaging). Differences in the annual mean diurnal cycle between observations and the MMF are decomposed into differences due to the relative frequency of states, the daily mean vertical profile of hydrometeor occurrence, and the (normalized) diurnal variation of hydrometeors in each state. Here the hydrometeors are classified as cloud or precipitation based solely on the reflectivity observed by a millimeter radar or generated by a radar simulator. The results show that the MMF does not capture the diurnal variation of low clouds well in any of the states but does a reasonable job capturing the diurnal variations of high clouds and precipitation in some states. In particular, the diurnal variations in states that occur during summer are reasonably captured by the MMF, while the diurnal variations in states that occur during the transition seasons (spring and fall) are not well captured. Overall, the errors in the annual composite are due primarily to errors in the daily mean of hydrometeor occurrence (rather than diurnal variations), but errors in the state frequency (that is, the distribution of weather states in the model) also play a significant role.

The Status of the ACRF Millimeter Wave Cloud Radars (MMCRs), the Path Forward for Future MMCR Upgrades, the Concept of 3D Volume Imaging Radar and the UAV Radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

P Kollias; MA Miller; KB Widener

2005-12-30

The United States (U.S.) Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) operates millimeter wavelength cloud radars (MMCRs) in several climatological regimes. The MMCRs, are the primary observing tool for quantifying the properties of nearly all radiatively important clouds over the ACRF sites. The first MMCR was installed at the ACRF Southern Great Plains (SGP) site nine years ago and its original design can be traced to the early 90s. Since then, several MMCRs have been deployed at the ACRF sites, while no significant hardware upgrades have been performed. Recently, a two-stage upgrade (first C-40 Digitalmore » Signal Processors [DSP]-based, and later the PC-Integrated Radar AcQuisition System [PIRAQ-III] digital receiver) of the MMCR signal-processing units was completed. Our future MMCR related goals are: 1) to have a cloud radar system that continues to have high reliability and uptime and 2) to suggest potential improvements that will address increased sensitivity needs, superior sampling and low cost maintenance of the MMCRs. The Traveling Wave Tube (TWT) technology, the frequency (35-GHz), the radio frequency (RF) layout, antenna, the calibration and radar control procedure and the environmental enclosure of the MMCR remain assets for our ability to detect the profile of hydrometeors at all heights in the troposphere at the ACRF sites.« less

"Atmospheric Radiation Measurement (ARM) Research Facility at Oliktok Point Alaska"

NASA Astrophysics Data System (ADS)

Helsel, F.; Ivey, M.; Hardesty, J.; Roesler, E. L.; Dexheimer, D.

2017-12-01

Scientific Infrastructure To Support Atmospheric Science, Aerosol Science and UAS's for The Department Of Energy's Atmospheric Radiation Measurement Programs At The Mobile Facility 3 Located At Oliktok Point, Alaska.The Atmospheric Radiation Measurement (ARM) Program's Mobile Facility 3 (AMF3) located at Oliktok Point, Alaska is a U.S. Department of Energy (DOE) site designed to collect data and help determine the impact that clouds and aerosols have on solar radiation. AMF3 provides a scientific infrastructure to support instruments and collect arctic data for the international arctic research community. The infrastructure at AMF3/Oliktok is designed to be mobile and it may be relocated in the future to support other ARM science missions. AMF3's present base line instruments include: scanning precipitation Radars, cloud Radar, Raman Lidar, Eddy correlation flux systems, Ceilometer, Balloon sounding system, Atmospheric Emitted Radiance Interferometer (AERI), Micro-pulse Lidar (MPL) Along with all the standard metrological measurements. In addition AMF3 provides aerosol measurements with a Mobile Aerosol Observing System (MAOS). Ground support for Unmanned Aerial Systems (UAS) and tethered balloon flights. Data from these instruments and systems are placed in the ARM data archives and are available to the international research community. This poster will discuss what instruments and systems are at the ARM Research Facility at Oliktok Point Alaska.

Measurement needs guided by synthetic radar scans in high-resolution model output

NASA Astrophysics Data System (ADS)

Varble, A.; Nesbitt, S. W.; Borque, P.

2017-12-01

Microphysical and dynamical process interactions within deep convective clouds are not well understood, partly because measurement strategies often focus on statistics of cloud state rather than cloud processes. While processes cannot be directly measured, they can be inferred with sufficiently frequent and detailed scanning radar measurements focused on the life cycleof individual cloud regions. This is a primary goal of the 2018-19 DOE ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) and NSF Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaigns in central Argentina, where orographic deep convective initiation is frequent with some high-impact systems growing into the tallest and largest in the world. An array of fixed and mobile scanning multi-wavelength dual-polarization radars will be coupled with surface observations, sounding systems, multi-wavelength vertical profilers, and aircraft in situ measurements to characterize convective cloud life cycles and their relationship with environmental conditions. While detailed cloud processes are an observational target, the radar scan patterns that are most ideal for observing them are unclear. They depend on the locations and scales of key microphysical and dynamical processes operating within the cloud. High-resolution simulations of clouds, while imperfect, can provide information on these locations and scales that guide radar measurement needs. Radar locations are set in the model domain based on planned experiment locations, and simulatedorographic deep convective initiation and upscale growth are sampled using a number of different scans involving RHIs or PPIs with predefined elevation and azimuthal angles that approximately conform with radar range and beam width specifications. Each full scan pattern is applied to output atsingle model time steps with time step intervals that depend on the length of time required to complete each scan in the real world. The ability of different scans to detect key processes within the convective cloud life cycle are examined in connection with previous and subsequent dynamical and microphysical transitions. This work will guide strategic scan patterns that will be used during CACTI and RELAMPAGO.

DOE ASR Final Report on “Use of ARM Observations to Investigate the Role of Tropical Radiative Processes and Cloud Radiative Effects in Climate Simulations”

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, Qiang; Comstock, Jennifer

The overall objective of this ASR funded project is to investigate the role of cloud radiative effects, especially those associated with tropical thin cirrus clouds in the tropical tropopause layer, by analyzing the ARM observations combined with numerical models. In particular, we have processed and analyzed the observations from the Raman lidar at the ARM SGP and TWP sites. In the tenure of the project (8/15/2013 – 8/14/2016 and with a no-cost extension to 8/14/2017), we have been concentrating on (i) developing an automated feature detection scheme of clouds and aerosols for the ARM Raman lidar; (ii) developing an automatedmore » retrieval of cloud and aerosol extinctions for the ARM Raman lidar; (iii) investigating cloud radiative effects based on the observations on the simulated temperatures in the tropical tropopause layer using a radiative-convective model; and (iv) examining the effect of changes of atmospheric composition on the tropical lower-stratospheric temperatures. In addition, we have examined the biases in the CALIPSO-inferred aerosol direct radiative effects using ground-based Raman lidars at the ARM SGP and TWP sites, and estimated the impact of lidar detection sensitivity on assessing global aerosol direct radiative effects. We have also investigated the diurnal cycle of clouds and precipitation at the ARM site using the cloud radar observations along with simulations from the multiscale modeling framework. The main results of our research efforts are reported in the six referred journal publications that acknowledge the DOE Grant DE-SC0010557.« less

Preliminary Findings from the One-Year Electric Field Study in the North Slope of Alaska (OYES-NSA), Atmospheric Radiation Measurement (ARM) Field Campaign

NASA Astrophysics Data System (ADS)

Lavigne, T.; Liu, C.

2017-12-01

Previous studies focusing on the comparison of the measured electric field to the physical properties of global electrified clouds have been conducted almost exclusively in the Southern Hemisphere. The One-Year Electric Field Study-North Slope of Alaska (OYES-NSA) aims to establish a long-running collection of this valuable electric field data in the Northern Hemisphere. Presented here is the six-month preliminary data and results of the OYES-NSA Atmospheric Radiation Mission (ARM) field campaign. The local electric field measured in Barrow, Alaska using two CS110 reciprocating shutter field meters, has been compared to simultaneous measurements from the ARM Ka-Band zenith radar, to better understand the influence and contribution of different types of clouds on the local electric field. The fair-weather electric field measured in Barrow has also been analyzed and compared to the climatology of electric field at Vostok Station, Antarctica. The combination of the electric field dataset in the Northern Hemisphere, alongside the local Ka cloud radar, global Precipitation Feature (PF) database, and quasi-global lightning activity (55oN-55oS), allows for advances in the physical understanding of the local electric field, as well as the Global Electric Circuit (GEC).

A Climatology of Surface Cloud Radiative Effects at the ARM Tropical Western Pacific Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

McFarlane, Sally A.; Long, Charles N.; Flaherty, Julia E.

Cloud radiative effects on surface downwelling fluxes are investigated using long-term datasets from the three Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) region. The Nauru and Darwin sites show significant variability in sky cover, downwelling radiative fluxes, and surface cloud radiative effect (CRE) due to El Niño and the Australian monsoon, respectively, while the Manus site shows little intra-seasonal or interannual variability. Cloud radar measurement of cloud base and top heights are used to define cloud types so that the effect of cloud type on the surface CRE can be examined. Clouds with low bases contributemore » 71-75% of the surface shortwave (SW) CRE and 66-74% of the surface longwave (LW) CRE at the three TWP sites, while clouds with mid-level bases contribute 8-9% of the SW CRE and 12-14% of the LW CRE, and clouds with high bases contribute 16-19% of the SW CRE and 15-21% of the LW CRE.« less

A 19-Month Climatology of Marine Aerosol-Cloud-Radiation Properties Derived From DOE ARM AMF Deployment at the Azores: Part I: Cloud Fraction and Single-Layered MBL Cloud Properties

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Minnis, Patrick; Wood, Robert

2013-01-01

A 19-month record of total, and single-layered low (0-3 km), middle (3-6 km), and high (> 6 km) cloud fractions (CFs), and the single-layered marine boundary layer (MBL) cloud macrophysical and microphysical properties has been generated from ground-based measurements taken at the ARM Azores site between June 2009 and December 2010. It documents the most comprehensive and longest dataset on marine cloud fraction and MBL cloud properties to date. The annual means of total CF, and single-layered low, middle, and high CFs derived from ARM radar-lidar observations are 0.702, 0.271, 0.01 and 0.106, respectively. More total and single-layered high CFs occurred during winter, while single-layered low CFs were greatest during summer. The diurnal cycles for both total and low CFs are stronger during summer than during winter. The CFs are bimodally distributed in the vertical with a lower peak at approx. 1 km and higher one between 8 and 11 km during all seasons, except summer, when only the low peak occurs. The persistent high pressure and dry conditions produce more single-layered MBL clouds and fewer total clouds during summer, while the low pressure and moist air masses during winter generate more total and multilayered-clouds, and deep frontal clouds associated with midlatitude cyclones.

Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.

2013-05-22

Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on themore » cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.« less

Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, Kirk W.; Oue, Mariko; Kollias, Pavlos

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with thosemore » from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s -1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s -1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. Lastly, the results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.« less

Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

DOE PAGES

North, Kirk W.; Oue, Mariko; Kollias, Pavlos; ...

2017-08-04

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with thosemore » from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s -1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s -1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. Lastly, the results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.« less

Observed Aerosol Influence on Ice Water Content of Arctic Mixed-Phase Clouds

NASA Astrophysics Data System (ADS)

Norgren, M.; de Boer, G.; Shupe, M.

2016-12-01

The response of ice water content (IWC) in Arctic mixed-phase stratocumulus to atmospheric aerosols is observed. IWC retrievals from ground based radars operated by the Atmospheric Radiation Measurement (ARM) program in Barrow, Alaska are used to construct composite profiles of cloud IWC from a 9-year radar record starting in January of 2000. The IWC profiles for high (polluted) and low (clean) aerosol loadings are compared. Generally, we find that clean clouds exhibit statistically significant higher levels of IWC than do polluted clouds by a factor of 2-4 at cloud base. For springtime clouds, with a maximum relative humidity with respect to ice (RHI) above 110% in the cloud layer, the IWC at cloud base was a factor of 3.25 times higher in clean clouds than it was in polluted clouds. We infer that the aerosol loading of the cloud environment alters the liquid drop size distribution within the cloud, with larger drops being more frequent in clean clouds. Larger cloud drops promote riming within the cloud layer, which is one explanation for the higher IWC levels in clean clouds. The drop size distribution may also be a significant control of ice nucleation events within mixed-phase clouds. Whether the high IWC levels in clean clouds are due to increased riming or nucleation events is unclear at this time.

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

NASA Astrophysics Data System (ADS)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

NASA Astrophysics Data System (ADS)

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

2017-07-01

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100-200 % for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASC measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18 % difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36 % for the individual events. Use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122 % for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. More accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.

An ARM Mobile Facility Designed for Marine Deployments

NASA Astrophysics Data System (ADS)

Wiscombe, W. J.

2007-05-01

The U.S. Dept. of Energy's ARM (Atmospheric Radiation Measurements) Program is designing a Mobile Facility exclusively for marine deployments. This marine facility is patterned after ARM's land Mobile Facility, which had its inaugural deployment at Point Reyes, California, in 2005, followed by deployments to Niger in 2006 and Germany in 2007 (ongoing), and a planned deployment to China in 2008. These facilities are primarily intended for the study of clouds, radiation, aerosols, and surface processes with a goal to include these processes accurately in climate models. They are preferably embedded within larger field campaigns which provide context. They carry extensive instrumentation (in several large containers) including: cloud radar, lidar, microwave radiometers, infrared spectrometers, broadband and narrowband radiometers, sonde-launching facilities, extensive surface aerosol measurements, sky imagers, and surface latent and sensible heat flux devices. ARM's Mobile Facilities are designed for 6-10 month deployments in order to capture climatically-relevant datasets. They are available to any scientist, U.S. or international, who wishes to submit a proposal during the annual Spring call. The marine facility will be adapted to, and ruggedized for, the harsh marine environment and will add a scanning two-frequency radar, a boundary-layer wind profiler, a shortwave spectrometer, and aerosol instrumentation adapted to typical marine aerosols like sea salt. Plans also include the use of roving small UAVs, automated small boats, and undersea autonomous vehicles in order to address the point-to-area-average problem which is so crucial for informing climate models. Initial deployments are planned for small islands in climatically- interesting cloud regimes, followed by deployments on oceanic platforms (like decommissioned oil rigs and the quasi-permanent platform of this session's title) and eventually on large ships like car carriers plying routine routes.

Using long-term ARM observations to evaluate Arctic mixed-phased cloud representation in the GISS ModelE GCM

NASA Astrophysics Data System (ADS)

Lamer, K.; Fridlind, A. M.; Luke, E. P.; Tselioudis, G.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2016-12-01

The presence of supercooled liquid in clouds affects surface radiative and hydrological budgets, especially at high latitudes. Capturing these effects is crucial to properly quantifying climate sensitivity. Currently, a number of CGMs disagree on the distribution of cloud phase. Adding to the challenge is a general lack of observations on the continuum of clouds, from high to low-level and from warm to cold. In the current study, continuous observations from 2011 to 2014 are used to evaluate all clouds produced by the GISS ModelE GCM over the ARM North Slope of Alaska site. The International Satellite Cloud Climatology Project (ISCCP) Global Weather State (GWS) approach reveals that fair-weather (GWS 7, 32% occurrence rate), as well as mid-level storm related (GWS 5, 28%) and polar (GWS 4, 14%) clouds, dominate the large-scale cloud patterns at this high latitude site. At higher spatial and temporal resolutions, ground-based cloud radar observations reveal a majority of single layer cloud vertical structures (CVS). While clear sky and low-level clouds dominate (each with 30% occurrence rate) a fair amount of shallow ( 10%) to deep ( 5%) convection are observed. Cloud radar Doppler spectra are used along with depolarization lidar observations in a neural network approach to detect the presence, layering and inhomogeneity of supercooled liquid layers. Preliminary analyses indicate that most of the low-level clouds sampled contain one or more supercooled liquid layers. Furthermore, the relationship between CVS and the presence of supercooled liquid is established, as is the relationship between the presence of supercool liquid and precipitation susceptibility. Two approaches are explored to bridge the gap between large footprint GCM simulations and high-resolution ground-based observations. The first approach consists of comparing model output and ground-based observations that exhibit the same column CVS type (i.e. same cloud depth, height and layering). Alternatively, the second approach consists of comparing model output and ground-based observations that exhibit the same large-scale GWS type (i.e. same cloud top pressure and optical depth patterns) where ground-based observations are associated to large-scale GWS every 3 hours using the closest satellite overpass.

Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, Michael P; Giangrande, Scott E; Bartholomew, Mary Jane

The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf] campaign was scheduled to take place from 15 July 2013 through 15 July 2015 (or until shipped for the next U.S. Department of Energy Atmospheric Radiation Measurement [ARM] Climate Research Facility first Mobile Facility [AMF1] deployment). The campaign involved the deployment of the AMF1 Scintec 915 MHz Radar Wind Profiler (RWP) at BNL, in conjunction with several other ARM, BNL and National Weather Service (NWS) instruments. The two main scientific foci of the campaign were: 1) To provide profiles of the horizontal wind to be used tomore » test and validate short-term cloud advection forecasts for solar-energy applications and 2) to provide vertical profiling capabilities for the study of dynamics (i.e., vertical velocity) and hydrometeors in winter storms. This campaign was a serendipitous opportunity that arose following the deployment of the RWP at the Two-Column Aerosol Project (TCAP) campaign in Cape Cod, Massachusetts and restriction from participation in the Green Ocean Amazon 2014/15 (GoAmazon 2014/15) campaign due to radio-frequency allocation restriction for international deployments. The RWP arrived at BNL in the fall of 2013, but deployment was delayed until fall of 2014 as work/safety planning and site preparation were completed. The RWP further encountered multiple electrical failures, which eventually required several shipments of instrument power supplies and the final amplifier to the vendor to complete repairs. Data collection began in late January 2015. The operational modes of the RWP were changed such that in addition to collecting traditional profiles of the horizontal wind, a vertically pointing mode was also included for the purpose of precipitation sensing and estimation of vertical velocities. The RWP operated well until the end of the campaign in July 2015 and collected observations for more than 20 precipitation events.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, Michael; Kollias, Pavlos; Giangrande, Scott

The Mid-latitude Continental Convective Clouds Experiment (MC3E) took place from April 22 through June 6, 2011, centered at the ARM Southern Great Plains site (http://www.arm.gov/sites/sgp) in northcentral Oklahoma. MC3E was a collaborative effort between the ARM Climate Research Facility and the National Aeronautics and Space Administration’s (NASA’s) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. The campaign leveraged the largest ground-based observing infrastructure available in the central United States, including recent upgrades through the American Recovery and Reinvestment Act of 2009, combined with an extensive sounding array, remote sensing and in situ aircraft observations, and additional radar and inmore » situ precipitation instrumentation. The overarching goal of the campaign was to provide a three-dimensional characterization of convective clouds and precipitation for the purpose of improving the representation of convective lifecycle in atmospheric models and the reliability of satellite-based retrievals of precipitation.« less

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

DOE PAGES

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

2017-07-20

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100–200% for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASCmore » measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18% difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36% for the individual events. The use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. Furthermore, accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.« less

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100–200% for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASCmore » measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18% difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36% for the individual events. The use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. Furthermore, accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.« less

A 3-Year Climatology of Cloud and Radiative Properties Derived from GOES-8 Data Over the Southern Great Plains

NASA Technical Reports Server (NTRS)

Khaiyer, M. M.; Rapp, A. D.; Doelling, D. R.; Nordeen, M. L.; Minnis, P.; Smith, W. L., Jr.; Nguyen, L.

2001-01-01

While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.

Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site

NASA Astrophysics Data System (ADS)

Dong, Xiquan; Minnis, Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-02-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-h interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30 km × 30 km box centered on the ARM SGP site. Two data sets were analyzed: all of the data (ALL), which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 ± 0.542 km and 0.108 ± 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 ± 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km-1. On the basis of a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius re, optical depth, and liquid water path for SL stratus are 0.1 ± 1.9 μm (1.2 ± 23.5%), -1.3 ± 9.5 (-3.6 ± 26.2%), and 0.6 ± 49.9 gm-2 (0.3 ± 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 ± 1.9 μm (2.5 ± 23.4%), 2.5 ± 7.8 (7.8 ± 24.3%), and 28.1 ± 52.7 gm-2 (17.2 ± 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in re was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of re is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. Methods for improving the cloud top height and microphysical property retrievals are suggested.

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Minnis Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-01-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Optimizing observations of drizzle onset with millimeter-wavelength radars

DOE PAGES

Acquistapace, Claudia; Kneifel, Stefan; Löhnert, Ulrich; ...

2017-05-12

Cloud Doppler radars are increasingly used to study cloud and precipitation microphysical processes. Typical bulk cloud properties such as liquid or ice content are usually derived using the first three standard moments of the radar Doppler spectrum. Recent studies demonstrated the value of higher moments for the reduction of retrieval uncertainties and for providing additional insights into microphysical processes. Large effort has been undertaken, e.g., within the Atmospheric Radiation Measurement (ARM) program to ensure high quality of radar Doppler spectra. However, a systematic approach concerning the accuracy of higher moment estimates and sensitivity to basic radar system settings, such asmore » spectral resolution, integration time and beam width, are still missing. Here In this study, we present an approach on how to optimize radar settings for radar Doppler spectra moments in the specific context of drizzle detection. The process of drizzle development has shown to be particularly sensitive to higher radar moments such as skewness. We collected radar raw data (I/Q time series) from consecutive zenith-pointing observations for two liquid cloud cases observed at the cloud observatory JOYCE in Germany. The I/Q data allowed us to process Doppler spectra and derive their moments using different spectral resolutions and integration times during identical time intervals. This enabled us to study the sensitivity of the spatiotemporal structure of the derived moments to the different radar settings. The observed signatures were further investigated using a radar Doppler forward model which allowed us to compare observed and simulated sensitivities and also to study the impact of additional hardware-dependent parameters such as antenna beam width. For the observed cloud with drizzle onset we found that longer integration times mainly modify spectral width ( S w) and skewness ( S k), leaving other moments mostly unaffected. An integration time of 2 s seems to be an optimal compromise: both observations and simulations revealed that a 10 s integration time – as it is widely used for European cloud radars – leads to a significant turbulence-induced increase of S w and reduction of S k compared to 2 s integration time. This can lead to significantly different microphysical interpretations with respect to drizzle water content and effective radius. A change from 2 s to even shorter integration times (0. 4 s) has much smaller effects on S w and S k. We also find that spectral resolution has a small impact on the moment estimations, and thus on the microphysical interpretation of the drizzle signal. Even the coarsest spectral resolution studied, 0. 08 ms -1, seems to be appropriate for calculation moments of drizzling clouds. Moreover, simulations provided additional insight into the microphysical interpretation of the skewness signatures observed: in low (high)-turbulence conditions, only drizzle larger than 20 µm (40 µm) can generate S k values above the S k noise level (in our case 0.4). Higher S k values are also obtained in simulations when smaller beam widths are adopted.« less

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

NASA Technical Reports Server (NTRS)

Chiu, J. C.; Marshak, A.; Huang, C.-H.; Varnai, T.; Hogan, R. J.; Giles, D. M.; Holben, B. N.; Knyazikhin, Y.; O'Connor, E. J.; Wiscombe, W. J.

2012-01-01

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Evaluating Microphysics in Cloud-Resolving Models using TRMM and Ground-based Precipitation Radar Observations

NASA Astrophysics Data System (ADS)

Krueger, S. K.; Zulauf, M. A.; Li, Y.; Zipser, E. J.

2005-05-01

Global satellite datasets such as those produced by ISCCP, ERBE, and CERES provide strong observational constraints on cloud radiative properties. Such observations have been widely used for model evaluation, tuning, and improvement. Cloud radiative properties depend primarily on small, non-precipitating cloud droplets and ice crystals, yet the dynamical, microphysical and radiative processes which produce these small particles often involve large, precipitating hydrometeors. There now exists a global dataset of tropical cloud system precipitation feature (PF) properties, collected by TRMM and produced by Steve Nesbitt, that provides additional observational constraints on cloud system properties. We are using the TRMM PF dataset to evaluate the precipitation microphysics of two simulations of deep, precipitating, convective cloud systems: one is a 29-day summertime, continental case (ARM Summer 1997 SCM IOP, at the Southern Great Plains site); the second is a tropical maritime case: the Kwajalein MCS of 11-12 August 1999 (part of a 52-day simulation). Both simulations employed the same bulk, three-ice category microphysical parameterization (Krueger et al. 1995). The ARM simulation was executed using the UCLA/Utah 2D CRM, while the KWAJEX simulation was produced using the 3D CSU CRM (SAM). The KWAJEX simulation described above is compared with both the actual radar data and the TRMM statistics. For the Kwajalein MCS of 11 to 12 August 1999, there are research radar data available for the lifetime of the system. This particular MCS was large in size and rained heavily, but it was weak to average in measures of convective intensity, against the 5-year TRMM sample of 108. For the Kwajalein MCS simulation, the 20 dBZ contour is at 15.7 km and the 40 dBZ contour at 14.5 km! Of all 108 MCSs observed by TRMM, the highest value for the 40 dBZ contour is 8 km. Clearly, the high reflectivity cores are off scale compared with observed cloud systems in this area. A similar conclusion can be reached by comparing the simulated microwave brightness temperatures with observed brightness temperatures at 85 GHz and 37 GHz. In each case, the simulations are more extreme than all observed MCSs in the region over the 5 year period. The situation is similar but less egregious for the southern Great Plains simulation. Inspection of the cloud microphysics output files reveals the source of the discrepancy between simulation and observations in the upper troposphere. The simulations have very large graupel concentrations between about 5-10 km, as high as 10 g/kg graupel mixing ratio. This guarantees that there are very high radar reflectivities extending into the upper troposphere, and unrealistically low microwave brightness temperatures. We also performed a set of short (6-h) numerical simulations of the life cycle of a single convection cell to examine the sensitivity of the simulated graupel fields to the intercept parameter and the density of the graupel. The control case used the same values as the ARM and KWAJEX simulations. Reducing the intercept parameter by a factor of 100 reduced the maximum graupel mixing ratios but increased the maximum dBZ values. This suggests that the discrepencies between the simulations and the observations must involve the graupel growth rates.

Cloudiness and Marine Boundary Layer Variability at the ARM Eastern North Atlantic Site

NASA Astrophysics Data System (ADS)

Remillard, J.; Kollias, P.; Zhou, X.; Luke, E. P.

2016-12-01

The US Department of Energy Atmospheric Radiation Measurement (ARM) program operates a fixed ground-based site at Graciosa Island in the Azores in the Eastern North Atlantic (ENA). The measurement record extends through two warm seasons where marine boundary layer (MBL) clouds prevail. Here, a plethora of ground-based observations from the ARM ENA site are used to characterize the vertical and horizontal variability of the MBL and associated cloudiness. In particular, the Doppler lidar observations along with thermodynamic information are used to determine the coupling or decoupling of the MBL. The horizontal variability of the sub-cloud layer is assessed via wavelet analysis and compared to the cloud scale, which is quantified by Fourier analysis of liquid water path (LWP) from microwave radiometer observations. The role of drizzle-induced evaporative cooling and moistening in modifying the MBL is examined using surface measurements, microwave radiometer, ceilometer, cloud radar and Doppler lidar observations. The MBL variability is categorized by the strength of drizzle and their relation is studied. Furthermore, the relationship between MBL cloudiness and subsidence is tested using reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Weather states from the International Satellite Cloud Climatology Project (ISCCP) put the results into a more general context, and provide an easy way to link them to the atmospheric situation surrounding the area.

Wide Angle Imaging Lidar (WAIL): Theory of Operation and Results from Cross-Platform Validation at the ARM Southern Great Plains Site

NASA Astrophysics Data System (ADS)

Polonsky, I. N.; Davis, A. B.; Love, S. P.

2004-05-01

WAIL was designed to determine physical and geometrical characteristics of optically thick clouds using the off-beam component of the lidar return that can be accurately modeled within the 3D photon diffusion approximation. The theory shows that the WAIL signal depends not only on the cloud optical characteristics (phase function, extinction and scattering coefficients) but also on the outer thickness of the cloud layer. This makes it possible to estimate the mean optical and geometrical thicknesses of the cloud. The comparison with Monte Carlo simulation demonstrates the high accuracy of the diffusion approximation for moderately to very dense clouds. During operation WAIL is able to collect a complete data set from a cloud every few minutes, with averaging over horizontal scale of a kilometer or so. In order to validate WAIL's ability to deliver cloud properties, the LANL instrument was deployed as a part of the THickness from Off-beam Returns (THOR) validation IOP. The goal was to probe clouds above the SGP CART site at night in March 2002 from below (WAIL and ARM instruments) and from NASA's P3 aircraft (carrying THOR, the GSFC counterpart of WAIL) flying above the clouds. The permanent cloud instruments we used to compare with the results obtained from WAIL were ARM's laser ceilometer, micro-pulse lidar (MPL), millimeter-wavelength cloud radar (MMCR), and micro-wave radiometer (MWR). The comparison shows that, in spite of an unusually low cloud ceiling, an unfavorable observation condition for WAIL's present configuration, cloud properties obtained from the new instrument are in good agreement with their counterparts obtained by other instruments. So WAIL can duplicate, at least for single-layer clouds, the cloud products of the MWR and MMCR together. But WAIL does this with green laser light, which is far more representative than microwaves of photon transport processes at work in the climate system.

Physical Validation of GPM Retrieval Algorithms Over Land: An Overview of the Mid-Latitude Continental Convective Clouds Experiment (MC3E)

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Jensen, Michael P.

2011-01-01

The joint NASA Global Precipitation Measurement (GPM) -- DOE Atmospheric Radiation Measurement (ARM) Midlatitude Continental Convective Clouds Experiment (MC3E) was conducted from April 22-June 6, 2011, centered on the DOE-ARM Southern Great Plains Central Facility site in northern Oklahoma. GPM field campaign objectives focused on the collection of airborne and ground-based measurements of warm-season continental precipitation processes to support refinement of GPM retrieval algorithm physics over land, and to improve the fidelity of coupled cloud resolving and land-surface satellite simulator models. DOE ARM objectives were synergistically focused on relating observations of cloud microphysics and the surrounding environment to feedbacks on convective system dynamics, an effort driven by the need to better represent those interactions in numerical modeling frameworks. More specific topics addressed by MC3E include ice processes and ice characteristics as coupled to precipitation at the surface and radiometer signals measured in space, the correlation properties of rainfall and drop size distributions and impacts on dual-frequency radar retrieval algorithms, the transition of cloud water to rain water (e.g., autoconversion processes) and the vertical distribution of cloud water in precipitating clouds, and vertical draft structure statistics in cumulus convection. The MC3E observational strategy relied on NASA ER-2 high-altitude airborne multi-frequency radar (HIWRAP Ka-Ku band) and radiometer (AMPR, CoSMIR; 10-183 GHz) sampling (a GPM "proxy") over an atmospheric column being simultaneously profiled in situ by the University of North Dakota Citation microphysics aircraft, an array of ground-based multi-frequency scanning polarimetric radars (DOE Ka-W, X and C-band; NASA D3R Ka-Ku and NPOL S-bands) and wind-profilers (S/UHF bands), supported by a dense network of over 20 disdrometers and rain gauges, all nested in the coverage of a six-station mesoscale rawinsonde network. As an exploratory effort to examine land-surface emissivity impacts on retrieval algorithms, and to demonstrate airborne soil moisture retrieval capabilities, the University of Tennessee Space Institute Piper aircraft carrying the MAPIR L-band radiometer was also flown during the latter half of the experiment in coordination with the ER-2. The observational strategy provided a means to sample the atmospheric column in a redundant framework that enables inter-calibration and constraint of measured and retrieved precipitation characteristics such as particle size distributions, or water contents- all within the umbrella of "proxy" satellite measurements (i.e., the ER-2). Complimenting the precipitation sampling framework, frequent and coincident launches of atmospheric soundings (e.g., 4-8/day) then provided a much larger mesoscale view of the thermodynamic and winds environment, a data set useful for initializing cloud models. The datasets collected represent a variety cloud and precipitation types including isolated cumulus clouds, severe thunderstorms, mesoscale convective systems, and widespread regions of light to moderate stratiform precipitation. We will present the MC3E experiment design, an overview of operations, and a summary of preliminary results.

A Ground-Based Doppler Radar and Micropulse Lidar Forward Simulator for GCM Evaluation of Arctic Mixed-Phase Clouds: Moving Forward Towards an Apples-to-apples Comparison of Hydrometeor Phase

NASA Astrophysics Data System (ADS)

Lamer, K.; Fridlind, A. M.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2017-12-01

An important aspect of evaluating Artic cloud representation in a general circulation model (GCM) consists of using observational benchmarks which are as equivalent as possible to model output in order to avoid methodological bias and focus on correctly diagnosing model dynamical and microphysical misrepresentations. However, current cloud observing systems are known to suffer from biases such as limited sensitivity, and stronger response to large or small hydrometeors. Fortunately, while these observational biases cannot be corrected, they are often well understood and can be reproduced in forward simulations. Here a ground-based millimeter wavelength Doppler radar and micropulse lidar forward simulator able to interface with output from the Goddard Institute for Space Studies (GISS) ModelE GCM is presented. ModelE stratiform hydrometeor fraction, mixing ratio, mass-weighted fall speed and effective radius are forward simulated to vertically-resolved profiles of radar reflectivity, Doppler velocity and spectrum width as well as lidar backscatter and depolarization ratio. These forward simulated fields are then compared to Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) ground-based observations to assess cloud vertical structure (CVS). Model evalution of Arctic mixed-phase cloud would also benefit from hydrometeor phase evaluation. While phase retrieval from synergetic observations often generates large uncertainties, the same retrieval algorithm can be applied to observed and forward-simulated radar-lidar fields, thereby producing retrieved hydrometeor properties with potentially the same uncertainties. Comparing hydrometeor properties retrieved in exactly the same way aims to produce the best apples-to-apples comparisons between GCM ouputs and observations. The use of a comprenhensive ground-based forward simulator coupled with a hydrometeor classification retrieval algorithm provides a new perspective for GCM evaluation of Arctic mixed-phase clouds from the ground where low-level supercooled liquid layer are more easily observed and where additional environmental properties such as cloud condensation nuclei are quantified. This should help assist in choosing between several possible diagnostic ice nucleation schemes for ModelE stratiform cloud.

Improved Arctic Cloud and Aerosol Research and Model Parameterizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kenneth Sassen

2007-03-01

In this report are summarized our contributions to the Atmospheric Measurement (ARM) program supported by the Department of Energy. Our involvement commenced in 1990 during the planning stages of the design of the ARM Cloud and Radiation Testbed (CART) sites. We have worked continuously (up to 2006) on our ARM research objectives, building on our earlier findings to advance our knowledge in several areas. Below we summarize our research over this period, with an emphasis on the most recent work. We have participated in several aircraft-supported deployments at the SGP and NSA sites. In addition to deploying the Polarization Diversitymore » Lidar (PDL) system (Sassen 1994; Noel and Sassen 2005) designed and constructed under ARM funding, we have operated other sophisticated instruments W-band polarimetric Doppler radar, and midinfrared radiometer for intercalibration and student training purposes. We have worked closely with University of North Dakota scientists, twice co-directing the Citation operations through ground-to-air communications, and serving as the CART ground-based mission coordinator with NASA aircraft during the 1996 SUCCESS/IOP campaign. We have also taken a leading role in initiating case study research involving a number of ARM coinvestigators. Analyses of several case studies from these IOPs have been reported in journal articles, as we show in Table 1. The PDL has also participated in other major field projects, including FIRE II and CRYSTAL-FACE. In general, the published results of our IOP research can be divided into two categories: comprehensive cloud case study analyses to shed light on fundamental cloud processes using the unique CART IOP measurement capabilities, and the analysis of in situ data for the testing of remote sensing cloud retrieval algorithms. One of the goals of the case study approach is to provide sufficiently detailed descriptions of cloud systems from the data-rich CART environment to make them suitable for application to cloud modeling groups, such as the GEWEX Cloud Simulation Study (GCSS) Cirrus Working Groups. In this paper we summarize our IOP-related accomplishments.« less

Validation of satellite-retrieved MBL cloud properties using DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, B.; Dong, X.; Minnis, P.; Sun-Mack, S.

2013-05-01

Marine Boundary Layer (MBL) cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) AMF AZORES site from June 2009 through December 2010. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS Ed4 cloud properties were averaged within a 30-km x 30-km box centered on the ARM AZORES site. Two datasets were analyzed: all of the single-layered unbroken decks (SL) and those cases without temperature inversions. The CERES-MODIS cloud top/base heights were determined from cloud top/base temperature by using a lapse rate method normalized to the 24-h mean surface air temperature. The preliminary results show: for all SL MBL at daytime, they are, on average, 0.148 km (cloud top) and 0.087 km (cloud base) higher than the ARM radar-lidar observed cloud top and base, respectively. At nighttime, they are 0.446 km (cloud top) and 0.334 km (cloud base). For those cases without temperature inversions, the comparisons are close to their SL counterparts. For cloud temperatures, the MODIS-derived cloud-top and -base temperatures are 1.6 K lower and 0.4 K higher than the surface values with correlations of 0.92 during daytime. At nighttime, the differences are slightly larger and correlations are lower than daytime comparisons. Variations in the height difference are mainly caused by uncertainties in the surface air temperatures and lapse rates. Based on a total of 61 daytime and 87 nighttime samples (ALL SL cases), the temperature inversion layers occur about 72% during daytime and 83% during nighttime. The difference of surface-observed lapse rate and the satellite derived lapse rate can be 1.6 K/km for daytime and 3.3K/km for nighttime. From these lapse rates, we can further analyze the surface air temperature difference that used to calculate these lapse rate, which are ~3K difference between surface-observed and the satellite derived during the daytime and 5.1 K during nighttime. Further studies of the cause of the temperature inversions that may help the cloud heights retrievals by satellite. The preliminary comparisons in MBL microphysical properties have shown that the averaged CERES-MODIS derived MBL cloud-droplet effective radius is only 1.5 μm larger than ARM retrieval (13.2 μm), and LWP values are also very close to each other (112 vs. 124 gm-2) with a relative large difference in optical depth (10.6 vs. 14.4).

Understanding Ice Supersaturation, Particle Growth, and Number Concentration in Cirrus Clouds

NASA Technical Reports Server (NTRS)

Comstock, Jennifer M.; Lin, Ruei-Fong; Starr, David O'C.; Yang, Ping

2008-01-01

Many factors control the ice supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, ice nucleation mechanisms, and ice crystal growth rate on the evolution and distribution of water vapor and cloud properties in nighttime cirrus clouds using a one-dimensional cloud model with bin microphysics and remote sensing measurements obtained at the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. We forced the model using both large-scale vertical ascent and, for the first time, mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where a classical theory heterogeneous scheme is compared with empirical representations. We evaluated model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities. Model sensitivity to the ice growth rate is also investigated. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast ice crystal growth, and initiate ice by either homogeneous or heterogeneous nucleation. Simulated ice crystal number concentrations (tens to hundreds particles per liter) are typically two orders of magnitude smaller than previously published results based on aircraft measurements in cirrus clouds, although higher concentrations are possible in isolated pockets within the nucleation zone.

The first observed cloud echoes and microphysical parameter retrievals by China's 94-GHz cloud radar

NASA Astrophysics Data System (ADS)

Wu, Juxiu; Wei, Ming; Hang, Xin; Zhou, Jie; Zhang, Peichang; Li, Nan

2014-06-01

By using the cloud echoes first successfully observed by China's indigenous 94-GHz SKY cloud radar, the macrostructure and microphysical properties of drizzling stratocumulus clouds in Anhui Province on 8 June 2013 are analyzed, and the detection capability of this cloud radar is discussed. The results are as follows. (1) The cloud radar is able to observe the time-varying macroscopic and microphysical parameters of clouds, and it can reveal the microscopic structure and small-scale changes of clouds. (2) The velocity spectral width of cloud droplets is small, but the spectral width of the cloud containing both cloud droplets and drizzle is large. When the spectral width is more than 0.4 m s-1, the radar reflectivity factor is larger (over -10 dBZ). (3) The radar's sensitivity is comparatively higher because the minimum radar reflectivity factor is about -35 dBZ in this experiment, which exceeds the threshold for detecting the linear depolarized ratio (LDR) of stratocumulus (commonly -11 to -14 dBZ; decreases with increasing turbulence). (4) After distinguishing of cloud droplets from drizzle, cloud liquid water content and particle effective radius are retrieved. The liquid water content of drizzle is lower than that of cloud droplets at the same radar reflectivity factor.

The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

DOE PAGES

Wang, Die; Giangrande, Scott E.; Bartholomew, Mary Jane; ...

2018-02-07

This study summarizes the precipitation properties collected during the GoAmazon2014/5 campaign near Manaus in central Amazonia, Brazil. Precipitation breakdowns, summary radar rainfall relationships and self-consistency concepts from a coupled disdrometer and radar wind profiler measurements are presented. The properties of Amazon cumulus and associated stratiform precipitation are discussed, including segregations according to seasonal (Wet/Dry regime) variability, cloud echo-top height and possible aerosol influences on the apparent oceanic characteristics of the precipitation drop size distributions. Overall, we observe that the Amazon precipitation straddles behaviors found during previous U.S. Department of Energy Atmospheric Radiation Measurements program (ARM) tropical deployments, with distributions favoringmore » higher concentrations of smaller drops than ARM continental examples. Oceanic type precipitation characteristics are predominantly observed during the Amazon Wet seasons. Finally, an exploration of the controls on Wet season precipitation properties reveals that wind direction, as compared with other standard radiosonde thermodynamic parameters or aerosol count/regime classifications performed at the ARM site, provides a good indicator for those Wet season Amazon events having an oceanic character for their precipitation drop size distributions.« less

The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Die; Giangrande, Scott E.; Bartholomew, Mary Jane

This study summarizes the precipitation properties collected during the GoAmazon2014/5 campaign near Manaus in central Amazonia, Brazil. Precipitation breakdowns, summary radar rainfall relationships and self-consistency concepts from a coupled disdrometer and radar wind profiler measurements are presented. The properties of Amazon cumulus and associated stratiform precipitation are discussed, including segregations according to seasonal (Wet/Dry regime) variability, cloud echo-top height and possible aerosol influences on the apparent oceanic characteristics of the precipitation drop size distributions. Overall, we observe that the Amazon precipitation straddles behaviors found during previous U.S. Department of Energy Atmospheric Radiation Measurements program (ARM) tropical deployments, with distributions favoringmore » higher concentrations of smaller drops than ARM continental examples. Oceanic type precipitation characteristics are predominantly observed during the Amazon Wet seasons. Finally, an exploration of the controls on Wet season precipitation properties reveals that wind direction, as compared with other standard radiosonde thermodynamic parameters or aerosol count/regime classifications performed at the ARM site, provides a good indicator for those Wet season Amazon events having an oceanic character for their precipitation drop size distributions.« less

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site. Part I; Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Minnis, Patrick; Xi, Baike

2005-01-01

A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 hours of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant, mixed-phase, low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (r(sub e)) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (tau), effective solar transmission (gamma), and cloud/top-of-atmosphere albedos (R(sub cldy)/R(sub TOA)) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations. In general, more stratus clouds occur during winter and spring than in summer. Cloud-layer altitudes and physical thicknesses were higher and greater in summer than in winter with averaged physical thicknesses of 0.85 km and 0.73 km for day and night, respectively. The seasonal variations of LWP, LWC, N. tau, R(sub cldy), and R(sub TOA) basically follow the same pattern with maxima and minima during winter and summer, respectively. There is no significant variation in mean r(sub e), however, despite a summertime peak in aerosol loading, Although a considerable degree of variability exists, the 6-yr average values of LWP, LWC, r(sub e), N, tau, gamma, R(sub cldy) and R(sub TOA) are 150 gm(exp -2) (138), 0.245 gm(exp -3) (0.268), 8.7 micrometers (8.5), 213 cm(exp -3) (238), 26.8 (24.8), 0.331, 0.672, 0.563 for daytime (nighttime). A new conceptual model of midlatitude continental low clouds at the ARM SGP site has been developed from this study. The low stratus cloud amount monotonically increases from midnight to early morning (0930 LT), and remains large until around local noon, then declines until 1930 LT when it levels off for the remainder of the night. In the morning, the stratus cloud layer is low, warm, and thick with less LWC, while in the afternoon it is high, cold, and thin with more LWC. Future parts of this series will consider other cloud types and cloud radiative forcing at the ARM SCF.

Climatology and Formation of Tropical Midlevel Clouds at the Darwin ARM Site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riihimaki, Laura D.; McFarlane, Sally A.; Comstock, Jennifer M.

A 4-yr climatology of midlevel clouds is presented from vertically pointing cloud lidar and radar measurements at the Atmospheric Radiation Measurement Program (ARM) site at Darwin, Australia. Few studies exist of tropical midlevel clouds using a dataset of this length. Seventy percent of clouds with top heights between 4 and 8 km are less than 2 km thick. These thin layer clouds have a peak in cloud-top temperature around the melting level (0°C) and also a second peak around -12.5°C. The diurnal frequency of thin clouds is highest during the night and reaches a minimum around noon, consistent with variationmore » caused by solar heating. Using a 1.5-yr subset of the observations, the authors found that thin clouds have a high probability of containing supercooled liquid water at low temperatures: ~20% of clouds at -30°C, ~50% of clouds at -20°C, and ~65% of clouds at -10°C contain supercooled liquid water. The authors hypothesize that thin midlevel clouds formed at the melting level are formed differently during active and break monsoon periods and test this over three monsoon seasons. A greater frequency of thin midlevel clouds are likely formed by increased condensation following the latent cooling of melting during active monsoon periods when stratiform precipitation is most frequent. This is supported by the high percentage (65%) of midlevel clouds with preceding stratiform precipitation and the high frequency of stable layers slightly warmer than 0°C. In the break monsoon, a distinct peak in the frequency of stable layers at 0°C matches the peak in thin midlevel cloudiness, consistent with detrainment from convection.« less

Cloud Thickness from Offbeam Returns (THOR) Validation Campaign on NASA's P3B Over the ARM/SGP

NASA Technical Reports Server (NTRS)

Cahalan, R. F.; Kolasinski, J.; McGill, M.; Lau, William K. M. (Technical Monitor)

2002-01-01

Physical thickness of a cloud layer, sometimes multiple cloud layers, is a crucial controller of solar heating of the Earth- atmosphere system, which drives the convective processes that produce storm systems. Yet clouds of average optical thickness are opaque to conventional lidar, so their thickness is well estimated only by combining a lidar above and another below cloud, or a radar and lidar on the same side, dual facilities not widely available. Here we report initial observations of a new airborne multiple field of view lidar, capable of determining physical thickness of cloud layers from time signatures of off-beam returns from a I kHz micropulse lidar at 540 rim. For a single layer, the time delay of light returning from the outer diffuse halo of light surrounding the beam entry point, relative to the time delay at beam center, determines the cloud physical thickness. The delay combined with the pulse stretch gives the optical thickness. This halo method requires cloud optical thickness exceeding 2, and improves with cloud thickness, thus complimenting conventional lidar, which cannot penetrate thick clouds. Results are presented from March 25, 2002, when THOR flew a butterfly pattern over the ARM site at 8.3 km, above a thin ice cloud at 5 km, and a thick boundary-layer stratus deck with top at 1.3 km, as shown by THOR channel 1, and a base at about 0.3 km as shown by the ground-based MPL. Additional information is included in the original extended abstract.

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site. Part II; Cloud Fraction and Surface Radiative Forcing

NASA Technical Reports Server (NTRS)

Xi, B.; Minnis, P.

2006-01-01

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0-3 km), middle (3-6 km), and high clouds (more than 6 km) using ARM SCG ground-based paired lidar-radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of approximately 10 Wm(exp -2). The annual averages of total, and single-layered low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total and low cloud amounts peak during January and February and reach a minimum during July and August, high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 Wm(exp-2), respectively) are less than those under middle and high clouds (188 and 201 Wm(exp -2), respectively), but the downwelling LW fluxes (349 and 356 Wm(exp -2)) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 Wm(exp -2)). Low clouds produce the largest LW warming (55 Wm(exp -2) and SW cooling (-91 Wm(exp -2)) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 Wm(exp -2)) and SW cooling (-37 Wm(exp -2)) effects at the surface. All-sky SW CRF decreases and LW CRF increases with increasing cloud fraction with mean slopes of -0.984 and 0.616 Wm(exp -2)%(exp -1), respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly affected by uncertainties in data sampling and clear-sky screening. Traditionally, cloud radiative forcing includes, not only the radiative impact of the hydrometeors, but also the changes in the environment. Taken together over the ARM SCF, changes in humidity and surface albedo between clear and cloudy conditions offset approximately 20% of the NET radiative forcing caused by the cloud hydrometeors alone. Variations in water vapor, on average, account for 10% and 83% of the SW and LW CRFs, respectively, in total cloud cover conditions. The error analysis further reveals that the cloud hydrometeors dominate the SW CRF, while water vapor changes are most important for LW flux changes in cloudy skies. Similar studies over other locales are encouraged where water and surface albedo changes from clear to cloudy conditions may be much different than observed over the ARM SCF.

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

DOE PAGES

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; ...

2016-06-10

Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty informationmore » on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. As a result, this is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.« less

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

NASA Astrophysics Data System (ADS)

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; Holmes, Aimee; Luke, Edward

2016-06-01

Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty information on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. This is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.

The 3-D Tropical Convective Cloud Spectrum in AMIE Radar Observations and Global Climate Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schumacher, Courtney

2015-08-31

During the three years of this grant performance, the PI and her research group have made a number of significant contributions towards determining properties of tropical deep convective clouds and how models depict and respond to the heating associated with tropical convective systems. The PI has also been an active ARM/ASR science team member, including playing a significant role in AMIE and GoAmazon2014/5. She served on the DOE ASR radar science steering committee and was a joint chair of the Mesoscale Convective Organization group under the Cloud Life Cycle working group. This grant has funded a number of graduate students,more » many of them women, and the PI and her group have presented their DOE-supported work at various universities and national meetings. The PI and her group participated in the AMIE (2011-12) and GoAmazon2014/5 (2014-15) DOE field deployments that occurred in the tropical Indian Ocean and Brazilian Amazon, respectively. AMIE observational results (DePasquale et al. 2014, Feng et al. 2014, Ahmed and Schumacher 2015) focus on the variation and possible importance of Kelvin waves in various phases of the Madden-Julian Oscillation (MJO), on the synergy of the different wavelength radars deployed on Addu Atoll, and on the importance of humidity thresholds in the tropics on stratiform rain production. Much of the PIs GoAmazon2014/5 results to date relate to overviews of the observations made during the field campaign (Martin et al. 2015, 2016; Fuentes et al. 2016), but also include the introduction of the descending arm and its link to ozone transport from the mid-troposphere to the surface (Gerken et al. 2016). Vertical motion and mass flux profiles from GoAmazon (Giangrande et al. 2016) also show interesting patterns between seasons and provide targets for model simulations. Results from TWP-ICE (Schumacher et al. 2015), which took place in Darwin, Australia in 2006 show that vertical velocity retrievals from the profilers provide structure to better quantify the transition between convective, stratiform, and anvil cloud types.« less

Investigation of the relationships between DCS cloud properties, lifecycle, and precipitation with meteorological regimes and aerosol sources at the ARM SGP Site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Xiquan

In this proposed research, we will investigate how different meteorological regimes and aerosol sources affect DCS properties, diurnal and life cycles, and precipitation using multiple observational platforms (surface, satellite, and aircraft) and NARR reanalysis at the ARM SGP site. The Feng et al. (2011, 2012) DCS results will serve as a starting point for this proposed research, and help us to address some fundamental issues of DCSs, such as convective initiation, rain rate, areal extent (including stratiform and convective regions), and longevity. Convective properties will be stratified by meteorological regime (synoptic/mesoscale patterns) identified by reanalysis. Aerosol information obtained from themore » ARM SGP site will also be stratified by meteorological regimes to understand their effects on convection. Finally, the aircraft in-situ measurements and various radar observations and retrievals during the MC3E campaign will provide a “cloud-truth” dataset and are an invaluable data source for verifying the findings and investigating the proposed hypotheses in Objective 1.« less

Ice Cloud Optical Thickness and Extinction Estimates from Radar Measurements.

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Shupe, Matthew D.; Heymsfield, Andrew J.; Zuidema, Paquita

2003-11-01

A remote sensing method is proposed to derive vertical profiles of the visible extinction coefficients in ice clouds from measurements of the radar reflectivity and Doppler velocity taken by a vertically pointing 35-GHz cloud radar. The extinction coefficient and its vertical integral, optical thickness τ, are among the fundamental cloud optical parameters that, to a large extent, determine the radiative impact of clouds. The results obtained with this method could be used as input for different climate and radiation models and for comparisons with parameterizations that relate cloud microphysical parameters and optical properties. An important advantage of the proposed method is its potential applicability to multicloud situations and mixed-phase conditions. In the latter case, it might be able to provide the information on the ice component of mixed-phase clouds if the radar moments are dominated by this component. The uncertainties of radar-based retrievals of cloud visible optical thickness are estimated by comparing retrieval results with optical thicknesses obtained independently from radiometric measurements during the yearlong Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. The radiometric measurements provide a robust way to estimate τ but are applicable only to optically thin ice clouds without intervening liquid layers. The comparisons of cloud optical thicknesses retrieved from radar and from radiometer measurements indicate an uncertainty of about 77% and a bias of about -14% in the radar estimates of τ relative to radiometric retrievals. One possible explanation of the negative bias is an inherently low sensitivity of radar measurements to smaller cloud particles that still contribute noticeably to the cloud extinction. This estimate of the uncertainty is in line with simple theoretical considerations, and the associated retrieval accuracy should be considered good for a nonoptical instrument, such as radar. This paper also presents relations between radar-derived characteristic cloud particle sizes and effective sizes used in models. An average relation among τ, cloud ice water path, and the layer mean value of cloud particle characteristic size is also given. This relation is found to be in good agreement with in situ measurements. Despite a high uncertainty of radar estimates of extinction, this method is useful for many clouds where optical measurements are not available because of cloud multilayering or opaqueness.

Exploiting Cloud Radar Doppler Spectra of Mixed-Phase Clouds during ACCEPT Field Experiment to Identify Microphysical Processes

NASA Astrophysics Data System (ADS)

Kalesse, H.; Myagkov, A.; Seifert, P.; Buehl, J.

2015-12-01

Cloud radar Doppler spectra offer much information about cloud processes. By analyzing millimeter radar Doppler spectra from cloud-top to -base in mixed-phase clouds in which super-cooled liquid-layers are present we try to tell the microphysical evolution story of particles that are present by disentangling the contributions of the solid and liquid particles to the total radar returns. Instead of considering vertical profiles, dynamical effects are taken into account by following the particle population evolution along slanted paths which are caused by horizontal advection of the cloud. The goal is to identify regions in which different microphysical processes such as new particle formation (nucleation), water vapor deposition, aggregation, riming, or sublimation occurr. Cloud radar measurements are supplemented by Doppler lidar and Raman lidar observations as well as observations with MWR, wind profiler, and radio sondes. The presence of super-cooled liquid layers is identified by positive liquid water paths in MWR measurements, the vertical location of liquid layers (in non-raining systems and below lidar extinction) is derived from regions of high-backscatter and low depolarization in Raman lidar observations. In collocated cloud radar measurements, we try to identify cloud phase in the cloud radar Doppler spectrum via location of the Doppler peak(s), the existence of multi-modalities or the spectral skewness. Additionally, within the super-cooled liquid layers, the radar-identified liquid droplets are used as air motion tracer to correct the radar Doppler spectrum for vertical air motion w. These radar-derived estimates of w are validated by independent estimates of w from collocated Doppler lidar measurements. A 35 GHz vertically pointing cloud Doppler radar (METEK MIRA-35) in linear depolarization (LDR) mode is used. Data is from the deployment of the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. There, another MIRA-35 was operated in simultaneous transmission and simultaneous reception (STSR) mode for obtaining measurements of differential reflectivity (ZDR) and correlation coefficient ρhv.

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, S-band Radar (williams-s_band)

DOE Data Explorer

Williams, Christopher

2012-11-06

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica

Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOVmore » ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.« less

Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Zhe; McFarlane, Sally A.; Schumacher, Courtney

2014-05-16

To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective cloudsmore » and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar dataset is produced to provide improved cloud boundary estimates, microphysics and radiative heating retrievals.« less

Variability of and Factors Controlling Precipitation Production in Shallow Cumulus - Results from the ARM Eastern North Atlantic Site

NASA Astrophysics Data System (ADS)

Luke, E. P.; Kollias, P.

2016-12-01

Shallow cumulus clouds are by far the most frequently observed cloud type over the Earth's oceans and frequently produce warm rain. However, quantitative rainfall estimates from these clouds are challenging to acquire from satellites due to their small horizontal scale. Here, two years of observations from the US Department of Energy Atmospheric Radiation Measurement Program (ARM) Eastern North Atlantic (ENA) site located on Graciosa Island in the Azores are used to characterize the frequency, intensity, and fractional coverage of shallow cumulus precipitation. The analyzed dataset is the most comprehensive of its type, considering both its temporal extent and the sophistication of the ground-based observations. The precipitation rate at the base of shallow cumulus is estimated using combined radar-lidar observations and the rain retrievals are compared to the rainfall measurements available at the ground by optical disdrometers. Using synergy between surfaced-based observations of aerosols and thermodynamic soundings, the vertical structure of the Marine Boundary Layer and the temporal variability of the cloud condensation nuclei (CCN) number concentration are determined. The observed variability in shallow cumulus precipitation is examined in relation to the variability of the large-scale environment as captured by the humidity profile, the magnitude of the low-level horizontal winds and aerosol loading.

Electric Field Magnitude and Radar Reflectivity as a Function of Distance from Cloud Edge

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.

2004-01-01

The results of analyses of data collected during a field investigation of thunderstorm anvil and debris clouds are reported. Statistics of the magnitude of the electric field are determined as a function of distance from cloud edge. Statistics of radar reflectivity near cloud edge are also determined. Both analyses use in-situ airborne field mill and cloud physics data coupled with ground-based radar measurements obtained in east-central Florida during the summer convective season. Electric fields outside of anvil and debris clouds averaged less than 3 kV/m. The average radar reflectivity at the cloud edge ranged between 0 and 5 dBZ.

Intercomparison of vertical structure of storms revealed by ground-based (NMQ) and spaceborne radars (CloudSat-CPR and TRMM-PR).

PubMed

Fall, Veronica M; Cao, Qing; Hong, Yang

2013-01-01

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts.

Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ) and Spaceborne Radars (CloudSat-CPR and TRMM-PR)

PubMed Central

Fall, Veronica M.; Hong, Yang

2013-01-01

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts. PMID:24459424

Retrieve Optically Thick Ice Cloud Microphysical Properties by Using Airborne Dual-Wavelength Radar Measurements

NASA Technical Reports Server (NTRS)

Wang, Zhien; Heymsfield, Gerald M.; Li, Lihua; Heymsfield, Andrew J.

2005-01-01

An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.

Calibration of a 35-GHz Airborne Cloud Radar: Lessons Learned and Intercomparison with a 94-GHz Airborne Cloud Radar

NASA Astrophysics Data System (ADS)

Ewald, Florian; Gross, Silke; Hagen, Martin; Hirsch, Lutz; Delanoë, Julien

2017-04-01

Clouds play an important role in the climate system since they have a profound influence on Earth's radiation budget and the water cycle. Uncertainties associated with their spatial characteristics as well as their microphysics still introduce large uncertainties in climate change predictions. In recent years, our understanding of the inner workings of clouds has been greatly advanced by the deployment of cloud profiling microwave radars from ground as well as from space like CloudSat or the upcoming EarthCARE satellite mission. In order to validate and assess the limitations of these spaceborne missions, a well-calibrated, airborne cloud radar with known sensitivity to clouds is indispensable. Within this context, the German research aircraft HALO was equipped with the high-power (30kW peak power) cloud radar operating at 35 GHz and a high spectral resolution lidar (HSRL) system at 532 nm. During a number of flight experiments over Europe and over the tropical and extra-tropical North-Atlantic, several radar calibration efforts have been made using the ocean surface backscatter. Moreover, CloudSat underflights have been conducted to compare the radar reflectivity and measurement sensitivity between the air- and spaceborne instruments. Additionally, the influence of different radar wavelengths was explored with joint flights of HALO and the French Falcon 20 aircraft, which was equipped with the RASTA cloud radar at 94 GHz and a HSRL at 355 nm. In this presentation, we will give an overview of lessons learned from different calibration strategies using the ocean surface backscatter. Additional measurements of signal linearity and signal saturation will complement this characterization. Furthermore, we will focus on the coordinated airborne measurements regarding the different sensitivity for clouds at 35 GHz and 94 GHz. By using the highly sensitive lidar signals, we show if the high-power cloud radar at 35 GHz can be used to validate spaceborne and airborne measurements at 94 GHz and which differences are to be expected. Furthermore, the coordinated measurements are used to explore the reflectivity cut-offs of CloudSat and future spaceborne constellations and compare them to ground-based systems.

Influence of Meteorological Regimes on Cloud Microphysics Over Ross Island, Antarctica

NASA Astrophysics Data System (ADS)

Glennon, C.; Wang, S. H.; Scott, R. C.; Bromwich, D. H.; Lubin, D.

2017-12-01

The Antarctic provides a sharp contrast in cloud microphysics from the high Arctic, due to orographic lifting and resulting strong vertical motions induced by mountain ranges and other varying terrain on several spatial scales. The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) deployed advanced cloud remote sensing equipment to Ross Island, Antarctica, from December 2015 until January 2016. This equipment included scanning and zenith radars operating in the Ka and X bands, a high spectral resolution lidar (HSRL), and a polarized micropulse lidar (MPL). A major AWARE objective is to provide state-of-the-art data for improving cloud microphysical parameterizations in climate models. To further this objective we have organized and classified the local Ross Island meteorology into distinct regimes using k-means clustering on ERA-Interim reanalysis data. We identify synoptic categories producing unique regimes of cloud cover and cloud microphysical properties over Ross Island. Each day of observations can then be associated with a specific meteorological regime, thus assisting modelers with identifying case studies. High-resolution (1 km) weather forecasts from the Antarctic Mesoscale Prediction System (AMPS) are sorted into these categories. AMPS-simulated anomalies of cloud fraction, near-surface air temperature, and vertical velocity at 500-mb are composited and compared with ground-based radar and lidar-derived cloud properties to identify mesoscale meteorological processes driving Antarctic cloud formation. Synoptic lows over the Ross and Amundsen Seas drive anomalously warm conditions at Ross Island by injecting marine air masses inland over the West Antarctic Ice Sheet (WAIS). This results in ice and mixed-phase orographic cloud systems arriving at Ross Island from the south to southeast along the Transantarctic Mountains. In contrast, blocking over the Amundsen Sea region brings classical liquid-dominated mixed-phase and thin liquid water clouds from the Southern Ocean. Low pressure systems over the Bellingshausen Sea produce outflow of cold, dry continental polar air, yielding predominantly tenuous ice cloud at Ross Island.

Synergizing High-Resolution EOS Terra Satellite Data and S-POLKa Radar Reflectivity to Assess Trade Wind Cumuli Precipitation

NASA Astrophysics Data System (ADS)

Snodgrass, E. R.; di Girolamo, L.; Rauber, R.; Zhao, G.

2005-12-01

During the RICO field campaign, the EOS Terra Spacecraft and NCAR's S-POLKa radar collected coincident high-resolution visible and near-IR satellite data and dual-polarized S-band and Ka-band radar reflectivity data to understand trade wind cumuli cloud distribution and precipitation. In this paper, the comparison of the trade wind cloud field's satellite-derived cloud properties and radar-derived precipitation characteristics are presented. Specifically, these results focus on the relationship between radar reflectivity and derived rain rate to the satellite visible radiance, cloud fraction, height and thickness. Also results concerning the relationship between cloud area estimated by satellite and cloud boundary estimated by radar Bragg and Rayleigh scattering will be presented. The resolution effects between visible satellite data from the ASTER instrument at 15m ground-resolution and the S-POLKa radar data will be reviewed. The potential applications of these results to the estimation of trade wind cumuli's role in returning water to the ocean through precipitation, and to cloud and climate model parameterization will be discussed.

Radar Evaluation of Optical Cloud Constraints to Space Launch Operations

NASA Technical Reports Server (NTRS)

Merceret, Francis J.; Short, David A.; Ward, Jennifer G.

2005-01-01

Weather constraints to launching space vehicles are designed to prevent loss of the vehicle or mission due to weather hazards (See, e.g., Ref 1). Constraints include Lightning Launch Commit Criteria (LLCC) designed to avoid natural and triggered lightning. The LLCC currently in use at most American launch sites including the Eastern Range and Kennedy Space Center require the Launch Weather Officer to determine the height of cloud bases and tops, the location of cloud edges, and cloud transparency. The preferred method of making these determinations is visual observation, but when that isn't possible due to darkness or obscured vision, it is permissible to use radar. This note examines the relationship between visual and radar observations in three ways: A theoretical consideration of the relationship between radar reflectivity and optical transparency. An observational study relating radar reflectivity to cloud edge determined from in-situ measurements of cloud particle concentrations that determine the visible cloud edge. An observational study relating standard radar products to anvil cloud transparency. It is shown that these three approaches yield results consistent with each other and with the radar threshold specified in Reference 2 for LLCC evaluation.

A Comparison of MERRA and NARR Reanalysis Datasets with the DOE ARM SGP Continuous Forcing data

NASA Technical Reports Server (NTRS)

Kennedy, Aaron D.; Dong, Xiquan; Xi, Baike; Xie, Shaocheng; Zhang, Yunyan; Chen, Junye

2010-01-01

In this study, the atmospheric state, precipitation, cloud fraction, and radiative fluxes from Modern Era Retrospective-analysis for Research and Applications (MERRA) and North American Regional Reanalysis (NARR) are collected and compared with the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) continuous forcing during the period 1999-2001. For the atmospheric state, the three datasets have excellent agreement for the horizontal wind components and air temperature. NARR and ARM have generally good agreement for humidity, except for several biases in the PBL and in the upper troposphere. MERRA, on the other hand, suffers from a year-round negative bias in humidity except for the month of June. For the vertical pressure velocity, significant differences exist 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. Both NARR and MERRA capture the seasonal variation of CF observed by ARM radar-lidar and GOES with high correlations (0.92-0.78), but having negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows a better agreement for both SW and 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- 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 time period, and more comparisons at different locations and longer time period are needed.

Report on the Radar/PIREP Cloud Top Discrepancy Study

NASA Technical Reports Server (NTRS)

Wheeler, Mark M.

1997-01-01

This report documents the results of the Applied Meteorology Unit's (AMU) investigation of inconsistencies between pilot reported cloud top heights and weather radar indicated echo top heights (assumed to be cloud tops) as identified by the 45 Weather Squadron (45WS). The objective for this study is to document and understand the differences in echo top characteristics as displayed on both the WSR-88D and WSR-74C radars and cloud top heights reported by the contract weather aircraft in support of space launch operations at Cape Canaveral Air Station (CCAS), Florida. These inconsistencies are of operational concern since various Launch Commit Criteria (LCC) and Flight Rules (FR) in part describe safe and unsafe conditions as a function of cloud thickness. Some background radar information was presented. Scan strategies for the WSR-74C and WSR-88D were reviewed along with a description of normal radar beam propagation influenced by the Effective Earth Radius Model. Atmospheric conditions prior to and leading up to both launch operations were detailed. Through the analysis of rawinsonde and radar data, atmospheric refraction or bending of the radar beam was identified as the cause of the discrepancies between reported cloud top heights by the contract weather aircraft and those as identified by both radars. The atmospheric refraction caused the radar beam to be further bent toward the Earth than normal. This radar beam bending causes the radar target to be displayed erroneously, with higher cloud top heights and a very blocky or skewed appearance.

Indirect and Semi-Direct Aerosol Campaign: The Impact of Arctic Aerosols on Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

McFarquhar, Greg; Ghan, Steven J.; Verlinde, J.

2011-02-01

A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the arctic boundary layer in the vicinity of Barrow, Alaska was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) sponsored by the Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric Science Programs. The primary aim of ISDAC was to examine indirect effects of aerosols on clouds that contain both liquid and ice water. The experiment utilized the ARM permanent observational facilities at the North Slope of Alaska (NSA) in Barrow. These include a cloud radar, a polarized micropulse lidar, and an atmosphericmore » emitted radiance interferometer as well as instruments specially deployed for ISDAC measuring aerosol, ice fog, precipitation and spectral shortwave radiation. The National Research Council of Canada Convair-580 flew 27 sorties during ISDAC, collecting data using an unprecedented 42 cloud and aerosol instruments for more than 100 hours on 12 different days. Data were obtained above, below and within single-layer stratus on 8 April and 26 April 2008. These data enable a process-oriented understanding of how aerosols affect the microphysical and radiative properties of arctic clouds influenced by different surface conditions. Observations acquired on a heavily polluted day, 19 April 2008, are enhancing this understanding. Data acquired in cirrus on transit flights between Fairbanks and Barrow are improving our understanding of the performance of cloud probes in ice. Ultimately the ISDAC data will be used to improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and to determine the extent to which long-term surface-based measurements can provide retrievals of aerosols, clouds, precipitation and radiative heating in the Arctic.« less

Characterization of snowfall properties at high-latitude sites through use of a combined Multi-Angle Snow Camera (MASC) and radar approach

NASA Astrophysics Data System (ADS)

Cooper, S.; Wood, N.; Garrett, T. J.; L'Ecuyer, T. S.; Pettersen, C.

2016-12-01

Estimates of snowfall rate derived from radar reflectivities alone are non-unique, as different combinations of snowfall rates and snowflake microphysical properties can conspire to produce nearly identical radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100-200% for individual events. Here, we use observations of snowflake particle size distribution, fallspeed, and habit from the Multi-Angle Snow Camera (MASC) to constrain estimates of snowfall derived from radar reflectivities. MASC measurements of microphysical properties and uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Initial results focus on the MASC and Ka-band Zenith Radar (KaZR) measurements at the ARM NSA Barrow Climate Facility site. Use of MASC fallspeed, MASC PSD, and a CloudSat particle model as base assumptions resulted in retrieved total accumulations with a -17% difference relative to nearby National Weather Service observations averaged over five snow events. Use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -63% to + 86% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fallspeed and habit, suggesting that MASC measurements may provide a path forward in reducing the non-uniqueness of the snowfall retrieval problem. Preliminary results also will be presented for the deployment of the MASC, MicroRain Radar (MRR), and Precipitation Imaging Package (PIP) to Haukeliseter, Norway during winter season 2016-17. These instruments will then be deployed to northern Sweden for winter 2017-18. It is hoped more accurate knowledge of snowfall properties dependent upon location and meteorological conditions will be useful for both weather and climate applications.

AERI Observations of Antarctic Clouds Properties During AWARE

NASA Astrophysics Data System (ADS)

Gero, P. J.; Rowe, P. M.; Walden, V. P.

2017-12-01

The ARM West Antarctic Radiation Experiment (AWARE) was a recent field campaign by the US Dept. of Energy's Atmospheric Radiation Measurement (ARM) program, in collaboration with the National Science Foundation, to measure the state of the atmosphere, the surface energy balance, and cloud properties in Antarctica. The main observing facility for AWARE, located near McMurdo Station, consisted of a wide variety of instrumentation, including an eddy-covariance system, surface aerosol measurements, cloud radar and lidar, broadband radiometers, microwave radiometer, and an infrared spectroradiometer (AERI). Collectively these measurements can be used to improve our understanding of the connections between the atmospheric state, cloud processes, and their effects on the surface energy budget. Thus, AWARE data have the potential to revolutionize our understanding of how the atmosphere and clouds impact the surface energy budget in this important region. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based instrument developed at the University of Wisconsin-Madison that measures downwelling thermal infrared radiance from the atmosphere. Observations are made in the 400-3020 cm-1 (3.3-19 μm) spectral range with a resolution of 1 cm-1, with an accuracy better than 1% of ambient radiance. These observations can be used to obtain vertical profiles of tropospheric temperature and water vapor in the lower troposphere, as well as measurements of the concentration of various trace gases and microphysical and optical properties of clouds. We present some preliminary results from the AERI dataset from AWARE, including analysis of the downwelling radiation and cloud structure over the annual cycle.

Parameterization and analysis of 3-D radiative transfer in clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varnai, Tamas

2012-03-16

This report provides a summary of major accomplishments from the project. The project examines the impact of radiative interactions between neighboring atmospheric columns, for example clouds scattering extra sunlight toward nearby clear areas. While most current cloud models don't consider these interactions and instead treat sunlight in each atmospheric column separately, the resulting uncertainties have remained unknown. This project has provided the first estimates on the way average solar heating is affected by interactions between nearby columns. These estimates have been obtained by combining several years of cloud observations at three DOE Atmospheric Radiation Measurement (ARM) Climate Research Facility sitesmore » (in Alaska, Oklahoma, and Papua New Guinea) with simulations of solar radiation around the observed clouds. The importance of radiative interactions between atmospheric columns was evaluated by contrasting simulations that included the interactions with those that did not. This study provides lower-bound estimates for radiative interactions: It cannot consider interactions in cross-wind direction, because it uses two-dimensional vertical cross-sections through clouds that were observed by instruments looking straight up as clouds drifted aloft. Data from new DOE scanning radars will allow future radiative studies to consider the full three-dimensional nature of radiative processes. The results reveal that two-dimensional radiative interactions increase overall day-and-night average solar heating by about 0.3, 1.2, and 4.1 Watts per meter square at the three sites, respectively. This increase grows further if one considers that most large-domain cloud simulations have resolutions that cannot specify small-scale cloud variability. For example, the increases in solar heating mentioned above roughly double for a fairly typical model resolution of 1 km. The study also examined the factors that shape radiative interactions between atmospheric columns and found that local effects were often much larger than the overall values mentioned above, and were especially large for high sun and near convective clouds such as cumulus. The study also found that statistical methods such as neural networks appear promising for enabling cloud models to consider radiative interactions between nearby atmospheric columns. Finally, through collaboration with German scientists, the project found that new methods (especially one called stepwise kriging) show great promise in filling gaps between cloud radar scans. If applied to data from the new DOE scanning cloud radars, these methods can yield large, continuous three-dimensional cloud structures for future radiative simulations.« less

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

2015-01-01

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Synergistic Measurement of Ice Cloud Microphysics using C- and Ka-Band Radars

NASA Astrophysics Data System (ADS)

Ewald, F.; Gross, S.; Hagen, M.; Li, Q.; Zinner, T.

2017-12-01

Ice clouds play an essential role in the climate system since they have a large effect on the Earth's radiation budget. Uncertainties associated with their spatial and temporal distribution as well as their optical and microphysical properties still account for large uncertainties in climate change predictions. Substantial improvement of our understanding of ice clouds was achieved with the advent of cloud radars into the field of ice cloud remote sensing. Here, highly variable ice crystal size distributions are one of the key issues remaining to be resolved. With radar reflectivity scaling with the sixth moment of the particle size, the assumed ice crystal size distribution has a large impact on the results of microphysical retrievals. Different ice crystal sizes distributions can, however, be distinguished, when cloud radars of different wavelength are used simultaneously.For this study, synchronous RHI scans were performed for a common measurement range of about 30 km between two radar instruments using different wavelengths: the dual-polarization C-band radar POLDIRAD operated at DLR and the Mira-36 Ka-band cloud radar operated at the University of Munich. For a measurement period over several months, the overlapping region for ice clouds turned out to be quite large. This gives evidence on the presence of moderate-sized ice crystals for which the backscatter is sufficient high to be visible in the C-band as well. In the range between -10 to +10 dBz, reflectivity measurements from both radars agreed quite well indicating the absence of large ice crystals. For reflectivities above +10 dBz, we observed differences with smaller values at the Ka-band due to Mie scattering effects at larger ice crystals.In this presentation, we will show how this differential reflectivity can be used to gain insight into ice cloud microphysics on the basis of electromagnetic scattering calculations. We will further explore ice cloud microphysics using the full polarization agility of the C-band radar and compare the results to simultaneous linear depolarization measurements with the Ka-band radar. In summary, we will explore if the scientific understanding of ice cloud microphysics can be advanced by the combination of C- and Ka-band radars.

Skill of ship-following large-eddy simulations in reproducing MAGIC observations across the northeast Pacific stratocumulus to cumulus transition region

DOE PAGES

McGibbon, J.; Bretherton, C. S.

2017-03-17

During the Marine ARM GPCI Investigation of Clouds (MAGIC) in October 2011 to September 2012, a container ship making periodic cruises between Los Angeles, CA, and Honolulu, HI, was instrumented with surface meteorological, aerosol and radiation instruments, a cloud radar and ceilometer, and radiosondes. Here large-eddy simulation (LES) is performed in a ship-following frame of reference for 13 four day transects from the MAGIC field campaign. The goal is to assess if LES can skillfully simulate the broad range of observed cloud characteristics and boundary layer structure across the subtropical stratocumulus to cumulus transition region sampled during different seasons andmore » meteorological conditions. Results from Leg 15A, which sampled a particularly well-defined stratocumulus to cumulus transition, demonstrate the approach. The LES reproduces the observed timing of decoupling and transition from stratocumulus to cumulus and matches the observed evolution of boundary layer structure, cloud fraction, liquid water path, and precipitation statistics remarkably well. Considering the simulations of all 13 cruises, the LES skillfully simulates the mean diurnal variation of key measured quantities, including liquid water path (LWP), cloud fraction, measures of decoupling, and cloud radar-derived precipitation. The daily mean quantities are well represented, and daily mean LWP and cloud fraction show the expected correlation with estimated inversion strength. There is a –0.6 K low bias in LES near-surface air temperature that results in a high bias of 5.6 W m –2 in sensible heat flux (SHF). Altogether, these results build confidence in the ability of LES to represent the northeast Pacific stratocumulus to trade cumulus transition region.« less

Preliminary Analysis of X-Band and Ka-Band Radar for Use in the Detection of Icing Conditions Aloft

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Koenig, George G.

2004-01-01

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. Radar has been identified as a strong tool for this work. However, since the remote detection of icing conditions with the intent to identify areas of icing hazard is a new and evolving capability, there are no set requirements for radar sensitivity. This work is an initial attempt to quantify, through analysis, the sensitivity requirements for an icing remote sensing radar. The primary radar of interest for cloud measurements is Ka-band, however, since NASA is currently using an X-band unit, this frequency is also examined. Several aspects of radar signal analysis were examined. Cloud reflectivity was calculated for several forms of cloud using two different techniques. The Air Force Geophysical Laboratory (AFGL) cloud models, with different drop spectra represented by a modified gamma distribution, were utilized to examine several categories of cloud formation. Also a fundamental methods approach was used to allow manipulation of the cloud droplet size spectra. And an analytical icing radar simulator was developed to examine the complete radar system response to a configurable multi-layer cloud environment. Also discussed is the NASA vertical pointing X-band radar. The radar and its data system are described, and several summer weather events are reviewed.

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tao, Wei-Kuo; Houze, Robert, A., Jr.; Zeng, Xiping

This three-year project, in cooperation with Professor Bob Houze at University of Washington, has been successfully finished as planned. Both ARM (the Atmospheric Radiation Measurement Program) data and cloud-resolving model (CRM) simulations were used to identify the water budgets of clouds observed in two international field campaigns. The research results achieved shed light on several key processes of clouds in climate change (or general circulation models), which are summarized below. 1. Revealed the effect of mineral dust on mesoscale convective systems (MCSs) Two international field campaigns near a desert and a tropical coast provided unique data to drive and evaluatemore » CRM simulations, which are TWP-ICE (the Tropical Warm Pool International Cloud Experiment) and AMMA (the African Monsoon Multidisciplinary Analysis). Studies of the two campaign data were contrasted, revealing that much mineral dust can bring about large MCSs via ice nucleation and clouds. This result was reported as a PI presentation in the 3rd ASR Science Team meeting held in Arlington, Virginia in March 2012. A paper on the studies was published in the Journal of the Atmospheric Sciences (Zeng et al. 2013). 2. Identified the effect of convective downdrafts on ice crystal concentration Using the large-scale forcing data from TWP-ICE, ARM-SGP (the Southern Great Plains) and other field campaigns, Goddard CRM simulations were carried out in comparison with radar and satellite observations. The comparison between model and observations revealed that convective downdrafts could increase ice crystal concentration by up to three or four orders, which is a key to quantitatively represent the indirect effects of ice nuclei, a kind of aerosol, on clouds and radiation in the Tropics. This result was published in the Journal of the Atmospheric Sciences (Zeng et al. 2011) and summarized in the DOE/ASR Research Highlights Summaries (see http://www.arm.gov/science/highlights/RMjY5/view). 3. Used radar observations to evaluate model simulations In cooperation with Profs. Bob Houze at University of Washington and Steven Rutledge at Colorado State University, numerical model results were evaluated with observations from W- and C-band radars and CloudSat/TRMM satellites. These studies exhibited some shortcomings of current numerical models, such as too little of thin anvil clouds, directing the future improvement of cloud microphysics parameterization in CRMs. Two papers of Powell et al (2012) and Zeng et al. (2013), summarizing these studies, were published in the Journal of the Atmospheric Sciences. 4. Analyzed the water budgets of MCSs Using ARM data from TWP-ICE, ARM-SGP and other field campaigns, the Goddard CRM simulations were carried out to analyze the water budgets of clouds from TWP-ICE and AMMA. The simulations generated a set of datasets on clouds and radiation, which are available http://cloud.gsfc.nasa.gov/. The cloud datasets were available for modelers and other researchers aiming to improve the representation of cloud processes in multi-scale modeling frameworks, GCMs and climate models. Special datasets, such as 3D cloud distributions every six minutes for TWP-ICE, were requested and generated for ARM/ASR investigators. Data server records show that 86,206 datasets were downloaded by 120 users between April of 2010 and January of 2012. 5. MMF simulations The Goddard MMF (multi-scale modeling framework) has been improved by coupling with the Goddard Land Information System (LIS) and the Goddard Earth Observing System Model, Version 5 (GOES5). It has also been optimized on NASA HEC supercomputers and can be run over 4000 CPUs. The improved MMF with high horizontal resolution (1 x 1 degree) is currently being applied to cases covering 2005 and 2006. The results show that the spatial distribution pattern of precipitation rate is well simulated by the MMF through comparisons with satellite retrievals from the CMOPRH and GPCP data sets. In addition, the MMF results were compared with three reanalyses (MERRA, ERA-Interim and CFSR). Although the MMF tends to produce a higher precipitation rate over some topical regions, it actually well captures the variations in the zonal and meridional means. Among the three reanalyses, ERA-Interim seems to have values close to those of the satellite retrievals especially for GPCP. It is interesting to note that the MMF obtained the best results in the rain forest of Africa even better than those of CFSR and ERA-Interim, when compared to CMORPH. MERRA fails to capture the precipitation in this region. We are now collaborating with Steve Rutledge (CSU) to validate the model results for AMMA 6. MC3E and the diurnal variation of precipitation processes The Midlatitude Continental Convective Clouds Experiment (MC3E) was a joint field campaign between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the NASA Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. It took place in central Oklahoma during the period April 22 _ June 6, 2011. Some of its major objectives involve the use of CRMs in precipitation science such as: (1) testing the fidelity of CRM simulations via intensive statistical comparisons between simulated and observed cloud properties and latent heating fields for a variety of case types, (2) establishing the limits of CRM space-time integration capabilities for quantitative precipitation estimates, and (3) supporting the development and refinement of physically-based GMI, DPR, and DPR-GMI combined retrieval algorithms using ground-based GPM GV Ku-Ka band radar and CRM simulations. The NASA unified WRF model (nu-WRF) was used for real time forecasts during the field campaign, and ten precipitation events were selected for post mission simulations. These events include well-organized squall lines, scattered storms and quasi-linear storms. A paper focused on the diurnal variation of precipitation will be submitted in September 2012. The major highlights are as follows: a. The results indicate that NU-WRF model could capture observed diurnal variation of rainfall (composite not individual); b. NU-WRF model could simulate two different types (propagating and local type) of the diurnal variation of rainfall; c. NU-WRF model simulation show very good agreement with observation in terms of precipitation pattern (linear MCS), radar reflectivity (a second low peak shallow convection); d. NU-WRF model simulation indicates that the cool-pool dynamic is the main physical process for MCS propagation speed; e. Surface heat fluxes (including land surface model and initial surface condition) do not play a major role in phase of diurnal variation (change rainfall amount slightly); f. Terrain effect is important for initial stage of MCS (rainfall is increased and close to observation by increasing the terrain height that is also close to observed); g. Diurnal variation of radiation is not important for the simulated variation of rainfall. Publications: Zeng, X., W.-K. Tao, S. Powell, R. Houze, Jr., P. Ciesielski, N. Guy, H. Pierce and T. Matsui, 2012: A comparison of the water budgets between clouds from AMMA and TWP-ICE. J. Atmos. Sci., 70, 487-503. Powell, S. W., R. A. Houze, Jr., A. Kumar, and S. A. McFarlane, 2012: Comparison of simulated and observed continental tropical anvil clouds and their radiative heating profiles. J. Atmos. Sci., 69, 2662-2681. Zeng, X., W.-K. Tao, T. Matsui, S. Xie, S. Lang, M. Zhang, D. Starr, and X. Li, 2011: Estimating the Ice Crystal Enhancement Factor in the Tropics. J. Atmos. Sci., 68, 1424-1434. Conferences: Zeng, X., W.-K. Tao, S. Powell, R. Houze, Jr., P. Ciesielski, N. Guy, H. Pierce and T. Matsui, 2012: Comparison of water budget between AMMA and TWP-ICE clouds. The 3rd Annual ASR Science Team Meeting. Arlington, Virginia, Mar. 12-16, 2012. Zeng, X., W.-K. Tao, S. Powell, R. A. Houze Jr., and P. Ciesielski, 2011: Comparing the water budgets between AMMA and TWP-ICE clouds. Fall 2011 ASR Working Group Meeting. Annapolis, September 12-16, 2011. Zeng, X. et al., 2011: Introducing ice nuclei into turbulence parameterizations in CRMs. Fall 2011 ASR Working Group Meeting. Annapolis, September 12-16, 2011.« less

A Wing Pod-based Millimeter Wave Cloud Radar on HIAPER

NASA Astrophysics Data System (ADS)

Vivekanandan, Jothiram; Tsai, Peisang; Ellis, Scott; Loew, Eric; Lee, Wen-Chau; Emmett, Joanthan

2014-05-01

One of the attractive features of a millimeter wave radar system is its ability to detect micron-sized particles that constitute clouds with lower than 0.1 g m-3 liquid or ice water content. Scanning or vertically-pointing ground-based millimeter wavelength radars are used to study stratocumulus (Vali et al. 1998; Kollias and Albrecht 2000) and fair-weather cumulus (Kollias et al. 2001). Airborne millimeter wavelength radars have been used for atmospheric remote sensing since the early 1990s (Pazmany et al. 1995). Airborne millimeter wavelength radar systems, such as the University of Wyoming King Air Cloud Radar (WCR) and the NASA ER-2 Cloud Radar System (CRS), have added mobility to observe clouds in remote regions and over oceans. Scientific requirements of millimeter wavelength radar are mainly driven by climate and cloud initiation studies. Survey results from the cloud radar user community indicated a common preference for a narrow beam W-band radar with polarimetric and Doppler capabilities for airborne remote sensing of clouds. For detecting small amounts of liquid and ice, it is desired to have -30 dBZ sensitivity at a 10 km range. Additional desired capabilities included a second wavelength and/or dual-Doppler winds. Modern radar technology offers various options (e.g., dual-polarization and dual-wavelength). Even though a basic fixed beam Doppler radar system with a sensitivity of -30 dBZ at 10 km is capable of satisfying cloud detection requirements, the above-mentioned additional options, namely dual-wavelength, and dual-polarization, significantly extend the measurement capabilities to further reduce any uncertainty in radar-based retrievals of cloud properties. This paper describes a novel, airborne pod-based millimeter wave radar, preliminary radar measurements and corresponding derived scientific products. Since some of the primary engineering requirements of this millimeter wave radar are that it should be deployable on an airborne platform, occupy minimum cabin space and maximize scan coverage, a pod-based configuration was adopted. Currently, the radar system is capable of collecting observations between zenith and nadir in a fixed scanning mode. Measurements are corrected for aircraft attitude changes. The near-nadir and zenith pointing observations minimize the cross-track Doppler contamination in the radial velocity measurements. An extensive engineering monitoring mechanism is built into the recording system status such as temperature, pressure, various electronic components' status and receiver characteristics. Status parameters are used for real-time system stability estimates and correcting radar system parameters. The pod based radar system is mounted on a modified Gulfstream V aircraft, which is operated and maintained by the National Center for Atmospheric Research (NCAR) on behalf of the National Science Foundation (NSF). The aircraft is called the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) (Laursen et al., 2006). It is also instrumented with high spectral resolution lidar (HSRL) and an array of in situ and remote sensors for atmospheric research. As part of the instrument suite for HIAPER, the NSF funded the development of the HIAPER Cloud Radar (HCR). The HCR is an airborne, millimeter-wavelength, dual-polarization, Doppler radar that serves the atmospheric science community by providing cloud remote sensing capabilities for the NSF/NCAR G-V (HIAPER) aircraft. An optimal radar configuration that is capable of maximizing the accuracy of both qualitative and quantitative estimated cloud microphysical and dynamical properties is the most attractive option to the research community. The Technical specifications of cloud radar are optimized for realizing the desired scientific performance for the pod-based configuration. The radar was both ground and flight tested and preliminary measurements of Doppler and polarization measurements were collected. HCR observed sensitivity as low as -37 dBZ at 1 km range and resolved linear depolarization ratio (LDR) signature better than -29 dB during its latest test flights. References: Kollias, P., and B. A. Albrecht, 2000: The turbulence structure in a continental stratocumulus cloud from millimeter wavelength radar observation. J. Atmos. Sci., 57, 2417-2434. Kollias, P., B.A. Albrecht, R. Lhermitte, and A. Savtchenko, 2001: Radar observations of updrafts, downdrafts, and turbulence in fair weather cumuli. J. Atmos. Sci. 58, 1750-1766. Laursen, K. K., D. P. Jorgensen, G. P. Brasseur, S. L. Ustin, and J. Hunning, 2006: HIAPER: The next generation NSF/NCAR research aircraft. Bulletin of the American Meteorological Society, 87, 896-909. Pazmany, A. L., R. E. McIntosh, R. Kelly, and V. G., 1994: An airborne 95-GHz dual-polarized radar for cloud studies. IEEE Trans. Geosci. Remote Sens., 32, 731-739. Vali, G., Kelly, R.D., French, J., Haimov, S., Leon, D., McIntosh, R., Pazmany, A., 1998. Fine-scale structure and microphysics of coastal stratus. J. Atmos. Sci. 55, 3540-3564.

Skill of ship-following large-eddy simulations in reproducing MAGIC observations across the northeast Pacific stratocumulus to cumulus transition region

NASA Astrophysics Data System (ADS)

McGibbon, J.; Bretherton, C. S.

2017-06-01

During the Marine ARM GPCI Investigation of Clouds (MAGIC) in October 2011 to September 2012, a container ship making periodic cruises between Los Angeles, CA, and Honolulu, HI, was instrumented with surface meteorological, aerosol and radiation instruments, a cloud radar and ceilometer, and radiosondes. Here large-eddy simulation (LES) is performed in a ship-following frame of reference for 13 four day transects from the MAGIC field campaign. The goal is to assess if LES can skillfully simulate the broad range of observed cloud characteristics and boundary layer structure across the subtropical stratocumulus to cumulus transition region sampled during different seasons and meteorological conditions. Results from Leg 15A, which sampled a particularly well-defined stratocumulus to cumulus transition, demonstrate the approach. The LES reproduces the observed timing of decoupling and transition from stratocumulus to cumulus and matches the observed evolution of boundary layer structure, cloud fraction, liquid water path, and precipitation statistics remarkably well. Considering the simulations of all 13 cruises, the LES skillfully simulates the mean diurnal variation of key measured quantities, including liquid water path (LWP), cloud fraction, measures of decoupling, and cloud radar-derived precipitation. The daily mean quantities are well represented, and daily mean LWP and cloud fraction show the expected correlation with estimated inversion strength. There is a -0.6 K low bias in LES near-surface air temperature that results in a high bias of 5.6 W m-2 in sensible heat flux (SHF). Overall, these results build confidence in the ability of LES to represent the northeast Pacific stratocumulus to trade cumulus transition region.