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Title: High Spectral Resolution Lidar Data

The HSRL provided calibrated vertical profiles of optical depth, backscatter cross section and depoloarization at a wavelength of 532 nm. Profiles were acquired at 2.5 second intervals with 7.5 meter resolution. Profiles extended from an altitude of 100 m to 30 km in clear air. The lidar penetrated to a maximum optical depth of ~ 4 under cloudy conditions. Our data contributed directly to the aims of the M-PACE experiment, providing calibrated optical depth and optical backscatter measurements which were not available from any other instrument.
Authors:
Publication Date:
DOE Contract Number:
DE-AC05-00OR22725
Product Type:
Dataset
Research Org(s):
Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US)
Collaborations:
PNL, BNL,ANL,ORNL
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Subject:
54 Environmental Sciences; HSRL, NSA
OSTI Identifier:
1254822
  1. ARM focuses on obtaining continuous measurements—supplemented by field campaigns—and providing data products that promote the advancement of climate models. ARM data include routine data products, value-added products (VAPs), field campaign data, complementary external data products from collaborating programs, and data contributed by ARM principal investigators for use by the scientific community. Data quality reports, graphical displays of data availability/quality, and data plots are also available from the ARM Data Center. Serving users worldwide, the ARM Data Center collects and archives approximately 20 terabytes of data per month. Datastreams are generally available for download within 48 hours.
No associated Collections found.
  1. These multi-wavelength lidar data were collected during the Combined HSRL and Raman lidar Measurement Study (CHARMS) IOP that occurred during July through September 2015 at SGP. During CHARMS the University of Wisconsin HSRL was located at SGP and acquired aerosol backscatter profiles at 532 nmmore » and 1064 nm and aerosol backscatter, extinction, and depolarization profiles at 532 nm. The HSRL aerosol profiles, when combined with the aerosol backscatter and extinction profiles (355 nm) collected by the SGP Raman lidar, provide a suite of three aerosol backscatter (355, 532, 1064 nm) and two aerosol extinction (355, 532 nm) profiles for use in advanced aerosol microphysical retrievals. The data files in this PI product contain this suite of aerosol backscatter (355, 532, 1064), extinction (355, 532 nm), and depolarization (532 nm) profiles. « less
  2. This Modeling Archive is in support of an NGEE Arctic discussion paper and available at http://www.the-cryosphere-discuss.net/tc-2016-29/. Vast carbon stocks stored in permafrost soils of Arctic tundra are under risk of release to atmosphere under warming climate. Ice--wedge polygons in the low-gradient polygonal tundra create amore » complex mosaic of microtopographic features. The microtopography plays a critical role in regulating the fine scale variability in thermal and hydrological regimes in the polygonal tundra landscape underlain by continuous permafrost. Modeling of thermal regimes of this sensitive ecosystem is essential for understanding the landscape behaviour under current as well as changing climate. We present here an end-to-end effort for high resolution numerical modeling of thermal hydrology at real-world field sites, utilizing the best available data to characterize and parameterize the models. We develop approaches to model the thermal hydrology of polygonal tundra and apply them at four study sites at Barrow, Alaska spanning across low to transitional to high-centered polygon and representative of broad polygonal tundra landscape. A multi--phase subsurface thermal hydrology model (PFLOTRAN) was developed and applied to study the thermal regimes at four sites. Using high resolution LiDAR DEM, microtopographic features of the landscape were characterized and represented in the high resolution model mesh. Best available soil data from field observations and literature was utilized to represent the complex heterogeneous subsurface in the numerical model. This data collection provides the complete set of input files, forcing data sets and computational meshes for simulations using PFLOTRAN for four sites at Barrow Environmental Observatory. It also document the complete computational workflow for this modeling study to allow verification, reproducibility and follow up studies. Vast carbon stocks stored in permafrost soils of Arctic tundra are under risk of release to atmosphere under warming climate. Ice--wedge polygons in the low-gradient polygonal tundra create a complex mosaic of microtopographic features. The microtopography plays a critical role in regulating the fine scale variability in thermal and hydrological regimes in the polygonal tundra landscape underlain by continuous permafrost. Modeling of thermal regimes of this sensitive ecosystem is essential for understanding the landscape behaviour under current as well as changing climate. We present here an end-to-end effort for high resolution numerical modeling of thermal hydrology at real-world field sites, utilizing the best available data to characterize and parameterize the models. We develop approaches to model the thermal hydrology of polygonal tundra and apply them at four study sites at Barrow, Alaska spanning across low to transitional to high-centered polygon and representative of broad polygonal tundra landscape. A multi--phase subsurface thermal hydrology model (PFLOTRAN) was developed and applied to study the thermal regimes at four sites. Using high resolution LiDAR DEM, microtopographic features of the landscape were characterized and represented in the high resolution model mesh. Best available soil data from field observations and literature was utilized to represent the complex hetogeneous subsurface in the numerical model. This data collection provides the complete set of input files, forcing data sets and computational meshes for simulations using PFLOTRAN for four sites at Barrow Environmental Observatory. It also document the complete computational workflow for this modeling study to allow verification, reproducibility and follow up studies. « less
  3. Planetary Boundary Layer (PBL) heights have been computed using potential temperature profiles derived from Raman lidar and AERI measurements. Raman lidar measurements of the rotational Raman scattering from nitrogen and oxygen are used to derive vertical profiles of potential temperature. AERI measurements of downwelling radiancemore » are used in a physical retrieval approach (Smith et al. 1999, Feltz et al. 1998) to derive profiles of temperature and water vapor. The Raman lidar and AERI potential temperature profiles are merged to create a single potential temperature profile for computing PBL heights. PBL heights were derived from these merged potential temperature profiles using a modified Heffter (1980) technique that was tailored to the SGP site (Della Monache et al., 2004). PBL heights were computed on an hourly basis for the period January 1, 2009 through December 31, 2011. These heights are provided as meters above ground level. « less
  4. This dataset represent a map of the high center (HC) and low center (LC) polygon boundaries delineated from high resolution LiDAR data for the arctic coastal plain at Barrow, Alaska. The polygon troughs are considered as the surface expression of the ice-wedges. The troughs aremore » in lower elevations than the interior polygon. The trough widths were initially identified from LiDAR data, and the boundary between two polygons assumed to be located along the lowest elevations on trough widths between them. « less
  5. 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.more » 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. « less