GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Supporting Advancement in Weather and Water Prediction in the Upper Colorado River Basin: The SPLASH Campaign
    American Meteorological Society ; 2023
    In:  Bulletin of the American Meteorological Society ( 2023-08-09)
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, ( 2023-08-09)
    Abstract: Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River Watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a two-year deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-22-0147.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2023
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19
    American Meteorological Society ; 2021
    In:  Bulletin of the American Meteorological Society Vol. 102, No. 2 ( 2021-02), p. E421-E445
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 102, No. 2 ( 2021-02), p. E421-E445
    Abstract: The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-19-0346.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Development of a Random-Forest Cloud-Regime Classification Model Based on Surface Radiation and Cloud Products
    American Meteorological Society ; 2021
    In:  Journal of Applied Meteorology and Climatology Vol. 60, No. 4 ( 2021-04), p. 477-491
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 60, No. 4 ( 2021-04), p. 477-491
    Abstract: Various methods have been developed to characterize cloud type, otherwise referred to as cloud regime. These include manual sky observations, combining radiative and cloud vertical properties observed from satellite, surface-based remote sensing, and digital processing of sky imagers. While each method has inherent advantages and disadvantages, none of these cloud-typing methods actually includes measurements of surface shortwave or longwave radiative fluxes. Here, a method that relies upon detailed, surface-based radiation and cloud measurements and derived data products to train a random-forest machine-learning cloud classification model is introduced. Measurements from five years of data from the ARM Southern Great Plains site were compiled to train and independently evaluate the model classification performance. A cloud-type accuracy of approximately 80% using the random-forest classifier reveals that the model is well suited to predict climatological cloud properties. Furthermore, an analysis of the cloud-type misclassifications is performed. While physical cloud types may be misreported, the shortwave radiative signatures are similar between misclassified cloud types. From this, we assert that the cloud-regime model has the capacity to successfully differentiate clouds with comparable cloud–radiative interactions. Therefore, we conclude that the model can provide useful cloud-property information for fundamental cloud studies, inform renewable energy studies, and be a tool for numerical model evaluation and parameterization improvement, among many other applications.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    URL: Article
    DOI: 10.1175/JAMC-D-20-0153.1
    RVK:
    UA 4547
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Regime‐Specific Cloud Vertical Overlap Characteristics From Radar and Lidar Observations at the ARM Sites
    American Geophysical Union (AGU) ; 2023
    In:  Journal of Geophysical Research: Atmospheres Vol. 128, No. 6 ( 2023-03-27)
    Details
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 128, No. 6 ( 2023-03-27)
    Abstract: Decorrelation length scales varied by cloud regime at the Atmospheric Radiation Measurement Program Southern Great Plains site between 0.04 and 4.58 km Decorrelation length scales varied by site with values ranging from near 1 km in the Arctic to near 3 km in Brazil Decorrelation length scales for the same cloud regime across the sites were similar, although some cloud regimes exhibited differences
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    URL: Article
    DOI: 10.1029/2022JD037772
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Evaluating convective planetary boundary layer height estimations resolved by both active and passive remote sensing instruments during the CHEESEHEAD19 field campaign
    Copernicus GmbH ; 2022
    In:  Atmospheric Measurement Techniques Vol. 15, No. 8 ( 2022-04-25), p. 2479-2502
    Details
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 15, No. 8 ( 2022-04-25), p. 2479-2502
    Abstract: Abstract. During the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, held in the summer of 2019 in northern Wisconsin, USA, active and passive ground-based remote sensing instruments were deployed to understand the response of the planetary boundary layer to heterogeneous land surface forcing. These instruments include radar wind profilers, microwave radiometers, atmospheric emitted radiance interferometers, ceilometers, high spectral resolution lidars, Doppler lidars, and collaborative lower-atmospheric mobile profiling systems that combine several of these instruments. In this study, these ground-based remote sensing instruments are used to estimate the height of the daytime planetary boundary layer, and their performance is compared against independent boundary layer depth estimates obtained from radiosondes launched as part of the field campaign. The impact of clouds (in particular boundary layer clouds) on boundary layer depth estimations is also investigated. We found that while all instruments are overall able to provide reasonable boundary layer depth estimates, each of them shows strengths and weaknesses under certain conditions. For example, radar wind profilers perform well during cloud-free conditions, and microwave radiometers and atmospheric emitted radiance interferometers have a very good agreement during all conditions but are limited by the smoothness of the retrieved thermodynamic profiles. The estimates from ceilometers and high spectral resolution lidars can be hindered by the presence of elevated aerosol layers or clouds, and the multi-instrument retrieval from the collaborative lower atmospheric mobile profiling systems can be constricted to a limited height range in low-aerosol conditions.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    URL: Article
    URL: Article
    DOI: 10.5194/amt-15-2479-2022
    DOI: 10.5194/amt-15-2479-2022-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2505596-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...