Regime‐Specific Cloud Vertical Overlap Characteristics From Radar and Lidar Observations at the ARM Sites

Climate and numerical weather prediction models require assumptions to represent the vertical distribution of subgrid‐scale clouds, which have radiative transfer implications. In this study, nearly 25 years of ground‐based radar and lidar observations of vertical cloud profiles at the Atmospheric Ra...

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Veröffentlicht in:Journal of geophysical research. Atmospheres 2023-03, Vol.128 (6), p.n/a
Hauptverfasser: Balmes, Kelly A., Sedlar, Joseph, Riihimaki, Laura D., Olson, Joseph B., Turner, David D., Lantz, Kathleen
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container_issue 6
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container_title Journal of geophysical research. Atmospheres
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creator Balmes, Kelly A.
Sedlar, Joseph
Riihimaki, Laura D.
Olson, Joseph B.
Turner, David D.
Lantz, Kathleen
description Climate and numerical weather prediction models require assumptions to represent the vertical distribution of subgrid‐scale clouds, which have radiative transfer implications. In this study, nearly 25 years of ground‐based radar and lidar observations of vertical cloud profiles at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site are utilized to derive cloud vertical overlap characteristics from the Cloud Type (CLDTYPE) data product. The cloud vertical overlap characteristics are further separated by cloud regime by considering seven cloud types (i.e., low cloud, congestus, deep convection, altocumulus, altostratus, cirrostratus, and cirrus) as well as periods of shallow cumulus. The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites among other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting. Plain Language Summary The complexity of cloud vertical structure requires approximations in weather and climate models, which has implication for the forecast of how much sunlight reaches the surface. Cloud observations from radars and lidars help to inform how cloud layers overlap vertically. The cloud observations ultimately inform what model assumptions best capture the observed cloud vertical structure. In this study, cloud profiles from ground‐based radars and lidars are considered to calculate cloud vertical overlap characteristics at 18 long‐term and short‐term sites across the globe. The cloud vertical overlap characteristics are also considered by cloud types to understand if cloud type provides additional information o
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The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites among other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting. Plain Language Summary The complexity of cloud vertical structure requires approximations in weather and climate models, which has implication for the forecast of how much sunlight reaches the surface. Cloud observations from radars and lidars help to inform how cloud layers overlap vertically. The cloud observations ultimately inform what model assumptions best capture the observed cloud vertical structure. In this study, cloud profiles from ground‐based radars and lidars are considered to calculate cloud vertical overlap characteristics at 18 long‐term and short‐term sites across the globe. The cloud vertical overlap characteristics are also considered by cloud types to understand if cloud type provides additional information on the model assumptions to use. The cloud vertical overlap characteristics are found to vary by site, season, and cloud type. The results could help inform development of cloud vertical overlap assumptions within weather and climate models and potentially improve prediction of sunlight reaching the surface, which has implications for weather, climate, and renewable energy forecasting. Key Points 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</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2022JD037772</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Altocumulus clouds ; Altostratus clouds ; Atmospheric models ; Atmospheric radiation ; Atmospheric radiation measurements ; Climate ; Climate and weather ; Climate models ; Climate prediction ; Cloud observations ; Cloud types ; Clouds ; Convection ; Downward long wave radiation ; ENVIRONMENTAL SCIENCES ; Geophysics ; Lidar ; Lidar observations ; Low clouds ; Meteorological satellites ; Modelling ; Numerical prediction ; Numerical weather forecasting ; Prediction models ; Radar ; Radiation measurement ; Radiative transfer ; Renewable energy ; Renewable resources ; Sunlight ; Vertical distribution ; Vertical profiles ; Weather ; Weather forecasting</subject><ispartof>Journal of geophysical research. 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The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites among other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting. Plain Language Summary The complexity of cloud vertical structure requires approximations in weather and climate models, which has implication for the forecast of how much sunlight reaches the surface. Cloud observations from radars and lidars help to inform how cloud layers overlap vertically. The cloud observations ultimately inform what model assumptions best capture the observed cloud vertical structure. In this study, cloud profiles from ground‐based radars and lidars are considered to calculate cloud vertical overlap characteristics at 18 long‐term and short‐term sites across the globe. 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ispartof Journal of geophysical research. Atmospheres, 2023-03, Vol.128 (6), p.n/a
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2169-8996
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recordid cdi_osti_scitechconnect_1960768
source Wiley Online Library; Alma/SFX Local Collection
subjects Altocumulus clouds
Altostratus clouds
Atmospheric models
Atmospheric radiation
Atmospheric radiation measurements
Climate
Climate and weather
Climate models
Climate prediction
Cloud observations
Cloud types
Clouds
Convection
Downward long wave radiation
ENVIRONMENTAL SCIENCES
Geophysics
Lidar
Lidar observations
Low clouds
Meteorological satellites
Modelling
Numerical prediction
Numerical weather forecasting
Prediction models
Radar
Radiation measurement
Radiative transfer
Renewable energy
Renewable resources
Sunlight
Vertical distribution
Vertical profiles
Weather
Weather forecasting
title Regime‐Specific Cloud Vertical Overlap Characteristics From Radar and Lidar Observations at the ARM Sites
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