scholarly journals Observing Clouds in 4D with Multiview Stereophotogrammetry

2018 ◽  
Vol 99 (12) ◽  
pp. 2575-2586 ◽  
Author(s):  
David M. Romps ◽  
Ruşen Öktem
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Life Cycles ◽  
Digital Cameras ◽  
Southern Great Plains ◽  
Stereo Cameras ◽  
Weather And Climate ◽  
Stereo Reconstruction ◽  
Shallow Clouds ◽  
Atmospheric Radiation Measurement

AbstractNewly installed stereo cameras ringing the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site in Oklahoma are providing a 4D gridded view of shallow clouds. Six digital cameras have been installed in pairs at a distance of 6 km from the site and with a spacing of 500 m between cameras in a pair. These pairs of cameras provide stereoscopic views of shallow clouds from all sides; when these data are combined, they allow for a complete stereo reconstruction. The result—the Clouds Optically Gridded by Stereo (COGS) product—is a 4D grid of cloudiness covering a 6 km × 6 km × 6 km cube at a spatial resolution of 50 m and a temporal resolution of 20 s. This provides a unique set of data on the sizes, lifetimes, and life cycles of shallow clouds. This type of information is critical for developing cloud macrophysical schemes for the next generation of weather and climate models.

scholarly journals Long-Term Trends in Downwelling Spectral Infrared Radiance over the U.S. Southern Great Plains

2011 ◽  
Vol 24 (18) ◽  
pp. 4831-4843 ◽  
Author(s):  
P. Jonathan Gero ◽  
David D. Turner
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Southern Great Plains ◽  
Infrared Radiance ◽  
Term Change ◽  
Atmospheric Radiation Measurement ◽  
Long Term Trends ◽  
Thin Cloud ◽  
The U.S

Abstract A trend analysis was applied to a 14-yr time series of downwelling spectral infrared radiance observations from the Atmospheric Emitted Radiance Interferometer (AERI) located at the Atmospheric Radiation Measurement Program (ARM) site in the U.S. Southern Great Plains. The highly accurate calibration of the AERI instrument, performed every 10 min, ensures that any statistically significant trend in the observed data over this time can be attributed to changes in the atmospheric properties and composition, and not to changes in the sensitivity or responsivity of the instrument. The measured infrared spectra, numbering more than 800 000, were classified as clear-sky, thin cloud, and thick cloud scenes using a neural network method. The AERI data record demonstrates that the downwelling infrared radiance is decreasing over this 14-yr period in the winter, summer, and autumn seasons but it is increasing in the spring; these trends are statistically significant and are primarily due to long-term change in the cloudiness above the site. The AERI data also show many statistically significant trends on annual, seasonal, and diurnal time scales, with different trend signatures identified in the separate scene classifications. Given the decadal time span of the dataset, effects from natural variability should be considered in drawing broader conclusions. Nevertheless, this dataset has high value owing to the ability to infer possible mechanisms for any trends from the observations themselves and to test the performance of climate models.

Prediction for cloud spacing confirmed using stereo cameras

2021 ◽  
Author(s):  
Ruşen Öktem ◽  
David M. Romps
Keyword(s):  
Great Plains ◽  
Cloud Base ◽  
Effective Diameter ◽  
Horizontal Scale ◽  
Convective Boundary ◽  
Southern Great Plains ◽  
Stereo Cameras ◽  
Atmospheric Radiation Measurement ◽  
The Mean ◽  
Lifting Condensation Level

AbstractUsing three years of the Clouds Optically Gridded by Stereo (COGS) product, the mean cloud base, cloud top, cloud width, and cloud spacing are described with respect to their seasonal and/or diurnal evolution at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. In addition to confirming and extending prior results, the data show that the effective diameter of shallow cumuli are approximately equal to the height above ground of the lifting condensation level (LCL). Furthermore, the cloud spacing is found to closely match a prediction by Thuburn and Efstathiou for the horizontal scale of the largest unstable eddies in an unsheared convective boundary layer.

scholarly journals Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

2021 ◽  
Vol 13 (12) ◽  
pp. 2309
Author(s):  
Jingjing Tian ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Likun Wang ◽  
Rusen Öktem ◽  
...  
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Detection Threshold ◽  
Department Of Energy ◽  
Surface Reflectance ◽  
Cloud Detection ◽  
Southern Great Plains ◽  
Clear Sky ◽  
Shallow Cumulus ◽  
Stereo Cameras

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ∆R. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

scholarly journals A Mechanistically Credible, Poleward Shift in Warm-Season Precipitation Projected for the U.S. Southern Great Plains?

2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Dry Season ◽  
Wet Season ◽  
Southern Great Plains ◽  
Poleward Shift

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.

scholarly journals Ground-based temperature and humidity profiling: combining active and passive remote sensors

2021 ◽  
Vol 14 (4) ◽  
pp. 3033-3048
Author(s):  
David D. Turner ◽  
Ulrich Löhnert
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Great Plains ◽  
Optimal Estimation ◽  
Differential Absorption ◽  
Southern Great Plains ◽  
Atmospheric Research ◽  
Remote Sensors ◽  
Central Portugal ◽  
Atmospheric Radiation Measurement

Abstract. Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal-estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigão field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for the IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties) and that the combined IR + MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR + DIAL and MW + DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is a slight increase in the information content in the retrieved temperature profile using the IR + DIAL relative to the IR-only; this was not observed in the MW + DIAL retrieval.

scholarly journals THOR—Cloud Thickness from Offbeam Lidar Returns

2005 ◽  
Vol 22 (6) ◽  
pp. 605-627 ◽  
Author(s):  
Robert F. Cahalan ◽  
Matthew McGill ◽  
John Kolasinski ◽  
Tamás Várnai ◽  
Ken Yetzer
Keyword(s):  
Great Plains ◽  
Detection System ◽  
Skin Depth ◽  
Field Of View ◽  
Wide Angle ◽  
Southern Great Plains ◽  
Diffuse Halo ◽  
Atmospheric Radiation Measurement ◽  
Cloud Thickness ◽  
Physical Thickness

Abstract Conventional wisdom is that lidar pulses do not significantly penetrate clouds having an optical thickness exceeding about τ = 2, and that no returns are detectible from more than a shallow skin depth. Yet optically thicker clouds of τ ≫ 2 reflect a larger fraction of visible photons and account for much of the earth’s global average albedo. As cloud-layer thickness grows, an increasing fraction of reflected photons are scattered multiple times within the cloud and return from a diffuse concentric halo that grows around the incident pulse, increasing in horizontal area with layer physical thickness. The reflected halo is largely undetected by narrow field-of-view (FOV) receivers commonly used in lidar applications. Cloud Thickness from Offbeam Returns (THOR) is an airborne wide-angle detection system with multiple FOVs, capable of observing the diffuse halo as a wide-angle signal, from which the physical thickness of optically thick clouds can be retrieved. This paper describes the THOR system, demonstrates that the halo signal is stronger for thicker clouds, and presents a validation of physical thickness retrievals for clouds having τ > 20, from NASA’s P-3B flights over the Department of Energy’s Atmospheric Radiation Measurement Southern Great Plains site, using the lidar, radar, and other ancillary ground-based data.

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