Nocturnal Near-Surface Temperature, but not Flow Dynamics, can be Predicted by Microtopography in a Mid-Range Mountain Valley

Pfister, Lena; Sigmund, Armin; Olesch, Johannes; Thomas, Christoph

doi:10.1007/s10546-017-0281-y

Cited by 21 publications

(26 citation statements)

References 29 publications

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“…A small fluctuation of the downwelling long-wave radiation in combination with a large net radiation balance led to radiative cooling across the entire transect. This is also supported by R ij ≃1.0 for the 64-min time-scale for NC 3 indicating horizontally homogeneous cooling, similar to the results of Thomas (2011) andPfister et al (2017). Lee turbulence impacted near-surface temperatures only for time-scales smaller 64 min, which was evident by the asymmetry in decay of R ij at the north and south shoulders (Figure 13c).…”

Section: Boundary-layer Regime Of Night Classsupporting

confidence: 86%

“…This is also supported by

R_{θ_{i j}} ≃

1.0 for the 64‐min time‐scale for NC 3 indicating horizontally homogeneous cooling, similar to the results of Thomas () and Pfister et al . (). Lee turbulence impacted near‐surface temperatures only for time‐scales smaller 64 min, which was evident by the asymmetry in decay of

R_{θ_{i j}}

at the north and south shoulders (Figure c).…”

Section: Resultsmentioning

confidence: 97%

“…A drop in the spatial correlation for temperature for the 64‐min time‐scale was observed (Figure a,b), in contrast to results from Thomas () and Pfister et al . () who also performed a MRD analysis of sonic network or DTS observations. Both studies found almost no drop of the spatial correlation for temperature across the entire domain at the 64‐min time‐scale, because near‐surface temperatures followed the diurnal cycle of heating during the day and cooling during the night.…”

Section: Resultsmentioning

confidence: 99%

“…; Pfister et al . ) complementing surface networks of classical eddy covariance stations. Near‐surface observations were taken by DTS at three levels up to 2 m above ground level (agl).…”

Section: Introductionmentioning

confidence: 99%

“…As a novelty, SCP featured measurements from the actively heated distributed temperature sensing (DTS) technique to obtain near-surface temperatures and wind speeds at a high spatial (0.25 m) and temporal (5 s) resolution. The DTS technique is an excellent tool for studying the nocturnal boundary layer due to spatially continuous measurements (Thomas et al, 2012;Sayde et al, 2015;Zeeman et al, 2015;Pfister et al, 2017) complementing surface networks of classical eddy covariance stations. Near-surface observations were taken by DTS at three levels up to 2 m above ground level (agl).…”

Section: Introductionmentioning

confidence: 99%

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Classifying the nocturnal atmospheric boundary layer into temperature and flow regimes

Pfister

Lapo

Sayde

et al. 2019

Quart J Royal Meteoro Soc

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We propose a classification scheme for nocturnal atmospheric boundary layers and apply it to investigate the spatio‐temporal structure of air temperature and wind speed in a shallow valley during the Shallow Cold Pool Experiment. This field campaign was the first to collect spatially continuous temperature and wind information at high resolution (1 s, 0.25 m) using the distributed temperature sensing technique across a 220 m long transect at three heights (0.5, 1.0, 2.0 m). The night‐time classification scheme was motivated by a surface energy balance and used a combination of static stability, wind regime and longwave radiative forcing as quantities to determine physically meaningful boundary‐layer regimes. Out of all potential combinations of these three quantities, 14 night‐time classes contained observations, of which we selected three for detailed analysis and comparison. The three classes represent a transition from mechanical to radiative forcing. The first night class represents conditions with strong dynamic forcing caused by locally induced lee turbulence dominating near‐surface temperatures across the shallow valley. The second night class was a concurrence of enhanced dynamic mixing due to significant winds at the valley shoulders and cold‐air pooling at the bottom of the shallow valley as a result of strong radiative cooling. The third night class was characteristic of weak winds eliminating the impact of mechanical mixing but emphasizing the formation and pooling of cold air at the valley bottom. The proposed night‐time classification scheme was found to sort the experimental data into physically meaningful regimes of surface flow and transport. It is suitable to stratify short‐ and long‐term experimental data for ensemble averaging and to identify case studies.

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Section: Boundary-layer Regime Of Night Classsupporting

confidence: 86%

“…This is also supported by

R_{θ_{i j}} ≃

R_{θ_{i j}}

at the north and south shoulders (Figure c).…”

Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

“…; Pfister et al . ) complementing surface networks of classical eddy covariance stations. Near‐surface observations were taken by DTS at three levels up to 2 m above ground level (agl).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Classifying the nocturnal atmospheric boundary layer into temperature and flow regimes

Pfister

Lapo

Sayde

et al. 2019

Quart J Royal Meteoro Soc

Self Cite

View full text Add to dashboard Cite

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Time–space variations of temperature in the nocturnal boundary layer

Mahrt

2020

Quart J Royal Meteoro Soc

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This study examines nocturnal temperature changes on time‐scales of 5–60 min over gentle terrain. Such temperature variations are often important after the early evening period of rapid cooling and can lead to large temporary warming or enhanced cooling. The time–space structure of temperature changes is examined statistically with a network of flux stations over gentle topography. Large temperature changes are often associated with coherent propagating modes and associated temporary reduction or elimination of the valley cold pool, local drainage flows, and lee turbulence. The largest variations of temperature with time occur for intermediate wind speeds. Low wind speeds correspond to greater spatial variability of temperature but less time dependence. Two nondimensional ratios are developed to represent the relative importance of temporal and spatial variability.

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Optical Fiber-Based Distributed Sensing Methods

Thomas

Selker

2021

Springer Handbook of Atmospheric Measurements

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Nocturnal Near-Surface Temperature, but not Flow Dynamics, can be Predicted by Microtopography in a Mid-Range Mountain Valley

Cited by 21 publications

References 29 publications

Classifying the nocturnal atmospheric boundary layer into temperature and flow regimes

Classifying the nocturnal atmospheric boundary layer into temperature and flow regimes

Time–space variations of temperature in the nocturnal boundary layer

Optical Fiber-Based Distributed Sensing Methods

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