Two Experiments on Using a Scintillometer to Infer the Surface Fluxes of Momentum and Sensible Heat

2012 ◽  
Vol 51 (9) ◽  
pp. 1685-1701 ◽  
Author(s):  
Edgar L Andreas
Keyword(s):  
Eddy Covariance ◽  
Correlation Coefficients ◽  
Arctic Sea Ice ◽  
Surface Fluxes ◽  
Index Structure ◽  
Quality Data ◽  
Sensible Heat ◽  
Traditional Use ◽  
Similarity Functions ◽  
Essential Question

AbstractA traditional use of scintillometry is to infer path-averaged values of the turbulent surface fluxes of sensible heat Hs and momentum τ (, where ρ is air density and u* is the friction velocity). Many scintillometer setups, however, measure only the path-averaged refractive-index structure parameter ; the wind information necessary for inferring u* and Hs comes from point measurements or is absent. The Scintec AG SLS20 surface-layer scintillometer system, however, measures both and the inner scale of turbulence ℓ0, where ℓ0 is related to the dissipation rate of turbulent kinetic energy ɛ. The SLS20 is thus presumed to provide path-averaged estimates of both u* and Hs. This paper describes comparisons between SLS20-derived estimates of u* and Hs and simultaneous eddy-covariance measurements of these quantities during two experiments: one, over Arctic sea ice; and a second, over a midlatitude land site during spring. For both experiments, the correlation between scintillometer and eddy-covariance fluxes is reasonable: correlation coefficients are typically above 0.7 for the better-quality data. For both experiments, though, the scintillometer usually underestimates u* and underestimates the magnitude of Hs when compared with the corresponding eddy-covariance values. The data also tend to be more scattered when < 10−14 m−2/3: the signal-to-noise ratio for scintillometer-derived fluxes decreases as decreases. An essential question that arises during these comparisons is what similarity functions to use for inferring fluxes from the scintillometer and ℓ0 measurements. The paper thus closes by evaluating whether any of four candidate sets of similarity functions is consistent with the scintillometer data.

scholarly journals Fetch Effect on Flux-Variance Estimations of Sensible and Latent Heat Fluxes of Camellia Sinensis

Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 299
Author(s):  
Noman Ali Buttar ◽  
Hu Yongguang ◽  
Josef Tanny ◽  
M Waqar Akram ◽  
Abdul Shabbir
Keyword(s):  
Heat Flux ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Sensible Heat Flux ◽  
Soil Heat Flux ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Effect Of Temperature ◽  
Sensible Heat ◽  
Fine Wire

Precise estimation of surface-atmosphere exchange is a major challenge in micrometeorology. Previous literature presented the eddy covariance (EC) as the most reliable method for the measurements of such fluxes. Nevertheless, the EC technique is quite expensive and complex, hence other simpler methods are sought. One of these methods is Flux-Variance (FV). The FV method estimates sensible heat flux (H) using high frequency (~10Hz) air temperature measurements by a fine wire thermocouple. Additional measurements of net radiation (Rn) and soil heat flux (G) allow the derivation of latent heat flux (LE) as the residual of the energy balance equation. In this study, the Flux Variance method was investigated, and the results were compared against eddy covariance measurements. The specific goal of the present study was to assess the performance of the FV method for the estimation of surface fluxes along a variable fetch. Experiment was carried out in a tea garden; an EC system measured latent and sensible heat fluxes and five fine-wire thermocouples were installed towards the wind dominant direction at different distances (fetch) of TC1 = 170 m, TC2 = 165 m, TC3 = 160 m, TC4 = 155 m and TC5 = 150 m from the field edge. Footprint analysis was employed to examine the effect of temperature measurement position on the ratio between 90% footprint and measurement height. Results showed a good agreement between FV and EC measurements of sensible heat flux, with all regression coefficients (R2) larger than 0.6; the sensor at 170 m (TC1), nearest to the EC system, had highest R2 = 0.86 and lowest root mean square error (RMSE = 25 Wm−2). The estimation of LE at TC1 was also in best agreement with eddy covariance, with the highest R2 = 0.90. The FV similarity constant varied along the fetch within the range 2.2–2.4.

scholarly journals Low-level jets and above-canopy drainage as causes of turbulent exchange in the nocturnal boundary layer

2014 ◽  
Vol 11 (16) ◽  
pp. 4507-4519 ◽  
Author(s):  
T. S. El-Madany ◽  
H. F. Duarte ◽  
D. J. Durden ◽  
B. Paas ◽  
M. J. Deventer ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Wind Speed ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Heat Fluxes ◽  
Vertical Wind ◽  
Sensible Heat ◽  
Intermittent Turbulence ◽  
Low Level Jets ◽  
Vertical Wind Velocity

Abstract. Sodar (SOund Detection And Ranging), eddy-covariance, and tower profile measurements of wind speed and carbon dioxide were performed during 17 consecutive nights in complex terrain in northern Taiwan. The scope of the study was to identify the causes for intermittent turbulence events and to analyze their importance in nocturnal atmosphere–biosphere exchange as quantified with eddy-covariance measurements. If intermittency occurs frequently at a measurement site, then this process needs to be quantified in order to achieve reliable values for ecosystem characteristics such as net ecosystem exchange or net primary production. Fourteen events of intermittent turbulence were identified and classified into above-canopy drainage flows (ACDFs) and low-level jets (LLJs) according to the height of the wind speed maximum. Intermittent turbulence periods lasted between 30 and 110 min. Towards the end of LLJ or ACDF events, positive vertical wind velocities and, in some cases, upslope flows occurred, counteracting the general flow regime at nighttime. The observations suggest that the LLJs and ACDFs penetrate deep into the cold air pool in the valley, where they experience strong buoyancy due to density differences, resulting in either upslope flows or upward vertical winds. Turbulence was found to be stronger and better developed during LLJs and ACDFs, with eddy-covariance data presenting higher quality. This was particularly indicated by spectral analysis of the vertical wind velocity and the steady-state test for the time series of the vertical wind velocity in combination with the horizontal wind component, the temperature, and carbon dioxide. Significantly higher fluxes of sensible heat, latent heat, and shear stress occurred during these periods. During LLJs and ACDFs, fluxes of sensible heat, latent heat, and CO2 were mostly one-directional. For example, exclusively negative sensible heat fluxes occurred while intermittent turbulence was present. Latent heat fluxes were mostly positive during LLJs and ACDFs, with a median value of 34 W m−2, while outside these periods the median was 2 W m−2. In conclusion, intermittent turbulence periods exhibit a strong impact on nocturnal energy and mass fluxes.

Area-Averaged Surface Fluxes Over the Litfass Region Based on Eddy-Covariance Measurements

2006 ◽  
Vol 121 (1) ◽  
pp. 33-65 ◽  
Author(s):  
Frank Beyrich ◽  
Jens-Peter Leps ◽  
Matthias Mauder ◽  
Jens Bange ◽  
Thomas Foken ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Surface Fluxes ◽  
Eddy Covariance Measurements

scholarly journals Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>

2016 ◽  
Vol 9 (11) ◽  
pp. 5523-5533 ◽  
Author(s):  
Sander van der Laan ◽  
Swagath Manohar ◽  
Alex Vermeulen ◽  
Fred Bosveld ◽  
Harro Meijer ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Activity Concentration ◽  
Regional Scale ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Spatial And Temporal Variability ◽  
Single Pair ◽  
The South ◽  
Practical Applications ◽  
Soil Flux

Abstract. We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values  > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

scholarly journals Air-Sea Fluxes of CO<sub>2</sub> and CH<sub>4</sub> from the Penlee Point Atmospheric Observatory on the South West Coast of the UK

2016 ◽  
Author(s):  
M. Yang ◽  
T. G. Bell ◽  
F. E. Hopkins ◽  
V. Kitidis ◽  
P. W. Cazenave ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
West Coast ◽  
Phytoplankton Bloom ◽  
Flux Measurement ◽  
Sensible Heat ◽  
The South ◽  
Eddy Covariance Method ◽  
Spring Phytoplankton Bloom ◽  
South West ◽  
South West Coast

Abstract. We present air-sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the South West coast of the United Kingdom. Measurements from the southwest direction (background marine air) at three different sampling heights (approximately 15, 18, 27 m above mean sea level, AMSL) in three different periods during 2014–2015 are shown. At sampling heights ≥ 18 m AMSL, measured fluxes of momentum and sensible heat demonstrate reasonable agreement with their expected transfer rates over the open ocean. This confirms the suitability of PPAO for air-sea exchange measurements. We observed reductions in the air-to-sea fluxes of CO2 from spring to summer in both years, which coincided with the breakdown of the spring phytoplankton bloom. At all sampling heights, mean CH4 fluxes were positive, suggesting marine emissions. Higher CH4 fluxes were observed during rising tides (20&amp;pm;3; 29&amp;pm;6; 38&amp;pm;3 μmole m−2 d−1 at 15, 27, 18 m AMSL) than during falling tides (14&amp;pm;2; 21&amp;pm;5; 22&amp;pm;2 μmole m−2 d−1, respectively), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. Based on observations at PPAO, we also estimate the detection limit of the eddy covariance CH4 flux measurement to be ~20 μmole m−2 d−1 over hourly timescales (~4 μmole m−2 d−1 over 24 hours).

scholarly journals Air–sea fluxes of CO<sub>2</sub> and CH<sub>4</sub> from the Penlee Point Atmospheric Observatory on the south-west coast of the UK

2016 ◽  
Vol 16 (9) ◽  
pp. 5745-5761 ◽  
Author(s):  
Mingxi Yang ◽  
Thomas G. Bell ◽  
Frances E. Hopkins ◽  
Vassilis Kitidis ◽  
Pierre W. Cazenave ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
West Coast ◽  
Phytoplankton Bloom ◽  
Open Ocean ◽  
Sensible Heat ◽  
The South ◽  
Sea Transport ◽  
Ch4 Emissions ◽  
South West ◽  
South West Coast

Abstract. We present air–sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the south-west coast of the United Kingdom. Measurements from the south-westerly direction (open water sector) were made at three different sampling heights (approximately 15, 18, and 27 m above mean sea level, a.m.s.l.), each from a different period during 2014–2015. At sampling heights  ≥  18 m a.m.s.l., measured fluxes of momentum and sensible heat demonstrate reasonable ( ≤  ±20 % in the mean) agreement with transfer rates over the open ocean. This confirms the suitability of PPAO for air–sea exchange measurements in shelf regions. Covariance air–sea CO2 fluxes demonstrate high temporal variability. Air-to-sea transport of CO2 declined from spring to summer in both years, coinciding with the breakdown of the spring phytoplankton bloom. We report, to the best of our knowledge, the first successful eddy covariance measurements of CH4 emissions from a marine environment. Higher sea-to-air CH4 fluxes were observed during rising tides (20 ± 3; 38 ± 3; 29 ± 6 µmole m−2 d−1 at 15, 18, 27 m a.m.s.l.) than during falling tides (14 ± 2; 22 ± 2; 21 ± 5 µmole m−2 d−1), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. These fluxes are a few times higher than the predicted CH4 emissions over the open ocean and are significantly lower than estimates from other aquatic CH4 hotspots (e.g. polar regions, freshwater). Finally, we found the detection limit of the air–sea CH4 flux by eddy covariance to be 20 µmole m−2 d−1 over hourly timescales (4 µmole m−2 d−1 over 24 h).

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (19) ◽  
pp. 7313-7323 ◽  
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.

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