A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Abstract Measurements made in the Columbia River Basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP 2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modelled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin-Obukhov similarity and (ii) a modified Priestley-Taylor (P-T) algorithm with physically based ecophysiological constraints which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP 2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various timescales based on the modelled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP 2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

2013 ◽  
Vol 17 (14) ◽  
pp. 1-22 ◽  
Author(s):  
Allison L. Steiner ◽  
Dori Mermelstein ◽  
Susan J. Cheng ◽  
Tracy E. Twine ◽  
Andrew Oliphant

Abstract Atmospheric aerosols scatter and potentially absorb incoming solar radiation, thereby reducing the total amount of radiation reaching the surface and increasing the fraction that is diffuse. The partitioning of incoming energy at the surface into sensible heat flux and latent heat flux is postulated to change with increasing aerosol concentrations, as an increase in diffuse light can reach greater portions of vegetated canopies. This can increase photosynthesis and transpiration rates in the lower canopy and potentially decrease the ratio of sensible to latent heat for the entire canopy. Here, half-hourly and hourly surface fluxes from six Flux Network (FLUXNET) sites in the coterminous United States are evaluated over the past decade (2000–08) in conjunction with satellite-derived aerosol optical depth (AOD) to determine if atmospheric aerosols systematically influence sensible and latent heat fluxes. Satellite-derived AOD is used to classify days as high or low AOD and establish the relationship between aerosol concentrations and the surface energy fluxes. High AOD reduces midday net radiation by 6%–65% coupled with a 9%–30% decrease in sensible and latent heat fluxes, although not all sites exhibit statistically significant changes. The partitioning between sensible and latent heat varies between ecosystems, with two sites showing a greater decrease in latent heat than sensible heat (Duke Forest and Walker Branch), two sites showing equivalent reductions (Harvard Forest and Bondville), and one site showing a greater decrease in sensible heat than latent heat (Morgan–Monroe). These results suggest that aerosols trigger an ecosystem-dependent response to surface flux partitioning, yet the environmental drivers for this response require further exploration.


2015 ◽  
Vol 15 (4) ◽  
pp. 2081-2103 ◽  
Author(s):  
J. Sievers ◽  
T. Papakyriakou ◽  
S. E. Larsen ◽  
M. M. Jammet ◽  
S. Rysgaard ◽  
...  

Abstract. Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm−2, |latent heat flux|> 20 Wm−2 and |CO2 flux|> 100 mmol m−2 d−1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5–20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23–98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.


2009 ◽  
Vol 48 (12) ◽  
pp. 2474-2486 ◽  
Author(s):  
Kun Yang ◽  
Jun Qin ◽  
Xiaofeng Guo ◽  
Degang Zhou ◽  
Yaoming Ma

Abstract To clarify the thermal forcing of the Tibetan Plateau, long-term coarse-temporal-resolution data from the China Meteorological Administration have been widely used to estimate surface sensible heat flux by bulk methods in many previous studies; however, these estimates have seldom been evaluated against observations. This study at first evaluates three widely used bulk schemes against Tibet instrumental flux data. The evaluation shows that large uncertainties exist in the heat flux estimated by these schemes; in particular, upward heat fluxes in winter may be significantly underestimated, because diurnal variations of atmospheric stability were not taken into account. To improve the estimate, a new method is developed to disaggregate coarse-resolution meteorological data to hourly according to statistical relationships derived from high-resolution experimental data, and then sensible heat flux is estimated from the hourly data by a well-validated flux scheme. Evaluations against heat flux observations in summer and against net radiation observations in winter indicate that the new method performs much better than previous schemes, and therefore it provides a robust basis for quantifying the Tibetan surface energy budget.


2021 ◽  
Vol 22 (10) ◽  
pp. 2547-2564
Author(s):  
Georg Lackner ◽  
Daniel F. Nadeau ◽  
Florent Domine ◽  
Annie-Claude Parent ◽  
Gonzalo Leonardini ◽  
...  

AbstractRising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux.


2019 ◽  
Vol 36 (9) ◽  
pp. 1849-1861
Author(s):  
Vidhi Bharti ◽  
Eric Schulz ◽  
Christopher W. Fairall ◽  
Byron W. Blomquist ◽  
Yi Huang ◽  
...  

Given the large uncertainties in surface heat fluxes over the Southern Ocean, an assessment of fluxes obtained by European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) product, the Australian Integrated Marine Observing System (IMOS) routine observations, and the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project hybrid dataset is performed. The surface fluxes are calculated using the COARE 3.5 bulk algorithm with in situ data obtained from the NOAA Physical Sciences Division flux system during the Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment on board the R/V Investigator during a voyage (March–April 2016) in the Australian sector of the Southern Ocean (43°–53°S). ERA-Interim and OAFlux data are further compared with the Southern Ocean Flux Station (SOFS) air–sea flux moored surface float deployed for a year (March 2015–April 2016) at ~46.7°S, 142°E. The results indicate that ERA-Interim (3 hourly at 0.25°) and OAFlux (daily at 1°) estimate sensible heat flux H s accurately to within ±5 W m−2 and latent heat flux H l to within ±10 W m−2. ERA-Interim gives a positive bias in H s at low latitudes (<47°S) and in H l at high latitudes (>47°S), and OAFlux displays consistently positive bias in H l at all latitudes. No systematic bias with respect to wind or rain conditions was observed. Although some differences in the bulk flux algorithms are noted, these biases can be largely attributed to the uncertainties in the observations used to derive the flux products.


2008 ◽  
Vol 9 (2) ◽  
pp. 173-193 ◽  
Author(s):  
D. Schüttemeyer ◽  
A. F. Moene ◽  
A. A. M. Holtslag ◽  
H. A. R. de Bruin

Abstract In this study different parameterizations for land surface models currently employed in meteorological models at ECMWF [Tiled ECMWF Surface Scheme for Exchange Processes over Land (TESSEL)] and NCEP (Noah) are evaluated for a semiarid region in Ghana, West Africa. Both schemes utilize the Jarvis–Stewart approach to calculate canopy conductance as the critical variable for partitioning the available energy into sensible and latent heat flux. Additionally, an approach within Noah is tested to calculate canopy conductance based on plant physiology (A-gs method), where the photosynthetic assimilation is coupled to the leaf stomatal conductance. All parameterizations were run offline for a seasonal cycle in 2002/03 using observations as forcings at two test sites. The two locations are in the humid tropical southern region and in the drier northern region. For the purpose of forcing and evaluation, a new set of data has been utilized to include surface fluxes obtained by scintillometry. The measurements include the rapid wet-to-dry transition after the wet season at both sites. As a general trend, it has been found that during the wet period of a season net radiation is described well by all parameterizations. During the drying process the errors in modeled net radiation increased at both sites. The models perform poorly in simulating soil heat fluxes with larger errors for TESSEL for both sites. The evolution in time for sensible heat flux and latent heat flux was tackled in different ways by the utilized parameterizations and sites with enhanced model performance for the more southern site. Soil moisture in the upper soil layers is modeled with small errors for the different parameterizations. Key adjustments for reducing net radiation during the dry period of a season are discussed. In particular, the ratio of roughness length of momentum and heat was found to be an important parameter, but will require seasonal adjustments.


2016 ◽  
Author(s):  
Seyed Hamed Alemohammad ◽  
Bin Fang ◽  
Alexandra G. Konings ◽  
Julia K. Green ◽  
Jana Kolassa ◽  
...  

Abstract. A new global estimate of surface turbulent fluxes, including latent heat flux (LE), sensible heat flux (H), and gross primary production (GPP) is developed using remotely sensed Solar-Induced Fluorescence (SIF) and other radiative and meteorological variables. The approach uses an artificial neural network (ANN) with a Bayesian perspective to learn from the training datasets: a target input dataset is generated using three independent data sources and a triple collocation (TC) algorithm to define a prior distribution. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides surface turbulent fluxes from 2007 to 2015 at 1° × 1° spatial resolution and on monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are validated using FLUXNET tower measurements across various climates and conditions. WECANN performs well in most cases and is strongly constrained by SIF information. The impact of SIF on WECANN retrievals is evaluated by removing it from the input dataset of the ANN, and it shows that SIF has significant influence, especially in regions of high vegetation cover and in humid conditions. When compared to in situ eddy covariance observations, WECANN typically outperforms other estimates, particularly for sensible and latent heat fluxes.


2016 ◽  
Vol 38 ◽  
pp. 75
Author(s):  
Rafael Maroneze ◽  
Otávio Costa Acevedo ◽  
Felipe Denardin Costa

The determination of the turbulent fluxes in very stable conditions is done, generally, through parameterizations. In this work the turbulent fluxes are estimated, by using a simplified model, through prognostic equations for the turbulent intensity, the sensible heat flux and the temperature variance. The results indicate that the model is able to reproduce both atmospheric coupling and the intermittent character of the turbulence in very stable conditions.


2009 ◽  
Vol 6 (3) ◽  
pp. 4619-4635 ◽  
Author(s):  
W. Ma ◽  
Y. Ma ◽  
Z. Hu ◽  
B. Su ◽  
J. Wang ◽  
...  

Abstract. Surface fluxes are important boundary conditions for climatological modeling and the Asian monsoon system. Recent availability of high-resolution, multi-band imagery from the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor has enabled us to estimate surface fluxes to bridge the gap between local scale flux measurements using micrometeorological instruments and regional scale land-atmosphere exchanges of water and heat fluxes that are fundamental for the understanding of the water cycle in the Asian monsoon system. A Surface Energy Balance System (SEBS) method based on ASTER data and field observations has been proposed and tested for deriving net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λ E) over heterogeneous land surface in this paper. As a case study, the methodology was applied to the experimental area of the WATER (Watershed Allied Telemetry Experimental Research), located at the mid-to-upstream sections of the Heihe River, northwest China. The ASTER data of 3 May and 4 June in 2008 was used in this paper for the case of mid-to-upstream sections of the Heihe River Basin. To validate the proposed methodology, the ground-measured land surface heat fluxes (net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λ E)) were compared to the ASTER derived values. The results show that the derived surface variables and land surface heat fluxes in different months over the study area are in good accordance with the land surface status. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface heat fluxes using the ASTER data and filed observation over the study area.


Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 299
Author(s):  
Noman Ali Buttar ◽  
Hu Yongguang ◽  
Josef Tanny ◽  
M Waqar Akram ◽  
Abdul Shabbir

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.


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