Intermittent Turbulence in the Stable Boundary Layer over Land. Part III: A Classification for Observations during CASES-99

Wiel, B.J.H. van de; Moene, Arnold F.; Hartogensis, O.K.; Bruin, H.A.R. de; Holtslag, A.A.M.

doi:10.1175/1520-0469(2003)060<2509:ititsb>2.0.co;2

Cited by 139 publications

(116 citation statements)

References 24 publications

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“…For forest in particular, even slightly better correlations have been reported using T a (Reichstein et al, 2005;Ruppert et al, 2006). Moreover, Van Dijk and Dolman (2004) found that using T a gives much more consistent results in inter-site comparisons, which they suggested to be due to problems and inconsistencies in the measurement of T s . Although they analysed R e of forest, the latter argument applies to other ecosystems as well.…”

Section: Net Ecosystem Exchange (Nee) and Ecosystem Resmentioning

confidence: 97%

Variability of annual CO<sub>2</sub> exchange from Dutch grasslands

Jacobs

Bosveld

et al. 2007

Biogeosciences

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Abstract. An intercomparison is made of the Net Ecosystem Exchange of CO 2 , NEE, for eight Dutch grassland sites: four natural grasslands, two production grasslands and two meteorological stations within a rotational grassland region. At all sites the NEE was determined during at least 10 months per site, using the eddy-covariance (EC) technique, but in different years. The NEE does not include any import or export other than CO 2 . The photosynthesis-light response analysis technique is used along with the respiration-temperature response technique to partition NEE into Gross Primary Production (GPP) and Ecosystem Respiration (R e ) and to obtain the eco-physiological characteristics of the sites at the field scale. Annual sums of NEE, GPP and R e are then estimated using the fitted response curves with observed radiation and air temperature from a meteorological site in the centre of The Netherlands as drivers. These calculations are carried out for four years (2002)(2003)(2004)(2005). Land use and management histories are not considered. The estimated annual R e for all individual sites is more or less constant per site and the average for all sites amounts to 1390±30 gC m −2 a −1 . The narrow uncertainty band (±2%) reflects the small differences in the mean annual air temperature. The mean annual GPP was estimated to be 1325 g C m −2 a −1 , and displays a much higher standard deviation, of ±110 gC m −2 a −1 (8%), which reflects the relatively large variation in annual solar radiation. The mean annual NEE amounts to -65±85 gC m −2 a −1 . From two sites, four-year records of CO 2 flux were available and analyzed (2002)(2003)(2004)(2005). Using the weather record of 2005 with optimizations from the other years, the standard deviation of annual GPP was estimated to be 171-206 gC m −2 a −1 (8-14%), of annual R e 227-247 gC m −2 a −1 (14-16%) and of annual NEE 176-276 gC m −2 a −1 . TheCorrespondence to: C. M. J. Jacobs (cor.jacobs@wur.nl) inter-site standard deviation was higher for GPP and R e , 534 gC m −2 a −1 (37.3%) and 486 gC m −2 a −1 (34.8%), respectively. However, the inter-site standard deviation of NEE was similar to the interannual one, amounting to 207 gC m −2 a −1 . Large differences occur due to soil type. The grasslands on organic (peat) soils show a mean net release of CO 2 of 220±90 g C m −2 a −1 while the grasslands on mineral (clay and sand) soils show a mean net uptake of CO 2 of 90±90 g C m −2 a −1 . If a weighing with the fraction of grassland on organic (20%) and mineral soils (80%) is applied, an average NEE of 28 ±90 g C m −2 a −1 is found. The results from the analysis illustrate the need for regionally specific and spatially explicit CO 2 emission estimates from grassland.

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Section: Net Ecosystem Exchange (Nee) and Ecosystem Resmentioning

confidence: 97%

Variability of annual CO<sub>2</sub> exchange from Dutch grasslands

Jacobs

Bosveld

et al. 2007

Biogeosciences

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“…Strongly stratified flow that develops due to clear-sky nocturnal longwave cooling of the ground in the presence of low wind speeds frequently exhibits turbulent mixing that is intermittent in nature (Businger 1973;Howell and Sun 1999;Mahrt 1999; Van de Wiel et al 2002a,b, 2003Vickers 2002, 2006;Banta et al 2007;Ohya et al 2008). If winds are very weak, cooling by radiative flux divergence in the lowest 50 m (usually ignored) can become comparable in magnitude to sensible heat-flux divergence, especially in the early evening and when fog is present (Van de Wiel et al 2003;Ha and Mahrt 2003;Sun et al 2003). In calm conditions, the surfacebased mixed layer can become very thin indeed (<30 m) and completely decoupled from the atmosphere above (Smedman 1988;Mahrt and Vickers 2006;Banta et al 2007;Mahrt 2011).…”

Section: Turbulent Mixing In the Nocturnal Stable Boundary Layer (Sbl)mentioning

confidence: 99%

Bulk Mixing and Decoupling of the Nocturnal Stable Boundary Layer Characterized Using a Ubiquitous Natural Tracer

Williams

Chambers

Griffiths

2013

Boundary-Layer Meteorol

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Vertical mixing of the nocturnal stable boundary layer (SBL) over a complex land surface is investigated for a range of stabilities, using a decoupling index (0 < D rb < 1) based on the 2-50 m bulk gradient of the ubiquitous natural trace gas radon-222. The relationship between D rb and the bulk Richardson number (R ib ) exhibits three broad regions: (1) a well-mixed region (D rb ≈ 0.05) in weakly stable conditions (R ib < 0.03); (2) a steeply increasing region (0.05 < D rb < 0.9) for "transitional" stabilities (0.03 < R ib < 1); and (3) a decoupled region (D rb ≈ 0.9-1.0) in very stable conditions (R ib > 1). D rb exhibits a large variability within individual R ib bins, however, due to a range of competing processes influencing bulk mixing under different conditions. To explore these processes in R ib -D rb space, we perform a bivariate analysis of the bulk thermodynamic gradients, various indicators of external influences, and key turbulence quantities at 10 and 50 m. Strong and consistent patterns are found, and five distinct regions in R ib -D rb space are identified and associated with archetypal stable boundary-layer regimes. Results demonstrate that the introduction of a scalar decoupling index yields valuable information about turbulent mixing in the SBL that cannot be gained directly from a single bulk thermodynamic stability parameter. A significant part of the high variability observed in turbulence statistics during very stable conditions is attributable to changes in the degree of decoupling of the SBL from the residual layer above. When examined in R ib -D rb space, it is seen that very different turbulence regimes can occur for the same value of R ib , depending on the particular combination of values for the bulk temperature gradient and wind shear, together with external factors. Extremely low turbulent variances and fluxes are found at 50 m height when R ib > 1 and D rb ≈ 1 (fully decoupled). These "quiescent" cases tend to occur when geostrophic forcing is very weak and subsidence is present, but are not associated with the largest bulk temperature gradients. Humidity and net radiation data indicate the presence of low cloud, patchy fog or dew, any of which may aid decoupling in these cases by preventing temperature gradients from increasing sufficiently to favour gravity wave activity. The largest temperature gradients in our dataset are actually associated with smaller values of the decoupling index (D rb < 0.7), indicating the presence of mixing. Strong evidence is seen from enhanced turbulence levels, fluxes and submeso activity at 50 m, as well as high temperature variances and heat flux intermittencies at 10 m, suggesting this region of the R ib -D rb distribution can be identified as a top-down mixing regime. This may indicate an important role for gravity waves and other wave-like phenomena in providing the energy required for sporadic mixing at this complex terrain site.

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“…These conditions generally correspond to very small averaged turbulent heat flux, as in the radiative regime of Van de Wiel et al (2003). The weak turbulence is generated primarily by non-stationary shear associated with wave-like modes and more complex submesoscale motions on time-scales of minutes or tens of minutes (e.g.…”

Section: Introductionmentioning

confidence: 99%

Turbulence in the nocturnal boundary layer with light and variable winds

Mahrt

Richardson

Seaman

et al. 2012

Quart J Royal Meteoro Soc

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Turbulence quantities are analyzed from nine months of data collected on the floor of a valley where nocturnal cold pools are frequent. Often the speed of the vectoraveraged wind over the night is less than 0.5 m s −1 (near-calm winds) with no preference for wind direction. The quantity of such near-calm data is sufficiently large to allow new types of analyses as well as the opportunity to examine statistics of the previously ignored near-neutral subclass of near-calm winds.For near-calm weak winds and strong stratification, the turbulence can be difficult to isolate from wave-like motions and more complex small-scale structures. The smallest scale perturbations on time-scales less than 5 s behave most like turbulence. Larger-scale perturbations are characterized by very weak vertical velocity fluctuations and large temperature fluctuations, but lead to systematic downward heat flux after extensive averaging.For near-calm nocturnal conditions, significant turbulence is mainly generated by short-term (minutes) accelerations of unknown origin. The turbulence between such infrequent mixing events is extremely weak, but not zero. While the turbulence in the events approximately follows similarity theory, the extremely weak turbulence scales neither with stratification nor bulk shear, and its inferred vertical length-scale is small compared to the distance from the ground, even at the 2 m level. Copyright

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Intermittent Turbulence in the Stable Boundary Layer over Land. Part III: A Classification for Observations during CASES-99

Cited by 139 publications

References 24 publications

Variability of annual CO<sub>2</sub> exchange from Dutch grasslands

Variability of annual CO<sub>2</sub> exchange from Dutch grasslands

Bulk Mixing and Decoupling of the Nocturnal Stable Boundary Layer Characterized Using a Ubiquitous Natural Tracer

Turbulence in the nocturnal boundary layer with light and variable winds

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Intermittent Turbulence in the Stable Boundary Layer over Land. Part III: A Classification for Observations during CASES-99

Cited by 139 publications

References 24 publications

Variability of annual CO&lt;sub&gt;2&lt;/sub&gt; exchange from Dutch grasslands

Variability of annual CO&lt;sub&gt;2&lt;/sub&gt; exchange from Dutch grasslands

Bulk Mixing and Decoupling of the Nocturnal Stable Boundary Layer Characterized Using a Ubiquitous Natural Tracer

Turbulence in the nocturnal boundary layer with light and variable winds

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Product

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Variability of annual CO<sub>2</sub> exchange from Dutch grasslands

Variability of annual CO<sub>2</sub> exchange from Dutch grasslands