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BOUNDARY LAYER (ATMOSPHERIC) AND AIR POLLUTION | Microclimate
Microclimate MW Rotach, University of Innsbruck, Innsbruck, Austria P Calanca, Agroscope Reckenholz-Taenikon, Zurich, Switzerland Ó 2015 Elsevier Ltd. All rights reserved.
Synopsis Microclimatology is concerned with the study of the processes by which the local surface properties affect the lowest layer of the atmosphere. Often the latter refers to the so-called roughness sublayer, but in some cases attention is more properly limited to the so-called canopy layer or then, conversely, the whole surface layer. Microclimates are described in terms of climatic variables, their temporal and vertical variability, as established by the balance equations that govern the exchange of radiation, heat, water, and other atmospheric constituents.
Introduction
characteristic temporal patterns observed in microclimatic records.
The word ‘climate’ stems from the Greek klíma (slope, zone), with its roots in klínein (to slope), and originally denoted ‘a zone of equal latitude,’ thus referring to the effects of latitude on the availability of solar energy. In fact, on a global scale the climate is above all determined by the latitudinal and seasonal distribution of incoming solar radiation as given by Earth’s orbital parameters. On very small scales, however, the climate is primarily shaped by the local surface properties that control the exchange of radiation, energy, momentum, and water between the ground and the atmosphere. The microclimate of a particular location can hence be defined as the collection of statistics describing the thermal and dynamical conditions prevailing in the atmospheric layer directly affected by the underlying surface. Accordingly, ‘descriptive microclimatology,’ can be identified as the study of the long-term average and typical variability of climate variables in the lowest layer of the atmosphere, while ‘physical microclimatology’ can be defined as the study of the processes by which the lowest layer of the atmosphere responds to surface boundary conditions. As is customary in climatology, the various aspects that concur in creating the microclimate of a particular location are identified with a number of so-called climate variables. Common climate variables include radiation, temperature, humidity, wind speed, and pressure (density), but, depending on the research focus, other variables need to be taken into account. For example, the health and comfort of the everincreasing number of people living in cities are directly related to the concentration and distribution of air pollutants, which are therefore required to characterize the microclimate of these particular environments. The surface properties determining a microclimate are seldom constant in time. Long-term variations may arise naturally or as a consequence of human-induced changes in land use. At the seasonal scale, variations in surface properties may be brought about by the presence of a snow cover or through the life cycle of plants. Short-term variations may, for example, be caused by the dynamic effects of the wind on the structure of the surface elements. Ultimately, it is this variability in surface properties that, along with the variability of the large-scale atmospheric forcing, is responsible for the
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The Lowest Layers of the Atmosphere The atmospheric layer affected by the local surface properties is called the ‘planetary boundary layer’ (PBL). It has a characteristic depth (zi) on the order of 1000 m and can be divided into an upper or outer layer (the uppermost 90%) and an inner or surface layer (SL) (the lowest 10%) (Figure 1). However, a direct influence of the surface characteristics on the atmospheric state is observed only in the lowest part of the SL, in the immediate vicinity of the roughness elements. If this layer of influence has any discernible thickness, it is because of a nonnegligible vertical extension of the ‘roughness elements’ (stones, vegetation, tress, and buildings). Therefore, this layer is usually called the ‘roughness sublayer.’ The upper part of the SL is then referred to as the ‘inertial sublayer.’ Over a relatively smooth surface such as short grass or sand, the roughness sublayer becomes very thin and the inertial sublayer is often associated with the entire SL (Figure 1). Based on these considerations, ‘microclimatology’ can also be defined as the study of the climatic state of the roughness sublayer or specific entities therein, even though the notion is most often extended to the examination of the entire SL or even PBL. Micrometeorology is then the study of the dynamics and thermodynamics of the SL or PBL.
The Roughness Sublayer In the roughness sublayer, the flow is affected by the individual roughness elements and hence is fully three-dimensional in nature. The upper boundary of the roughness sublayer, zr, is the level at which the horizontal variability associated with the roughness elements vanishes and the flow properties become horizontally homogeneous. Properly scaled ‘profiles’ of either mean flow characteristics or turbulence statistics will then merge to one curve whose shape is characteristic for the underlying surface. The depth of the roughness sublayer depends on the height and distribution of the roughness elements. For most surfaces, 2zh < zr < 5zh covers the range of estimates, where zh is the average height of roughness elements.
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Figure 1 Conceptual sketch and terminology for the lowest layers of the atmosphere over a rough surface. Note the logarithmic height scale. Level zi refers to the boundary layer height, zr to the height of the roughness sublayer, and zh to the (average) height of roughness elements.
The Canopy Layer The lowest part of the roughness sublayer is the canopy layer. It ranges from the surface to zh. In this layer, form (or pressure) drag and viscous drag on any individual roughness element are both significant and lead to a retardation of the flow. In addition, the material and orientation of the obstacles give rise to large variations in the energy balance, primarily through variations in the radiation balance, and also as a result of the distribution of sources and sinks of sensible heat, water vapor, or trace gases. Figure 2 shows the height ranges covered by the roughness sublayer and its lower part, the canopy layer, in dimensionless
Figure 2 Sketch of the vertical extension of the various layers over rough surfaces and their variation with the nondimensional quantities z/zh and zi/zh. Here, z denotes the (physical) height, zi refers to the boundary layer height, and zh is the (average) height of roughness elements. A value of zr/zh ¼ 3 is assumed for the height of the roughness sublayer. The arrows labeled with ‘city,’ ‘forest,’ ‘crop,’ and ‘short grass’ are based on typical values for the height of the roughness elements zh and the boundary layer height zi. Redrawn from Rotach, M.W., 1999. On the urban roughness sublayer. Atmospheric Environment 33, 4001–4008.
form. Arrows indicate how surfaces covered with short grass, crops, trees, and houses, respectively, fit into this scheme. It can be seen that the vertical range, to which the study of microclimate is confined, can extend up to several tens of meters or more in the case of an urban surface. However, in the case of a shallow boundary layer (small zi and large roughness elements), no inertial sublayer may be present at all.
Internal Boundary Layers The above considerations are valid for horizontally homogenous surfaces. In the presence of a pronounced small-scale variability of surface properties, internal boundary layers may form downwind of each major change in the surface characteristics. Internal boundary layers may be ‘thermal’ if they are primarily prompted by an abrupt change in surface temperature, as for example across a shoreline. Alternatively, if changes are primarily in the surface roughness, internal boundary layers are called ‘mechanical.’ Most common is, of course, the development of combined thermal and mechanical internal boundary layers. Internal boundary layers increase in depth with distance downstream from the surface discontinuities causing their development. Within a developing internal boundary layer, profiles of climate variables exhibit a continuous transition from conditions adjusted to the new surface characteristics close to the ground, to conditions still nearly in equilibrium with the conditions upstream of the leading edge. At still greater heights, horizontal gradients associated with surface heterogeneities become negligibly small due to the effects of turbulent mixing. The concept of a blending height has been introduced to denote the level at which the flow becomes independent of the local surface condition. In its strictest sense, the study of microclimate over heterogeneous surfaces is then confined to the airspace below the blending height.
Surface Characteristics The surface characteristics that determine the microclimate can be organized according to which aspect of the
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atmospheric dynamics and thermodynamics they affect for the most part: l
l
l
l
l
l
‘Radiative properties’ determine the radiation budget. These are the albedo (a), or surface reflectivity in the shortwave band of the radiation spectrum; the emissivity of the effective surface (ε); and the geometric properties that influence the receipt and loss of radiation, such as the skyview factor in the case of an urban surface or the canopy extinction coefficient (ke) in the case of a vegetated surface. ‘Aerodynamic properties’ determine the momentum budget. These are the surface roughness length (z0), the zero-plane displacement (d), and the drag coefficient (Cd). ‘Thermal properties’ determine the heat flow in the underlying substrate–roughness elements. These are the thermal conductivity (kg), the heat capacity (cg), and the thermal diffusivity (lg ¼ kg/cg). In soils, all of these properties strongly depend on the soil water content (SWC). ‘Soil hydraulic properties and vegetation characteristics’ affect soil moisture, the availability of water for evaporation and transpiration, and hence the partitioning between the turbulent energy fluxes and the conductive ground heat flux in the surface energy balance. ‘Vegetation properties’ control the distribution of radiation and the transfer of water vapor and trace gases within a canopy. In many modeling studies, these are primarily the Leaf Area Index (LAI) and stomatal conductance (gst), but they should more properly encompass all botanical, physiological, and geometric characteristics as well as species composition. ‘Water properties’ control the thermal state and the phase transitions in water bodies, in particular during the seasonal development of snow covers and ice bodies at high latitudes and elevated altitudes. These include, among others, the volumetric heat capacities of water (cw) and ice (ci), and the latent heat of fusion (Lf) and vaporization (Lv).
Although, in general, all properties concur in determining the local microclimate, their relative importance may vary
depending on the specific circumstances. Table 1 provides examples of parameters that are particularly significant in relation to specific surface types and situations. In many instances, the effective surface cannot be treated as static but undergoes dynamic changes. The examples in Table 1 emphasize the dynamic effects of the wind, either in the case of bending roughness elements (vegetated surfaces) or in the presence of water (waves) and snow (drift) surfaces. In complex terrain, the topographic characteristics that control the development of ‘mesoscale circulation systems,’ such as land and sea breezes or mountain and valley winds, need also to be taken into account to understand the nature of microclimates.
The Budget Equations The main role of the surface properties discussed in this article is to regulate the exchange of radiation, heat, and mass (water and carbon or other trace gases) between the ground and the atmosphere, establishing corresponding balances defined by the following budget equations: l
l
l
Radiation: Q ¼ KY K[ þ LY L[
[1]
Q ¼ QE þ QH þ QG þ DQS
[2]
Energy:
Water (mass): P ¼ E þ R þ In þ DW
[3]
In these equations, Q* denotes the net (all-wave) radiation flux at the surface; KY and K[ are the incoming and
Table 1 Relevant microclimatological parameters for broad categories of characteristic surfaces and for selected aspects of the establishment of local microclimates Surface type
Relevant parameters
Particular aspects
Bare soil
a, ε, z0, cg(SWC), kg(SWC)
Short vegetation (crops)
a, ε, z0, d, LAI, gst, ke
Tall vegetation (forest)
a, ε, z0, d, LAI, gst, ke
Water
a, z0, Cd
Snow and ice
a, ε, z0, cw, ci, Lf, Lv
Urban
a, ε, z0, d, Cd, SVF
Usually considered the simplest case of surfaces, providing in many cases a reference; soil thermal properties depend on SWC, which may also affect the albedo. Flexible roughness elements; zero-plane displacement is relatively small and in many cases negligible; in crops there is pronounced seasonal development, with the growth stage determining the LAI and eventually the exchange of radiation, energy, and water. Strong dynamic interactions with the atmospheric flow; often nonuniform vertical distribution of leaf density; importance of the storage terms in the balance equations. Albedo is a function of solar elevation (diurnal variations) and momentum exchange, as controlled by z0 or Cd; strongly dependent on wind regime and resulting wave height (Charnock’s roughness length model). Albedo depends on snow or ice age (seasonal variability) and is a function of solar elevation (diurnal variability); especially with low snow densities, the surface roughness of snow covers depends on drift conditions; melting leads to well-defined surface temperature. Stiff roughness elements; strong influence of the thermal properties of building material; geometry and distribution of roughness elements are of paramount importance for radiation, energy, and momentum exchange.
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Figure 3 Energy fluxes appearing in the energy budget equation for a layer of finite thickness. Subscripts g and h refer to the ground level and the average canopy height zh, respectively. QA denotes the contribution from horizontal advection to energy storage (DQS) in the volume. The latter is given by the divergence of all vertical and horizontal fluxes.
outgoing shortwave radiation fluxes, respectively; LY and L[ are the incoming and outgoing longwave radiation fluxes, respectively; QE and QH are the turbulent fluxes of latent and sensible heat, respectively; QG is the conductive heat flux to the substrate; DQS is the change in heat storage associated with the divergence of horizontal or vertical energy fluxes that arise from the finite size of the volume under consideration; P is the water input through precipitation; E is the loss of water vapor through evapotranspiration; R is the surface runoff; In is the vertical infiltration into the ground; and DW is the change in water storage. Moreover, on the right-hand side of the energy and water budget equations, fluxes directed away (toward) the surface are considered positive (negative). In the presence of snow and ice, transitions between the solid and liquid phases (melting and freezing) significantly contribute to both the energy and mass budgets. In urban environments, anthropogenic heat release also adds another contribution to the energy budget. In the case of vegetated surfaces, the net photosynthetic heat uptake or release appears as an additional term in the energy budget equation. Furthermore, in this latter case, the water budget equation needs to be modified to account for the interception of precipitation and the buildup of an interception store, from which water can evaporate. Another important remark should be made in relation to the budget equations. Although it is customary to refer to
eqns [1]–[3] as the ‘surface balance equations,’ it is essential to recall that in most cases they are established with respect to a layer of finite thickness (Figure 3). This makes it necessary to include the storage terms that account for changes in the energy and mass content of this layer (DQS and DW, respectively). The storage terms become particularly important when dealing with the microclimates of vegetative canopies or urban areas.
Profiles of Mean Quantities and Turbulence Characteristics One of the fundamental characteristics of climate variables in the atmospheric layer directly affected by the surface is their pronounced vertical variability. The associated ‘vertical profiles’ again depend in a systematic way on the surface properties, displaying temporal variations in correspondence to the time scales that characterize the governing budget equations. Figure 4 exemplarily shows daytime profiles of mean wind speed and potential temperature above a bare soil and a forest. In the panel on the right-hand side of the figure, d þ z0 refers to the height above which the shapes of the profiles start to become comparable to those observed over a bare soil. This feature of the profiles implies that they can be formulated using z0 and d as characteristic length scales. A ‘bare soil’ or relatively
Figure 4 Typical daytime mean vertical profiles of mean wind speed (u) and potential temperature (q) over a bare soil (left) and a vegetated surface (right). On the right-hand side of the figure, zh denotes the average height of the canopy, d w 2/3zh is the zero-plane displacement, and z0 w 0.1zh is the roughness length.
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smooth surface (lower-right corner in Figure 2) would then simply be characterized through a very small zero-plane displacement. The form of the profiles is, in general, complex. Under strongly simplifying assumptions, the profiles can nevertheless be approximated by analytical equations. Well established from theoretical and experimental studies, as well as from laboratory flow experiments, is the ‘logarithmic wind profile,’ or log-profile (eqn [4]). Strictly speaking, the log-profile is valid over only bare, flat, homogenous terrain and at a sufficiently large distance from the surface (i.e., within the inertial sublayer), and it can be described on the basis of the Monin– Obukhov similarity theory. For negligibly small d, it reads: z u z [4] ln JM uðzÞ ¼ z0 L k where u* is the ‘friction velocity’ as determined by the Reynolds stress at zr, k ¼ 0.4 is the von Kàrmàn constant, and the effect of atmospheric stability is taken into account through the socalled Obukhov length L and the associated stability function JM. In the case of a nonnegligible zero-plane displacement, z should be replaced by the reduced height z d. In practical applications, zero-plane displacement and roughness length can be determined from fitting observed wind speed profiles to eqn [4] or, alternatively, from morphometric properties of the surface. As a rule of thumb, d w 2/3 zh and z0 w 0.1 zh may be used. Within the roughness sublayer, the mean wind speed departs from the logarithmic behavior, with a strong retardation at the mean height of the roughness elements (Figure 4) due to form and viscous drag. Under special conditions, the momentum balance equation for the roughness sublayer can be solved analytically to yield an exponential function usually expressed as: z uðzÞ ¼ u ðzh Þexp a 1 [5] zh where a is a parameter that depends on the density and character of the roughness elements and is experimentally found to be in the range of 1–4. Note that while stability is a strong factor determining the shape of the wind profile away from the surface, the form, character, and distribution of roughness elements exert a much stronger influence within the roughness sublayer than stability does. For this reason, eqn [5] without stability extension provides a very good first-order approximation. Variables other than wind speed and temperature also display characteristic vertical profiles. In plant stands, the vertical distribution of net radiation depends on the albedo of the canopy, as well as on the extinction of solar radiation and the absorption and emission of thermal radiation at different levels within the canopy. Owing to the greater absorption in the visible range compared to the near-infrared range, the spectral composition of the solar radiation flux varies from the top to the bottom of a stand. Profiles of humidity and CO2 (not shown) in forest stands often display an inflection point within the canopy, as illustrated for potential temperature in Figure 4. This feature can be explained by the divergence of the relevant energy and mass fluxes, the distribution of the sources and sinks of water vapor
and CO2 (including those at ground level), and advective effects. In plant stands, turbulence statistics such as velocity variances or turbulent fluxes of sensible heat and momentum exhibit a strong reduction in magnitude from the canopy top to the ground, where very small or vanishing values are observed. The most striking feature of canopy turbulence is probably the fact that it is governed by so-called coherent structures with spatial scales on the order of the canopy height. As a consequence, the turbulent exchange of heat, moisture, or trace gases within canopies is often characterized by countergradient transport. This means that ‘K theory,’ which is based on the assumption of small dominating eddies and is a well-established concept for the inertial sublayer, is not a useful description of turbulent transport in the roughness sublayer. Owing to the rough nature of the surface, turbulent mixing is stronger in the upper part of the roughness sublayer than in the inertial sublayer. As for the fluxes of sensible and latent heat, this increase is most pronounced under near-neutral conditions. In this case, the turbulent transport just above the canopy can be up to three times larger than in the inertial sublayer, whereas for momentum the enhancement is of the order of 10%.
Comparison of Urban and Rural Microclimates The ways in which microclimates are shaped by properties of the underlying surfaces can be illustrated by contrasting rural and urban environments. Radiative energy fluxes over the urban surface are different from those found in rural areas, mainly due to enhanced aerosol load and smaller albedo in the urban environment. The latter reflects the fact that a substantial part of the shortwave incoming radiation is trapped between the buildings, heating up the surface material. During the daytime hours (Figure 5(a)), the urban environment gets more net radiative energy due to the smaller albedo. During night, on the other hand, the net radiation is typically larger over a rural than over an urban surface (Figure 5(b)) owing to differences in the longwave loss. Spatial heterogeneity in the availability of water for evapotranspiration in an urban fabric typically leads to a substantially different partitioning of the atmospheric energy fluxes across different surface types, which is best illustrated in terms of the Bowen ratio, that is, the ratio of sensible to latent heat, b ¼ QH/QE (Figure 6). For this particular case (a midlatitude European type of city structure), the turbulent flux of sensible heat (QH) dominates the latent heat flux (QE) over the urban surface (b z 2), while the situation is reversed (b z 0.5) over the nearby rural surfaces, with the suburban sites exhibiting an intermediate behavior. For all types of surfaces, the partitioning of the available energy between latent and sensible heat undergoes a pronounced daily cycle, reflecting changes in the vertical profiles of wind speed, temperature, humidity, and, in the case of the urban environment, heat storage (DQS). The characteristic energy flux partitioning seen in Figure 6 results in an enhanced near-surface temperature within an urban area that usually is referred to as the ‘urban heat island’
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Figure 6 Ternary plot contrasting atmospheric energy flux partitioning over urban, suburban, and rural sites in and around Basel, Switzerland. Data cover one summer month in 2002. Modified after Christen, A., Vogt, R., 2004. Energy and radiation balance of a central European city. International Journal of Climatology 24 (11), 1395–1421, with permission from the author.
Figure 5 (a) Average daily cycles of the radiation balance components at an urban site in the city of Basel, Switzerland (data from September 2001 to August 2002); (b) daily cycle of the corresponding urban–rural difference (DU–R) for these mean radiation fluxes (‘urban’ data are averaged over two urban sites, and ‘rural’ data are averaged over three rural sites around Basel); and (c) daily cycle of urban–rural difference in temperature (gray lines, left scale) and absolute humidity (black line, right scale). Note that DTU–R represents a measure of the so-called urban heat island (see text for details); the data represent averages from two sites (urban) and three sites (rural), respectively, and stem from one summer month of the full-year data of (a) and (b). Composed from figures in Christen, A., 2005. Atmospheric Turbulence and Surface Exchange in Urban Environments, PhD dissertation, University of Basel, Switzerland, published as stratus 11, p. 140.
(UHI). The UHI is often associated with a drier urban environment, and its strength is a strong function of time and position within the roughness sublayer (Figure 5(c)). Apart from being related to the size of the urban population (i.e., the city), the maximum strength of the UHI has been shown in other studies to be associated with geometric and surface properties of the urban environment (Figure 7). Within and above urban canopy layers, temperature, humidity, and wind speed exhibit characteristic profiles similar to those shown in Figure 4 (right) for a forest stand. These profiles are the result of turbulent exchange processes, which are strongly determined by the character of the roughness elements (form and building material) and their density and
Figure 7 Maximum heat island intensity in Canadian cities and its relation to surface properties (aspect ratio, top scale or sky-view factor, and lower scale). Redrawn after Oke, T.R., 1997. Urban environments. In: Bailey, W.G., Oke, T.R., Rouse, W.R. (Eds.). The Surface Climates of Canada. McGill-Queen’s University Press, Montreal, pp. 303–327.
height distribution. Far away from the roughness elements (i.e., within the inertial sublayer), these turbulent fluxes are essentially constant with height, and this corresponds to the situation over relatively smooth surfaces. Closer to the surface, however, the complicated distribution of sources and sinks yields more complicated profiles (Figure 8). The distribution of sources and sinks of heat and air pollutants, from traffic at the street level and chimneys from domestic heating near rooftops, suggests that in urban environments, profiles of the sensible heat flux, mean temperature, and air pollutants are less systematic than corresponding profiles of the momentum flux, for which the main sink is at ground level. Vertical variations in turbulent fluxes also affect the height distribution of other turbulence-related variables such as velocity or scalar variances. These, in turn, govern the turbulent diffusion of energy, water vapor, and air pollutants.
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Climate Change: Energy Balance Climate Models; Overview. Numerical Models: Parameterization of Physical Processes: Turbulence and Mixing. Turbulence and Mixing: Turbulent Diffusion.
Further Reading
Figure 8 Mean profiles of turbulent fluxes of momentum hu0 w0 i (left) and sensible heat hw0 q0 i (right), normalized with their respective values far from the roughness elements. In the case of the momentum flux, normalization was achieved with the square of the friction velocity to preserve the negative sign. The two gray areas indicate the height range where pronounced inflection points appear in the profiles. For both fluxes, the dashed and dotted lines represent profiles taken within the urban area, whereas the thick continuous lines refer to profiles collected in a suburban environment. Composed from figures in Christen, A., 2005. Atmospheric Turbulence and Surface Exchange in Urban Environments, PhD dissertation, University of Basel, Switzerland, published as stratus 11, p. 140.
See also: Agricultural Meteorology and Climatology. Boundary Layer (Atmospheric) and Air Pollution: Coherent Structures; Complex Terrain; Modeling and Parameterization; Overview; Stably Stratified Boundary Layer; Surface Layer. Climate and
Arya, P.S., 2001. Introduction to micrometeorology. In: Holton, J.R. (Ed.), International Geophysics Series, second ed. vol. 71. Academic Press, San Diego, CA,. p. 420. Bailey, W.G., Oke, T.R., Rouse, W.R., 1997. The Surface Climates of Canada. McGillQueen’s University Press, Montreal, p. 369. Brutsaert, W.H., 1982. Evaporation into the Atmosphere. Reidel, Dordrecht, p. 299. Cermak, J.E., Davenport, A.G., Plate, E.J., Viegas, D.X., 1995. Wind climates in cities. In: NATO ASI Series E: Applied Sciences, vol. 27. Kluwer Academic Publishers, Dordrecht, p. 771. Garratt, J.R., 1992. The Atmospheric Boundary Layer. Cambridge University Press, Montreal, p. 316. Geiger, R., Aron, R.H., Todhunter, P., 2009. The Climate Near the Ground, seventh ed. Rowman & Littlefield Publishers, Lanham, MD, p. 623. Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology, second ed. Cambridge University Press, Cambridge, p. 428. Monteith, J.L., Unsworth, M.H., 2008. Principles of Environmental Physics, third ed. Academic Press, Burlington, VT, p. 418. Oke, T.R., 1987. Boundary Layer Climates, second ed. Methuen, London, p. 372. Rosenberg, N.J., Blad, B.L., Verma, S.B., 1983. Microclimate: The Biological Environment, second ed. Wiley Interscience, New York, p. 495.
Synopsis Microclimatology is concerned with the study of the processes by which the local surface properties affect the lowest layer of the atmosphere. Often the latter refers to the so-called roughness sublayer, but in some cases attention is more properly limited to the so-called canopy layer or then, conversely, the whole surface layer. Microclimates are described in terms of climatic variables, their temporal and vertical variability, as established by the balance equations that govern the exchange of radiation, heat, water, and other atmospheric constituents.
Introduction
characteristic temporal patterns observed in microclimatic records.
The word ‘climate’ stems from the Greek klíma (slope, zone), with its roots in klínein (to slope), and originally denoted ‘a zone of equal latitude,’ thus referring to the effects of latitude on the availability of solar energy. In fact, on a global scale the climate is above all determined by the latitudinal and seasonal distribution of incoming solar radiation as given by Earth’s orbital parameters. On very small scales, however, the climate is primarily shaped by the local surface properties that control the exchange of radiation, energy, momentum, and water between the ground and the atmosphere. The microclimate of a particular location can hence be defined as the collection of statistics describing the thermal and dynamical conditions prevailing in the atmospheric layer directly affected by the underlying surface. Accordingly, ‘descriptive microclimatology,’ can be identified as the study of the long-term average and typical variability of climate variables in the lowest layer of the atmosphere, while ‘physical microclimatology’ can be defined as the study of the processes by which the lowest layer of the atmosphere responds to surface boundary conditions. As is customary in climatology, the various aspects that concur in creating the microclimate of a particular location are identified with a number of so-called climate variables. Common climate variables include radiation, temperature, humidity, wind speed, and pressure (density), but, depending on the research focus, other variables need to be taken into account. For example, the health and comfort of the everincreasing number of people living in cities are directly related to the concentration and distribution of air pollutants, which are therefore required to characterize the microclimate of these particular environments. The surface properties determining a microclimate are seldom constant in time. Long-term variations may arise naturally or as a consequence of human-induced changes in land use. At the seasonal scale, variations in surface properties may be brought about by the presence of a snow cover or through the life cycle of plants. Short-term variations may, for example, be caused by the dynamic effects of the wind on the structure of the surface elements. Ultimately, it is this variability in surface properties that, along with the variability of the large-scale atmospheric forcing, is responsible for the
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The Lowest Layers of the Atmosphere The atmospheric layer affected by the local surface properties is called the ‘planetary boundary layer’ (PBL). It has a characteristic depth (zi) on the order of 1000 m and can be divided into an upper or outer layer (the uppermost 90%) and an inner or surface layer (SL) (the lowest 10%) (Figure 1). However, a direct influence of the surface characteristics on the atmospheric state is observed only in the lowest part of the SL, in the immediate vicinity of the roughness elements. If this layer of influence has any discernible thickness, it is because of a nonnegligible vertical extension of the ‘roughness elements’ (stones, vegetation, tress, and buildings). Therefore, this layer is usually called the ‘roughness sublayer.’ The upper part of the SL is then referred to as the ‘inertial sublayer.’ Over a relatively smooth surface such as short grass or sand, the roughness sublayer becomes very thin and the inertial sublayer is often associated with the entire SL (Figure 1). Based on these considerations, ‘microclimatology’ can also be defined as the study of the climatic state of the roughness sublayer or specific entities therein, even though the notion is most often extended to the examination of the entire SL or even PBL. Micrometeorology is then the study of the dynamics and thermodynamics of the SL or PBL.
The Roughness Sublayer In the roughness sublayer, the flow is affected by the individual roughness elements and hence is fully three-dimensional in nature. The upper boundary of the roughness sublayer, zr, is the level at which the horizontal variability associated with the roughness elements vanishes and the flow properties become horizontally homogeneous. Properly scaled ‘profiles’ of either mean flow characteristics or turbulence statistics will then merge to one curve whose shape is characteristic for the underlying surface. The depth of the roughness sublayer depends on the height and distribution of the roughness elements. For most surfaces, 2zh < zr < 5zh covers the range of estimates, where zh is the average height of roughness elements.
Encyclopedia of Atmospheric Sciences 2nd Edition, Volume 1
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Figure 1 Conceptual sketch and terminology for the lowest layers of the atmosphere over a rough surface. Note the logarithmic height scale. Level zi refers to the boundary layer height, zr to the height of the roughness sublayer, and zh to the (average) height of roughness elements.
The Canopy Layer The lowest part of the roughness sublayer is the canopy layer. It ranges from the surface to zh. In this layer, form (or pressure) drag and viscous drag on any individual roughness element are both significant and lead to a retardation of the flow. In addition, the material and orientation of the obstacles give rise to large variations in the energy balance, primarily through variations in the radiation balance, and also as a result of the distribution of sources and sinks of sensible heat, water vapor, or trace gases. Figure 2 shows the height ranges covered by the roughness sublayer and its lower part, the canopy layer, in dimensionless
Figure 2 Sketch of the vertical extension of the various layers over rough surfaces and their variation with the nondimensional quantities z/zh and zi/zh. Here, z denotes the (physical) height, zi refers to the boundary layer height, and zh is the (average) height of roughness elements. A value of zr/zh ¼ 3 is assumed for the height of the roughness sublayer. The arrows labeled with ‘city,’ ‘forest,’ ‘crop,’ and ‘short grass’ are based on typical values for the height of the roughness elements zh and the boundary layer height zi. Redrawn from Rotach, M.W., 1999. On the urban roughness sublayer. Atmospheric Environment 33, 4001–4008.
form. Arrows indicate how surfaces covered with short grass, crops, trees, and houses, respectively, fit into this scheme. It can be seen that the vertical range, to which the study of microclimate is confined, can extend up to several tens of meters or more in the case of an urban surface. However, in the case of a shallow boundary layer (small zi and large roughness elements), no inertial sublayer may be present at all.
Internal Boundary Layers The above considerations are valid for horizontally homogenous surfaces. In the presence of a pronounced small-scale variability of surface properties, internal boundary layers may form downwind of each major change in the surface characteristics. Internal boundary layers may be ‘thermal’ if they are primarily prompted by an abrupt change in surface temperature, as for example across a shoreline. Alternatively, if changes are primarily in the surface roughness, internal boundary layers are called ‘mechanical.’ Most common is, of course, the development of combined thermal and mechanical internal boundary layers. Internal boundary layers increase in depth with distance downstream from the surface discontinuities causing their development. Within a developing internal boundary layer, profiles of climate variables exhibit a continuous transition from conditions adjusted to the new surface characteristics close to the ground, to conditions still nearly in equilibrium with the conditions upstream of the leading edge. At still greater heights, horizontal gradients associated with surface heterogeneities become negligibly small due to the effects of turbulent mixing. The concept of a blending height has been introduced to denote the level at which the flow becomes independent of the local surface condition. In its strictest sense, the study of microclimate over heterogeneous surfaces is then confined to the airspace below the blending height.
Surface Characteristics The surface characteristics that determine the microclimate can be organized according to which aspect of the
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atmospheric dynamics and thermodynamics they affect for the most part: l
l
l
l
l
l
‘Radiative properties’ determine the radiation budget. These are the albedo (a), or surface reflectivity in the shortwave band of the radiation spectrum; the emissivity of the effective surface (ε); and the geometric properties that influence the receipt and loss of radiation, such as the skyview factor in the case of an urban surface or the canopy extinction coefficient (ke) in the case of a vegetated surface. ‘Aerodynamic properties’ determine the momentum budget. These are the surface roughness length (z0), the zero-plane displacement (d), and the drag coefficient (Cd). ‘Thermal properties’ determine the heat flow in the underlying substrate–roughness elements. These are the thermal conductivity (kg), the heat capacity (cg), and the thermal diffusivity (lg ¼ kg/cg). In soils, all of these properties strongly depend on the soil water content (SWC). ‘Soil hydraulic properties and vegetation characteristics’ affect soil moisture, the availability of water for evaporation and transpiration, and hence the partitioning between the turbulent energy fluxes and the conductive ground heat flux in the surface energy balance. ‘Vegetation properties’ control the distribution of radiation and the transfer of water vapor and trace gases within a canopy. In many modeling studies, these are primarily the Leaf Area Index (LAI) and stomatal conductance (gst), but they should more properly encompass all botanical, physiological, and geometric characteristics as well as species composition. ‘Water properties’ control the thermal state and the phase transitions in water bodies, in particular during the seasonal development of snow covers and ice bodies at high latitudes and elevated altitudes. These include, among others, the volumetric heat capacities of water (cw) and ice (ci), and the latent heat of fusion (Lf) and vaporization (Lv).
Although, in general, all properties concur in determining the local microclimate, their relative importance may vary
depending on the specific circumstances. Table 1 provides examples of parameters that are particularly significant in relation to specific surface types and situations. In many instances, the effective surface cannot be treated as static but undergoes dynamic changes. The examples in Table 1 emphasize the dynamic effects of the wind, either in the case of bending roughness elements (vegetated surfaces) or in the presence of water (waves) and snow (drift) surfaces. In complex terrain, the topographic characteristics that control the development of ‘mesoscale circulation systems,’ such as land and sea breezes or mountain and valley winds, need also to be taken into account to understand the nature of microclimates.
The Budget Equations The main role of the surface properties discussed in this article is to regulate the exchange of radiation, heat, and mass (water and carbon or other trace gases) between the ground and the atmosphere, establishing corresponding balances defined by the following budget equations: l
l
l
Radiation: Q ¼ KY K[ þ LY L[
[1]
Q ¼ QE þ QH þ QG þ DQS
[2]
Energy:
Water (mass): P ¼ E þ R þ In þ DW
[3]
In these equations, Q* denotes the net (all-wave) radiation flux at the surface; KY and K[ are the incoming and
Table 1 Relevant microclimatological parameters for broad categories of characteristic surfaces and for selected aspects of the establishment of local microclimates Surface type
Relevant parameters
Particular aspects
Bare soil
a, ε, z0, cg(SWC), kg(SWC)
Short vegetation (crops)
a, ε, z0, d, LAI, gst, ke
Tall vegetation (forest)
a, ε, z0, d, LAI, gst, ke
Water
a, z0, Cd
Snow and ice
a, ε, z0, cw, ci, Lf, Lv
Urban
a, ε, z0, d, Cd, SVF
Usually considered the simplest case of surfaces, providing in many cases a reference; soil thermal properties depend on SWC, which may also affect the albedo. Flexible roughness elements; zero-plane displacement is relatively small and in many cases negligible; in crops there is pronounced seasonal development, with the growth stage determining the LAI and eventually the exchange of radiation, energy, and water. Strong dynamic interactions with the atmospheric flow; often nonuniform vertical distribution of leaf density; importance of the storage terms in the balance equations. Albedo is a function of solar elevation (diurnal variations) and momentum exchange, as controlled by z0 or Cd; strongly dependent on wind regime and resulting wave height (Charnock’s roughness length model). Albedo depends on snow or ice age (seasonal variability) and is a function of solar elevation (diurnal variability); especially with low snow densities, the surface roughness of snow covers depends on drift conditions; melting leads to well-defined surface temperature. Stiff roughness elements; strong influence of the thermal properties of building material; geometry and distribution of roughness elements are of paramount importance for radiation, energy, and momentum exchange.
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Figure 3 Energy fluxes appearing in the energy budget equation for a layer of finite thickness. Subscripts g and h refer to the ground level and the average canopy height zh, respectively. QA denotes the contribution from horizontal advection to energy storage (DQS) in the volume. The latter is given by the divergence of all vertical and horizontal fluxes.
outgoing shortwave radiation fluxes, respectively; LY and L[ are the incoming and outgoing longwave radiation fluxes, respectively; QE and QH are the turbulent fluxes of latent and sensible heat, respectively; QG is the conductive heat flux to the substrate; DQS is the change in heat storage associated with the divergence of horizontal or vertical energy fluxes that arise from the finite size of the volume under consideration; P is the water input through precipitation; E is the loss of water vapor through evapotranspiration; R is the surface runoff; In is the vertical infiltration into the ground; and DW is the change in water storage. Moreover, on the right-hand side of the energy and water budget equations, fluxes directed away (toward) the surface are considered positive (negative). In the presence of snow and ice, transitions between the solid and liquid phases (melting and freezing) significantly contribute to both the energy and mass budgets. In urban environments, anthropogenic heat release also adds another contribution to the energy budget. In the case of vegetated surfaces, the net photosynthetic heat uptake or release appears as an additional term in the energy budget equation. Furthermore, in this latter case, the water budget equation needs to be modified to account for the interception of precipitation and the buildup of an interception store, from which water can evaporate. Another important remark should be made in relation to the budget equations. Although it is customary to refer to
eqns [1]–[3] as the ‘surface balance equations,’ it is essential to recall that in most cases they are established with respect to a layer of finite thickness (Figure 3). This makes it necessary to include the storage terms that account for changes in the energy and mass content of this layer (DQS and DW, respectively). The storage terms become particularly important when dealing with the microclimates of vegetative canopies or urban areas.
Profiles of Mean Quantities and Turbulence Characteristics One of the fundamental characteristics of climate variables in the atmospheric layer directly affected by the surface is their pronounced vertical variability. The associated ‘vertical profiles’ again depend in a systematic way on the surface properties, displaying temporal variations in correspondence to the time scales that characterize the governing budget equations. Figure 4 exemplarily shows daytime profiles of mean wind speed and potential temperature above a bare soil and a forest. In the panel on the right-hand side of the figure, d þ z0 refers to the height above which the shapes of the profiles start to become comparable to those observed over a bare soil. This feature of the profiles implies that they can be formulated using z0 and d as characteristic length scales. A ‘bare soil’ or relatively
Figure 4 Typical daytime mean vertical profiles of mean wind speed (u) and potential temperature (q) over a bare soil (left) and a vegetated surface (right). On the right-hand side of the figure, zh denotes the average height of the canopy, d w 2/3zh is the zero-plane displacement, and z0 w 0.1zh is the roughness length.
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smooth surface (lower-right corner in Figure 2) would then simply be characterized through a very small zero-plane displacement. The form of the profiles is, in general, complex. Under strongly simplifying assumptions, the profiles can nevertheless be approximated by analytical equations. Well established from theoretical and experimental studies, as well as from laboratory flow experiments, is the ‘logarithmic wind profile,’ or log-profile (eqn [4]). Strictly speaking, the log-profile is valid over only bare, flat, homogenous terrain and at a sufficiently large distance from the surface (i.e., within the inertial sublayer), and it can be described on the basis of the Monin– Obukhov similarity theory. For negligibly small d, it reads: z u z [4] ln JM uðzÞ ¼ z0 L k where u* is the ‘friction velocity’ as determined by the Reynolds stress at zr, k ¼ 0.4 is the von Kàrmàn constant, and the effect of atmospheric stability is taken into account through the socalled Obukhov length L and the associated stability function JM. In the case of a nonnegligible zero-plane displacement, z should be replaced by the reduced height z d. In practical applications, zero-plane displacement and roughness length can be determined from fitting observed wind speed profiles to eqn [4] or, alternatively, from morphometric properties of the surface. As a rule of thumb, d w 2/3 zh and z0 w 0.1 zh may be used. Within the roughness sublayer, the mean wind speed departs from the logarithmic behavior, with a strong retardation at the mean height of the roughness elements (Figure 4) due to form and viscous drag. Under special conditions, the momentum balance equation for the roughness sublayer can be solved analytically to yield an exponential function usually expressed as: z uðzÞ ¼ u ðzh Þexp a 1 [5] zh where a is a parameter that depends on the density and character of the roughness elements and is experimentally found to be in the range of 1–4. Note that while stability is a strong factor determining the shape of the wind profile away from the surface, the form, character, and distribution of roughness elements exert a much stronger influence within the roughness sublayer than stability does. For this reason, eqn [5] without stability extension provides a very good first-order approximation. Variables other than wind speed and temperature also display characteristic vertical profiles. In plant stands, the vertical distribution of net radiation depends on the albedo of the canopy, as well as on the extinction of solar radiation and the absorption and emission of thermal radiation at different levels within the canopy. Owing to the greater absorption in the visible range compared to the near-infrared range, the spectral composition of the solar radiation flux varies from the top to the bottom of a stand. Profiles of humidity and CO2 (not shown) in forest stands often display an inflection point within the canopy, as illustrated for potential temperature in Figure 4. This feature can be explained by the divergence of the relevant energy and mass fluxes, the distribution of the sources and sinks of water vapor
and CO2 (including those at ground level), and advective effects. In plant stands, turbulence statistics such as velocity variances or turbulent fluxes of sensible heat and momentum exhibit a strong reduction in magnitude from the canopy top to the ground, where very small or vanishing values are observed. The most striking feature of canopy turbulence is probably the fact that it is governed by so-called coherent structures with spatial scales on the order of the canopy height. As a consequence, the turbulent exchange of heat, moisture, or trace gases within canopies is often characterized by countergradient transport. This means that ‘K theory,’ which is based on the assumption of small dominating eddies and is a well-established concept for the inertial sublayer, is not a useful description of turbulent transport in the roughness sublayer. Owing to the rough nature of the surface, turbulent mixing is stronger in the upper part of the roughness sublayer than in the inertial sublayer. As for the fluxes of sensible and latent heat, this increase is most pronounced under near-neutral conditions. In this case, the turbulent transport just above the canopy can be up to three times larger than in the inertial sublayer, whereas for momentum the enhancement is of the order of 10%.
Comparison of Urban and Rural Microclimates The ways in which microclimates are shaped by properties of the underlying surfaces can be illustrated by contrasting rural and urban environments. Radiative energy fluxes over the urban surface are different from those found in rural areas, mainly due to enhanced aerosol load and smaller albedo in the urban environment. The latter reflects the fact that a substantial part of the shortwave incoming radiation is trapped between the buildings, heating up the surface material. During the daytime hours (Figure 5(a)), the urban environment gets more net radiative energy due to the smaller albedo. During night, on the other hand, the net radiation is typically larger over a rural than over an urban surface (Figure 5(b)) owing to differences in the longwave loss. Spatial heterogeneity in the availability of water for evapotranspiration in an urban fabric typically leads to a substantially different partitioning of the atmospheric energy fluxes across different surface types, which is best illustrated in terms of the Bowen ratio, that is, the ratio of sensible to latent heat, b ¼ QH/QE (Figure 6). For this particular case (a midlatitude European type of city structure), the turbulent flux of sensible heat (QH) dominates the latent heat flux (QE) over the urban surface (b z 2), while the situation is reversed (b z 0.5) over the nearby rural surfaces, with the suburban sites exhibiting an intermediate behavior. For all types of surfaces, the partitioning of the available energy between latent and sensible heat undergoes a pronounced daily cycle, reflecting changes in the vertical profiles of wind speed, temperature, humidity, and, in the case of the urban environment, heat storage (DQS). The characteristic energy flux partitioning seen in Figure 6 results in an enhanced near-surface temperature within an urban area that usually is referred to as the ‘urban heat island’
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Figure 6 Ternary plot contrasting atmospheric energy flux partitioning over urban, suburban, and rural sites in and around Basel, Switzerland. Data cover one summer month in 2002. Modified after Christen, A., Vogt, R., 2004. Energy and radiation balance of a central European city. International Journal of Climatology 24 (11), 1395–1421, with permission from the author.
Figure 5 (a) Average daily cycles of the radiation balance components at an urban site in the city of Basel, Switzerland (data from September 2001 to August 2002); (b) daily cycle of the corresponding urban–rural difference (DU–R) for these mean radiation fluxes (‘urban’ data are averaged over two urban sites, and ‘rural’ data are averaged over three rural sites around Basel); and (c) daily cycle of urban–rural difference in temperature (gray lines, left scale) and absolute humidity (black line, right scale). Note that DTU–R represents a measure of the so-called urban heat island (see text for details); the data represent averages from two sites (urban) and three sites (rural), respectively, and stem from one summer month of the full-year data of (a) and (b). Composed from figures in Christen, A., 2005. Atmospheric Turbulence and Surface Exchange in Urban Environments, PhD dissertation, University of Basel, Switzerland, published as stratus 11, p. 140.
(UHI). The UHI is often associated with a drier urban environment, and its strength is a strong function of time and position within the roughness sublayer (Figure 5(c)). Apart from being related to the size of the urban population (i.e., the city), the maximum strength of the UHI has been shown in other studies to be associated with geometric and surface properties of the urban environment (Figure 7). Within and above urban canopy layers, temperature, humidity, and wind speed exhibit characteristic profiles similar to those shown in Figure 4 (right) for a forest stand. These profiles are the result of turbulent exchange processes, which are strongly determined by the character of the roughness elements (form and building material) and their density and
Figure 7 Maximum heat island intensity in Canadian cities and its relation to surface properties (aspect ratio, top scale or sky-view factor, and lower scale). Redrawn after Oke, T.R., 1997. Urban environments. In: Bailey, W.G., Oke, T.R., Rouse, W.R. (Eds.). The Surface Climates of Canada. McGill-Queen’s University Press, Montreal, pp. 303–327.
height distribution. Far away from the roughness elements (i.e., within the inertial sublayer), these turbulent fluxes are essentially constant with height, and this corresponds to the situation over relatively smooth surfaces. Closer to the surface, however, the complicated distribution of sources and sinks yields more complicated profiles (Figure 8). The distribution of sources and sinks of heat and air pollutants, from traffic at the street level and chimneys from domestic heating near rooftops, suggests that in urban environments, profiles of the sensible heat flux, mean temperature, and air pollutants are less systematic than corresponding profiles of the momentum flux, for which the main sink is at ground level. Vertical variations in turbulent fluxes also affect the height distribution of other turbulence-related variables such as velocity or scalar variances. These, in turn, govern the turbulent diffusion of energy, water vapor, and air pollutants.
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Climate Change: Energy Balance Climate Models; Overview. Numerical Models: Parameterization of Physical Processes: Turbulence and Mixing. Turbulence and Mixing: Turbulent Diffusion.
Further Reading
Figure 8 Mean profiles of turbulent fluxes of momentum hu0 w0 i (left) and sensible heat hw0 q0 i (right), normalized with their respective values far from the roughness elements. In the case of the momentum flux, normalization was achieved with the square of the friction velocity to preserve the negative sign. The two gray areas indicate the height range where pronounced inflection points appear in the profiles. For both fluxes, the dashed and dotted lines represent profiles taken within the urban area, whereas the thick continuous lines refer to profiles collected in a suburban environment. Composed from figures in Christen, A., 2005. Atmospheric Turbulence and Surface Exchange in Urban Environments, PhD dissertation, University of Basel, Switzerland, published as stratus 11, p. 140.
See also: Agricultural Meteorology and Climatology. Boundary Layer (Atmospheric) and Air Pollution: Coherent Structures; Complex Terrain; Modeling and Parameterization; Overview; Stably Stratified Boundary Layer; Surface Layer. Climate and
Arya, P.S., 2001. Introduction to micrometeorology. In: Holton, J.R. (Ed.), International Geophysics Series, second ed. vol. 71. Academic Press, San Diego, CA,. p. 420. Bailey, W.G., Oke, T.R., Rouse, W.R., 1997. The Surface Climates of Canada. McGillQueen’s University Press, Montreal, p. 369. Brutsaert, W.H., 1982. Evaporation into the Atmosphere. Reidel, Dordrecht, p. 299. Cermak, J.E., Davenport, A.G., Plate, E.J., Viegas, D.X., 1995. Wind climates in cities. In: NATO ASI Series E: Applied Sciences, vol. 27. Kluwer Academic Publishers, Dordrecht, p. 771. Garratt, J.R., 1992. The Atmospheric Boundary Layer. Cambridge University Press, Montreal, p. 316. Geiger, R., Aron, R.H., Todhunter, P., 2009. The Climate Near the Ground, seventh ed. Rowman & Littlefield Publishers, Lanham, MD, p. 623. Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology, second ed. Cambridge University Press, Cambridge, p. 428. Monteith, J.L., Unsworth, M.H., 2008. Principles of Environmental Physics, third ed. Academic Press, Burlington, VT, p. 418. Oke, T.R., 1987. Boundary Layer Climates, second ed. Methuen, London, p. 372. Rosenberg, N.J., Blad, B.L., Verma, S.B., 1983. Microclimate: The Biological Environment, second ed. Wiley Interscience, New York, p. 495.