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Virtual temperature

Virtual temperature is a fictitious temperature in atmospheric thermodynamics that represents the temperature a sample of dry air would need to achieve the same as a given sample of moist air at the same total and moisture content. It accounts for the lower molecular weight of water vapor compared to dry air, making moist air less dense than dry air at the same actual and , and thus virtual temperature is always slightly higher than the actual for humid conditions. The concept derives from the applied to moist air, where total pressure p = p_d + e (dry air partial pressure plus partial pressure) and total density \rho = \rho_d + \rho_v + \rho_l (dry air, vapor, and liquid water densities), leading to the defining relation p = \rho R_d T_v, with R_d as the for dry air. A common approximation for the virtual temperature T_v is T_v \approx T (1 + 0.608 q), where T is the actual temperature in and q is the water vapor mixing ratio (mass of vapor per mass of dry air); this factor 0.608 arises from the ratio of gas constants for and dry air (\epsilon \approx 0.622). For more precision including liquid water, the formula extends to T_v = T \frac{1 + q/\epsilon}{1 + q + l}, where l is the liquid water mixing ratio. In , virtual temperature is essential for evaluating air parcel and static , as it allows the use of dry-air equations for moist conditions in calculations like convective available potential energy (), which is critical for forecasting development. It also facilitates of atmospheric profiles, such as via radio acoustic sounding systems (RASS), and is used in modeling turbulent fluxes and hydrostatic balance in prediction models. By simplifying the treatment of moisture's effects, virtual temperature enhances accuracy in , numerical , and climate simulations without altering the fundamental dry-air framework.

Overview

Definition

Virtual temperature, denoted T_v, is defined as the temperature that a theoretical parcel of dry air would need to possess in order to have the same total and as an actual parcel of moist air at the same location. This construct arises in to account for the effects of on air while allowing moist air behavior to be approximated using dry air equations. The definition presupposes the ideal gas law for dry air, expressed as p = \rho R_d T, where p is the total pressure, \rho is the density, R_d is the specific gas constant for dry air (approximately 287 J kg⁻¹ K⁻¹), and T is the temperature. In this framework, T_v adjusts the temperature term to reflect the lower density of moist air due to the lighter molecular weight of water vapor compared to dry air constituents. In unsaturated moist air, T_v exceeds the actual temperature T because the presence of water vapor reduces the parcel's density relative to dry air at the same T and p. Conversely, in saturated air with suspended liquid water droplets (known as liquid water loading), the added mass of these denser droplets increases the overall density, resulting in T_v being lower than T. Virtual temperature is measured in kelvin and functions as a scalar multiplier that can substitute for actual temperature in thermodynamic relations originally formulated for dry air.

Significance

The serves a critical purpose in by permitting the dry-air to be applied to moist air through a simple scaling, which streamlines hydrostatic balance computations and thermodynamic analyses in and climate models. This adjustment accounts for the lower of compared to dry air, avoiding the need for separate moist-air formulations and reducing in regions with significant . The concept of virtual temperature was first introduced by Cato Guldberg and Henrik Mohn in 1876. It has since been used to overcome shortcomings in representations of moist air dynamics, as exemplified in D. K. Lilly's 1968 analysis of cloud-topped mixed layers, where virtual temperature facilitated more accurate modeling of and under strong inversions. Without incorporating virtual temperature, miscalculations in humid environments can lead to errors in pressure-to-height conversions of up to 10-20 meters across tropospheric layers, particularly in the where moisture content is high. A key impact of virtual temperature lies in its representation of the vapor , which introduces an approximate 1 K warming in the tropical relative to actual ; this enhancement promotes greater in moist air parcels, thereby intensifying convective processes and contributing to increased clear-sky by about 1 W m⁻² globally. Such effects help stabilize the tropical through negative feedbacks that mitigate excessive warming in dry subsiding regions.

Physical Principles

Air Density and Water Vapor Effects

The density of moist air arises from its composition as a mixture of dry air and water vapor, treated as ideal gases following Dalton's law of partial pressures. According to this law, the total atmospheric pressure p equals the sum of the partial pressure of dry air p_d and the vapor pressure e: p = p_d + e. This partial pressure framework allows the densities of each component to be calculated separately using the ideal gas law. The molecular weight of dry air is approximately 29 g/mol, primarily from (28 g/mol) and oxygen (32 g/mol), whereas has a lower molecular weight of 18 g/mol. The total of moist air \rho is thus the sum of the dry air \rho_d and the \rho_v: \rho = \rho_d + \rho_v. Since molecules are lighter than the average dry air molecules they displace, the presence of reduces the overall mass per unit volume, making moist air less dense than dry air at the same and . This density reduction stems from variations in the ideal gas law for moist air. The specific gas constant for dry air is R_d \approx 287 J kg⁻¹ K⁻¹, while for water vapor it is R_v \approx 461 J kg⁻¹ K⁻¹, reflecting the inverse relationship with molecular weight. The effective gas constant R for moist air can be expressed as R = R_d \left[1 - \frac{e}{p} (1 - \epsilon)\right]^{-1}, where \epsilon = 0.622 is the ratio of the molecular weight of water vapor to dry air (\epsilon = M_v / M_d). At constant temperature T and total pressure p, the higher effective R causes moist air to occupy a greater volume than dry air, further lowering its density by replacing heavier dry air molecules with lighter water vapor ones. In humid regions like the , where mixing ratios can exceed 20 g kg⁻¹, this effect becomes notable; for instance, at 30°C and a mixing ratio of 20 g kg⁻¹, the of moist air is reduced by approximately 1.2% compared to dry air at the same conditions. Overall, reductions reach up to 2-3% in highly saturated tropical air, enhancing and influencing atmospheric processes. This physical mechanism underpins the virtual temperature concept, which equates the of moist air to that of dry air at an adjusted .

Vapor Buoyancy Mechanism

In the atmosphere, the buoyancy acceleration of a rising air parcel is determined by b = g \frac{\Delta \rho}{\rho}, where g is the , \Delta \rho is the density difference between the parcel and its , and \rho is the environmental . This acceleration drives vertical motion, with positive occurring when the parcel density is lower than the surrounding air. Water contributes to this by reducing the overall of the moist parcel relative to dry air at the same and , as its molecular weight (18 ) is lower than that of dry air (29 ), thereby enhancing the ascent rate compared to an equivalent dry parcel. The vapor effect, quantified through , provides an equivalent perturbation that amplifies in moist air. For a mixing ratio of 10 g/kg, this effect corresponds to roughly 1-2 of warming in typical tropospheric conditions (around 280-300 ), promoting stronger updrafts in moist convective processes by making vapor-laden parcels effectively warmer and lighter. This dynamic enhancement is particularly pronounced in regions with high , where even modest increases in mixing ratio can significantly boost convective vigor. A key aspect of this mechanism is its dependence on the phase of water in the parcel. During unsaturated ascent, the virtual temperature directly increases owing to the low of alone. However, once occurs and forms clouds, the added mass of liquid water droplets (liquid loading) increases the parcel's , often counteracting or reversing the vapor-induced gain and potentially slowing or inhibiting further ascent. This mechanism also influences Earth's global energy budget, particularly in the . By elevating the virtual temperature in moist regions and inducing compensatory warming in adjacent drier columns to maintain hydrostatic balance, the vapor buoyancy effect enhances clear-sky by approximately 1-3 W/m², providing a stabilizing that increases as surface temperatures rise.

Formulation

Derivation

The derivation of the virtual temperature begins with the equation of state for moist air, treated as an mixture of air and under the assumptions of and of s. The of air is p_d = p - e, where p is the total and e is the . The density of air is given by \rho_d = \frac{p_d}{R_d T} = \frac{p - e}{R_d T}, where R_d is the specific for air and T is the actual temperature in . Similarly, the density of is \rho_v = \frac{e}{R_v T}, with R_v as the specific for . The total density \rho of unsaturated moist air (neglecting liquid water) is then \rho = \rho_d + \rho_v = \frac{p - e}{R_d T} + \frac{e}{R_v T}.[22] The virtual temperature T_v is defined such that the moist air equals that of dry air at the same total pressure p and T_v, using the dry air : \rho = \frac{p}{R_d T_v}.[22] Equating the two expressions for \rho, \frac{p}{R_d T_v} = \frac{p - e}{R_d T} + \frac{e}{R_v T}. Multiplying through by R_d T yields \frac{p T}{T_v} = (p - e) + e \frac{R_d}{R_v}. The of gas constants is \varepsilon = \frac{R_d}{R_v} \approx 0.622, derived from the molar masses of dry air (M_d \approx 28.97 g/mol) and (M_v = 18 g/mol) via \varepsilon = \frac{M_v}{M_d}, since R_d = \frac{R^*}{M_d} and R_v = \frac{R^*}{M_v} with R^* the universal . Substituting gives \frac{p}{T_v} = \frac{p - e(1 - \varepsilon)}{T}, and solving for T_v produces the exact formula T_v = \frac{T}{1 - \frac{e}{p} (1 - \varepsilon)}.[22] This derivation assumes ideal gas behavior for both components, negligible liquid water content (valid for unsaturated air), and that all constituents share the same T. It is applicable below the homopause (approximately 90 km altitude) where dry air is well-mixed.

Approximate Expressions

In , linear approximations for virtual temperature simplify computations by relating it directly to the actual air temperature and a measure of , bypassing the need for precise calculations. A standard form uses specific humidity q (in kg/kg):
T_v \approx T (1 + 0.608 q),
valid for q < 0.02 kg/kg, which encompasses most tropospheric scenarios where moisture content is moderate. This expression assumes small perturbations from dry air conditions and leverages the for moist air.
The coefficient 0.608 arises from the physical properties of air components, specifically (1 - \epsilon)/\epsilon \approx 0.608, where \epsilon = 0.622 is the ratio of the molecular weight of water vapor to dry air (or equivalently, the ratio of their specific gas constants). This approximation holds under the condition of small e/p, the ratio of vapor pressure to total pressure. For cases where mixing ratio w (in g/kg) is the available humidity metric, equivalent approximations are:
T_v \approx T + \frac{w}{6}
(with T and T_v in °C), or in Kelvin,
T_v \approx T \left(1 + 0.608 \frac{w}{1000}\right).
These derive from the specific humidity form by noting w \approx 1000 q for low moisture levels, facilitating practical use in field measurements or models.
These linear forms yield errors below 0.5 in typical tropospheric conditions (e.g., w < 20 g/kg), as higher-order terms in the are negligible; however, inaccuracies grow in extreme exceeding these limits. They prove valuable for rapid assessments in analyses or forecasting tools lacking full thermodynamic data.

Virtual Potential Temperature

Virtual potential temperature, denoted \theta_v, is defined as the potential temperature derived from the virtual temperature T_v rather than the actual temperature T. Specifically, \theta_v = \theta \times (T_v / T), where \theta is the dry potential temperature given by \theta = T (p_0 / p)^{R_d / C_p}, p_0 is the reference pressure (typically 1000 hPa), p is the pressure, R_d is the specific gas constant for dry air, and C_p is the specific heat capacity of dry air at constant pressure. An approximate form is \theta_v \approx \theta (1 + 0.608 q), where q is the water vapor mixing ratio (kg/kg); this approximation holds for typical atmospheric conditions in unsaturated moist air. In unsaturated moist air, \theta_v is conserved during adiabatic processes, such as vertical ascent or descent of an air parcel up to the lifting condensation level. Unlike virtual temperature T_v, which depends on and is not conserved in vertical motion, \theta_v remains constant under adiabatic conditions, providing a height-independent measure of potential. This property makes \theta_v valuable in and convective parcel , where it helps assess the potential for atmospheric without effects. The conservation of \theta_v applies only to unsaturated conditions, as condensation releases latent heat and deviates from dry adiabatic behavior. Parcel theory applications of \theta_v also assume no entrainment of environmental air, which can dilute buoyancy in real updrafts.

Density Temperature

Density temperature, denoted as T_\rho, is defined as the temperature that dry air would need to have in order to match the density of a moist air parcel containing both water vapor and condensed phases such as liquid droplets or ice crystals, at the same pressure. This concept extends the virtual temperature T_v by incorporating the mass loading effect of non-gaseous water substances. The formulation is given by T_\rho = T \frac{1 + w / \epsilon}{1 + w_T}, where T is the actual temperature of the moist air, w is the water vapor mixing ratio (kg/kg), \epsilon = 0.622 is the ratio of the gas constants for dry air and water vapor, and w_T = w + w_L + w_I is the total water mixing ratio, with w_L and w_I representing the liquid water and ice mixing ratios, respectively. In unsaturated air, where w_L = w_I = 0, T_\rho approximates T_v. The primary purpose of density temperature is to correct for the increased density caused by condensed water phases, which are denser than an equivalent mass of and thus reduce the buoyancy of cloudy air parcels compared to what virtual temperature alone would predict. Cloud droplets and ice particles add mass without contributing to the gas-phase , leading to a heavier parcel that sinks more readily; this loading effect is particularly significant in precipitating clouds, where T_\rho < T_v by amounts on the order of 1 or more, depending on the condensed water content. For ice phases, the formula incorporates adjustments via w_I, accounting for the lower of relative to liquid , though the overall effect remains a density increase over vapor-only scenarios. Unlike virtual temperature, which addresses only the buoyancy enhancement from water vapor's lower molecular weight, density temperature explicitly includes the non-gaseous water to provide a more complete density equivalent for cloudy conditions. This distinction is crucial in assessing parcel , as the added weight from condensed phases can suppress . Density temperature is essential in cumulus parameterization schemes within numerical and models, where it helps evaluate the and vertical motion of updrafts by integrating both vapor and condensate effects.

Applications

Atmospheric Stability and Convection

Virtual temperature plays a crucial role in evaluating atmospheric stability and convective processes by accurately accounting for the buoyancy effects of in air parcels. In the calculation of (CAPE), which measures the potential for atmospheric , is integrated along the ascent path of a lifted parcel using virtual potential temperature (θ_v). The standard formulation involves \text{CAPE} = \int_{\text{LFC}}^{\text{EL}} g \frac{\theta_{v,\text{parcel}} - \theta_{v,\text{env}}}{\theta_{v,\text{env}}} \, dz where g is gravitational acceleration, LFC is the level of free convection, and EL is the equilibrium level; this integration is typically performed on skew-T log-P diagrams to visualize parcel trajectories and environmental profiles. In atmospheric soundings, plotting virtual temperature (T_v) profiles enables adjustments to moist adiabats, uncovering hidden instabilities in humid layers where actual temperature alone might suggest stability. This correction highlights the enhanced of moist air relative to dry air, preventing underestimation of convective potential in vapor-rich environments. In tropical regions, neglecting the virtual correction can lead to substantial underestimation of in highly moist conditions, with relative errors increasing as decreases. Studies from the , such as those by and Seidel, illustrate how virtual temperature effects contribute to stabilizing feedbacks in the through enhanced in moist columns.

Numerical Modeling and Forecasting

In (NWP) models, virtual temperature is incorporated into the hydrostatic equation, \frac{dp}{dz} = -\rho g, to compute air \rho accurately and derive heights, ensuring precise vertical structure representations in moist atmospheres. This approach has been standard in major models since the 1990s, including the Weather Research and Forecasting (WRF) model, where dedicated functions calculate virtual temperature from and mixing ratio outputs for post-processing and diagnostic analyses. Similarly, the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) employs virtual temperature in its spectral transformations for horizontal wind, , and , supporting hydrostatic computations across grid points. In climate modeling, virtual temperature parameterizes effects within general circulation models (GCMs) such as the Community Earth System Model (CESM), particularly in moist schemes that account for vapor's influence on atmospheric and vertical motion. For instance, CESM's Community Atmosphere Model uses virtual temperature to adjust thermodynamic profiles in microphysics and , enhancing simulations of convective processes. This incorporation extends to large-scale tropical , where virtual temperature profiles help model moisture-modified circulations and patterns in GCMs, improving fidelity in regions dominated by humid air masses. Post-2023 developments in AI-hybrid NWP systems, such as ECMWF's blending of the physics-based IFS with the Forecasting System (AIFS), utilize virtual temperature profiles to nudge large-scale components toward AI predictions, enabling faster assessments of atmospheric . These hybrids address limitations in older models by integrating virtual temperature into forecasts. Computationally, approximations of virtual temperature—such as those using mixing ratio directly with temperatures—reduce runtime in lower-resolution runs, while exact formulations are retained in high-resolution simulations to maintain accuracy in buoyancy-driven .

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