Air temperature equation derived from sonic temperature and water vapor mixing ratio for turbulent airflow sampled through closed-path eddy-covariance flux systems

Air temperature (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, knowing where (in relation to other essential measurements) and at what frequency T must be measured is critical to accurately describing such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response sensors of a three-dimensional sonic anemometer and infrared CO2–H2O analyzer, respectively. T is then computed by use of either T=Ts1+0.51q-1, where q is specific humidity, or T=Ts1+0.32e/P-1, where e is water vapor pressure and P is atmospheric pressure. Converting q and e/P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raising the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations; therefore, neither of their accuracies was evaluated, nor was the question answered. Based on first principles, this study derives the T equation in terms of Ts and the water vapor molar mixing ratio (χH2O) without any assumption and approximation. Thus, this equation inherently lacks error, and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and χH2O. Based on current specifications for Ts and χH2O in the CPEC300 series, and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00 K) from the uncertainty in Ts measurements and a little (±0.02 K) from the uncertainty in χH2O measurements. An improvement in measurement technologies, particularly for Ts, would be a key to narrowing this accuracy range. Under normal sensor and weather conditions, the specified accuracy range is overestimated, and actual accuracy is better. Equation-computed T has a frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. Synchronized at a temporal scale of the measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has advanced merits in boundary-layer meteorology and applied meteorology.

Calibration of water vapor Raman lidar measurements by use of radiosonde and microwave radiometer measurements

<p>Water vapor profiles with high vertical and temporal resolution were determined by use of the Raman lidar PollyXT within the MOSAiC campaign in the Arctic during the winter time 2019 – 2020. These measurements need a calibration. Usually, radiosonde data are utilized to calibrate the lidar data by the profile or the linear fit method, respectively. The radiosonde is drifting with the wind; thus, it is often measuring different atmospheric volumes compared to the lidar observations.</p> <p>The period 5-7 February 2020 is used to demonstrate the results. The correlation coefficient of the linear fit between the radiosonde and the lidar data varies with the different atmospheric conditions. The calibration results from the profile method coincide with those of the linear fit method, but the selection of the appropriate calibration setup is not straightforward. The varying correlation of the calibration results is attributed to the partly too low data-variability of the water vapor mixing ratio in the respective heights.  Moreover, the drift of the radiosondes with the wind and hence measurements of atmospheric volumes with lateral distances will have decreased the correlation between the lidar and the radiosonde measurements.</p> <p>During MOSAiC a microwave radiometer was collocated close to the lidar. This system was measuring the same atmospheric vertical column. Its product, the integrated water vapor, might be useful for the calibration of the lidar.</p> <p>Hence, the contribution will analyze the error of the lidar retrieved water vapor mixing ratio that includes the calibration with the radiosonde data and the microwave radiometer product.</p> <p> </p>

Effects of the large-scale circulation on temperature and water vapor distributions in the Π Chamber

Microphysical processes are important for the development of clouds and thus Earth's climate. For example, turbulent fluctuations in the water vapor mixing ratio, r, and temperature, T, cause fluctuations in the saturation ratio, S. Because S is the driving factor in the condensational growth of droplets, fluctuations may broaden the cloud droplet size distribution due to individual droplets experiencing different growth rates. The small-scale turbulent fluctuations in the atmosphere that are relevant to cloud droplets are difficult to quantify through field measurements. We investigate these processes in the laboratory using Michigan Tech's Π Chamber. The Π Chamber utilizes Rayleigh–Bénard convection (RBC) to create the turbulent conditions inherent in clouds. In RBC it is common for a large-scale circulation (LSC) to form. As a consequence of the LSC, the temperature field of the chamber is not spatially uniform. In this paper, we characterize the LSC in the Π Chamber and show how it affects the shape of the distributions of r, T, and S. The LSC was found to follow a single roll with an updraft and downdraft along opposing walls of the chamber. Near the updraft (downdraft), the distributions of T and r were positively (negatively) skewed. At each measuring position, S consistently had a negatively skewed distribution, with the downdraft being the most negative.

Numerically consistent budgets of energy, momentum and mass in Cartesian coordinates: Application to the WRF model

Numerically accurate budgeting of the forcing terms in the governing equations of a numerical weather prediction model is hard to achieve. Because individual budget terms are generally two to three orders of magnitude larger than the resulting tendency, exact closure of the budget can only be achieved if the contributing terms are calculated consistently with the model numerics. We present WRFlux, an open-source software that allows precise budget evaluation for the WRF model, as well as transformation of the budget equations from the terrain-following grid of the model to the Cartesian coordinate system. The theoretical framework of the numerically consistent coordinate transformation is also applicable to other models. We demonstrate the performance and a possible application of WRFlux with an idealized simulation of convective boundary layer growth over a mountain range. We illustrate the effect of inconsistent approximations by comparing the results of WRFlux with budget calculations using a lower-order advection operator and two alternative formulations of the coordinate transformation. With WRFlux, the sum of all forcing terms for potential temperature, water vapor mixing ratio and momentum agrees with the respective model tendencies to high precision. In contrast, the approximations lead to large residuals: The root mean square error between the sum of the diagnosed forcing terms and the actual tendency is one to three orders of magnitude larger than with WRFlux. Furthermore, WRFlux decomposes the resolved advection into mean advective and resolved turbulence components, which is useful in the analysis of large-eddy simulation output.

Air temperature equation derived from sonic temperature and water vapor mixing ratio for air flow sampled through closed-path eddy-covariance flux systems

Air temperar (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, it is critical to know where (in relation to other essential measurements) and at what frequency T must be measured to accurately describe such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response senosrs of three-dimensional sonic anemometer and infrared gas analyzer, respectively. T then is computed by use of either T = Ts (1 + 0.51q)−1, where q is specific humidity, or T = Ts (1 + 0.32e / P)−1, where e is water vapor pressure and P is atmospheric pressure. Converting q and e / P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raises the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations. Therefore, neither of their accuracies were evaluated, nor was the question answered. Based on the first principles, this study derives the T equation in terms of Ts and water vapor molar mixing ratio (χH2O) without any assumption and approximation. Thus, this equation itself does not have any error and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and χH2O. Based on current specifications for Ts and χH2O in the CPEC300 series and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00 K) from the uncertainty in Ts measurements and little (±0.03 K) from the uncertainty in χH2O measurements. Apparently, the improvement on measurement technologies particularly for Ts would be a key to narrow this accuracy range. Under normal sensor and weather conditions, the specified accuracy is overestimated and actual accuracy is better. Equation-computed T has frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. As synchronized at a temporal scale of measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has its advanced merits in boundary-layer meteorology and applied meteorology.

Day and nighttime observations of water vapor and aerosol optical profiles in the boundary layer observed by Caeli Raman lidar during the TROpomi vaLIdation eXperiment (TROLIX’19)

<p>To foster our understanding of the role that the vertical distribution of atmospheric aerosols and water vapor plays on the climate system, the Cabauw Experimental Site for Atmospheric Research in the Netherlands has been providing measurements with its high performance multi-wavelength Raman lidar (Caeli) on a regular basis and during intensive periods of observations.</p><p>From late August to early October, 2019, the Cabauw site was the central point for the active remote sensing activities during the TROpomi vaLIdation eXperiment (TROLIX’19), a campaign which used a combination of in-situ and remote sensing measurements, both ground and air-borne based, for the validation of Sentinel-5p/TROPOMI level 2 products. During this campaign, Raman lidar measurements were performed under a variety of atmospheric conditions.</p><p>In this work, we present the Caeli simultaneous measurements of aerosol optical properties and water vapor mixing ratio profiles during the TROLIX'19 campaign. A general clean atmosphere was observed, with eventual occurrence of mid-tropospheric aerosol layers and a persistent stratospheric layer observed for many days. Profiles of extinction and backscatter coefficients have been processed both locally and through the central processing facilities of the European lidar network (ACTRIS-EARLINET). The precision of the day and nighttime water vapor mixing ratio retrievals were accessed, showing that high resolution profiles were possible in the planetary boundary layer (PBL) during daytime and throughout the troposphere during nighttime, allowing the measurement of dry air mixing in the PBL and information for heat flux studies. Time and vertically resolved aerosol and water vapor fields around cloud formation events are explored.</p>

Convective Boundary Layer Clouds as Observed with Ground-Based Lidar at a Mid-Latitude Plain Site

A total of 3047 individual shallow cumuli were identified from 9 years of polarization lidar measurements (2011–2019) at Wuhan, China (30.5°N, 114.4°E). These fair-weather shallow cumuli occurred at the top edge of the convective boundary layer between April and October with the maximum occurrence in July over the 30°N plain site. They persisted mostly (>92%) for a short period of ~1–10 min and had a geometrical thickness of ~50–600 m (a mean of 209 ± 138 m). The majority (>94%) of the cloud bases of these cumuli were found to appear ~50–560 m (a mean of 308 ± 254 m) above the lifting condensation level (LCL). In this height range from the LCL to the cloud base, the lidar volume depolarization ratio (δδV) slightly decreased with increasing height, showing gradually increasing condensation in this sub-cloud region due to penetrative thermals. Most of the observed shallow cumuli (79%) formed under the conditions of high near-surface air temperature (>30 °C) and water vapor mixing ratio (>15 g kg−1).

Atmospheric Turbulence and Clouds in the Tropics: Shipborne Lidar Measurements of Dynamics and Thermodynamics During EUREC4A

<p>During the EUREC4A campaign (Bony et al., 2017, Stevens et al, 2020), a unique combination of lidar systems was operated to study ocean-atmosphere interaction on the German research vessel R/V Maria S Merian between 18 January and 18 February 2020. These systems observed the maritime boundary layer (MBL) and its relation to cloud development in the trade wind alley east of Barbados and in the "Boulevard des Tourbillons" east of Venezuela with turbulence resolving resolution.</p><p>For this purpose, for the first time, the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) (Lange et al. 2019; Lange et al. this conference) was operated on a shipborne platform in vertically staring mode. This system is capable of measuring water-vapor, temperature, and aerosol profiles with unprecedented resolution of 7.5 m and 10 s in the lower troposphere. ARTHUS was combined with one Doppler lidar in vertically staring mode and a second one in a 6-beam scanning mode.</p><p>For studying the above mentioned processes, a data set was collected, which includes profiles of water vapor mixing ratio, temperature, relative humidity, vertical and horizontal wind as well as the statistics of higher-order moments of these parameters. Synergetic parameters from the combination of the data are turbulent kinetic energy (TKE), momentum flux, dissipation rate, sensible and latent heat flux profiles (Behrendt et al. 2020). At the conference, highlights of the measurements will be presented which show the dependence of cloud evolution on sea surface temperature and MBL properties as well as the interaction with the trade wind layer.</p><p> </p><p><strong>References</strong></p><p> </p><p>Behrendt et al. 2020, https://doi.org/10.5194/amt-13-3221-2020</p><p>Bony et al. 2017, https://doi.org/10.1007/s10712-017-9428-0</p><p>Lange et al. 2019, https://doi.org/10.1029/2019GL085774</p><p>Stevens et al. 2020, submitted to ESSD</p>

The lacustrine-water vapor isotope inventory experiment L-WAIVE

In order to gain understanding on the vertical structure of atmospheric water vapour above mountain lakes and to assess the respective influence of evaporation and advection processes, the L-WAIVE (Lacustrine-Water vApor Isotope inVentory Experiment) field campaign was conducted in the Annecy valley in the French Alps in June 2019. This campaign was based on a synergy between a suite of ground-based, boat-borne, and airborne measuring platforms implemented to characterise the thermodynamic and isotopic state above the lake environment using both in-situ and remote sensing instruments. Two ultra-light aircrafts (ULA), one equipped with a Rayleigh-Mie lidar, solar fluxmeters and an optical counter, and one equipped with a Cavity Ring-down Spectrometer (CRDS) and an in-cloud liquid water collector, were deployed to characterize the vertical distribution of the main stable water vapour isotopes (H216O, H218O and H2H16O), and their potential interactions with clouds and aerosols. ULA flight patterns were repeated several times per day to capture the diurnal evolution as well as variability associated with different weather events. ULA flights were anchored to continuous water vapour and wind profiling of the lower troposphere performed by two dedicated ground-based lidars. Additional flights have been conducted to map the spatial variability of the water vapour isotope composition regarding the lake and surrounding topography. Throughout the campaign, ship-borne lake temperature profiles as well as liquid water samples at the air-water interface and at 2 m depth were made, supplemented on one occasion by atmospheric water vapour isotope measurements from the ship. The campaign period included a variety of weather events leading to contrasting humidity and cloud conditions, slope wind regimes and aerosol contents in the valley. The water vapor mixing ratio values in the valley atmospheric boundary layer were found to range from 3–4 g kg−1 to more than 10 g kg−1 and to be strongly influenced by the subsidence of higher altitude air masses as well as slope winds. A significant variability of the isotopic composition was observed within the first 3 km above ground level. The influence of the lake evaporation was mainly detected in the first 500 m of the atmosphere. Well-mixed conditions prevailed in the lower free troposphere, mainly above the mean altitude of the mountain tops surrounding the lake.