Quantification of cloud water mass from synergetic ground-based remote sensing measurements
by Alexander Myagkov, Athina Argyrouli, Edouard Martins, Jordi Tiana-Alsina and Tom Goren1
1The Hebrew University of Jerusalem, Israel
1. Introduction
Clouds are one of the key climate regulators since they influence Earth’s energy balance by interacting with solar and terrestrial radiation (however the cloud feedback in the current global models has large uncertainty). Quantifying the amount of water in a cloud is a valuable information in order to determine the precipitation initiation and to assess better the contribution of liquid water droplets to Earth’s energy budget. Additionally, climate models need a validation of the in-cloud parameterizations. To estimate the water mass and energy inside a cloud, we have used both passive (microwave radiometer) and active (cloud radar, ceilometer, and wind lidar) ground-based remote sensing instruments located at Jülich research center facilities (Löhnert et al., 2014). The synergetic use of measurements collocated in time and space allows the reasonable assessment of the three dimensional distribution of cloud macro- and micro-physical properties.
2. Results
For the estimation of the amount of liquid water a simple scheme, based on liquid water path (LWP) data from the radiometer, CLOUDNET categorization, and horizontal wind component from the Doppler lidar, was implemented. First, using the CLOUDNET categorization two days (5 Jun 2013 and 25 Apr 2013) with cumulus clouds, containing only liquid water, were chosen. For the detection and separation of clouds the LWP data was used. Also, using the radiometer data, the time period, during which a cloud was passing over the measurement site, was estimated for every cloud. Using this information and the horizontal wind component the horizontal extent of clouds was found. Based on the satellite images it was assumed that the majority of clouds were symmetric in horizontal axis. Also we computed the clouds size over Jülich for the relevant days from satellite images. A comparison between the clouds’ size from the satellite and from the instruments showed a good agreement. Under the assumption, that clouds are symmetrical, the amount of liquid water for every cloud was estimated by multiplying the area covered by a cloud and its mean LWP. The vertical extent was obtained from the information about cloud base and cloud top from the CLOUDNET in order to estimate the volume of clouds. The amount of energy released by the condensation of the amount of water, contained in clouds, was estimated using the latent heat of water condensation (2260 J/g).
2.1 Cloud Water
The amount of water in the clouds was converted to mass in order to give us a unit that is used in daily life and can be compared to vehicles’ mass, for example. The calculations show that the smallest clouds, which have the volume of ~109 m3 weighted like a big truck, clouds with the volume of ~1010 m3 weighted like the huge Airbus A380 plane, and the largest clouds that had volume of ~1011 m3 weighted like a huge cargo ship (see Figure 1a). It should be mentioned that the largest cloud is in fact a shallow small cumulus cloud that did not produce any precipitation. Moreover, the satellites’ algorithm could not retrieve the LWC for these “biggest” clouds because they were too small in comparison with the coarse resolution of the satellite (which is 1x1 km). Given that, the large amount of water in these clouds is impressive. This also manifests the advantages and disadvantages of instruments with narrow field of view but with high spatial resolution, (i.e. ground-based instruments that we used), vs satellites, that have a wider field of view, but with coarser resolution.
2.2 Cloud Energy
In order to estimate how much energy is being released in the clouds, we calculated the latent heat release, based on the amount of water that was condensed in the clouds (see section 3.1). The results show that the largest clouds release the amount of energy that could maintain households in Jülich during about half a year, and that is equal to one month of operation of the largest photovoltaic park that occupies 10km2 and which is located at Agua Caliente Solar Project in Arizona, USA (see Figure 1b). Keep in mind that the largest cloud is not so large, as mentioned in section 3.1. This “large” cloud has also the same amount of energy than the largest nuclear power plant in Japan produces in almost one week. An interesting aspect of the cloud energy is whether the clouds precipitate or not. If the clouds do not precipitate, the released latent heat is being consumed by the evaporation of the cloud. Once the clouds precipitate, the released latent heat remains in the atmosphere and may alter the thermodynamic profile of the boundary layer (e.g., heating the upper layers and cooling the lower layers - more stable atmosphere). Aerosols affect the ability of the clouds to precipitate and thus should be considered in studies that involve energy balance in clouds.
Figure 1: (a) Cloud volume as function of cloud water mass and (b) Cloud volume as function of latent heat.
3. Description of the pseudo-adiabatic air parcel concept
When an air parcel ascends in the atmosphere, its temperature decreases with height according to its dry lapse rate. During this lift, the air parcel behaves as a closed adiabatic system (i.e., its enthalpy is a conserved quantity). The air parcel stops rising at a constant potential temperature θ along the dry adiabatic line until it becomes saturated with water vapor. At this altitude, the air parcel has reached its Lifting Condensation Level (LCL) and any further lifting results in the condensation of liquid water which releases latent heat. If all of the condensation products stay in the rising parcel, the process may still be reversible and, therefore adiabatic even though latent heat is released in the system. This is only true if there is no heat exchange between the air parcel and the ambient air. On the contrary, if all of the condensation products fall out of the air parcel, the process turns as irreversible because the condensation products carry some latent heat. By definition, the latent heat is the type of heat which when supplied to a system produces change in phase without a change in temperature. The enthalpy of this system decreases when it undergoes the transition from vapor phase to liquid phase. This is called a pseudo-adiabatic process and the air parcel keeps rising in the atmosphere at a constant equivalent potential temperature θE along the wet adiabatic line.
The amount of condensed water when the air parcel is lifted from the LCL to an altitude h can be estimated as:
where χ is the liquid water mixing ratio [kg/kg] and ρ is the density of dry air [kg m-3].
The total energy that is released during this phase change is the product of the water mass with the latent heat of condensation (Wallace & Hobbs, 2006).
4. Conclusions:
• From the synergy of Cloud Radar, Ceilometer, Wind Lidar and Microwave Radiometer, the water content that was calculated could fill from a truck (~10 tons) to a cargo ship (~105 tons).
• The energy released by the condensation of all the water vapor to the largest cloud could provide energy to Jülich households during six months.
• Pseudo-adiabatic calculations underestimate the amount of water in a cumulus. In particular, the liquid water content was estimated equal to 0.30g/m3 whereas the corresponding value from the observations was approximately 0.42g/m3.
Acknowledgments:
We thank Domenico Cimini and Ulrich Löhnert for their insightful comments. We gratefully acknowledge ITaRS (FP7-PEOPLE-2011-ITN under grant 289923). We also acknowledge the European Space Agency for providing a financial support to Tom Goren for participating in the summer school.
References:
1) Löhnert, U., J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barrera-Verdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O'Connor, C. Simmer, A. Wahner, S. Crewell, 2014: JOYCE: Jülich Observatory for Cloud Evolution Bulletin of the American Meteorological Society, http://dx.doi.org/10.1175/BAMS-D-14-00105.1
2) Wallace, J. M., P. V. Hobbs, Atmospheric Science: An Introductory Survey, 2nd ed., Academic Press, New-York, 467 pp., 2006.