Optimization of Aerosol Seeding In rain enhancement Strategies (OASIS)

Background

It has been well established that aerosol particles can strongly impact cloud formation, cloud microphysics and the onset of precipitation. However, the associated physical processes remain poorly quantified, to a large part because of the highly varying aerosol-cloud-precipitation interactions in different meteorological and environmental conditions. This lack of theoretical understanding makes effective cloud seeding in the real atmosphere a challenge. Hence, it has become clear that breakthroughs in effective rain enhancement require also more basic research into the fundamental processes underlying effective cloud seeding, including the role of background and seed aerosol characteristics, cloud microphysics, and aerosol-cloud-precipitation interactions in different atmospheric conditions.

Objectives

The overall objective of the project is to provide solid scientific knowledge of optimized aerosol seeding strategies for precipitation enhancement in the UAE region. The proposed work combines experimental, theoretical and modeling approaches to simultaneously advance the fundamental knowledge underlying rain enhancement efforts, and to provide practical guidance and tools for future field explorations.

The specific scientific objectives are to:

quantify the characteristics and the vertical profile of current background aerosol population as well as the key meteorological drivers of cloud formation in the study region,
identify optimal seeding strategies (in terms of e.g., time, location, amount of seeding) by using cloud-resolving model simulations with a highly advanced aerosol microphysics description
quantify the characteristics of theoretically optimal ice nucleation seed aerosol in order to support future experimental work aiming to develop more efficient ice nuclei
utilize novel statistical approaches to identify the major sources of uncertainty in prediction of rain enhancement success and to guide future research efforts.

Methodology

WP1: Observation-based quantification of aerosol-cloud-precipitation interactions

Optimal cloud seeding requires detailed knowledge of both the background aerosol properties and the underlying meteorological drivers of aerosol-cloud-precipitation interactions in the lower atmosphere. WP1 will provide such a comprehensive set of new high-quality observations in the UAE region with state-of-the-art techniques. This new data will be obtained carrying out a one-year in-situ and ground-based remote sensing measurement campaign in a selected location that will most efficiently benefit the rain enhancement activities in the UAE. The novelty of the approach is in the co-located measurements of aerosols (potential cloud and ice nuclei), water vapor, and 3D-winds (turbulence and convection), observed from the surface up to the free troposphere. This allows the identification of the finest details of cloud formation and cycling processes, taking also into account the aerosol processes dependent on moisture and turbulence such as nucleation of droplets, their hygroscopic growth, droplet evaporation and deposition and land-atmosphere-cloud interactions. Results will be up-scaled to larger regional scales by using complementary remote sensing data.

Link to latest observations

WP2: Model simulations of optimized cloud seeding strategies

As a starting point of the modeling approach, meteorological reanalyses, available precipitation measurements, and one of the leading mesoscale weather forecast models HARMONIE will be used to characterize the conditions leading to cloud formation and potential surface precipitation in the study area.

A typical winter precipitation phenomena in the United Arab Emirate area simulated by HARMONIE. Left figure represent total cloudiness (surface precipitation) on 3rd of January 2016 at 10 o'clock. A large and thick stratiform cloud over Arabic peninsula is moving Southeast with frontal systems. Weak precipitation is observed in a large area for several hours and strong local precipitation events are quite common feature as well. These frontal systems occur from November to May.

A typical summer precipitation phenomena in the United Arab Emirate region simulated by HARMONIE. Left (right) figure represent total cloudiness (surface precipitation) on 12th of July 2016 at 0 o'clock. Small intense convective cloud cells near Haral mountain are caused by forced lifting of moist air. These convective cells occur from June to October.

This information, together with observational data from WP1, will be used as input for the state-of-the-science large eddy simulation (LES) model UCLALES-SALSA to investigate how the clouds in the study region should be seeded to enhance surface rain. The LES model will also be used to assess other cloud-scale impacts of seeding. Finally, breakthrough potential in seeding of ice and mixed-phase clouds will be sought by utilizing state-of-the-art molecular-level quantum mechanical simulation methods to study the theoretical limit for cloud seeding efficiency through heterogeneous freezing.

Vertical cross section of an intense deep convection cell in a test simulation performed with the UCLALES-SALSA model. The left panel shows cloud water (red) and cloud ice (blue) mixing ratios in kg/kg. The overlaid contours show the aerosol particle number concentration in #/cm3. The right panel shows the corresponding cross section for vertical velocities, which reach more than 30 m/s in the updraft cores. The simulated cell is undergoing the storm split at the time of analysis, which is a typical feature of supercell thunderstorms.

WP3: Novel tools to evaluate rain enhancement potential

WP3 will use the new knowledge gained in WPs 1 and 2 together with state-of-the-art stochastic methods to develop a computationally fast statistical representation of the LES model. This representation will be applied to identify the factors related to both seed aerosol properties and background conditions that lead to the largest uncertainties in reliable prediction of rain enhancement potential. The obtained information will be valuable for guiding the focus of future experimental and modeling research efforts as well as field explorations. After the statistical representation has been thoroughly validated against a wide range of observational data from WP1, it can also serve as a basis for developing tools to forecast the efficiency and success of seeding in different meteorological conditions for operational purposes.

Silver iodide is one of the most effective ice nucleation agents known, widely used for rain seeding. Our all-atom MD simulations reveal the role of defects in its ice nucleation activity.

Project outlook

Through the methodology described above, the project will provide a comprehensive quantification of the role of the atmospheric aerosols in efficient precipitation enhancement efforts in the UAE region. Furthermore, the project will also contribute to capacity building in the UAE through research visits, student exchange and international workshops.

Peer-reviewed articles of the project

Published

Callewaert S., S. Vandenbussche, N. Kumps, A. Kylling, X. Shang, M. Komppula, P. Goloub and M. De Mazière (2019), The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and evaluation, Atmos. Meas. Tech., 12, 3673-3698, doi:10.5194/amt-12-3673-2019. Roudsari, G., B. Reischl, O.H. Pakarinen, and H. Vehkamäki (2020), Atomistic simulation of ice nucleation on silver iodide (0001) surfaces with defects, J. Phys. Chem. C, 124, 1, 436-445, doi:10.1021/acs.jpcc.9b08502.

Submitted

Tonttila, J., A. Afzalifar, H. Kokkola, T. Raatikainen, H. Korhonen, and S. Romakkaniemi (2020), Precipitation enhancement in stratocumulus clouds through airbourne seeding: sensitivity analysis by UCLALES, submitted to Atmos. Chem. Phys. Discuss.

Filioglou, M. et al. (2020), Characterization of background aerosol particles properties over the United Arab Emirates, submitted to Atm. Chem. Phys. Discuss.

Acknowledgement

This material is based on work supported by the National Center of Meteorology, Abu Dhabi, UAE under the UAE Research Program for Rain Enhancement Science.

Disclaimer

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Center of Meteorology, Abu Dhabi, UAE, funder of the research.