farid golkar

Determination of affected area by seeding agents, the so-called target area, is an essential requirement for evaluation of cloud seeding projects. The most conservative and credible estimates of seeding effects were obtained from control matches drawn from outside the operational target within 2 hours of the time that each unit was seeded initially (DeFelice et al., 2014). A coupled modeling system consisting of the mesoscale WRF model and the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT), provides capability to simulate the transportation and dispersion of seeding materials and to characterize target area on the map.
This study is devoted to sensitivity analysis of simulated dispersion patterns to several parameters including different configuration based on physical parameterizations used in WRF model, horizontal and temporal resolution of WRF and spatial resolution of HYSPLIT, to determine the most probable dispersion patterns.
Since temperature and wind parameters are the most important parameters in cloud seeding operations, they are measured instantaneously at 1-second intervals at the flight height of the airplane during each flight and therefore, they are very valuable data to assess the performance of the WRF model in simulating these fields. Hence, at first the WRF model outputs such as temperature and wind are validated by data measured by the airplane. Results indicate that there is an acceptable agreement between field data and WRF outputs that are going to be used as input data for dispersion model.
In this study, eight configurations of the WRF model based on different physical parameterization schemes are used for 34 flights in cloud seeding project in 2015 and HYSPLIT model is run by these types of input data and resulting target area are compared on the map. Then, HYSPLIT model is run for four selected seeding operations according to three temporal and two horizontal resolutions of input data in addition to three spatial resolutions of HYSPLIT model and the transport of seeding plumes is characterized on the geographical map.
The results indicate that dispersion model is sensitive to all mentioned parameters. Also, in most cases, dispersion model results at the flight height of cloud seeding aircraft are significantly influenced by the input data provided by the WRF model. In addition, the dispersion model results are less sensitive to other parameters. Furthermore, when the spatial resolution of the HYSPLIT model is close to the horizontal resolution of the input meteorological data provided by the WRF model, affected area of seeding agents is more integrated and therefore there is a greater degree of certainty in determining the target area.

Study of the physical characteristics of cloud with the aim of estimate of precipitation occurence helps to study the possibility of performing cloud seeding project in the appropriate time and place and reduce errors in making decisions in execution of increased precipitation operations and thus reduce the costs of projects. One of the best options to achieve physical and microphysical properties of clouds, especially in the absence of weather radar data, is the use of meteorological satellites products and data, such as MODIS.
MODIS high spectral resolution with 36 spectral bands and also installed sensors for cloud studies will enable researchers to identify different types of clouds among which 26 bands are allocated for purposes of investigation of atmospheric characteristics such as cloud cover, atmospheric profiles, characteristics of aerosols and total precipitable water and cloud properties.
Also, the findings of Seemann and his colleagues in MODIS high spatial resolution imagery (1 km and less) makes it very suitable for meteorological applications.
The purpose of this research is the use of cloud physics level-2 products (mode 06) of MODIS to identify and separate raining from non-raining cloud regions in order to increase accuracy and reduce operation costs of precipitation enhancement project and to investigate the precipitation conditions and forecast using cloud physical and microphysical characteristics. Due to lack of extensive coverage in weather radar and airborne laboratory in Iran, inevitably must do some innovative methods using available satellite data to detect the position of the rain clouds in the broad and diverse geographic extent in the shortest time.
Rosenfeld et al., (1994) investigated Relationship between precipitation and effective particle diameter in the top of cloud and showed that in clouds that the average of effective droplets radius is over 14 microns, the probability of precipitation is very high so that the results mentioned above are also used in this study.
On the other hand the results of the study conducted by Nauss and Kokhanovsky (2006) about a description of precipitation using cloud properties derived from optical satellite data for mid latitude front clouds were used.
Therefore, this article attempts to separate the raining and non-raining clouds using the results of research conducted, also the optical depth of clouds over a maximum of 40 units from 60 units with a high probability of precipitation were analyzed. On indirect or remote sensing is used physical characteristics of clouds for detection and prediction of precipitation. Present study was conducted in February 2009 in the Fars province. In this month the most cloud seeding flights of the year 2009 was performed (13 flights in 8 days cloud seeding operations) and local weather radar information is lacking.
To do a research on accuracy of flights during this time, in addition to MODIS satellite data including Physics and cloud microphysics products obtained through the NASA Web site, required weather maps produced by NOAA website (reanalysis maps from NCEP-NCAR) were used. Timely implementation of cloud seeding operations requires instantaneous information of weather conditions and cloud physics in the area. So that the country has access to MODIS sensor data through satellite receivers, it is possible to use these products for operational purposes and cloud seeding. For research purposes of available data of MODIS products on the NASA Website can also be used. MOD06 products which contains information on the characteristics of the cloud such as cloud phase, cloud top temperature, cloud top pressure, effective droplets diameter in the top of cloud and cloud optical depth or optical thickness have been used in the MOD06 algorithms and the results of it.
Results and Due to the large number of days and performed cloud seeding flights on February 2009 and also pictures and maps of flights, was decided to discuss as an example, two different and chosen days regarding to appropriate cloud systems or inappropriate for seeding is discussed. Therefore, the general conditions for cloud seeding operation is available if these conditions are occurred simultaneously, optical depth is greater than 35 units, cloud top temperature more than - 30 ° C, height of top of middle clouds is higher than 500 mb, diameter of inside middle cloud droplets is more than 19 mm and cloud fraction is as a unit in designed area.
Otherwise if dont establish two or more of the criteria listed, the cloud seeding operation should be avoided .This study determined if cloud seeding project in Fars province on February 2009 was used products from MOD06, the number of cloud seeding operation days can be reduced from 8 of cloudy day (in uncertain conditions of existence of appropriate measures for cloud seeding) to 3 useful and rainy days and consequently can be avoided of 6 completely ineffective cloud seeding flights.
So, in addition to reduce costs the possibility of increasing project accuracy and using of other seeding opportunities in other talented areas of the country was provided.

Today, according to the limitation of water resources and direct effect of precipitation on the amount of obtainable water, developing cloud seeding projects is one of the strategies in management of water resources. Therefore, the optimum use of water resources, including atmospheric water resources (clouds and humidity of atmosphere) plays an important role in reducing the effects of this crisis. The aim of this study is to investigate increasing runoff due to cloud seeding in two sub-basins, namely Kuhdasht and Rumishgan. Thus, after investigating the Isorain maps and the study area’s topography and considering the precipitation systems, the target areas of cloud seeding were determined in two ways, i.e., ground-based generators and airborne generators. Then, determining the potential cloud seeding months, it was attempted to determine the volume of the target area’s rainfall in the potential cloud seeding months. Finally, assuming a 10% increase in precipitation, the runoff volume and the cost of each cubic meter water obtained by cloud seeding in two sub-basins Kuhdasht and Rumishgan were determined. The cost evaluation of the increasein the runoff caused by cloud seeding was performed by using mixed cloud seeding cost.