The Idaho Power Company (IPC) conducts a winter cloud seeding program to augment snowfall along the Snake River Basin and its tributaries for hydroelectric generation. The program has been focused in the Payette River basin in western Idaho and the upper Snake River system in eastern Idaho, and has recently expanded into the Boise and Wood basins in western Idaho.
Map of the Snake Watershed in Idaho (large red outline) and existing ground generator and observational facility sites on a map of terrain height (m; color shading). The Payette River Basin, Boise Basin, and Woods Basin target areas are located (north to southeast) in the western Snake watershed, north of Boise and each is also outlined in red. The Upper Snake River Basin target area is located in Eastern Idaho, also outlined in red. Ground generator locations are identified as circle and triangle symbols, and color-coded as red-filled circles (Payette, Boise, Woods), blue (north Eastern Idaho), and green (south Eastern Idaho). The circles are Idaho Power owned generators, and the triangles are generators operated by Let it Snow. Grey lines indicate flight tracks used by the cloud seeding aircraft. Black squares indicate the location of microwave radiometers, black x’s for atmospheric sounding sites, open blue and red circles are high-resolution snow gauge sites (located in the western Snake Basin).
In FY16, RAL completed a numerical modeling “Phase Five” study to provide real-time and retrospective model-based guidance on the effectiveness of cloud seeding using ground generators and aircraft tracks. The primary goal of Phase Five was to complete the development of a real-time cloud seeding forecast guidance system using the WRF model developed in Phases Three–Four, including a real-time web-based display to provide IPC forecasters with graphical output from the real-time forecast system. Since the completion of Phase Five, a Phase Six study was begun with goals to continue research and improvements to the cloud-seeding module utilized in Phases One–Five. Planning for an upcoming field project, SNOWIE, funded by the National Science Foundation (NSF) in partnership with IPC is also underway.
In 2016, RAL provided real-time and retrospective model-based guidance on the effectiveness of cloud seeding using ground generators and aircraft tracks. Components of this effort included:
- refining the real-time cloud-seeding decision algorithm;
- collaboration with the University of Arizona (UofA) to incorporate the cloud-seeding module into the UofA real-time WRF model;
- running a research version of WRF on the UofA computing cluster that provided tailored precipitation and cloud-seeding forecasting relevant to the Idaho Power cloud-seeding operations during the 2015-2016 winter season;
- completing a prototype web-based display system to incorporate the IPC observational data in near real time and the display of model validation data alongside available observations, and then running it during the 2015-2016 season;
- simulating cloud-seeding effects for selected cases that were seeded by Idaho Power during the winter season (hereafter, the retrospective cases);
- improving the dispersion and physical removal processes of AgI in the model;
- comparing model simulation results with observations when available, such as measurements of silver in the snow; and,
- preparing for an upcoming NSF field project called Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE)
Box and whisker plots of model-simulated SWE (top) and Ag concentration (bottom) for every 30 minutes from 0530 to 0900 UTC (black boxes, red ‘x’ for mean). The distributions for the boxes and whiskers (dashed lines) were based upon the 9 data points surrounding the sampling site (left column) and 25 data points (right column). Overlaid on each panel are observations from the SNOTEL (blue open circles; top row) and BSU lab Ag in snow measurements (blue open circles for measurement mean and blue triangles to show the profile sample means; bottom row) from the 0200-0530 UTC period. (The model simulation of precipitation showed a 3.5-hour time offset in when the simulated storm began producing precipitation, thus the time offset analyzed above).
Given that the dispersion of AgI is a key process that determines the targeting efficiency and ultimately the seeding effect on the ground, improving how the model simulates this process is of paramount importance for the model to realistically simulate cloud seeding impacts. Therefore, simulations were performed to understand the behavior of AgI dispersion using different Planetary Boundary Layer (PBL) and Land Surface Model (LSM) schemes, as well as testing the new inline dispersion model (i.e. HYSPLIT) feature in the WRF model. The results of these tests were then utilized to simulate three cases from the 2015–2016 winter season in which trace chemistry (i.e. silver) measurements in the snow had been collected for comparison with the model simulations. The trace chemistry sampling experiment to measure silver in the snow was carried out by Boise State University. The measurements were collected in target and downwind areas to serve as validation data for the AgI dispersion simulated by the model. However, the original cloud seeding module (Wintertime AgI Seeding Parameterization, or WASP) did not consider some physical processes related to AgI removal that can impact the simulated silver deposition and downwind seeding effect. To address these issues, the WASP was modified to include the missing physics: AgI self-coagulation, AgI scavenging by precipitating particles, and AgI dry deposition due to surface roughness and turbulence. At the same time, the WASP was implemented into the new Thompson-Eidhammer microphysics scheme in WRF v3.7.1 to take advantage of prognostic aerosol effects on clouds and precipitation. An example analysis comparing the silver in snow measurements with the model simulations is presented in the figure.
Images from the Cloud Imaging Probe on the Univ. Wyoming King Air on 12 February 2014 at 4300 m MSL altitude (–10°C) indicating supercooled drizzle-sized drops and occasional dendritic ice crystals. The vertical axis corresponds to 1600 μm.
Five cases from 2015–2016 were selected for further study with retrospective case simulations. These cases were chosen to evaluate the potential seeding effects for cases seeded by IPC in a manner not specifically called by the real-time model. Additional simulations for each case were also run to test the sensitivity of the results to initialization time, whether the new scavenging processes added to the cloud seeding parameterization were turned on or not, and to seeding rate or ground or airborne seeding method. Several model simulations were also conducted in order to optimize the program design of the IPC cloud seeding program, including testing the impacts of doubling the number of ground-based generators versus doubling the seeding rates of existing generators, using aircraft instead of or in addition to ground generators, and investigating using bin microphysics schemes in a real three-dimensional simulation to see if a more sophisticated microphysics scheme improved simulation results. The latter bin microphysics test simulations were performed on a case that occurred when “pre-SNOWIE” research aircraft measurements were being made in February 2014. This case consisted of stable orographic wintertime clouds with freezing drizzle observed near Boise, Idaho during an atmospheric river event during which the University of Wyoming King Air collected in situ microphysical measurements as well as cloud radar measurements. Analysis of the observations and measurements collected in this case and model simulations of this case were presented at the American Geophysical Union (AGU) fall meeting in December 2015 and at the International Conference on Clouds and Precipitation (ICCP) in July 2016.
Map of ground-based instruments deployed for SNOWIE
A new program, Seeded and Natural Orographic Wintertime clouds—the Idaho Experiment (SNOWIE), was funded by NSF in the spring of 2016. The project is led by Dr. Jeff French (Univ. Wyoming), with involvement from Dr. Bart Geerts (Univ. Wyoming), Bob Rauber (Univ. Illinois), and Katja Friedrich (Univ. Colorado), as well as Roy Rasmussen, Sarah Tesendorf and Lulin Xue of RAL. With funding support from IPC, RAL has also been heavily involved in the planning of this field project, from the proposal writing to planning for the operations and deploying instruments (i.e., high-resolution snow gauges, radiometers, snow depth sensors) to the field (Fig 11 below).The project will take place in January–March 2017 and aims to evaluate ground and airborne cloud seeding using physical and numerical modeling approaches, as well as to validate the cloud seeding module. RAL will participate in the SNOWIE field project and continue making improvements to the cloud seeding forecast guidance system. As part of the Phase Six effort, RAL has developed a new case-calling algorithm that will be tested in parallel with the real-time modeling system during the 2016–2017 winter season. New features will also be added to the web-based display.
- Run the newly created seeding case-calling algorithm in parallel with the real-time model for the 2016-2017 season;
- Run updated display system with new features for 2016–2017 winter season;
- Conduct the SNOWIE field project and collaborate with SNOWIE university PIs to perform preliminary analysis on high priority cases;
- Run simulations of cases with silver in snow samples and collaborate with Boise State University to compare model results with measurements;
- Perform detailed case study simulations and analyses to improve the cloud seeding module, using cases from SNOWIE and pre-SNOWIE;
- Publish journal papers on the major findings from these studies.
Idaho Power conducts a winter cloud seeding program to augment snowfall along the Snake River Basin and its tributaries for hydro-generation purposes. The program is presently focused in two areas; the Payette River watershed and the upper Snake River system in eastern Idaho.
Idaho Power has invested over 15 years of research and development in the subject of cloud seeding to enhance winter snowpack. Snowpack enhancement activities rely heavily upon operational forecast models to provide guidance on when conditions are generally suitable for cloud seeding. High resolution, tailored forecast models can also provide more accurate guidance for cloud seeding operations and other activities of interest to Idaho Power, such as stream flow forecasting.
A “Phase One” cloud seeding feasibility study using the Weather Research and Forecasting (WRF) mesoscale model was undertaken by the National Center for Atmospheric Research (NCAR) Research Applications Laboratory (RAL) in order to provide model-based guidance on the effectiveness of cloud seeding using the existing ground generators, aircraft tracks, and planned new ground generator sites in the Payette, Eastern Idaho, and Western Wyoming regions operated by Idaho Power. The WRF model was run coupled with a silver iodide (AgI) cloud seeding parameterization (Xue et al. 2013a,b) to simulate potential cloud seeding impacts from 10 actual cloud seeding events across the southern Idaho region.
A “Phase Two” study was conducted by NCAR in order to investigate the sensitivities of the seeding effect in the WRF cloud seeding model and compare the WRF model output with available observations. The sensitivity tests showed that the simulated seeding effect is most impacted by the seeding rate and whether the seeding occurred via airborne seeding or ground generators. Airborne seeding was shown to be more effective than ground in all cases due to the improved targeting of the AgI to the optimal cloud regions for snow crystal growth and fallout. The results also showed that small changes in the background meteorological conditions (such as wind speed and relative humidity) could induce precipitation changes similar in magnitude to the seeding effect.
The optimal configuration for cloud seeding simulations needs to effectively simulate precipitation, cloud water, and the dispersion of AgI. The model configuration tests indicated that the initialization data and the choice of domain and resolution were highly influential factors impacting the simulated precipitation, while the boundary layer scheme had less of an impact (on the simulated precipitation). However, Phase Two analysis with ice nuclei measurements (from Wyoming) concluded that the boundary layer schemes do not adequately simulate the vertical diffusion of AgI from ground seeding. Rather, a Large Eddy Simulation (LES) framework coupled with high horizontal and vertical model resolution seemed to capture the transport of AgI much more adequately.
NCAR is currently conducting a two-year “Phase Three” effort, building upon the cloud seeding modeling research conducted in Phases One and Two, to develop and implement a real-time cloud seeding forecast guidance system using WRF and the cloud seeding parameterization (Xue et al. 2013a,b). As part of this effort, NCAR is working with the University of Arizona to run a research version of WRF to obtain tailored precipitation and cloud seeding forecasting relevant to the Idaho Power cloud seeding operations.