Winter Weather

Wyoming Cloud Seeding Research

BACKGROUND

After the completion of the Wyoming Weather Modification Pilot Project (WWMPP) in 2014, the Wyoming Water Development Commission (WWDC) funded NCAR to perform a study to design an operational cloud seeding program in the Medicine Bow and Sierra Madre Ranges.  A model-based evaluation of the WWMPP Randomized Statistical Experiment (RSE) was included as part of this study and compared with the snow gauge data collected during the WWMPP (Figure 1).  This report summarizes the key accomplishments during the completion of this study in FY18.

Figure 1. Depiction of topography and instrumentation deployment in the Sierra Madre and Medicine Bow mountain ranges for the WWMPP.  Highway 47 (HY) was the target site for the Sierra Madre Range, and GLEES (GL) was the target site for the Medicine Bow Range.  The covariate sites were Sandstone (SS) and Elk River (ER) for the Sierra Madre Range and Barrett Ridge (BR) and Chimney Park (CP) for the Medicine Bow Range. Alternative target sites were Battle Pass (BP) for the Sierra Madre Range and Towner Lake (TL) for the Medicine Bow Range. From Rasmussen et al. (2018).
Figure 1. Depiction of topography and instrumentation deployment in the Sierra Madre and Medicine Bow mountain ranges for the WWMPP.  Highway 47 (HY) was the target site for the Sierra Madre Range, and GLEES (GL) was the target site for the Medicine Bow Range.  The covariate sites were Sandstone (SS) and Elk River (ER) for the Sierra Madre Range and Barrett Ridge (BR) and Chimney Park (CP) for the Medicine Bow Range. Alternative target sites were Battle Pass (BP) for the Sierra Madre Range and Towner Lake (TL) for the Medicine Bow Range. From Rasmussen et al. (2018).

FY2018 ACCOMPLISHMENTS

A study to evaluate the cloud seeding model by simulating all 118 RSE cases from the WWMPP was completed and a manuscript describing these results was accepted for publication. This effort, which began in FY16, established an ensemble approach that allows one to better account for initial condition and model biases and random errors in the model simulations. 

A set of 96 total simulations were conducted for each RSE case: 24 served as control simulations and 72 as seeding simulations. The 72-member seeding ensemble was used to address the seeding process uncertainties in the model.  This ensemble resulted in the creation of 8,496 seeded simulations and 2,832 non-seeded simulations.  The members were designed to encompass uncertainties arising from the use of different initialization data sets, boundary layer schemes, cloud condensation nuclei and ice nuclei background levels, silver iodide (AgI) activation and removal functions, as well as spatial and temporal uncertainties of the simulated precipitation. These ensemble simulations were analyzed and compared to snow gauge data (at sites illustrated in Figure 1).  The ensemble-based modeling approach indicated a spread of results, as intended, but suggested a median seeding effect of 5% relative to seedable storms over a given winter season, with an inner quartile range of 3-7% (Figure 2).

Figure 1. Depiction of topography and instrumentation deployment in the Sierra Madre and Medicine Bow mountain ranges for the WWMPP.  Highway 47 (HY) was the target site for the Sierra Madre Range, and GLEES (GL) was the target site for the Medicine Bow Range.  The covariate sites were Sandstone (SS) and Elk River (ER) for the Sierra Madre Range and Barrett Ridge (BR) and Chimney Park (CP) for the Medicine Bow Range. Alternative target sites were Battle Pass (BP) for the Sierra Madre Range and Towner Lake (TL) for the Medicine Bow Range. From Rasmussen et al. (2018).
Figure 2. Distributions of the fractional increase in precipitation at the Medicine Bow range target (GL), the Sierra Madre target (HY) and both (average of the two)  based on the difference between seed and no-seed model ensemble simulations (8,946 cases simulated). The horizontal bar is the median and the red X the mean value. The top and bottom of the boxes represent the quartile ranges. From Rasmussen et al. (2018).

In addition, methods were developed and demonstrated to use the WRF-Hydro model to evaluate the impacts of cloud seeding on streamflow using a coupled cloud seeding plus hydrological modeling approach. The process for this involved calibrating the WRF-Hydro model using a long-term high-resolution WRF simulation and running the WRF-Hydro model using forcings from both the WRF long-term simulation and that same simulation coupled with output from the ensemble of WWMPP RSE seeding simulations using the WRF cloud-seeding model.

Idaho Power Project

BACKGROUND

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 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.

In FY18, RAL completed a “Phase Seven” 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 Seven was to complete the development of a real-time cloud seeding forecast guidance system using the WRF model developed in Phases Three–Six, and to conduct research using data from a field project that was funded by the National Science Foundation (NSF) in partnership with IPC, entitled “Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment”, or SNOWIE.

The SNOWIE project aims to study the impacts of cloud seeding on winter orographic clouds.  The field campaign took place in Idaho between 7 January–17 March 2017 and employed a comprehensive suite of instrumentation, including ground-based radars and airborne sensors, to collect in situ and remotely-sensed data in and around clouds containing supercooled liquid water before and after they were seeded with silver iodide aerosol particles (Figure 1). Seeding material was released primarily by a seeding aircraft, which produced zig-zag lines of silver iodide as it dispersed downwind.  In several cases, unambiguous zig-zag lines of radar reflectivity were detected by radar, and in situ measurements within these lines have been analyzed to examine the microphysical response of seeding the cloud (Figure 2).  The measurements from SNOWIE aim to address long-standing questions about the efficacy of cloud seeding, starting with documenting the physical chain of events following seeding.  The data is also being used to evaluate and improve computer modeling parameterizations, including the cloud-seeding parameterization developed in RAL that will be used to further evaluate and quantify the impacts of cloud seeding.  

Figure 3. Terrain map of the SNOWIE project domain north of Boise, Idaho, illustrating the sites of ground-based instrument locations (see legend) as well as an example flight track for the Seeding Aircraft and University of Wyoming King Air, assuming conditions with westerly winds.  The Payette River Basin is outlined in thick gray, and was the target region for the SNOWIE field campaign.  From Tessendorf et al. (2019).
Figure 3. Terrain map of the SNOWIE project domain north of Boise, Idaho, illustrating the sites of ground-based instrument locations (see legend) as well as an example flight track for the Seeding Aircraft and University of Wyoming King Air, assuming conditions with westerly winds.  The Payette River Basin is outlined in thick gray, and was the target region for the SNOWIE field campaign.  From Tessendorf et al. (2019).
Figure 4. PPI scans (0.99-degree elevation angle) at 0109 UTC (left) and 0137 UTC (right) from the Packer John DOW radar. The red line denotes the track of the seeding aircraft. The track was repeated 8 times between 00:03 and 01:29 UTC. The wind barbs indicate mean flight-level winds. From Tessendorf et al. (2019).
Figure 4. PPI scans (0.99-degree elevation angle) at 0109 UTC (left) and 0137 UTC (right) from the Packer John DOW radar. The red line denotes the track of the seeding aircraft. The track was repeated 8 times between 00:03 and 01:29 UTC. The wind barbs indicate mean flight-level winds. From Tessendorf et al. (2019).

FY2018 ACCOMPLISHMENTS

In 2018, 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:

  • refactoring the real-time cloud-seeding decision algorithm and software;
  • collaborating 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 2017-2018 winter season, along with updates to the web-based display;
  • running model simulations of cases from SNOWIE where unambiguious seeding lines were observed;
  • and comparing model simulation results with observations, such as radiometer, sounding, snow gauge, and aircraft data from SNOWIE.

An article summarizing the SNOWIE field campaign was led by Dr. Sarah Tessendorf, and has been accepted for publication in the Bulletin of the American Meteorological Society (BAMS).  Another manuscript, led by Dr. Jeff French, was published in FY18 that provided the first direct evidence of seeding effects on ice nucleation and precipitation formation as observed in a few of the SNOWIE IOPs.   SNOWIE modeling simulations revealed a strong sensitivity of the simulated seeding effect to the amount of background ice produced by the model.  Multiple ice nucleation schemes and background aerosol levels were simulated to quantify this sensitivity and determine which configuration best replicated the observed conditions. Analyses to improve the model in this regard is underway and will be a major focus for FY19.

FY2019 PLANS

  • Conduct additional data analysis and model simulations from the SNOWIE field project and collaborate with SNOWIE university PIs to perform analysis on high priority cases
  • Perform detailed case study simulations and analyses to improve the cloud seeding model, using cases from SNOWIE and pre-SNOWIE, especially with regard to ice production in the model
  • Publish journal papers on the major findings from these studies.