Medicine Bow and Sierra Madre Ranges

Overview

Figure 1. A map of Wyoming with coarse representation of topography and major river basins. Yellow areas denote the five mountain ranges under study related to winter orographic cloud seeding programs: Medicine Bow, Sierra Madre, Wind River, Salt River/Wyoming, and Bighorn Ranges.

Figure 1. A map of Wyoming with coarse representation of topography and major river basins. Yellow areas denote the five mountain ranges under study related to winter orographic cloud seeding programs: Medicine Bow, Sierra Madre, Wind River, Salt River/Wyoming, and Bighorn Ranges.

Given the results of the WWMPP, the WWDC decided to fund a study to develop a final design for operational cloud seeding in the Medicine Bow and Sierra Madre Ranges in southeast Wyoming.  RAL leads this program with collaboration from WMI and Heritage Environmental Consultants (HEC). This project began in June 2015 and highlights from the analyses conducted in FY16 are presented below.  The results were submitted in a draft report to the WWDC in early FY17.

A climatological analysis indicated that the predominant wind regime is westerly and western regions of both mountain ranges were shown to have the most frequent occurrence of seedable conditions for both ground and airborne techniques. In order to test a wide variety of program design options based upon results of the climatological analysis, several groups of potential ground-based generator sites were established (see Figure 2).

Figure 2. Topography map of the Medicine Bow and Sierra Madre Ranges (m) illustrating the locations of nine ground-based generator design groups.

Figure 2. Topography map of the Medicine Bow and Sierra Madre Ranges (m) illustrating the locations of nine ground-based generator design groups.

Four cases were selected from the WWMPP Randomized Statistical Experiment (RSE) to represent a range of typical seeding conditions in the Sierra Madre and Medicine Bow region in order to investigate the potential designs of a ground-based seeding program using the NCAR WRF-WxMod® model. WRF-WxMod simulations of these four cases showed that supercooled liquid water (SLW) was present in both ranges throughout the simulations in all cases, which was a prerequisite for precipitation enhancement via seeding. The WRF-WxMod simulations of ground seeding showed that seeding depleted SLW in a shallow layer close to the terrain and increased precipitation over the mountain.  The simulations also indicated that seeding simulated using all six of the Sierra Madre generator groups, including the two upwind groups (E–F), produced the greatest precipitation increases in both ranges for most of the cases tested. The airborne seeding test simulations showed that, airborne seeding for a period of about two hours was shown to produce nearly similar simulated seeding effects to that from ground seeding (compare RUN15 and RUN16 in Figure 3).

Figure 3. Change in precipitation (mm) due to simulated cloud seeding for model simulations using only Sierra Madre Groups A–F (RUN15) compared to two hours of simulated airborne seeding (RUN16) in the 13 January 2014 case.

Figure 3. Change in precipitation (mm) due to simulated cloud seeding for model simulations using only Sierra Madre Groups A–F (RUN15) compared to two hours of simulated airborne seeding (RUN16) in the 13 January 2014 case.

This project demonstrated a new method for estimating streamflow changes due to seeding impacts on precipitation using the WRF-Hydro hydrological model, coupled with the results of the WRF-WxMod simulations from the WWMPP.  This WRF-Hydro simulation method directly ingested the timing, spatial distribution, and magnitude of the simulated seeding effect from cloud seeding simulations as forcing into WRF-Hydro over two water years from the WWMPP. These hydrological simulations indicated that the simulated cloud seeding yielded an additional 5,000–7,750 acre-feet of streamflow across the study region (see Figure 4). It should be noted, however, that at the present time this simulation represents only two years of simulated seeding cases from the WWMPP, which may not be representative of a longer-term average.  Moreover, the seeding criteria in the WWMPP were fairly strict and RSE cases were limited to only 4 hours of seeding, so seeding impacts on streamflow from an operational program that has no time limit on seeding periods, for example, could be greater than these results imply.  Similar methods should be used to evaluate such impacts on streamflow going forward.

Figure 4. WRF-Hydro simulation results from water year 2010: difference between seeded and unseeded snow water equivalent (SWE) for 1 May 2010 (colored), along with accumulated precipitation difference (mm; contour) on the left, and total accumulated streamflow differences (AF) for the 2010 water year from the non-seeded to seeded simulation by basin on the right.  The basins shown in the right panel are outlined in thick black lines on the left for reference.

Figure 4. WRF-Hydro simulation results from water year 2010: difference between seeded and unseeded snow water equivalent (SWE) for 1 May 2010 (colored), along with accumulated precipitation difference (mm; contour) on the left, and total accumulated streamflow differences (AF) for the 2010 water year from the non-seeded to seeded simulation by basin on the right.  The basins shown in the right panel are outlined in thick black lines on the left for reference.

A study to evaluate the cloud seeding model by simulating all 118 RSE cases from the WWMPP is underway.  In FY16, the design of this study was developed and focuses on an ensemble modeling approach to better address uncertainties in the model. A set of 96 total simulations will be conducted for each RSE case: 24 serving as control simulations and 72 seeding simulations. The 72-member seeding ensemble will be used to address the seeding process uncertainties in the model.  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.<

Contact

Please direct questions/comments about this page to:

Sarah Tessendorf

Proj Scientist III

email