• Bangsund, D., and L. Leistritz, 2009: Economic impacts of cloud seeding on agricultural crops in North Dakota. North Dakota Atmospheric Resource Board Rep., 43 pp.

  • Bangsund, D., and N. Hodur, 2019: Economic impacts of cloud seeding on agricultural crops in North Dakota. Agribusiness and Applied Economics Rep. 791, 60 pp., https://doi.org/10.22004/ag.econ.291806.

    • Crossref
    • Export Citation
  • Broughel, J., and W. Valdivia, 2018: Three approaches to the social discount rate. Mercatus Symp., Arlington, VA, Mercatus Center at George Mason University, https://www.mercatus.org/publications/regulation/three-approaches-social-discount-rate.

  • Burgess, D. F., 2018: The appropriate measure of the social discount rate and its role in the analysis of policies with long-run consequences. Mercatus Symp., Arlington, VA, Mercatus Center at George Mason University, https://www.mercatus.org/system/files/burgess_-_mercatus_research_-_the_appropriate_measure_of_the_social_discount_rate_and_its_role_in_the_analysis_of_policies_with_long-run_consequences_-_v1.pdf.

    • Crossref
    • Export Citation
  • Butchbaker, A. F., 1970: Results of the Bowman-Slope hail suppression program. Farm Res., 27 (5), 1116.

  • Changnon, S. A., 1962: Areal frequencies of hail and thunderstorm days in Illinois. Mon. Wea. Rev., 90, 519524, https://doi.org/10.1175/1520-0493(1962)090<0519:AFOHAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Changnon, S. A., 1967: Areal-temporal variations of hail intensity in Illinois. J. Appl. Meteor., 6, 536541, https://doi.org/10.1175/1520-0450(1967)006<0536:ATVOHI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Changnon, S. A., 1977: On the status of hail suppression. Bull. Amer. Meteor. Soc., 58, 2028, https://doi.org/10.1175/1520-0477(1977)058<0020:OTSOHS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Changnon, S. A., and G. E. Stout, 1967: Crop-hail intensities in central and northwest United States. J. Appl. Meteor., 6, 542548, https://doi.org/10.1175/1520-0450(1967)006<0542:CHIICA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Che, Y., H. Feng, and D. A. Hennessy, 2020: Recency effects and participation at the extensive and intensive margins in the U.S. Federal Crop Insurance Program. Geneva Pap. Risk Insur. Issues Pract., 45, 5285, https://doi.org/10.1057/s41288-019-00147-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crow, E. L., A. B. Long, J. E. Dye, and A. J. Heymsfield, 1979: Results of a randomized hail suppression experiment in northeast Colorado. Part II: Surface data base and primary statistical analysis. J. Appl. Meteor., 18, 15381558, https://doi.org/10.1175/1520-0450(1979)018<1538:ROARHS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hakala, K., L. Jauhiainen, S. J. Himanen, R. Rotter, T. Salo, and H. Kahiluoto, 2012: Sensitivity of barley varieties to weather in Finland. J. Agric. Sci., 150, 145160, https://doi.org/10.1017/S0021859611000694.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hausle, E. A., 1972: Potential economic values of weather modification on Great Plains grasslands. J. Range Manage., 25, 9295, https://doi.org/10.2307/3896792.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, J. E., R. C. Coon, and J. W. Enz, 1989: Economic benefits of crop-hail reduction efforts in North Dakota. Agricultural Economics Rep. 247, 29 pp., https://www.dwr.nd.gov/arb/ndcmp/pdfs/EconBen_CropHailRed_1989.pdf.

  • Klink, K., J. J. Wiersma, C. J. Crawford, and D. D. Stuthman, 2014: Impacts of temperature and precipitation variability in the northern plains of the United States and Canada on the productivity of spring barley and oat. Int. J. Climatol., 34, 28052818, https://doi.org/10.1002/joc.3877.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lanning, S. P., K. Kephart, G. R. Carlson, J. E. Eckhoff, R. N. Stougaard, D. M. Wichman, J. M. Martin, and L. E. Talbert, 2010: Climatic change and agronomic performance of hard red spring wheat from 1950 to 2007. Crop Sci., 50, 835841, https://doi.org/10.2135/cropsci2009.06.0314.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lichtenberg, E., and D. Zilberman, 1986: The econometrics of damage control: Why specification matters. Amer. J. Agric. Econ., 68, 261273, https://doi.org/10.2307/1241427.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miller, J. R., and M. J. Fuhs, 1987: Results of hail suppression efforts in North Dakota as shown by crop hail insurance data. J. Wea. Modif., 19, 4549.

    • Search Google Scholar
    • Export Citation
  • Miller, J. R., E. I. Boyd, R. A. Schleusener, and A. S. Dennis, 1975: Hail suppression data from western North Dakota, 1969–1972. J. Appl. Meteor., 14, 755762, https://doi.org/10.1175/1520-0450(1975)014<0755:HSDFWN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moore, M. A., and A. R. Vining, 2018: The social rate of time preference and the social discount rate. Mercatus Symp., Arlington, VA, Mercatus Center at George Mason University, https://www.mercatus.org/system/files/moore_and_vining_-_mercatus_research_-_a_social_rate_of_time_preference_approach_to_social_discount_rate_-_v1.pdf.

    • Crossref
    • Export Citation
  • Newell, H. E., 1966: A recommended national program in weather modification. Interdepartmental Committee for Atmospheric Science Rep. 10a, 97 pp., https://ntrs.nasa.gov/search.jsp?R=19680002906.

  • Rivera, J. A., F. Otero, E. N. Tamayo, and M. Silva, 2020: Sixty years of hail suppression activities in Mendoza, Argentina: Uncertainties, gaps in knowledge and future perspectives. Front. Environ. Sci., 8, 45, https://doi.org/10.3389/fenvs.2020.00045.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rose, R. L., and T. C. Jameson, 1986: Evaluation studies of long-term hail damage reduction programs in North Dakota. J. Wea. Modif., 18, 1720.

    • Search Google Scholar
    • Export Citation
  • Schlenker, W., and M. J. Roberts, 2009: Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. Proc. Natl. Acad. Sci. USA, 106, 15 59415 598, https://doi.org/10.1073/pnas.0906865106.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schleusener, R. A., and P. C. Jennings, 1959: An energy method for relative estimates of hail intensity. Bull. Amer. Meteor. Soc., 41, 372376, https://doi.org/10.1175/1520-0477-41.7.372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, M. D., and D. W. Langerud, 2011: Operational improvement on the North Dakota cloud modification project. J. Wea. Modif., 43, 8488.

    • Search Google Scholar
    • Export Citation
  • Setter, T. L., and I. Waters, 2003: Review of prospects for germplasm improvement for waterlogging tolerance in wheat, barley and oats. Plant Soil, 253, 134, https://doi.org/10.1023/A:1024573305997.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, P. L., J. R. Miller, and P. W. Mielke, 1987: An exploratory study of crop-hail insurance data for evidence of seeding effects in North Dakota. Consortium for Atmospheric Resources Development Rep. SDSMT/IAS/R-87/01, 25 pp., https://www.dwr.nd.gov/arb/ndcmp/pdfs/CARD_ExplStudyCropHailData_1987.pdf.

  • Smith, P. L., R. L. Johnson, D. L. Priegnitz, and P. W. Mielke, 1992: A target-control analysis of wheat yield data for the North Dakota cloud modification project region. J. Wea. Modif., 24, 98105.

    • Search Google Scholar
    • Export Citation
  • Smith, P. L., R. L. Johnson, and D. L. Priegnitz, 1997: An exploratory analysis of crop hail insurance data for evidence of cloud seeding effects in North Dakota. J. Appl. Meteor., 36, 463473, https://doi.org/10.1175/1520-0450(1997)036<0463:AEAOCH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sonka, S. T., and C. W. Potter, 1977: Evaluation of potential farmers benefits from hail suppression. West. J. Agric. Econ., 1, 176180.

    • Search Google Scholar
    • Export Citation
  • Swanson, E. R., F. A. Huff, and S. A. Changnon, 1972: Potential benefits of weather modification for Illinois agriculture. Ill. Agric. Econ., 12, 3136, https://doi.org/10.2307/1348769.

    • Search Google Scholar
    • Export Citation
  • Tessendorf, S. A., 2019: A transformational approach to winter orographic weather modification research: The SNOWIE project. Bull. Amer. Meteor. Soc., 100, 7192, https://doi.org/10.1175/BAMS-D-17-0152.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • USDA Risk Management Agency, 2019: North Dakota crop insurance: State profile. https://www.rma.usda.gov/en/RMALocal/North-Dakota/State-Profile/2019.

  • Weather Modification Association, 2009: WMA position statement on the environmental impact of using silver iodide as a cloud seeding agent. WMA Doc., 7 pp., http://weathermod.org/wp-content/uploads/2018/03/EnvironmentalImpact.pdf.

  • Weather Modification International, 2019: North Dakota Cloud Modification Project 2019 final operations report. North Dakota Atmospheric Resource Board Rep., 67 pp., https://www.dwr.nd.gov/arb/ndcmp/pdfs/finalreport.pdf.

  • Wiersma, J. J., 2018: Late planting spring small grains. https://extension.umn.edu/planting-small-grains/late-planting-spring-small-grains.

  • Wiersma, J. J., and J. K. Ransom, 2005: The Small Grains Field Guide. University of Minnesota Extension Service, 158 pp.

  • Xu, Z., D. A. Hennessy, K. Sardana, and G. Moschini, 2013: The realized yield effect of genetically engineered crops: U.S. maize and soybean. Crop Sci., 53, 735745, https://doi.org/10.2135/cropsci2012.06.0399.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 255 255 60
Full Text Views 47 47 11
PDF Downloads 59 59 13

Cloud Seeding and Crops Yields: Evaluation of the North Dakota Cloud Modification Project

View More View Less
  • 1 a Independent Researcher, Springfield, Virginia
  • | 2 b Department of Agricultural, Food and Resource Economics, Michigan State University, East Lansing, Michigan
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

The North Dakota Cloud Modification Project was established in 1951 to reduce severe hail damage and increase precipitation in specific counties in North Dakota. Every year, participating counties receive cloud-seeding treatment during the months of June, July, and August. Although some atmospheric studies have examined the efficacy of the treatment, few have used statistical procedures to determine how the program affected crop yields and crop losses. We use the panel nature of historical cloud-seeding participation and crop data to estimate a two-way fixed-effects regression with county-specific time trends to examine the effect of cloud seeding on wheat and barley yields. In addition, we use federal crop insurance data to estimate the effect of cloud seeding on losses for those same crops. Our evaluation indicates that the cloud-seeding program had significant positive effects on crop yields and improved loss ratios.

Significance Statement

The North Dakota Cloud Modification Project was established in 1951 to reduce severe hail damage and increase precipitation in specific counties in North Dakota. Every year, participating counties receive cloud-seeding treatment during the months of June, July, and August. We use the historical cloud-seeding participation to estimate the effect of cloud seeding on wheat and barley yields. In addition, we estimate the effect of cloud seeding on insurance losses for those same crops. Our evaluation indicates that the cloud-seeding program had significant positive effects on crop yields and improved loss ratios. The examination offers new evidence about the effectiveness of hail suppression through cloud seeding.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mark Skidmore, mskidmor@msu.edu

Abstract

The North Dakota Cloud Modification Project was established in 1951 to reduce severe hail damage and increase precipitation in specific counties in North Dakota. Every year, participating counties receive cloud-seeding treatment during the months of June, July, and August. Although some atmospheric studies have examined the efficacy of the treatment, few have used statistical procedures to determine how the program affected crop yields and crop losses. We use the panel nature of historical cloud-seeding participation and crop data to estimate a two-way fixed-effects regression with county-specific time trends to examine the effect of cloud seeding on wheat and barley yields. In addition, we use federal crop insurance data to estimate the effect of cloud seeding on losses for those same crops. Our evaluation indicates that the cloud-seeding program had significant positive effects on crop yields and improved loss ratios.

Significance Statement

The North Dakota Cloud Modification Project was established in 1951 to reduce severe hail damage and increase precipitation in specific counties in North Dakota. Every year, participating counties receive cloud-seeding treatment during the months of June, July, and August. We use the historical cloud-seeding participation to estimate the effect of cloud seeding on wheat and barley yields. In addition, we estimate the effect of cloud seeding on insurance losses for those same crops. Our evaluation indicates that the cloud-seeding program had significant positive effects on crop yields and improved loss ratios. The examination offers new evidence about the effectiveness of hail suppression through cloud seeding.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mark Skidmore, mskidmor@msu.edu
Save