The role of climate normals in crop specific weather forecasts. Department of Geography, Western Michigan University, Kalamazoo, MI, USA 2
|
|
- Cameron Rogers
- 5 years ago
- Views:
Transcription
1 The role of climate normals in crop specific weather forecasts K.M. Baker 1, J. Williams 2, T.L. Lake 2 and W.W. Kirk 3 1 Department of Geography, Western Michigan University, Kalamazoo, MI, USA 2 Department of Computer Science, Western Michigan University, Kalamazoo, MI, USA 3 Department of Plant Pathology, Michigan State University, East Lansing, MI, USA kathleen.baker@wmich.edu Abstract Crop specific weather forecasts for risk advisories in the US have been developed for a number of crops. We take the first steps toward increasing transferability of models across regions and crop systems by reducing the overall number of model inputs and substituting readily available climate data for spatial relationship variables which had to be individually calculated regionally in previous incarnations. We use a rigorously tested potato late blight model from the north central US for our analysis. Models that incorporate climate normals produce statistically similar results to models that use spatio-temporal markers. The relationship between models that incorporate climatology and those that do not varies depending on forecast length and the month of the forecast. Keywords: Artificial neural networks, climatology, plant disease, potato late blight Introduction One of the key hopes for research in the development of synoptic weather forecasting for crop specific disease risk is that results from models trained and tested at the regional scale will have widespread applications across spatial regions, and possibly across crop systems. So far, however, forecast development has been specific to a single crop and region. Weather-based prediction models have been used to estimate environmental conditions that are favorable for epidemic risk, and fungicide recommendations appropriate to that risk for more than 50 years (Beaumont, 1947; Cook, 1949; Wallin, 1960). Forecast models work to limit grower expenditures and reduce the amount of chemical released to the environment while achieving optimal control of disease. The incorporation of extended range forecast data into disease risk systems has rendered these systems even more valuable in recent years by providing prediction of risk conditions up to several days in advance of their occurrence. Baker et al. (2007) developed an extended range forecasting model to predict potato late blight disease risk up to five days in the future now in service at neuroweather.php. A number of economically important crops, in addition to potato, rely heavily on the use of fungicide application as the primary management strategy to control diseases and produce high quality marketable produce. Many plant pathogens have multiple crop hosts and similar EFITA/WCCA
2 temperature and relative humidity requirements for disease initiation. Thus, the extended range forecasting models which have been created specifically for late blight risk management in Michigan have far wider implications for crop diseases in general. In order to increase transferability of forecasting models across regions and crop systems the overall number of model inputs must be reduced and regionally unique variables must be eliminated. Using a rigorously tested potato late blight model from the north central US, we compare forecast models that use readily available climate normals to replace spatial relationship variables in reduced variable models. Spatial relationship variables were individually calculated by regions in previous incarnations and limited the widespread applicability of results. Methods Extended range forecast model output statistics (MOS) including 192 hour maximum and minimum daily temperatures have been produced by the National Weather Service (NWS) since 1994 with the Global Forecast System (GFS) numerical model. Since 2003, improvements to NWS forecasting accuracy have dramatically improved the usefulness of this data for use in agricultural and environmental modeling (Carrol & Maloney, 2004). Baker and Kirk (2007) developed a method to derive hourly microclimate variables associated with potato late blight risk from the available MOS produced by the NWS. This data was then fed into an artificial neural network (ANN) computer algorithm which generated accurate predictions of late blight disease risk up to five days in the future. Accuracy of predictions for all stations and years was examined through comparison of predicted potato late blight disease severity values with those computed based on the Unedited Local Climatological Data (ULCD). Forecast accuracy was significantly higher than expected values based on climate normals. A revised version of the model was made available online for growers use during the 2010 growing season (Wharton et al., 2008). The model relied on 48 input variables described previously (Baker & Kirk, 2007), including spatial relationship models. Extensive testing of network representation, learning algorithm, variable representation, ANN platforms, training set characteristics, normalization and simplification of inputs resulted in a much more efficient and more accurate base model (results not shown here). The final improved base potato late blight model used a resilient propagation (JE-Rprop) learning function in the JavaNNS software package. The model was trained on 80 percent of five day forecast data from growing seasons (May 1 to Sept 30) for 45 NWS forecast locations in Michigan. Accuracy of predictions was examined through comparison with risk computed based on the Unedited Local Climatological Data (ULCD) which records the actual weather which took place on a forecast day. The model was validated on the additional 20 percent of those seasons. Long term model accuracy was assessed by testing the 7 growing seasons from Variables were limited at estimated maximum and minimum values and normalized within the range 0 to 1. The final limited base data set of 10 variables (Table 1) was supplemented by 4 climate normal variables or 12 spatial cluster variables and a month variable. The accuracy of models was compared using a paired t-test across stations and years (n=314). 494 EFITA/WCCA 11
3 Table 1. Variables used in ANN generated crop specific forecast models, using potato late blight as a test case. Base Model Julian Day Minimum Temperature Cloud Cover - AM Cloud Cover - PM Quantity of Precip - AM Quantity of Precip - PM Over RH Threshold - Min Over RH Threshold - Max Minimum Risk Value Maximum Risk Value Climatology Model Normal Max Temp Normal Min Temp Normal Avg Temp Normal Total Precip Spatio-Temporal Model Spatial Markers Month Results Accuracy of long term results from the climatology model were remarkably similar to those of the spatio-temporal model (Table 2). For most daily forecasts, from hours into the future and for most months of the growing season the two models were statistically equivalent. The spatio-temporal model was statistically more accurate for June forecasts of moderate range (48-72 hours). Table 2. Differences in forecast accuracy between climatology (C) and spatio-temporal models (S). The model represented represents the model of greatest accuracy. (=) is used when the models were statistically similar (p = 0.05). 24hr 48hr 72hr 96hr 120hr All Overall = = = = = = May = = = = = = June = S S = = S July = C = = = = August = = = = = = September = = = = = = When compared with the base model the climatology model was more accurate as forecast length increased (Table 3). There were no significant differences between the base model accuracy and climatology model accuracy in the 24 hour forecasts except in September. By 120 hours, the climatology model was significantly more accurate for all months. When the five forecast days were combined, the base model was equivalent to the climatology only during the month of August. EFITA/WCCA
4 Overall accuracies of the 3 models (Table 4) that the climatology model greatly improves the minimum annual station forecast accuracy by over 10 percent from the spatio-temporal model. The climatology model has a greater maximum and minimum annual station forecast accuracy than the base model. Table 3. Differences in forecast accuracy between climatology (C) and the base model (B). The model represented represents the model of greatest accuracy. (=) is used when the models were statistically similar (p=0.05). 24hr 48hr 72hr 96hr 120hr All Overall = C C C C C May = = = C C C June = C = C C C July = = C C C C August = = = = C = September C C C C C C Table 4. Overall hr accuracies for the three potato late blight forecast models by station and year. Min Max Mean SD Climatology Spatio-Temporal Base Discussion For most of the forecast days and for most of the growing season, no statistical difference was found between the climatology and spatial-temporal models. The impact of normal climate characteristics is equivalent to that of clustering the locations by spatial similarity and breaking up the season by months. This equivalence allows for flexibility in model development depending on data availability. In most US locations, 30-year climate normals are readily available. Developing models with climate normals, maximizes transferability of crop specific models to other regions. In areas for which climate data is not distributed, including non-us locations, geographic clusters and temporal markers can easily be used instead. Although it makes logical sense that climate and geography should be closely linked, to our knowledge no previous study has investigated their equivalence for forecast purposes. As length of forecast increases, or time from the forecast is made until it is applicable increases, the significance of climate normals increases. This result is expected given the fact that weather forecasts in general decrease significantly in accuracy with length and eventually 496 EFITA/WCCA 11
5 are only able to forecast climatology at about 8 days from the day the forecast is made. For 24 hour forecasts, input values are more highly accurate and so generalization of the regional climate adds nothing to the model. August is the only month when the climate model is not more accurate than the base model for the complete 5 day forecast. This is probably because potato late blight risk during August in this region is generally driven by summer storms moving through in a fairly unpredictable spatial pattern from year to year. The next step of this research is to use the regionally developed, north central US potato late blight forecasts with limited variable set and climate normals to train and test data from other regions. This process is currently ongoing. Some measure of transferability of regional forecasts to other regions will be a huge step forward for the crop disease risk modeling community. The idea of transferability of model characteristics from one crop disease to another is still in its infancy, but many crop diseases result from similar temperature and relative humidity conditions. Variables that are significant in the prediction of temperature-humidity dependent systems should be similar among applications. Preliminary development of forecast models for Fusarium head blight of barley in the Great Plains of the US (Bondalapati et al., 2009) has determined a significant variable set very similar to the climatology model for potato late blight. Acknowledgements Funding provided by USDA RAMP Co-PIs: Jeffrey Stein, South Dakota State U; William Kirk, Michigan State U; Phillip Wharton, U Idaho; Mark Boudreau, U Georgia; Dennis Todey, South Dakota State U. Special thanks to Jason Smith, Douglas Rivet, and Dr. Robert Trenary at Western Michigan University for their technical assistance throughout the project. EFITA/WCCA
6 References Baker, K.M. and Kirk, W.W Comparative analysis of models for integration of extended range synoptic forecast data into potato late blight risk systems. Computers and Electronics in Agriculture, 57: Baker, K.M., Wharton, P. and Kirk, W.W Inclusion of synoptic weather forecast models in decision support systems for agriculture. In: proceedings of MODSIM 07: International Congress on Modeling and Simulation, Dec, Christchurch, New Zealand. Beaumont, A The dependence on the weather of the dates of outbreak of potato late blight. Transactions of the British Mycological Society. 31; Bondalapati, K.D., J.M. Stein, K.M. Baker, and Chen, D.G Using Forecasted Weather Data and Neural Networks for DON Prediction in Barley. Poster: Proceedings of the 2009 National Fusarium Head Blight Forum, Orlando, FL. Canty, S., Clark, A., Mundell, J., Walton, E., Ellis, D., and Van Sanford, D. (Eds.), University of Kentucky, Erlanger, KY. pp Carrol, K.L., and J.C. Maloney, J.C Improvements in extended-range temperature and probability of precipitation guidance. Symposium on the 50th Anniversary of Operational Numerical Weather Prediction, College Park, MD, Amer. Meteor. Soc. Cook, H Forecasting late blight epiphytotics of potatoes and tomatoes. Journal of Agricultural Research 78; Wallin, J.R., and Schuster, M.L Forecasting potato late blight in western Nebraska. Plant Disease Reporter 44; Wharton, P.S., Kirk, W.W., Baker, K.M., and Duynslager, L A web-based interactive system for risk management of Phytophthora infestans in potato canopies in Michigan. Computers and Electronics in Agriculture, 61: EFITA/WCCA 11
Regional Variability in Crop Specific Synoptic Forecasts
Regional Variability in Crop Specific Synoptic Forecasts Kathleen M. Baker 1 1 Western Michigan University, USA, kathleen.baker@wmich.edu Abstract Under climate change scenarios, growing season patterns
More informationVALIDATION AND ADAPTATION OF THE "BLITECAST" MODEL FOR PREDICTING DEVELOPMENT OF POTATO LATE BLIGHT IN OREGON
VALIDATION AND ADAPTATION OF THE "BLITECAST" MODEL FOR PREDICTING DEVELOPMENT OF POTATO LATE BLIGHT IN OREGON Clinton C. Shock and Brad Coen, Malheur Experiment Station Lynn Jensen, Malheur County Extension
More informationEVALUATION OF PEANUT DISEASE DEVELOPMENT FORECASTING. North Carolina State University, Raleigh, North Carolina
P244 EVALUATION OF PEANUT DISEASE DEVELOPMENT FORECASTING John A. McGuire* 1, Mark S. Brooks 1, Aaron P. Sims 1, Barbara Shew 2, and Ryan Boyles 1 1 State Climate Office of North Carolina, 2 Department
More informationPREDICTING THE ONSET AND SEVERITY OF POTATO LATE BLIGHT IN OREGON
PREDICTING THE ONSET AND SEVERITY OF POTATO LATE BLIGHT IN OREGON Clinton C. Shock, Cedric A. Shock, and Lamont D. Saunders Malheur Experiment Station Lynn Jensen Malheur County Extension Service Oregon
More informationVolume XIV, Number 1 January 6, 2014
Research & Extension for the Potato Industry of Idaho, Oregon, & Washington Andrew Jensen, Editor. ajensen@potatoes.com; 208-939-9965 www.nwpotatoresearch.com Volume XIV, Number 1 January 6, 2014 Accuracy
More informationPREDICTING THE SPREAD AND SEVERITY OF POTATO LATE BLIGHT (PHYTOPHTHORA INFES TANS) IN OREGON, 2003
PREDCTNG THE SPREAD AND SEVERTY OF POTATO LATE BLGHT (PHYTOPHTHORA NFES TANS) N OREGON, 23 Clinton C. Shock, Cedric Shock, Lamont Saunders, and Susan Sullivan Malheur Experiment Station Lynn Jensen Malheur
More informationEXAMINATION OF MODELS FOR THE PREDICTION OF THE ONSET AND SEVERITY OF POTATO LATE BLIGHT IN OREGON
EXAMINATION OF MODELS FOR THE PREDICTION OF THE ONSET AND SEVERITY OF POTATO LATE BLIGHT IN OREGON Clinton C. Shock, Cedric A. Shock, Lamont D. Saunders, and Brad Coen Malheur Experiment Station Lynn Jensen
More informationFusarium Head Blight (FHB)
Fusarium Head Blight (FHB) FHB is a Fungal disease of cereal crops that affects kernel development 1999 declared a pest under the Agricultural Pest Act 2002 Alberta released Fusarium Risk Management Plan
More informationPREDICTING THE SPREAD AND SEVERITY OF POTATO LATE BLIGHT (PHYTOPHTHORA INFESTANS) IN OREGON, 2002
PREDICTING THE SPREAD AND SEVERITY OF POTATO LATE BLIGHT (PHYTOPHTHORA INFESTANS) IN OREGON, 22 Clint Shock, Cedric Shock, Lamont Saunders, and Katie Kimberling Malheur Experiment Station Lynn Jensen Malheur
More informationGuide to the Late Blight Decision Support System (DSS) For Potatoes and Tomatoes
Guide to the Late Blight Decision Support System (DSS) For Potatoes and Tomatoes 1 Setting up an Account: The first step in using the Decision Support System (DSS) is to obtain an account. Laura Joseph
More informationVariability of Reference Evapotranspiration Across Nebraska
Know how. Know now. EC733 Variability of Reference Evapotranspiration Across Nebraska Suat Irmak, Extension Soil and Water Resources and Irrigation Specialist Kari E. Skaggs, Research Associate, Biological
More informationpest management decisions
Using Enviroweather to assist pest management decisions Emily Pochubay 2014 Integrated Pest Management Academy February 19, 2014 Okemos, MI www.enviroweather.msu.edu Enviro-weather An online resource that
More informationSPC Fire Weather Forecast Criteria
SPC Fire Weather Forecast Criteria Critical for temperature, wind, and relative humidity: - Sustained winds 20 mph or greater (15 mph Florida) - Minimum relative humidity at or below regional thresholds
More informationMidwest and Great Plains Climate- Drought Outlook 19 November 2015
Midwest and Great Plains Climate- Drought Outlook 19 November 2015 Dr. Dennis Todey State Climatologist South Dakota State Univ. dennis.todey@sdstate.edu 605-688-5678 Photo taken Feb 19, 2013 SDSU Campus
More informationNational Wildland Significant Fire Potential Outlook
National Wildland Significant Fire Potential Outlook National Interagency Fire Center Predictive Services Issued: September, 2007 Wildland Fire Outlook September through December 2007 Significant fire
More informationCustomWeather Statistical Forecasting (MOS)
CustomWeather Statistical Forecasting (MOS) Improve ROI with Breakthrough High-Resolution Forecasting Technology Geoff Flint Founder & CEO CustomWeather, Inc. INTRODUCTION Economists believe that 70% of
More information15.11 THE ADVANTAGES OF INTERACTIVE ANALYSIS TOOLS TO DETERMINE DIFFERENCES BETWEEN CO-LOCATED MULTIRESOLUTION, TEMPORALLY DYNAMIC DATA SETS
15.11 THE ADVANTAGES OF INTERACTIVE ANALYSIS TOOLS TO DETERMINE DIFFERENCES BETWEEN CO-LOCATED MULTIRESOLUTION, TEMPORALLY DYNAMIC DATA SETS Phillip A. Zuzolo*, Alfred M. Powell, Jr., Steven G. Hoffert,
More informationImpacts of the April 2013 Mean trough over central North America
Impacts of the April 2013 Mean trough over central North America By Richard H. Grumm National Weather Service State College, PA Abstract: The mean 500 hpa flow over North America featured a trough over
More informationMidwest and Great Plains Climate- Drought Outlook 20 April 2017
Midwest and Great Plains Climate- Drought Outlook 20 April 2017 Dr. Dennis Todey Director USDA Midwest Climate Hub Nat l Lab. for Ag. and Env. Ames, IA dennis.todey@ars.usda.gov 515-294-2013 Photo: BJ
More informationSEPTEMBER 2013 REVIEW
Monthly Long Range Weather Commentary Issued: October 21, 2013 Steven A. Root, CCM, President/CEO sroot@weatherbank.com SEPTEMBER 2013 REVIEW Climate Highlights The Month in Review The average temperature
More informationDoug Kluck NOAA Kansas City, MO National Center for Environmental Information (NCEI) National Integrated Drought Information System (NIDIS)
National Integrated Drought Information System (NIDIS) for the Missouri River Basin Drought Early Warning Information System (DEWS) & Runoff Trends in the Missouri Basin & Latest Flood Outlook Doug Kluck
More informationApplication of the Integrated Aerobiology Modeling System to Soybean Rust Forecasting in 2006
Application of the Integrated Aerobiology Modeling System to Soybean Rust Forecasting in 2006 Scott A. Isard Penn State University & Joseph M. Russo ZedX Inc. Integrated Aerobiology Modeling System (IAMS)
More informationMinnesota s Climatic Conditions, Outlook, and Impacts on Agriculture. Today. 1. The weather and climate of 2017 to date
Minnesota s Climatic Conditions, Outlook, and Impacts on Agriculture Kenny Blumenfeld, State Climatology Office Crop Insurance Conference, Sep 13, 2017 Today 1. The weather and climate of 2017 to date
More information138 ANALYSIS OF FREEZING RAIN PATTERNS IN THE SOUTH CENTRAL UNITED STATES: Jessica Blunden* STG, Inc., Asheville, North Carolina
138 ANALYSIS OF FREEZING RAIN PATTERNS IN THE SOUTH CENTRAL UNITED STATES: 1979 2009 Jessica Blunden* STG, Inc., Asheville, North Carolina Derek S. Arndt NOAA National Climatic Data Center, Asheville,
More informationOperational MRCC Tools Useful and Usable by the National Weather Service
Operational MRCC Tools Useful and Usable by the National Weather Service Vegetation Impact Program (VIP): Frost / Freeze Project Beth Hall Accumulated Winter Season Severity Index (AWSSI) Steve Hilberg
More informationYACT (Yet Another Climate Tool)? The SPI Explorer
YACT (Yet Another Climate Tool)? The SPI Explorer Mike Crimmins Assoc. Professor/Extension Specialist Dept. of Soil, Water, & Environmental Science The University of Arizona Yes, another climate tool for
More informationP3.1 Development of MOS Thunderstorm and Severe Thunderstorm Forecast Equations with Multiple Data Sources
P3.1 Development of MOS Thunderstorm and Severe Thunderstorm Forecast Equations with Multiple Data Sources Kathryn K. Hughes * Meteorological Development Laboratory Office of Science and Technology National
More informationThe Palfai Drought Index (PaDI) Expansion of applicability of Hungarian PAI for South East Europe (SEE) region Summary
The Palfai Drought Index () Expansion of applicability of Hungarian PAI for South East Europe (SEE) region Summary In Hungary the Palfai drought index (PAI) worked out for users in agriculture and in water
More informationThe Climate of Payne County
The Climate of Payne County Payne County is part of the Central Great Plains in the west, encompassing some of the best agricultural land in Oklahoma. Payne County is also part of the Crosstimbers in the
More informationNorth Carolina Climate January 2012
North Carolina Climate January 2012 Online: http://www.nc-climate.ncsu.edu/office/newsletters North Carolina Climate, the monthly newsletter of the State Climate Office of NC, covers information on experimental
More informationMultiple-Year Droughts In Nebraska
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Drought Mitigation Center Faculty Publications Drought -- National Drought Mitigation Center 2005 Multiple-Year Droughts
More informationMidwest and Great Plains Climate- Drought Outlook 16 April 2015
Midwest and Great Plains Climate- Drought Outlook 16 April 2015 Dr. Dennis Todey State Climatologist South Dakota State Univ. dennis.todey@sdstate.edu 605-688-5141 Photo taken Feb 19, 2013 Wildfire Wind
More information5B.1 DEVELOPING A REFERENCE CROP EVAPOTRANSPIRATION CLIMATOLOGY FOR THE SOUTHEASTERN UNITED STATES USING THE FAO PENMAN-MONTEITH ESTIMATION TECHNIQUE
DEVELOPING A REFERENCE CROP EVAPOTRANSPIRATION CLIMATOLOGY FOR THE SOUTHEASTERN UNITED STATES USING THE FAO PENMAN-MONTEITH ESTIMATION TECHNIQUE Heather A. Dinon*, Ryan P. Boyles, and Gail G. Wilkerson
More informationNorth Central U.S. Climate Summary and Outlook Webinar July 21, 2016
North Central U.S. Climate Summary and Outlook Webinar July 21, 2016 Stuart Foster State Climatologist for Kentucky Department of Geography and Geology Western Kentucky University Stuart.foster@wku.edu
More information6.2 DEVELOPMENT, OPERATIONAL USE, AND EVALUATION OF THE PERFECT PROG NATIONAL LIGHTNING PREDICTION SYSTEM AT THE STORM PREDICTION CENTER
6.2 DEVELOPMENT, OPERATIONAL USE, AND EVALUATION OF THE PERFECT PROG NATIONAL LIGHTNING PREDICTION SYSTEM AT THE STORM PREDICTION CENTER Phillip D. Bothwell* NOAA/NWS/NCEP/SPC, Norman, Oklahoma 772 1.
More informationUsing NEWA Resources in a Vineyard IPM Strategy. Tim Weigle and Juliet Carroll NYS IPM Program, Cornell Cooperative Extension
Using NEWA Resources in a Vineyard IPM Strategy Tim Weigle and Juliet Carroll NYS IPM Program, Cornell Cooperative Extension Historically, control practices for vineyard pests in the eastern United States
More informationGreat Plains and Midwest Climate Outlook February 18, 2016
Great Plains and Midwest Climate Outlook February 18, 2016 Dr. Jim Angel State Climatologist Illinois State Water Survey University of Illinois jimangel@illinois.edu General Information Providing climate
More informationWeatherManager Weekly
Issue 288 July 14, 2016 WeatherManager Weekly Industries We Serve Agriculture Energy/Utilities Construction Transportation Retail Our Weather Protection Products Standard Temperature Products Lowest Daily
More informationClimate outlook, longer term assessment and regional implications. What s Ahead for Agriculture: How to Keep One of Our Key Industries Sustainable
Climate outlook, longer term assessment and regional implications What s Ahead for Agriculture: How to Keep One of Our Key Industries Sustainable Bureau of Meteorology presented by Dr Jeff Sabburg Business
More informationThe Climate of Grady County
The Climate of Grady County Grady County is part of the Central Great Plains, encompassing some of the best agricultural land in Oklahoma. Average annual precipitation ranges from about 33 inches in northern
More informationPut the Weather to Work for Your Company
SAP Data Network Put the Weather to Work for Your Company Extend the Value of Your Business and Transactional Solutions by Incorporating Weather Data 1 / 7 Table of Contents 3 Enrich Business Data with
More informationMidwest/Great Plains Climate-Drought Outlook September 20, 2018
Midwest/Great Plains Climate-Drought Outlook September 20, 2018 Brian Fuchs National Drought Mitigation Center University of Nebraska-Lincoln School of Natural Resources September 20, 2018 General Information
More informationUPPLEMENT A COMPARISON OF THE EARLY TWENTY-FIRST CENTURY DROUGHT IN THE UNITED STATES TO THE 1930S AND 1950S DROUGHT EPISODES
UPPLEMENT A COMPARISON OF THE EARLY TWENTY-FIRST CENTURY DROUGHT IN THE UNITED STATES TO THE 1930S AND 1950S DROUGHT EPISODES Richard R. Heim Jr. This document is a supplement to A Comparison of the Early
More informationMidwest/Great Plains Climate-Drought Outlook August 17, 2017
Midwest/Great Plains Climate-Drought Outlook August 17, 2017 Brian Fuchs National Drought Mitigation Center University of Nebraska-Lincoln School of Natural Resources General Information Providing climate
More informationDenver International Airport MDSS Demonstration Verification Report for the Season
Denver International Airport MDSS Demonstration Verification Report for the 2015-2016 Season Prepared by the University Corporation for Atmospheric Research Research Applications Division (RAL) Seth Linden
More informationP4.479 A DETAILED ANALYSIS OF SPC HIGH RISK OUTLOOKS,
P4.479 A DETAILED ANALYSIS OF SPC HIGH RISK OUTLOOKS, 2003-2009 Jason M. Davis*, Andrew R. Dean 2, and Jared L. Guyer 2 Valparaiso University, Valparaiso, IN 2 NOAA/NWS Storm Prediction Center, Norman,
More informationThe Kentucky Mesonet: Entering a New Phase
The Kentucky Mesonet: Entering a New Phase Stuart A. Foster State Climatologist Kentucky Climate Center Western Kentucky University KCJEA Winter Conference Lexington, Kentucky February 9, 2017 Kentucky
More informationSOUTHERN CLIMATE MONITOR
SOUTHERN CLIMATE MONITOR MARCH 2011 VOLUME 1, ISSUE 3 IN THIS ISSUE: Page 2 to 4 Severe Thunderstorm Climatology in the SCIPP Region Page 4 Drought Update Page 5 Southern U.S. Precipitation Summary for
More informationCentral Region Climate Outlook May 15, 2014
Central Region Climate Outlook May 15, 2014 Dr. Jim Angel State Climatologist IL State Water Survey University of Illinois jimangel@illinois.edu 217-333-0729 Chicago-area flooding General Information Providing
More informationUsing an Artificial Neural Network to Predict Parameters for Frost Deposition on Iowa Bridgeways
Using an Artificial Neural Network to Predict Parameters for Frost Deposition on Iowa Bridgeways Bradley R. Temeyer and William A. Gallus Jr. Graduate Student of Atmospheric Science 31 Agronomy Hall Ames,
More informationAn Online Platform for Sustainable Water Management for Ontario Sod Producers
An Online Platform for Sustainable Water Management for Ontario Sod Producers 2014 Season Update Kyle McFadden January 30, 2015 Overview In 2014, 26 weather stations in four configurations were installed
More informationSEASONAL CLIMATE OUTLOOK VALID FOR JULY-AUGUST- SEPTEMBER 2013 IN WEST AFRICA, CHAD AND CAMEROON
SEASONAL CLIMATE OUTLOOK VALID FOR JULY-AUGUST- SEPTEMBER 2013 IN WEST AFRICA, CHAD AND CAMEROON May 29, 2013 ABUJA-Federal Republic of Nigeria 1 EXECUTIVE SUMMARY Given the current Sea Surface and sub-surface
More informationDoug Kluck Regional Climate Services Director Kansas City, MO
Climate Resilience and Information: Opportunities with Tribes and the National Oceanic and Atmospheric Administration (NOAA) and Partners National Congress of American Indians Annual Convention (October
More information2012 Growing Season Weather Summary for North Dakota. Adnan Akyüz and Barbara A. Mullins Department of Soil Science October 30, 2012
2012 Growing Season Weather Summary for North Dakota Adnan Akyüz and Barbara A. Mullins Department of Soil Science October 30, 2012 Introduction The 2012 growing season (the period from April through September)
More informationThe Climate of Marshall County
The Climate of Marshall County Marshall County is part of the Crosstimbers. This region is a transition region from the Central Great Plains to the more irregular terrain of southeastern Oklahoma. Average
More information4/17/2015. Overview. Introduction to decision support systems. Introduction to decision support systems. Introduction to decision support systems
PLP 6404 Epidemiology of Plant Diseases Spring 2015 Lecture 29: Decision support systems Prof. Dr. Ariena van Bruggen Emerging Pathogens Institute and Plant Pathology Department, IFAS University of Florida
More informationClimate Change Impact on Air Temperature, Daily Temperature Range, Growing Degree Days, and Spring and Fall Frost Dates In Nebraska
EXTENSION Know how. Know now. Climate Change Impact on Air Temperature, Daily Temperature Range, Growing Degree Days, and Spring and Fall Frost Dates In Nebraska EC715 Kari E. Skaggs, Research Associate
More informationThe AIR Crop Hail Model for Canada
The AIR Crop Hail Model for Canada In 2016, the Canadian Prairie Provinces experienced one of the most active and longest hail seasons in at least 25 years. The number of hailstorms more than doubled the
More informationDECISION SUPPORT FOR FREEZE PROTECTION USING ARTIFICIAL NEURAL NETWORKS
Agricultural Outlook Forum 2005 Presented Thursday February 24, 2005 DECISION SUPPORT FOR FREEZE PROTECTION USING ARTIFICIAL NEURAL NETWORKS Ronald W. McClendon, Professor Gerrit Hoogenboom, Professor
More informationDrought and Climate Extremes Indices for the North American Drought Monitor and North America Climate Extremes Monitoring System. Richard R. Heim Jr.
Drought and Climate Extremes Indices for the North American Drought Monitor and North America Climate Extremes Monitoring System Richard R. Heim Jr. NOAA/NESDIS/National Climatic Data Center Asheville,
More informationProceedings, International Snow Science Workshop, Innsbruck, Austria, 2018
RELEASE OF AVALANCHES ON PERSISTENT WEAK LAYERS IN RELATION TO LOADING EVENTS IN COLORADO, USA Jason Konigsberg 1, Spencer Logan 1, and Ethan Greene 1 1 Colorado Avalanche Information Center, Boulder,
More informationWater Year 2019 Wet or Dry?? Improving Sub-seasonal to Seasonal Precipitation Forecasting Jeanine Jones, Department of Water Resources
Water Year 2019 Wet or Dry?? Improving Sub-seasonal to Seasonal Precipitation Forecasting Jeanine Jones, Department of Water Resources Sub-Seasonal to Seasonal (S2S) Precipitation Forecasting Operational
More informationCliGen (Climate Generator) Addressing the Deficiencies in the Generator and its Databases William J Rust, Fred Fox & Larry Wagner
CliGen (Climate Generator) Addressing the Deficiencies in the Generator and its Databases William J Rust, Fred Fox & Larry Wagner United States Department of Agriculture, Agricultural Research Service
More informationWeather and Climate Summary and Forecast August 2018 Report
Weather and Climate Summary and Forecast August 2018 Report Gregory V. Jones Linfield College August 5, 2018 Summary: July 2018 will likely go down as one of the top five warmest July s on record for many
More informationthe Great Lakes Region
Climatological Trends in Michigan and the Great Lakes Region Climate Trends in Michigan and the Great Lakes Region Jeffrey A. Andresen Dept. Jeff Andresen of Geography Michigan State University Michigan
More informationEnhancing Weather Information with Probability Forecasts. An Information Statement of the American Meteorological Society
Enhancing Weather Information with Probability Forecasts An Information Statement of the American Meteorological Society (Adopted by AMS Council on 12 May 2008) Bull. Amer. Meteor. Soc., 89 Summary This
More informationProject Name: Implementation of Drought Early-Warning System over IRAN (DESIR)
Project Name: Implementation of Drought Early-Warning System over IRAN (DESIR) IRIMO's Committee of GFCS, National Climate Center, Mashad November 2013 1 Contents Summary 3 List of abbreviations 5 Introduction
More informationIdentifying Blizzards in Present and Future Climates. 3 May 2017 Climate Prediction Applications Science Workshop. Dr.
Identifying Blizzards in Present and Future Climates 3 May 2017 Climate Prediction Applications Science Workshop Dr. Aaron Kennedy Brooke Hagenhoff University of North Dakota Supported by: NSF project
More informationWhy Models Need Standards Update on AgGateway Initiative
Why Models Need Standards Update on AgGateway Initiative Joe Russo, Jean Batzer, Mark Gleason and Roger Magarey Midwest Weather Working Group 6 th Annual Meeting Austin, Texas August 9, 2013 Copyright
More informationALASKA REGION CLIMATE FORECAST BRIEFING. October 27, 2017 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE FORECAST BRIEFING October 27, 2017 Rick Thoman National Weather Service Alaska Region Today Feature of the month: West Pacific Typhoons Climate Forecast Basics Climate System Review
More informationAn Algorithm to Nowcast Lightning Initiation and Cessation in Real-time
An Algorithm to Nowcast Initiation and Cessation in Real-time An Data Mining Model Valliappa 1,2 Travis Smith 1,2 1 Cooperative Institute of Mesoscale Meteorological Studies University of Oklahoma 2 Radar
More informationThe Climate of Kiowa County
The Climate of Kiowa County Kiowa County is part of the Central Great Plains, encompassing some of the best agricultural land in Oklahoma. Average annual precipitation ranges from about 24 inches in northwestern
More informationOperational Perspectives on Hydrologic Model Data Assimilation
Operational Perspectives on Hydrologic Model Data Assimilation Rob Hartman Hydrologist in Charge NOAA / National Weather Service California-Nevada River Forecast Center Sacramento, CA USA Outline Operational
More informationWeather and Climate Summary and Forecast Summer 2017
Weather and Climate Summary and Forecast Summer 2017 Gregory V. Jones Southern Oregon University August 4, 2017 July largely held true to forecast, although it ended with the start of one of the most extreme
More informationCondition Monitoring: A New System for Drought Impacts Reporting through CoCoRaHS
Condition Monitoring: A New System for Drought Impacts Reporting through CoCoRaHS Amanda Farris Carolinas Integrated Sciences & Assessments (CISA) University of South Carolina WERA 1012 Annual Conference
More informationChanging Hydrology under a Changing Climate for a Coastal Plain Watershed
Changing Hydrology under a Changing Climate for a Coastal Plain Watershed David Bosch USDA-ARS, Tifton, GA Jeff Arnold ARS Temple, TX and Peter Allen Baylor University, TX SEWRU Objectives 1. Project changes
More informationComparing the Relationships Between Heat Stress Indices and Mortality in North Carolina
Comparing the Relationships Between Heat Stress Indices and Mortality in North Carolina Jordan Clark PhD Student CISA Research Assistant Department of Geography UNC-Chapel Hill 10/30/2018 Overview Background
More informationKANSAS CLIMATE SUMMARY August 2015
KANSAS CLIMATE SUMMARY August 2015 Cool and Dry August was drier than normal in most of the state. State-wide average precipitation was 2.80 inches or 85 percent of normal. The Northeast division of the
More informationMGC September Webinar Taking Climate Action September 22, 2016
MGC September Webinar Taking Climate Action September 22, 2016 Today s Agenda Presentations B.J. Baule, Great Lakes Integrated Sciences and Assessments Kate Madigan, Michigan Environmental Council/Michigan
More informationUnderstanding Weather and Climate Risk. Matthew Perry Sharing an Uncertain World Conference The Geological Society, 13 July 2017
Understanding Weather and Climate Risk Matthew Perry Sharing an Uncertain World Conference The Geological Society, 13 July 2017 What is risk in a weather and climate context? Hazard: something with the
More informationThe Climate of Murray County
The Climate of Murray County Murray County is part of the Crosstimbers. This region is a transition between prairies and the mountains of southeastern Oklahoma. Average annual precipitation ranges from
More informationWEATHER NORMALIZATION METHODS AND ISSUES. Stuart McMenamin Mark Quan David Simons
WEATHER NORMALIZATION METHODS AND ISSUES Stuart McMenamin Mark Quan David Simons Itron Forecasting Brown Bag September 17, 2013 Please Remember» Phones are Muted: In order to help this session run smoothly,
More informationThe Climate of Texas County
The Climate of Texas County Texas County is part of the Western High Plains in the north and west and the Southwestern Tablelands in the east. The Western High Plains are characterized by abundant cropland
More informationExperimental MOS Precipitation Type Guidance from the ECMWF Model
Experimental MOS Precipitation Type Guidance from the ECMWF Model Phillip E. Shafer David E. Rudack National Weather Service Meteorological Development Laboratory Silver Spring, MD Development Overview:
More information10.5 PROBABLISTIC LIGHTNING FORECASTS AND FUEL DRYNESS LEVEL FORECASTS IN THE GRAPHICAL FOREAST EDITOR: EXPANDED DOMAIN AND DISTRIBUTION FOR 2009
10.5 PROBABLISTIC LIGHTNING FORECASTS AND FUEL DRYNESS LEVEL FORECASTS IN THE GRAPHICAL FOREAST EDITOR: EXPANDED DOMAIN AND DISTRIBUTION FOR 2009 Chris V. Gibson 1*, and P. D. Bothwell 2, S. Sharples 3,
More informationDrought Impacts in the Southern Great Plains. Mark Shafer University of Oklahoma Norman, OK
Drought Impacts in the Southern Great Plains Mark Shafer University of Oklahoma Norman, OK Causes of Drought: Large-Scale, Stationary High Pressure Air rotates clockwise around high pressure steers storms
More informationMidwest and Great Plains Climate- Drought Outlook 20 October 2016
Midwest and Great Plains Climate- Drought Outlook 20 October 2016 Laura Edwards Acting State Climatologist SDSU Extension, Aberdeen, SD Laura.edwards@sdstate.edu 605-626-2870 Cottonwood Fire 17 Oct 2016
More informationMidwest and Great Plains Climate- Drought Outlook 21 August 2014
Midwest and Great Plains Climate- Drought Outlook 21 August 2014 Dr. Jeff Andresen State Climatologist Michigan State University andresen@msu.edu 517-432-4756 Flooding along I-696 in Warren, MI 11 AUG
More information2008 California Fire Season Outlook
2008 California Fire Season Outlook For July through October 2008 (issued 6/25/08) 1 North Ops Concerns and Implications for Management NOPS currently in a worsening drought, due to the driest spring on
More informationA sensitivity and uncertainty analysis. Ministry of the Walloon Region Agricultural Research Centre
Development of an agrometeorological model integrating leaf wetness duration estimation and weather radar data to assess the risk of head blight infection in wheat A sensitivity and uncertainty analysis
More informationSeasonal Predictions for South Caucasus and Armenia
Seasonal Predictions for South Caucasus and Armenia Anahit Hovsepyan Zagreb, 11-12 June 2008 SEASONAL PREDICTIONS for the South Caucasus There is a notable increase of interest of population and governing
More informationGreat Plains & Midwest Climate Outlook June 18, 2015
Great Plains & Midwest Climate Outlook June 18, 2015 Pat Guinan Extension/State Climatologist University of Missouri guinanp@missouri.edu 573-882-5908 Saturated Soybeans, Monroe County, MO Yellow Corn,
More informationUsing Temperature and Dew Point to Aid Forecasting Springtime Radiational Frost and/or Freezing Temperatures in the NWS La Crosse Service Area
Using Temperature and Dew Point to Aid Forecasting Springtime Radiational Frost and/or Freezing Temperatures in the NWS La Crosse Service Area WFO La Crosse Climatology Series #21 The formation of radiational
More informationClimatic Trends and Potato Late Blight Risk in the Upper Great Lakes Region
Climatic Trends and Potato Late Blight Risk in the Upper Great Lakes Region Kathleen M. Baker 1, William W. Kirk 2, 4, Jeffre M. Stein 2, and Jeffre A. Andresen 3 ADDITIONAL INDEX WORDS. potato late blight,
More information2002 Drought History in Colorado A Brief Summary
1 2002 Drought History in Colorado A Brief Summary Colorado Climate Center Roger Pielke, Sr, Director and Nolan Doesken, Research Associate Prepared by Odie Bliss & Tara Green http://climate.atmos.colostate.edu
More informationEvolving 2014 Weather Patterns. Leon F. Osborne Chester Fritz Distinguished Professor of Atmospheric Sciences University of North Dakota
Evolving 2014 Weather Patterns Leon F. Osborne Chester Fritz Distinguished Professor of Atmospheric Sciences University of North Dakota Northern Pulse Growers January 27, 2014 Minot, ND Outline Today s
More informationUSING GRIDDED MOS TECHNIQUES TO DERIVE SNOWFALL CLIMATOLOGIES
JP4.12 USING GRIDDED MOS TECHNIQUES TO DERIVE SNOWFALL CLIMATOLOGIES Michael N. Baker * and Kari L. Sheets Meteorological Development Laboratory Office of Science and Technology National Weather Service,
More informationArizona Drought Monitoring Sensitivity and Verification Analyses
Arizona Drought Monitoring Sensitivity and Verification Analyses A Water Sustainability Institute, Technology and Research Initiative Fund Project Christopher L. Castro, Francina Dominguez, Stephen Bieda
More information1. TEMPORAL CHANGES IN HEAVY RAINFALL FREQUENCIES IN ILLINOIS
to users of heavy rainstorm climatology in the design and operation of water control structures. A summary and conclusions pertaining to various phases of the present study are included in Section 8. Point
More informationEarly May Cut-off low and Mid-Atlantic rains
Abstract: Early May Cut-off low and Mid-Atlantic rains By Richard H. Grumm National Weather Service State College, PA A deep 500 hpa cutoff developed in the southern Plains on 3 May 2013. It produced a
More information