Extreme Values on Spatial Fields p. 1/1
|
|
- Imogen Blake
- 5 years ago
- Views:
Transcription
1 Extreme Values on Spatial Fields Daniel Cooley Department of Applied Mathematics, University of Colorado at Boulder Geophysical Statistics Project, National Center for Atmospheric Research Philippe Naveau Department of Applied Mathematics, University of Colorado at Boulder Laboratiore des Sciences du Climat et de l Environnement, IPSL-CNRS, Gif-sur-Yvette, France Doug Nychka Geophysical Statistics Project, National Center for Atmospheric Research Extreme Values on Spatial Fields p. 1/1
2 Background 5th year graduate student 2nd year with GSP Anticipated graduation date: Fall 2005 Extreme Values on Spatial Fields p. 2/1
3 Background 5th year graduate student 2nd year with GSP Anticipated graduation date: Fall 2005 Projects Extreme value model for Lichenometry Spatial dependence estimation and prediction for annual maxima Colorado Front Range Precipitation Extreme Values on Spatial Fields p. 2/1
4 Colorado Precipitation Project Goal: Create a map of precipitation return levels for Colorado s Front Range. Extreme Values on Spatial Fields p. 3/1
5 Colorado Precipitation Project Goal: Create a map of precipitation return levels for Colorado s Front Range. project originated from ISSE, interested in flooding NWS has done maps for Southwest US (AZ, NM, UT, NV) and mid-atlantic (OH, PA, MD, NJ, NC, WV) plans to do entire US (contingent on funding) handles spatial dependence and prediction differently present NWS with our method and results Extreme Values on Spatial Fields p. 4/1
6 Front Range Data Data: hourly precipitation from 56 weather stations, years of data, Apr1 - Oct 31. latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo Limon Extreme Values on Spatial Fields p. 5/1
7 Univariate Extreme Values GEV: Used to model block (annual) maxima wasteful of data used by NWS to produce their maps Extreme Values on Spatial Fields p. 6/1
8 %& $ "! # ' Univariate Extreme Values GEV: Used to model block (annual) maxima wasteful of data used by NWS to produce their maps GPD: Models exceedences above a threshold # where Less wasteful of data Must choose threshold How to go spatial? Extreme Values on Spatial Fields p. 6/1
9 /. 3 Bayesian Hierarchical Model Let - (*),+ be observation from station. : 9 ) ) (*) + Extreme Values on Spatial Fields p. 7/1
10 /. 3 : 0 : Bayesian Hierarchical Model Let - (*),+ be observation from station. : 9 ) ) (*) + 4BA > ;=< 4BD 8 D A 8 C 8 are functions of covariates are functions of distance Extreme Values on Spatial Fields p. 7/1
11 /. 3 : 0 : Bayesian Hierarchical Model Let - (*),+ be observation from station. : 9 ) ) (*) + 4BA > ;=< 4BD 8 D A 8 C 8 are functions of covariates are functions of distance Plan: Use existing spatial techniques on the parameters, then convert to the desired return levels. Extreme Values on Spatial Fields p. 7/1
12 Covariates To do spatial prediction, any covariate must be available for every location in the region. sigma xi log(sigma) xi elevation elevation Extreme Values on Spatial Fields p. 8/1
13 PO # N Q PO I 4 c: : 4 C A [ [ 4 4 c: : 3 D [ [ : : k k First Model E E # J I H BEGF S Q R KML I J T distance \ W `ba _ ]^ Y \ W U elevation V W Z Y VXW U distance \ d `ba _ ]^ Y \ d U elevation Vd Z Y Vd U k 8 4 j a / g h 0 \ ee k 8 4 j a / gih 0 Vfee Extreme Values on Spatial Fields p. 9/1
14 Model Results log(sigma) xi elevation elevation Extreme Values on Spatial Fields p. 10/1
15 s o Model Results prq lnm latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo longitude Limon latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo longitude Limon Extreme Values on Spatial Fields p. 11/1
16 Model Results latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo longitude Limon latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo longitude Limon Extreme Values on Spatial Fields p. 12/1
17 Model Results 20-year Return Levels latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo Limon latitude Breckenridge Ft. Collins Greeley Boulder Denver Colo Spgs Pueblo Limon longitude longitude Extreme Values on Spatial Fields p. 13/1
18 Future Work Extend spatially Search for covariates Speed up MCMC method Examine covariance structure Test other models Model comparison (DIC)??? Extreme Values on Spatial Fields p. 14/1
Bayesian Spatial Modeling of Extreme Precipitation Return Levels
Bayesian Spatial Modeling of Extreme Precipitation Return Levels Daniel Cooley 1,2 Doug Nychka 2 Philippe Naveau 3,4 1 Department of Statistics Colorado State University, Fort Collins, CO 2 Geophysical
More informationExtreme Value Theory (or how to go beyond of the range data)
Extreme Value Theory (or how to go beyond of the range data) Sept 2007, Romania Philippe Naveau Laboratoire des Sciences du Climat et l Environnement (LSCE) Gif-sur-Yvette, France Katz et al., Statistics
More informationTwo practical tools for rainfall weather generators
Two practical tools for rainfall weather generators Philippe Naveau naveau@lsce.ipsl.fr Laboratoire des Sciences du Climat et l Environnement (LSCE) Gif-sur-Yvette, France FP7-ACQWA, GIS-PEPER, MIRACLE
More informationCoCoRaHS Monitoring Colorado s s Water Resources through Community Collaborations
CoCoRaHS Monitoring Colorado s s Water Resources through Community Collaborations Nolan Doesken Colorado Climate Center Atmospheric Science Department Colorado State University Presented at Sustaining
More informationModels for Spatial Extremes. Dan Cooley Department of Statistics Colorado State University. Work supported in part by NSF-DMS
Models for Spatial Extremes Dan Cooley Department of Statistics Colorado State University Work supported in part by NSF-DMS 0905315 Outline 1. Introduction Statistics for Extremes Climate and Weather 2.
More informationExtreme Precipitation: An Application Modeling N-Year Return Levels at the Station Level
Extreme Precipitation: An Application Modeling N-Year Return Levels at the Station Level Presented by: Elizabeth Shamseldin Joint work with: Richard Smith, Doug Nychka, Steve Sain, Dan Cooley Statistics
More informationFunding provided by NOAA Sectoral Applications Research Project CLIMATE. Basic Climatology Colorado Climate Center
Funding provided by NOAA Sectoral Applications Research Project CLIMATE Basic Climatology Colorado Climate Center Remember These? Factor 1: Our Energy Source Factor 2: Revolution & Tilt Factor 3: Rotation!
More informationNATS 101 Section 13: Lecture 3. Weather vs. Climate
NATS 101 Section 13: Lecture 3 Weather vs. Climate Definition of Weather Weather: Condition of the atmosphere at a particular time and place. Comprised of: Air temperature: Degree of hotness or coldness
More informationUnited States Climate
25-1 Alabama Annual Average Temperature Data Source: http://www.wrcc.dri.edu/cgi-bin/divplot1_form.pl?0106 25-2 How does climate vary as we traverse the U.S. along 40 N? 25-3 Average Temperature Along
More informationA comparison of U.S. precipitation extremes under two climate change scenarios
A comparison of U.S. precipitation extremes under two climate change scenarios Miranda Fix 1 Dan Cooley 1 Steve Sain 2 Claudia Tebaldi 3 1 Department of Statistics, Colorado State University 2 The Climate
More informationWhat is the difference between Weather and Climate?
What is the difference between Weather and Climate? Objective Many people are confused about the difference between weather and climate. This makes understanding the difference between weather forecasts
More informationTracking the Climate Of Northern Colorado Nolan Doesken State Climatologist Colorado Climate Center Colorado State University
Tracking the Climate Of Northern Colorado Nolan Doesken State Climatologist Colorado Climate Center Colorado State University Northern Colorado Business Innovations November 20, 2013 Loveland, Colorado
More informationGenerating gridded fields of extreme precipitation for large domains with a Bayesian hierarchical model
Generating gridded fields of extreme precipitation for large domains with a Bayesian hierarchical model Cameron Bracken Department of Civil, Environmental and Architectural Engineering University of Colorado
More informationExtremes and Atmospheric Data
Extremes and Atmospheric Data Eric Gilleland Research Applications Laboratory National Center for Atmospheric Research 2007-08 Program on Risk Analysis, Extreme Events and Decision Theory, opening workshop
More information2003 Water Year Wrap-Up and Look Ahead
2003 Water Year Wrap-Up and Look Ahead Nolan Doesken Colorado Climate Center Prepared by Odie Bliss http://ccc.atmos.colostate.edu Colorado Average Annual Precipitation Map South Platte Average Precipitation
More informationWeather Delays When Should They Be Granted?
Weather Delays When Should They Be Granted? If Weather Data is Normally Distributed, When Is the Weather Abnormal? Marty Cuerdon Senior Consultant 1 Weather Delays Normally Excusable but not Compensable
More informationClimate Update. Wendy Ryan and Nolan Doesken Colorado Climate Center. Atmospheric Science Department Colorado State University
Climate Update Wendy Ryan and Nolan Doesken Colorado Climate Center Atmospheric Science Department Colorado State University Presented to Water Availability Task Force June 26, 2008 Denver, CO Prepared
More informationUSGS ATLAS. BACKGROUND
USGS ATLAS. BACKGROUND 1998. Asquith. DEPTH-DURATION FREQUENCY OF PRECIPITATION FOR TEXAS. USGS Water-Resources Investigations Report 98 4044. Defines the depth-duration frequency (DDF) of rainfall annual
More informationEXTREMAL MODELS AND ENVIRONMENTAL APPLICATIONS. Rick Katz
1 EXTREMAL MODELS AND ENVIRONMENTAL APPLICATIONS Rick Katz Institute for Study of Society and Environment National Center for Atmospheric Research Boulder, CO USA email: rwk@ucar.edu Home page: www.isse.ucar.edu/hp_rick/
More informationWeather generators for studying climate change
Weather generators for studying climate change Assessing climate impacts Generating Weather (WGEN) Conditional models for precip Douglas Nychka, Sarah Streett Geophysical Statistics Project, National Center
More informationExtreme Value Analysis and Spatial Extremes
Extreme Value Analysis and Department of Statistics Purdue University 11/07/2013 Outline Motivation 1 Motivation 2 Extreme Value Theorem and 3 Bayesian Hierarchical Models Copula Models Max-stable Models
More informationAnalyzing Severe Weather Data
Chapter Weather Patterns and Severe Storms Investigation A Analyzing Severe Weather Data Introduction Tornadoes are violent windstorms associated with severe thunderstorms. Meteorologists carefully monitor
More informationSpatial Extremes in Atmospheric Problems
Spatial Extremes in Atmospheric Problems Eric Gilleland Research Applications Laboratory (RAL) National Center for Atmospheric Research (NCAR), Boulder, Colorado, U.S.A. http://www.ral.ucar.edu/staff/ericg
More informationUse your text to define the following term. Use the terms to label the figure below. Define the following term.
Mapping Our World Section. and Longitude Skim Section of your text. Write three questions that come to mind from reading the headings and the illustration captions.. Responses may include questions about
More informationRichard L. Smith Department of Statistics and Operations Research University of North Carolina Chapel Hill, NC
EXTREME VALUE THEORY Richard L. Smith Department of Statistics and Operations Research University of North Carolina Chapel Hill, NC 27599-3260 rls@email.unc.edu AMS Committee on Probability and Statistics
More informationExtreme Value Theory (or how to go beyond the data range)
Extreme Value Theory (or how to go beyond the data range) Philippe Naveau Laboratoire des Sciences du Climat et l Environnement (LSCE) Gif-sur-Yvette, France 17 novembre 2010 Nous avons anticipé dans la
More informationLecture 26 Section 8.4. Mon, Oct 13, 2008
Lecture 26 Section 8.4 Hampden-Sydney College Mon, Oct 13, 2008 Outline 1 2 3 4 Exercise 8.12, page 528. Suppose that 60% of all students at a large university access course information using the Internet.
More informationJackson County 2019 Weather Data 68 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center
Jackson County 2019 Weather Data 68 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center Doug Mayo Jackson County Extension Director 1952-2008 Rainfall Data
More informationA STATISTICAL APPROACH TO OPERATIONAL ATTRIBUTION
A STATISTICAL APPROACH TO OPERATIONAL ATTRIBUTION Richard L. Smith Department of Statistics and Operations Research University of North Carolina Chapel Hill, NC 27599-3260, USA rls@email.unc.edu IDAG Meeting
More informationAPPENDIX G-7 METEROLOGICAL DATA
APPENDIX G-7 METEROLOGICAL DATA METEOROLOGICAL DATA FOR AIR AND NOISE SAMPLING DAYS AT MMR Monthly Normals and Extremes for Honolulu International Airport Table G7-1 MMR RAWS Station Hourly Data Tables
More informationJackson County 2014 Weather Data
Jackson County 2014 Weather Data 62 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center Doug Mayo Jackson County Extension Director 1952-2008 Rainfall Data
More informationANSWER KEY. Part I: Weather and Climate. Lab 16 Answer Key. Explorations in Meteorology 72
ANSWER KEY Part I: Weather and Climate Table 2 lists the maximum and minimum temperatures (in F) and precipitation (in inches) for every day during April 2003 at Fairbanks, Alaska. You will compare your
More informationBayesian Model Averaging for Multivariate Extreme Values
Bayesian Model Averaging for Multivariate Extreme Values Philippe Naveau naveau@lsce.ipsl.fr Laboratoire des Sciences du Climat et l Environnement (LSCE) Gif-sur-Yvette, France joint work with A. Sabourin
More informationDrought Monitoring Capability of the Oklahoma Mesonet. Gary McManus Oklahoma Climatological Survey Oklahoma Mesonet
Drought Monitoring Capability of the Oklahoma Mesonet Gary McManus Oklahoma Climatological Survey Oklahoma Mesonet Mesonet History Commissioned in 1994 Atmospheric measurements with 5-minute resolution,
More informationSupplementary Information Dynamical proxies of North Atlantic predictability and extremes
Supplementary Information Dynamical proxies of North Atlantic predictability and extremes Davide Faranda, Gabriele Messori 2 & Pascal Yiou Laboratoire des Sciences du Climat et de l Environnement, LSCE/IPSL,
More informationLet s Talk Climate! Nolan Doesken Colorado Climate Center Colorado State University. Yampatika Seminar February 16, 2011 Steamboat Springs, Colorado
Let s Talk Climate! Nolan Doesken Colorado Climate Center Colorado State University Yampatika Seminar February 16, 2011 Steamboat Springs, Colorado First -- A short background In 1973 the federal government
More informationNorth American Weather and Climate Extremes
North American Weather and Climate Extremes Question V. What do we understand about future changes? L. O. Mearns, NCAR Aspen Global Change Institute July 17, 2005 Question 5 Subtopics How do models simulate
More informationColorado s 2003 Moisture Outlook
Colorado s 2003 Moisture Outlook Nolan Doesken and Roger Pielke, Sr. Colorado Climate Center Prepared by Tara Green and Odie Bliss http://climate.atmos.colostate.edu How we got into this drought! Fort
More informationStatistics for extreme & sparse data
Statistics for extreme & sparse data University of Bath December 6, 2018 Plan 1 2 3 4 5 6 The Problem Climate Change = Bad! 4 key problems Volcanic eruptions/catastrophic event prediction. Windstorms
More informationExtremes Analysis for Climate Models. Dan Cooley Department of Statistics
Extremes Analysis for Climate Models Dan Cooley Department of Statistics In collaboration with Miranda Fix, Grant Weller, Steve Sain, Melissa Bukovsky, and Linda Mearns. CMIP Analysis Workshop NCAR, August
More informationBayesian spatial hierarchical modeling for temperature extremes
Bayesian spatial hierarchical modeling for temperature extremes Indriati Bisono Dr. Andrew Robinson Dr. Aloke Phatak Mathematics and Statistics Department The University of Melbourne Maths, Informatics
More informationLecture 2 APPLICATION OF EXREME VALUE THEORY TO CLIMATE CHANGE. Rick Katz
1 Lecture 2 APPLICATION OF EXREME VALUE THEORY TO CLIMATE CHANGE Rick Katz Institute for Study of Society and Environment National Center for Atmospheric Research Boulder, CO USA email: rwk@ucar.edu Home
More informationR.Garçon, F.Garavaglia, J.Gailhard, E.Paquet, F.Gottardi EDF-DTG
Homogeneous samples and reliability of probabilistic models : using an atmospheric circulation patterns sampling for a better estimation of extreme rainfall probability R.Garçon, F.Garavaglia, J.Gailhard,
More informationDraft Report. Prepared for: Regional Air Quality Council 1445 Market Street, Suite 260 Denver, Colorado Prepared by:
Draft Report Evaluation of Preliminary MM5 Meteorological Model Simulation for the June-July 2006 Denver Ozone SIP Modeling Period Focused on Colorado Prepared for: Regional Air Quality Council 1445 Market
More informationUncertainty and regional climate experiments
Uncertainty and regional climate experiments Stephan R. Sain Geophysical Statistics Project Institute for Mathematics Applied to Geosciences National Center for Atmospheric Research Boulder, CO Linda Mearns,
More informationMultivariate Non-Normally Distributed Random Variables
Multivariate Non-Normally Distributed Random Variables An Introduction to the Copula Approach Workgroup seminar on climate dynamics Meteorological Institute at the University of Bonn 18 January 2008, Bonn
More informationSEVERE WEATHER UNDER A CHANGING CLIMATE: LARGE-SCALE INDICATORS OF EXTREME EVENTS
SEVERE WEATHER UNDER A CHANGING CLIMATE: LARGE-SCALE INDICATORS OF EXTREME EVENTS Matthew Heaton 1, Matthias Katzfuß 2, Yi Li 3, Kathryn Pedings 4, Shahla Ramachandar 5 Problem Presenter: Dr. Eric Gilleland
More informationOverview of Geophysical Statistics Project and NCAR
Overview of Geophysical Statistics Project and NCAR Douglas Nychka Geophysical Statistics Project Institute for Mathematics Applied to Geosciences National Center for Atmospheric Research Outline NCAR,
More informationApplications of Tail Dependence II: Investigating the Pineapple Express. Dan Cooley Grant Weller Department of Statistics Colorado State University
Applications of Tail Dependence II: Investigating the Pineapple Express Dan Cooley Grant Weller Department of Statistics Colorado State University Joint work with: Steve Sain, Melissa Bukovsky, Linda Mearns,
More informationThis content downloaded on Tue, 12 Feb :45:29 AM All use subject to JSTOR Terms and Conditions
Bayesian Spatial Modeling of Extreme Precipitation Return Levels Author(s): Daniel Cooley, Douglas Nychka and Philippe Naveau Reviewed work(s): Source: Journal of the American Statistical Association,
More informationMay 2016 Volume 23 Number 5
The Weather Wire May 2016 Volume 23 Number 5 Contents: Winter Summary Current Colorado and West-wide Snow Pack Drought Monitor April Summary/Statistics May Preview Snowfall Totals Winter Summary The Front
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 informationUSSD Conference, Denver 2016
USSD Conference, Denver 2016 M Schaefer, MGS Engineering Consultants K Neff, TVA River Operations C Jawdy, TVA River Operations S Carney, Riverside Technology B Barker, MGS Engineering Consultants G Taylor,
More information2003 Moisture Outlook
2003 Moisture Outlook Nolan Doesken and Roger Pielke, Sr. Colorado Climate Center Prepared by Tara Green and Odie Bliss http://climate.atmos.colostate.edu Through 1999 Through 1999 Fort Collins Total Water
More informationSpatial Optimization of CoCoRAHS Network in Tennessee. Joanne Logan Department of Biosystems Engineering and Soil Science University of Tennessee
Spatial Optimization of CoCoRAHS Network in Tennessee Joanne Logan Department of Biosystems Engineering and Soil Science University of Tennessee Abstract CoCoRaHS (Community Collaborative Rain, Hail and
More informationSkew Generalized Extreme Value Distribution: Probability Weighted Moments Estimation and Application to Block Maxima Procedure
Skew Generalized Extreme Value Distribution: Probability Weighted Moments Estimation and Application to Block Maxima Procedure Pierre Ribereau ( ), Esterina Masiello ( ), Philippe Naveau ( ) ( ) Université
More informationSupplementary Material for On the evaluation of climate model simulated precipitation extremes
Supplementary Material for On the evaluation of climate model simulated precipitation extremes Andrea Toreti 1 and Philippe Naveau 2 1 European Commission, Joint Research Centre, Ispra (VA), Italy 2 Laboratoire
More informationSemi-parametric estimation of non-stationary Pickands functions
Semi-parametric estimation of non-stationary Pickands functions Linda Mhalla 1 Joint work with: Valérie Chavez-Demoulin 2 and Philippe Naveau 3 1 Geneva School of Economics and Management, University of
More informationExtreme Rain all Frequency Analysis for Louisiana
78 TRANSPORTATION RESEARCH RECORD 1420 Extreme Rain all Frequency Analysis for Louisiana BABAK NAGHAVI AND FANG XIN Yu A comparative study of five popular frequency distributions and three parameter estimation
More informationClimate Regions. Combining Climate Graphs and Köppen s Classification
Lab 15 Climate Regions Combining knowledge of the global patterns behind the major climatic controls, this lab will teach students how to construct climate graphs and then allow them to explore patterns
More informationJackson County 2018 Weather Data 67 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center
Jackson County 2018 Weather Data 67 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center Doug Mayo Jackson County Extension Director 1952-2008 Rainfall Data
More informationAssessing methods to disaggregate daily precipitation for hydrological simulation
Assessing methods to disaggregate daily precipitation for hydrological simulation Peng Gao, Gregory Carbone, Daniel Tufford, Aashka Patel, and Lauren Rouen Department of Geography University of South Carolina
More informationAppendix C. AMEC Evaluation of Zuni PPIW. Appendix C. Page C-1 of 34
AMEC s Independent Estimate of PPIW Crop Water Use Using the ASCE Standardized Reference Evapotranspiration via Gridded Meteorological Data, and Estimation of Crop Coefficients, and Net Annual Diversions
More informationTowards a Bankable Solar Resource
Towards a Bankable Solar Resource Adam Kankiewicz WindLogics Inc. SOLAR 2010 Phoenix, Arizona May 20, 2010 Outline NextEra/WindLogics Solar Development Lessons learned TMY - Caveat Emptor Discussion 2
More informationNCAR Initiative on Weather and Climate Impact Assessment Science Extreme Events
NCAR Initiative on Weather and Climate Impact Assessment Science Extreme Events Linda O. Mearns NCAR/ICTP MICE Poznan, January 2004 Elements of the Assessment Initiative www.esig.ucar.edu/assessment Characterizing
More informationPresentation Overview. Southwestern Climate: Past, present and future. Global Energy Balance. What is climate?
Southwestern Climate: Past, present and future Mike Crimmins Climate Science Extension Specialist Dept. of Soil, Water, & Env. Science & Arizona Cooperative Extension The University of Arizona Presentation
More informationYour Creekside at Bethpage Weather with 2017 Forecasts. By Kevin Walls
Your Creekside at Bethpage Weather with 2017 Forecasts By Kevin Walls Lets discuss. What are the Weather Extremes? Why are our wind patterns always the same? What are the causes of our weather patterns?
More informationA spatio-temporal model for extreme precipitation simulated by a climate model
A spatio-temporal model for extreme precipitation simulated by a climate model Jonathan Jalbert Postdoctoral fellow at McGill University, Montréal Anne-Catherine Favre, Claude Bélisle and Jean-François
More informationJackson County 2013 Weather Data
Jackson County 2013 Weather Data 61 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center Doug Mayo Jackson County Extension Director 1952-2008 Rainfall Data
More informationWeather and Climate of the Rogue Valley By Gregory V. Jones, Ph.D., Southern Oregon University
Weather and Climate of the Rogue Valley By Gregory V. Jones, Ph.D., Southern Oregon University The Rogue Valley region is one of many intermountain valley areas along the west coast of the United States.
More informationNovember 2017 Volume 24 Number 11
The Weather Wire November 2017 Volume 24 Number 11 Contents: Colorado Snow Statistics Drought Monitor October Summary/Statistics November Preview Snowfall Totals Rainfall Totals Colorado Snow Statistics
More informationSite Description: Tower Site
Resource Summary for Elizabeth Site Final Report Colorado Anemometer Loan Program Monitoring Period: 7/3/06 /26/07 Report Date: January, 0 Site Description: The site is.6 miles northeast of the town of
More informationOctober 2015 Volume 22 Number 10
The Weather Wire October 2015 Volume 22 Number 10 Contents: Local Frost/Freeze Information Drought Monitor September Summary/Statistics October Preview Rainfall Totals Local Frost Freeze Information Many
More informationDownscaling Extremes: A Comparison of Extreme Value Distributions in Point-Source and Gridded Precipitation Data
Downscaling Extremes: A Comparison of Extreme Value Distributions in Point-Source and Gridded Precipitation Data Elizabeth C. Mannshardt-Shamseldin 1, Richard L. Smith 2 Stephan R. Sain 3,Linda O. Mearns
More informationAreal Reduction Factors for the Colorado Front Range and Analysis of the September 2013 Colorado Storm
Areal Reduction Factors for the Colorado Front Range and Analysis of the September 2013 Colorado Storm Doug Hultstrand, Bill Kappel, Geoff Muhlestein Applied Weather Associates, LLC - Monument, Colorado
More informationWeather to Climate Investigation: Snow
Name: Date: Weather to Climate Investigation: Snow Guiding Questions: What are the historical and current weather patterns or events for a location in the United States? What are the long-term weather
More informationRISK AND EXTREMES: ASSESSING THE PROBABILITIES OF VERY RARE EVENTS
RISK AND EXTREMES: ASSESSING THE PROBABILITIES OF VERY RARE EVENTS Richard L. Smith Department of Statistics and Operations Research University of North Carolina Chapel Hill, NC 27599-3260 rls@email.unc.edu
More informationBayesian dynamic modeling for large space-time weather datasets using Gaussian predictive processes
Bayesian dynamic modeling for large space-time weather datasets using Gaussian predictive processes Sudipto Banerjee 1 and Andrew O. Finley 2 1 Biostatistics, School of Public Health, University of Minnesota,
More informationObserved Climate Variability and Change: Evidence and Issues Related to Uncertainty
Observed Climate Variability and Change: Evidence and Issues Related to Uncertainty David R. Easterling National Climatic Data Center Asheville, North Carolina Overview Some examples of observed climate
More informationSite Description: Tower Site
Resource Summary for Fort Collins Site Final Report Colorado Anemometer Loan Program Monitoring Period: /0/00 11/03/007 Report Date: January 1, 00 Site Description: The site is located adjacent to the
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 informationDOWNSCALING EXTREMES: A COMPARISON OF EXTREME VALUE DISTRIBUTIONS IN POINT-SOURCE AND GRIDDED PRECIPITATION DATA
Submitted to the Annals of Applied Statistics arxiv: math.pr/0000000 DOWNSCALING EXTREMES: A COMPARISON OF EXTREME VALUE DISTRIBUTIONS IN POINT-SOURCE AND GRIDDED PRECIPITATION DATA By Elizabeth C. Mannshardt-Shamseldin
More informationAreal Reduction Factors for the Colorado Front Range and Analysis of the September 2013 Colorado Storm
Areal Reduction Factors for the Colorado Front Range and Analysis of the September 2013 Colorado Storm Doug Hultstrand, Bill Kappel, Geoff Muhlestein Applied Weather Associates, LLC - Monument, Colorado
More informationWEATHER FORECASTING Acquisition of Weather Information WFO Regions Weather Forecasting Tools Weather Forecasting Tools Weather Forecasting Methods
1 2 3 4 5 6 7 8 WEATHER FORECASTING Chapter 13 Acquisition of Weather Information 10,000 land-based stations, hundreds of ships and buoys; four times a day, airports hourly Upper level: radiosonde, aircraft,
More informationHierarchical Modeling for Univariate Spatial Data
Hierarchical Modeling for Univariate Spatial Data Geography 890, Hierarchical Bayesian Models for Environmental Spatial Data Analysis February 15, 2011 1 Spatial Domain 2 Geography 890 Spatial Domain This
More informationClimatography of the United States No
Climate Division: CA 5 NWS Call Sign: Elevation: 6 Feet Lat: 37 Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 1 Number of s (3)
More informationClimatography of the United States No
Climate Division: CA 4 NWS Call Sign: Elevation: 13 Feet Lat: 36 Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 1 Number of s
More informationClimatography of the United States No
Climate Division: CA 5 NWS Call Sign: Elevation: 1,14 Feet Lat: 36 Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 1 Number of
More informationClimatography of the United States No
Climate Division: CA 4 NWS Call Sign: Elevation: 2 Feet Lat: 37 Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 1 Number of s (3)
More information4840 South State Rd Cell:
DR. REBECCA A. BOLINGER NOAA GLERL Work: 734-741- 2248 4840 South State Rd Cell: 850-766- 6520 Ann Arbor, MI 48108 becky.bolinger@noaa.gov RESEARCH INTERESTS Hydroclimate variability, hydrologic cycle,
More informationData. Climate model data from CMIP3
Data Observational data from CRU (Climate Research Unit, University of East Anglia, UK) monthly averages on 5 o x5 o grid boxes, aggregated to JJA average anomalies over Europe: spatial averages over 10
More informationarxiv: v1 [stat.ap] 8 Oct 2010
The Annals of Applied Statistics 2010, Vol. 4, No. 1, 484 502 DOI: 10.1214/09-AOAS287 c Institute of Mathematical Statistics, 2010 arxiv:1010.1604v1 [stat.ap] 8 Oct 2010 DOWNSCALING EXTREMES: A COMPARISON
More informationClimatography of the United States No
Climate Division: CA 6 NWS Call Sign: LAX Elevation: 1 Feet Lat: 33 Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 1 Number of
More informationClimatography of the United States No
Climate Division: CA 6 NWS Call Sign: TOA Elevation: 11 Feet Lat: 33 2W Temperature ( F) Month (1) Min (2) Month(1) Extremes Lowest (2) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 1 Number
More informationThree main areas of work:
Task 2: Climate Information 1 Task 2: Climate Information Three main areas of work: Collect historical and projected weather and climate data Conduct storm surge and wave modeling, sea-level rise (SLR)
More informationDaily Operations Briefing Friday, November 29, :30 a.m. EST
Daily Operations Briefing Friday, November 29, 2013 8:30 a.m. EST 1 Significant Activity: Nov 27 29 Significant Events: Winter Storm Eastern US (Final) Tropical Activity: Atlantic Area 1 (Low chance/10%)
More informationYour Galactic Address
How Big is the Universe? Usually you think of your address as only three or four lines long: your name, street, city, and state. But to address a letter to a friend in a distant galaxy, you have to specify
More informationOverview of Extreme Value Analysis (EVA)
Overview of Extreme Value Analysis (EVA) Brian Reich North Carolina State University July 26, 2016 Rossbypalooza Chicago, IL Brian Reich Overview of Extreme Value Analysis (EVA) 1 / 24 Importance of extremes
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 informationSupplementary appendix
Supplementary appendix This appendix formed part of the original submission and has been peer reviewed. We post it as supplied by the authors. Supplement to: Lowe R, Stewart-Ibarra AM, Petrova D, et al.
More information