Forecast Forecasts PowerPoint Presentations - PPT

Who cares about S2S research to improve forecasts?
Who cares about S2S research to improve forecasts? - presentation

alexa-sche

Ali Stevens, Annarita Mariotti, Dan Barrie, Heather Archambault, Emily Read. Climate Program Office. Contact: alison.stevens@noaa.gov. NMME/SubX Science Meeting. September 13-15, 2017. **Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration..

1 Summary of CFS ENSO Forecast
1 Summary of CFS ENSO Forecast - presentation

cheryl-pis

. May . 2010. update. Mingyue Chen, . Wanqiu. Wang and . Arun. Kumar . Climate Prediction Center. . Latest forecast of Nino3.4 index (slide 2). Hindcast. skill of Nino3.4 index (slide 3). Hindcast.

1 Summary of CFS ENSO Forecast
1 Summary of CFS ENSO Forecast - presentation

ellena-man

. December 2010. . update. Mingyue Chen, Wanqiu Wang and Arun Kumar . Climate Prediction Center. . Latest forecast of Nino3.4 index (slide 2). Hindcast. skill of Nino3.4 index (slide 3). Hindcast.

Cb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logi
Cb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logi - presentation

alida-mead

Martin Köhler. DLR Oberpfaffenhofen. 8th European Conference on . Severe. . Storms – ECSS 2015. 14 – 18 September 2015, Wiener Neustadt, Austria. Adverse. . weather. . is. . responsible. . for.

CBRFC Forecast Products:
CBRFC Forecast Products: - presentation

trish-goza

Where, When, and What is Issued?. CBRFC Fourth Annual Stakeholder Forum. February 25. th. – 26. th. , 2014. Salt Lake City, Utah. NOAA’s National Weather Service. Colorado Basin River Forecast Center.

1 Summary of CFS ENSO Forecast
1 Summary of CFS ENSO Forecast - presentation

cheryl-pis

. June . 2010. update. Mingyue Chen, . Wanqiu. Wang and . Arun. Kumar . Climate Prediction Center. . Latest forecast of Nino3.4 index (slide 2). Hindcast. skill of Nino3.4 index (slide 3). Hindcast.

A Regression Model for Ensemble Forecasts
A Regression Model for Ensemble Forecasts - presentation

lindy-duni

David Unger. Climate Prediction Center. Summary. A linear regression model can be designed specifically for ensemble prediction systems.. It is best applied to direct model forecasts of the element in question..

A Regression Model for Ensemble Forecasts
A Regression Model for Ensemble Forecasts - presentation

test

A Regression Model for Ensemble Forecasts David Unger Climate Prediction Center Summary A linear regression model can be designed specifically for ensemble prediction systems. It is best applied to direct model forecasts of the element in question.

Statistical Weather Forecasting
Statistical Weather Forecasting - presentation

alida-mead

Independent Study. Daria. . Kluver. From Statistical Methods in the Atmospheric Sciences by Daniel . Wilks. Perfect . Prog. and MOS. Classical statistical forecasts for projections over a few days are not used. Current dynamical NWP models are more accurate..

Stealing From The Bottom Line.
Stealing From The Bottom Line. - presentation

kittie-lec

Professor Bob Berry (NUBS). What is “the bottom line”?. The phrase has come into common usage from accounting.. Profit After Interest and Tax (PAIT) might be a candidate.. An alternative, more general, current interpretation is “the most important thing”..

Using qualitative business cycle forecasting in MBA Macroec
Using qualitative business cycle forecasting in MBA Macroec - presentation

pamella-mo

Terry Long. Marymount University. Gulf Coast Economics Conference. October 2011. MBA Macroeconomics. Premise. Effective business decisions require knowledge about the future course of economic activity.

Statistical Weather Forecasting
Statistical Weather Forecasting - presentation

natalia-si

3. Daria . Kluver. Independent Study. From. Statistical . Methods in the Atmospheric Sciences. By . Daniel . Wilks. Let’s review a few concepts that were introduced last time on Forecast Verification.

NDFD Weather Element
NDFD Weather Element - presentation

stefany-ba

(“ugly string”) Verification. Paul Fajman. NOAA/NWS/MDL. September 7, 2011. NDFD ugly string. NDFD Forecasts and encoding. Observations. Assumptions. Output, Scores and Display. Results. Future Work.

Ensemble Forecasting and
Ensemble Forecasting and - presentation

tatiana-do

its. . Verification. Malaquías. Peña. Environmental Modeling Center, NCEP/NOAA. 1. Material comprises Sects. . . 6.6, 7.4 and 7.7 in . Wilks. (2. nd. Edition). Additional material and notes from .

Equity Analysts’ Economic Outlook
Equity Analysts’ Economic Outlook - presentation

giovanna-b

Investment horizon: 3 – 5 years. Need long-term economic forecasts . Equity analysts estimate (nominal) fundamental growth rates for the stocks they cover using firm-level information from the 10-Ks. They adjust the growth rates taking into account industry-level information, as well as real GDP and inflation forecasts..

Communicating Uncertainty via Probabilistic Forecasts for the January 2016 Blizzard in Southern New
Communicating Uncertainty via Probabilistic Forecasts for th - presentation

pamella-mo

Frank M Nocera, Stephanie L. . Dunten. & Kevin J. . Cadima. NOAA/National Weather Service Boston, MA.. 2014-2015 Probabilistic Snow Method. WPC 90. th. Percentile. What QPF is driving WPC Percentile Forecasts?.

A Few Words on Hurricane Forecasts
A Few Words on Hurricane Forecasts - presentation

celsa-spra

Forecast Track Error. Rule of Thumb for . Forecast Track Errors:. 24 hours .  40 nm. 48 hours  70 nm. 72 hours  100 nm. Today’s 3-Day Forecast. i. s as good as a 1-Day. Forecast in 1990.. Intensity Error.

Forecasting Chapter 3	 Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproductio
Forecasting Chapter 3 Copyright © 2015 McGraw-Hill Educati - presentation

kittie-lec

You should be able to:. LO 3.1 List features common to all forecasts. LO 3.2 Explain why forecasts are generally wrong. LO 3.3 List elements of a good forecast. LO 3.4 Outline the steps in the forecasting process.

The Ides Of October Storm
The Ides Of October Storm - presentation

alexa-sche

A Difficult Forecast of an Unusual Event. Cliff Mass . University of Washington. Typhoon . Songda. : October 3-October 16, 2016. Forecasts Early in the Week. Suggested the Possibility of an Extraordinary Event.

Latin American and Caribbean Flood and Drought Monitor –
Latin American and Caribbean Flood and Drought Monitor – - presentation

lindy-duni

What it does and does not do. Figure showing current system. Coarse resolution. 25km, daily. Satellite and . global data only. 7-day forecast. Deterministic – single forecast. Stream discharge only.

Cb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logi
Cb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logi - presentation

calandra-b

Martin Köhler. DLR Oberpfaffenhofen. 15th EMS/12th ECAM. 07 – 11 September, Sofia, . Bulgaria. Adverse. . weather. . is. . responsible. . for. . 40-50%. . of. all . delays. in . Europe . (.

Interim Findings from NCHRP 08-110 Traffic Forecasting Accuracy Assessment Research
Interim Findings from NCHRP 08-110 Traffic Forecasting Accur - presentation

pasty-tole

Interim Findings from NCHRP 08-110 Traffic Forecasting Accuracy Assessment Research March 15, 2019 Greg Erhardt & Jawad Hoque University of Kentucky Dave Schmitt Connetics Transportation Group 2

An evaluation of precipitation forecasts
An evaluation of precipitation forecasts - presentation

calandra-b

during November . 12-15, . 2015 and November 16-19, 2015. Robert Conrick, Qi Zhong, and Cliff Mass. University of Washington. . Pacific NW Weather Workshop 2017. Cases: November . 12-15, . 2015.

NCHRP 08-110 Traffic Forecasting Accuracy Assessment Research
NCHRP 08-110 Traffic Forecasting Accuracy Assessment Researc - presentation

karlyn-boh

NCHRP 08-110 Traffic Forecasting Accuracy Assessment Research May 2019 Greg Erhardt & Jawad Hoque University of Kentucky Dave Schmitt Connetics Transportation Group 2 “The greatest knowledge gap in US travel demand modeling is the unknown accuracy of US urban road

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