The NOAA CPO Modeling, Analysis, Prediction, and Projections (MAPP) program hosted a webinar on the topic of Weather-Climate Linkages: Analysis, Modeling, and Prediction Efforts on Thursday, February 12, 2015. The announcement is provided below; you are invited to remotely join the session.
|February 12, 2015
1:00 PM – 2:00 PM ET
|Weather-Climate Linkages: Analysis, Modeling, and Prediction Efforts|
|Speakers and Topics:||Chris Bretherton (University of Washington)
Clouds and Their Impacts in Weather Prediction and Climate Models
Marty Hoerling (NOAA ESRL)
|Remote Access:||To view the slideshow:
1. Click the link below or copy and paste the link to a browser: https://cpomapp.webex.com/cpomapp/onstage/g.php?t=a&d=292954186
2. Enter your name and e-mail address, and click “Join Now”. If necessary, enter the event passcode: 20910
To hear the audio:
Utilize the on-screen dial-in instructions visible after logging into webex
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(Right click and Save Link As) .wmv
ABSTRACTS: Chris Bretherton – Clouds are important to both climate and weather through their impacts on radiation and atmospheric circulations on all scales. Certain cloud types, such as cumulus convection and clouds tied to turbulent circulations in the atmospheric boundary layer, are notoriously difficult to simulate in weather and climate models. In some cases, such as daytime fog or low cloud over land, a correct forecast of cloudiness is crucial to a skillful short-term temperature forecast. Because clouds form and dissipate rapidly, they are also very responsive to day-to-day weather changes. Thus, diagnosis of cloud in short-range weather forecasts is an ideal way to test the representation of cloud-forming processes in weather and climate models. This is illustrated by comparing short-term global cloud forecasts generated by the NOAA Cloud Climate Process Team using the GFS weather forecast model and GFDL climate model to simultaneous satellite observations.
Martin Hoerling – U.S. annual precipitation has increased in recent decades, especially over the Northeast where totals have risen about 15% since 1901. Accompanying this increase in total precipitation have been increases in the frequency and intensity of very heavy precipitation events. In this presentation, the effect of various factors causing trends in very wet days is diagnosed in order to better characterize their recent change.
Long integrations of atmosphere and coupled atmosphere–ocean models are used to diagnose the variability and change in U.S. heavy precipitation events, focusing on the 1979-2014 period. We ask if changes in weather statistics of heavy precipitation are reconcilable with a deterministic response to climate forcing? What is the nature of that forcing, and in particular what role has been played by global warming dynamics? Alternatively, we also ask if the observed changes in weather statistics of heavy precipitation reflect an extreme manifestation of internal variability, either of the atmosphere alone, or of the coupled ocean-atmosphere system.
Answers to these questions are central to knowing if a change in the statistics of weather-related precipitation extremes has been detected regionally, and what those changes tell us about extreme precipitation events in coming decades.
Nat Johnson – Weather and climate prediction for lead times between 15 and 30 days presents significant challenges, yet recent work has identified potential sources of predictability that may allow NOAA to bridge its gap in extended and long range forecast products for lead times of three to four weeks. In this presentation, we discuss some of the primary sources of predictability at these lead times, including the El Niño/Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO). We demonstrate that statistical guidance based on the initial state of ENSO and the MJO and the long-term trend may allow skillful forecasts in weeks 3 and 4 under certain initial conditions. We also present preliminary analyses of CFSv2 performance in weeks 3-4, indicating the promise of dynamical forecast guidance to complement statistical guidance. We highlight outstanding questions and challenges that we plan to address in order to develop a seamless forecast system that bridges shorter range Week 2 outlooks and longer range monthly outlooks.