Presentation is loading. Please wait.

Presentation is loading. Please wait.

Where is the Interface between Weather and Climate? Klaus Wolter NOAA-ESRL & University of Colorado at Boulder, Kudos to Ed O’Lenic.

Similar presentations


Presentation on theme: "Where is the Interface between Weather and Climate? Klaus Wolter NOAA-ESRL & University of Colorado at Boulder, Kudos to Ed O’Lenic."— Presentation transcript:

1 Where is the Interface between Weather and Climate? Klaus Wolter NOAA-ESRL & University of Colorado at Boulder, Kudos to Ed O’Lenic for getting me into this mess; CPC for putting ppt’s on the internet; Tom Hamill, Klaus Weickmann, and Jon Eischeid for lots of figures… A few examples to illuminate this interface in Colorado Where are seams in NOAA’s ‘Seamless Forecast Suite’? A few examples from NOAA-ESRL-PSD1 (a.k.a. “CDC”) What about the future? AMS Summer Community Meeting Boulder,

2 A few (personal?) definitions of weather vs. climate: Climate = Integral over weather events; Climate is more than 1st moment statistics (means); Interface of weather and climate is where we don’t care anymore about deterministic forecasts of conditions at a point in time, but rather the probability distribution of conditions around that point in time. This interface is fuzzy - predictability is seasonally, regionally, and weather-regime dependent, and will hopefully improve in the future.

3 What are the climatological probabilities for precipitation around here? Western Regional Climate Center,

4 What are the climatological probabilities for precipitation around here? Western Regional Climate Center, This is when the local WSFO should not talk about increased rainfall chances if predicting 30% odds!

5 How important are different seasons around here? Based on PRISM data Winter contributes most at highest elevations, while summer is most important in eastern Colorado. Lack of precip during peak season often leads to onset of drought conditions.

6 How important is ENSO around here? Based on PRISM data Winter tends to be wet (dry) in the highest (lowest) elevations with La Ni ñ a (El Ni ñ o). Summer tends to be wet (dry) with El Ni ñ o (La Ni ñ a) over eastern CO.

7 ENSO impacts (subseasonal) In the Front Range, damaging wind storms tend to be less frequent with El Niño than under ENSO-Neutral or La Niña conditions. However, there are longer-term fluctuations that enhance/suppress the odds for wind storms around here (60s & early 70s had more frequent & severe cases than recent years). Since wind storms are one mechanism to evacuate pollutants (to Kansas), El Niño may have more/ longer-lasting winter air pollution episodes. El Niño winters tend to have fewer arctic air outbreaks along the spine of the Rockies than Neutral or La Niña winters, while the lack of wind storms also reduces the risk of ‘full- blown’ (warm) Chinook conditions. Therefore, the intraseasonal temperature range tends to be suppressed with El Niño (few sub-zero lows, as well as few highs in the 70sF - yes, that is a suppressed range), while La Niña and Neutral winters tend to have a wider temperature range.

8 ENSO vs. Colorado weather: Denver Snow Storms Spring and fall snow storms are more likely with El Ni ñ o, but moderate mid- winter snows are more frequent with La Ni ñ a. Heavy snow storms (>12 ” /day) are not common in Denver, but much more likely with El Ni ñ o than with La Ni ñ a. Since , Denver has seen four such storms in October ‘ 97, March ‘ 98, March ‘ 03, and December ‘ 06 (all during El Ni ñ o seasons).

9 Front Range City Snowstorms Top 10 Snowstorms in Fort Collins, Boulder, and Denver (since 1950) Units are in 1/10”; bold = 2ft.+; underlined dates refer to storms at two+ stations. FCLBOUDEN (17-19mr03) 299(24-26oc97)318(17-19mr03) (5-7my78) 260(20-21de06)238(24-25de82) (20-22no79) 259(29-31mr70) 219(24-25oc97) (29-31mr70) 241(8-10ap59) 215(26-27no83) (3-5ap83) 240(20-21no79) 207(21de06) (2-3ap57) 230(5-6my78) 187(5-6mr83) (21-22de06) 229(2-3ap57) 177(19-21no79) 8.195(30mr-1ap88) 225(18-19mr03) 173(2ap57) 9.187(1-3ja71) 215(23-25no92) 169(20-21mr52) (2-4no73) 210(17-19se71) 162(16-18no91) #spring storms: 6 (latest: May) Spring: 5 (latest: May) Spring: 4 (latest: April) There are four big storms shared across all three stations: in April ‘57, November ‘79, March ‘03, and December ‘06. Before 1950, the early December 1913 and early November 1946 storms are the two biggest snow storms on record.

10 Front Range City Snowstorms and ENSO Top 10 Snowstorms in Fort Collins, Boulder, and Denver (since 1950) Units are 1/10”; MEI >0.5/<-.5 for El Niño/La Niña conditions (+/- for smaller ∆). FCLBOUDEN (17-19mr03) 299(24-26oc97)318(17-19mr03) (5-7my78 - ) 260(20-21de06)238(24-25de82) (20-22no79) 259(29-31mr70 + ) 219(24-25oc97) (29-31mr70 + ) 241(8-10ap59 + ) 215(26-27no83 - ) (3-5ap83) 240(20-21no79) 207(21de06) (2-3ap57 + ) 230(5-6my78 - ) 187(5-6mr83) (21-22de06) 229(2-3ap57 + ) 177(19-21no79) 8.195(30mr-1ap88) 225(18-19mr03) 173(2ap57 + ) 9.187(1-3ja71) 215(23-25no92) 169(20-21mr52 + ) (2-4no73) 210(17-19se71) 162(16-18no91) Count: 5E, 2 L 5 E, 1 L 7 E, 0 L Only one season features more than one “Top 10” storm: (3*)! (Both Dec ‘13 and Nov ‘46 storms happened during modest El Ni ñ o conditions)

11 Climate/Weather Linkage Week 2 Hazards Assessment ForecastUncertaintyForecastUncertainty Minutes Hours Days 1 Week 2 Week Months Seasons Years The “NOAA Seamless Suite of Forecast Products Spanning Climate and Weather” (CPC, 2007) CPC Forecast Lead Time Warnings & Alert Coordination Watches Forecasts Threats Assessments Guidance Outlook Benefits TPCOPC HPC SWPCAWCSPC Service Center Perspective Winter Weather Desk Days 1-3 Tropical Storms to Day 5 Severe Weather to Day 3 NDFD, Days Day Forecast MaritimeMaritime Life & Property Space Operations RecreationRecreation EcosystemEcosystem EnvironmentEnvironment Emergency Mgmt AgricultureAgriculture Reservoir Control Energy Planning CommerceCommerce HydropowerHydropower Fire Weather HealthHealth AviationAviation The NCEP Centers span Seamless Suite

12 Climate/Weather Linkage ForecastUncertaintyForecastUncertainty Minutes Hours Days 1 Week 2 Week Months Seasons Years The “NOAA Seamless Suite of Forecast Products Spanning Climate and Weather” (CPC, 2007) North American Ensemble Forecast System Climate Forecast System Forecast Lead Time Warnings & Alert Coordination Watches Forecasts Threats Assessments Guidance Outlook Benefits Short-Range Ensemble Forecast Ocean Model Hurricane Models Global Forecast System North American Forecast Rapid Update Cycle for Aviation Dispersion Models for DHS -GFDL -WRF NCEP Model Perspective MaritimeMaritime Life & Property Space Operations RecreationRecreation EcosystemEcosystem EnvironmentEnvironment Emergency Mgmt AgricultureAgriculture Reservoir Control Energy Planning CommerceCommerce HydropowerHydropower Fire Weather HealthHealth AviationAviation NCEPs model production suite provides guidance for climate prediction

13 A few comments on the “NOAA Seamless Suite of Forecast Products Spanning Climate and Weather” How well do we really know the current and future forecast uncertainty? Is uncertainty at weather-climate interface biggest?

14 A few comments on the “NOAA Seamless Suite of Forecast Products Spanning Climate and Weather” How well do we really know the current and future forecast uncertainty? Is uncertainty at weather-climate interface biggest? How well do the different forecast centers (alphabet soup below CPC) interact with each other and with CPC? Should CPC have more competition?

15 A few comments on the “NOAA Seamless Suite of Forecast Products Spanning Climate and Weather” How well do we really know the current and future forecast uncertainty? Is uncertainty at weather-climate interface biggest? How well do the different forecast centers (alphabet soup below CPC) interact with each other and with CPC? Should CPC have more competition? 1.What about ENSO composites,’OCN’, ‘CCA’, all of those statistical workhorses that have gotten us this far?! What about some newer tools like Reforecasts, Linear Inverse Models, statistical forecasts of the MJO? What about the collective human expertise (CPC+)?

16 A few comments on the “NOAA Seamless Suite of Forecast Products Spanning Climate and Weather” How well do we really know the current and future forecast uncertainty? Is uncertainty at weather-climate interface biggest? How well do the different forecast centers (alphabet soup below CPC) interact with each other and with CPC? Should CPC have more competition? 1.What about ENSO composites,’OCN’, ‘CCA’, all of those statistical workhorses that have gotten us this far?! What about some newer tools like Reforecasts, Linear Inverse Models, statistical forecasts of the MJO? What about the collective human expertise (CPC+)? 2.Don’t throw out the baby with the bathwater - even ten years fron now, CFS should not be the only tool around, since so much more ‘bang for the buck’ can be extracted with statistical methods!

17 What is a reforecast? A hindcast, a numerical prediction for a date in the past using the model and data assimilation system that is currently operational. Hamill, pers.comm., 2008

18 Why compute reforecasts? For many forecast problems, such as long- lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating the probabilistic forecasts. Hamill, pers.comm., 2008

19 Comparison against NCEP / CPC forecasts at 155 stations, 100 days in winter Reforecast calibrated Week-2 forecasts more skillful than operational NCEP/CPC 6-10 day, which was based on human blending of NCEP, ECMWF, other tools. precipitation forecasts temperature forecasts Hamill, pers.comm., 2008

20 More recent findings Reforecasts shown to aid in calibration of forecasts for a wide variety of applications Still a large benefit from forecast calibration, even with state-of-the-art ECMWF forecast model. –Temperature calibration: Short leads: a few previous forecasts adequate for calibration Long leads: better skill with long reforecast training data set. –Precipitation calibration Low thresholds: a few previous forecasts somewhat ok for calibration Larger thresholds: large benefit from large training data set. Skill when trained with daily data not much larger than when trained with weekly data (preliminary result, more testing needed). Hagedorn, R., T. M. Hamill, and J. S. Whitaker, 2008: Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Forecasts. Part I: Surface Temperature. Mon. Wea. Rev., 136, Hamill, T. M., J. S. Whitaker, and R. Hagedorn, 2008: Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Forecasts. Part II: Precipitation. Mon. Wea. Rev., 136,

21 western Pacific convection meridional RWD PNA+ west hemisphere/ Africa convection transition to twin subtropical anticyclones W Pac cyclones Indian Ocean convection meridional RWD PNA- transition to twin subtropical cyclones w Pac anticyclones Maritime continent convection M R > 0 M R < 0 dM R /dt < 0 dM R /dt > 0 weak MJO Weickmann&Barry, pers.comm., 2008 ‘Milking’ the MJO/ Angular momentum cycles

22 H H H H H LL RWD from WPAC tropical convection forces western USA trough storms MJO phase 8 plus La-Nina!!! L Weickmann&Barry, pers.comm., 2008

23 GFS ENS mean predicts a ridge ACC ~0! Weickmann&Barry, pers.comm., 2008 Ed Barry’s blog hinted at the trough scenario on March 15th! See:

24 Downscaling will be important for monitoring and prediction products GIS: Geographical Information System A popular format that allows meteorological fields to be superposed over topography, rivers, roads, and cities. GIS format is preferred by many users. CPC is working with NCO to convert its monitoring and outlook products (CPC, 2007)

25 Climate Test Bed NCEP and CPO Climate Support: Climate Test Bed Climate Community Climate Community Research & Development Research & Development NOAA Climate Forecast Operations NOAA Climate Forecast Operations Mission: Mission: To accelerate the transition of scientific advances from the climate research community to improved NOAA climate forecast products and services. (CPC, 2007)

26 NCEP and CPO Climate Support: Climate Test Bed The CTB is a resource to accelerate scientific advances to operations –Bridging the “Valley of Death” between research & operational service applications –Embracing the R2O and O2R paradigms The CTB emphasizes high profile science activities –CFS/GFS Improvements (CFSRR) –Multi-model ensembles (IMME, NMME) –Objective climate forecast products and applications (drought / NIDIS) Competitive Grants Program - How is the funding situation??? CTB-COLA Seminar Series CPC-RISA Program Distinguished Visiting Scientist Program (FY09) (CPC, 2007)

27 What is around the corner? Yes, it will be warmer years from now. Meanwhile, what will happen in the next decade or two? –What is the likelihood of shifts in PDO and AMO towards a colder climate? Not unrelated, what if we get more prolonged La Ni ñ a events? –If we get more intense precipitation events, could this translate into a better chance for heavy snow storms which might result in more intense, shallow cold waves? The late December 2006 blizzard was followed by the coldest winter on record in southeastern Colorado, despite above-normal temperatures above the boundary layer! –If we continue to see earlier snow melt seasons, does this translate into earlier monsoon seasons as well since the surface heat low can set up earlier? Or will the longer snow-free season result in a longer wildfire season which could suppress the monsoon thru aerosols, mid-tropospheric inversions, and lower incoming radiation? IMHO, that is what happened in 2002.

28 What is around the corner? What about the weather-climate interface? –What is the MJO going to look like with a warmer tropical ocean to support convection? Does this make the 1-4 week forecast problem easier or harder? –Now that we have barely figured out what the ENSO teleconnections are, how stable will they be, given that the planet is warming up? –Are we going to solve how to incorporate snow-albedo- as well as soil moisture - temperature feedbacks to make better 1-4 week forecasts? –With people moving (back) into urban areas, are we going to take into account the urban heat island effect in our forecasts, and does it intensify over time during heat waves?


Download ppt "Where is the Interface between Weather and Climate? Klaus Wolter NOAA-ESRL & University of Colorado at Boulder, Kudos to Ed O’Lenic."

Similar presentations


Ads by Google