April 2015 Dry Times interactive

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10 RESEARCHcontinued from previous pageidentified a circulation patternthat appears predictable at theselonger ranges. Analysis of heatwaves in this model indicates thattheir likelihood of occurrence overNorth America is influenced bythis circulation pattern, so thatthere is some skill at predictingthe probability of heat waves anddry spells more than two weeks inadvance.This special circulation pattern,which is also seen in nature, canarise as a result of midlatitudeatmospheric processes. It does notrely on slowly varying surface ortropical conditions, and thus isdistinct from the phenomena thathave previous been relied on fortwo- to three-week predictions.A noteworthy attribute of thepattern (sometimes referred toas a circumglobal teleconnectionpattern, or CGT), is that it consistsof a chain of five pairs of alternatinghigh and low pressure features thatencircle the Northern Hemisphere.Our team has expanded previousstudies of the link between thispattern and U.S. heat waves sothat we now recognize that thispattern and a second CGT impactthe likelihood of heat waves and dryspells in the Northern Hemisphere.When strong circulation anomaliesresemble one of these patterns, theprobability of heat waves can beincreased or reduced in key regionsby a factor of 4, concurrently and inthe following two weeks (Fig.1 onpage 9.)An extension of our effortconcerns investigating how thestructure and behavior of thesecirculation patterns may changeas the climate changes. Usingmechanistic models, we have foundthat the structure of these patternschanges if the mean circulationchanges, in particular the strengthand placement of the troposphericjet.Because of the impact that thesepatterns have on heat waves anddry spells, our work will providea mechanism by which climatechange can influence the likelihoodand geographical distribution ofthese extreme events.Fig. 1Warm seasonclimatology ofprecipitation(shaded) and the850-hPa meridionalwinds (contoured).Winds > 1 m s −1 arecontoured at 1 ms −1 intervals andprecipitation > 2mm day −1 is shaded.The positive(negative) contoursdenote southerly(northerly)meridional windcomponents.Understanding changes in theregional variability of U.S. droughtBY SCOTT WEAVERNOAA/NCEP/CPCSome recent studies suggest that duringmeteorological summer (June, July, August)the interannual variability of North Americanprecipitation has been increasing over the lastsix decades. However, upon closer examination itis evident that trends in this variability are morenuanced than previously thought. During <strong>April</strong>,May and June both the Great Plains and Southeastshowed an increasing trend in interannual variabilityof precipitation over 1950-2010; however, duringJuly, August and September the changes invariability exhibit a more decadal appearance.The North American low-level jet (NALLJ) isa dynamical feature of the atmosphere (Fig. 1,above) that is typically active over the Great Plains,effectively acting as a scale transfer mechanismbetween the large-scale forcing and regional climate.Variations of this pattern focus regional scaleprecipitation anomalies leading to the occurrence ofdrought and/or pluvial conditions (Fig. 2, at left).This research project investigates the role of theNALLJ in promoting the multidecadal changes tothe year-to-year (interannual) variability in regionalprecipitation and the interplay between naturalvariability and anthropogenic climate changeusing a suite of observations and climate modelexperiments.Fig. 2Recurrent patterns of springtime NALLJ variability (contours)and precipitation regressions (shaded) for 1980-2010. TheEOF modes are contoured at 0.2 m s -1 and precipitationregressions are shaded at 0.1 mm day −1 intervals.
RESEARCH11Combining short-range and long-range temperature and precipitation forecastscan help to boost skill of drought forecastToward more skillful predictionBY LIFENGLUOMichigan StateUniversityPANG-NINGTANMichigan StateUniversityDAN BARRIENOAA ClimateProgram OfficeFig. 1Predicted droughtconditions (withuncertainty)(middle andbottom) for June2012 and thecorrespondingverification (top).Lower valuesindicate relativelydrier soil moistureconditions.Forecasts wereissued on <strong>April</strong> 6,2012, and the leadtime is about 2.5months. The ESPforecast approach(bottom) isadopted by theRiver ForecastCenters at NWS,serving as areference here.Fig.2Ensembleprediction ofbasin-averagedroughtconditions overthe ColoradoRiver Basinfor a 4-monthperiod since thetime of forecaston August 23,2013. The blackcurve is theanalysis servingas the proxy forobservations.The gray curvesare from the ESPforecast servingas a reference.Prior research has demonstrated the feasibilityof using hydrological models to predict futuredrought in the U.S. via soil moisture and otherhydrological variables at subseasonal to seasonaltime scales. The key to a skillful prediction ofsuch is the accuracy of the initial hydrologicalstates at the time of the forecast, and the weatherevolution weeks and months afterwards.Since accurate weather prediction is impossiblebeyond about two weeks due to the chaotic natureof the climate system, how to best represent thepossible weather sequences and the associateduncertainties in an ensemble framework is amajor challenge.An ongoing research project, supported bythe NOAA Climate Program Office Modeling,Analysis, Prediction, and Projections (MAPP)program, tackles such a challenge by exploringmethods to better utilize existing weather andclimate forecasts to improve seasonal droughtforecast.In particular, we explore ways to combineshort-range (e.g. seven-day quantitativeprecipitation forecasts, or QPF) and long-range(e.g., Climate Forecast System version 2 orCFSv2) forecasts of temperature and precipitationto better represent the likelihood of weatherconditions at various lead times. The newapproaches developed in this research are eitherbased on Bayesian statistics or machine learningalgorithms that are traditionally used in the fieldof data mining.These methods have been implemented ina Drought Monitoring and Prediction System,and they have shown encouraging results inimproving drought forecast skills. For example,the ability to predict the much drier than normalconditions over the Central Plains for June 2012two months in advance (Fig. 1, above left) makesthese forecasts useful for early drought warning.The system has also shown the ability topredict wetter than normal conditions quitesuccessfully. In August 2013, we predicted higherthan normal rainfall, thus wetter than normalsoil moisture conditions over the Colorado RiverBasin, which was verified nicely by subsequentobservations (Fig. 2, lower left).More information about the project, includingpast and real-time forecast can be found at http://drought.geo.msu.edu/research/forecast/ .
Page 1: DRY TIMES1NATIONAL INTEGRATED DROUG
Page 4: 4NIDIS: WHO WE AREa deep understand
Page 8 and 9: 8RESEARCHThe observation: The stren
Page 12 and 13: 12DATA AND TOOLSA conversation abou
Page 14 and 15: 14DATA AND TOOLSmajor impacts on re
Page 16 and 17: 16 IMPACTSMAY 2009No droughtAUGUST
Page 19 and 20: EARLY WARNING SYSTEMS: CALIFORNIA19
Page 22: 22 EARLY WARNING SYSTEMS: MISSOURI

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