1 / 30

Understanding seasonality and regionality in climate trends over the United States during 1950-2000

Understanding seasonality and regionality in climate trends over the United States during 1950-2000. Hailan Wang 12 , Siegfried Schubert 1 , Max Suarez 1 , Junye Chen 13 , Martin Hoerling 4 and Arun Kumar 5 1 NASA/GMAO; 2 UMBC/GEST; 3 UMD/ESSIC; 4 NOAA/ESRL; 5 NOAA/NCEP/CPC.

justus
Télécharger la présentation

Understanding seasonality and regionality in climate trends over the United States during 1950-2000

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Understanding seasonality and regionality in climate trends over the United States during 1950-2000 Hailan Wang12, Siegfried Schubert1, Max Suarez1, Junye Chen13, Martin Hoerling4 and Arun Kumar5 1NASA/GMAO; 2UMBC/GEST; 3UMD/ESSIC; 4NOAA/ESRL; 5NOAA/NCEP/CPC NASA MAP “Understanding and quantifying the 1970s climate transition in the presence of a rapidly changing observing system” (PI: Siegfried Schubert)

  2. Observed Seasonality and Regionality in Climate Trends over U.S. HadCRU; 1950-2000 Surface Air Temperature (T) Precip (P)

  3. Observed Seasonality and Regionality in Climate Trends over U.S. HadCRU; 1950-2000 3-mon RunMean 3-mon RunMean Black: US mean (235°E-285°E; 28°N-50°N) Gray: central US mean (250°E-275°E; 30°N-48°N) Distinct cooling and wetting trends during late summer and fall

  4. Motivation • Attribution of seasonality and regionality in observed climate trends over the U.S. during 1950-2000; specifically: • To what extent do the leading SST patterns explain the observed seasonality and regionality of the surface air temperature and precipitation trends over the U.S. during 1950-2000? • What are the physical and dynamical processes through which the key SST patterns affect the climate trends over the U.S.?

  5. Model (AMIP) vs Obs NASA NSIPP AGCM 3deg; 1950-2000 NASA NSIPP AMIP EnsMean(14) HadCRU

  6. NSIPP AMIP EnsMean vs HadCRU: Seasonality NSIPP AMIP EnsMean HadCRU 3-mon RunMean 3-mon RunMean The observed climate trends over the U.S. can be mostly explained by changes in SST

  7. Leading SST Modes: Global Warming (GW) and Decadal Variability (DV) Hadley SST; 1901-2000 30% (Long-term trend) 12% 1976 1950 Chen et al. (2007a, b), J. Climate, submitted

  8. Linear trend of SST: GW+DV+Residual Hadley SST; 1950-2000 Global Warming (GW) Decadal Variability (DV) Total Residual Input for a set of idealized AGCM experiments

  9. Idealized AGCM Experiments NASA NSIPP AGCM; 3deg • All runs are integrated for 100 years • Data averaged over the last 60 years taken as climatology • Climatological difference between control run and an anomaly run represents • effect of corresponding SST trend

  10. Surface Air Temperature (T) Response in Idealized AGCM Experiments Total GW DV Residual DJF MAM JJA SON

  11. Precip (P) Response in Idealized AGCM Experiments Total GW DV Residual DJF MAM JJA SON

  12. Seasonality (amplitude) in Idealized AGCM Experiments • GW: • does not contribute • spatial pattern unimportant • DV • dominant for all seasons • mainly from Pacific • Residual • important in fall • mainly from NH tro Atlantic (not shown)

  13. Atmospheric Moisture Budget Analysis where: (Precip)´ is balanced by: (MoistConv)´due to (AtmosCirculation)´ + (MoistConv)´due to (AtmosMoist)´+ (Evap)´

  14. Atmospheric Moisture Budget Analysis:DV_Pacific in JJA H (Precip)´ over central US: comparably by (MoistConv)´due to (AtmosCirculation)´and (Evap)´

  15. Atmospheric Moisture Budget Analysis:Residual in SON H (Precip)´ over central US: primarily by (MoistConv)´ due to (AtmosCirculation)´, secondly by (Evap)´

  16. Stationary Wave Modeling (SWM) Diagnosis • Maintenance of the low-level high over the Gulf of Mexico in AGCM (DV_Pacific) and AGCM (Residual) • About the Stationary Wave Model: • Developed by Mingfang Ting’s group (Ting and Yu 1998) • Essentially a dry dynamical core of an AGCM • Based on 3-D primitive equations • Time-dependent and nonlinear • Resolution: R30L14 • In this study: • Mean state: • 3-D climatological seasonal mean flow of control run • Stationary wave forcing anomalies • Mean difference between control run and anomaly run • Diabatic heating: directly from model output • Transients: major terms in 3-D primitive equations

  17. Vert_Integrated Diabatic Heating Anom: DV_Pacific-Ctrl in JJA

  18. Stationary Wave Modeling (SWM) Diagnosis:DV_Pacific in JJA Eddy StrmFunction at σ=0.866 AGCM SWM[Heat+Tran] SWM[Heat] SWM[Tran] SWM[Pac_Heat] SWM[local_Heat] SWM[local_Cool] SWM[local_Heat]

  19. Vert_Integrated Diabatic Heating Anom: Residual-Ctrl in SON

  20. Stationary Wave Modeling (SWM)Diagnosis:Residual in SON Eddy StrmFunction at σ=0.866 SWM[Heat] AGCM SWM[nonlocal_Heat] SWM[local_Heat] SWM[local_Heat] SWM[local_Cool]

  21. Seasonality of T and P in IPCC AR4 20th Century Climate Simulations 1950-2000 • State-of-the-art • Fully coupled • 14 models(n>3) examined Warming and drying trends in late summer 14 Multi-Model Ensemble Mean

  22. Conclusions • The observed climate trends over the U.S. during 1950-2000 exhibit distinct seasonality and regionality. In particular, there are notable cooling and wetting trends in late summer and fall. • The observed climate trends can be mostly explained by changes in SST • Among the leading SST patterns: • Global Warming (GW): • does not contribute; mainly leads to a general warming trend • spatial pattern unimportant • Decadal Variability (DV): • plays a prominent role throughout all seasons • Residual: • mainly contribute in late summer and fall; contribution in fall comparable to that of DV

  23. Conclusions (cont’d) • How do Decadal Variability (DV) and Residual SSTA affect the U.S. climate in summer and fall • Decadal Variability (DV): • Dominated by SST warming in Pacific (El Nino like) • Excite atmospheric circulation anomalies and regulate moisture distribution over U.S. and Gulf of Mexico, leads to precipitation increase over the U.S.; enhanced by strong local land soil moisture processes • Residual SST: • Dominated by SST cooling in tropical and subtropical Atlantic • Excite a strong low-level anticyclonic anomaly over the eastern Gulf of Mexico, which helps transport more moisture northward to the central U.S., leading to precipitation increase there

  24. Supplement

  25. Time Series of observed U.S. Mean SfcAirTemp and Precip HadCRU 1950-2000 5-yr RunMean 1-yr RunMean SAT Pr

  26. Significance test of linear trend of SfcTemp over US HadCRU 1950-2000; Student’s t test

  27. Significance test of linear trend of Precip over US HadCRU 1950-2000; Student’s t test

  28. 3rd and 4th SST modes Hadley SST; Jan1901-Dec2000

  29. Seasonality (spatial pattern) in Idealized AGCM Experiments

More Related