GEOS 513 ENSO: Past, Present and Future

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1 GEOS 513 ENSO: Past, Present and Future Jessica Conroy Department of Geosciences Stephen W. Bieda, III Department of Atmospheric Sciences February 22, 2006: Regional Teleconnections (Observations) References: Gutzler et al. (2002), Biggins et al. (1999), Adams and Comrie (1997), Reyes (1988), Harrington et al. (1992) 1) 2) 3) 4) What is the relationship between warm and cold ENSO events and seasonal percent departure from normal precipitation values in AZNM, NWMX, and SWMX? What is the proposed physical reason for the statistically significant correlation between SWMX seasonal percent departure from normal precipitation values and warm/cold events? What is the relationship between wet and dry summer monsoons in AZNM and conditions in the SW US and Pacific NW during the preceding winter? Why does this relationship exist? According to Gutzler et al., does the PDO provide any predictive skill for southwest precipitation? If so, how? If not, why not? Of all parameters related to ENSO that we have read (including Gutzler et al. and Higgins et al.), which one parameter (if any) is best correlated to above normal, normal, or below normal North American Monsoon activity?

2 Pacific Decadal Oscillation (PDO) The Pacific Decadal Oscillation (henceforth known as PDO) is a long-lived El Niño like pattern of Pacific climate variability. The first EOF of SSTs in the North Pacific Ocean. Most visible in the North Pacific/North American sector. Source:

3 Pacific Decadal Oscillation (PDO) Cool PDO regimes have occurred twice in recent instrumental history: and Warm PDO regimes have occurred: and since th Century periodicities have shown to run between years and as long as 70 years. Source:

4 Pacific Decadal Oscillation (PDO) Warm Phase Cold Phase Source:

5 Pacific Decadal Oscillation (PDO) Source:

6 PDO, ENSO, and SW US Winter Precipitation Measurements taken from Niño-3 SST Index (5 N-5 S, W).

7 PDO, ENSO and SW US Winter Precipitation ENSO signal in wintertime North America climate anomalies is significantly enhanced when the PDO and ENSO constructively interfere (El Niño + high PDO, La Niña + low PDO) The opposite is true if the PDO and ENSO destructively interfere (El Niño + low PDO, La Niña + high PDO). Source: Gutzler et al. (2002)

8 PDO, ENSO, and SW US Winter Precipitation Source: Gutzler et al. (2002)

9 PDO, ENSO, and SW US Winter Precipitation It should be noted that the bottom figure is just from Fort Bayard, NM (a.k.a. the Southwest Mountains division of NM). The southwest portion of NM is not all mountains, despite the description. There is a desert plain out there notorious for blowing dust.

10 PDO, ENSO, and SW US Winter Precipitation Based on priori hypothesis (from previous studies), the upper-tercile Niño-3 or PDO values should systematically lead to uppertercile precipitation anomalies. Lower-tercile SST indices should lead to lower-tercile precipitation anomalies. Source: Gutzler et al. (2002)

11 PDO, ENSO, and SW US Winter Precipitation Assessment of predictive skill was carried out using a modified Brier score. X + Y + Z = N (where X = # of dry (lower tercile) precipitation anomalies, Y = the number of near-normal anomalies, Z = the number of wet anomalies, and N is the number of winters under consideration). If the relationship of Niño-3 were perfect, then the precipitation anomaly would be x/y/z = 0/0/N. If Niño-3 values has no effect, then the expected tercile distribution would be even (i.e. x/y/z = a/a/a, where a = N/3). Source: Gutzler et al. (2002)

12 PDO, ENSO, and SW US Winter Precipitation To define predictive skill, x/y/z is scored by using a 0 (hit), 1 (observed medial anomaly), 2 (wrong). Distributions of wet winter predictions (following positive Niño-3 or PDO values), the skill score is: S+ = (2x + y)/n Distributions of dry winter predictions (following negative Niño-3 or PDO values), the skill score is: S- = (y + 2z)/N Source: Gutzler et al. (2002)

13 PDO, ENSO, and SW US Winter Precipitation Source: Gutzler et al. (2002)

14 PDO, ENSO, and SW US Winter Precipitation Negative PDO yields NO predictive skill at all! Positive PDO generates slightly less seasonal predictive skill of winter precipitation than does warm Niño-3. This generally shows that PDO cannot be reliably used as a predictive parameter. Source: Gutzler et al. (2002)

15 PDO, ENSO, and SW US Winter Precipitation Warm Niño-3 demonstrates a historically strong positive effect on Winter precipitation in the NM4 climate division. Cold Niño-3 shows little or no basis for a long-lead outlook that is different from climatology. This shows that this parameter can only be reliable when Niño-3 is warm. Source: Gutzler et al. (2002)

16 1970 s Regime Shift Source: Gutzler et al. (2002)

17 1970 s Regime Shift Pre-1977 period, the PDO was largely negative, predictive skill was high for cold Niño-3 temperatures leading dry winters in the southwest. Post-1977 period, an asymmetry in predictability reversed, and El Niño was a better basis for a seasonal forecast than La Niña.

18 Skill-score Maps Figures 3 and 4

19 Skill-score Maps

20 Skill-score Maps After the 1977 PDO shift Prior to the 1977 PDO Regime

21 Gutzler et al. (2002) Conclusions PDO regime shift in 1977 changed the predictability of SW US Winter Precipitation using Nino-3 SST s. Using PDO (either + or -) as a prediction parameter had little or no skill in determining SW US winter precipitation. Using Nino-3 for warm events were useful as a predictive parameter, however cold events were not.

22 Monsoon Introduction Monsoon: Seasonal wind reversal related to differential heating between a land mass and the adjacent ocean /ecol438/monsoon.gif

23 North American Monsoon System Pronounced warm-season (JJAS) increase in precipitation associated with convective activity over Mexico and southwestern US Centered over Sierra Madre Occidental Seasonal warming of land (high elevation, too) plus moisture from nearby maritime sources (Gulf of CA, eastern Pacific) Adams and Comrie,

24 North American Monsoon System North American Monsoon Experiment (NAME)

25 Higgins et al. (1999) Regions and Data 3 Regions: AZNM: Arizona-New Mexico NWMEX: Northwest Mexico SWMEX: Southwest Mexico Time period: Jan 1963-Dec 1988 Data: hourly (US)/daily (Mexico) precipitation observations combined and averaged into 2 x2.5 grid cells over 3 regions ENSO: 5 month running average of the SOI (pos=la Niña, neg=el Niño) Cold or Warm episodes from

26 AZNM NWMEX SWMEX

27 Characteristics of NAMS: Onset 0.5 mm/day, 3 days 1 mm/day, 5 days 2 mm/day, 5 days

28 Characteristics of NAMS: Onset Average of all monsoons in each region relative to the day when the threshold criteria are passed Onset day = 0 Average Calendar Date Onset: AZNM = July 7 NWMEX = 17 June SWMEX = 7 June

29 Characteristics of NAMS: Precipitation

30 Characteristics of NAMS: Precipitation

31 Characteristics of NAMS: Low and Upper-Level Flow

32 Characteristics of NAMS: Low and Upper-Level Flow

33 Characteristics of NAMS: Regional Precipitation AZ, Sonora, Jalisco: single peak, monsoon max TX, OK, MT: two peaks (May, September) due to out-of-phase relationship between SW precipitation and Great Plains/Northern Tier precipitation Oaxaca: two peaks (June and September) due to migration of ITCZ

34 Interannual Variability of NAMS Precipitation Correlations of seasonal % departure of precipitation for: AZNM and NWMEX: 0.54 (sig. at 95%level) AZNM and SWMEX: 0.02 NWMEX and SWMEX: 0.26 AZNM and NWMEX are still disparate regions (based on mean precip, onset date)

35 Interannual Variability of NAMS Precipitation and the SOI Correlations of Seasonal % Departure from Normal Precip and the SOI: AZNM and SOI: NWMEX and SOI: 0.18 SWMEX and SOI: 0.48 (sig. At 95% level) Wet (dry) summer monsoons in SWMEX tend to be associated with La Niña (El Niño)

36 Interannual Variability of NAMS Precipitation and ENSO Composite Seasonal % Departure: AZNM NWMEX SWMEX El Niño La Niña El Niño = deficient monsoons in NWMEX and SWMEX La Niña = heavy monsoons in SWMEX and deficient monsoons in AZNM

37 Interannual Variability of NAMS Onset Correlations of Onset Date: AZNM and NWMEX: 0.18 AZNM and SWMEX: 0.33 NWMEX and SWMEX: 0.22 Onset is regionally independent

38 Interannual Variability of NAMS Onset Early Monsoons in AZNM: several months of above average precipitation Late monsoons in NWMEX: several months of below average precipitation Generally more intraseasonal fluctuations Correlation between SOI and onset date: SOI AZNM NWMEX 0.27 SWMEX Onset is not related to ENSO

39 NAMS Onset and Regional Precipitation

40 NAMS Onset and Regional Precipitation 60-Day period after onset of SWMEX monsoon: AZNM and NWMEX: 0.80 (sig. at 95% level) AZNM and SWMEX: 0.47 (sig. at 95% level) NWMEX and SWMEX: 0.70 (sig. at 95% level) 60-Day period after onset of NWMEX monsoon: AZNM and NWMEX: 0.75 (sig. at 95% level) AZNM and SWMEX: 0.26 NWMEX and SWMEX: 0.53 (sig. at 95% level) 60-Day period after onset of AZNM monsoon: AZNM and NWMEX: 0.31 AZNM and SWMEX: NWMEX and SWMEX: 0.15 Early (late) monsoons in SWMEX favor less (more) rainfall over all 3 regions

41 Characteristics of Wet and Dry Monsoons Composite JJAS % Departure from Normal for: AZNM NWMEX SWMEX Wet Dry Wet (dry) monsoons in AZNM are preceded by dry (wet) conditions during the previous winter in the SW and wet (dry) conditions in the Pacific NW. Why?

42 Composite Precip. Anomalies vs ENSO SWMEX wet and La Nina: r= 0.67 SWMEX dry and El Nino: r= 0.71

43

44

45 Higgins et al. (1999) Conclusions Does ENSO modulate the interannual variability of the NAMS? Wet (dry) summer monsoons in SWMEX are associated with La Nina (El Nino) Dry monsoons in NWMEX in El Nino years? Dry monsoons in AZNM in La Nina years? What about the scarcity of data (only 6 El Ninos and 5 La Ninas to work with)?

46 Other conclusions Adams and Comrie (1997) concluded that any relationship between ENSO and the NAMS remains elusive. Harrington et al. (1992) concluded that no correlation could be established between ENSO and the NAMS. Reyes (1988) concluded that precipitation could be enhanced in the southern (i.e. Mexico) region according to ITCZ activity and ENSO.

47 So does the data support Higgins conclusions? In Higgins own paper, 5 COLD events were used to draw a broad conclusion of the region overall. The variation in AZNM is considerable given what he used. The percent departure ranged from -42.9% %, which is a HUGE range. Higgins concluded for 6 WARM events that NWMEX was dry during the El Nino events. However, with only 6 events used, and one of those events stating otherwise, how can such a conclusion be drawn? Higgins concluded that wet (dry) summer monsoons in SWMEX are associated with La Nina (El Nino). In his own data, 1987 was called a WARM year with a +10.9% departure. In 1988, a COLD year, the departure was still positive with a +15.3%.

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