24
Downstream weather impacts associated with atmospheric blocking: Linkage between low-frequency variability and weather extremes Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

  • Upload
    markku

  • View
    30

  • Download
    0

Embed Size (px)

DESCRIPTION

Downstream weather impacts associated with atmospheric blocking: Linkage between low-frequency variability and weather extremes. Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA. Objective. - PowerPoint PPT Presentation

Citation preview

Page 1: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Downstream weather impacts associated with atmospheric

blocking:

Linkage between low-frequency variability and weather extremes

Marco L. Carrera, R. W. Higgins and V. E. Kousky

Climate Prediction Center NCEP/NWS/NOAA

Page 2: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Objective • To assess the relationship between weather extremes and atmospheric

blocking.• Do the statistical distributions of temperature and precipitation change

during blocking regimes?

Motivation• During the NH cool season atmospheric blocking occurs

frequently over the North Pacific and North Atlantic Oceans.• Strong and persistent atmospheric blocks are often associated

with anomalous storm tracks which can influence monthly and seasonal values of temperature and precipitation.

Page 3: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Gulf of Alaska Blocking• High-amplitude ridging over the Gulf of Alaska

has been identified as one of the principal flow regimes dominating the Pacific-North American sector during the NH cool season (Stoss and Mullen 1995; Robertson and Ghil 1999).

• Positive height anomalies in the vicinity of Alaska have been linked to heavy precipitation events along the US West Coast (Ely et al. 1994; Lackmann and Gyakum 1999).

• The persistence of positive 700 hPa height anomalies in northern Alaska is an important predictor of monthly mean surface temperatures over the US (Klein 1983).

Page 4: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Data• Daily averaged 500 hPa heights from

NCEP/NCAR reanalysis, 1979-2000.

• Global gridded daily mean temperature, 2.5o resolution, 1979-.

• Historical unified US-Mexico Precipitation Dataset, 1o resolution, 1948-2000.

Page 5: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Methodology: Identification of Blocking Events

• 500 hPa heights: Anomalies calculated first by removing the local seasonal cycle (Mean + 1st 2 harmonics) and then applying a 10 day low-pass filter (Lanczos 121 weights).

• Threshold crossing procedure of Dole and Gordon (1983) applied to anomaly time-series for DJFM 1979-2000 at key point 162.5oW, 62.5oN.

• Threshold and duration criteria used were (100m, 8 days).

• Result: 37 events with durations ranging from 8 days to 25 days with a mean duration of 11.3 days.

• Percentage of days belonging to a blocking events is 15.6%.

Page 6: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Interannual Variability of Gulf of Alaska Blocking

Number of

Blocked Days

Page 7: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Time-Averaged Circulation During Blocking Events

Page 8: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Onset Time

Page 9: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

End Time

Page 10: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Time-Averaged over 11 Day Period Prior to

Blocking

Time-Averaged over Duration of Blocking

Events

Time-Averaged over 11 Day Period After

Blocking

Page 11: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Onset Time

Page 12: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

End Time

Page 13: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Onset Time

Page 14: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

End Time

Page 15: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Statistical Distribution of Mean Daily Temperature During Blocking Regime• Calculate the daily anomalies of mean temperature by

removing a smooth annual cycle (defined as mean daily values for each day of the year based upon the 22 year period 1979-2000).

• Consider all DJFMs from 1979 to 2000 and calculate the upper and lower tercile percentiles of the daily anomalies. By definition, each tercile will contain 1/3rd of the daily anomalies.

• For the subset of days during DJFM 1979-2000 belonging

to the “blocking regime” calculate the number of days with daily temperature anomalies in each of the three terciles.

Page 16: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

BLOCKING REGIME

Page 17: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA
Page 18: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA
Page 19: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

At least 1 Day of Daily Area-Averaged

Precipitation over Southern California >

90th Percentile

At least 1 Day of Daily Area-Averaged

Precipitation over Ohio Valley > 90th Percentile

Page 20: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Onset Time

Page 21: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Summary1. Interannual Variability

• Gulf of Alaska blocking is sensitive to the phase of ENSO. Reduced (increased) number of blocking days during El Niño (La Niña/Neutral) conditions.

• Difference in the mean number of blocked days between El Niño and Neutral DJFMs is statistically significant at the 99% level.

Page 22: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Summary Cont’d2. Mean Daily Temperature Distribution During

Blocking Comparison of blocking regime with the DJFM 1979-2000

mean daily temperature distribution:

• (i) in the region extending from northern British Columbia southeastwards to the southern Plains of the US a dramatic increase in the number of blocking days with daily temperature anomalies in the lower tercile, 30-40% greater than the expected number of 33.3%,

• (ii) in this same region there is increase in the occurrence of extreme cold days,

• (iii) in western Alaska an increase a dramatic increase in the number of blocking days with daily temperature anomalies in the upper tercile, up to 25% greater than expected (33.3%),

• (iv) in this same region there is an increase in the occurrence of extreme warm days.

Page 23: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Summary Cont’d3. Daily Precipitation Analysis Results not as robust as for mean daily

temperature.

• Two key regions with an increased frequency of heavy precipitation events during Gulf of Alaska blocking: (I) US Southwest, (II) Ohio Valley and Southeast.

• Stratification of the 37 blocking events based upon heavy precipitation occurrence over Southern California and the Ohio Valley revealed;

• (i) Southern California: equatorward of the blocking ridge, the anomalous storm track and the associated southwesterly moisture transports (“pineapple express”) are more prominent and extend eastward toward the US West Coast,

• (ii) Ohio Valley: enhanced ridging off the US East Coast a few days after block onset is associated with anomalous southerly moisture transports from the Gulf of Mexico.

Page 24: Marco L. Carrera, R. W. Higgins and V. E. Kousky Climate Prediction Center NCEP/NWS/NOAA

Future Work

• Determine the statistical significance of the frequency changes of daily mean temperature anomalies and precipitation during the blocking regime. Bootstrapping methods selecting individual blocks of data to preserve the temporal correlation in the data.

• Make use of a global pentad precipitation dataset to examine the precipitation structures over oceanic regions.

• Examine the downstream weather impacts associated with blocking episodes further west over the eastern North Pacific.