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US Precipitation and Temperature Trends Analysis by Dr. Imke Durre

Explore annual US-averaged precipitation trends and temperature projections. Investigate seasonal differences, heavy event frequency, and factors impacting trends. Understand the significance of temperature variations and challenges in observing and analyzing trends. Contact Dr. Imke Durre for insightful information.

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US Precipitation and Temperature Trends Analysis by Dr. Imke Durre

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  1. US Precipitation and Temperature Trends Dr. Imke Durre Contact: Imke.Durre@noaa.gov +1 828 271 4870

  2. Annual US-Averaged Precipitation

  3. M Model precipitation projections, smoothed with a 13-year filter.

  4. Precipitation: What happened and why? Seasonal differences in spatial patterns of trends in amount: * Precise seasonal evolution of trends? * Relevant factors? Increased frequency of heavy events during the past three decades: * Sensitivity to analysis technique? * Interdecadal variability or global warming? Frequency distribution of amounts: * Are we observing it correctly? * Do we understand its variations?

  5. Annual US-Averaged TMAX/TMIN 1979-2005: TMAX Trend: +0.30 C/Decade TMIN Trend: +0.31 C/Decade

  6. Annual US-Averaged DTR

  7. from Dai et al. (2006)

  8. Surface Air Temperature trends 1958-1999 (DJFM) from Quadrelli and Wallace (2004) Linear Trend Component of trend that’s linearly congruent with the two leading PCs of the detrended SLP field. Residual Trend

  9. Temperature: What happened and why? Trend towards fewer cold days in winter: * Boundary layer feedbacks? Summertime diurnal asymmetry in trends: * Water vapor feedback? Significant local trends: * Natural?

  10. Winter Inversions: Heights of Warmest Levels

  11. Tucson

  12. Negative Correlations Between 850-SFC Precipitable Water and Cooling Rate

  13. Major Challenges What's natural and what isn't? * Significant local temperature trends * Precipitation characteristics and changes Addressing shortcomings of linear trends: * Need for less arbitrary methods for analyzing variations * Need for diagnosing simultaneous observed variations in multiple variables Local versus large-scale feedbacks * Relative importance? * Interactions? Role of the boundary layer?

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