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Land Surface Processes in NAMS

Land Surface Processes in NAMS

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Land Surface Processes in NAMS

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  1. Land Surface Processes in NAMS Dennis P. Lettenmaier Department of Civil and Environmental Engineering University of Washington for presentation at Eighth Annual Meeting of WCRP/CLIVAR/VAMOS Panel (VPM8) Mexico City March 7, 2005

  2. Motivation for talk • Draws from our own work (esp. Zhu et al, 2005) • Attempts to generalize hypotheses, and identify ways in which ongoing and future work can test them

  3. Hypothesis for land surface role in NAMS • Anomalously wet (dry) monsoon years tend to be preceded by anomalously dry (wet) antecedent winter precipitation (e.g. Higgins et al, 1998; 2000), and/or • Anomalously wet (dry) monsoon years tend to be preceded by anomalously low (high) snowpack in the previous winter (e.g. Gutzler and Preston, 1997) • Hypothesized mechanisms are different, but both lead to enhanced (suppressed) land-ocean contrast, hence strong (weak) NAMS • Reality is, of course, more complicated – questions of lag/lead, geographic location of signal, stability over time

  4. Monsoon West Monsoon South Monsoon North Monsoon East Study Domain Monsoon regions are defined as in Comrie & Glenn (1998)

  5. JFM PI 15-year Moving Average Correlation of PI versus MW JJAS rainfall JFM Precipitation Index (PI) Winter Precipitation – Monsoon Relationship

  6. 15-year Moving Average Correlation of SWE versus MW JJAS rainfall April Snow Index (SWE) Snow – Monsoon Relationship

  7. Winter Precipitation - Monsoon Rainfall feedback hypothesis Higher (lower) winter precipitation & spring snowpack More (less) spring & early summer soil moisture Lower (higher) spring & early summer surface temperature Weak (strong) monsoon Higher (lower) winter precipitation and spring snowpack More (less) spring or early summer soil moisture lower (higher) spring and early summer surface temperature Weak (strong) monsoon

  8. DRY WET WET DRY Wet Monsoon Dry Monsoon JFM Precipitation in extreme monsoon years Apr-May Soil Moisture in extreme monsoon years

  9. Dry Wet Soil moisture anomalies persist from spring until June Correlation of June Sm & JFM PI (1965-1999) What is the feedback to the atmosphere ?

  10. Correlation: April SWE & May-June Ts (Negative relationship ) Correlation: June Sm & June Ts (No significant relationship in MW ) SW Sm has no significant relationship with Ts

  11. Dry Wet Cold Warm June Sm in extreme monsoon years × × June Ts in extreme monsoon years

  12. Winter Precipitation - Monsoon Rainfall feedback hypothesis Higher (lower) winter precipitation & spring snowpack More (less) spring & early summer soil moisture × ? Lower (higher) spring & early summer surface temperature Weak (strong) monsoon

  13. Correlation: June Ts & July MW precipitation SW desert daily precipitation in extreme years Negative correlation between SW desert pre-monsoon Ts & July precipitation ? Wet years June 30 Dry years

  14. North American Monsoon Conceptual Basis • The combination of seasonally warm land surfaces in lowlands and elevated areas together with atmospheric moisture supplied by nearby maritime sources is conductive to the formation of a monsoon like system. ( Adams D. K and A. C. Comrie, 1997: The North American Monsoon. Bull. Amer. Meter. Soc.,2197-2213. ) • The inverse spring snow – summer rainfall relationship proposes the hypothesis intuitively: excessive spring snow means cold continental temperature, thus inhibiting the summer time land surface heating that drives the monsoon. (Gutzler D. S. and J. W. Preston, 1997: Evidence for a relationship between spring snow cover in North America and summer rainfall in New Mexico. Geophys. Res. Let., 24, 2207-2210.) Higher (lower) June TsStronger (weaker) monsoon

  15. Wet Monsoon June High Low Z500 (m) anomalies in wet years June Ts anomalies in wet years

  16. Dry Monsoon June Low High June Ts anomalies in dry years Z500 (m) anomalies in dry years The strong positive relationship between June Ts and Z500 anomalies, suggesting that pre-monsoon Ts are not modulated by the local land-surface conditions.

  17. Summary ● Southwest winter precipitation is a potential predictor for MW summer monsoon, even though this relationship varies with time ● Spring land surface conditions in the SW U.S. are strongly determined by the previous winter’s precipitation, and this land memory can persist through April and May into June. However, this memory appears to contribute little to the magnitude of NAM precipitation. ● June positive Z500 anomalies in dry years induce an increase in surface temperature in AZ and NV, and vice versa for wet year, which suggesting that the controlling factor for the pre-monsoon Ts anomalies may not be local

  18. Comments • Question as to whether (lack of) persistence in soil moisture from previous winter-spring to onset of monsoon is model artifact • Coupled model experiments (possibly along lines of Koster-Suarez land-ocean-atmosphere coupling design) are probably needed to make further progress • Such experiments have been hampered in the past by model-specific behavior, and/or lack of consistency between off-line and coupled land schemes. • Latter can be resolved by multi-model ensemble framework for off-line runs, and consistent LDAS forcing data for NAMS region (which have now been assembled)