1. Relationship between Antecedent Land Surface Conditions and Warm Season Precipitation in the North American Monsoon Region Chunmei Zhu a, Dennis P. Lettenmaier a, and Tereza Cavazos b a Department of Civil & Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195 b Department of Physical Oceanography, Centro de Investigacion Cientifica de Educacion, Superior de Ensenada, Ensenada, Mexico Introduction We explore possible links between North American Monsoon System (NAMS) seasonal (Jun-Jul- Aug-Sep) precipitation and pre-monsoon seasonal land surface conditions including precipitation (P), temperature (T), soil moisture (Sm) and snow water equivalent (SWE) anomalies. We found statistically negatively significant winter precipitation and snow related regions in SW and the mountainous region in UT and CO respectively. Their linkage with Monsoon West (Arizona and western New Mexico) monsoon rainfall is strong from 1965-1990s and weak otherwise, as has suggested by previous studies. We proposed a land surface feedback hypothesis: winter P leads to more winter and early spring SWE in the predictor area, hence more spring and early summer Sm, and lower spring and early summer Ts, which induces a weaker onset of the NAMS and vice versa. We tested all of the 3 links in this hypothesis and confirmed the existence of the land memory of winter precipitation and snow anomaly. This land memory can even persist from April, May into June. However, our results show that this land memory contributes little to the magnitude of NAM precipitation. It is interesting that the pre-monsoon (June) surface temperature over the U.S. Southwest desert shows a negative relationship with monsoon precipitation, which is the reverse of what we expect based on the monsoon driving force concept of land-sea temperature contrasts. The apparent reason is the June upper-troposphere atmospheric circulation pattern: the June 500 mb positive anomalies in dry years induces an increase in surface temperature in the U.S. Southwest, and vice versa. References: Comrie A.C. and E.C. Glenn, 1998: Principal components-based regionalization of precipitation regimes across the southwest United States and northern Mexico, with an application to monsoon precipitation variability. Clim. Res., 10, 201-215.Guzler D.S., 2000: Co variability of spring snowpack and summer rainfall across the southwest United States. J. Climate, 13, 4018-1027. Higgins R.W. and W.Shi, 2000: Dominant factors responsible for interannual variability of the summer monsoon in the Southwestern United States. J. Climate, 13, 759-776. Hu Q. and F. Song, 2002: Interannual rainfall variations in the North American Summer Monsoon Region: 1900-98. J. Climate, 15, 1189-1202. Lo F. and M.P. Clark, 2002: Relationships between spring snow mass and summer precipitation in the Southwestern United States associated with North American monsoon system. J. Climate, 15, 1378-1385. Matsui T, V. Lakshml and B. Small, 2003: Links between snow cover, surface skin temperature, and rainfall variability in the North American Monsoon system. J. Climate, 16, 1821-1829. Maurer E.P., A.W. Wood, J.C. Adam, D.P. Lettenmaier, and B. Nijssen, 2002: A long-term hydrologically-based data set of land surface fluxes and states for the conterminous United States. J. Climate, Vol. 15, 3237–3251. Study Domain 1 The figures show apparent relationships between strong and weak MW monsoon precipitation and soil moisture in the preceding spring. The lower left figure shows the strong (weak) monsoons are associated with dry (wet) antecedent soil moisture. Note that the left figure appears similar to higher left figure, and indicates that spring soil moisture in the Southwest is a reflection of winter precipitation. The right figure is is for June, and confirms that in much of the Southwest, soil moisture anomalies persist from winter through the following spring (immediately prior to the monsoon). Note that the Great Plains and Southwest show reverse signals. Winter Precipitation-monsoon rainfall feedback hypothesis 2 4 5 Figure 2a: Monsoon West winter predictor region. Conclusions: ● Southwest winter precipitation could be a potential predictor for MW summer monsoon, even though this relationship varies with time, strong from 1965-1990s and weak otherwise ● SW USA has land memory of winter precipitation, and this land memory can even persist through April, May into June. However, it contributes little to the magnitude of NAM precipitation. ● June positive Z500 anomalies in dry years induce an increase in surface temperature in AZ/NV, vice versa for wet years. The atmospheric circulation pattern causes the negative relationship between monsoon precipitation and June Ts in SW desert region. Monsoon West Monsoon South Monsoon North Monsoon East Monsoon regions are defined as in Comrie & Glenn paper (1998) based on the seasonality and variability of JJAS monsoon precipitation from 1961-1990. In the following section we evaluate the possible effects of previous land surface conditions in various subcontinental “predictor regions” on Monsoon West (MW) monsoon precipitation. Winter Precipitation, Snow - JJAS MW Rainfall Figure 2b: 15-year moving average correlation of JJAS MW rainfall with winter precipitation index ● The statistically significant negatively related winter precipitation region includes southern California, Nevada, Utah, Arizona, western Colorado and New Mexico, which is the potential winter predictor region for MW monsoon rainfall (Figure 2a). ● A snow index equal to JFM SWE in the mountainous part of the U.s. Southwest (blue area in Figure 2c) and JJAS MW precipitation shows a negative correlation. ● The negative relationship varies in strength. It is strong during the 1965-1990 period, but weak otherwise (Figure 2b,2d). MW JFM relative precipitation anomaly composite for extreme years 3 Figure 2c: Monsoon West snow index area Figure 2d: 15-year moving average correlation of MW snow index versus JJAS monsoon rainfall 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 Winter precipitation – spring soil moisture link Soil moisture – surface temperature link Beyond what we expect, June surface air temperature anomaly map in extreme years (lower left) in Southwest doesn’t show the opposite pattern of June soil moisture (upper left), which is consistent with the correlation map of June soil moisture and surface temperature (upper right). In Southwest, there is no significant negative relationship between soil moisture and surface air temperature in pre-monsoon season June. Why? Pre-monsoon SAT – monsoon precipitation Antecedent June surface air temperature (SAT) in Northern AZ and in the Southern Rockies is positively correlated with July MW precipitation. However in the core of the monsoon (SW lower desert) the relationship is negative. Daily area (red circle in left figure) mean precipitation shows this negative relationship is not related with the earlier arrival of monsoon rainfall there (lower figure). × Correlation of June soil moisture vs. June SAT 6 SW desert daily precipitation in wet years (red) and dry years (green) from 1 June to 30 July. Period: 1965-1999. 7 500mb Geopotential height (Z500) – surface air temperature June Z500 anomaly maps in extreme years (upper figures) show similar pattern with June SAT anomaly maps (lower figure in section 5 ), suggesting the correlation between upper-tropospheric circulation pattern with surface air temperature. Z500 could have impact on surface air temperature. The June Z500 higher anomaly in dry years induces warmer surface temperature and vice versa for wet years. One reason may be the small evapotranspiration signal in this semiarid area (right Fig.), the sparse vegetation in the SW doesn’t favor much extraction of soil water from the deep soils where most of the moisture is stored. The long-term mean June evaporation spatial distribution (right Fig.) exhibits somewhat a consistent pattern with June Sm and June Ts correlation map (upper right in this box)