1. Conclusions: ● We produced a long-term observation-derived and hydrological model-derived dataset of land surface fluxes and states with a period of 1950-2002, at 1/8 degree resolution for the whole Mexico. Because the simulated runoff is shown to match with observations well over some small river basins. it is argued that the other water balance components such as soil moisture and evapotranspiration is well presented at least in an acceptable quality. ● The pre-monsoon season (JFM and AM) land surface conditions may partly influence Monsoon South summer precipitation through precipitation - soil moisture – surface temperature feedback mechanism at least for extreme years. The upper-tropospheric circulation condition may also play an important role in the surface thermal condition, thus influence on the summer monsoon. The relative importance of land surface feedback and atmospheric circulation effect on the monsoon system needs to be further investigated. The Role of Antecedent Land Surface Conditions in Warm Season Monsoon Precipitation over Northwestern Mexico 1950-2002: a Study Based on a Long-Term Hydrological Dataset of Land Surface Fluxes and States for Mexico 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 The role of antecedent (previous autumn, winter, and spring) land surface conditions (precipitation, surface air temperature, soil moisture, snow cover) in the North American Monsoon (NAM) warm season (Jun-Jul-Aug-Sep) is important for improving seasonal monsoon predictability, especially for the NAM core region of northwestern Mexico. Unlike its Asian monsoon sister, relatively little previous work has addressed NAM teleconnections over Northwestern Mexico through data analysis because of the lack of land surface variables such as soil moisture over a long enough time period, and sufficient spatial extent, to support meaningful analyses. In this study, a long-term observation-derived and hydrological model-derived data set of land surface fluxes and states is presented for Mexico. This data set spans the period of 1950 – 2002 at 3 hourly time step with a spatial resolution of 1/8 degree. Precipitation and surface air temperature are gridded directly from observations. Production of these gridded data sets is a major challenge because of the sparse gauge station distribution and discontinuous gage records over Mexico. In this effort, we combined three different sources of station data : ERIC2, a product (1940-1998) from the Mexican Institute of Technology of Water (IMTA) of the SEMARNAP; DATA322, produced by SMN (Servicio MeterorolÓgico Nacional, 2000) with some stations dating back to the 1915; and SMN daily historical precipitation data ( 1995 – near real-time), to create gridded forcing data of acceptable quality for long-term (1950-2002) retrospective runs with the Variable Infiltration Capacity (VIC) macroscale hydrology model. Simulated runoff is shown to match with observations well over some small river basins in northwestern Mexico. On this basis, and given the physically based model parameterizations, we argue that the other water balance components such as soil moisture and evapotranspiration are represented well enough to support our preliminary analysis study of land surface feedback mechanisms. The land surface predictors used in the preliminary study are monthly aggregates from the 1950-2002 VIC archive. The retrospective archive includes gridded precipitation (P), mean surface air temperature (Ts), and Variable Infiltration Capacity (VIC) land surface model-derived soil moisture (Sm). We found in extreme years that there may exist a precipitation - soil moisture – surface temperature land surface feedback mechanism which affects the Monsoon South summer precipitation. The pre-monsoon season (JFM and AM) precipitation shows the reverse relationship with summer monsoon in extreme years with dry (wet) monsoon preceded by wet (dry) winter and spring in SW USA and upper part of Northwestern Mexico. Spring soil moisture has memory of winter and spring precipitation anomaly signal, and this soil memory negatively correlates with pre-monsoon surface air temperature, which directly influences the initiation of the monsoon circulation. Besides the land surface conditions, the upper- tropospheric circulation condition may also play an important role in the surface thermal condition, thus affects the summer monsoon. The relative importance of land surface feedback and atmospheric circulation effect on the monsoon system needs to be further investigated in future study. 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. Hu Q. and F. Song, 2002: Interannual rainfall variations in the North American Summer Monsoon Region: 1900-98. J. Climate, 15, 1189-1202. 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. Zhu, C.M., D.P. Lettenmaier and T. Cavazos, 2005, Role of antecedent land surface conditions on North American Monsoon rainfall variability. J. Climate. (accepted). 1 Hydrological Model 2 4 Long-term mean precipitation spatial pattern Monsoon South Monsoon North Monsoon West Monsoon East Monsoon regions are defined as in Comrie & Glenn (1998) based on the seasonality and variability of JJAS monsoon precipitation from 1961-1990. In the following section we will exhibit some preliminary analysis of the possible effects of previous land surface conditions in various subcontinental “predictor regions” on Monsoon South (MS) monsoon precipitation. Gridded Precipitation and Temperature Dataset (1925-2003) 3 This spatial plot shows reasonable pattern with lower precipitation in desert region and higher magnitude in coastal and south Mexico. Model Development Study Domain Standardized Monsoon South JJAS rainfall The streamflow dataset we are using is the Mexico acronym BANDAS, which is a product of CNA and IMTA. Because nearly all of the larger basins are regulated and up to now no naturalized streamflow can be available, we selected comparatively small basins (less than 10,000 km 2 ) with long-term records during the period 1970s-1990s (which has higher precipitation guage stations density). 5 6 VIC Model Features: ● Multiple vegetation classes in each cell ● Sub-grid elevation band definition (for snow) ● 3 soil layers used ● Energy and water budget closure at each time step ● Subgrid infiltration/runoff variability ● Non-linear baseflow generation  Surface forcing data: Daily precipitation, maximum and minimum temperatures ERIC2 (1940-1998) a product from Mexican Institute of Technology of Water (IMTA) of the SEMARNAP, over 5,000 stations Data322 (mainly for data pre-1940, and for Northwestern mexico) produced by SMN (Servicio MeterorolÓgico Nacional, 2000), around 70 stations extending back to 1920s. SMN daily historical precipitation data (1995 – near realtime) provided courtesy of Miguel Cortez Vázquez of SMN, around 1,000 stations. Guage Station Distribution (ERIC2)  Soil parameters: derived from FAO global soil map.  Vegetation coverage from the University of Maryland 1-km Global Land Cover product (derived from AVHRR) SMN ERIC2 Data322 This plot shows lower temperature over mountainous area (~10C), and higher value over the coastal line especially in South Mexico. Comparisons with SMN climatologic Tmean over some state’s capitals (http://smn.cna.gob.mx/productos/normale s/medias.html) :http://smn.cna.gob.mx/productos/normale s/medias.html SMN (1961-1990)Gridded(1925-2003) LatLon TmeanLatLon Tmean 24.8-107.1524.524.8125-107.187525.33 24.4-106.724.924.4375-106.687523.00 19.2-103.826.119.1875-103.812526.995 18.8-103.6726.218.8125-103.6875 27.51 17.9-101.7827.017.9375-101.812528.36 17.38-101.0726.717.4375-101.062527.30 16.37-98.0527.416.3025-98.062528.14 15.5-93.0727.415.4375-93.062528.50 22.83-99.2325.022.8125-99.187525.68 Long-term mean daily temperature Regional Precipitation Comparison with CPC data NW Mex Mex East Mex South NW Mexico Mex East VIC Model Features: Mex South Basically, the regional precipitation temporal pattern of our dataset matches with CPC very well except for differences in southern Mexico. These differences are attributable to differences in spatial resolution and gridding methods. Comparison of simulated and observed streamflow 1 2 3 4 56 7 8 9 11 12 13 10 15 14 In most cases, simulated hydrographs show acceptable correspondence with observations, except that sometimes the simulations have much higher peaks These higher peaks could be associated with bias in the observed precipitation. The general match between simulation and observation shows that water balance components such as soil moisture and evapotranspiration is well presented at least in an acceptable quality, which support our preliminary analysis study of land surface feedback mechanism shown in later section. Pre-monsoon Winter and Spring Precipitation - Soil Moisture Wet years 1954 1955 1958 1959 1963 1966 1984 1990 Dry years 1951 1979 1982 1987 1992 2000 Through correlation analysis, we cannot find any robust correlation of JJAS MS rainfall vs. JFM or AM precipitation as we found for Monsoon West (Zhu et al, 2005). But for extreme years, there exist some strong signals ( shown in above figures ) that dry (wet) monsoon is preceded by wet (dry) winter and spring in SW USA and upper part of Northwestern Mexico especially for dry years. Soil moisture has memory of winter and spring precipitation anomaly in SW USA and Northern Mexico. 7 Land Surface Feedback or Atmospheric Circulation effect? The May surface air temperature anomaly map above is consistent with the land-sea thermal contrast concept for the monsoon initiation. Wet monsoon years has higher surface temperature than normal, the reverse is true for dry years. May soil moisture negatively correlates with temperature in the region with the strong temperature anomaly signal (left figure), implying that pre-monsoon land surface conditions may affect the monsoon system through it’s effect on the surface thermal condition. Z500 anomaly map shows the consistent pattern with temperature anomaly map, indicating atmospheric circulation may influence surface temperature and thus play an important role in the monsoon circulation.