In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS(1)database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50x50 km(2)). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe. A faithful representation of the soil moisture distribution at SMOS pixel scale (50x50 km(2)) requires an accurate estimation of the amount and temporal/spatial distribution of precipitation. To quantify the gain of using the comprehensive PERSIANN database instead of sparsely distributed rain gauge measurements, comparisons between in situ observations and satellite rainfall data are done both at point and areal scale. An overestimation of the satellite rainfall amounts is observed in most of the cases (about 66%) but the precipitation occurrences are in general retrieved (about 67%). To simulate the high variability in space and time of surface soil moisture, a Soil Vegetation Atmosphere Transfer (SVAT) model - ISBA (Interactions between Soil Biosphere Atmosphere) is used. The interest of using satellite rainfall estimates as well as the influence that the precipitation events can induce on the modelling of the water content in the soil is depicted by a comparison between different soil moisture data. Point-like and spatialized simulated data using rain gauge observations or PERSIANN - CCS database as well as ground measurements are used. It is shown that a good adequacy is reached in most part of the year, the precipitation differences having less impact upon the simulated soil moisture. The behaviour of simulated surface soil moisture at SMOS scale is verified by the use of remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E). We show that the PERSIANN database provides useful information at temporal and spatial scales in the context of soil moisture retrieval.

ObjectivesWe examined the association between comorbidity and long-term mortality from breast cancer and other causes among African-American and white women with breast cancer. MethodsA total of 170 African-American and 829 white women aged 40-84. years were followed for up to 28. years with median follow-up of 11.3 years in the Health and Functioning in Women (HFW) study. The impact of the Charlson Comorbidity Score (CCS) in the first few months following breast cancer diagnosis on the risk of mortality from breast cancer and other causes was examined using extended Cox models. ResultsMedian follow-up was significantly shorter for African-American women than their white counterparts (median 8.5 years vs. 12.3 years). Compared to white women, African-American women had significantly fewer years of education, greater body mass index, were more likely to have functional limitations and later stage at breast cancer diagnosis, and fewer had adequate financial resources (all P < 0.05). Proportionately more African-American women died of breast cancer than white women (37.1% vs. 31.4%, P = 0.15). A positive and statistically significant time-varying effect of the Charlson Comorbidity Score (CCS) on other-cause mortality persisted throughout the first 5. years of follow-up (P < 0.001) but not for its remainder. Conclusions Higher CCS was associated with increased risk of other-cause mortality, but not breast cancer specific mortality; the association did not differ among African-American and white women. © 2014 Elsevier Inc.