Monthly correlation coefficients between Niņo 3 SST anomalies and MODIS land surface variables for the period 2001-2010 indicate a strong relationship between these variables. Changes in ENSO cause variations in skin temperature (Tskin), vegetation cover, and precipitable water vapor (PWV) through two mechanisms: large-scale climate dynamics (such as cloud cover, rainfall, and circulation) and local impacts (topography, land cover change). In the month of January, Niņo 3 SST anomalies are positively correlated with Tskin over the western USA and much of Eurasia, while notably strong negative correlation coefficients are present over northern Mexico. This suggests that during El Niņo events, warmer skin temperatures tend to be present over the first two regions while cooler conditions occur in the latter region. Certain areas, such as the Norway/Sweden/Finland region, have strongly positive/negative correlations for January and vice versa for July, with values of -0.4 to -1 in January and 0.2 to 1 in July. Standard deviation plots of yearly correlation coefficients are examined to determine areas of high variance, and show that the regions with Tskin most sensitive to ENSO are generally in the Southern Hemisphere latitudes between 0°-40°S, including parts of South America, southern Africa, and much of Australia. This also helps to determine which land surface types are most sensitive to changes in ENSO, and gives evidence of the local mechanisms. In Australia, strongly negative correlations occur in the central lowlands, while positive values are present in the mountains. The January correlation coefficients between Niņo 3 SST anomalies and PWV show a striking resemblance to those for Niņo 3 SST anomalies and Tskin, which illustrates a strong connection between these two variables (greenhouse effect). This research will be useful to compare to past research comparing ENSO to surface parameters measured by satellite, in particular, surface temperature, which has a different physical meaning than skin temperature.