LTER Grad Student Workshop: Can we find anomalies in precipitation using long-term data from multiple sites?
The effects of anthropogenic-associated activities on the global climate system over the past two centuries have become undeniable, and supported by a vast body of scientific literature (IPCC, 2014). Increased levels of greenhouse gases in the atmosphere have changed the energy cycling of the global climate system, creating greater variability in temperature and precipitation. Global Climate Change models (GCM’s) are accurate at predicting changes in temperature for any given area, but are highly variable when forecasting potential changes in precipitation (Beckage, 2014). One reason for the inability of models to accurately downscale globally forecasted changes in precipitation to the regional or local-scale level. Despite inaccuracies in climate models, the effects of precipitation variability at the local and regional levels are increasingly evident, with severe droughts and floods becoming more common across the world. Therefore, a clear scientific need to investigate the magnitude of changes in precipitation at the local level has been identified.
One key mission of the LTER is to document long-term biological processes at particular designated sites: “place-based science”, and despite critiques of this approach, one strength is that LTER sites have many, large, comparable datasets. Specifically at the Luquillo LTER (LUQ), daily rainfall data have been collected dating back to 1975 using the National Atmospheric Deposition Program methodology. These data have been verified using classic rainfall collection techniques. Specifically, at LUQ the past two “weak” El Niño events (2014 & 2015) have resulted in summer droughts caused by the lack of rainfall in the month of May (the month with the highest variance in rainfall average since 1975), which have greatly affected water availability on the island and caused economic and social stress. However, despite observational evidence of an increased variability in precipitation, there is little statistical support of these claims when the data is analyzed, resulting in little scientific evidence for these claims and an inability to forecast precipitation variability into the future. The question is: Can we find statistical evidence of increasing variance in precipitation records from LTER sites over time, using site precipitation data? If so, this would be a crucial finding to support claims of global climate change, and justify the scientific merit of continued LTER site data collection.
Between other graduate students at the upcoming LTER ASM in the graduate student symposium, we propose a discussion aimed at investigating changes in local-scale precipitation using LTER site precipitation data from multiple sites. Observed changes in precipitation could be shared among students and investigated using the data. Data analysis and statistical techniques for investigating these anomalies could be proposed and further developed, and most importantly, cross-site comparisons could be made and compared with GCM’s, to help provide information about global climate change effects and their possible impacts into the future. Please share this with any LTER graduate students that may be interested, and if attending please bring data.