Final Report: Understanding and Communicating the Role of Natural Climate Variability in a Changing World
Dates
Publication Date
2016-09
Citation
Alexander Gershunov, Daniel R Cayan, Suraj Polade, and Kristen Guirguis, Final Report: Understanding and Communicating the Role of Natural Climate Variability in a Changing World: .
Summary
Natural climate variability can strongly temporarily enhance or obscure long-term trends in regional weather due to global climate change. We planned to explore (from our original proposal): (1) The influence of low frequency climate variability (interannual and decadal) on the seasonal probability distributions of daily weather (temperature and precipitation) within the Southwest, with a view on how natural variability modulates regional trends due to global warming. We explored natural climate variability and its impacts on extreme temperatures in Guirguis et al. (2015). We also explored natural climate variability and its impacts on precipitation extremes in Cavanaugh et al. (2015), Cavanugh and Gershunov (2015) and Gershunov et [...]
Summary
Natural climate variability can strongly temporarily enhance or obscure long-term trends in regional weather due to global climate change. We planned to explore (from our original proposal): (1) The influence of low frequency climate variability (interannual and decadal) on the seasonal probability distributions of daily weather (temperature and precipitation) within the Southwest, with a view on how natural variability modulates regional trends due to global warming. We explored natural climate variability and its impacts on extreme temperatures in Guirguis et al. (2015). We also explored natural climate variability and its impacts on precipitation extremes in Cavanaugh et al. (2015), Cavanugh and Gershunov (2015) and Gershunov et al. (in review). (2) Quantify the teleconnections/relationships traditionally important for seasonal climate prediction to quantify the predictable natural interannual to decadal variability of daily weather statistics. We have explored natural climate variability responsible for seasonal predictability of precipitation in Gershunov et al. (in review) as well as for temperature extremes (Guirguis et al. 2015). (3) Investigate the projected effects of climate change on the stability of these teleconnections/relationships. We have come to the realization that the natural climate forcings (ENSO, PDO) and their teleconnections are not adequately enough represented in GCMs, nor robustly enough projected, for a meaningful investigation of projected changes in natural climate variability in the current (CMIP5) version of climate models. We are pursuing elements of this work by focusing on mechanistic analysis of projected precipitation changes by examining Atmospheric Rivers as causes of many of the regional precipitation extremes. Work by Guirguis et al. (in review) and Polade et al. (2014) and Polade et al. (in review) focuses more broadly on how natural variability in precipitation is affected by projected climate change, i.e. via increases natural variability of annual precipitation in the Southwest. We plan to investigate the implications of these changes to water resources in our region where water resources are already highly volatile.
We focused on entire seasonal distributions of daily weather, especially on high-impact extreme events, to quantify their variability in past climate (Guirguis et al. 2015, Cavanaugh et al. 2015, Cavanaugh and Gershunov 2015) and related it to known natural climate forcings using multivariate statistical techniques (Gershunov et al. in review). We investigated the impact of natural variability on climate change trends (Guirguis et al. in review) and, conversely, the impact of climate change on these natural modes of regional variability in weather and climate over the Southwest (Polade et al. 2015 and Polade et al. in review). We quantified the associations between multi-year changes and the seasonal PDFs of daily weather, quantifying uncertainty, and identifying predictable signals in temperature extremes (Guirguis et al. in review).
We were also planning to investigate the impact of natural variability and anthropogenic trends on peak streamflow, particularly its impact on California's Bay-Delta. This last element we were not able to address as the original version of LOCA downscaling, that was to be used to drive the VIC hydrologic model, was flawed and the entire LOCA downscaling exercise had to be re-run for all GCMs. This unfortunate development hampered our progress on projected streamflow/runoff analysis and this is something that we are still planning to pursue in the future with our USGS partner Noah Knowles.
