Using Climate for Operational Management and Ecologic Restoration of the Everglades
Upmanu Lall (Professor, EEE)
Hyun-Han Kwon (Postdoctoral Research Scientist, EEE)
abedalrazq f. Khalil (Postdoctoral Research Scientist, EEE)
The ecologic restoration of the Everglades in Florida is a landmark study that brings forth some rather interesting questions as how ‘‘natural’’ conditions can be defined and achieved in a highly modified and managed system. Water no longer flows at the same times or durations as it did historically because the movement of water is now controlled by a series of hydrologic structures. The basic challenge of restoration in this context is to operate these controlled structures in a manner that allows the desired quantity and quality of water to be delivered to the Everglades at the right times to the right locations. An understanding of long-term variations in seasonal rainfall is needed for such operational management, to make forecasts for the upcoming season and to inform long-term planning decisions.
This project characterizes the interannual variability in Everglades seasonal rainfall by identifying regions of Pacific and Atlantic oceans whose sea surface temperatures (SSTs) may be the carriers of the low-frequency information associated with Everglades rainfall. These low frequency oscillations can occur on interannual and interdecadal timescales, the amplitudes of these oscillations may vary with time, and the dominant frequency can also vary by season. Thus identifying climatic phenomena that influence specific low-frequency aspects of rainfall is a considerable challenge, which is addressed here using a statistical technique called wavelet analysis to diagnose the time-varying low-frequency structure of rainfall.
Long-term rainfall records from the eight stations indicated below are averaged to generate three different annual timeseries of Everglades rainfall, representing the February-April (FMA), May-July (MJJ) and August-October (ASO) seasons.A wavelet analysis is performed on each timeseries, and filtered timeseries representing variability in the 2 to 8 year band were reconstructed.
The filtered timeseries are correlated with gridded sea surface temperature (SST) over the Pacific and Atlantic oceans, which are characterized by low-frequency climate modes.For each rainfall season, same season and previous season SSTs are considered, and the six resulting correlation fields are shown below.FMA rainfall is strongly related to equatorial Pacific SST, indicative of an Everglades response to the El Nino – Southern Oscillation (ENSO).MJJ rainfall is influenced by tropical Pacific and Atlantic SST.ASO rainfall is related to tropical Atlantic SST typically associated with tropical storm and hurricane development.These correlations are quite consistent with what is expected based on the dominant dynamical mechanisms during these seasons, and demonstrate the potential for developing operational tools for rainfall timeseries simulation and forecasting.This will allow for effective operational management of the Everglades, and ultimately its ecologic restoration.
