Potentiality of Non-homogeneous Hidden Markov Model (NHMM) as predictive tool of rainfall and temperature patterns in Everglades National Park under the Global Warming Scenarios

• Main Authors: CIOFFI, Francesco, A. Monti, F. Conticello
• Other Authors: Cioffi, Francesco, A., Monti, F., Conticello
• Format: Other/Unknown Material
• Language: English
• Published: 2013
• Subjects: wetland management; rainfall and temperature downscaling model; climate change; North Atlantic
• Online Access: http://hdl.handle.net/11573/548223

Climate change poses a number of problems for the management and restoration of Everglades National Park and for the water supply systems in South Florida. Changes due to anthropogenic global warming in rainfall seasonality, intermittence and intensity together with variations of temperature and sea level (SL) may interact and determine the potential outcomes for surface and groundwater flows as well as other factors such as erosion, mangrove retreat, salinity and ecological diversity. Due to the coarse spatial resolution of general circulation models (GCMs), and due to other factors, the statistics of precipitation at the local scale can be strongly biased in retrospective simulations. Many engineering models are designed to work with historical point precipitation data, and practitioners prefer to assess the performance of GCMs in the context of their models and the associated data inputs. Dynamical and statistical downscaling schemes are consequently employed. Here, a Non-Homogeneous Hidden Markov Model (NHMM) is applied for simulating future daily rainfall at nineteen stations in South Florida. The CMIP 5 simulation of the coupled ocean-atmosphere model CMCC-CMS from 1950-2100 is used for projection. The application directly considers seasonality through changes in the driving variables, rather than developing separate models for each canonical season. Biases between the re-analysis model and retrospective simulations of the CMCC-CMS are addressed. The results indicate that, as a consequence of increase of the CO2 concentration and temperature, South Florida may be subjected to drier conditions for most of the year. The number of wet days reduces while extreme rainfall frequency increases. These are consistent with trends of rainfall observed in the recent data. A modest reduction in total rainfall in the February to May period, and a slight increase in the September-October projected rainfall is noted. Changes in the expression of the North Atlantic Subtropical High in the model appear to correspond to ...