Large scale climate and rainfall seasonality in a Mediterranean Area: Insights from a non‐homogeneous Markov model applied to the Agro‐Pontino plain

Abstract

In the context of climate change and variability, there is considerable interest in how large scale climate indicators influence regional precipitation occurrence and its seasonality. Seasonal and longer climate projections from coupled ocean-atmosphere models need to be downscaled to regional levels for hydrologic applications, and the identification of appropriate state variables from such models that can best inform this process is also of direct interest. Here, a Non-Homogeneous Hidden Markov Model (NHMM) for downscaling daily rainfall is developed for the Agro-Pontino Plain, a coastal reclamation region very vulnerable to changes of hydrological cycle. The NHMM, through a set of atmospheric predictors, provides the link between large scale meteorological features and local rainfall patterns. Atmospheric data from the NCEP/NCAR archive and 56-years record (1951-2004) of daily rainfall measurements from 7 stations in Agro-Pontino Plain are analyzed. A number of validation tests are carried out, in order to: 1) identify the best set of atmospheric predictors to model local rainfall; 2) evaluate the model performance to capture realistically relevant rainfall attributes as the inter-annual and seasonal variability, as well as average and extreme rainfall patterns. Validation tests show that the best set of atmospheric predictors are the following: mean sea level pressure, temperature at 1000 hPa, meridional and zonal wind at 850 hPa and precipitable water, from 20°N to 80°N of latitude and from 80°W to 60°E of longitude. Furthermore, the validation tests show that the rainfall attributes are simulated realistically and accurately. The capability of the NHMM to be used as a forecasting tool to quantify changes of rainfall patterns forced by alteration of atmospheric circulation under climate change and variability scenarios is discussed

Variability of Temperature and Its Impact on Reference Evapotranspiration: The Test Case of the Apulia Region (Southern Italy)

“…In the last three decades, many studies have addressed the issue of climate evolution under anthropic pressure [1]. An increase of the annual mean global temperature and changes of other climate parameters have been observed in the last century [2][3][4][5]. In fact, many papers particularly concern global climate modelling and the recent warming due to human activity.…”

Climate Changes and Their Impact on Agricultural Market Systems: Examples from Nepal

“…A variety of numerical models representing the physical processes in the atmosphere, ocean, cryosphere and land surface simulate the response of the global climate systems to increasing greenhouse gas concentrations and forecast how the climate is expected to change until 2050 and 2070 [1]. A recent study using a non-homogenous Markov model shows that the best atmospheric predictor variables are mean sea level pressure, temperatures at 1000 hPa, meridional and zonal winds at 850 hPa and precipitation at the latitude of 20 • N to 80 • N and longitude of 80 • W to 60 • E [2]. Wilby and Dawson [3] suggest that a focus on physically meaningful quantities, such as wind speeds, wave heights, phenological and hazard metrics, could improve our understanding of downscaled models.…”

Efficiency Assessment of Existing Pumping/Hydraulic Network Systems to Mitigate Flooding in Low-Lying Coastal Regions under Different Scenarios of Sea Level Rise: The Mazzocchio Area Study Case

“…In this study, we used daily rainfall amount because previous studies [11,35] have shown that 24-h-long heavy rainfall (with a daily rainfall amount greater than 100 mm) has in the past induced serious flash flooding in the examined site. It should also be underlined that downscaling models aimed to project future changes in the precipitation regime [10] generally refer to the daily rainfall amount, and therefore it is reasonable to use the return period associated to such a quantity.…”

“…As a number of authors suggest, such methodologies must evolve to address "change" from climate variability at the global scale to local human impacts [8,9]. Recently, rainfall downscaling models have been constructed to perform projections of rainfall occurrence and amount at the basin level, under different global warming scenarios simulated by global or regional circulation models (GCMs and RCMs) [10,11]. Therefore, such models can be used to provide the hydrological inputs necessary to run hydraulic models to assess the reliability of existing hydraulic infrastructures, and eventually the design of new ones, to manage future flooding risk at the local scale.…”