Seasonal Predictability of Daily Rainfall Characteristics in Central Northern Chile for Dry-Land Management

Abstract

The seasonal predictability of daily winter rainfall characteristics relevant to dry-land management was investigated in the Coquimbo region of central northern Chile, with focus on the seasonal rainfall total, daily rainfall frequency, and mean daily rainfall intensity on wet days at the station scale. Three approaches of increasing complexity were tested. First, an index of the simultaneous El Niño–Southern Oscillation (ENSO) was regressed onto May–August (MJJA) observed precipitation; this explained 32% of station-averaged rainfall-amount variability, but performed poorly in a forecasting setting. The second approach used retrospective seasonal forecasts made with three general circulation models (GCMs) to produce downscaled seasonal rainfall statistics by means of canonical correlation analysis (CCA). In the third approach, a nonhomogeneous hidden Markov model (nHMM) driven by the GCM’s seasonal forecasts was used to model stochastic daily rainfall sequences. While the CCA is used as a downscaling method for the seasonal rainfall characteristics themselves, the nHMM has the ability to simulate a large ensemble of daily rainfall sequences at each station from which the rainfall statistics were calculated. Similar cross-validated skill estimates were obtained using both the CCA and nHMM, with the highest correlations with observations found for seasonal rainfall amount and rainfall frequency (up to 0.9 at individual stations). These findings were interpreted using analyses of observed rainfall spatial coherence, and by means of synoptic rainfall states derived from the HMM. The downscaled hindcasts were then tailored to meteorological drought prediction, using the standardized precipitation index (SPI) based on seasonal values, the frequency of substantial rainfall days (>15 mm; FREQ15) and the daily accumulated precipitation deficit. Deterministic hindcasts of SPI showed high hit rates, with high ranked probability skill score for probabilistic hindcasts of FREQ15 obtained via the nHMM.

Evaluation of the Usle Model to Estimate Water Erosion in an Alfisol

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Should seasonal rainfall forecasts be used for flood preparedness?

“…Forecasts of the frequency of extreme rainfall events would likely provide a better indication of floodiness, compared to seasonal total rainfall forecasts, for much of Sub-Saharan Africa. Studies have shown the potential predictability of this variable in several locations (Anderson et al, 2015;Higgins et al, 2000;Verbist et al, 2010). Seasonal forecasts of soil moisture could give a useful indication of flood risk in dry regions of Africa (Fig.…”

Climate information for humanitarian agencies: some basic principles

“…Further research into seasonal forecasts for extreme events is necessary to improve the range of decisions that can be informed based on climate information. While rainfall intensity reflects a good deal of atmospheric "noise", there is evidence that frequency of rainfall above a certain threshold might show considerable forecasting skill at the seasonal level, perhaps even greater than the existing skill of total rainfall forecasts (Moron et al 2007;Robertson et al 2009;Verbist et al 2010). Recent research also indicates potential skill in forecasting subseasonal scenarios (Moron et al 2013).…”