2015
DOI: 10.5194/asr-12-121-2015
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Ten years water and energy surface balance from the CNR-ISAC micrometeorological station in Salento peninsula (southern Italy)

Abstract: Abstract. Data of surface-atmosphere energy and water transfer from a ten years (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) period of activity of the ISAC-Lecce micrometeorological station (http://www.basesperimentale.le.isac.cnr.it) have been analyzed: to the authors' knowledge this is the first decadal data set of surface-atmosphere transfer in Salento peninsula. The surface energy budget shows a tendency to a positive bias possibly due to several reasons that require more investigatio… Show more

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Cited by 16 publications
(13 citation statements)
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“…Table 1 also shows that the scatter and the correlation are worse but still comparable with those of case (1) and (2) (flux calibration), but with a much larger uncertainty for the obtained parameters P1 and P2, that affects the slope of the regression curve. [38]. -The elimination of the measured fluxes in the calibration procedure (case 3) sensibly increases the statistical uncertainty in the parameter P1 and P2, and this means a smaller sensitivity in the parameter evaluation when the model is calibrated using the surface-air temperature differences only.…”
Section: Resultsmentioning
confidence: 99%
“…Table 1 also shows that the scatter and the correlation are worse but still comparable with those of case (1) and (2) (flux calibration), but with a much larger uncertainty for the obtained parameters P1 and P2, that affects the slope of the regression curve. [38]. -The elimination of the measured fluxes in the calibration procedure (case 3) sensibly increases the statistical uncertainty in the parameter P1 and P2, and this means a smaller sensitivity in the parameter evaluation when the model is calibrated using the surface-air temperature differences only.…”
Section: Resultsmentioning
confidence: 99%
“…However, the uncertainty can be quite large due to the missing data in the considered period. An estimation of the total measurement uncertainty considering both instrumentation errors and missing data has been suggested in [23], where the missing data uncertainty was estimated as proportional to both the contribution of the single measurement error and the total number of missing data (the total number of missing data per year is always less than 10%). The seasonal/yearly average/total values for P,I, and soil moisture at 2 cm in the short study period 2009-2011 are shown in Table 2, where the error interval now represents the total estimated measurement uncertainty from [23] (not the "climatic" standard deviation of the whole 2003-2016 period as in the long term averages of Table 1).…”
Section: Resultsmentioning
confidence: 99%
“…The data are stored as 30-min averages in the web database. More details about the base instruments, calibrations and the database can be found elsewhere [20,23,40]. Figure 2 shows the typical yearly distribution of the footprints of the scalar turbulent fluxes measured from the mast, calculated by the analytic model of Hsieh et al [41].…”
Section: Methodsmentioning
confidence: 99%
“…In Table 2, the measured total precipitation for the flooding events are shown for the selected surface meteorological stations. The climatic annual average precipitation in Southern Salento is about 650 mm [27], so that the total for the selected period represents more than 35% of the average annual precipitation in less than three weeks. The soil moisture at 30-cm depth recorded at the ISAC-CNR station (reported here as a proxy for the bulk soil saturation conditions) was more than 0.30 m 3 /m 3 (relative volumetric soil moisture R about 70%, see definition later) before the beginning of the precipitation.…”
Section: F1 11/11/2013-2/12/2013mentioning
confidence: 99%