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.2% of the site, but there were no green leaves during the period of the analysis because of lack of rainfall. This site was fenced and covered an area of 50 × 35 m 2 . Cup anemometers, thermometers, hygrometers, a wind vane, and an ultrasonic anemometer were installed on multiple poles at the site. T-type thermocouples (depth: 1, 2.5, 5, 10, and 15 cm), time-domain reflectometry (TDR)-type soil moisture sensors Imko TRIME-EZ, depth: 2.5 (five sensors), 5, 10, and 15 cm], and three ground heat flux
.2% of the site, but there were no green leaves during the period of the analysis because of lack of rainfall. This site was fenced and covered an area of 50 × 35 m 2 . Cup anemometers, thermometers, hygrometers, a wind vane, and an ultrasonic anemometer were installed on multiple poles at the site. T-type thermocouples (depth: 1, 2.5, 5, 10, and 15 cm), time-domain reflectometry (TDR)-type soil moisture sensors Imko TRIME-EZ, depth: 2.5 (five sensors), 5, 10, and 15 cm], and three ground heat flux
disconnection of a signal cable, the disturbance in air CO 2 concentration due to entry of researchers into the GM for measuring and sampling plants and soil, and facility maintenance. Falge et al. (2001) suggested three representative gap-filling methods, the mean diurnal variation method, the nonlinear regression analysis, and the lookup-tables method. In this study, the former two methods were applied for gap filling of data of CO 2 exchange rates. The gap filling was performed separately for R e
disconnection of a signal cable, the disturbance in air CO 2 concentration due to entry of researchers into the GM for measuring and sampling plants and soil, and facility maintenance. Falge et al. (2001) suggested three representative gap-filling methods, the mean diurnal variation method, the nonlinear regression analysis, and the lookup-tables method. In this study, the former two methods were applied for gap filling of data of CO 2 exchange rates. The gap filling was performed separately for R e
surface ( Rasmussen et al. 1992 ; Emanuel 2005 ). Two extreme Mediterranean storms are studied hereafter. The first is an intense mesoscale convective system (MCS), originally developing over West Africa, becoming reinforced while crossing the Mediterranean warm waters (for a complete analysis of the event see Mastrangelo et al. 2011 ). The MCS hits southern Italy and in particular the Apulia region (the heel of the Italian peninsula) on 12, 13, and 14 November 2004 with severe floods induced by
surface ( Rasmussen et al. 1992 ; Emanuel 2005 ). Two extreme Mediterranean storms are studied hereafter. The first is an intense mesoscale convective system (MCS), originally developing over West Africa, becoming reinforced while crossing the Mediterranean warm waters (for a complete analysis of the event see Mastrangelo et al. 2011 ). The MCS hits southern Italy and in particular the Apulia region (the heel of the Italian peninsula) on 12, 13, and 14 November 2004 with severe floods induced by
differences in water management and form of human appropriation (e.g., agriculture and forestry). Namely, countries above the regression line would be more efficient in terms of NPP use at the cost of unit water withdrawal. Fig . 7. Country-based analysis of the relationships (a) between NPP and precipitation simulated by the VISIT model for 1995–2004 and (b) between agricultural water withdrawal and HANPP. e. Limitations and advantages of the present analyses With regard to uncertainty, the results
differences in water management and form of human appropriation (e.g., agriculture and forestry). Namely, countries above the regression line would be more efficient in terms of NPP use at the cost of unit water withdrawal. Fig . 7. Country-based analysis of the relationships (a) between NPP and precipitation simulated by the VISIT model for 1995–2004 and (b) between agricultural water withdrawal and HANPP. e. Limitations and advantages of the present analyses With regard to uncertainty, the results
gravimetric measurements were made by state-operated soil moisture networks in the former Soviet Union, China, and Mongolia ( Robock et al. 2000 ). These measurements span decades for some stations, and provide sufficient coverage for some limited spatial and temporal analysis ( Vinnikov and Yeserkepova 1991 ; Gao and Dirmeyer 2006 ). Measurements were taken several times a month, primarily in agricultural settings, but the stations are spaced dozens if not hundreds of kilometers apart, and cover only a
gravimetric measurements were made by state-operated soil moisture networks in the former Soviet Union, China, and Mongolia ( Robock et al. 2000 ). These measurements span decades for some stations, and provide sufficient coverage for some limited spatial and temporal analysis ( Vinnikov and Yeserkepova 1991 ; Gao and Dirmeyer 2006 ). Measurements were taken several times a month, primarily in agricultural settings, but the stations are spaced dozens if not hundreds of kilometers apart, and cover only a
conditions In this analysis, we separated the data into the daytime (when incoming solar radiation R g > 0 W m −2 ) and nighttime periods ( R g = 0 W m −2 ) because the mechanism of energy partitioning is different between day and night. For simplicity, we excluded the snow events from our analysis, which amounted to ~1.5% of the total precipitation. 1) GDK site During the 1-yr study period, the precipitation added up to 1503 mm (i.e., 10% higher than the 30-yr normal). The rainfalls occurred 68 times
conditions In this analysis, we separated the data into the daytime (when incoming solar radiation R g > 0 W m −2 ) and nighttime periods ( R g = 0 W m −2 ) because the mechanism of energy partitioning is different between day and night. For simplicity, we excluded the snow events from our analysis, which amounted to ~1.5% of the total precipitation. 1) GDK site During the 1-yr study period, the precipitation added up to 1503 mm (i.e., 10% higher than the 30-yr normal). The rainfalls occurred 68 times
