Since 10 August 2012, micrometeorological measurements have been conducted at a hilly zone experimental site (28°20'N, 112°34'E), approximately 4 km from Ningxiang county and about 36 km from Changsha City (hereafter, this site is referred to as Ningxiang observatory), based in eastern Hunan Province in the subtropical monsoon region of southern China (Fig. 1a). The site terrain is relatively flat with a homogenous underlying surface. The site is surrounded by similar vegetation, mainly evergreen broadleaved forest and shrub, and some secondary vegetation. The average height of vegetation is approximately 7 m. The soil is predominantly red soil with rapid drainage of water (Figs. 1b, 1d, and 1e).The average elevation is approximately 110 m, annual mean temperature is 16.8°C, annual mean rainfall is 1358 mm, average relative humidity is 81%, and annual average sunshine is 1739.2 hours. The micrometeorological measurement sensors are installed in a measurement tower of height 20 m. Figure 1 shows the location and site of the observatory and its main measurement instruments, taken on 9 August 2012.

The various instruments at the observatory measure: (1) water table depth (at nine different wells surrounding the measurement tower); (2) heat and water content of soil; (3) boundary layer meteorological parameters; (4) surface radiation; and (5) surface flux.

The principle micrometeorological instruments at Ningxiang observatory comprise: (1) a surface layer meteorology observation system; (2) a radiation flux observation system; (3) an eddy covariance system (EC); and (4) a soil temperature/humidity measuring system.

Surface meteorological measurements include wind speed and direction (WindSonic1405-PK052, Gill), and air temperature and relative humidity (HMP155A-L, Vaisala) at 9.5 and 13.5 m above the ground (Fig. 1c). Barometric pressure is measured with a CS106 Barometric Pressure Sensor (Vaisala) over a 500 to 1100 hParange. Precipitation is measured by a tipping bucket Rain Gauge (TE525MM-L, Texas Electronics) at 0.1 mm increments mounted at 20 m on the tower. These signals are logged to a data logger (CR1000, Campbell) and recorded every 10 min.

The surface radiation system observes upward and downward short-wave radiation (UR and DR), and upward and downward long-wave radiation (ULR and DLR). Radiation is intercepted by a 4-Component Net Radiation Sensor (CNR4, Kipp & Zonen) mounted at a height of 17.5 m (Fig. 1c). The data are recorded by a Datataker (CR3000, Campbell) equipped with a memory card. The data are sampled each minute and averaged every 30 min.

The eddy covariance instruments include a three- dimensional sonic anemometer (CSAT3, Campbell) and an open path infrared CO₂ and H₂O analyzer (EC150, Campbell). The CSAT3 points toward the prevailing wind direction and measures the means and standard deviations of the wind velocity components (i.e., u, v, and w) and air temperature ( T). The EC150 measures the means and standard deviations of water vapor density and CO₂. Sensor outputs are recorded at a sampling rate of 10 Hz, averaged over 30 min periods, and logged to the above-mentioned data logger. The sensors are installed on a tower 17.5 m above the ground (Fig. 1d). The momentum, latent, and sensible heat fluxes are calculated by the eddy covariance method. The turbulent fluxes are post-field data processed by a set of necessary correlation procedures, such as coordinate rotation by the planar fits method (PF) ( Wilczak et al., 2001), frequency response correction ( Moore, 1986), sonic temperature correction ( Schotanus et al, 1983), and density flux correction accounting for density effects due to heat and water vapor fluctuations (WPL correction, Webb et al., 1980).

Soil moisture and temperature are measured with a water content reflectometer (CS616-L, Campbell) and a soil temperature profile sensor (109-L, Campbell) respec tively (Fig. 1e). These instruments sample at seven soil depths (0.05, 0.10, 0.20, 0.40, 0.60, 0.80, and 1.00 m). To complete the surface energy balance, soil heat flux is measured by a heat flux plate (HFP01-L50, Campbell) embedded 0.05 m deep in the soil (this instrument was installed 16 November 2012). The data are recorded at 10 min intervals by a Datataker (CR1000, Campbell) with a memory card.

Figure 1

Figure 1 Ningxiang field experiment observatory: (a) location and elevation; (b) underlying canopy surface; (c) measurement tower; (d) EC 150 sensor and underlying surface; (e) soil temperature and moisture sensors and their site; (f) water table depth sensor.

The main instrument for water table measurement at Ningxiang observatory is the HOBO U20 series water table sensor, which includes data loggers (U20, Onset; see Fig. 1f) placed in nine different wells, connected to a computer through a Universal Optic-USB Base station (BASE-U-4, Onset). Data from the HOBO loggers are launched, read out and plotted by HOBO ware Pro software (BHW-PC, Onset).

Figures 2a-d show the temporal variations in daily average wind direction (WD), wind speed (WS), air temperature ( T), and relative humidity (RH) at heights of 9.5 m and 13.5 m. Figures 2e-f present the air pressure and daily total rainfall at Ningxiang observatory. As shown in Figs. 2a-d, the daily mean WD and WS at 9.5 m (225.9° and 0.91 m s^-1, respectively) is slightly less than at 13.5 m (245.3° and 1.39 m s^-1, respectively). The variability in these quantities is very similar at both heights ( R_WD=0.87, R_WS=0.97 at 9.5 and 13.5 m, respectively, where R denotes the correlation coefficient). The maximum daily mean wind speed on 29 September 2012 was 1.89 m s^-1 at 9.5 m and 2.69 m s^-1 at 13.5 m. The air temperature and relative humidity at 9.5 m ( T_mean= 21.73°C, RH_mean= 80.77%) are essentially the same at 13.5 m ( T_mean= 21.88°C, RH_mean=80.09%, R_T=1, R_RH=1). The air temperature varied significantly with season (from late summer to autumn). The daily mean air temperature (at 9.5 m) reached a maximum (31.3°C) on 20 August, while the lowest air temperature (12.55°C) was recorded on 5 November 2012. Seasonal variation was also observed in air pressure ( P) ( P_max = 1013 hPa; P_min = 991 hPa), and was significant negatively correlated with T ( R = -0.9). Figure 2 displays typical subtropical monsoon climate characteristics at this time of year. The water table depth ranged 4-6 m (data not shown).

Near-surface soil moisture and soil temperature control the partitioning of energy in latent and sensible heat fluxes at the soil-atmosphere interface ( Albergel et al., 2012). Figure 3a plots the temporal variation of daily mean air temperature, while Figs. 3b and 3c show the temporal and diurnal variation of soil temperature at depths of 0.05, 0.10, 0.20, 0.40, 0.60, 0.80 and 1.00 m. Figure 3d shows the variation of daily total rainfall, while the temporal and diurnal variations of soil moisture at the abovementioned depths are plotted in Figs. 3e-f.

The temporal variation trends of soil and air temperatures are similar, especially in the shallow layers ( R_{0.05 m} = 0.97, R_{0.10 m} = 0.95, and R_{0.20 m} = 0.93). Soil temperature changed seasonally in each soil layer. These changes were significant in shallow layers and weakened with increasing depth (Figs. 3a-b); the maximum standard deviation (SDV, 4.10°C) occurred at depth 0.05 m, while the lowest (1.79°C) was recorded at 1.00 m. Soil temperature showed significant diurnal variation in shallow layers, but almost no diurnal variation in deeper layers (≥ 0.40 m; see Fig. 3c).

In each layer, soil moisture was strongly affected by rainfall. Significant differences occurred after a heavy rainfall even in deep layers (e.g., 22 September, 30 October, and 10-11 November, see Figs. 3d-e). Dramatic diurnal changes in deep-layer soil moisture after heavy rainfall are evident in Fig. 3f. Figures 3e and 3f also show negligible seasonal and diurnal variation in soil moisture at 0.20 m (SDV = 0.009 m³ m^-3; SDV > 0.3 m³m^-3 at other depths); this anomaly is attributable to the soil texture at this depth over the study area.

Figure 2

Figure 2 Meteorological data collected at Ningxiang observatory at 9.5 m (red) and 13.5 m (blue) from 10 August to 16 November 2012: (a) Wind Direction (WD); (b) Wind Speed (WS); (c) Air Temperature (Air T); (d) Relative Humidity (RH); (e) Air Pressure ( P); (f) Rainfall (daily).

Figure 4 plots the temporal and diurnal variation of 30- min means of albedo (Figs. 4a and 4b), radiation components (DR, UR, DLR, and ULR; Figs. 4c and 4d), and energy components (net radiation (RN), sensible heat flux ( H), and latent heat flux (LE); Figs. 4e and 4f). Measurements of soil heat flux, which were started on 16 November, are not shown. The albedo of the underlying surface is the ratio of the maximum UR to maximum DR. The RN was calculated from four radiation components. As shown in Figs. 4b, 4d, and 4f, the diurnal courses of radiation and energy components were similar on three days in late summer (25-27 August 2012), and displayed significant variation. The maximum RN, DR, LE, and H (789.6 W m^-2, 936.1 W m^-2, 411.8 W m^-2, and 253.7 W m^-2, respectively) occurred at noon of 26 August. LE of evaporation was the main consumer of available energy in late summer. The diurnal variations of RN, DR, and LE were generally consistent ( R (DR, LE) = 0.968, R (RN, LE) = 0.967, R (RN, DR) = 0.998). In Figs. 4a, 4c, and 4e, we observe little seasonal variation in albedo, radiation components, and energy components throughout the ex- perimental period. These quantities adequately character ize the energy partition on the vegetation canopy over hilly zones in the subtropical monsoon region of Southern China.

Figure 3

Figure 3 (a) Temporal variation of daily mean Air T; (b-c) Temporal variation (daily mean) and diurnal variation (10 min intervals) of soil temperature (Soil T)at depths of 0.05 (pink), 0.10 (black), 0.20 (green), 0.40 (dark blue), 0.60 (sky blue), 0.80 (red), and 1.00 m (yellow); (d) Temporal variation of daily total rainfall; (e-f) Temporal variation (daily mean), diurnal variation (10 min intervals) of soil moisture(Soil M) at the depths given in (b-c).

The CO₂ flux is obtained from the WPL correction ( Webb et al., 1980). Noise and other interference is eliminated from 30 minute observations by imposing the criterionor, where F( t) is the observation, is the mean, and σ is SDV over the interval. Figure 5 shows the temporal and diurnal variation of 30-min means of CO₂ flux (negative fluxes indicate CO₂ absorption by vegetation). As shown in Fig. 5b, the diurnal course of CO₂ flux was similar on three days in late summer (25-27 August 2012). Diurnal variation was evident during this time, and the maximum daytime CO₂ flux absorbed by the vegetation canopy reached ~ 1.30 mg m^-2 s^-1 on 26 August 2012. The maximum CO₂ flux released during the night was ~ 0.75 mg m^-2 s^-1 on 27 August 2012. These results are consistent with those reported by Song et al. (2004). CO₂ flux exhibits little seasonal variation throughout the experimental period, which covers neither the growing season nor the winter season (Fig. 5a). The vegetation canopy comprised the underlying surface, and the mean CO₂ flux was negative (-0.1 mg m^-2 s^-1) during the entire experimental period. These results are attributable to photosynthesis in the vegetation canopy, which is especially active in late summer, and which increases the CO₂ absorption and the LE released in the daylight. As shown in Figs. 4f and 5b, the diurnal variations of LE and CO₂ flux were generally consistent, but in reverse phase ( R as high as -0.94).