Effects of forest cover types and environmental factors on soil respiration dynamics in a coastal sand dune of subtropical China

Trees on sand dunes are more sensitive to environmental changes because sandy soils have extremely low water holding capacity and nutrient availability. We investigated the dynamics of soil respiration(Rs) for secondary natural Litsea forest and plantations of casuarina,pine, acacia and eucalyptus. Results show that significant diurnal variations of Rsoccurred in autumn for the eucalyptus species and in summer for the pine species, with higher mean soil respiration at night. However, significant seasonal variations of Rswere found in all five forest stands. Rschanged exponentially with soil temperatures at the 10-cm depth; the models explain 43.3–77.0% of Rs variations. Positive relationships between seasonal Rsand soil moisture varied with stands. The correlations were significant only in the secondary forest, and the eucalyptus and pine plantations. The temperature sensitivity parameter(Q10 value) of Rsranged from 1.64 in casuarina plantation to 2.32 the in secondary forest; annual Rswas highest in the secondary forest and lowest in the pine plantation. The results indicate that soil temperatures and moisture are the primary environmental controls of soil respiration and mainly act through a direct influence on roots and microbial activity. Differences in root biomass, quality of litter,and soil properties(pH, total N, available P, and exchangeable Mg) were also significant factors.

Statistics of the Z–R Relationship for Strong Convective Weather over the Yangtze–Huaihe River Basin and Its Application to Radar Reflectivity Data Assimilation for a Heavy Rain Event

The relationship between the radar reflectivity factor （Z） and the rainfall rate （R） is recalculated based on radar ob- servations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze-Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The Z-R relationship is combined with an empirical qr-R relationship to obtain a new Z-qr relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational （3DVar） data assimilation system of the Weather Research and Forecasting （WRF） model to im-prove the analysis and prediction of severe convective weather over the Yangtze--Huaihe River basin. The perform- ance of the corrected reflectivity operator used in the WRF 3DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z-R relationship. Three experiments are conducted with the WRF model and its 3DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected refleetivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better per-forrnance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original re-flectivity operator. This suggests that the new statistical Z-R relationship is more suitable for predicting severe con- vective weather over the Yangtze-Huaihe River basin than the Z-R relationships currently in use.