Effects of Drought on Net Primary Productivity:Roles of Temperature,Drought Intensity,and Duration

Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity(NPP) in Northeast China remain unclear. In this paper, the droughts that occurred in Northeast China between 1999 and 2013 were identified using the Standardized Precipitation Evapotranspiration Index(SPEI). The NPP standardized anomaly index(NPP-SAI) was used to evaluate NPP anomalies. The years of 1999, 2000, 2001, and 2007 were further investigated in order to explore the influence of droughts on NPP at different time scales(3, 6, and 12 months). Based on the NPP-SAI of normal areas, we found droughts overall decreased NPP by 112.06 Tg C between 1999 and 2013. Lower temperatures at the beginning of the growing season could cause declines in NPP by shortening the length of the growing season. Mild drought or short-term drought with higher temperatures might increase NPP, and weak intensity droughts intensified the lag effects of droughts on NPP.

Validation and Comparison of Calibration Techniques for Measurements of Carbon Dioxide in Atmospheric Air Standards

The increase in the concentration of carbon dioxide (CO2) in the atmosphere has led the scientific community to investigate the adverse effects on humanity and nature, including the greenhouse effect, which contributes to global warming and can lead to climate change, besides the risks associated with human health. Due to the importance of metrological issues in the current scenario, the Laboratory of Gas Analysis (Lanag) of the National Institute of Metrology, Quality and Technology (Inmetro) is developing the methodology of preparation of such primary standard gas mixtures through gravimetry. For the preparation of these standards, an analysis verification step is necessary, carried out by means of an analytical technique of comparison, at low levels of concentration, by cavity ringdown (CRDS) and by gas chromatography using a flame ionization detector coupled to a methaniser catalyst (GC-FIDmeth). This work presents the method validation of both methodologies developed to analyze a range of concentration of atmospheric standards of CO2 at a matrix of synthetic clean dry air (SCDA) by CRDS and GC-FIDmeth, of which the analysis results can compromise the measurements on atmospheric air quality. The objective is to compare results of method validation of both analytical methods for low CO2 concentration through the use of primary reference mixtures developed and also by certified reference material. The validation measurement results were analyzed according to the requirements of ISO 5725: 1994 parts 1 and 2, and the calculation of measurement uncertainty followed the methodology described in ISO 6143:2001, with results showing satisfactory consistent between both selected techniques. According to the work presented here, the obtained validation results for CRDS are better than the GC results, such as the relative uncertainty of samples evaluated for CRDS was 0.4% and 2.7% for GC_FID meth.

Resilient timekeeping algorithm with multi‑observation fusion Kalman filter

The timescales incorporated into the Primary Frequency Standard(PFS)exhibit excellent stability and accuracy.However,during the dead time of PFS,the reliability of the timescale can be compromised.To address this issue,a resilient timekeeping algorithm with a Multi-observation Fusion Kalman Filter(MFKF)is proposed.This algorithm fuses the frequency measurements from hydrogen masers with various reference frequency standards,including PFS and commercial cesium beam atomic clocks.The simulation results show that the time deviation and instability of the timescale generated by MFKF are improved compared to those with Kalman filtering.The experimental results demonstrate that even within 70 days of PFS dead time the resilient timescale generated by MFKF can operate reliably.Furthermore,it is theoretically proven that MFKF produces a smaller post-covariance than that with singleobservation Kalman filtering.