Tropospheric temperature variation over India and links with the Indian summer monsoon : 1971-2000

In the context of the ever increasing interest in the regional aspects of global warming, understanding the spatio-temporal variations of tropospheric temperature over India is of great importance. The present study, based on the data from 19 well distributed radiosonde stations for the period 1971-2000, examines the seasonal and annual mean temperature variations at the surface and five selected upper levels, viz., 850, 700, 500, 200 and 150 hPa. An attempt has also been made to bring out the association between tropospheric temperature variations over India and the summer monsoon variability, including the role of its major teleconnection parameter, the El Niño/Southern Oscillation (ENSO). Seasonal and annual mean all-India temperature series are analyzed for surface and five tropospheric levels. The mean annual cycles of temperature at different tropospheric levels indicate that the pre-monsoon season is slightly warmer than the monsoon season at the surface, 850 hPa and 150 hPa levels, while it is relatively cooler at all intermediate levels. The mean annual temperature shows a warming of 0.18° C and 0.3° C per 10 years at the surface and 850 hPa, respectively. Tropospheric temperature anomaly composites of excess (deficient) monsoon rainfall years show pronounced positive (negative) anomalies during the month of May, at all the levels. The pre-monsoon pressure of Darwin has significant positive correlation with the monsoon temperature at the surface and 850 hPa.

A Data-driven Platform for Simulating Vehicular Fog Computing Environment

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

A Data-driven Platform for Simulating Vehicular Fog Computing Environment

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

Inter- and intra-event rainfall partitioning dynamics of two typical xerophytic shrubs in the Loess Plateau of China

Rainfall is known as the main water replenishment in dryland ecosystem, and rainfall partitioning by vegetation reshapes the spatial and temporal distribution patterns of rainwater entry into the soil. The dynamics of rainfall partitioning have been extensively studied at the inter-event scale, yet very few studies have explored its finer intra-event dynamics and the relating driving factors for shrubs. Here, we conducted a concurrent in-depth investigation of rainfall partitioning at inter- and intra-event scales for two typical xerophytic shrubs (Caragana korshinskii and Salix psammophila) in the Liudaogou catchment of the Loess Plateau, China. The event throughfall (TF), stemflow (SF), and interception loss (IC) and their temporal variations within the rainfall event as well as the meteorological factors and vegetation characteristics were systematically measured during the 2014–2015 rainy seasons. The C. korshinskii had significantly higher SF percentage (9.2 %) and lower IC percentage (21.4 %) compared to S. psammophila (3.8 % and 29.5 %, respectively) (p < 0.05), but their TF percentages were not significantly different (69.4 % vs. 66.7 %). At the intra-event scale, TF and SF of S. psammophila was initiated (0.1 vs. 0.3 h and 0.7 vs. 0.8 h) and peaked (1.8 vs. 2.0 h and 2.1 vs. 2.2 h) more quickly, and TF of S. psammophila lasted longer (5.2 vs. 4.8 h), delivered more intensely (4.3 vs. 3.8 mm∙h−1), whereas SF of C. korshinskii lasted longer (4.6 vs. 4.1 h), delivered more intensely (753.8 vs. 471.2 mm∙h−1). For both shrubs, rainfall amount was the most significant factor influencing inter-event rainfall partitioning, and rainfall intensity and duration controlled the intra-event TF and SF variables. The C. korshinskii with larger branch angle, more small branches and smaller canopy area, has an advantage to produce stemflow more efficiently over S. psammophila. The S. psammophila has lower canopy water storage capacity to generate and peak throughfall and stemflow earlier, and it has larger aboveground biomass and total canopy water storage of individual plant to produce higher interception loss compared to C. korshinskii. These findings contribute to the fine characterization of shrub-dominated eco-hydrological processes, and improve the accuracy of water balance estimation in dryland ecosystem.

Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates

Mapping canopy photosynthesis in both high spatial and temporal resolution is essential for carbon cycle monitoring in heterogeneous areas. However, well established satellites in sun-synchronous orbits such as Sentinel-2, Landsat and MODIS can only provide either high spatial or high temporal resolution but not both. Recently established CubeSat satellite constellations have created an opportunity to overcome this resolution trade-off. In particular, Planet Fusion allows full utilization of the CubeSat data resolution and coverage while maintaining high radiometric quality. In this study, we used the Planet Fusion surface reflectance product to calculate daily, 3-m resolution, gap-free maps of the near-infrared radiation reflected from vegetation (NIRvP). We then evaluated the performance of these NIRvP maps for estimating canopy photosynthesis by comparing with data from a flux tower network in Sacramento-San Joaquin Delta, California, USA. Overall, NIRvP maps captured temporal variations in canopy photosynthesis of individual sites, despite changes in water extent in the wetlands and frequent mowing in the crop fields. When combining data from all sites, however, we found that robust agreement between NIRvP maps and canopy photosynthesis could only be achieved when matching NIRvP maps to the flux tower footprints. In this case of matched footprints, NIRvP maps showed considerably better performance than in situ NIRvP in estimating canopy photosynthesis both for daily sum and data around the time of satellite overpass (R 2 = 0.78 vs. 0.60, for maps vs. in situ for the satellite overpass time case). This difference in performance was mostly due to the higher degree of consistency in slopes of NIRvP -canopy photosynthesis relationships across the study sites for flux tower footprint-matched maps. Our results show the importance of matching satellite observations to the flux tower footprint and demonstrate the potential of CubeSat constellation imagery to monitor canopy photosynthesis remotely at high spatio-temporal resolution.