Exploring the participation motivations of ongoing and former citizen scientists in Taiwan Roadkill Observation Network

2021 ◽  
Vol 64 ◽  
pp. 126055
Author(s):  
Chia-Hsuan Hsu ◽  
Te-En Lin
Keyword(s):  
Observation Network

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

Topology detection of a distribution network based on adaptive state observer

2021 ◽  
pp. 1-9
Author(s):  
Yong Xiao ◽  
Yonggang Zeng ◽  
Yun Zhao ◽  
Yuxin Lu ◽  
Weibin Lin
Keyword(s):  
Smart Grid ◽  
Distribution Network ◽  
Detection Algorithm ◽  
State Observer ◽  
Matlab Simulation ◽  
Unknown Parameters ◽  
State Observation ◽  
Observation Network ◽  
Topology Information ◽  
Adaptive State Observer

The traditional distribution network lacks real-time topology information, which makes the implementation of smart grid complicated. The smart grid needs to monitor and dispatch the grid to maintain the economic and safe operation of the system. In this paper, we propose a topology detection algorithm of the distribution network based on adaptive state observer. Based on the transient dynamic model of the distribution network, the line states of the distribution network are regarded as unknown parameters, a virtual adaptive state observation network is built, and the topology can be inferred by the changes of adaptive state parameters. Finally, the effectiveness of our algorithm is verified by the MATLAB simulation experiments.

scholarly journals A Computational Methodology for the Calibration of Tephra Transport Nowcasting at Sakurajima Volcano, Japan

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 104
Author(s):  
Alexandros P. Poulidis ◽  
Atsushi Shimizu ◽  
Haruhisa Nakamichi ◽  
Masato Iguchi
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Volcanic Eruptions ◽  
Weather Research And Forecasting ◽  
Sakurajima Volcano ◽  
Observation Network ◽  
Complementary Strategy ◽  
Physical Quantities ◽  
Do So

Ground-based remote sensing equipment have the potential to be used for the nowcasting of the tephra hazard from volcanic eruptions. To do so raw data from the equipment first need to be accurately transformed to tephra-related physical quantities. In order to establish these relations for Sakurajima volcano, Japan, we propose a methodology based on high-resolution simulations. An eruption that occurred at Sakurajima on 16 July 2018 is used as the basis of a pilot study. The westwards dispersal of the tephra cloud was ideal for the observation network that has been installed near the volcano. In total, the plume and subsequent tephra cloud were recorded by 2 XMP radars, 1 lidar and 3 optical disdrometers, providing insight on all phases of the eruption, from plume generation to tephra transport away from the volcano. The Weather Research and Forecasting (WRF) and FALL3D models were used to reconstruct the transport and deposition patterns. Simulated airborne tephra concentration and accumulated load were linked, respectively, to lidar backscatter intensity and radar reflectivity. Overall, results highlight the possibility of using such a high-resolution modelling-based methodology as a reliable complementary strategy to common approaches for retrieving tephra-related quantities from remote sensing data.

scholarly journals Maps, trends, and temperature sensitivities—phenological information from and for decreasing numbers of volunteer observers

2021 ◽  
Author(s):  
Ye Yuan ◽  
Stefan Härer ◽  
Tobias Ottenheym ◽  
Gourav Misra ◽  
Alissa Lüpke ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Strong Decrease ◽  
Temperature Changes ◽  
Interpolation Accuracy ◽  
Observation Network ◽  
Shiny App ◽  
Long Term Trends ◽  
Autumn And Winter

AbstractPhenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of −0.2 to −0.3 days year−1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year−1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change–induced temperature changes.

scholarly journals A Role for the Action Observation Network in Apraxia After Stroke

2019 ◽  
Vol 13 ◽  
Author(s):  
Gloria Pizzamiglio ◽  
Zuo Zhang ◽  
James Kolasinski ◽  
Jane M. Riddoch ◽  
Richard E. Passingham ◽  
...  
Keyword(s):  
Action Observation ◽  
Action Observation Network ◽  
Observation Network

scholarly journals Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface CO<sub>2</sub> observations for the period 2006–2010

2014 ◽  
Vol 14 (11) ◽  
pp. 5807-5824 ◽  
Author(s):  
H. F. Zhang ◽  
B. Z. Chen ◽  
I. T. van der Laan-Luijk ◽  
T. Machida ◽  
H. Matsueda ◽  
...  
Keyword(s):  
A Priori ◽  
Carbon Fluxes ◽  
Terrestrial Carbon ◽  
Tropical Asia ◽  
Observation Network ◽  
Fossil Fuel Emission ◽  
Annual Total ◽  
Co2 Sink ◽  
Summer Flood ◽  
Ecosystem Flux

Abstract. Current estimates of the terrestrial carbon fluxes in Asia show large uncertainties particularly in the boreal and mid-latitudes and in China. In this paper, we present an updated carbon flux estimate for Asia ("Asia" refers to lands as far west as the Urals and is divided into boreal Eurasia, temperate Eurasia and tropical Asia based on TransCom regions) by introducing aircraft CO2 measurements from the CONTRAIL (Comprehensive Observation Network for Trace gases by Airline) program into an inversion modeling system based on the CarbonTracker framework. We estimated the averaged annual total Asian terrestrial land CO2 sink was about −1.56 Pg C yr−1 over the period 2006–2010, which offsets about one-third of the fossil fuel emission from Asia (+4.15 Pg C yr−1). The uncertainty of the terrestrial uptake estimate was derived from a set of sensitivity tests and ranged from −1.07 to −1.80 Pg C yr−1, comparable to the formal Gaussian error of ±1.18 Pg C yr−1 (1-sigma). The largest sink was found in forests, predominantly in coniferous forests (−0.64 ± 0.70 Pg C yr−1) and mixed forests (−0.14 ± 0.27 Pg C yr−1); and the second and third large carbon sinks were found in grass/shrub lands and croplands, accounting for −0.44 ± 0.48 Pg C yr−1 and −0.20 ± 0.48 Pg C yr−1, respectively. The carbon fluxes per ecosystem type have large a priori Gaussian uncertainties, and the reduction of uncertainty based on assimilation of sparse observations over Asia is modest (8.7–25.5%) for most individual ecosystems. The ecosystem flux adjustments follow the detailed a priori spatial patterns by design, which further increases the reliance on the a priori biosphere exchange model. The peak-to-peak amplitude of inter-annual variability (IAV) was 0.57 Pg C yr−1 ranging from −1.71 Pg C yr−1 to −2.28 Pg C yr−1. The IAV analysis reveals that the Asian CO2 sink was sensitive to climate variations, with the lowest uptake in 2010 concurrent with a summer flood and autumn drought and the largest CO2 sink in 2009 owing to favorable temperature and plentiful precipitation conditions. We also found the inclusion of the CONTRAIL data in the inversion modeling system reduced the uncertainty by 11% over the whole Asian region, with a large reduction in the southeast of boreal Eurasia, southeast of temperate Eurasia and most tropical Asian areas.

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