Typical plant phenological observation dataset of Chinese phenological observation network, Beijing (1963-2012)

Continuous satellite datasets are widely used in tracking vegetation responses to climate variability. Start of season (SOS), for example, can be derived using a number of methods from the time series of satellite reflectance data; however, various methods often produce different SOS measures which limit the application of satellite data in phenological studies. Therefore, we employed five methods to estimate SOS from the Advanced Very High Resolution Radiometer (AVHRR)/normalized difference vegetation index (NDVI) dataset. Subsequently, we compared the SOS with the ground-based first leaf date (FLD) of 12 deciduous broadleaved plant species at 12 sites of the Chinese Phenological Observation Network (CPON). The results show that the latitudinal patterns of five satellite-derived SOS measures are similar to each other but different from the pattern of ground phenology. For individual methods, the variability of SOS time series is significantly different from ground phenology except for HANTS, Polyfit, and Midpoint methods. The SOS calculated using the Midpoint method showed significant correlations with ground phenophases most frequently (in 47.1% of cases). Using the SOS derived from the Midpoint method, significantly earlier trends in SOS were detected in 50.7% of the natural vegetation area from 1982 to 2006.

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Variation of Main Phenophases in Phenological Calendar in East China and Their Response to Climate Change

Advances in Meteorology ◽

10.1155/2016/9546380 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Fengyi Zheng ◽

Zexing Tao ◽

Yachen Liu ◽

Yunjia Xu ◽

Junhu Dai ◽

...

Keyword(s):

Climate Change ◽

Root Mean Square Error ◽

Mean Square Error ◽

East China ◽

Mean Square ◽

Phenological Data ◽

Phenological Observation ◽

Observation Network ◽

Autumn And Winter ◽

Beginning Date

Based on the phenological data from China Phenological Observation Network, we compiled the phenological calendars of 3 phenological observation stations (Shanghai, Nanjing, and Hefei) in East China for 1987–1996 and 2003–2012 according to the sequences of mean phenophases. We calculated the correlated coefficient and the root mean square error (RMSE) between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. By comparing new phenological calendars with the old ones, we discussed the variation of phenophases and their responses to temperature. The conclusions are as follows. (1) The beginning dates of spring and summer advanced, while those of autumn and winter delayed. Thus, summers got longer and winters got shorter. (2) The beginning time of the four phenological seasons was advancing during 1987–1996, while it was delaying during 2003–2012. (3) Most spring and summer phenophases occur earlier and most autumn and winter phenophases occur later in 2003–2012 than in 1987–1996. (4) The beginning time of phenological seasons was significantly correlated with temperature. The phenological sensitivities to temperature ranged from −6.49 to −6.55 days/°C in spring, −3.65 to −5.02 days/°C in summer, 8.13 to 10.27 days/°C in autumn, and 4.76 to 10.00 days/°C in winter.

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An overview of the phenological observation network and the phenological database of Germany's national meteorological service (Deutscher Wetterdienst)

Advances in Science and Research ◽

10.5194/asr-11-93-2014 ◽

2015 ◽

Vol 11 (1) ◽

pp. 93-99 ◽

Cited By ~ 20

Author(s):

F. Kaspar ◽

K. Zimmermann ◽

C. Polte-Rudolf

Keyword(s):

Plant Development ◽

18Th Century ◽

Pollen Dispersion ◽

Phenological Observation ◽

Observation Network ◽

Phenological Phases

Abstract. First phenological observations have been performed in Germany already in the 18th century. The onset dates of characteristic phases of plant development (phenological phases) are observed and recorded. Today, Germany's national meteorological service (Deutscher Wetterdienst, DWD) maintains a dense phenological observation network and a database with phenological observations. The data are used in many applications, esp. for advisory activities to agriculture or pollen dispersion information.

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Studies of rootstocks for stone fruit breeds (sweet cherry) in the condition of Hissar valley in Tajikistan

Agricultural Technologies ◽

10.35599/agritech/01.04.05 ◽

2019 ◽

Vol 1 (4) ◽

pp. 28-34

Author(s):

Rahima I. Ismoilova ◽

Sodzhida D. Umarova

Keyword(s):

Sweet Cherry ◽

Sour Cherry ◽

High Specificity ◽

Stone Fruit ◽

Wild Cherry ◽

Phenological Observation ◽

Entire Observation Period ◽

The Individual ◽

Leaf System ◽

Observation Period

This paper is about studying the rootstocks for stone fruit breeds (sweet cherry) in condition of Hissar valley in Tajikistan. Each type of rootstock has its own biological characteristics and imposes specific requirements for growing and development, both during reproduction in the mother plantation and during the growth of trees. For example, the root system in sour cherry is more superficial that of wild sweet cherry. Therefore, the care of trees grafted on sour cherry and wild cherry and of mother plantation bushes of these rootstocks cannot be same. Besides, there are very significant differences among the individual groups of rootstocks. Wild cherry, Mahaleb cherry and Lubskaya cherry are used as rootstocks in the conditions of the Hissar Valley in Tajikistan. High specificity of sweet cherry cultivar varieties depends on the rootstocks. Phenological observation were carried out in our experiments during years 2013-2018 in order to study their winter resistance, yield capacity and fruit quality. The same care for root and grafted plants was carried out during the entire observation period. At the same time a certain ratio between the leaf system of the rootstock and the graft was maintained by trimming the crown. As a result of the evolution and selection, we have identified the wild cherry forms which are distinguished by the highest yields. The most valuable cultivar varieties are Napoleon cherry and Bagration cherry. Compotes made of these varieties have received high evaluation in tasting.

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

Brazilian Journal of Geophysics ◽

10.22564/rbgf.v31i2.18 ◽

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).

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Topology detection of a distribution network based on adaptive state observer

Journal of Computational Methods in Sciences and Engineering ◽

10.3233/jcm-214998 ◽

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.

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

Atmosphere ◽

10.3390/atmos12010104 ◽

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.

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

International Journal of Biometeorology ◽

10.1007/s00484-021-02110-3 ◽

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.

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