Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Sensitivity of phenology models to the selection of driving meteorological datasets

View through CrossRef
<p>Plant phenology focuses on the annual repetitive development phases of the terrestrial vegetation. Since the date of the onset and the cessation of vegetation growth define the possible time period for photosynthesis, plant phenology strongly affects the carbon cycle of the ecosystems. Phenology has a serious impact on the climate system through the carbon-, water- and energy cycle. Observations indicate changes in the phenological cycle of the vegetation worldwide that are clear indicators of climate change. Warming climate can be associated with more intense carbon uptake, but it can also negatively affect production. Current studies clearly indicated that the phenological cycle is not properly represented in the Earth System Models which means that further research is needed.</p><p>Meteorological variables affecting the state of the environment, such as temperature and precipitation, also play a key role in the development of vegetation. Phenology models of different complexity were developed to quantify the timing of the onset of vegetation growth based on meteorological data. The sensitivity of the models to the source meteorological datasets is rarely studied. The aim of the present study is to quantify the sensitivity of widely used phenology models to the selection of the driving meteorological dataset.</p><p>Two phenology models were used to evaluate the different databases. One is the so-called Growing Degree Day (GDD) method, which calculates the onset date based on the degree day logic. The GDD model is further divided into simple thermal forcing model and thermal model, where the latter includes chilling requirement as well. The second method uses minimum temperature, photoperiod and vapor pressure deficit and calculates a so-called Growing Season Index (GSI) which is used to estimate onset date</p><p>Considering the meteorological data, three different datasets were used. The ERA5 is a reanalysis database, which is the product of the European Centre for Medium-Range Weather Forecasts (ECMWF). The CarpatClim and the FORESEE (Open Database FOR ClimatE Change-Related Impact Sudies in CEntral Europe) are observation based, gridded datasets for the larger Carpathian Region (Central Europe).  </p><p>In any modelling exercise aiming at simulating the stages of phenology, observations are essential. In the present study the phenological observation data is originating from satellite data and field observations. The first means the third generation Normalized Vegetation Index (NDVI3g) disseminated by GIMMS (Global Inventory Modeling and Mapping Studies), and the latter means the PEP725 phenology dataset and field observations from the botanical garden of Eötvös Loránd University, located in Budapest.</p>
Title: Sensitivity of phenology models to the selection of driving meteorological datasets
Description:
<p>Plant phenology focuses on the annual repetitive development phases of the terrestrial vegetation.
Since the date of the onset and the cessation of vegetation growth define the possible time period for photosynthesis, plant phenology strongly affects the carbon cycle of the ecosystems.
Phenology has a serious impact on the climate system through the carbon-, water- and energy cycle.
Observations indicate changes in the phenological cycle of the vegetation worldwide that are clear indicators of climate change.
Warming climate can be associated with more intense carbon uptake, but it can also negatively affect production.
Current studies clearly indicated that the phenological cycle is not properly represented in the Earth System Models which means that further research is needed.
</p><p>Meteorological variables affecting the state of the environment, such as temperature and precipitation, also play a key role in the development of vegetation.
Phenology models of different complexity were developed to quantify the timing of the onset of vegetation growth based on meteorological data.
The sensitivity of the models to the source meteorological datasets is rarely studied.
The aim of the present study is to quantify the sensitivity of widely used phenology models to the selection of the driving meteorological dataset.
</p><p>Two phenology models were used to evaluate the different databases.
One is the so-called Growing Degree Day (GDD) method, which calculates the onset date based on the degree day logic.
The GDD model is further divided into simple thermal forcing model and thermal model, where the latter includes chilling requirement as well.
The second method uses minimum temperature, photoperiod and vapor pressure deficit and calculates a so-called Growing Season Index (GSI) which is used to estimate onset date</p><p>Considering the meteorological data, three different datasets were used.
The ERA5 is a reanalysis database, which is the product of the European Centre for Medium-Range Weather Forecasts (ECMWF).
The CarpatClim and the FORESEE (Open Database FOR ClimatE Change-Related Impact Sudies in CEntral Europe) are observation based, gridded datasets for the larger Carpathian Region (Central Europe).
 </p><p>In any modelling exercise aiming at simulating the stages of phenology, observations are essential.
In the present study the phenological observation data is originating from satellite data and field observations.
The first means the third generation Normalized Vegetation Index (NDVI3g) disseminated by GIMMS (Global Inventory Modeling and Mapping Studies), and the latter means the PEP725 phenology dataset and field observations from the botanical garden of Eötvös Loránd University, located in Budapest.
</p>.

Related Results

Soil fertility advances spring phenology of deciduous trees across temperate European forests 
Soil fertility advances spring phenology of deciduous trees across temperate European forests 
Phenology affects tree growth, as well as ecosystem dynamics such as the carbon, water and nutrient cycles. As phenology represents a plastic response of trees to environmental cha...
Using Citizen Science to build baseline data on tropical tree phenology
Using Citizen Science to build baseline data on tropical tree phenology
Abstract Large-scale and long-term understanding of the phenology of widespread tree species is lacking in the tropics, and particularly in the I...
Selection Gradients
Selection Gradients
Natural selection and sexual selection are important evolutionary processes that can shape the phenotypic distributions of natural populations and, consequently, a primary goal of ...
Poems
Poems
poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poem...
phenoC++: An open-source tool for retrieving vegetation phenology from satellite remote sensing data
phenoC++: An open-source tool for retrieving vegetation phenology from satellite remote sensing data
Satellite-retrieved vegetation phenology has great potential for application in characterizing seasonal and annual land surface dynamics. However, obtaining regional-scale vegetati...
A warmer growing season triggers earlier following spring phenology
A warmer growing season triggers earlier following spring phenology
AbstractUnder global warming, advances in spring phenology due to the rising temperature have been widely reported. However, the physiological mechanisms underlying the warming-ind...

Back to Top