scholarly journals Supplementary material to "A new global dataset of phase synchronization of temperature and precipitation: its climatology and contribution to global vegetation productivity"

2018 ◽  
Author(s):  
Zhigang Sun ◽  
Zhu Ouyang ◽  
Xubo Zhang ◽  
Wei Ren
Keyword(s):  
Phase Synchronization ◽  
Vegetation Productivity ◽  
Temperature And Precipitation ◽  
Supplementary Material ◽  
Global Vegetation

scholarly journals A new global dataset of phase synchronization of temperature and precipitation: its climatology and contribution to global vegetation productivity

2018 ◽  
Author(s):  
Zhigang Sun ◽  
Zhu Ouyang ◽  
Xubo Zhang ◽  
Wei Ren
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Phase Synchronization ◽  
Temporal Variations ◽  
Coefficient Of Determination ◽  
Terrestrial Vegetation ◽  
Maximum Increase ◽  
Vegetation Productivity ◽  
Temperature And Precipitation ◽  
Maximum Value

Abstract. Besides cumulative temperature and precipitation, the phase synchronization of temperature and precipitation also helps to regulate vegetation distribution and productivity across global lands. However, the phase synchronization has been rarely considered in previous studies related to climate and biogeography due to a lack of a robust and quantitative approach. In this study, we proposed a synchronization index of temperature and precipitation (SI-TaP) and then investigated its global spatial distribution, interannual fluctuation, and long-term trend derived from a global 60-year dataset of meteorological forcings. Further investigation was conducted to understand the relationship between SI-TaP and the annually summed Normalized Difference Vegetation Index (NDVI), which could be a proxy of terrestrial vegetation productivity. Results show differences in both spatial patterns and temporal variations between SI-TaP and air temperature and precipitation, but SI-TaP may help to explain the distribution and productivity of terrestrial vegetation. About 60 % of regions where annually summed NDVI is greater than half of its maximum value overlap regions where SI-TaP is greater than half of its maximum value. By using SI-TaP to explain vegetation productivity along with temperature and precipitation, the maximum increase in the coefficient of determination is 0.66 across global lands. Results from this study suggest that the proposed SI-TaP index is helpful to better understand climate change and its relation to the biota. Dataset available at http://www.dx.doi.org/10.11922/sciencedb.642 or http://www.sciencedb.cn/dataSet/handle/642.

Global vegetation productivity responses to the West Pacific Warm Pool

2019 ◽  
Vol 655 ◽  
pp. 641-651
Author(s):  
Mei Huang ◽  
Zhaosheng Wang ◽  
Shaoqiang Wang ◽  
Fengxue Gu ◽  
He Gong ◽  
...  
Keyword(s):  
Warm Pool ◽  
The West ◽  
Vegetation Productivity ◽  
West Pacific ◽  
Pacific Warm Pool ◽  
Global Vegetation

Changing sensitivity of global vegetation productivity to hydro-climate drivers

2021 ◽  
Author(s):  
Wantong Li ◽  
Matthias Forkel ◽  
Mirco Migliavacca ◽  
Markus Reichstein ◽  
Sophia Walther ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Growing Season ◽  
Climatic Conditions ◽  
Terrestrial Vegetation ◽  
Spatial And Temporal Patterns ◽  
Vegetation Productivity ◽  
Area Index ◽  
Global Vegetation

<p>Terrestrial vegetation couples the global water, energy and carbon exchange between the atmosphere and the land surface. Thereby, vegetation productivity is determined by a multitude of energy- and water-related variables. While the emergent sensitivity of productivity to these variables has been inferred from Earth observations, its temporal evolution during the last decades is unclear, as well as potential changes in response to trends in hydro-climatic conditions. In this study, we analyze the changing sensitivity of global vegetation productivity to hydro-climate conditions by using satellite-observed vegetation indices (i.e. NDVI) at the monthly timescale from 1982–2015. Further, we repeat the analysis with simulated leaf area index and gross primary productivity from the TRENDY vegetation models, and contrast the findings with the observation-based results. We train a random forest model to predict anomalies of productivity from a comprehensive set of hydro-meteorological variables (temperature, solar radiation, vapor pressure deficit, surface and root-zone soil moisture and precipitation), and to infer the sensitivity to each of these variables. By training models from temporal independent subsets of the data we detect the evolution of sensitivity across time. Results based on observations show that vegetation sensitivity to energy- and water-related variables has significantly changed in many regions across the globe. In particular we find decreased (increased) sensitivity to temperature in very warm (cold) regions. Thereby, the magnitude of the sensitivity tends to differ between the early and late growing seasons. Likewise, we find changing sensitivity to root-zone soil moisture with increases predominantly in the early growing season and decreases in the late growing season. For better understanding the mechanisms behind the sensitivity changes, we analyse land-cover changes, hydro-climatic trends, and abrupt disturbances (e.g. drought, heatwave events or fires could result in breaking points of sensitivity evolution in the local interpretation). In summary, this study sheds light on how and where vegetation productivity changes its response to the drivers under climate change, which can help to understand possibly resulting changes in spatial and temporal patterns of land carbon uptake.</p>

scholarly journals Water memory effects and their impacts on global vegetation productivity and resilience

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Laibao Liu ◽  
Yatong Zhang ◽  
Shuyao Wu ◽  
Shuangcheng Li ◽  
Dahe Qin
Keyword(s):  
Memory Effects ◽  
Vegetation Productivity ◽  
Global Vegetation

Global vegetation productivity response to climatic oscillations during the satellite era

2016 ◽  
Vol 22 (10) ◽  
pp. 3414-3426 ◽  
Author(s):  
Alemu Gonsamo ◽  
Jing M. Chen ◽  
Danica Lombardozzi
Keyword(s):  
Vegetation Productivity ◽  
Climatic Oscillations ◽  
Global Vegetation

scholarly journals Assessing Global Vegetation–Climate Feedbacks from Observations*

2006 ◽  
Vol 19 (5) ◽  
pp. 787-814 ◽  
Author(s):  
Zhengyu Liu ◽  
M. Notaro ◽  
J. Kutzbach ◽  
Naizhuang Liu
Keyword(s):  
Positive Feedback ◽  
Surface Air Temperature ◽  
Climate Feedback ◽  
Vegetation Feedback ◽  
Feedback Analysis ◽  
Temperature And Precipitation ◽  
Significant Seasonal Variation ◽  
Northern United States ◽  
Vegetation Models ◽  
Global Vegetation

Abstract The feedback between global vegetation greenness and surface air temperature and precipitation is assessed using remote sensing observations of monthly fraction of photosynthetically active radiation (FPAR) for 1982 to 2000 with a 2.5° grid resolution. Lead/lag correlations are used to infer vegetation–climate interactions. Furthermore, a statistical method is used to quantify the efficiency of vegetation feedback on climate in the observations. This feedback analysis provides a first quantitative assessment of global vegetation feedback on climate. In northern mid- and high latitudes, vegetation variability is found to be driven predominantly by temperature; in the meantime, vegetation also exerts a strong positive feedback on temperature with the feedback accounting for over 10%–25% of the total monthly temperature variance. The strongest positive feedback occurs in the boreal regions of southern Canada/northern United States, northern Europe, and southern Siberia, where the feedback efficiency exceeds 1°C (0.1 FPAR)−1. Over most of the Tropics and subtropics (outside the equatorial rain belt), vegetation is driven primarily by precipitation. However, little vegetation feedback is found on local precipitation when averaged year-round, with the feedback explained variance usually accounting for less than 5% of the total precipitation variance. Nevertheless, in a few isolated small regions such as Northeast Brazil, East Africa, East Asia, and northern Australia, there appears to be some positive vegetation feedback on local precipitation, with the feedback efficiency over 1 cm month−1 (0.1 FPAR)−1. Further studies suggest a significant seasonal variation of the vegetation feedback in some regions. A preliminary analysis also seems to suggest an enhanced intensity of the vegetation feedback, especially on precipitation, at longer time scales and over a larger grid box area. Limitations and implications of the assessment of vegetation feedback are also discussed. The assessed vegetation feedback is shown to be valuable for the evaluation of vegetation–climate feedback in coupled climate–vegetation models.

Estimation of global vegetation productivity from 1981 to 2018 With remote sensing data

2020 ◽  
Author(s):  
Rui Sun ◽  
Juanmin Wang ◽  
Zhiqiang Xiao ◽  
Anran Zhu ◽  
Mengjia Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Growth Rate ◽  
Remote Sensing Data ◽  
The Other ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Vegetation Productivity ◽  
Sensing Data ◽  
Global Vegetation

<p><span>ly during 1981 and 2018, which was in great agreement with the other similar products. The global NPP has shown a significant increase trend, with an annual growth rate of 0.10 PgC/yr (R<sup>2</sup>=0.4684) </span></p>

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