scholarly journals The Impact of the 20–50-Day Atmospheric Intraseasonal Oscillation on the Gross Primary Productivity between the Yangtze and Yellow Rivers

2020 ◽  
Vol 33 (8) ◽  
pp. 2967-2984
Author(s):  
Jianying Li ◽  
Jin-Soo Kim ◽  
Jong-Seong Kug

AbstractGiven their high carbon uptake, the terrestrial ecosystems in the East Asia summer monsoon (EASM) region play an irreplaceable role in the global carbon cycle. Because the rich vegetation growth over East Asia benefits mainly from the sufficient water supply brought by the EASM, which is characterized by a strong intraseasonal oscillation (ISO), the intraseasonal spatiotemporal variations and underlying drivers of photosynthesis activity over East Asia have been comprehensively investigated using the daily gross primary productivity (GPP) and meteorological data. Strong intraseasonal fluctuations of GPP have been identified over the area between the Yangtze and Yellow Rivers (YYR) with a magnitude of 0.4 gC m−2 day−1. The mean power spectrum suggests that 20–50-day variation is the major component of the intraseasonal GPP anomalies over the YYR during the summers of 1980–2013. The 20–50-day ISO of YYR GPP anomalies is modulated by the local 20–50-day precipitation variation via soil moisture, with precipitation (soil moisture) leading GPP by 10 (7) days. The 20–50-day YYR precipitation anomalies are in turn controlled by tropical ISO signals, particularly the convective activity over the western North Pacific. This leading relationship between the 20–50-day atmospheric ISO and GPP suggests a potential for extended-range predictability of vegetation growth.

2021 ◽  
Author(s):  
Jasdeep Singh Anand ◽  
Alessandro Anav ◽  
Marcello Vitale ◽  
Daniele Peano ◽  
Nadine Unger ◽  
...  

Abstract. Tropospheric O3 damages leaves and directly inhibits photosynthesis, posing a threat to terrestrial carbon sinks. Previous investigations have mostly relied on sparse in-situ data or simulations using land surface models. This work is the first to use satellite data to quantify the effect of O3 exposure on gross primary productivity (GPP). O3-induced GPP reductions were estimated to vary between 0.36–9.55% across European forests along a North-South transect between 2003–2015, in line with prior estimates. No significant temporal trend could be determined over most of Europe, while Random Forest analysis (RFA) shows that soil moisture is a significant variable governing GPP reductions over the Mediterranean. Comparisons between this work and GPP reductions simulated by the Yale Interactive Biosphere (YIBs) model suggest that satellite-based estimates over the Mediterranean region may be biased by +12%, potentially because of differences in modelling stomatal sensitivity to soil moisture and prior O3 exposure. This work has demonstrated for the first time that satellite-based datasets can be leveraged to assess the impact of O3 on the terrestrial carbon sink, which are comparable with in-situ or model-based analyses.


Author(s):  
S. A. Lysenko

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.


2021 ◽  
Author(s):  
Yinghan Sang ◽  
Hong-Li Ren ◽  
Yi Deng ◽  
Xiaofeng Xu ◽  
Xueli Shi ◽  
...  

Abstract This paper reports findings from a diagnostic and modeling analysis that investigates the impact of the late-spring soil moisture anomaly over North Eurasia on the boreal summer rainfall over northern East Asia (NEA). Soil moisture in May in the region from the Kara-Laptev Sea coasts to Central Siberian Plateau is found to be negatively correlated with the summer rainfall from Mongolia to Northeast China. The atmospheric circulation anomalies associated with the anomalously dry soil are characterized by a pressure dipole with the high-pressure center located over North Eurasia and the low-pressure center over NEA, where an anomalous lower-level moisture convergence occurs, favoring rainfall formation. Diagnoses and Modeling experiments demonstrate that the effect of the spring low soil moisture over North Eurasia may persist into the following summer through modulating local surface latent and sensible heat fluxes, increasing low-level air temperature at higher latitudes, and effectively reducing the meridional temperature gradient. The weakened temperature gradient could induce the decreased zonal wind and the generation of a low-pressure center over NEA, associated with a favorable condition of local synoptic activity. The above relationships and mechanisms are vice versa for the prior wetter soil and decreased NEA rainfall. These findings suggest that soil moisture anomalies over North Eurasia may act as a new precursor providing an additional predictability source for better predicting the summer rainfall in NEA.


2021 ◽  
Author(s):  
Markus Todt ◽  
Pier Luigi Vidale ◽  
Patrick C. McGuire ◽  
Omar V. Müller

<p>Capturing soil moisture-atmosphere feedbacks in a weather or climate model requires realistic simulation of various land surface processes. However, irrigation and other water management methods are still missing in most global climate models today, despite irrigated agriculture being the dominant land use in parts of Asia. In this study, we test the irrigation scheme available in the land model JULES (Joint UK Land Environment Simulator) by running land-only simulations over South and East Asia driven by WFDEI (WATCH Forcing Data ERA-Interim) forcing data. Irrigation in JULES is applied on a daily basis by replenishing soil moisture in the upper soil layers to field capacity, and we use a version of the irrigation scheme that extracts water for irrigation from groundwater and rivers, which physically limits the amount of irrigation that can be applied. We prescribe irrigation for C3 grasses in order to simulate the effects of agriculture, albeit retaining the simpler, widely used 5-PFT (plant functional type) configuration in JULES. Irrigation generally increases soil moisture and evapotranspiration, which results in increasing latent heat fluxes and decreasing sensible heat fluxes. Comparison with combined observational/machine-learning products for turbulent fluxes shows that while irrigation can reduce biases, other biases in JULES, unrelated to irrigation, are larger than improvements due to the inclusion of irrigation. Irrigation also affects water fluxes within the soil, e.g. runoff and drainage into the groundwater level, as well as soil moisture outside of the irrigation season. We find that the irrigation scheme, at least in the uncoupled land-atmosphere setting, can rapidly deplete groundwater to the point that river flow becomes the main source of irrigation (over the North China Plain and the Indus region) and can have the counterintuitive effect of decreasing annual average soil moisture (over the Ganges plain). Subsequently, we will explore the impact of irrigation on regional climate by conducting coupled land-atmosphere simulations.</p>


2020 ◽  
Author(s):  
Timothy Lam ◽  
Amos P. K. Tai

<p>This study utilises in-situ and reanalysis soil moisture data inputs from various sources to evaluate the effect of soil water stress on Gross Primary Productivity (GPP) of different Plant Functional Types (PFTs) using Terrestrial Ecosystem Model in R (TEMIR), which is under development by Tai Group of Atmosphere-Biosphere Interactions (Tai et al. in prep.). An empirical soil water stress function with reference to Community Land Model (CLM) Version 4.5 is employed to quantify water stress experienced by vegetation which hinders stomatal conductance and thus carboxylation rate. The model results are compared against observations at FLUXNET sites in semi-arid regions across the globe at daily timescale where in-situ GPP data is available and water stress inhibits plant functions to some extent. By dividing the soil into two layers (topsoil and root zone), GPP simulation improves significantly comparing with using single layer bulk soil (Modified Nash-Sutcliffe Model Efficiency Coefficient N increases from -0.686 to -0.586). Such upgrade is particularly substantial for vegetation with shallow roots such as grass PFTs. Despite this improvement, the model is characterised by an overall overestimation of GPP when water stress occurs, and inconsistency of accuracy subject to PFTs and degree of water stress experienced. This study informs responses of various PFTs to soil water stress, capacity of TEMIR in simulating the responses, and possible drawbacks of empirical soil water stress functions, and highlights the importance of topsoil moisture data input for vegetation drought monitoring.</p><p>Keywords: Soil water stress, Terrestrial model representation, Photosynthesis, In-situ data, Reanalysis data, FLUXNET</p>


2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Miao Zhang ◽  
Xing Yuan ◽  
Jason A. Otkin

Abstract Background Flash drought poses a great threat to terrestrial ecosystems and influences carbon dynamics due to its unusually rapid onset and increasing frequency in a warming climate. Understanding the response of regional terrestrial carbon dynamics to flash drought requires long-term observations of carbon fluxes and soil moisture at a large scale. Here, MODIS satellite observations of ecosystem productivity and ERA5 reanalysis modeling of soil moisture are used to detect the response of ecosystems to flash drought over China. Results The results show that GPP, NPP, and LAI respond to 79–86% of the flash drought events over China, with highest and lowest response frequency for NPP and LAI, respectively. The discrepancies in the response of GPP, NPP, and LAI to flash drought result from vegetation physiological and structural changes. The negative anomalies of GPP, NPP, and LAI occur within 19 days after the start of flash drought, with the fastest response occurring over North China, and slower responses in southern and northeastern China. Water use efficiency (WUE) is increased in most regions of China except for western regions during flash drought, illustrating the resilience of ecosystems to rapid changes in soil moisture conditions. Conclusions This study shows the rapid response of ecosystems to flash drought based on remote-sensing observations, especially for northern China with semiarid climates. Besides, NPP is more sensitive than GPP and LAI to flash drought under the influence of vegetation respiration and physiological regulations. Although the mean WUE increases during flash drought over most of China, western China shows less resilience to flash drought with little changes in WUE during the recovery stage. This study highlights the impacts of flash drought on ecosystems and the necessity to monitor rapid drought intensification.


Sign in / Sign up

Export Citation Format

Share Document