scholarly journals Are Soybean Yields Getting a Free Ride From Climate Change? Evidence From Argentine Time Series

2018 ◽  
Author(s):  
Hildegart Ahumada ◽  
Magdalena Cornejo
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Extreme Rainfall ◽  
Co2 Concentration ◽  
Interesting Case ◽  
Extreme Rainfall Events ◽  
Beneficial Effects ◽  
Positive Effects ◽  
Long Run ◽  
Equilibrium Correction

Soybean yields are often indicated as an interesting case of climate change mitigation due to the beneficial effects of CO2 fertilization. In this paper we econometrically study this effect using a time series model of yields in a multivariate framework for a main producer and exporter of this commodity, Argentina. We have to deal with the upward behavior of soybean yields trying to identify which variables are the long-run determinants responsible of its observed trend. With this aim we adopt a partial system approach to estimate subsets of long-run relationships due to climate, technological and economic factors. Using an automatic selection algorithm we evaluate encompassing of the different obtained equilibrium correction models. We found that only technological innovations due to new crop practices and the use of modified seeds explain soybean yield in the long run. Regarding short run determinants we found positive effects associated with the use of standard fertilizers and also from changes in atmospheric CO2 concentration which would suggest a mitigation effect from global warming. However, we also found negative climate effects from periods of droughts associated with La Niña episodes, high temperatures and extreme rainfall events during the growing season of the plant.

Changes in grassland ecosystem function due to extreme rainfall events: implications for responses to climate change

2008 ◽  
Vol 14 (7) ◽  
pp. 1600-1608 ◽  
Author(s):  
PHILIP A. FAY ◽  
DAWN M. KAUFMAN ◽  
JESSE B. NIPPERT ◽  
JONATHAN D. CARLISLE ◽  
CHRISTOPHER W. HARPER
Keyword(s):  
Climate Change ◽  
Ecosystem Function ◽  
Extreme Rainfall ◽  
Grassland Ecosystem ◽  
Extreme Rainfall Events ◽  
Rainfall Events

scholarly journals Evaluation of climate change impacts on extreme rainfall events characteristics using a synoptic weather typing-based daily precipitation downscaling model

2017 ◽  
Vol 8 (3) ◽  
pp. 388-411 ◽  
Author(s):  
Hamed Tavakolifar ◽  
Ebrahim Shahghasemi ◽  
Sara Nazif
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Daily Precipitation ◽  
Extreme Event ◽  
Climate Change Impacts ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Study Region ◽  
Rainfall Events ◽  
Synoptic Weather Typing

Climate change has impacted all phenomena in the hydrologic cycle, especially extreme events. General circulation models (GCMs) are used to investigate climate change impacts but because of their low resolution, downscaling methods are developed to provide data with high enough resolution for regional studies from GCM outputs. The performance of rainfall downscaling methods is commonly acceptable in preserving average characteristics, but they do not preserve the extreme event characteristics especially rainfall amount and distribution. In this study, a novel downscaling method called synoptic statistical downscaling model is proposed for daily precipitation downscaling with an emphasis on extreme event characteristics preservation. The proposed model is applied to a region located in central Iran. The results show that the developed model can downscale all percentiles of precipitation events with an acceptable performance and there is no assumption about the similarity of future rainfall data with the historical observations. The outputs of CCSM4 GCM for two representative concentration pathways (RCPs) of RCP4.5 and RCP8.5 are used to investigate the climate change impacts in the study region. The results show 40% and 30% increase in the number of extreme rainfall events under RCP4.5 and RCP8.5, respectively.

scholarly journals Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 degrees’ warmer worlds – How anthropogenic aerosols change the story

2018 ◽  
Author(s):  
Ruksana H. Rimi ◽  
Karsten Haustein ◽  
Emily J. Barbour ◽  
Sarah N. Sparrow ◽  
Sihan Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Model ◽  
Substantial Reduction ◽  
Extreme Rainfall ◽  
Extreme Weather Events ◽  
Future Climate Change ◽  
Anthropogenic Aerosols ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract. Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5 °C and 2 °C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5 °C, and 2.0 °C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5 °C compared with 2 °C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events.

Vegetation dynamics in a climate change hotspot: trend analysis in a Spanish dehesa

2021 ◽  
Author(s):  
Fabian Reddig ◽  
Georg Bareth ◽  
Christina Bogner
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Water Stress ◽  
Vegetation Dynamics ◽  
Data Driven ◽  
Seasonal Component ◽  
Positive Effects ◽  
Oak Trees ◽  
Starting Point ◽  
Ndvi Time Series

<p><strong>      Introduction </strong>The Mediterranean region has been identified as a hotspot of climate change characterized by a large tree mortality. Extended drought periods, shifts in rainfall patterns, and increasing water stress are probably the main drivers. Especially holm (<em>Quercus ilex L.</em>) and cork oak trees (<em>Quercus suber L.</em>) in high-value and nature-based agroforestry systems (in Spain known as dehesa) have multiple positive effects on the microclimate, carbon storage, erosion prevention, increase of soil water content, and soil nutrient concentration, for example. With their positive effect on wind velocity, they are also considered the last natural barrier protecting the Iberian Peninsula and Central Europe from desertification processes advancing from North Africa.<br><strong>     Objective </strong>We assume that wrong management, biotic causes like pests and diseases, and especially water stress are responsible for a decreased resilience of oak trees. Our goal was to analyse the vegetation dynamics with the help of the Normalized Difference Vegetation Index (NDVI) time series as an indicator for greenness and vitality. In particular, we focused on the trend of NDVI over about two decades.<br><strong>    Material and Methods</strong> We have selected eight plots (250 m x 250 m) with different topographical conditions and analysed an 18 years long NDVI time series (2003 - 2020) from MODIS (MYD13Q1). To extract the trend, we decomposed the time series into trend, seasonal component, and the high-frequency remainder. Subsequently, we did the Mann-Kendall test on the trend component to determine whether the trend is significant. Since environmental time series are rarely linear or stationary, many statistical decomposition methods are not suitable to produce physically meaningful results. Therefore we used the data-driven method <em>Complete Ensemble Empirical Mode Decomposition with adaptive Noise</em> (CEEMDAN) by Torres et al. 2011.<br><strong>     Results </strong>Depending on the topographical conditions of the plot, we were able to extract different NDVI trend signals from the time series. The NDVI values on the north-facing plots were larger than on the south-facing plots. The extracted trends were positive and significant (p <0.01). The seasonal component corresponded to the expected annual cycle.<br><strong>      Conclusion</strong> In order to assess vegetation dynamics, NDVI time series can be regarded as a good starting point, although one indicator alone does not allow to make final conclusions about vegetation changes. The purely data-driven decomposition method CEEMDAN avoids strong assumptions about the shape of the trend.</p>

scholarly journals Riverbed Migrations in Western Taiwan under Climate Change

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1631 ◽  
Author(s):  
Yi-Chiung Chao ◽  
Chi-Wen Chen ◽  
Hsin-Chi Li ◽  
Yung-Ming Chen
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Peak Flow ◽  
Extreme Rainfall ◽  
Base Period ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Flow Discharge ◽  
The Future ◽  
The Impact

In recent years, extreme weather phenomena have occurred worldwide, resulting in many catastrophic disasters. Under the impact of climate change, the frequency of extreme rainfall events in Taiwan will increase, according to a report on climate change in Taiwan. This study analyzed riverbed migrations, such as degradation and aggradation, caused by extreme rainfall events under climate change for the Choshui River, Taiwan. We used the CCHE1D model to simulate changes in flow discharge and riverbed caused by typhoon events for the base period (1979–2003) and the end of the 21st century (2075–2099) according to the climate change scenario of representative concentration pathways 8.5 (RCP8.5) and dynamical downscaling of rainfall data in Taiwan. According to the results on flow discharge, at the end of the 21st century, the average peak flow during extreme rainfall events will increase by 20% relative to the base period, but the time required to reach the peak will be 8 h shorter than that in the base period. In terms of the results of degradation and aggradation of the riverbed, at the end of the 21st century, the amount of aggradation will increase by 33% over that of the base period. In the future, upstream sediment will be blocked by the Chichi weir, increasing the severity of scouring downstream. In addition, due to the increased peak flow discharge in the future, the scouring of the pier may be more serious than it is currently. More detailed 2D or 3D hydrological models are necessary in future works, which could adequately address the erosive phenomena created by bridge piers. Our results indicate that not only will flood disasters occur within a shorter time duration, but the catchment will also face more severe degradation and aggradation in the future.

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