scholarly journals Monitoring the Reduced Resilience of Forests in Southwest China Using Long-Term Remote Sensing Data

2021 ◽  
Vol 14 (1) ◽  
pp. 32
Author(s):  
Hao Jiang ◽  
Lisheng Song ◽  
Yan Li ◽  
Mingguo Ma ◽  
Lei Fan
Keyword(s):  
Climate Change ◽  
Water Availability ◽  
Southwest China ◽  
Remote Sensing Data ◽  
Root Systems ◽  
Severe Drought ◽  
Spatial Distributions ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Good Agreement

An increase in the frequency and severity of droughts associated with global warming has resulted in deleterious impacts on forest productivity in Southwest China. Despite attempts to explore the response of vegetation to drought, less is known about forest’s resilience in response to drought in Southwest China. Here, the reduced resilience of the forest was found based on remotely sensed optical and microwave vegetation products. The spatial distribution and temporal variation of resilience-reduced forest were assessed using the standardized precipitation evapotranspiration index (SPEI) and vegetation optical depth (VOD). Our findings showed that 40–50% of the forest appeared to have abnormally low resilience approximately 6 months after the severe drought. The spatial distributions of abnormally low resilience had a good agreement with the regions affected by the 2009–2011 drought events. In particular, our results indicated that areas of afforestation were more susceptible to drought than natural forest, maybe due to the different water uptake strategy of the diverse root systems. Our findings highlight the vulnerability of afforestation areas to climate change, and recommend giving more attention to soil water availability.

scholarly journals Spatiotemporal Differences in Dominants of Dryness/Wetness Changes in Southwest China

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Shujia Zhou ◽  
Shanlei Sun ◽  
Wanrong Shi ◽  
Jiazhi Wang ◽  
Jinjian Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Development ◽  
Southwest China ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Full Analysis

A full analysis of 3-month Standardized Precipitation-Evapotranspiration index (SPEI-3) changes and attribution analyses are of significance for deeply understanding dryness/wetness evolutions and thus formulating specific measures to sustain regional development. In this study, we analyze monthly and annual SPEI-3 changes over Southwest China (SWC; including Sichuan (SC), Chongqing (CQ), Guizhou (GZ), Yunnan (YN), and west Guangxi (wGX)) during 1961–2012, using the SPEI model and routine meteorological measurements at 269 weather sites. For SWC and each subregion (excluding wGX), annual SPEI-3 during 1961–2012 tends to decrease, and drying is at most of months in January and September–December, but wetting is in February–August (excluding March for wGX). Additionally, more than 50% of sites show declined and increased SPEI-3 in January, April, June, and August–December and the remaining months, respectively. Except for wGX with dominant of ET0, annual SPEI-3 changes in SWC and other four subregions have dominant of precipitation. Spatially, annual SPEI-3 changes at 59% of sites are because of precipitation, generally located in southeast SC, south YN, CQ, GZ, and south and northeast wGX. Nevertheless, dominants at regional and site scales vary among months, e.g., SWC, SC, CQ, and GZ, having dominant of precipitation (ET0) during September–December (most of months during January–August), YN always with dominant of precipitation, and wGX with dominant of precipitation (ET0) in February–April and July–December (January, May, and June). Importantly, this study provides a reference for quantitatively evaluating spatiotemporal dryness/wetness variations with climate change, especially for regions with significant drying/wetting.

scholarly journals Exploring the Evolution of Drought Characteristics in Balochistan, Pakistan

2020 ◽  
Vol 10 (3) ◽  
pp. 913 ◽  
Author(s):  
Shoaib Jamro ◽  
Falak Naz Channa ◽  
Ghulam Hussain Dars ◽  
Kamran Ansari ◽  
Nir Y. Krakauer
Keyword(s):  
Climate Change ◽  
Drought Index ◽  
Risk Index ◽  
Trend Test ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Long Duration ◽  
Tree Edge ◽  
Edge Removal ◽  
The 1960S

In the wake of a rapidly changing climate, droughts have intensified, in both duration and severity, across the globe. The Germanwatch long-term Climate Risk Index ranks Pakistan among the top 10 countries most affected by the adverse effects of climate change. Within Pakistan, the province of Balochistan is among the most vulnerable regions due to recurring prolonged droughts, erratic precipitation patterns, and dependence on agriculture and livestock for survival. This study aims to explore how the characteristics of droughts have evolved in the region from 1902–2015 using 3-month and 12-month timescales of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The region was divided into six zones using Spatial “K”luster Analysis using Tree Edge Removal (SKATER) method, and run theory was applied to characterize droughts in terms of duration, severity, intensity, and peak. The results of the non-parametric Mann–Kendall trend test applied to SPEI indicate prevailing significant negative trends (dryer conditions) in all the zones. Balochistan experienced its most severe droughts in the 1960s and around 2000. The effects of climate change are also evident in the fact that all the long duration droughts occurred after 1960. Moreover, the number of droughts identified by 3-month SPEI showed a significant increase after 1960 for all six zones. The same trend was found in the 12-month SPEI but for only three zones.

scholarly journals Merged SAGE II, Ozone_cci and OMPS ozone profile dataset and evaluation of ozone trends in the stratosphere

2017 ◽  
Vol 17 (20) ◽  
pp. 12533-12552 ◽  
Author(s):  
Viktoria F. Sofieva ◽  
Erkki Kyrölä ◽  
Marko Laine ◽  
Johanna Tamminen ◽  
Doug Degenstein ◽  
...  
Keyword(s):  
Climate Change ◽  
Stratospheric Ozone ◽  
European Space Agency ◽  
Space Agency ◽  
Ozone Profile ◽  
Ozone Trends ◽  
Stratospheric Cooling ◽  
The Individual ◽  
Good Agreement

Abstract. In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on Suomi-NPP. The merged dataset is created in the framework of the European Space Agency Climate Change Initiative (Ozone_cci) with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and intercompared; only those datasets which are in good agreement, and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE–CCI–OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE–CCI–OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at midlatitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.

scholarly journals Merged SAGE II, Ozone_cci and OMPS ozone profiles dataset and evaluation of ozone trends in the stratosphere

2017 ◽  
Author(s):  
Viktoria F. Sofieva ◽  
Erkki Kyrölä ◽  
Marko Laine ◽  
Johanna Tamminen ◽  
Doug Degenstein ◽  
...  
Keyword(s):  
Climate Change ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stratospheric Ozone ◽  
European Space Agency ◽  
Space Agency ◽  
Ozone Trends ◽  
The Individual ◽  
Good Agreement

Abstract. In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on Suomi-NPP. The merged dataset is created in the framework of European Space Agency Climate Change Initiative (Ozone_cci) with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and inter-compared; only those datasets, which are in good agreement and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE-CCI-OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE-CCI-OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at mid-latitudes in the upper stratosphere and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s.

scholarly journals Climate Adaptation in the Water Sector in India

2019 ◽  
pp. 498-518
Author(s):  
Veena Srinivasan
Keyword(s):  
Climate Change ◽  
Water Availability ◽  
Climate Models ◽  
Climate Adaptation ◽  
Hydrologic Cycle ◽  
Rainfall Trends ◽  
Droughts And Floods ◽  
Regional Redistribution ◽  
Short Term Variability

Climate change is likely to affect both the short-term variability of water resources through increased frequency and intensity of droughts and floods, and long-term changes in mean renewable water supply. Both models and historical data suggest that temperatures have increased in most parts of India, affecting the hydrologic cycle through decreased Himalayan snowpack, increased evaporation, and evapotranspirative demand by vegetation. In contrast, there are uncertainties about the climate–rainfall relationship. While most climate models predict intensification of the Indian monsoon, past rainfall trends suggest a weakening and a regional redistribution, perhaps due to local factors such as aerosols, land use change, and sea surface temperatures. Translating these uncertain projections to water availability is complicated by sparse hydrologic records and human modifications of catchments. Empirical research suggests that climate change is not the only stressor. As climate and socio-economic futures are interlinked, this requires participatory, adaptive management and mainstreaming of adaptation across agencies.

scholarly journals Stochastic System Dynamics Modelling for climate change water scarcity assessment on a reservoir in the Italian Alps

2021 ◽  
Author(s):  
Stefano Terzi ◽  
Janez Sušnik ◽  
Stefan Schneiderbauer ◽  
Silvia Torresan ◽  
Andrea Critto
Keyword(s):  
Climate Change ◽  
System Dynamics ◽  
Water Availability ◽  
Water Scarcity ◽  
Stochastic System ◽  
Anthropogenic Activities ◽  
Short Term ◽  
System Dynamics Modelling ◽  
Dynamics Modelling

Abstract. Water management in mountain regions is facing multiple pressures due to climate change and anthropogenic activities. This is particularly relevant for mountain areas where water abundance in the past allowed for many anthropogenic activities, exposing them to future water scarcity. To better understand the processes involved in water scarcity impact, an innovative stochastic System Dynamics Modelling (SDM) explores water stored and turbined in the S.Giustina reservoir (Province of Trento, Italy). The integration of outputs from climate change simulations as well as from a hydrological model and statistical models into the SDM is a quick and effective tool to simulate past and future water availability and demand conditions. Short-term RCP4.5 simulations depict conditions of highest volume and outflow reductions starting in spring (−16.1 % and −44.7 % in May compared to the baseline). Long-term RCP8.5 simulations suggest conditions of volume and outflow reductions starting in summer and lasting until the end of the year. The number of events with stored water below the 30th and above the 80th quantiles suggest a general reduction both in terms of low and high volumes. These results call for the need to adapt to acute short-term water availability reductions in spring and summer while preparing for hydroelectric production reductions due to the chronic long-term trends affecting autumn and mid-winter. This study provides results and methodological insights for potential SDM upscaling across strategic mountain socio-economic sectors (e.g., hydropower, agriculture and tourism) to expand water scarcity assessments and prepare for future multi-risk conditions and impacts.

scholarly journals Long-Term Variability in Potential Evapotranspiration, Water Availability and Drought under Climate Change Scenarios in the Awash River Basin, Ethiopia

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 883 ◽  
Author(s):  
Mahtsente Tadese ◽  
Lalit Kumar ◽  
Richard Koech
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Water Availability ◽  
Potential Evapotranspiration ◽  
Management Strategies ◽  
Water Shortage ◽  
Climate Change Scenarios ◽  
Awash River Basin ◽  
Mitigate Climate Change

Understanding the hydrological processes of a watershed in response to climate change is vital to the establishment of sustainable environmental management strategies. This study aimed to evaluate the variability of potential evapotranspiration (PET) and water availability in the Awash River Basin (ARB) under different climate change scenarios and to relate these with long-term drought occurrences in the area. The PET and water availability of the ARB was estimated during the period of 1995–2009 and two future scenarios (2050s and 2070s). The representative concentration pathways (RCP4.5 and RCP8.5) simulations showed an increase in the monthly mean PET from March to August in the 2050s, and all the months in the 2070s. The study also identified a shortage of net water availability in the majority of the months investigated and the occurrence of mild to extreme drought in about 40–50% of the analysed years at the three study locations (Holetta, Koka Dam, and Metehara). The decrease in water availability and an increase in PET, combined with population growth, will aggravate the drought occurrence and food insecurity in the ARB. Therefore, integrated watershed management systems and rehabilitation of forests, as well as water bodies, should be addressed in the ARB to mitigate climate change and water shortage in the area.

A new method of PWV retrieval over land with remote sensing data: a case of AMSR2

2020 ◽  
Author(s):  
Nan Jiang ◽  
Yan Xu ◽  
Tianhe Xu
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Global Climate ◽  
Weather Prediction ◽  
Remote Sensing Data ◽  
Precipitable Water ◽  
Global Scale ◽  
Brightness Temperatures ◽  
Climate Studies

<p>Precipitable water vapor (PWV) is an important parameter reflecting the amount of solid water in the atmosphere, which is widely utilized in the studies of numerical weather prediction (NWP) and climate change. The microwave radiance measurements made by the space-based remote sensing satellites give us the opportunity to make the climate studies on a global scale. So far, PWV retrieval over the ocean has a long data record and the technology is very mature, but in the case of PWV retrieval over land, it is more challenging to isolate the atmospheric signals from the varied surface signals. In this study, we will apply a new retrieval method over land based on the dual-polarized difference (vertical and horizontal) at 19 GHz and 23 GHz using the brightness temperatures from the Global Change Observation Mission-Water (GCOM-W)/Advanced Microwave Scanning Radiometer 2 (AMSR2). We found polarization difference in brightness temperatures has an exponential relation on the amount of PWV. The validation results of the PWV retrieval from the ground-based GNSS stations show that the proposed method has a mean accuracy of 3.9 mm. Thus, the proposed method can give a possibility to improve the accuracy of data assimilation in the NWP applications and is useful for the studies of global climate change with the long-term data records.</p>

A multi-risk assessment of water scarcity in the south-eastern Italian Alps using a System Dynamics approach

2020 ◽  
Author(s):  
Stefano Terzi ◽  
Janez Sušnik ◽  
Sara Masia ◽  
Silvia Torresan ◽  
Stefan Schneiderbauer ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Availability ◽  
Water Scarcity ◽  
Water Demand ◽  
Anthropogenic Activities ◽  
High Water ◽  
Climate Change Scenarios ◽  
Multiple Impacts ◽  
Dam Reservoirs

<p>Mountain regions are facing multiple impacts due to climate change and anthropogenic activities. Shifts in precipitation and temperature are affecting the available water influencing a variety of economic activities that still rely on large quantities of water (e.g. ski tourism, energy production and agriculture). The Alps are among those areas where recent events of decreased water availability triggered emerging water disputes and spread of economic impacts across multiple sectors and from upstream high water availability areas to downstream high water demand areas. In order to make our water management systems more resilient, there is a need to unravel the interplays and dependencies that can lead to multiple impacts across multiple sectors. However, current assessments dealing with climate change usually account for a mono sectoral and single risk perspective.</p><p>This study hence shows an integrative assessment of multi-risk processes across strategic sectors of the Alpine economy. System dynamics modelling (SDM) is applied as a powerful tool to evaluate the multiple impacts stemming from interactions and feedbacks among water-food-energy economic sectors of the Noce river catchment in the Province of Trento (Italy).</p><p>The SDM developed for the Noce catchment combined outputs from physically based models to evaluate water availability and statistical assessments for water demands from three main sectors: (i) apple orchards cultivation, (ii) water releases from large dam reservoirs for hydropower production and (iii) domestic and seasonal tourism activities.</p><p>Hydrological results have been validated on historical time series (i.e. 2009-2017) and projected in the future considering RCP 4.5 and 8.5 climate change scenarios for 2021-2050 medium term and 2041-2070 long term. Results show a precipitation decrease affecting river streamflow with consequences on water stored and turbined in all dam reservoirs of the Noce catchment, especially for long-term climate change scenarios. Moreover, temperature scenarios will increase the amount of water used for agricultural irrigation from upstream to downstream. Nevertheless, decreasing population projections will have a beneficial reduction of water demand from residents, counterbalancing the increasing demand from the other sectors.</p><p>Finally, the integrated SDM fostered discussions in the Noce catchment on interplays between climate change and anthropogenic activities to tackle climate-related water scarcity.</p>

scholarly journals Analyzing climate variations on multiple timescales can guide Zika virus response measures

2016 ◽  
Author(s):  
Á.G. Muñoz ◽  
M. C. Thomson ◽  
L. Goddard ◽  
S. Aldighieri
Keyword(s):  
Climate Change ◽  
El Niño ◽  
Zika Virus ◽  
El Nino ◽  
Severe Drought ◽  
Multiple Timescales ◽  
Climate Conditions ◽  
Decadal Scale ◽  
Climate Signals

AbstractBackgroundThe emergence of Zika virus (ZIKV) as a public health emergency in Latin America and the Caribbean (LAC) occurred during a period of severe drought and unusually high temperatures. Speculation in the literature exists that these climate conditions were associated with the 2015/2016 El Niño event and/or climate change but to date no quantitative assessment has been made. Analysis of related flaviviruses –such as dengue and chikungunya, which are transmitted by the same vectors– suggests that ZIKV dynamics is sensitive to climate seasonality and longer-term variability and trends. A better understanding the climate conditions conducive to the 2014-2016 epidemic may permit the development of climate-informed short- and long-term strategies for ZIKV prevention and control.ResultsUsing a novel timescale-decomposition methodology, we demonstrate that extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change –as speculated–, but are the result of a particular combination of climate signals acting at multiple timescales. In Brazil, the heart of the epidemic, we find that dry conditions present during 2013-2015 are explained primarily by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the extreme warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability.ConclusionsZIKV response strategies adapted for a drought context in Brazil during El Niño 2015/2016 may need to be revised to accommodate the likely return of heavy rainfall associated with the probable 2016/2017 La Niña. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals.

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