Observed and projected changes in extreme drought and wet-prone regions over India under CMIP5 RCP8.5 using a new vulnerability index

2021 ◽  
Author(s):  
Pravat Jena ◽  
sarita azad
Keyword(s):  
East Coast ◽  
Monsoon Rainfall ◽  
Coupled Model ◽  
Vulnerability Index ◽  
Extreme Drought ◽  
Time Period ◽  
Economic Parameters ◽  
Spatio Temporal ◽  
Projected Changes ◽  
Individual Grid

Abstract Past versions of vulnerability index have shown ability to detect susceptible region by assessing socio-economic parameters at local scales. However, due to variability of these vulnerability index respect to socio-economic parameters, cann’t be utilized to predict the susceptibility region. The present endeavor aims to develops a new vulnerable index which identify and predict the spatio-temporal imprint of extreme drought and wet events at various scales 1o×1o in India by analyzing monthly observed and Coupled Model Inter-Comparison Phase 5 (CMIP5) rainfall data at spatial scale of time period pertaining to 1901-2100. New vulnerability index is proposed by consolidating the outcomes of Standard Precipitation Index (SPI) at different time scales such as 3- and 12-month and along with weights of individual grids. The weights of individual grid is calculated through the occurrence of extreme drought and wet events in the recent past which is to include a climate change factor in the proposed index. Based on the spatial distribution of high index values, the expected vulnerable regions concerning extreme drought events will be in Northeast, Northeast Central, East Coast, West, Northwest, Northcentral, and some grids in South part of India. Similarly, vulnerable regions concerning extreme wet events are likely to be in the Northeast, West Coast, East Coast, and some grids in the Peninsular region.Further, a conceptual model is presented to quantify the severity of extreme events. The analyses reveal that on the CMIP5 model data, it is obtained that 2024, 2026-27, 2035, 2036-37, 2043-44, 2059-60, 2094 are likely to be the most prominent drought years in all-India monsoon rainfall and their impact will persist for a longer time. Similarly, the most prominent wet events are predicted to be 2076, 2079-80, 2085, 2090, 2092, and 2099.

Projected changes of Precipitation over the far Eastern Tropical Pacific and Western Colombia

2021 ◽  
Author(s):  
Juliana Valencia ◽  
John F. Mejía
Keyword(s):  
Coupled Model ◽  
Temporal Distribution ◽  
Tropical Pacific ◽  
System Model ◽  
Eastern Tropical Pacific ◽  
Climate System Model ◽  
Project Phases ◽  
Spatio Temporal ◽  
Projected Changes ◽  
Far Eastern

<p>The far Eastern Tropical Pacific and Western Colombia is one of the rainiest places on Earth, and the Choco low-level jet (ChocoJet) is one of the processes that influence the formation of precipitation and convection organization in this region. This study examines projected changes in precipitation using historical and future simulations based on the NCAR Community Climate System Model (CCSM2, 4) and the Community Earth System Model (CESM2), contributing to the Coupled Model Inter-Comparison Project phases 3, 5, and 6 (CMIP3, 5, and 6).  We use detailed process-based diagnostic approaches to evaluate the ability of the models in simulating ChocoJet and precipitation relationships at different temporal scales, from daily to interannual.  Overall, day-to-day positive disturbances in ChocoJet relate to an increase in intense precipitation events.  This relationship is found even in locations far inland in the intermountain valleys of the Colombian Andes. Our results show that relative to CMIP3 and CMIP5 the CMIP6-CESM2 historical simulations show a considerable improvement of precipitation spatio-temporal distribution, with the day-to-day variability and precipitation response resembling more closely that of the observations.  In general, late 21<sup>st</sup> century simulations show a decrease in mean and extreme precipitation consistent the decreased ChocoJet activity.  The down trend in ChocoJet activity appears to be connected to a projected increase in frequency and intensity of the warm phase of ENSO.</p>

Do CMIP5 models hint at a warmer and wetter India in the 21st century?

2015 ◽  
Vol 7 (2) ◽  
pp. 280-295 ◽  
Author(s):  
Rajib Maity ◽  
Ankit Aggarwal ◽  
Kironmala Chanda
Keyword(s):  
General Circulation ◽  
Winter Season ◽  
Coupled Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Historical Period ◽  
The North ◽  
North Eastern ◽  
Spatio Temporal ◽  
Projected Changes

This study diagnoses the spatio-temporal variation of three major hydroclimatic variables (temperature, precipitation and evaporation) estimated from four general circulation models participating in the Fifth Phase of the Coupled Model Intercomparision Project (CMIP5). Changes in climate regime are analyzed across India for the historical scenario (1850–2005) and for the RCP8.5 scenario (2006–2100). The study provides a relative assessment of projected changes in climatic pattern over different zones in India, broadly divided as southern, Eastern, Western, Central, North-Eastern and Himalayan regions. Monthly data for both the scenarios were obtained, and all the data were re-gridded to a common resolution. All the models show a stronger warming in the future as compared to the historical period. The North-Eastern, Northern and Himalayan regions are likely to be severely affected. Though inconsistencies have been observed among the models, the majority of them predict an increase in precipitation in future, with a major increment in southern cities. The Himalayan belt is expected to receive heavy rainfall in the summer season, with little change in the winter season. Most of the regions are not expected to experience change in evaporation in pre-monsoonal months, but substantial change is expected in some regions during monsoonal and post-monsoonal months.

scholarly journals Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6

2021 ◽  
Vol 18 (13) ◽  
pp. 6760
Author(s):  
Isaac Kwesi Nooni ◽  
Daniel Fiifi T. Hagan ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Jiao Lu ◽  
...  
Keyword(s):  
Extreme Events ◽  
Coupled Model ◽  
Baseline Period ◽  
Model Intercomparison ◽  
Additional Information ◽  
Intercomparison Project ◽  
Key Drivers ◽  
Model Ensembles ◽  
Projected Changes ◽  
Near Future

The main goal of this study was to assess the interannual variations and spatial patterns of projected changes in simulated evapotranspiration (ET) in the 21st century over continental Africa based on the latest Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) provided by the France Centre National de Recherches Météorologiques (CNRM-CM) model in the Sixth Phase of Coupled Model Intercomparison Project (CMIP6) framework. The projected spatial and temporal changes were computed for three time slices: 2020–2039 (near future), 2040–2069 (mid-century), and 2080–2099 (end-of-the-century), relative to the baseline period (1995–2014). The results show that the spatial pattern of the projected ET was not uniform and varied across the climate region and under the SSP-RCPs scenarios. Although the trends varied, they were statistically significant for all SSP-RCPs. The SSP5-8.5 and SSP3-7.0 projected higher ET seasonality than SSP1-2.6 and SSP2-4.5. In general, we suggest the need for modelers and forecasters to pay more attention to changes in the simulated ET and their impact on extreme events. The findings provide useful information for water resources managers to develop specific measures to mitigate extreme events in the regions most affected by possible changes in the region’s climate. However, readers are advised to treat the results with caution as they are based on a single GCM model. Further research on multi-model ensembles (as more models’ outputs become available) and possible key drivers may provide additional information on CMIP6 ET projections in the region.

scholarly journals Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece

2021 ◽  
Vol 2 (1) ◽  
pp. 113-139
Author(s):  
Dimitrios Tsiotas ◽  
Thomas Krabokoukis ◽  
Serafeim Polyzos
Keyword(s):  
Network Analysis ◽  
Complex Network ◽  
Community Detection ◽  
Optimization Algorithm ◽  
Spatial Dimension ◽  
Economic Dimension ◽  
Complex Network Analysis ◽  
Time Period ◽  
Time Patterns ◽  
Spatio Temporal

Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP-6 models

2020 ◽  
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Global Mean Temperature ◽  
Almost All

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP-5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP-5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP-6 are of interest. Here, we analyse 32 models of the latest CMIP-6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with high agreement between the models and independent of the SSP; the multi-model mean for JJAS projects an increase of 0.33 mm/day and 5.3 % per degree of global warming. This is significantly higher than in the CMIP-5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP-6 simulations largely confirm the findings from CMIP-5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

scholarly journals An Assessment of Vulnerability of Fishers’ Livelihood to Climate Change in Coastal Odisha

2019 ◽  
Vol 14 (1) ◽  
pp. 60-67 ◽  
Author(s):  
Sambit Priyadarshi ◽  
S. N. Ojha ◽  
Arpita Sharma
Keyword(s):  
Climate Change ◽  
Adaptive Capacity ◽  
East Coast ◽  
Vulnerability Index ◽  
The State ◽  
Context Specificity ◽  
East Coast Of India ◽  
Index Approach ◽  
Vulnerability Score

A study was conducted in Odisha, a state on the east coast of India, with the objective of assessing the vulnerability of fishers’ livelihood to climate change. The state was chosen for study since it is considered as one of the most vulnerable states due to climate change. A total of 120 fishers were interviewed from two districts, Balasore and Ganjam, to assess their livelihood vulnerability by considering their exposure, sensitivity and adaptive capacity to climate change. A composite livelihood vulnerability index by suggesting that fishers are vulnerable to climate change. For fishers of + 0.03 and for Ganjam it was 0.5 minima 0, and maxima 1 was used for the purpose. Baleswar the score was 0.56 0.04, s. The aggregated vulnerability score was found to be 0.54+The composite livelihood vulnerability index approach calculates vulnerability by aggregating data for a set of indicators for the components of vulnerability which include exposure, sensitivity, and adaptive capacity + 0.04. Vulnerability score was relatively higher in Baleswar due to higher scores on the exposure and sensitivity parameters overshadowing the higher adaptive capacity. The study shows evidence that marine fishers of Odisha are vulnerable to climate change. Also, it throws light on the location and context specificity of livelihood vulnerability.

scholarly journals Projected changes in temperature and precipitation over mainland Southeast Asia by CMIP6 models

2021 ◽  
Author(s):  
S. Supharatid ◽  
J. Nafung ◽  
T. Aribarg
Keyword(s):  
Climate Change ◽  
Coupled Model ◽  
Southwest Monsoon ◽  
Future Climate Change ◽  
Boreal Summer ◽  
Northeast Monsoon ◽  
Adaptation Measures ◽  
Mitigation And Adaptation ◽  
Temperature And Precipitation ◽  
Projected Changes

Abstract Five mainland SEA countries (Cambodia, Laos, Myanmar, Vietnam, and Thailand) are threatened by climate change. Here, the latest 18 Coupled Model Intercomparison Project Phase 6 (CMIP6) is employed to examine future climate change in this region under two SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP2-4.5 and SSP5-8.5). The bias-corrected multi-model ensemble (MME) projects a warming (wetting) over Cambodia, Laos, Myanmar, Vietnam, and Thailand by 1.88–3.89, 2.04–4.22, 1.88–4.09, 2.03–4.25, and 1.90–3.96 °C (8.76–20.47, 12.69–21.10, 9.54–21.10, 13.47–22.12, and 7.03–15.17%) in the 21st century with larger values found under SSP5-8.5 than SSP2-4.5. The MME model displays approximately triple the current rainfall during the boreal summer. Overall, there are robust increases in rainfall during the Southwest Monsoon (3.41–3.44, 8.44–9.53, and 10.89–17.59%) and the Northeast Monsoon (−2.58 to 0.78, −0.43 to 2.81, and 2.32 to 5.45%). The effectiveness of anticipated climate change mitigation and adaptation strategies under SSP2-4.5 results in slowing down the warming trends and decreasing precipitation trends after 2050. All these findings imply that member countries of mainland SEA need to prepare for appropriate adaptation measures in response to the changing climate.

scholarly journals PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

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