scholarly journals Climate Simulation and Change in the Brazilian Climate Model

2013 ◽  
Vol 26 (17) ◽  
pp. 6716-6732 ◽  
Author(s):  
Paulo Nobre ◽  
Leo S. P. Siqueira ◽  
Roberto A. F. de Almeida ◽  
Marta Malagutti ◽  
Emanuel Giarolla ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Climate Simulation ◽  
Climate Change Research ◽  
Ocean Atmosphere

Abstract The response of the global climate system to atmospheric CO2 concentration increase in time is scrutinized employing the Brazilian Earth System Model Ocean–Atmosphere version 2.3 (BESM-OA2.3). Through the achievement of over 2000 yr of coupled model integrations in ensemble mode, it is shown that the model simulates the signal of recent changes of global climate trends, depicting a steady atmospheric and oceanic temperature increase and corresponding marine ice retreat. The model simulations encompass the time period from 1960 to 2105, following the phase 5 of the Coupled Model Intercomparison Project (CMIP5) protocol. Notwithstanding the accurate reproduction of large-scale ocean–atmosphere coupled phenomena, like the ENSO phenomena over the equatorial Pacific and the interhemispheric gradient mode over the tropical Atlantic, the BESM-OA2.3 coupled model shows systematic errors on sea surface temperature and precipitation that resemble those of other global coupled climate models. Yet, the simulations demonstrate the model’s potential to contribute to the international efforts on global climate change research, sparking interest in global climate change research within the Brazilian climate modeling community, constituting a building block of the Brazilian Framework for Global Climate Change Research.

scholarly journals Controls on the Diversity in Climate Model Projections of Early Summer Drying over Southern Africa

2019 ◽  
Vol 32 (12) ◽  
pp. 3707-3725 ◽  
Author(s):  
C. Munday ◽  
R. Washington
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Stability ◽  
Coupled Model ◽  
Early Summer ◽  
Intergovernmental Panel ◽  
Surface Temperature Change

Abstract Ninety-five percent of climate models contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) project early summer [October–December (OND)] rainfall declines over subtropical southern Africa by the end of the century, under all emissions forcing pathways. The intermodel consensus underlies the Intergovernmental Panel on Climate Change (IPCC) assessment that rainfall declines are “likely” and implies that significant climate change adaptation is needed. However, model consensus is not necessarily a good indicator of confidence, especially given that there is an order of magnitude difference in the scale of rainfall decline among models in OND (from <10 mm season−1 to ~100 mm season−1), and that the CMIP5 ensemble systematically overestimates present-day OND precipitation over subtropical southern Africa (in some models by a factor of 2). In this paper we investigate the uncertainty in the OND drying signal by evaluating the climate mechanisms that underlie the diversity in model rainfall projections. Models projecting the highest-magnitude drying simulate the largest increases in tropospheric stability over subtropical southern Africa associated with anomalous upper-level subsidence, reduced evaporation, and amplified surface temperature change. Intermodel differences in rainfall projections are in turn related to the large-scale adjustment of the tropical atmosphere to emissions forcing: models with the strongest relative warming of the northern tropical sea surface temperatures compared to the tropical mean warming simulate the largest rainfall declines. The models with extreme rainfall declines also tend to simulate large present-day biases in rainfall and in atmospheric stability, leading the authors to suggest that projections of high-magnitude drying require further critical attention.

scholarly journals GCMs Derived Projection of Precipitation and Analysis of Spatio-Temporal Variation over N-W Himalayan Region

2016 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Dharmaveer Singh ◽  
R.D. Gupta ◽  
Sanjay K. Jain
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Global Climate Models ◽  
Himalayan Region ◽  
Mean Annual Precipitation ◽  
Hadcm3 Model

The ensembles of two Global Climate Models (GCMs) namely, third generation Canadian Coupled Global Climate Model (CGCM3) and Hadley Center Coupled Model, version 3 (HadCM3) are used to project future precipitation in a part of North-Western (N-W) Himalayan region, India. Statistical downscaling method is used to downscale and generate future scenarios of precipitation at station scale from large scale climate variables obtained from GCMs. The observed historical precipitation data has been collected for three metrological stations, namely, Rampur, Sunni and Kasol falling in the basin for further analysis. The future trends and patterns in precipitation under scenarios A2 and A1B for CGCM3 model, and A2 and B2 for HadCM3 model are analyzed for these stations under three different time periods: 2020’s, 2050’s and 2080’s. An overall rise in mean annual precipitation under scenarios A2 and A1B for CGCM3 model have been noticed for future periods: 2020’s, 2050’s and 2080’s. Decrease, in precipitation has been found under A2 and B2 scenarios of HadCM3 model for 2050’s and slight increase for 2080’s periods. Based on the analysis of results, CGCM3 model has been found better for simulation of precipitation in comparison to HadCM3 model.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.1-14

scholarly journals A Large-Scale Bibliometric Analysis of Global Climate Change Research Between 2001 and 2018

2021 ◽  
Author(s):  
Hui-Zhen Fu ◽  
Ludo Waltman
Keyword(s):  
Climate Change ◽  
Bibliometric Analysis ◽  
Global Climate Change ◽  
Large Scale ◽  
Energy Use ◽  
Global Climate ◽  
Future Research ◽  
Public Attention ◽  
Intergovernmental Panel ◽  
Climate Change Research

Abstract Global climate change is attracting widespread scientific, political, and public attention owing to the involvement of international initiatives such as the Paris Agreement and the Intergovernmental Panel on Climate Change. We present a large-scale bibliometric analysis based on approximately 120,000 climate change publications between 2001 and 2018 to examine how climate change is studied in scientific research. Our analysis provides an overview of scientific knowledge, shifts of research hotspots, global geographical distribution of research, and focus of individual countries. In our analysis, we identify five key fields in climate change research: physical sciences, paleoclimatology, climate-change ecology, climate technology, and climate policy. We draw the following key conclusions: (1) Over the investigated time period, the focus of climate change research has shifted from understanding the climate system toward climate technologies and policies, such as efficient energy use and legislation. (2) There is an imbalance in scientific production between developed and developing countries. (3) Geography, national demands, and national strategies have been important drivers that influence the research interests and concerns of researchers in different countries. Our study can be used by researchers and policy makers to reflect on the directions in which climate change research is developing and discuss priorities for future research.

scholarly journals Impacts of climate change on suitability zonation for potato cultivation in Jilin Province, Northeast China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yaqiu Zhu ◽  
Qiang Yu ◽  
Qiyou Luo ◽  
Hua Zhang ◽  
Jinling Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Positive Impact ◽  
Global Climate ◽  
Central Area ◽  
Principal Component ◽  
Jilin Province ◽  
Climatic Parameters

AbstractGlobal climate change is causing notable shifts in the environmental suitability of the main regions involved in potato cultivation and has, thus, changed the production potential of potatoes. These shifts can be mapped at fine scales to better understand climate change within areas of potato cultivation and to find infrastructural- and breeding-based solutions. As a case study, we have identified and mapped the structural and spatial shifts that occurred in areas suitable for potato cultivation in Jilin Province, China. We identified a discontinuity in climate change trends between 1961 and 2018 based on data for Jilin Province, and analyzed the averages and linear trends for six important climatic parameters. We used the averages of these climatic parameters to establish climate models for the province and determined cultivation using a multi-criteria, decision-based model that integrates Analytical Hierarchy Process Weighted Principal Component Analysis (AHP-PCA) and Geographic Information System (GIS). We mapped the environmentally suitable areas for potato cultivation at a 3-km resolution based on the geo-climate model for each time period and analyzed differences between them. We found that "Most suitable” areas for potato cultivation were mainly distributed in the central area of Jilin Province, “Suitable” areas were located in the northwestern plains, and “Sub-suitable” areas were located in the eastern mountainous areas. In contrast, “Not suitable” areas occur mainly in the high-altitude areas in the east. The areas of “Most suitable” and “Suitable” areas for potato cultivation in Jilin Province were increasing, with increasing rates of 0.37 × 1,000 km2 decade−1 (R2 = 0.58, P < 0.01) and 0.20 × 1,000 km2 decade−1 (R2 = 0.28, P < 0.01), respectively, while the extent of “Sub-suitable” areas is decreasing, with a decreasing rate of 0.58 × 1,000 km2 decade−1 (R2 = 0.53, P < 0.05). The area of “Not suitable” areas had undergone little change. “Most suitable” and “Suitable” areas for potato cultivation showed a trend towards northward expansion. Overall, our results suggest that global climate change has had a positive impact on potato cultivation in Jilin Province over the past 58 years.

scholarly journals Impacts of climate change on suitability zonation for potato cultivation in Jilin Province, Northeast China

2021 ◽  
Author(s):  
Yaqiu Zhu ◽  
Qiang Yu ◽  
Qiyou Luo ◽  
Hua Zhang ◽  
Jinling Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Positive Impact ◽  
Global Climate ◽  
Central Area ◽  
Jilin Province ◽  
Climatic Parameters ◽  
Time Period

Abstract Global climate change is causing notable shifts in the environmental suitability of the main regions involved in potato cultivation and has, thus, changed the production potential of potatoes. These shifts can be mapped at fine scales to better understand climate change within areas of potato cultivation and to find infrastructural- and breeding-based solutions. As a case study, we have identified and mapped the structural and spatial shifts that occurred in areas suitable for potato cultivation in Jilin Province, China. We identified a discontinuity in climate change trends between 1961 and 2018 based on data for Jilin Province, and analyzed the averages and linear trends for six important climatic parameters. We used the averages of these climatic parameters to establish climate models for the province and determined cultivation using a multi-criterion, decision-based model that integrates AHP-PCA and GIS. We mapped the environmentally suitable areas for potato cultivation at a 3-km resolution based on the geo-climate model for each time period and analyzed differences between them. We found that "Most suitable” areas for potato cultivation are mainly distributed in the central area of Jilin Province, “Suitable” areas were located in the northwestern plains, and “Sub-suitable” areas in the eastern mountainous areas. In contrast, “Not suitable” areas occur mainly in the high-altitude areas in the east. The areas of “Most suitable” and “Suitable” areas for potato cultivation in Jilin Province are increasing, with increasing rates of 0.37 × 1,000 km² decade− 1 (R2 = 0.58, P < 0.01) and 0.20 × 1,000 km² (R2 = 0.28, P < 0.01), respectively, while the extent of “Sub-suitable” areas is decreasing, with a decreasing rate of 0.58 × 1,000 km² decade− 1 (R2 = 0.53, P < 0.05). The area of “Not suitable” areas has undergone little change. “Most suitable” and “Suitable” areas for potato cultivation showed a trend towards northward expansion. Overall, our results suggest that global climate change has had a positive impact on potato cultivation in Jilin Province over the past 58 years.

scholarly journals Dynamic Downscaling of the Impact of Climate Change on the Ocean Circulation in the Galápagos Archipelago

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Yanyun Liu ◽  
Lian Xie ◽  
John M. Morrison ◽  
Daniel Kamykowski
Keyword(s):  
Climate Change ◽  
Ocean Circulation ◽  
Global Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Ocean Model ◽  
Reanalysis Dataset ◽  
Equatorial Undercurrent ◽  
Galapagos Archipelago ◽  
The Impact

The regional impact of global climate change on the ocean circulation around the Galápagos Archipelago is studied using the Hybrid Coordinate Ocean Model (HYCOM) configured for a four-level nested domain system. The modeling system is validated and calibrated using daily atmospheric forcing derived from the NCEP/NCAR reanalysis dataset from 1951 to 2007. The potential impact of future anthropogenic global warming (AGW) in the Galápagos region is examined using the calibrated HYCOM with forcing derived from the IPCC-AR4 climate model. Results show that although the oceanic variability in the entire Galápagos region is significantly affected by global climate change, the degree of such effects is inhomogeneous across the region. The upwelling region to the west of the Isabella Island shows relatively slower warming trends compared to the eastern Galápagos region. Diagnostic analysis suggests that the variability in the western Galápagos upwelling region is affected mainly by equatorial undercurrent (EUC) and Panama currents, while the central/east Galápagos is predominantly affected by both Peru and EUC currents. The inhomogeneous responses in different regions of the Galápagos Archipelago to future AGW can be explained by the incoherent changes of the various current systems in the Galápagos region as a result of global climate change.

scholarly journals A trait-based approach to assess climate change sensitivity of freshwater invertebrates across Swedish ecoregions

2014 ◽  
Vol 60 (2) ◽  
pp. 221-232 ◽  
Author(s):  
Leonard Sandin ◽  
Astrid Schmidt-Kloiber ◽  
Jens-Christian Svenning ◽  
Erik Jeppesen ◽  
Nikolai Friberg
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Large Scale ◽  
Global Climate ◽  
Species Traits ◽  
Freshwater Ecosystems ◽  
Biological Data ◽  
Conservation Strategies ◽  
Measured Temperature ◽  
Buffer Strips

Abstract Freshwater habitats and organisms are among the most threatened on Earth, and freshwater ecosystems have been subject to large biodiversity losses. We developed a Climate Change Sensitivity (CCS) indicator based on trait information for a selection of stream- and lake-dwelling Ephemeroptera, Plecoptera and Trichoptera taxa. We calculated the CCS scores based on ten species traits identified as sensitive to global climate change. We then assessed climate change sensitivity between the six main ecoregions of Sweden as well as the three Swedish regions based on Illies. This was done using biological data from 1, 382 stream and lake sites where we compared large-scale (ecoregional) patterns in climate change sensitivity with potential future exposure of these ecosystems to increased temperatures using ensemble-modelled future changes in air temperature. Current (1961~1990) measured temperature and ensemble-modelled future (2100) temperature showed an increase from the northernmost towards the southern ecoregions, whereas the predicted temperature change increased from south to north. The CCS indicator scores were highest in the two northernmost boreal ecoregions where we also can expect the largest global climate change-induced increase in temperature, indicating an unfortunate congruence of exposure and sensitivity to climate change. These results are of vital importance when planning and implementing management and conservation strategies in freshwater ecosystems, e.g., to mitigate increased temperatures using riparian buffer strips. We conclude that traits information on taxa specialization, e.g., in terms of feeding specialism or taxa having a preference for high altitudes as well as sensitivity to changes in temperature are important when assessing the risk from future global climate change to freshwater ecosystems.

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 Co-occurrence of extreme ozone and heat waves in two cities from Morocco

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Kenza KHOMSI 1,2 ◽  
Houda NAJMI 2 ◽  
Zineb SOUHAILI 1
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Extreme Events ◽  
Global Climate Change ◽  
Large Scale ◽  
Heat Waves ◽  
Global Climate ◽  
Meteorological Factor ◽  
Two Cities ◽  
Change Context

Temperature is the first meteorological factor to be directly involved in leading ozone (O3) extreme events. Generally, upward temperatures increase the probability of having exceedance in ozone adopted thresholds. In the global climate change context more frequent and/or persistent heat waves and extreme ozone (O3) episodes are likely to occur during in coming decades and a key question is about the coincidence and co-occurrence of these extremes. In this paper, using 7 years of surface temperature and air quality observations over two cities from Morocco (Casablanca and Marrakech) and implementing a percentile thresholding approach, we show that the extremes in temperature and ozone (O3) cluster together in many cases and that the outbreak of ozone events generally match the first or second days of heat waves. This co-occurrence of extreme episodes is highly impacted by humidity and may be overlapping large-scale episodes.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

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