A multivariate assessment of climate change projections over South America using the fifth phase of the Coupled Model Intercomparison Project

Author(s):  
Valerie Thaler ◽  
Paul C. Loikith ◽  
C. Roberto Mechoso ◽  
Luana Albertani Pampuch
2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Udit Bhatia ◽  
Amar Deep Tiwari

Abstract Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.


2018 ◽  
Vol 8 (1) ◽  
pp. 13-24 ◽  
Author(s):  
MBOTE BETH WAMBUI ◽  
ALFRED OPERE ◽  
JOHN M. GITHAIGA ◽  
FREDRICK K. KARANJA

Wambui MB, Opere A, Githaiga MJ, Karanja FK. 2017. Assessing the impacts of climate variability and climate change on biodiversity in Lake Nakuru, Kenya. Bonorowo Wetlands 1: 13-24. This study evaluates the impacts of the raised water levels and the flooding of Lake Nakuru and its surrounding areas on biodiversity, specifically, the phytoplankton and lesser flamingo communities, due to climate change and climate variability. The study was to review and analyze noticed climatic records from 2000 to 2014. Several methods were used to ascertain the past and current trends of climatic parameters (temperature, rainfall and evaporation), and also the physicochemical characteristics of Lake Nakuru (conductivity, phytoplankton, lesser flamingos and the lake depth). These included time series analysis, and trend analysis, so the Pearson’s correlation analysis was used to show a relationship between the alterations in lake conductivity to alterations in population estimates of the lesser flamingos and the phytoplankton. Data set extracted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) (IPCC Fifth Assessment Report (AR5) Atlas subset) models were subjected to time series analysis method where the future climate scenarios of near surface temperature, rainfall and evaporation were plotted for the period 2017 to 2100 (projection) for RCP2.6 and RCP8.5 relative to the baseline period 1971 to 2000 in Lake Nakuru were analysed. The results were used to evaluate the impact of climate change on the lesser flamingos and phytoplankton abundance. It was noticed that there was a raise in the mean annual rainfall during the study period (2009 to 2014) which brought the increment in the lake’s surface area from a low area of 31.8 km² in January 2010 to a high of 54.7 km² in Sept 2013, indicating an increment of 22.9 km² (71.92% surface area increment). Mean conductivity of the lake also lessened leading to the loss of phytoplankton on which flamingos feed making them to migrate. A strong positive correlation between conductivity and the lesser flamingo population was noticed signifying that low conductivity affects the growth of phytoplankton and since the lesser flamingos depend on the phytoplankton for their feed, this subsequently revealed that the phytoplankton density could be a notable predictor of the lesser flamingo occurrence in Lake Nakuru. There was also a strong positive correlation noticed between phytoplankton and the lesser flamingo population which confirms that feed availability is a key determining factor of the lesser flamingo distribution in the lake. It is projected that there would be an increment in temperatures, rainfall and evaporation for the period 2017 to 2100 under RCP2.6 and RCP8.5 relative to the baseline period 1971 to 2000 obtained from the Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble. As a result, it is expected that the lake will further increment in surface area and depth by the year 2100 due to increased rainfall thereby affecting the populations of the lesser flamingos and phytoplankton, as the physicochemical factors of the lake will alter as well during the projected period.


2020 ◽  
Vol 14 (9) ◽  
pp. 3155-3174 ◽  
Author(s):  
Eleanor J. Burke ◽  
Yu Zhang ◽  
Gerhard Krinner

Abstract. Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.


2020 ◽  
Vol 148 (9) ◽  
pp. 3653-3680 ◽  
Author(s):  
Stephanie Fiedler ◽  
Traute Crueger ◽  
Roberta D’Agostino ◽  
Karsten Peters ◽  
Tobias Becker ◽  
...  

Abstract The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden–Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming.


2020 ◽  
Vol 20 (21) ◽  
pp. 12905-12920
Author(s):  
David S. Stevenson ◽  
Alcide Zhao ◽  
Vaishali Naik ◽  
Fiona M. O'Connor ◽  
Simone Tilmes ◽  
...  

Abstract. We analyse historical (1850–2014) atmospheric hydroxyl (OH) and methane lifetime data from Coupled Model Intercomparison Project Phase 6 (CMIP6)/Aerosols and Chemistry Model Intercomparison Project (AerChemMIP) simulations. Tropospheric OH changed little from 1850 up to around 1980, then increased by around 9 % up to 2014, with an associated reduction in methane lifetime. The model-derived OH trends from 1980 to 2005 are broadly consistent with trends estimated by several studies that infer OH from inversions of methyl chloroform and associated measurements; most inversion studies indicate decreases in OH since 2005. However, the model results fall within observational uncertainty ranges. The upward trend in modelled OH since 1980 was mainly driven by changes in anthropogenic near-term climate forcer emissions (increases in anthropogenic nitrogen oxides and decreases in CO). Increases in halocarbon emissions since 1950 have made a small contribution to the increase in OH, whilst increases in aerosol-related emissions have slightly reduced OH. Halocarbon emissions have dramatically reduced the stratospheric methane lifetime by about 15 %–40 %; most previous studies assumed a fixed stratospheric lifetime. Whilst the main driver of atmospheric methane increases since 1850 is emissions of methane itself, increased ozone precursor emissions have significantly modulated (in general reduced) methane trends. Halocarbon and aerosol emissions are found to have relatively small contributions to methane trends. These experiments do not isolate the effects of climate change on OH and methane evolution; however, we calculate residual terms that are due to the combined effects of climate change and non-linear interactions between drivers. These residual terms indicate that non-linear interactions are important and differ between the two methodologies we use for quantifying OH and methane drivers. All these factors need to be considered in order to fully explain OH and methane trends since 1850; these factors will also be important for future trends.


2015 ◽  
Vol 7 (5) ◽  
pp. 891
Author(s):  
José Ueliton Pinheiro ◽  
Josemir Araújo Neves ◽  
Rosane Rodrigues Chaves ◽  
David Mendes ◽  
Naurinete Costa Barreto

A pesquisa estudou a saída de modelos de mudanças climáticas que melhor expressam a atuação dos Vórtices Ciclônicos em Altos Níveis (VCANs) no Nordeste Brasileiro (NEB). Os VCANs foram quantificados pela sua ocorrência diária durante 5 anos (1995-1999), no período de outubro a março. O objeto de estudo foram 13 modelos do CMIP5/IPCC/AR5 (Coupled Model Intercomparison Project Phase 5/Intergovernmental Panel on Climate Change/Fifth Assessment Report), comparados com os resultados do NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research), por meio de métodos estatísticos para escolha do modelo que melhor indica a presença dos VCANs no NEB. A primeira análise comparativa foi feita através das correlações de Pearson, Kendall e Spearman, Raiz quadrada do erro quadrático médio, Raiz quadrada do erro quadrático médio normalizada e os índices de Eficiência e desempenho, Nash-Sutcliffe (NSE), Kling-Gupta (KGE) e o Índice de Concordância de Willmott (d). Em seguida foram selecionados os modelos de melhor desempenho e com significância estatística para uma análise posterior de acertos e erros através dos índices: Índice de Proporção Correta (PC), Índice de Sucesso Crítico (ISC), Probabilidade de Detecção (POD), Taxa de alarme Falso (TAF) e Taxa de Tendência (VIÉS). Para os testes estatísticos aplicados na primeira avaliação realizada o modelo MIROC4h foi o que apresentou os melhores índices seguido pelo MIROC-ESM e inmCM4, respectivamente. Além destes, ainda apresentaram correlação estatística significante o MPI-ESM-LR,o MRI-CGCM3 e o CSIRO-MK3-6-0. A segunda análise também apresentou o MIROC4h com os melhores valores de PC, ISC e POD, excetuando-se o VIÉS que apresentou o segundo melhor resultado e o TAF com o pior resultado em relação aos outros 5 modelos. Dessa forma o MIROC4h apresentou-se como o mais indicado entre os modelos do CMIP5 para estudos de cenários presentes e futuros de VCANs no NEB.   A B S T R A C T The research studied the output of climate change models that best express the actions of Upper Tropospheric Cyclonic Vortices (UTCV) in high levels in the Northeast Brazil (NEB). The UTCV were quantified by a daily occurrence for 5 years (1995-1999) in the period from October to March. The object of the study were 13 models from CMIP5/IPCC/AR5 (Coupled Model Intercomparison Project Phase 5 / Intergovernmental Panel on Climate Change / Fifth Assessment Report ), compared with results from the NCEP / NCAR (National Centers for Environmental Prediction / National Center for Atmospheric Research) by means of statistical methods for choosing the model which best indicates the presence of UTCV in the NEB. The first comparative analysis was performed using the Pearson, Spearman and Kendall correlations, mean square error, normalized mean square error and efficiency and performance indices, Nash-Sutcliff (NSE), Kling-Gupta (KGE) and Index of Agreement of the Willmott (d). Then models with better performance and statistical significance for further analysis of successes and mistakes through the indices were selected: Index Proportion Correct (PC), Critical Success Index (CSI), Probability of Detection (POD), False Alarm Rate (FAR) and Trend Rate (BIAS). For the statistical analyzes used in the first test performed MIROC4h model showed the best rates followed by MIROC-ESM and inmCM4 respectively. In addition, further significant statistical correlation MPI-ESM-LR, MRI-CGCM3 and CSIRO-MK3-6-0. The second analysis also showed the MIROC4h with the best values ​​of PC, CSI and POD, except the BIAS that had the second best result and the FAR with the worst result in relation to the other five models considered in this phase. Thus the MIROC4h introduced himself as the most suitable model of the CMIP5 for studies of the present and future scenarios of UTCV in the NEB   


2020 ◽  
Vol 35 (3) ◽  
pp. 449-457
Author(s):  
Ilma Ribeiro de Lima ◽  
Cleiton da Silva Silveira ◽  
Francisco das Chagas Vasconcelos Júnior

Resumo A viabilidade hídrica do Complexo Industrial de exploração e beneficiamento de urânio e fosfato em Santa Quitéria - Ceará foi analisada a partir da relação nexo água, energia e clima. Para tanto, foram usadas projeções de precipitação, evapotranspiração e vazão adotanto os modelos globais do Coupled Model Intercomparison Project Phase 5 (CMIP5, utilizados no quinto relatório do Intergovernmental Panel on Climate Change - IPCC-AR5). Dados da matriz energética do Ceará também foram considerados com o intuito de verificar o aumento da demanda energética do estado e a analisar o impacto da sua produção frente aos recursos hídircos. Os modelos divergem quanto ao futuro das precipitações, mas a maioria assinala um aumento da evapotranspiração nos três períodos projetados (2015 - 2044, 2045 - 2074 e 2075 a 2099) nos dois cenários escolhidos (RCP4.5 e RCP8.5) indicando um possível aumento da demanda hídrica para a região.


2014 ◽  
Vol 27 (22) ◽  
pp. 8372-8383 ◽  
Author(s):  
Angeline G. Pendergrass ◽  
Dennis L. Hartmann

Abstract Changes in the frequency and intensity of rainfall are an important potential impact of climate change. Two modes of change, a shift and an increase, are applied to simulations of global warming with models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The response to CO2 doubling in the multimodel mean of CMIP5 daily rainfall is characterized by an increase of 1% K−1 at all rain rates and a shift to higher rain rates of 3.3% K−1. In addition to these increase and shift modes of change, some models also show a substantial increase in rainfall at the highest rain rates called the extreme mode of response to warming. In some models, this extreme mode can be shown to be associated with increases in grid-scale condensation or gridpoint storms.


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