Climate change projections from Coupled Model Intercomparison Project phase 5 multi-model weighted ensembles for Mexico, the North American monsoon, and the mid-summer drought region

2018 ◽  
Vol 38 (15) ◽  
pp. 5699-5716 ◽  
Author(s):  
Gabriela Colorado-Ruiz ◽  
Tereza Cavazos ◽  
José Antonio Salinas ◽  
Pamela De Grau ◽  
Rosario Ayala
2013 ◽  
Vol 26 (18) ◽  
pp. 7187-7197 ◽  
Author(s):  
Wei Cheng ◽  
John C. H. Chiang ◽  
Dongxiao Zhang

Abstract The Atlantic meridional overturning circulation (AMOC) simulated by 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical (1850–2005) and future climate is examined. The historical simulations of the AMOC mean state are more closely matched to observations than those of phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similarly to CMIP3, all models predict a weakening of the AMOC in the twenty-first century, though the degree of weakening varies considerably among the models. Under the representative concentration pathway 4.5 (RCP4.5) scenario, the weakening by year 2100 is 5%–40% of the individual model's historical mean state; under RCP8.5, the weakening increases to 15%–60% over the same period. RCP4.5 leads to the stabilization of the AMOC in the second half of the twenty-first century and a slower (then weakening rate) but steady recovery thereafter, while RCP8.5 gives rise to a continuous weakening of the AMOC throughout the twenty-first century. In the CMIP5 historical simulations, all but one model exhibit a weak downward trend [ranging from −0.1 to −1.8 Sverdrup (Sv) century−1; 1 Sv ≡ 106 m3 s−1] over the twentieth century. Additionally, the multimodel ensemble–mean AMOC exhibits multidecadal variability with a ~60-yr periodicity and a peak-to-peak amplitude of ~1 Sv; all individual models project consistently onto this multidecadal mode. This multidecadal variability is significantly correlated with similar variations in the net surface shortwave radiative flux in the North Atlantic and with surface freshwater flux variations in the subpolar latitudes. Potential drivers for the twentieth-century multimodel AMOC variability, including external climate forcing and the North Atlantic Oscillation (NAO), and the implication of these results on the North Atlantic SST variability are discussed.


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.


2015 ◽  
Vol 28 (17) ◽  
pp. 6707-6728 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Carlos M. Carrillo ◽  
David J. Gochis ◽  
Dorit M. Hammerling ◽  
Rachel R. McCrary ◽  
...  

Abstract This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for the North American monsoon system in the southwestern United States and northwestern Mexico. The focus is on changes in precipitation and the processes driving the projected changes from the regional climate simulations and their driving coupled atmosphere–ocean global climate models. The effect of known biases on the projections is also examined. Overall, there is strong ensemble agreement for a large decrease in precipitation during the monsoon season; however, this agreement and the magnitude of the ensemble-mean change is likely deceiving, as the greatest decreases are produced by the simulations that are the most biased in the baseline/current climate. Furthermore, some of the greatest decreases in precipitation are being driven by changes in processes/phenomena that are less credible (e.g., changes in El Niño–Southern Oscillation, when it is initially not simulated well). In other simulations, the processes driving the precipitation change may be plausible, but other biases (e.g., biases in low-level moisture or precipitation intensity) appear to be affecting the magnitude of the projected changes. The most and least credible simulations are clearly identified, while the other simulations are mixed in their abilities to produce projections of value.


2013 ◽  
Vol 120 (4) ◽  
pp. 965-975 ◽  
Author(s):  
L. O. Mearns ◽  
S. Sain ◽  
L. R. Leung ◽  
M. S. Bukovsky ◽  
S. McGinnis ◽  
...  

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 24 (3) ◽  
pp. 1131-1143 ◽  
Author(s):  
Thanh Le ◽  
Deg-Hyo Bae

Abstract. Climate extremes, such as floods and droughts, might have severe economic and societal impacts. Given the high costs associated with these events, developing early-warning systems is of high priority. Evaporation, which is driven by around 50 % of solar energy absorbed at surface of the Earth, is an important indicator of the global water budget, monsoon precipitation, drought monitoring and the hydrological cycle. Here we investigate the response of global evaporation to main modes of interannual climate variability, including the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO) and the El Niño–Southern Oscillation (ENSO). These climate modes may have an influence on temperature, precipitation, soil moisture and wind speed and are likely to have impacts on global evaporation. We utilized data of historical simulations and RCP8.5 (representative concentration pathway) future simulations derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results indicate that ENSO is an important driver of evaporation for many regions, especially the tropical Pacific. The significant IOD influence on evaporation is limited in western tropical Indian Ocean, while NAO is more likely to have impacts on evaporation of the North Atlantic European areas. There is high agreement between models in simulating the effects of climate modes on evaporation of these regions. Land evaporation is found to be less sensitive to considered climate modes compared to oceanic evaporation. The spatial influence of major climate modes on global evaporation is slightly more significant for NAO and the IOD and slightly less significant for ENSO in the 1906–2000 period compared to the 2006–2100 period. This study allows us to obtain insight about the predictability of evaporation and hence, may improve the early-warning systems of climate extremes and water resource management.


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