scholarly journals An analysis of the risk of cocoa moniliasis occurrence in Brazil as the result of climate change

2012 ◽  
Vol 38 (1) ◽  
pp. 30-35 ◽  
Author(s):  
Wanderson Bucker Moraes ◽  
Waldir Cintra de Jesus Júnior ◽  
Leonardo de Azevedo Peixoto ◽  
Willian Bucker Moraes ◽  
Edson Luiz Furtado ◽  
...  
Keyword(s):  
Climate Change ◽  
Potential Risk ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Scenarios ◽  
Intergovernmental Panel ◽  
Climate Conditions ◽  
Third Assessment Report ◽  
Impacts Of Climate Change

The aim of this study was to evaluate the potential risk of moniliasis occurrence and the impacts of climate change on this disease in the coming decades, should this pathogen be introduced in Brazil. To this end, climate favorability maps were devised for the occurrence of moniliasis, both for the present and future time. The future scenarios (A2 and B2) focused on the decades of 2020, 2050 and 2080. These scenarios were obtained from six global climate models (GCMs) made available by the third assessment report of Intergovernmental Panel on Climate Change (IPCC). Currently, there are large areas with favorable climate conditions for moniliasis in Brazil, especially in regions at high risk of introduction of that pathogen. Considering the global warming scenarios provided by the IPCC, the potential risk of moniliasis occurrence in Brazil will be reduced. This decrease is predicted for both future scenarios, but will occur more sharply in scenario A2. However, there will still be areas with favorable climate conditions for the development of the disease, particularly in Brazil's main producing regions. Moreover, pathogen and host alike may undergo alterations due to climate change, which will affect the extent of their impacts on this pathosystem.

scholarly journals An Overview of CMIP5 and the Experiment Design

2012 ◽  
Vol 93 (4) ◽  
pp. 485-498 ◽  
Author(s):  
Karl E. Taylor ◽  
Ronald J. Stouffer ◽  
Gerald A. Meehl
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Experiment Design ◽  
Global Climate Models ◽  
Model Output ◽  
Earth System ◽  
Intergovernmental Panel ◽  
System Models ◽  
Earth System Models

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.

scholarly journals Assessing the Impact of Projected Climate Change on Zoo Visitation in Toronto (Canada)

2016 ◽  
Vol 8 (2) ◽  
pp. 30 ◽  
Author(s):  
Micah J. Hewer ◽  
William A. Gough
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Positive Impact ◽  
Global Climate ◽  
Global Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Local Climate ◽  
The Impact

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.

Going with the trend: forecasting seasonal climate conditions under climate change

2021 ◽  
Author(s):  
Yawen Shao ◽  
Quan J. Wang ◽  
Andrew Schepen ◽  
Dongryeol Ryu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Daily Maximum ◽  
Post Processing ◽  
Seasonal Forecasts ◽  
Climate Conditions ◽  
Seasonal Climate

AbstractFor managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations. Furthermore, this problem is not addressed by existing forecast post-processing methods that are needed to remedy biases and uncertainties in model forecasts. The inability of the forecasts to reproduce the trends severely undermines user confidence in the forecasts. In our previous work, we proposed a new statistical post-processing model that counteracted departures in trends of model forecasts from observations. Here, we further extend this trend-aware forecast post-processing methodology to carefully treat the trend uncertainty associated with the sampling variability due to limited data records. This new methodology is validated on forecasting seasonal averages of daily maximum and minimum temperatures for Australia based on the SEAS5 climate model of the European Centre for Medium-Range Weather Forecasts. The resulting post-processed forecasts are shown to have proper trends embedded, leading to greater accuracy in regions with significant trends. The application of this new forecast post-processing is expected to boost user confidence in seasonal climate forecasts.

scholarly journals Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Zhenchun Hao ◽  
Qin Ju ◽  
Weijuan Jiang ◽  
Changjun Zhu
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Surface Air Temperature ◽  
Global Climate Models ◽  
The Tibetan Plateau ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Ipcc Ar4

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least.

scholarly journals Using Integrated Hydrological Models to Assess the Impacts of Climate Change on Discharges and Extreme Flood Events in the Upper Yangtze River Basin

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 299
Author(s):  
Yanjuan Wu ◽  
Gang Luo ◽  
Cai Chen ◽  
Zheng Duan ◽  
Chao Gao
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Models ◽  
Hydrological Models ◽  
Flood Events ◽  
Temperature And Precipitation ◽  
Extreme Flood ◽  
Impacts Of Climate Change

Amongst the impacts of climate change, those arising from extreme hydrological events are expected to cause the greatest impacts. To assess the changes in temperature and precipitation and their impacts on the discharge in the upper Yangtze Basin from pre-industrial to the end of 21st century, four hydrological models were integrated with four global climate models. Results indicated that mean discharge was simulated to increase slightly for all hydrological models forced by all global climate models during 1771–1800 and 1871–1900 relative to the 1971–2000 reference period, whereas the change directions in mean discharge were not consistent among the four global climate models during 2070–2099, with increases from HadGEM2-ES and MIROC5, and decreases from GFDL-ESM2M and IPSL-CM5A-LR. Additionally, our results indicated that decreases in precipitation may always result in the decrease in mean discharge, but increases in precipitation did not always lead to increases in discharge due to high temperature rise. The changes in extreme flood events with different return intervals were also explored. These extreme events were projected to become more intense and frequent in the future, which could have potential devastating impacts on the society and ecosystem in this region.

scholarly journals Long-Term Rainfall Trends and Future Projections over Xijiang River Basin, China

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Muhammad Touseef ◽  
Lihua Chen ◽  
Kaipeng Yang ◽  
Yunyao Chen
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Scenarios ◽  
Emission Scenarios ◽  
Xijiang River ◽  
The Xijiang River

Precipitation trend detection is vital for water resources development and decision support systems. This study predicts the climate change impacts on long-term precipitation trends. It deals with the analysis of observed historical (1960–2010) and arithmetic mean method in assembling precipitation from CMIP5 Global Climate Models (GCMs) datasets for a future period (2020–2099) under four emission scenarios. Daily precipitation data of 32 weather stations in the Xijiang River Basin were provided by National Meteorological Information Centre (NMIC) of the China Meteorological Administration (CMA) and Global Climate Models (GCMs) with all four emission scenarios statistically downscaled using Bias Correction Special Disaggregation (BCSD) and applied for bias correction via Climate Change Toolkit (CCT). Nonparametric Mann–Kendall test was applied for statistical significance trend analysis while the magnitude of the trends was determined by nonparametric Sen’s estimator method on a monthly scale to detect monotonic trends in annual and seasonal precipitation time series. The results showed a declined trend was observed for the past 50 years over the basin with negative values of MK test (Z) and Sen’s slope Q. Historical GCMs precipitation detected decreasing trends except for NoerESM1-M which observed slightly increasing trends. The results are further validated by historical precipitation recorded by the Climate Research Unit (CRU-TS-3.1). The future scenarios will likely be positive trends for annual rainfall. Significant positive trends were observed in monsoon and winter seasons while premonsoon and postmonsoon seasons will likely be slightly downward trends. The 2040s will likely observe the lowest increase of 6.6% while the 2050s will observe the highest increase of 11.5% over the 21st century under future scenarios. However, due to the uncertainties in CMIP5, the future precipitation projections should be interpreted with caution. Thus, it could be concluded that the trend of change in precipitation around the Xijiang River Basin is on the increase under future scenarios. The results can be valuable to water resources and agriculture management policies, as well as the approach for managing floods and droughts under the perspective of global climate change.

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