scholarly journals Rapid decline and shift in the future distribution predicted for the endangered Sokoke Scops Owl Otus ireneae due to climate change

2012 ◽  
Vol 23 (2) ◽  
pp. 247-258 ◽  
Author(s):  
ARA MONADJEM ◽  
MUNIR Z. VIRANI ◽  
COLIN JACKSON ◽  
APRIL RESIDE
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Conservation Status ◽  
Circulation Model ◽  
Rapid Decline ◽  
Complete Disappearance ◽  
Forest Fragments ◽  
Close Monitoring ◽  
Niche Modelling ◽  
The Future

SummaryClimate change is predicted to have serious impacts on the conservation status of numerous species of birds, particularly low-density, range-restricted species occupying narrow habitats. One such species is the globally “Endangered” Sokoke Scops Owl Otus ireneae that currently survives in just two or three small pockets of forest in coastal Kenya and north-eastern Tanzania. We assessed the potential impact of changes in future climate on this species using predictive niche modelling. Distributional data were obtained from various published and unpublished sources, and field surveys. Maximum Entropy (Maxent) was used to model the current distribution of Sokoke Scops Owl. A general circulation model was used to predict the distribution of this species in 2080. This scenario predicts a southward shift in the future distribution of this species in Kenya and a complete disappearance from the Usambara mountains in Tanzania, with a concomitant 64% reduction in areas of high environmental suitability. Considering the isolated nature of the forest fragments in which this owl survives and the sea of inhospitable human-modified habitat which surrounds these fragments, the future conservation prospects of this species are bleak. Close monitoring of the species is strongly recommended and potential conservation interventions are discussed.

scholarly journals Future Changes in Drought Characteristics under Extreme Climate Change over South Korea

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Joo-Heon Lee ◽  
Hyun-Han Kwon ◽  
Ho-Won Jang ◽  
Tae-Woong Kim
Keyword(s):  
Climate Change ◽  
South Korea ◽  
General Circulation ◽  
Standardized Precipitation Index ◽  
Low Frequency ◽  
Circulation Model ◽  
Significance Test ◽  
Precipitation Index ◽  
Intergovernmental Panel ◽  
The Future

This study attempts to analyze several drought features in South Korea from various perspectives using a three-month standard precipitation index. In particular, this study aims to evaluate changes in spatial distribution in terms of frequency and severity of droughts in the future due to climate change, using IPCC (intergovernmental panel on climate change) GCM (general circulation model) simulations. First, the Mann-Kendall method was adopted to identify drought trends at the five major watersheds. The simulated temporal evolution of SPI (standardized precipitation index) during the winter showed significant drying trends in most parts of the watersheds, while the simulated SPI during the spring showed a somewhat different feature in the GCMs. Second, this study explored the low-frequency patterns associated with drought by comparing global wavelet power, with significance test. Future spectra decreased in the fractional variance attributed to a reduction in the interannual band from 2 to 8 years. Finally, the changes in the frequency and the severity under climate change were evaluated through the drought spell analyses. Overall features of drought conditions in the future showed a tendency to increase (about 6%) in frequency and severity of droughts during the dry season (i.e., from October to May) under climate change.

Evaluation of climate change impacts and adaptation strategies for maize cultivation in the Himalayan foothills of India

2015 ◽  
Vol 6 (3) ◽  
pp. 596-614 ◽  
Author(s):  
Proloy Deb ◽  
Anthony S. Kiem ◽  
Mukand S. Babel ◽  
Sang Thi Chu ◽  
Biplab Chakma
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Circulation Model ◽  
Maize Yield ◽  
Future Climate ◽  
Future Climate Change ◽  
Daily Maximum ◽  
Study Region ◽  
Supplementary Irrigation ◽  
The Future

This study evaluates the impacts of climate change on rainfed maize (Zea mays) yield and evaluates different agro-adaptation measures to counteract its negative impacts at Sikkim, a Himalayan state of India. Future climate scenarios for the 10 years centered on 2025, 2055 and 2085 were obtained by downscaling the outputs of the HadCM3 General Circulation Model (GCM) under for A2 and B2 emission scenarios. HadCM3 was chosen after assessing the performance analysis of six GCMs for the study region. The daily maximum and minimum temperatures are projected to rise in the future and precipitation is projected to decrease (by 1.7 to 22.6% relative to the 1991–2000 baseline) depending on the time period and scenarios considered. The crop simulation model CERES-Maize was then used to simulate maize yield under future climate change for the future time windows. Simulation results show that climate change could reduce maize productivity by 10.7–18.2%, compared to baseline yield, under A2 and 6.4–12.4% under B2 scenarios. However, the results also indicate that the projected decline in maize yield could be offset by early planting of seeds, lowering the farm yard manure application rate, introducing supplementary irrigation and shifting to heat tolerant varieties of maize.

scholarly journals Investigating the Impact of Climate Change on Future Runoff of River Satluj

2016 ◽  
Vol 8 (1) ◽  
pp. 10-21
Author(s):  
Narayan P Gautam ◽  
Manohar Arora ◽  
N.K. Goel ◽  
A.R.S. Kumar
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
General Circulation ◽  
Circulation Model ◽  
Climate Change Scenarios ◽  
Impact Of Climate Change ◽  
Basin Scale ◽  
The Future ◽  
Future Climatic Condition ◽  
The Impact

Climate change has been emerging as one of the challenges in the global environment. Information of predicted climatic changes in basin scale is highly useful to know the future climatic condition in the basin that ultimately becomes helpful to carry out planning and management of the water resources available in the basin. Climatic scenario is a plausible and often simplified representation of the future climate, based on an internally consistent set of climatological relationships that has been constructed for explicit use in investigating the potential consequences of anthropogenic climate change. This study based on statistical downscaling, provide good example focusing on predicting the rainfall and runoff patterns, using the coarse general circulation model (GCM) outputs. The outputs of the GCMs are utilized to study the impact of climate change on water resources. The present study has been taken up to identify the climate change scenarios for Satluj river basin, India.Journal of Hydrology and Meteorology, Vol. 8(1) p.10-21

scholarly journals Impact of climate change on drought in the Daklak province

2014 ◽  
Vol 17 (3) ◽  
pp. 5-11
Author(s):  
Khoi Nguyen Dao ◽  
Quang Nguyen Xuan Chau
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Standardized Precipitation Index ◽  
Circulation Model ◽  
Meteorological Drought ◽  
Impact Of Climate Change ◽  
The Future ◽  
Delta Change ◽  
The Standardized Precipitation Index ◽  
The Impact

The main objective of this study was to evaluate the impact of climate change on the meteorological drought in the Daklak province. In this study, the meteorological drought was calculated using the Standardized Precipitation Index (SPI).From this result, two scensrios fot the precipitation VA1B and B1 were downscaled, from the outputs of 4 GCMs (General Circulation Model): CGCM3.1 (T63), CM2.0, CM2.1, and HadCM3 using the simple downscaling method (delta change method). The impacts of climate change on the droughts were assessed by comparing the present (1980- 2009) and the future droughts (2010-2039, 2040-2069, and 2070-2099).Results of the study suggested that the future temperature would increase by 0.9-2.8ºC and the future precipitation would decrease by 0.4-4.7% for both A1B and B1 scenarios. Under the future climate scenarios, the frequency and severity of extreme drought would increase. The results obtained in this study could be useful for planning and managing water resources at this region.

The Arctic cryosphere in the Mid-Pliocene and the future

2008 ◽  
Vol 367 (1886) ◽  
pp. 49-67 ◽  
Author(s):  
Daniel J Lunt ◽  
Alan M Haywood ◽  
Gavin L Foster ◽  
Emma J Stone
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Circulation Model ◽  
Future Climate ◽  
Arctic Climate ◽  
The Arctic ◽  
Future Climate Change ◽  
The Future

The Mid-Pliocene ( ca 3 Myr ago) was a relatively warm period, with increased atmospheric CO 2 relative to pre-industrial. It has therefore been highlighted as a possible palaeo-analogue for the future. However, changed vegetation patterns, orography and smaller ice sheets also influenced the Mid-Pliocene climate. Here, using a general circulation model and ice-sheet model, we determine the relative contribution of vegetation and soils, orography and ice, and CO 2 to the Mid-Pliocene Arctic climate and cryosphere. Compared with pre-industrial, we find that increased Mid-Pliocene CO 2 contributes 35 per cent, lower orography and ice-sheet feedbacks contribute 42 per cent, and vegetation changes contribute 23 per cent of Arctic temperature change. The simulated Mid-Pliocene Greenland ice sheet is substantially smaller than that of modern, mostly due to the higher CO 2 . However, our simulations of future climate change indicate that the same increase in CO 2 is not sufficient to melt the modern ice sheet substantially. We conclude that, although the Mid-Pliocene resembles the future in some respects, care must be taken when interpreting it as an exact analogue due to vegetation and ice-sheet feedbacks. These act to intensify Mid-Pliocene Arctic climate change, and act on a longer time scale than the century scale usually addressed in future climate prediction.

QUANTITATIVE ESTIMATION OF THE IMPACT OF CLIMATE CHANGE ON CROP EVAPOTRANSPIRATION AND YIELD IN THE CENTRAL REGION OF INDIA

2021 ◽  
pp. 83-89
Author(s):  
A. BALVANSHI ◽  
◽  
H. L. TIWARI ◽  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Quantitative Estimation ◽  
Circulation Model ◽  
Future Climate Change ◽  
Crop Evapotranspiration ◽  
Yield Data ◽  
Aquacrop Model ◽  
The Future ◽  
The Impact

The present work focuses on estimation of future evapotranspiration of paddy, maize, soybean and assessment of yields of these crops under RCP scenarios 2.6, 4.5, and 8.5 for years 1997-2099 using FAO Cropwat and AquaCrop yield simulating models for the Sehore district, in central state of India. Statistically downscaled General Circulation Model CanESM2 data were used as input to Cropwat and AquaCrop tools for generation of future crop evapotranspiration and crop yield data. The AquaCrop yield model was first checked for its suitability and accuracy in prediction of yield for years 1997-2010. The future scenario RCP 8.5 shows the highest reduction in the yield of paddy (-8.5%), maize (-4.52%), and soybean (-3.93%) during the future period. It was concluded that the FAO AquaCrop model can be applied to many other crops as well as in the other regions to formulate proper cropping strategies that will help to decrease the risks due to future climate change.

“Modes of Variability” and Climate Change

2009 ◽  
Vol 22 (10) ◽  
pp. 2639-2658 ◽  
Author(s):  
Grant Branstator ◽  
Frank Selten
Keyword(s):  
Climate Change ◽  
Stochastic Model ◽  
General Circulation ◽  
Climate Changes ◽  
Circulation Model ◽  
Meridional Wind ◽  
Model Atmosphere ◽  
Linear Pattern ◽  
Modes Of Variability ◽  
Mean State

Abstract A 62-member ensemble of coupled general circulation model (GCM) simulations of the years 1940–2080, including the effects of projected greenhouse gas increases, is examined. The focus is on the interplay between the trend in the Northern Hemisphere December–February (DJF) mean state and the intrinsic modes of variability of the model atmosphere as given by the upper-tropospheric meridional wind. The structure of the leading modes and the trend are similar. Two commonly proposed explanations for this similarity are considered. Several results suggest that this similarity in most respects is consistent with an explanation involving patterns that result from the model dynamics being well approximated by a linear system. Specifically, the leading intrinsic modes are similar to the leading modes of a stochastic model linearized about the mean state of the GCM atmosphere, trends in GCM tropical precipitation appear to excite the leading linear pattern, and the probability density functions (PDFs) of prominent circulation patterns are quasi-Gaussian. There are, on the other hand, some subtle indications that an explanation for the similarity involving preferred states (which necessarily result from nonlinear influences) has some relevance. For example, though unimodal, PDFs of prominent patterns have departures from Gaussianity that are suggestive of a mixture of two Gaussian components. And there is some evidence of a shift in probability between the two components as the climate changes. Interestingly, contrary to the most prominent theory of the influence of nonlinearly produced preferred states on climate change, the centroids of the components also change as the climate changes. This modification of the system’s preferred states corresponds to a change in the structure of its dominant patterns. The change in pattern structure is reproduced by the linear stochastic model when its basic state is modified to correspond to the trend in the general circulation model’s mean atmospheric state. Thus, there is a two-way interaction between the trend and the modes of variability.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

scholarly journals Identifying suitable general circulation model for future building cooling energy analysis

2019 ◽  
Vol 111 ◽  
pp. 06056
Author(s):  
Kuo-Tsang Huang ◽  
Yu-Teng Weng ◽  
Ruey-Lung Hwang
Keyword(s):  
General Circulation ◽  
Meteorological Data ◽  
Circulation Model ◽  
Building Energy ◽  
Building Simulation ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Global Circulation Models ◽  
The Future ◽  
Energy Use Intensity

These future building energy studies mainly stem from hourly based dynamic building simulation results with the future weather data. The reliability of the future building energy forecast heavily relies on the accuracy of these future weather data. The global circulation models (GCMs) provided by IPCC are the major sources for constructing future weather data. However, there are uncertainties existed among them even with the same climate change scenarios. There is a need to develop a method on how to select the suitable GCM for local application. This research firstly adopted principal component analysis (PCA) method in choosing the suitable GCM for application in Taiwan, and secondly the Taiwanese hourly future meteorological data sets were constructed based on the selected GCM by morphing method. Thirdly, the future cooling energy consumption of an actual office building in the near (2011-2040), the mid (2041-2070), and the far future (2071-2100), were analysed. The results show that NorESM1-M GCM has the lowest root mean square error (RMSE) as opposed to the other GCMs, and was identified as the suitable GCM for further future climate generation processing. The building simulation against the future weather datasets revealed that the average cooling energy use intensity (EUIc) in Taipei will be increased by 12%, 17%, and 34% in the 2020s, 2050s, and 2080s, respectively, as compared to the current climate.

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