Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Impacts of climate change on heat waves in northern coast of Persian Gulf

Authors
gelaleh molodi
asadolah khorani
abbas moradi
10.18869/acadpub.jsaeh.3.1.1
Abstract
Climate change is one of the most significant threats facing the world today. One of the most important consequences of climate change is increasing frequency of climate hazards, mainly heat waves. This phenomena has a robust impacts on human and other ecosystems. The aim of this study is investigating changes of heat waves in historical (1980-2014) and projected (2040-2074) data in northern cost of Persian Gulf.



The focus here is on Mean daily maximum temperature and Fujibe index to extract heat waves. For this purpose 6 weather stations locating in north coast of Persian Gulf, Iran, are used (table 1).



Table1: weather stations





Station


Latitude


Longitude


Elevation(m)




Abadan


30° 22' N


48° 20' E


6.6




Boushehr


28° 55' N


50° 55' E


9




Bandarabbas


27° 15' N


56° 15' E


9.8




Bandarlengeh


26° 35' N


54° 58' E


22.7




Kish


26° 54' N


53° 54' E


30









In addition, 4 model ensemble outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are used to project future occurrence and severity of heat waves (2040 to 2070), under Representative Concentration Pathways 8.5 (RCP8.5), adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5) (table 2).



Table2: List of the AR5 CMIP5 Used Models





Model


Modeling Cener


Country




CanESM2


Canadian Earth System Model


Canada




MPI-ESM-MR


Max-Planck-Institut für Meteorologie


Germany




CSIRO-Mk3-6-0


Commonwealth Scientific and Industrial Research Organization


Australia




CMCC-CESM


CMCC Carbon Earth System Model


Italy







The output of models is downscaled using artificial neural network method (ANN). A feed-forward network of multi-layer perceptron with an input layer, a hidden layer and an output layer is used for this purpose. 73 percent (1980 – 2000) of the data is used for training and 27 percent (2000-2005) for testing ANN models. Root Mean Square Error (RMSE) is used as an indicator of the accuracy of Models.

RMSE=

Here is the outputs of ANN models (downscaled data) and is the observation data.

Fujibe et all (2007) used an index based on Normalized Thermal Deviation (NTD) for extracting long-term changes of temperature extremes and day to day variability using following equations:



Where N is the number of days in the summation except missing values. Then nine-day running average was applied three times in order to filter out day-to-day irregularities.

=(i,j,n)=T(i,j,n)-T(I,j)

The departure from the climatic mean is given by



=



If NTD >2 and at least lasts for 2 days it determine as a heat wave.



Results

Table 3 shows the results of downscaling selected GCM models.








nodes


RMSE


Average RMSE







Sigmoid function


Linear function


Abadan


Bushehr


Bandarabbas


Bandar-e-Lengeh


Kish




CanESM2


5


1


9.6


6.1


4.85


4.7


4.5


5.97




MPI-ESM-MR




5


1


9.3


7.1


3.9


5


4.3


5.9




CSIRO-MK3-6-0


15


1


8.8


5.6


3.6


3.4


3.6


5




CMCC-CESM


10


1


9.2


5.8


3.9


4.7


3.9


5.5







Table 4 compares the frequency of heat waves for GCMs and historical data.








CanESM2


MPI-ESM-MR


CSIRO-Mk3-6-0


CMCC-CESM


Historical data




Abadan


434


401


448


387


430




Bushehr


376


423


420


406


407




Bandarabbas


441


405


457


382


410




Bandar-e-Lengeh


380


414


388


401


400




Kish


421


442


415


442


399





For historical data, heat waves are more frequent in Abadan station than other stations. There is an increasing trend in the occurrence of heat waves in historical data and monthly frequency of heat waves show the highest amounts for summer.

For both historical and future data 2 days listening heat waves are more frequent.



Table 5 shows seasonal changes of heat waves for historical data and GCMs.








season


The ratio of heat waves from total historical data (percent)


The ratio of heat waves from total projected data (percent)




Abadan


Spring


30.43


24.02




Summer


29.19


27.87




Autumn


17.39


22.61




Winter


22.98


25.48




Bushehr


Spring


21.42


24.23




Summer


25


26.21




Autumn


28.57


24.82




Winter


24


25.32




Bandarabbas


Spring


21.73


24.7




Summer


26.81


27.01




Autumn


25.81


25.17




Winter


24.1


24.63




Bandar-e-Lengeh


Spring


23.55


23.74




Summer


23.33


29.82




Autumn


23.74


25.81




Winter


25.17


20.8




Kish


Spring


24.27


24.8




Summer


25.53


28.32




Autumn


23.35


25.21




Winter


23.1


23.8







In recent years the frequency of heat waves is increasing in all studied stations. Coincide with Russia and Europe, the highest amounts of heat waves is occurred in 2010 in northern coast of Persian Gulf and this is adopted Esmaeilnezhad et all (2013), Gavidel (2015) and Azizi (2011).
Keywords
Climate Change
RCP8.5
Heat waves
Persian Gulf
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