Abnormal weather conditions and extreme weather existed over the Kingdom Saudi Arabia (KSA) through the last decades. The present paper investigates the relationship between the Oceanic Nino Index (ONI) and variability of surface air temperature and precipitation rate over KSA through the period from 1950 to 2015 year. The NCEP/NCAR Reanalysis of monthly data sets of the mean surface air temperature and precipitation rate for the domain of the KSA is used. In addition, El Nino3.4 monthly data through the period (1950-2015) are used. For that period, the data set of the three months moving average of Nino3.4 anomaly, Oceanic Nino index (ONI), is used and analyzed. The time series, anomaly and correlation coefficient techniques are used to analyze the data sets through the present study. The results revealed that the KSA climate parameters, temperature and precipitation rates are controlled by ONI mainly in the autumn and winter seasons.
In the last decades, the King Saudi Arabia (KSA) suffered from extreme weather events. Extreme heat waves and flash floods became more frequent. There are several scientific literatures challenging the climate changes and the extreme temperature and precipitation over KSA [
The NCEP/NCAR Reanalysis project is using a state-of-the-art analysis/forecast system to perform data assimilation, within resolution of 2.5˚ × 2.5˚ degree lat/long grid, using past data from 1948 to 2016. Monthly data sets of the surface air temperature and precipitation rate over the King Saudi Arabia (KSA) for the period from the year 1950 to the year of 2015 is used. This data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA and [
Anomaly methodology has been used to analysis the surface air temperature and precipitation rate over the KSA through the study period (1950-2015). The climatic mean values of the surface air temperature and the precipitation rate are taken through the period (1981-2010). Whereas, the period of climatic mean must be a 30 year mean. In addition, the climatic mean through the period (1981-2010) is the recently climatic mean for climatological studies.
The calculations of seasonal and annual averages of temperature and precipitation for each grid point in the domain of KSA, [9 × 12-degree lat/long grids] done. Seasonally and annual averages for the temperature, precipitation
and El Nino 3.4 have been calculated using the NCEP/NCAR reanalysis monthly data sets along the period 1950-2015. The seasonal averages through the year are calculated; e.g., for the winter season averages of air temperature, precipitation over the KSA have been calculated using the NCEP/NCAR reanalysis monthly data sets for winter season (December + January + February)/3. The climatic mean of the temperature and precipitation rate are taken for the period (1981-2010). The spring, summer, autumn and annual means of surface air temperature, precipitation rate, El Nino 3.4 calculated in the same manner. However, the interactive plotting and analysis NCEP/NCAR software program is used for this analysis.
For a linear correlation analysis of the ONI datasets and the mean surface air temperature and precipitation rate over the KSA during the study period 1950-2015, the methodology of Monte-Carlo has been used, [
For given monthly and seasonally resolved means of surface air temperature and precipitation rate at each grid point correlated with El Nino3.4. Each grid point correlation is t-tested for local significance using [
The NCEP/NCAR reanalysis monthly data of the surface air temperature and precipitation rate (mm/day) for KSA through the period from the year of 1950 to the year of 2015 used. These data sets are analyzed by time series analysis and anomaly method and it became clear that:
1. The annual surface air temperature composite mean value reached to its maximum value (+30˚C) over the southeastern part of KSA. The annual surface temperature composite reached to its minimum value (21˚C) over the northwestern part of KSA during the period of study (1950-2015), see
2. Analysis of the anomaly of surface air temperature composite shows that the southwestern part of KSA has a negative temperature anomaly of (−0.75˚C) less than its normal. Meanwhile, the northern part of KSA has a positive temperature anomaly reached to (+0.75˚C) more than its normal value over the northwestern part of KSA through the study period, see
3. Time series analysis of the annual mean surface air temperature over the KSA clear that there is cooling existed over the KSA through the interval between the year of 1950 and the year of 1980. Through that interval, the mean surface air temperature over the KSA reached to its extreme negative anomaly (−1.3˚C) on the year of 1963. The outstanding warming over the KSA appears after the year of 1997 to the year of 2015. The maximum temperature anomaly over KSA exists on the year of 2010 and it is reached to (+0.98˚C) more than its normal value. However, the climatic mean of surface temperature over the KSA is (+25.21˚C) for the period (1981-2010). The linear trend of annual surface air temperature over the KSA is a positive trend with slope (+0.0159˚C year−1) through the period (1950-2015). It illustrated from
4. Analysis of the annual precipitation rate (mm/day) composite mean for KSA through the period (1950-2015) shows that all of KSA has a precipitation rate less than (1 mm/day) except a small part at the southwestern part of KSA it is more than (1 mm/day) and reached to its maximum value (2 mm/day) through the study period. As it illustrated in
5. It is clear that the northern western part of KSA has a positive anomaly of precipitation rate reached to (+0.2 mm/day). In addition, there exist of a positive anomaly of precipitation rate of (+0.6 mm/day) over only the small part in the southwestern of KSA. Meanwhile, the southeastern part of KSA has a negative anomaly of precipitation rate reached to (−0.2 mm/day), as it shown in
6. Analysis of the time series for annual precipitation rate anomaly revealed that there is an outstanding increase in the precipitation rate over KSA through the period of interval (1950-1963). The precipitation rate anomaly reached to its positive extreme value (+10.8 mm/day) on the year of 1960. After the year of 1973, the annual precipitation rate value oscillates around its normal value until the year of 2008. However, the normal climatic mean of precipitation rate over the KSA is (3.76 mm/day) for the period (1981-2010). After the year, 2008 it is notice that there is continues increase in the precipitation rate rather than its normal value until the year of 2015. It is noticed that the linear trend of annual precipitation rate is a negative trend (−0.084 (mm/day) year−1), through the period (1950-2015), see
The data of Oceanic Niño Index (ONI, three month running mean of ERSST.v4 SST anomalies in the Nino 3.4 region (5˚N-5˚S, 120˚W - 170˚W) had been used and analyzed through the period (1950-2015). This data analyzed by time series method. Events are defined as 3 consecutive overlapping 3-month periods at or above the +0.5 anomaly for warm (El Nino) events and at or below the −0.5 anomaly for cold (La Nina) events. The threshold is further broken down into Weak (with a 0.5 to 0.9 SST anomaly), Moderate (1.0 to 1.4), Strong (1.5 to 1.9) and Very Strong (≥2.0) events. The results are the following:
1)
2)
3) It becomes clear that ONI index is enhancement of monthly El Nino3.4 anomaly data. The ONI index is more liable to identify El Nino, La Nina, and ENSO cases, see
4) There exist of 20 cases of El Nino and 17 cases of La Nina with total frequency of 30% and 26% respectively through 65 years of period (1950-2015) as it is clear in
Phenomena | El Nino | La Nina | ||||||
---|---|---|---|---|---|---|---|---|
Strength | Weak | Moderate | Strong | Very Strong | Weak | Moderate | Strong | |
Number of cases | 8 | 6 | 3 | 3 | 8 | 6 | 3 | |
Frequency | 12% | 9% | 4% | 4% | 12% | 9% | 4% | |
Total number | 20 Cases | 17 Cases | ||||||
Total frequency | 30% | 26% | ||||||
5) El Nino and La Nina cases has the same number and frequency for weak, moderate and strong cases. Whereas, the number and frequency is (8, 12%), (6, 9%) and (3, 4%) weak, moderate and strong cases respectively as shown in
6) There are three cases of very strong El Nino for the years, 1982/1983, 1997/1998 and 2015/2016, see
7) El Nino and La Nina cases together represents of 56% of the study period of 65 years from 1950 to 2015. About 44% of the study period, the central Pacific Ocean is in natural case.
Here we are using the monthly data of the El Nino3.4, ONI, and the surface air temperature and precipitation rate over the KSA to find out the relationship between ONI and weather conditions for KSA during the period (1950-2015). The moving averages through the year has taken for the months as the following abbreviation manner. DJF: December, January, and February months. JFM: January, February and March months. FMA: February, March, and April months. MAM: March, April and May months. AMJ: April, May and June months. MJJ: May, June and July months. JJA: June, July and August months. JAS: July, August and September months. ASO: August, September and October months. SON: September, October and November months. OND: October, November and December months, NDJ: November, December and January months. The Monte-Carlo correlation coefficient technique and Pearson correlation method used to reach this goal. Analysis of these data sets observed that:
1) The distribution of annual surface air temperature over the KSA correlated to El Nino3.4 mainly over the southwestern part of KSA. The significant positive correlation is +0.32 over the southwestern part of KSA through the period of study (1950-2015), see
2) The distribution of annual precipitation rate over the KSA correlated to El Nino3.4 mainly over Jeddah, central and southeastern of KSA. The significant positive correlation coefficient +0.24 over these parts of KSA. Meanwhile, there is a negative correlation over the northwestern part of KSA through the period of study, see
3) For winter season (Dec.-Feb.) there is a positive significant correlation (+0.3) between El Nino3.4 and surface air temperature over the southern part of KSA. Meanwhile, over Jeddah, the correlation is a negative correlation less than −0.2. Moreover, it is clear that there is a positive correlation +0.2 between the precipitation rate and El Nino3.4 over southern part of KSA see
4) For spring season (Mar.-May) there is no significant correlation between El Nino3.4 and surface air temperature over the southern part of KSA. Meanwhile, there is a positive correlation + 0.3 between the precipitation rate and El Nino3.4 over southeastern part of KSA and a negative correlation -0.4 over southwestern part of KSA, see
5) For summer season (Jun.-Aug.) there is a positive significant correlation (+0.3) between El Nino3.4 and surface air temperature over the southwestern part of KSA. Meanwhile, it is clear that there is a negative correlation −0.3 between the precipitation rate and El Nino3.4 over western part of KSA see
6) For autumn season (Sep.-Nov.) there is a positive significant correlation reached to (+0.5) between El Nino3.4 and surface air temperature over the southwestern part of KSA. In addition to that, there is a positive correlation reached to +0.5 between the precipitation rate and El Nino3.4 over central part of KSA see
7) Analysis of three moving average of El Nino anomaly (ONI) shows that there is a significant positive correlation coefficient reached to +0.2 in autumn season between the ONI and surface air temperature over the KSA through the study period (1950-2015) see
8) The maximum correlation coefficient between ONI and precipitation rate is +0.32 over the KSA in autumn season. Moreover +0.23 in winter season. As illustrated in
Corr. Coefficient and Parameters | Winter of KSA | Spring of KSA | Summer of KSA | Autumn of KSA | ||||
---|---|---|---|---|---|---|---|---|
Temp. | Prec. Rate | Temp. | Prec. Rate | Temp. | Prec. Rate | Temp. | Prec. Rate | |
Winter of ONI | 0.092 | 0.223 | 0.073 | −0.070 | 0.136 | 0.110 | 0.002 | −0.046 |
Spring of ONI | 0.108 | 0.341 | −0.081 | 0.037 | 0.180 | 0.095 | 0.157 | 0.105 |
Summer of ONI | −0.009 | 0.170 | −0.237 | 0.062 | 0.069 | 0.008 | 0.193 | 0.277 |
autumn of ONI | 0.052 | 0.130 | −0.167 | 0.079 | 0.018 | 0.012 | 0.191 | 0.266 |
In the present study, we study the relationship between the ONI and surface air temperature and precipitation rate over the KSA through the period (1950-2015). The NCEP/NCAR Reanalysis of monthly mean surface air temperature and precipitation rate data sets for the domain of KSA has been used and analyzed. For that period, the data set of the Oceanic Nino Index (ONI) is used and analyzed. Time series, anomaly methodology, correlation coefficient methods have been used to analysis the datasets. The results revealed that the distribution of annual precipitation rate over KSA correlated to El Nino3.4 mainly over Jeddah, central and southeastern of KSA. For winter season, there is a positive significant correlation (+0.3) between El Nino3.4 and surface air temperature over the southern part of KSA. Meanwhile, over Jeddah, the correlation is a negative correlation less than −0.2. For spring season, there is no significant correlation between El Nino3.4 and surface air temperature over the southern part of KSA. Meanwhile, there is a positive correlation +0.3 between the precipitation rate and El Nino3.4 over southeastern part of KSA and has a negative correlation −0.4 over southwestern part of KSA. For summer season, there is a positive significant correlation (+0.3) between El Nino3.4 and surface air temperature over the southwestern part of KSA. Meanwhile, it is clear that there is a negative correlation −0.3 between the precipitation rate and El Nino3.4 over western part of KSA. For autumn season, there is a positive significant correlation reached to (+0.5) between El Nino3.4 and surface air temperature over the southwestern part of KSA. In addition to that, there is a positive correlation reached to +0.5 between the precipitation rate and El Nino3.4 over central part of KSA. In addition, there is a significant positive correlation coefficient between the ONI and surface air temperature over KSA reached to +0.2 in autumn season. The maximum correlation coefficient between ONI and precipitation rate over KSA is +0.32 in autumn season. Moreover, it reach to +0.23 in winter season. Finally, one can conclude that it is clear that the surface air temperature and precipitation rate over the KSA changes from year to year through the period (1950-2015) and it has influenced in distinct parts by ONI variability mainly in the autumn and winter seasons through the period of study.
It is a pleasure to the authors to thank the Climate Diagnostics Centre for supporting the data used throughout the present study. Plots and images were provided by the NOAA-CIRES Climate Diagnostics Centre, Boulder, Colorado, the USA from their Web site at http://www.cdc.noaa.gov. Also, thanks to the Climate Prediction Centre for supporting the El Nino 3.4 and ONI data that obtained through the website http://www.cpc.ncep.noaa.gov/products/monitoring_data. Thanks, Trenberth, Kevin & National Center for Atmospheric Research Staff (Eds) for supporting ONI, the Climate Data Guide: Nino SST Index ONI, Retrieved from https://climatedataguide.ucar.edu/climate-data/nino-sst-indices-nino-12-3-34-4-oni-and-tni.
Yehia Hafez, (2016) Study on the Relationship between the Oceanic Nino Index and Surface Air Temperature and Precipitation Rate over the Kingdom of Saudi Arabia. Journal of Geoscience and Environment Protection,04,146-162. doi: 10.4236/gep.2016.45015