SciFed Journal of Global Warming Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria

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1 Abiodun Daniel Olabode,, 2017, 1:3 SciFed Journal of Global Warming Research Article Open Access Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria * Abiodun Daniel Olabode * Department of Geography and Planning Sciences, Adekunle Ajasin University Akungba-Akoko, Ondo, Nigeria Abstract The current trend of global warming has been on significant increase over the years. This study considered impact-assessment of cloud cover in relation to dynamic surface temperature over considerable periods between 1980 and 2014 in Nigeria. Data on cloud cover were obtained from the NIMET, Ikeja, Lagos; while data on surface temperature were collected from FAOSTAT online data domain. Both data indicate the readings of maximum dataset for the periods under study. A line graph analysis was employed to identify the trend of the temperature and the cloud cover, while correlation analysis determined relationships between the annual cloud cover and temperature. Regression model was employed to identify the influence of cloud cover on the annual temperature. The study revealed that; cloud cover has downward trend with recorded maximum data of and in 1980 and 2014 respectively indicating reduced cloud cover, existing relationships between the cloud cover and temperature over the years was recorded, and correlation coefficient of 0.79 signifies 79% influence of cloud cover over the temperature of this area, while the remaining 21% could be attributed to other factors in the study area. The examined relationships of annual temperature and cloud cover established that surface temperature is high when cloud cover low. It is however adequate to sensitize the public on heat related issues based on temperature dynamism and its impact on human life and the environment in general. Keywords Cloud; Temperature; Nigeria; Cloud Cover; Global Warming Introduction Over the years, the trend of global warming has been on significant increase all over the world. Many researchers have traced the major cause of global warming to increase in surface temperature. Authors like Odjugo [1] and UNDP [2] have predicted a temperature rise of to C for Nigeria in the 21st century. It could be further adjudged based on severe warming experienced in the world today where major influence of the temperature increase is engendered by the warming of the world regions. In a much clearer way, Yue and Hashino [3] explained that regional variations can be much wider, and considerable spatial and temporal variations may exist between climatically different regions. The status of any cloud cover plays significant role in either increasing or decreasing warming of a particular region. In the developing countries, for instance, the impact of temperature increase is highly noticeable dayby-day both on human life and the environment in general. Understanding major changes through varying atmospheric cloud cover forms a significant trend in today s climate. This trend, for some years back, establishes the current situation of temperature and also critical to the general climate system. *Corresponding author: Abiodun Daniel Olabode, Afilation. Olabiodun4real@gmail.com Tel: Received October 4, 2017; Accepted October 6, 2017; Published October 19, 2017 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. Copyright: 2017 Abiodun Daniel Olabode. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. page 1 of 8

2 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. Nigeria is one of the developing nations of the world. Predicting her climate could be understood by focusing the cloud cover and its feedback effects. For instance, The Wikipedia [4] established that cloud feedback plays between cloudiness and surface air temperature in which a change in radiative forcing perturbs the surface air temperature, leading to a change in clouds, which could then amplify or diminish the initial temperature perturbation. Not only this, Cess, et al. [5] and Stocker, et al. [6] noted that cloud cover determines climate s sensitivity to change. It is noteworthy that both clouds and the atmosphere have reciprocating effect. That is, cloud could prevent radiation that usually triggers hot atmosphere and as well give a considerable cool weather. As a result of the dual roles, it should be established that a slight change in cloud cover could lead to a large impact on the climate. In Nigeria, Dammo et al. [7] opined that there was significant increase (positive trend) in temperature in major cities. In a similar trend, International Panel on Climate Change [8] asserted that cloud cover thus plays an important role in the energy balance of the atmosphere and a variation of it is a consequence of and to the climate change expected in recent years. Based on the fact that cloud cover is significant to general operation of climate system, its study will further help in environmental monitoring and control strategies. This is more so in a country like Nigeria, where not many works have been done on the subject of cloud-temperature relationships. This study therefore focused on impact-assessment of cloud cover in relation to surface temperature dynamics over the considerable periods in the nation. 2. Literature Review 2.1 Climate Change and Cloud Cover Manabe and Wetherald and Schneider have noted that cloud cover can exert a large influence upon climate. This assertion is supported with situation where cloud cover reflects a large fraction of incoming solar radiation, thereby decreasing the solar energy absorbed by the earth-atmosphere system. In another perspective, cloud cover lowers the temperature of the effective source for the outgoing terrestrial radiation and decreases the loss of energy from the system. Since the magnitudes of these two opposing effects often differ substantially from each other, the change in the distribution of cloud cover can have a large effect upon the sensitivity of climate. This scenario have formed a lead into many works of researchers who conducted their researches on the influence of the cloud feedback process upon the sensitivity of climate. For instance, the studies of Cess [9], Hartmann and Short [10] and Ohring and Clapp [11] established the influence of cloud cover upon the radiation balance of the earth-atmosphere system based upon the data from meteorological satellites. Also, Wetherald and Manabe [12] and Hansen et al. [13] and Hansen et al. [14] examined how the interaction between cloud cover and radiative transfer affects the sensitivity of a model climate. Wetherald and Manabe [12] equally noted that the cloud feedback process in their model has a very little effect upon the sensitivity of climate to a forcing in such a way that a change of solar constant or that of atmospheric carbon dioxide. On the other hand, the study of Hansen et al. [14] indicates that it markedly enhances the surface warming orchestrated by the doubling of atmospheric carbon dioxide. 2.2 Effect of Cloud Feedback on Temperature Nicole [15] have reported that clouds emit infrared radiation back to the surface, and so exert a warming effect. Clouds reflect sunlight and emit infrared radiation to space, and so exert a cooling effect. As observed by Hartmann et.al. [16] cloud representations vary among global climate models, and small changes in cloud cover have a large impact on the climate. According to Cess et al. [5], differences in planetary boundary layer cloud modeling schemes can lead to large differences in derived values of climate sensitivity. A model that decreases boundary layer clouds in response to global warming has a climate sensitivity twice that of a model that does not include this feedback [17]. However, satellite data show that cloud optical thickness actually increases with increasing temperature [18]. Whether the net effect is warming or cooling depends on details such as the type and altitude of the cloud; details that are difficult to represent in climate models. In addition to how clouds themselves will respond to increased temperatures, other feedbacks affect clouds properties and formation. The amount and vertical distribution of water vapor is closely linked to the formation of clouds. Ice crystals have been shown to largely influence the amount of water vapor. Donner et al. [19] opined that water vapor in the subtropical upper troposphere has been linked to the convection of water vapor and ice. Changes in subtropical humidity could provide a negative feedback that decreases the amount page 2 of 8

3 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. of water vapor which in turn would act to mediate global climate transitions [20]. Fowler [21] is of the opinion that the albedo of increased cloudiness cools the climate, resulting in a negative feedback; while the reflection of infrared radiation by clouds warms the climate, resulting in a positive feedback. This feedback would partially cancel the increased surface warming due to the cloudiness. This negative feedback has less effect than the positive feedback. As put forward by Wetherald and Manabe [22], the upper atmosphere cancels negative feedback that causes cooling, and therefore the increase of CO 2 is actually exacerbating the positive feedback as more CO 2 enters the system. 3. Materials and Methods This study employed secondary data-set. Data on cloud cover and temperature between years 1980 and Data on cloud cover were obtained from NIMET, Ikeja; while data on surface temperature were obtained from FAOSTAT online data domain. Both data indicate the readings of maximum data-set for the periods under study. A line graph analysis was employed to identify the trend of the temperature and the cloud cover. Correlation analysis determined relationships between the annual cloud cover and temperature. Regression model was employed to identify the influence of cloud cover on temperature. Tables and graphs were generally used for data presentation. 4. Results and Discussions 4.1 Annual Surface Temperature and Cloud Cover During 1980 to 2014 Annual data on cloud cover and maximum temperature for this study were presented in Table 1. The data on cloud cover was measured in Octal within the period of thirty-five years (1980 to 2014). The data reflect periodic changes which necessitates the studies to understand the influence of the examined variables (cloud cover and temperature). In the study, the cloud cover was recorded with and in 1980 and 2014 respectively. This recorded data indicates reduced cloud cover over the years. However, the pattern of recorded surface temperature rises. The initial recorded temperature of C in 1980 was observed, while recent temperature in 2014 is C. This observation confirms that there is increase level of temperature with reduced cloud cover in the recent times. For instance, Figure 1 portraits temperature rise, while Figure 2 demonstrates the downward trend of cloud cover in this study. This observed annual trend of temperature was influenced by the reduced level of cloud cover experienced within the study area. This was particularly noted when a sharp rise in temperature was recorded between 2010 and However, the study explains stable trend of temperature in 2014 with downward trend of cloud cover in Figures 1 and 2. Table 1: Annual Cloud Cover and Surface Temperature Between 1980 and 2014 Serial No Year Annual Cloud Cover (octal) Annual Maximum Temperature ( O C)C) , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,62 page 3 of 8

4 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. Figure 1: Trend of Temperature During Year 1980 and 2014 observation, the measure of relationships of 0.28, between cloud cover and the observed periods indicate not only weak relationship (0.280) but as well presenting the relationships to be less significant. This implies that cloud cover varies with the period under consideration. However, the study shows existing positive relationship (0.358) of cloud cover and temperature over the years. Table 2: Correlation Matrix of Cloud Cover and Temperature Variable Year Cloud cover Temperature Year ** Cloud cover. 1 * Temperature 1 Figure 2: Trend of Cloud Cover During Year 1980 and Cloud - Temperature Relationship in Nigeria This study confirms the existing relationship of the annual influence of cloud cover and the temperature in Table 2. As put forward by Manabe and Wetherald and Schneider, cloud cover can exert a large influence upon climate. The level of cloud cover in this study is essentially responsible for the amount of atmospheric temperature received on earth. It was revealed in the correlation matrix where two out of three pairs of correlation were significant. This study further revealed that the periods under consideration are not only correlated with the temperature increase but also significant at 0.05 level of significance. Also, the positive correlation (0.576) recorded implies increase in temperature as the years emerge. In another This observed relationship between the cloud cover and temperature established the fact that there is general reduction in the impact of cloud cover. It is evident that Nigeria is experiencing more heat in the recent years based on reduced impact of cloud cover. Not only this, the study identified that the influence of cloud cover is significant based on the impact of amount of solar radiation received on earth surface. This study confirmed the submissions of Cess [9], Hartmann and Short [10] and Ohring and Clapp [11]. Their studies established the influence of cloud cover upon the radiation balance of the earth-atmosphere system based upon the data from meteorological satellites. In order to examine basic impact of cloud cover on temperature of the study location, this study considered four levels of cloud cover that include clear, scattered, broken and overcast. These observed cloud covers were determined in Table 3 based on less or equal to 0-1/10 for clear; 1/10 th -5/10 th for scattered; 5/10 th -9/10 th for broken and 9/10 th -10/10 th for overcast. Figure 3: Trend Showing Cloud-Temperature Relationship page 4 of 8

5 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. Table 3: Categories of Cloud cover in Nigeria Source: NIMET, FAOSTAT and Author s Computations (2016) Year Cloud Cover (Octal) Temperature ( o C) o C) Clear Scattered 1/10th-5/10th Broken 5/10th-9/10th Overcast 9/10th-10/10th ,51 824,3 4121,5 7418, ,32 768, , ,32 783, , ,62 626,3 3131,5 5636, ,21 724, , ,87 758,9 3794,5 6830, ,09 710, , ,16 685,1 3425,5 6165, ,79 746, , ,98 720,1 3600,5 6480, ,51 757,5 3787,5 6817, ,65 745, , ,36 625,1 3125,5 5625, ,13 702,3 3511,5 6320, ,71 702,5 3512,5 6322, ,18 771, , ,39 791, , ,94 686,3 3431,5 6176, ,64 646, , ,92 762,9 3814,5 6866, ,16 731, , ,92 691, , ,72 714,7 3573,5 6432, ,55 720,1 3600,5 6480, ,1 764,1 3820,5 6876, ,78 688, , ,86 754,5 3772,5 6790, ,12 755,5 3777,5 6799, ,62 747,1 3735,5 6723, ,25 751,9 3759,5 6767, ,24 806, , ,56 790, , ,59 795, , ,24 840, , ,62 777,9 3889,5 7001, Source: NIMET, FAOSTAT and Author s Computations (2016) page 5 of 8

6 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. Figure 3 illustrates trend of the cloud cover and annual maximum temperature under the study periods. The observed trend depicts increasing rise of both cloud cover and temperature. However, there was a different observation in the trend in 2013 where both the cloud and temperature strive. It is equally noted that a sharp rise in temperature occurred in 2014 with the livelihood of its continuous increase in the subsequent years. This is evident in the observed reduced cloud cover that necessitates the temperature rise. The related study of Ayoade [23] has revealed that the current change pattern which is marked by global warming with attendant consequences is of concern for three main reasons, which bothers on constantly increasing temperatures in 10,000 years (as have been known to be associated with natural climate changes). Secondly, there is a strong correlation between current global warming and increases in the atmospheric concentration of greenhouse gases, and the third hinges on the uncomfortable realization that climate change is exacerbated by humanly induced activities. 4.3 Influence of Cloud Cover on Surface Temperature Level of cloud cover is reflected in Figure 4. These levels of cloud cover are superimposed on each other where the clear cloud forms the base-cloud and the overcast is identified as top-cloud. More essentially, it should be noted that the typical nature of prevailing cloud Figure 4: Cloud Cover Model Generated from Data covers in Nigeria are diverse as represented in Figure 4. The clear cloud has been identify with a light display, following by the scattered and broken cloud. However, the overcast cloud cover at the top of the chart signifies a thick coverage. The consideration here ensures how does earth temperature relate to cloud cover of any particular level. The intensity of solar radiation received on earth is majorly a function of prevailing cloud cover. Regression model was employed to identify the influence and strength of cloud cover on temperature. The calculated values of the regression analysis are presented in Table 4. This contains the dependent variable (temperature) and independent variables (cloud cover). The decision rule states that reject H 0 if F c > F α at V 1 V 2 of 95% confidence level. The above statement shows that the calculated F value of 0.10 is significant at P= In addition, the R value (0.133 a ) indicates existing relationship between temperature and cloud cover. This implies that the cloud cover under consideration over the years is crucial for determining variation in atmospheric temperature of the study area. The explanation is that temperature dynamic depends on type of observed cloud cover. The correlation coefficient of 0.79 signifies that cloud has 79% influence over the temperature while the remaining 21% could be attributed to other factors of atmospheric system in the study area. Table 4: Summary of Regression Model on Cloud-Temperature Relationship Model R R Square Adjusted R Square Std. Error of the Estimate R Square Change Change Statistics F Change df1 df2 Sig. F Change a page 6 of 8

7 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. 5. Conclusions This study has observed the influence of annual cloud cover on surface temperature in Nigeria between 1980 and It concludes that; the observed annual temperature upward trends in this study could be attributable to the influence of reduced low level of cloud cover. As a result, Nigeria is experiencing more heat in the recent years based on reduced impact of cloud cover. It has been equally noted that a sharp rise in temperature occurred in 2014 with the livelihood of its continuous increase in the subsequent years with yearly increase in the intensity of solar radiation received. The situation of temperature dynamism was confirmed majorly as a function of prevailing cloud cover (clear, broken, scattered and overcast) in the study area. References 1. Odjugo PA (2010) General overview of climate change impacts in Nigeria. Journal of Human Ecology 29: United Nations Development Program (2010) Climate Change Country Profiles Nigeria. New York 91: Yue S, Hashino M (2003) Long term trends of annual and monthly precipitation in Japan. Journal American Water Resources Association 39: The Wikipedia (2016) cloud feedback. cloudiness and surface air temperature [ 5. Cess RD et al. (1990) Intercomparison and Interpretation of Climate Feedback Processes in 19 Atmospheric General Circulation Models. J Geophys 95: 16,601-16, Stocker TF et al. (2001) Physical climate processes and feedbacks. In JT Houghton, et al. Climate Change 2001: The Scientific Basis. Contributions of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge. UK. Cambridge University Press. 7. Dammo MN, Abubakar BS, Sangodoyin AY (2015) Trend and Change Analysis of Monthly and Seasonal Temperature Series over North-Eastern Nigeria. Journal of Geography, Environment and Earth Science International 3: IPCC (2013) Summary for Policymakers. In: Climate Change. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, TF, Qin D, Plattner GK, Tignor M, Allen SK, et al. USA. New York. Cambridge University Press. 9. Cess, Robert D (1976) Climate Change: An Appraisal of Atmospheric Feedback Mechanisms Employing Zonal Climatology. J Atmos Sci 33: Hartmann, Dennis L, Short, et al. (1980) On the Use of Earth Radiation Budget Statistics for Studies of Clouds and Climate. J Atmos Sci 37: Ohring, George, Clapp, et al. (1980) The Effect of Changes in Cloud Amount on the Net Radiation at the Top of the Atmosphere. J Atmos Sci 37: Weherland RT, Manabe S (1980) Cloud cover and climate sensitivity. J Atmos Sci 37: Hansen JD, Johnson A, Lacis S, et al. (1981) climate impact of increasing atmospheric carbon dioxide. Science 213: Hansen J, Lacis A (1984) Climate sensitivity: analysis of feedback mechanisms. Climate process and climate sensitivity. Maurice Ewing Series (5). Hansen JE, Takahashi, T Amer. Geophys. Union Nicole Orttung (2016) How climate change is altering Earth s cloud cover Shifting cloud patterns bear the hallmarks of a warming world. And will likely contribute to global warming going forward. The Christian Science Monitor. 16. Hartmann DL, Ockert-Bell ME, Michelsen ML (1992) The Effect of Cloud Type on Earth s Energy Balance: Global Analysis J Climate 5: National Research Council (2004) Understanding Climate Change Feedbacks. Panel on Climate Change Feedbacks, Climate Research Committee. National Academies Press. 18. Tselioudis G, Rossow WB, Rind D (1992) Global Patterns of Cloud Optical Thickness Variation with Temperature. J Climate 5: Donner LJ, Seman CJ, Soden BJ, et al. (1997) Large-scale ice clouds in the GFDL SKYHI general circulation model. J Geophys Res 102: 21,745-21, Pierrehumbert RT, Roca R (1998) Evidence for Control of Atlantic Subtropical Humidity by Large Scale Advection (PDF). Geophys Res Lett 25: Fowler LD, Randall DA (1996) Liquid and Ice Cloud Microphysics in the CSU General Circulation Model. Part III: Sensitivity to Modeling Assumptions. J Climate 9: Wetherald R, Manabe S (1988) Cloud Feedback Process in general Circulation Model. J Atmos Sci. 45: page 7 of 8

8 Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1: Ayoade JO (2003) Climate Change: A Synopsis of its Nature, Causes, Effects and Management. Ibadan Vintage Publishers. Citation: Abiodun Daniel Olabode (2017) Assessment of Annual Cloud Cover and Temperature Relationship in Nigeria. 1:3. page 8 of 8