scholarly journals Sensitivity of PM<sub>2.5</sub> to climate in the Eastern US: a modeling case study

2007 ◽  
Vol 7 (16) ◽  
pp. 4295-4309 ◽  
Author(s):  
J. P. Dawson ◽  
P. J. Adams ◽  
S. N. Pandis
Keyword(s):  
Wind Speed ◽  
Cloud Cover ◽  
Meteorological Parameters ◽  
Transport Model ◽  
Absolute Humidity ◽  
Major Effect ◽  
Base Case ◽  
Chemical Transport Model ◽  
Mixing Height ◽  
Sulfate Production

Abstract. The individual effects of various meteorological parameters on PM2.5 concentrations in the Eastern US are examined using the PMCAMx chemical transport model so that these effects and their relative magnitudes can be better understood. A suite of perturbations in temperature, wind speed, absolute humidity, mixing height, cloud cover, and precipitation are imposed individually on base case conditions corresponding to periods in July 2001 and January 2002 in order to determine the sensitivities of PM2.5 concentrations and composition to these separate meteorological parameters. Temperature had a major effect on average PM2.5 in January (−170 ng m−3 K−1) due largely to the evaporation of ammonium nitrate and organic aerosol at higher temperatures; increases in sulfate production with increased temperature counteracted much of this decrease in July. Changes in mixing height also had major effects on PM2.5 concentrations: 73 ng m−3 (100 m)−1 in January and 210 ng m−3 (100 m)−1 in July. Changes in wind speed (30 to 55 ng m−3 %−1) and absolute humidity (15 to 20 ng m−3 %−1) also had appreciable effects on average PM2.5 concentrations. Precipitation changes had large impacts on parts of the domain (a consequence of the base case meteorology), with sensitivities to changing area of precipitation in July up to 100 ng m−3 %−1. Perturbations in cloud cover had the smallest effects on average PM2.5 concentrations. The changes in PM2.5 concentrations resulting from changing all eight meteorological parameters simultaneously were approximately within 25% or so of the sum of the changes to the eight individual perturbations. The sensitivities of PM2.5 concentrations to changes in these meteorological parameters indicate that changes in climate could potentially have important impacts on PM2.5 concentrations.

scholarly journals Sensitivity of PM<sub>2.5</sub> to climate in the Eastern U.S.: a modeling case study

2007 ◽  
Vol 7 (3) ◽  
pp. 6487-6525 ◽  
Author(s):  
J. P. Dawson ◽  
P. J. Adams ◽  
S. N. Pandis
Keyword(s):  
Wind Speed ◽  
Cloud Cover ◽  
Meteorological Parameters ◽  
Transport Model ◽  
Absolute Humidity ◽  
Major Effect ◽  
Base Case ◽  
Chemical Transport Model ◽  
Mixing Height ◽  
Sulfate Production

Abstract. The effects of various meteorological parameters on PM2.5 concentrations in the Eastern US are examined using the PMCAMx chemical transport model. A suite of perturbations in temperature, wind speed, absolute humidity, mixing height, cloud cover, and precipitation are imposed on base case conditions corresponding to periods in July 2001 and January 2002 in order to determine the sensitivities of PM2.5 concentrations and composition to these meteorological parameters. Temperature had a major effect on average PM2.5 in January (–170 ng m−3 K−1) due largely to the evaporation of ammonium nitrate and organic aerosol at higher temperatures; increases in sulfate production with increased temperature counteracted much of this decrease in July. Changes in mixing height also had major effects on PM2.5 concentrations: 73 ng m−3 (100 m)−1 in January and 210 ng m−3 (100 m)−1 in July. Changes in wind speed (30 to 55 ng m−3 %−1) and absolute humidity (15 to 20 ng m−3 %−1) also had appreciable effects on average PM2.5 concentrations. Precipitation changes had large impacts on parts of the domain (a consequence of the base case meteorology), with sensitivities to changing area of precipitation in July up to 100 ng m−3 %−1. Perturbations in cloud cover had the smallest effects on average PM2.5 concentrations. The changes in PM2.5 concentrations resulting from changing all eight meteorological parameters simultaneously were approximated within 25% or so by summing the changes that resulted when the eight perturbations were imposed separately. The sensitivities of PM2.5 concentrations to changes in these meteorological parameters indicate that changes in climate may have important impacts on PM2.5 concentrations.

scholarly journals Linking climate and air quality over Europe: effects of meteorology on PM<sub>2.5</sub> concentrations

2014 ◽  
Vol 14 (18) ◽  
pp. 10283-10298 ◽  
Author(s):  
A. G. Megaritis ◽  
C. Fountoukis ◽  
P. E. Charalampidis ◽  
H. A. C. Denier van der Gon ◽  
C. Pilinis ◽  
...  
Keyword(s):  
Wind Speed ◽  
Meteorological Parameters ◽  
Transport Model ◽  
Absolute Humidity ◽  
Reaction Rates ◽  
Sea Salt ◽  
Phase Reaction ◽  
Chemical Transport Model ◽  
Mixing Height ◽  
The Future

Abstract. The effects of various meteorological parameters such as temperature, wind speed, absolute humidity, precipitation and mixing height on PM2.5 concentrations over Europe were examined using a three-dimensional chemical transport model, PMCAMx-2008. Our simulations covered three periods, representative of different seasons (summer, winter, and fall). PM2.5 appears to be more sensitive to temperature changes compared to the other meteorological parameters in all seasons. PM2.5 generally decreases as temperature increases, although the predicted changes vary significantly in space and time, ranging from −700 ng m−3 K−1 (−8% K−1) to 300 ng m−3 K−1 (7% K−1). The predicted decreases of PM2.5 are mainly due to evaporation of ammonium nitrate, while the higher biogenic emissions and the accelerated gas-phase reaction rates increase the production of organic aerosol (OA) and sulfate, having the opposite effect on PM2.5. The predicted responses of PM2.5 to absolute humidity are also quite variable, ranging from −130 ng m−3 %−1 (−1.6% %−1) to 160 ng m−3 %−1 (1.6% %−1) dominated mainly by changes in inorganic PM2.5 species. An increase in absolute humidity favors the partitioning of nitrate to the aerosol phase and increases the average PM2.5 during summer and fall. Decreases in sulfate and sea salt levels govern the average PM2.5 response to humidity during winter. A decrease of wind speed (keeping the emissions constant) increases all PM2.5 species (on average 40 ng m−3 %−1) due to changes in dispersion and dry deposition. The wind speed effects on sea salt emissions are significant for PM2.5 concentrations over water and in coastal areas. Increases in precipitation have a negative effect on PM2.5 (decreases up to 110 ng m−3 %−1) in all periods due to increases in wet deposition of PM2.5 species and their gas precursors. Changes in mixing height have the smallest effects (up to 35 ng m−3 %−1) on PM2.5 . Regarding the relative importance of each of the meteorological parameters in a changed future climate, the projected changes in precipitation are expected to have the largest impact on PM2.5 levels during all periods (changes up to 2 μg m−3 in the fall). The expected effects in future PM2.5 levels due to wind speed changes are similar in all seasons and quite close to those resulting from future precipitation changes (up to 1.4 μg m−3). The expected increases in absolute humidity in the future can lead to large changes in PM2.5 levels (increases up to 2 μg m−3) mainly in the fall due to changes in particulate nitrate levels. Despite the high sensitivity of PM2.5 levels to temperature, the small expected increases of temperature in the future will lead to modest PM2.5 changes and will not dominate the overall change.

scholarly journals Linking climate and air quality over Europe: effects of meteorology on PM<sub>2.5</sub> concentrations

2014 ◽  
Vol 14 (7) ◽  
pp. 10345-10391 ◽  
Author(s):  
A. G. Megaritis ◽  
C. Fountoukis ◽  
P. E. Charalampidis ◽  
H. A. C. Denier van der Gon ◽  
C. Pilinis ◽  
...  
Keyword(s):  
Wind Speed ◽  
Meteorological Parameters ◽  
Transport Model ◽  
Absolute Humidity ◽  
Reaction Rates ◽  
Sea Salt ◽  
Phase Reaction ◽  
Chemical Transport Model ◽  
Mixing Height ◽  
The Future

Abstract. The effects of various meteorological parameters such as temperature, wind speed, absolute humidity, precipitation and mixing height on PM2.5 concentrations over Europe were examined using a three-dimensional chemical transport model, PMCAMx-2008. Our simulations covered three periods, representative of different seasons (summer, winter, and fall). PM2.5 appears to be more sensitive to temperature changes compared to the other meteorological parameters in all seasons. PM2.5 generally decreases as temperature increases, although the predicted changes vary significantly in space and time, ranging from −700 ng m−3 K−1 (−8% K−1) to 300 ng m−3 K−1 (7% K−1). The predicted decreases of PM2.5 are mainly due to evaporation of ammonium nitrate, while the higher biogenic emissions and the accelerated gas-phase reaction rates increase the production of organic aerosol (OA) and sulfate, having the opposite effect on PM2.5. The predicted responses of PM2.5 to absolute humidity are also quite variable, ranging from −130 ng m−3%−1 (−1.6% %−1) to 160 ng m−3 %−1 (1.6% %−1) dominated mainly by changes in inorganic PM2.5 species. An increase in absolute humidity favors the partitioning of nitrate to the aerosol phase and increases the average PM2.5 during summer and fall. Decreases in sulfate and sea salt levels govern the average PM2.5 response to humidity during winter. A decrease of wind speed (keeping constant the emissions) increases all PM2.5 species (on average 40 ng m−3 %−1) due to changes in dispersion and dry deposition. The wind speed effects on sea salt emissions are significant for PM2.5 concentrations over water and in coastal areas. Increases in precipitation have a negative effect on PM2.5 (decreases up to 110 ng m−3 %−1) in all periods due to increases in wet deposition of PM2.5 species and their gas precursors. Changes in mixing height have the smallest effects (up to 35 ng m−3 %−1) on PM2.5. Regarding the relative importance of each of the meteorological parameters in a changed future climate, the projected changes in precipitation are expected to have the largest impact on PM2.5 levels during all periods (changes up to 2 μg m−3 in the fall). The expected effects in future PM2.5 levels due to wind speed changes are similar in all seasons and quite close to those resulting from future precipitation changes (up to 1.4 μg m−3). The expected increases in absolute humidity in the future can lead to large changes in PM2.5 levels (increases up to 2 μg m−3) mainly in the fall due to changes in particulate nitrate levels. Despite the high sensitivity of PM2.5 levels to temperature, the small expected increases of temperature in the future will lead to modest PM2.5 changes and will not dominate the overall change.

scholarly journals Sensitivity of chemical tracers to meteorological parameters in the MOZART-3 chemical transport model

2007 ◽  
Vol 112 (D20) ◽  
Author(s):  
D. E. Kinnison ◽  
G. P. Brasseur ◽  
S. Walters ◽  
R. R. Garcia ◽  
D. R. Marsh ◽  
...  
Keyword(s):  
Meteorological Parameters ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Chemical Tracers

scholarly journals Effects of various meteorological conditions and spatial emissionresolutions on the ozone concentration and ROG/NO<sub>x</sub> limitationin the Milan area (I)

2004 ◽  
Vol 4 (2) ◽  
pp. 423-438 ◽  
Author(s):  
N. Baertsch-Ritter ◽  
J. Keller ◽  
J. Dommen ◽  
A. S. H. Prevot
Keyword(s):  
Wind Speed ◽  
Ozone Concentration ◽  
Meteorological Conditions ◽  
Point Sources ◽  
Ozone Production ◽  
Specific Humidity ◽  
Large Field ◽  
Base Case ◽  
Emission Inventories ◽  
Mixing Height

Abstract. The three-dimensional photochemical model UAM-V is used to investigate the effects of various meteorological conditions and of the coarseness of emission inventories on the ozone concentration and ROG/NOx limitation of the ozone production in the Po Basin in the northern part of Italy. As a base case, the high ozone episode with up to 200ppb on 13 May 1998 was modelled and previously thoroughly evaluated with measurements gained during a large field experiment. Systematic variations in meteorology are applied to mixing height, air temperature, specific humidity and wind speed. Three coarser emission inventories are obtained by resampling from 3x3km2 up to 54x54km2 emission grids. The model results show that changes in meteorological input files strongly influence ozone in this area. For instance, temperature changes peak ozone by 10.1ppb/&amp;degC and the ozone concentrations in Milan by 2.8ppb/&amp;degC. The net ozone formation in northern Italy is more strongly temperature than humidity dependent, while the humidity is very important for the ROG/NOx limitation of the ozone production. For all meteorological changes (e.g. doubling the mixing height), the modelled peak ozone remains ROG limited. A strong change towards NOx sensitivity in the ROG limited areas is only found if much coarser emission inventories were applied. Increasing ROG limited areas with increasing wind speed are found, because the ROG limited ozone chemistry induced by point sources is spread over a larger area. Simulations without point sources tend to increase the NOx limited areas.

scholarly journals Improving the representation of secondary organic aerosol (SOA) in the MOZART-4 global chemical transport model

2012 ◽  
Vol 5 (4) ◽  
pp. 4187-4232 ◽  
Author(s):  
A. Mahmud ◽  
K. C. Barsanti
Keyword(s):  
South America ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Organic Aerosol ◽  
Basis Set ◽  
Base Case ◽  
Chemical Transport Model ◽  
Annual Average ◽  
Modeling Studies ◽  
The Usa

Abstract. The secondary organic aerosol (SOA) module in the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4) has been updated by replacing existing two-product (2p) parameters with those obtained from two-product volatility basis set (2p-VBS) fits, and by treating SOA formation from the following volatile organic compounds (VOCs): isoprene, propene and lumped alkenes. Strong seasonal and spatial variations in global SOA distributions were demonstrated, with significant differences in the predicted concentrations between the base-case and updated model versions. The base-case MOZART-4 predicted annual average SOA of 0.36 ± 0.50 μg m−3 in South America, 0.31 ± 0.38 μg m−3 in Indonesia, 0.09 ± 0.05 μg m−3 in the USA, and 0.12 ± 0.07 μg m−3 in Europe. Concentrations from the updated versions of the model showed a~marked increase in annual average SOA. Using the updated set of parameters alone (MZ4-v1) increased annual average SOA by ~8%, ~16%, ~56%, and ~108% from the base-case in South America, Indonesia, USA, and Europe, respectively. Treatment of additional parent VOCs (MZ4-v2) resulted in an even more dramatic increase of ~178–406% in annual average SOA for these regions over the base-case. The increases in predicted SOA concentrations further resulted in increases in corresponding SOA contributions to annual average total aerosol optical depth (AOD) by <1% for MZ4-v1 and ~1–6% for MZ4-v2. Estimated global SOA production was ~6.6 Tg yr−1 and ~19.1 Tg yr−1 with corresponding burdens of ~0.24 Tg and ~0.59 Tg using MZ4-v1 and MZ4-v2, respectively. The SOA budgets predicted in the current study fall well within reported ranges for similar modeling studies, 6.7 to 96 Tg yr−1, but are lower than recently reported observationally-constrained values, 50 to 380 Tg yr−1. With MZ4-v2, simulated SOA concentrations at the surface were also in reasonable agreement with comparable modeling studies and observations. Concentrations of estimated organic aerosol (OA) at the surface, however, showed under-prediction in Europe and over-prediction in the Amazonian regions and Malaysian Borneo during certain months of the year. Overall, the updated version of MOZART-4, MZ4-v2, showed consistently better skill in predicting SOA and OA levels and spatial distributions as compared with unmodified MOZART-4. The MZ4-v2 updates may be particularly important when MOZART-4 output is used to generate boundary conditions for regional air quality simulations that require more accurate representation of SOA concentrations and distributions.

scholarly journals Functionalization and fragmentation during ambient organic aerosol aging: application of the 2-D volatility basis set to field studies

2012 ◽  
Vol 12 (4) ◽  
pp. 9857-9901 ◽  
Author(s):  
B. N. Murphy ◽  
N. M. Donahue ◽  
C. Fountoukis ◽  
M. Dall'Osto ◽  
C. O'Dowd ◽  
...  
Keyword(s):  
Organic Compounds ◽  
Aqueous Phase ◽  
Transport Model ◽  
Field Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Base Case ◽  
Chemical Transport Model ◽  
Heterogeneous Oxidation ◽  
Phase Chemistry

Abstract. Multigenerational oxidation chemistry of atmospheric organic compounds and its effects on aerosol loadings and chemical composition is investigated by implementing the Two-Dimensional Volatility Basis Set (2-D-VBS) in a Lagrangian host chemical transport model. Three model formulations were chosen to explore the complex interactions between functionalization and fragmentation processes during gas-phase oxidation of organic compounds by the hydroxyl radical. The base case model employs a conservative transformation by assuming a reduction of one order of magnitude in effective saturation concentration and an increase of oxygen content by one or two oxygen atoms per oxidation generation. A second scheme simulates functionalization in more detail using group contribution theory to estimate the effects of oxygen addition to the carbon backbone on the compound volatility. Finally, a fragmentation scheme is added to the detailed functionalization scheme to create a functionalization-fragmentation parameterization. Two condensed-phase chemistry pathways are also implemented as additional sensitivity tests to simulate (1) heterogeneous oxidation via OH uptake to the particle-phase and (2) aqueous-phase chemistry of glyoxal and methylglyoxal. The model is applied to summer and winter periods at three sites where observations of organic aerosol (OA) mass and O:C were obtained during the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) campaigns. The base case model reproduces observed mass concentrations and O:C well, with fractional errors (FE) lower than 55% and 25%, respectively. The detailed functionalization scheme tends to overpredict OA concentrations, especially in the summertime, and also underpredicts O:C by approximately a factor of 2. The detailed functionalization model with fragmentation agrees well with the observations for OA concentration, but still underpredicts O:C. Both heterogeneous oxidation and aqueous-phase processing have small effects on OA levels but heterogeneous oxidation, as implemented here, does enhance O:C by about 0.1. The different schemes result in very different fractional attribution for OA between anthropogenic and biogenic sources.

scholarly journals Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe

2013 ◽  
Vol 13 (8) ◽  
pp. 4319-4337 ◽  
Author(s):  
È. Lecœur ◽  
C. Seigneur
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Transport Model ◽  
Model Simulation ◽  
Model Performance ◽  
Monitoring And Evaluation ◽  
The Other ◽  
Chemical Transport Model ◽  
Performance Goal ◽  
Dynamic Evaluation

Abstract. A 9 yr air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP). The spatial distribution of PM2.5 over Europe shows high concentrations over northern Italy (36 μg m−3) and some areas of Eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM2.5 composition differs among regions. The operational evaluation shows satisfactory model performance for ozone (O3). PM2.5, PM10, and sulfate (SO4=) meet the performance goal of Boylan and Russell (2006). Nitrate (NO3−) and ammonium (NH4+) are overestimated, although NH4+ meets the performance criterion. The correlation coefficients between simulated and observed data are 63% for O3, 57% for PM10, 59% for PM2.5, 57% for SO4=, 42% for NO3−, and 58% for NH4+. The comparison with other recent 1 yr model simulations shows that all models overestimate nitrate. The performance of PM2.5, sulfate, and ammonium is comparable to that of the other models. The dynamic evaluation shows that the response of PM2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM2.5 and its components (except for sea salt, which shows a positive correlation), which tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM2.5 and its components are better reproduced by the model than the effects of temperature. This is mainly due to the fact that temperature has different effects on the PM2.5 components, unlike precipitation and wind speed, which impact most of the PM2.5 components in the same way. These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM2.5 and therefore are suitable to investigate the effects of climate change on particulate air quality, although uncertainties remain concerning semivolatile PM2.5 components.

scholarly journals Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe

2013 ◽  
Vol 13 (1) ◽  
pp. 475-526
Author(s):  
È. Lecœur ◽  
C. Seigneur
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Transport Model ◽  
Model Simulation ◽  
Model Performance ◽  
The Other ◽  
Performance Criteria ◽  
Chemical Transport Model ◽  
Performance Goal ◽  
Dynamic Evaluation

Abstract. A nine-year air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP). The spatial distribution of PM2.5 over Europe shows high concentrations over northern Italy (36 μg m−3) and some areas of eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM2.5 composition differs among regions. The operational evaluation shows satisfactory model performance for ozone (O3). PM2.5, PM10, and sulfate (SO42−) meet the performance goal of Boylan and Russell (2006). Nitrate (NO3−) and ammonium (NH4+) are overestimated, although NH4+ meets the performance criteria. The correlation coefficients between simulated and observed data are 63% for O3, 57% for PM10, 59% for PM2.5, 57% for SO42−, 42% for NO3−, and 58% for NH4+. The comparison with other recent one-year model simulations shows that all models overestimate nitrate. The performance of PM2.5, sulfate, and ammonium is comparable to that of the other models. The dynamic evaluation shows that the response of PM2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM2.5 and its components (except for sea salt, which shows a positive correlation), that tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM2.5 and its components are better reproduced by the model than the effects of temperature. This is mainly due to the fact that temperature has different effects on the PM2.5 components, unlike precipitation and wind speed which impact most of the PM2.5 components in the same way. These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM2.5 and, therefore, are suitable to investigate the effects of climate change on particulate air quality.

scholarly journals A Comparative study of Time Series, Empirical Orthogonal Transformation and Descriptive Statistical Analysis on Meteorological Parameters over Ogoja and Maiduguri

2019 ◽  
pp. 1-14
Author(s):  
D. O. Akpootu ◽  
B. I. Tijjani ◽  
U. M. Gana
Keyword(s):  
Statistical Analysis ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Cloud Cover ◽  
Meteorological Parameters ◽  
Orthogonal Transformation ◽  
Global Solar Radiation ◽  
Mean Temperature ◽  
Sunshine Hours

In this study, time series statistical analysis was carried out on the monthly average daily meteorological parameters of global solar radiation, sunshine hours, wind speed, mean temperature, rainfall, cloud cover and relative humidity during the period of thirty one years (1980 – 2010) using IBM SPSS Statistics version 20 with expert modeler to determine the level, trend and seasonal variations for Ogoja and Maiduguri. Seasonal Auto Regressive Integrated Moving Average models were determined for the two locations along with their respective statistical indicators of coefficient of determination, Root Mean Square Error, Mean Absolute Percentage Error and Mean Absolute Error and are found suitable for one step ahead forecast for the studied area. The factor analysis (empirical orthogonal transformation) and descriptive statistical analysis was also carried out for the study areas under investigation. The results indicated that the model type for all the meteorological parameters for Ogoja is simple seasonal while that for Maiduguri is simple seasonal except for rainfall and cloud cover with winter’s additive and ARIMA models respectively. The correlation matrix obtained from the factor analysis for the studied area indicated that the global solar radiation and wind speed are more correlated with the mean temperature. The sunshine hours and mean temperature are more correlated with the global solar radiation. The rainfall is more correlated with the relative humidity; similarly, the relative humidity is more correlated with the rainfall. However, the cloud cover is more correlated to the rainfall for Ogoja while for Maiduguri the cloud cover is more correlated to the relative humidity. The component matrix analysis revealed that two seasons are identified for Ogoja; the rainy and dry seasons while for Maiduguri three seasons are identified; the rainy, cool dry (harmattan) and hot dry seasons. The skewness and kurtosis test for Ogoja indicated that the global solar radiation, sunshine hours, cloud cover and relative humidity are negatively skewed and the wind speed, mean temperature and rainfall are positively skewed while the global solar radiation, sunshine hours, wind speed, cloud cover and relative humidity indicates possibility of a leptokurtic distribution and the mean temperature and rainfall indicates possibility of a platykurtic distribution. The skewness and kurtosis for Maiduguri indicated that the solar radiation, rainfall and relative humidity are positively skewed and the sunshine hours, wind speed, mean temperature and cloud cover are negatively skewed while the global solar radiation, rainfall and cloud cover indicates possibility of a leptokurtic distribution and the sunshine hours, wind speed, mean temperature and relative humidity indicates possibility of a platykurtic distribution.

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