Seasonal Variation of Aerosol Optical Depth in the Guangdong Area of China Based on 39 Years of MERRA-2 Data

As NASA’s Global Modeling and Assimilation Office and Goddard Earth Sciences Data and Information Services Center are providing aerosol assimilated reanalysis dataset of the ongoing satellite era, it is convenient to subset the global MERRA-2 two dimensional, Monthly mean value, Instantaneous, Single-Level, Assimilation, Aerosol Optical Depth Analysis V5.12.4 (instM_2d_gas_Nx aka M2IMNXGAS 5.12.4) dataset into the size of Guangdong with Hong Kong and Macau (GDHM) to see the spatial-temporal AOD change over there. This paper uses the dataset above to calculate the average AOD of three adjacent monthly AODs as quarterly AOD in three ways and display their time series to find difference and similarity during the time from 1980 to February 2019. The First step is to overlay 470 corresponding monthly MERRA-2 AOD spatial subset grids (grid resolution: 0.625 longitude×0.5 latitude, 14 columns×13 rows, identified grid center point number from upper left 1 to lower right 182 of the extent 109.0625E-117.8125E and 20N-26N) to the administrative borderline of Guangdong with Hong Kong and Macau, use four to six original grids to form five rectangles then calculate the rectangle center points of monthly AOD for comparison. The vertices of chosen rectangles of GDHM are under the order: Central (average of the values of grid point ID 77, 78, 91, 92), North (average of the values of grid point ID 35, 36, 49, 50), South (average of the values of grid point ID 105, 106, 107, 119, 120, 121), East (average of the values of grid point ID 68, 69, 82, 83, 96, 97) and West (average of the values of grid point ID 128, 129, 142, 143, 156, 157). The AOD time series per quarter of the past 39 years of the comparing five groups are displayed by three ways. The first way to calculate quarterly mean AOD of twelve continual months’ values a year is under the order JFM (January, February and March), AMJ (April, May and June), JAS (July, August and September) and OND (October, November and December). The second way is FMA, MJJ, ASO, NDJ (January of the next year) and the last way is MAM, JJA, SON, DJF (January, February of the next year). All the five rectangles’ center average AOD indicates that most of the years their JFM average AODs are higher than the other three quarterly AODs except for 1982, 2003 (AMJ the highest), 1991(JAS the highest), 2006(OND the highest). FMA started series reveal those FMA average AODs in most of the years are also higher than NDJ averages, AOS averages and MJJ Averages. Five MAM started series appear similar that all these five regional average AODs went to a MAM AOD peak and a JJA valley and a climbing from JJA to DJF in most of the years except in 1991 their JJA AOD was higher than MAM AOD. Comparing the JFM AOD average, FMA AOD average and MAM AOD average in the past 39 years, central FMA AOD was higher than its JFM AOD and MAM AOD each year. FMA AODs of north, south, east and west are also higher than their JFM AODs and MAM AODs in each year. However there were 19 years central JFM AODs were higher than central MAM AODs, 24 years north JFM AODs were higher than north MAM AODs, 23 years south JFM AODs were higher than central MAM AODs, 17years east JFM AODs were higher than east MAM AOD and 25 years west JFM AODs were higher than west MAM AODs. Central, North and South MAM AOD maximums in the past 39 years happened in 2010, East and West MAM AOD maximums in the past 39 years happened in 2016 and all smaller than the former three places’ MAM in the same year. FMA AOD of Central and North reached to the top among the 39 years in 2007, South, East and West FMA AOD peaks were in 2016. The highest Central JFM AOD and the highest North JFM AOD were both in 2010; the highest South JFM AOD and the highest West JFM AOD were both in 2004 and the highest East JFM AOD was in 2007. Take JFM started series for instance, there were eleven ways (0001, 0011, 0110, 0100, 0111, 1000, 1011, 1001, 1100, 1110, 1111) to show seasonal average changes in a year as these permutation and combination of conditions: if JFM AOD is the maximum of the four seasons, true 1 false 0; AMJ AOD > JAS AOD, true 1 false 0, OND>JAS, true 1 false 0; OND> AMJ, true 1 false 0. Central seasonal average AODs and east seasonal average AODs had seven kinds of seasonal change ways in a year and they both had these five ways (0001 both in year 1991, 0100 both in year 1982, 1000, 1110 and 1111) during the 39 years period. West AODs had one more special seasonal trend in 2003 (0111) than central and east (uniquely 0110 in 2003). South seasonal AODs in a year had nine different trends and it is the most seasonal variation ways area among the others four comparing areas while north’s cases were the least during the 39 years period. All the five areas had these four kinds of seasonal AODs variation ways in a year: 0001, 0100, 1110 and 1111 in the past 39 years. And one way of seasonal change in a year (1100) were happened in north, south, east and west. All these three kinds of times series reveals seasonal average accumulation of AOD of the five selected areas went apparent increase during late 1990s to middle late 2000s and oscillated decrease yearly after then while those AODs of central and north of GDHM remain higher than the other directional comparing places in the past 39 years. As aerosol optical depth is an indicator to air pollution due to industrial and traffic emissions plus transportation not only natural particles matter sources migration, these five areas’ AOD seasonal variation lines reflect the imbalance economy status and population distribution in Guangdong province of China.