<jupyter_start><jupyter_text>Import ERA-5 JJA data<jupyter_code>era_5_jun_06  = np.load('../../ERA_5_monthly_TLS_maps/june_2006_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_07  = np.load('../../ERA_5_monthly_TLS_maps/june_2007_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_08  = np.load('../../ERA_5_monthly_TLS_maps/june_2008_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_09  = np.load('../../ERA_5_monthly_TLS_maps/june_2009_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_10  = np.load('../../ERA_5_monthly_TLS_maps/june_2010_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_11  = np.load('../../ERA_5_monthly_TLS_maps/june_2011_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_12  = np.load('../../ERA_5_monthly_TLS_maps/june_2012_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_13  = np.load('../../ERA_5_monthly_TLS_maps/june_2013_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_14  = np.load('../../ERA_5_monthly_TLS_maps/june_2014_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_15  = np.load('../../ERA_5_monthly_TLS_maps/june_2015_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_16  = np.load('../../ERA_5_monthly_TLS_maps/june_2016_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_17  = np.load('../../ERA_5_monthly_TLS_maps/june_2017_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_18  = np.load('../../ERA_5_monthly_TLS_maps/june_2018_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_19  = np.load('../../ERA_5_monthly_TLS_maps/june_2019_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jun_20  = np.load('../../ERA_5_monthly_TLS_maps/june_2020_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)

era_5_jul_06  = np.load('../../ERA_5_monthly_TLS_maps/july_2006_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_07  = np.load('../../ERA_5_monthly_TLS_maps/july_2007_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_08  = np.load('../../ERA_5_monthly_TLS_maps/july_2008_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_09  = np.load('../../ERA_5_monthly_TLS_maps/july_2009_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_10  = np.load('../../ERA_5_monthly_TLS_maps/july_2010_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_11  = np.load('../../ERA_5_monthly_TLS_maps/july_2011_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_12  = np.load('../../ERA_5_monthly_TLS_maps/july_2012_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_13  = np.load('../../ERA_5_monthly_TLS_maps/july_2013_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_14  = np.load('../../ERA_5_monthly_TLS_maps/july_2014_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_15  = np.load('../../ERA_5_monthly_TLS_maps/july_2015_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_16  = np.load('../../ERA_5_monthly_TLS_maps/july_2016_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_17  = np.load('../../ERA_5_monthly_TLS_maps/july_2017_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_18  = np.load('../../ERA_5_monthly_TLS_maps/july_2018_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_19  = np.load('../../ERA_5_monthly_TLS_maps/july_2019_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_jul_20  = np.load('../../ERA_5_monthly_TLS_maps/july_2020_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)

era_5_aug_06  = np.load('../../ERA_5_monthly_TLS_maps/august_2006_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_07  = np.load('../../ERA_5_monthly_TLS_maps/august_2007_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_08  = np.load('../../ERA_5_monthly_TLS_maps/august_2008_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_09  = np.load('../../ERA_5_monthly_TLS_maps/august_2009_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_10  = np.load('../../ERA_5_monthly_TLS_maps/august_2010_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_11  = np.load('../../ERA_5_monthly_TLS_maps/august_2011_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_12  = np.load('../../ERA_5_monthly_TLS_maps/august_2012_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_13  = np.load('../../ERA_5_monthly_TLS_maps/august_2013_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_14  = np.load('../../ERA_5_monthly_TLS_maps/august_2014_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_15  = np.load('../../ERA_5_monthly_TLS_maps/august_2015_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_16  = np.load('../../ERA_5_monthly_TLS_maps/august_2016_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_17  = np.load('../../ERA_5_monthly_TLS_maps/august_2017_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_18  = np.load('../../ERA_5_monthly_TLS_maps/august_2018_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_19  = np.load('../../ERA_5_monthly_TLS_maps/august_2019_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)
era_5_aug_20  = np.load('../../ERA_5_monthly_TLS_maps/august_2020_ERA_5_daily_zonal_mean_TLS_map_5_10.npy', allow_pickle=True)

era5_jja = np.concatenate([era_5_jun_06, era_5_jun_07, era_5_jun_08, era_5_jun_09, era_5_jun_10, era_5_jun_11, 
                           era_5_jun_12, era_5_jun_13, era_5_jun_14, era_5_jun_15, era_5_jun_16, era_5_jun_17, 
                           era_5_jun_18, era_5_jun_19, era_5_jun_20, era_5_jul_06, era_5_jul_07, era_5_jul_08, 
                           era_5_jul_09, era_5_jul_10, era_5_jul_11, era_5_jul_12, era_5_jul_13, era_5_jul_14, 
                           era_5_jul_15, era_5_jul_16, era_5_jul_17, era_5_jul_18, era_5_jul_19, era_5_jul_20, 
                           era_5_aug_06, era_5_aug_07, era_5_aug_08, era_5_aug_09, era_5_aug_10, era_5_aug_11, 
                           era_5_aug_12, era_5_aug_13, era_5_aug_14, era_5_aug_15, era_5_aug_16, era_5_aug_17,
                           era_5_aug_18, era_5_aug_19, era_5_aug_20])

era_5_jja_df = pd.DataFrame(era5_jja, columns=['Day', 'Hour', 'Year', 'Lat', 'Lon', 'Temp'])
daily_mean_removed = era5_tools.daily_mean_remover(era_5_jja_df)
daily_mean_removed['hourbin'] = daily_mean_removed.Hour.map(era5_tools.to_bin_hour)
sorted_dd = era5_tools.df_organizer(daily_mean_removed)
cycles_in_boxes = era5_tools.diurnal_binner(sorted_dd)
#np.save('JJA_ERA5_5x10_boxes_diurnal_cycles', cycles_in_boxes)<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup