Question: Weight a serie of values by another serie

Hi everyone! I need to weight a serie of values which x₁ range go from 280 to 4000 by the factors provided by another serie of values, which x₂ values go from 206.6 to 12400. In the graphs, the red curve is a listplot of the serie which y₁ values I want to weight by the y₂ values of the listplot of the serie in black. I want the resulting serie in the x₁ range, but with the y₃ values equal to y₂*y₁. How can I do that since the series have different intervals?

Serie in red=S and serie in black=t

S:=

...[417., .96392], [418., .92392], [419., .96354], [420., .88467], [421., 1.0067], [422., .99499], [423., .96531], [424., .96182], [425., .99312], [426., .96667], [427., .9355], [428., .94625], [429., .87766], [430., .70134], [431., .63779], [432., 1.0628], [433., .9905], [434., .91653], [435., 1.007], [436., 1.1061], [437., 1.1306], [438., .99368], [439., .95753], [440., 1.0993], [441., 1.0859], [442., 1.164], [443., 1.1823], [444., 1.1537], [445., 1.1992], [446., 1.0766], [447., 1.2257], [448., 1.2422], [449., 1.2409], [450., 1.2881], [451., 1.3376], [452., 1.2822], [453., 1.1854], [454., 1.273], [455., 1.2655], [456., 1.3088], [457., 1.3213], [458., 1.2946], [459., 1.2859], [460., 1.2791], [461., 1.3255], [462., 1.3392], [463., 1.3452], [464., 1.3055], [465., 1.2905], [466., 1.319], [467., 1.2616], [468., 1.3178], [469., 1.3247], [470., 1.2749], [471., 1.2975], [472., 1.3661], [473., 1.3144], [474., 1.3304], [475., 1.3755], [476., 1.3299], [477., 1.3392], [478., 1.3839], [479., 1.3586], [480., 1.3825], [481., 1.3836], [482., 1.3899], [483., 1.3742], [484., 1.3492], [485., 1.3457], [486., 1.0918], [487., 1.2235], [488., 1.3252], [489., 1.2492], [490., 1.3968], [491., 1.3435], [492., 1.2818], [493., 1.3719], [494., 1.3402], [495., 1.4238], [496., 1.3548], [497., 1.3788], [498., 1.3421], [499., 1.3429], [500., 1.3391], [501., 1.299], [502., 1.2991], [503., 1.3597], [504., 1.2682], [505., 1.3598], [506., 1.4153], [507., 1.3548], [508., 1.321], [509., 1.385], [510., 1.3497], [511., 1.3753], [512., 1.4125], [513., 1.3277], [514., 1.3003], [515., 1.3385], [516., 1.3514], [517., 1.1017], [518., 1.2605], [519., 1.2222], [520., 1.3349], [521., 1.3452], [522., 1.376], [523., 1.2976], [524., 1.3962], [525., 1.3859], [526., 1.3479], [527., 1.1795], [528., 1.3508], [529., 1.4142], [530., 1.3598], [531., 1.4348], [532., 1.4094], [533., 1.259], [534., 1.3491], [535., 1.3701], [536., 1.4292], [537., 1.3229], [538., 1.3896], [539., 1.3558], [540., 1.3096], [541., 1.2595], [542., 1.3714], [543., 1.3493], [544., 1.3971], [545., 1.3657], [546., 1.3536], [547., 1.3717], [548., 1.3331], [549., 1.3752], [550., 1.3648], [551., 1.3639], [552., 1.3923], [553., 1.3533], [554., 1.3802], [555., 1.3883], [556., 1.3651], [557., 1.3321], [558., 1.3613], [559., 1.2885], [560., 1.3118], [561., 1.3885], [562., 1.3225], [563., 1.3731], [564., 1.3466], [565., 1.3555], [566., 1.2823], [567., 1.3673], [568., 1.3554], [569., 1.3228], [570., 1.324], [571., 1.281], [572., 1.3534], [573., 1.3595], [574., 1.3527], [575., 1.3225], [576., 1.3118]...

t:=

[[206.6000, 0.9110470095e-3], [210.1000, 0.8504840202e-3], [213.8000, 0.8153191021e-3], [217.5000, 0.7517070516e-3], [221.4000, 0.7035057451e-3], [225.4000, 0.6694785180e-3], [229.6000, 0.6318423899e-3], [233.9000, 0.5994622965e-3], [238.4000, 0.5764355678e-3], [243.1000, 0.5331430203e-3], [248.0000, 0.4950946716e-3], [253.0000, 0.4422658739e-3], [258.3000, 0.4023846661e-3], [263.8000, 0.3732428357e-3], [269.5000, 0.3444825682e-3], [275.5000, 0.3307336604e-3], [281.8000, 0.3570645679e-3], [288.3000, 0.4052774535e-3], [295.2000, 0.4741877081e-3], [302.4000, 0.5345931300e-3], [310.0000, 0.6002211844e-3], [317.9000, 0.7217256785e-3], [326.3000, 0.9176207886e-3], [335.1000, 0.1271492339e-2], [344.4000, 0.1679935813e-2], [354.2000, 0.1976514731e-2], [364.7000, 0.2169413297e-2], [375.7000, 0.2420056977e-2], [387.5000, 0.2698356864e-2], [399.9000, 0.3092320191e-2], [413.3000, 0.3891714441e-2], [427.5000, 0.4875961623e-2], [442.8000, 0.6098167657e-2], [459.2000, 0.8645631738e-2], [476.9000, 0.1639763449e-1], [495.9000, 0.1611551307e-1], [516.6000, 0.1102654621e-1], [539.1000, 0.5287562153e-2], [563.6000, 0.3253578980e-2], [590.4000, 0.2176718340e-2], [619.9000, 0.1510939515e-2], [652.5000, 0.1117755662e-2], [688.8000, 0.8568924681e-3], [729.3000, 0.6693019750e-3], [774.9000, 0.5484788449e-3], [826.6000, 0.4632457834e-3], [885.6000, 0.3982461677e-3], [953.7000, 0.3505755460e-3], [1033.000, 0.3130972421e-3], [1127.000, 0.2814970511e-3], [1240.000, 0.2609345123e-3], [1305.000, 0.2500612658e-3], [1378.000, 0.2397447628e-3], [1459.000, 0.2312899569e-3], [1550.000, 0.2268792462e-3], [1653.000, 0.2197119097e-3], [1771.000, 0.2106962051e-3], [1907.000, 0.2046935228e-3], [2066.000, 0.2003490235e-3], [2254.000, 0.1974613611e-3], [2480.000, 0.1948841680e-3], [2755.000, 0.1957355188e-3], [3100.000, 0.1937027704e-3], [3542.000, 0.1867538618e-3], [4133.000, 0.1849393481e-3], [4959.000, 0.1835339010e-3], [6199.000, 0.1838769393e-3], [8266.000, 0.1869179329e-3], [12400.00, 0.1990760933e-3]]