Drought　is　one　of　the　most　complicated　natural　hazards　and　is　among　those　that　pose　the　greatest　socioeconomic　risks.　How　long-term　climate　change　on　a　large　scale　affects　different　types　of　drought　has　not　been　well　understood.　This　study　aimed　to　enhance　comprehension　of　this　critical　issue　by　integrating　the　run　theory　for　drought　identification,　Mann-Kendall　trend　analysis,　and　partial　correlation　attribution　methods　to　analyze　global　drought　dynamics　in　1901-2018.　Methodological　innovations　include:　(1)　a　standardized　drought　severity　metric　enabling　cross-typology　comparisons;　and　(2)　quantitative　separation　of　precipitation　and　temperature　impacts.　Key　findings　reveal　that　socioeconomic　drought　severity　exceeded　meteorological,　agricultural,　and　hydrological　droughts　by　350.48%,　47.80%,　and　14.40%,　respectively.　Temporal　analysis　of　Standardized　Precipitation　Evapotranspiration　Index　(SPEI)　trends　demonstrated　intensification　gradients:　SPEI24　(-　0.09　slope/100　yr)　＞　SPEI01　(-　0.088/100　yr)　＞　SPEI06　(-　0.087/100　yr)　＞　SPEI12　(-　0.086/100　yr).　Climate　drivers　exhibited　distinct　patterns,　with　precipitation　showing　stronger　partial　correlations　across　all　drought　types　(meteorological:　0.78;　agricultural:　0.76;　hydrological:　0.60;　socioeconomic:　0.39)　compared　to　temperature　(meteorological:　-　0.45;　agricultural:　-　0.38;　hydrological:　-　0.27;　socioeconomic:　-　0.18).　These　results　quantitatively　establish　a　hierarchical　climate　response　gradient　among　drought　types.　The　framework　advances　drought　typology　theory　through　three　original　contributions:　(1)　systematic　quantification　of　cross-typology　drought　severity　disparities;　(2)　precipitation-temperature　influence　partitioning　across　drought　types;　and　(3)　identification　of　socioeconomic　drought　as　the　most　climate-decoupled　yet　fastest-intensifying　type.　This　study　refined　drought　typological　theories　and　provides　a　methodological　foundation　for　climate-resilient　drought　management　planning.