This　study　investigates　the　multi-scale　dynamic　correlations　and　information　spillover　effects　between　climate　risks　and　digital　cryptocurrencies　using　wavelet　analysis　and　the　Time-frequency　Domain　QVAR　model.　By　analyzing　non-stationary　financial　time-series　data,　we　uncover　latent　patterns　and　quantify　the　dynamic　interactions　between　climate　risks　and　cryptocurrency　markets　across　different　time　scales.　The　findings　reveal　significant　spillover　effects,　highlighting　how　climate　risks,　particularly　through　energy-intensive　mining　and　extreme　weather　disruptions,　influence　cryptocurrency　volatility.　The　research　contributes　to　the　understanding　of　risk　transmission　mechanisms　in　emerging　financial　markets,　offering　insights　into　the　broader　implications　of　climate　risks　on　global　financial　stability.　The　results　underscore　the　importance　of　integrating　climate　risk　assessments　into　cryptocurrency　market　analyses,　providing　a　foundation　for　informed　policy-making　and　risk　management　strategies.