Spectral Divergence in Hydroclimate and Temperature Between Models and Reconstructions Over the Common Era

Climate models and paleoclimate proxies have temperature variability that diverge from each other locally and at long timescales. It is unknown to what extent these divergences also apply to hydroclimate and whether long-term hydroclimate variability is fundamentally different than temperature variability. Here we evaluate the long-term variability of near surface air temperature (tas) and hydroclimate (Palmer Drought Severity Index [PDSI]) using a climate model (the Community Earth System Model-Last Millennium Ensemble [CESM-LME]) and a paleoclimate reconstruction based on this model (the Paleo Hydrodynamics Data Assimilation product [PHYDA]); this framework allows us to see how a model's long-term climate variability is affected by informing it with proxy data. Using power-scaling exponents, we find universally higher scaling values in PHYDA (except for global mean tas) compared to the CESM-LME model. Thus, PHYDA's global PDSI, local PDSI, and local tas are more dominated by low-frequency variability than CESM-LME's. Additionally, PDSI is spectrally flatter than tas in CESM-LME, whereas scaling values of tas and PDSI are comparable in PHYDA. These results indicate that the paleoclimate reconstruction process adds low-frequency variability that CESM-LME otherwise would not have. Based on a range of null reconstruction experiments, we attribute the origin of low-frequency variability in PHYDA to proxy information and not the mathematical properties of the data assimilation methodology. This implies that long-term variability in PHYDA is dependent on the selection of assimilated proxy data.