Modeled surface air temperature response to snow depth variability

Earth's climate can be understood as a dynamical system that changes due to external forcing and internal couplings. It can be characterized from the evolution of essential climate variables, such as surface air temperature. Yet, the mechanisms, amplitudes, and spatiotemporal patterns of global and local temperature fluctuations around its mean, called temperature variability, are insufficiently understood. Discrepancies exist between temperature variability from model and paleoclimate data at the temporal scale of years to centuries and at the local scale, both of which are important socio-economic scales for long-term planning. Here, we clarify whether global and local temperature signals from the last millennia show a stationary variance on these timescales and thus behave in a stable manner or not. Therefore, we contrast power spectral densities and their scaling behaviors using simulated, observed, and reconstructed temperatures on periods between 10 and 200 years. Despite careful consideration of possible spectral biases, we find that local temperatures from paleoclimate data tend to show unstable behavior, while simulated temperatures almost exclusively show stable behavior. Conversely, the global mean temperature tends to be stable. We explain this by introducing the gain as a powerful tool to analyze the forced temperature response, based on a novel estimate of the joint power spectrum of radiative forcing. Our analysis identifies main deficiencies in the properties of temperature variability and offers new insights into the linkage between raditative forcing and temperature response, relevant to the understanding of Earth&#8217;s dynamics and the assessment of climate risks.

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The Influence of the MJO on the Intraseasonal Variability of Northern Hemisphere Spring Snow Depth

Journal of Climate ◽

10.1175/jcli-d-15-0092.1 ◽

2015 ◽

Vol 28 (18) ◽

pp. 7250-7262 ◽

Cited By ~ 13

Author(s):

Bradford S. Barrett ◽

Gina R. Henderson ◽

Joshua S. Werling

Keyword(s):

North America ◽

Northern Hemisphere ◽

Air Temperature ◽

Snow Depth ◽

Intraseasonal Variability ◽

Rank Correlation ◽

Surface Air Temperature ◽

Correlation Coefficients ◽

Strong Relationship ◽

The Relationship

Abstract Intraseasonal variability in springtime Northern Hemisphere daily snow depth change (ΔSD) by phase of the MJO was explored in this study. Principal findings of the relationship between ΔSD and the MJO included the following: 1) Statistically significant regions of lagged ΔSD anomalies for multiple phases of the MJO were found in March, April, and May in both North America and Eurasia. 2) In each month, lagged ΔSD anomalies were physically supported by corresponding lagged anomalies of 500-hPa height (Z500) and surface air temperature (SAT). Spearman rank correlation coefficients indicated a moderate to strong relationship between both Z500 and ΔSD and SAT and ΔSD in both Eurasia and North America for phases 5 and 7 in March. In April, a moderately strong relationship between Z500 and ΔSD was found over Eurasia for phase 5, but the relationship between SAT and ΔSD was weak. In May, correlations between ΔSD and both Z500 and SAT over a hemisphere-wide latitude band from 60° to 75°N were close to −0.5 and −0.4, respectively. Given the strength of these statistical relationships, the following physical pathway is proposed for intraseasonal variability of spring snow depth changes: poleward-propagating Rossby waves in response to tropical MJO convection interact with Northern Hemisphere background flow, leading to anomalous troughing and ridging. These anomalous circulation centers then impact daily snow depth change via precipitation processes and anomalies in surface air temperature.

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