A New Look at the Variance of Summertime Temperatures over Land

Zeppetello, Lucas R. Vargas; Battisti, David S.; Baker, M.

doi:10.1175/jcli-d-19-0887.1

Cited by 8 publications

(6 citation statements)

References 27 publications

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“…Such anomalous θ* are expected given the wide array of climatic conditions that can shift θ* beyond moisture availability (Denissen et al., 2020; Feldman et al., 2019; Haghighi et al., 2018). Nevertheless, the observed increase in energy flux variance in more water‐limited regions is consistent with expectations from an idealized land surface model (Vargas Zeppetello, Battisti, & Baker et al., 2020). SRF progressively increases with time spent water‐limited and slightly decreases above ∼90% time spent water‐limited.…”

Section: Resultssupporting

confidence: 87%

“…These mechanisms are empirically based and can be detected with observations alone. Physically describing why these mechanisms hold can be evaluated in analytical frameworks coupling the surface water and energy balances as in Vargas Zeppetello, Battisti, & Baker et al., 2020. However, this would require water and energy balance models and assumptions and is ultimately beyond the scope of this study.…”

Section: Methodsmentioning

confidence: 99%

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Observed Landscape Responsiveness to Climate Forcing

Feldman

Gianotti

Trigo

et al. 2022

Water Resources Research

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Climate variability and change shift environmental conditions on global land surfaces, creating uncertainties in predicting hydrologic flows, crop yields, and land carbon uptake. Land surfaces can present varying degrees of inertia to atmospheric forcing variability (e.g., precipitation). This study asks: are regions with the most variable environmental forcing necessarily the regions with the largest land surface variability? Specifically, it seeks to determine why land surfaces show varying responsiveness to environmental forcing. The degree to which and the mechanisms for how landscapes modulate the forcing are evaluated using a decade‐long satellite observation record of Africa's diverse climates. Surface responsiveness is quantified using intra‐seasonal energy flux variability, based on the observed diurnal temperature amplitude. We map the responsiveness and analyze the underlying mechanisms over intra‐seasonal timescales (especially interstorms). We show that, at a location, land surface responsiveness is dependent on the soil moisture distribution and the nonlinear relationship between energy fluxes and soil moisture. Land surfaces with greater responsiveness to climate are those with soil moisture distributions that span the threshold between evaporation regimes and spend most of their time in the water‐limited regime. Consequently, surface responsiveness mechanisms drive land surface variability beyond high climatic variability. Since we find these results to hold from intra‐seasonal to interannual timescales, we expect that these responsive regions will be most vulnerable to long‐term shifts in climate forcing. The quantification of these phenomena and determination of their geographic distributions based on observations can help assess land surface models used to evaluate hydrologic consequences of climate change.

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Section: Resultssupporting

confidence: 87%

Section: Methodsmentioning

confidence: 99%

Observed Landscape Responsiveness to Climate Forcing

Feldman

Gianotti

Trigo

et al. 2022

Water Resources Research

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“…VZ20 is derived in Vargas Zeppetello et al. (2020); here, we provide a summary of that derivation to establish nomenclature and then describe the revisions made to obtain VZ20r. A full derivation of VZ20r can be found in Appendix A.…”

Section: Sensitivity Growth and Suppressed Evapotranspirationmentioning

confidence: 99%

“…Recently, Vargas Zeppetello et al. (2020) developed a simple diagnostic model, here referred to as VZ20, to understand the origin of monthly temperature variance in NH mid‐latitudes. The VZ20 model captures spatial features of multimodel mean Δ σ 2 ( T ) that are attributable to land‐surface coupling associated with increases in atmospheric water vapor deficit and attendant changes in evapotranspiration (Vargas Zeppetello & Battisti, 2020).…”

Section: Introductionmentioning

confidence: 99%

Differences in Radiative Forcing, Not Sensitivity, Explain Differences in Summertime Land Temperature Variance Change Between CMIP5 and CMIP6

et al. 2022

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Increased frequency of extreme high temperatures is largely attributable to increases in mean temperature (Huntingford et al., 2013;Rhines & Huybers, 2013). Although significant changes in summertime temperature variance have not been observed in the historic record (McKinnon et al., 2016), climate model simulations generally indicate greater summertime temperature variance in a warming climate (e.g., Duan et al.

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“…In recent work, Vargas Zeppetello et al (2020a) used the local surface energy and water budgets to derive an equation for monthly‐averaged summertime temperature variance σ 2 ( T ′ ) as a function of monthly anomalies in shortwave radiation

{scriptF}^{'}

and precipitation

{scriptP}^{'}

, as well as two parameters Γ and ζ that will be described below:

σ^{2} false(T^{'} false) = \frac{1}{{normalΓ}^{2}} ([], σ^{2} false({scriptF}^{'} false) - 2 L ζ \overset{{scriptF}^{'} {scriptP}^{'}}{true} + {false(ζ L false)}^{2} σ^{2} false({scriptP}^{'} false)) .

…”

Section: Introductionmentioning

confidence: 99%

Projected Increases in Monthly Midlatitude Summertime Temperature Variance Over Land Are Driven by Local Thermodynamics

Zeppetello

Battisti

2020

Geophysical Research Letters

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The increasing frequency of very high temperatures driven by global warming has motivated growing interest in how the probability distribution of summertime temperatures will evolve in the future. Climate models forced by increasing CO 2 simulate increasing monthly-averaged temperature variance across the midlatitudes. In this study we present evidence that these projections are credible and driven primarily by the magnitude of local warming. A first-principles analytic theory reproduces the increased midlatitude summertime temperature variance in climate models extremely well by considering only the warming-induced change in the climatological vapor pressure deficit. The impacts of local warming on saturation specific and relative humidity are shown to have roughly equal contributions to increases in summertime temperature variance. The vegetation response to increasing CO 2 is found to be an important contributor to the uncertainty in modeled temperature variance change, highlighting the role of plants in shaping the summertime temperature distribution. Plain Language Summary Extreme summertime temperatures are a focal point for the impacts of climate change. Climate models driven by increasing CO 2 emissions project increasing summertime temperature variability by the end of the 21 st century. If credible, these increases imply that extreme summertime temperatures will become even more frequent than a simple shift in the contemporary probability distribution would suggest. Given the impacts of extreme temperatures on public health, food security, and the global economy, it is of great interest to understand whether the projections of increased temperature variance are credible. In this study, we use a theoretical model of the land surface to demonstrate that the large increases in summertime temperature variance projected by climate models are credible, predictable from first principles, and driven by the effects of warmer temperatures on evapotranspiration. We also find that the response of plants to increased CO 2 and mean warming is important to the projections of increased temperature variability.

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A New Look at the Variance of Summertime Temperatures over Land

Cited by 8 publications

References 27 publications

Observed Landscape Responsiveness to Climate Forcing

Observed Landscape Responsiveness to Climate Forcing

Differences in Radiative Forcing, Not Sensitivity, Explain Differences in Summertime Land Temperature Variance Change Between CMIP5 and CMIP6

Projected Increases in Monthly Midlatitude Summertime Temperature Variance Over Land Are Driven by Local Thermodynamics

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