scholarly journals A simple explanation for the sensitivity of the hydrologic cycle to global climate change

2013 ◽  
Vol 4 (2) ◽  
pp. 853-868 ◽  
Author(s):  
A. Kleidon ◽  
M. Renner
Keyword(s):  
Energy Balance ◽  
Solar Radiation ◽  
Surface Energy ◽  
Surface Temperature ◽  
Greenhouse Effect ◽  
Surface Energy Balance ◽  
Hydrologic Cycle ◽  
Maximum Power ◽  
Solar Radiation Management ◽  
Simple Explanation

Abstract. The global hydrologic cycle is likely to increase its strength with global warming. Climate models generally predict an increase in strength of 2.2% K−1, which is much weaker than what would be expected from the increase in saturation vapor pressure of 6.5% K−1. Furthermore, it has been reported that the sensitivity of the hydrologic cycle to surface temperature differences caused by solar radiation is about 50% greater than by an equivalent difference induced by the greenhouse effect. Here we show that these sensitivities can be derived analytically from an extremely simple surface energy balance model that is constrained by the assumption that vertical convective transport within the atmosphere operates at maximum power. Using current climatic mean conditions, this model predicts a sensitivity of the hydrologic cycle of 2.2% K−1 to surface temperature induced by differences in the greenhouse effect, and a sensitivity of 3.2% K−1 for differences caused by absorbed solar radiation. These sensitivities can be explained by considering the changes in the surface energy balance in which the heating by solar radiation is partitioned equally into radiative and turbulent cooling at a state of maximum power of convective exchange. This explanation emphasizes the different roles that solar and terrestrial radiation play in the surface energy balance and hydrologic cycling that cannot be lumped together into a radiative forcing concept. We illustrate one implication of this explanation for the case of geoengineering, which aims to undo surface temperature differences by solar radiation management, but will nevertheless result in substantial differences in hydrologic cycling due to the difference in sensitivities. We conclude that the overall sensitivity of the hydrologic cycle to surface temperature can be understood and predicted by very simple physical considerations.

scholarly journals A simple explanation for the sensitivity of the hydrologic cycle to surface temperature and solar radiation and its implications for global climate change

2013 ◽  
Vol 4 (2) ◽  
pp. 455-465 ◽  
Author(s):  
A. Kleidon ◽  
M. Renner
Keyword(s):  
Solar Radiation ◽  
Surface Temperature ◽  
Climate Models ◽  
Turbulent Fluxes ◽  
Hydrologic Cycle ◽  
Balance Model ◽  
Solar Radiation Management ◽  
Simple Explanation ◽  
Additional Increase ◽  
Surface Warming

Abstract. The global hydrologic cycle is likely to increase in strength with global warming, although some studies indicate that warming due to solar absorption may result in a different sensitivity than warming due to an elevated greenhouse effect. Here we show that these sensitivities of the hydrologic cycle can be derived analytically from an extremely simple surface energy balance model that is constrained by the assumption that vertical convective exchange within the atmosphere operates at the thermodynamic limit of maximum power. Using current climatic mean conditions, this model predicts a sensitivity of the hydrologic cycle of 2.2% K−1 to greenhouse-induced surface warming which is the sensitivity reported from climate models. The sensitivity to solar-induced warming includes an additional term, which increases the total sensitivity to 3.2% K−1. These sensitivities are explained by shifts in the turbulent fluxes in the case of greenhouse-induced warming, which is proportional to the change in slope of the saturation vapor pressure, and in terms of an additional increase in turbulent fluxes in the case of solar radiation-induced warming. We illustrate an implication of this explanation for geoengineering, which aims to undo surface temperature differences by solar radiation management. Our results show that when such an intervention compensates surface warming, it cannot simultaneously compensate the changes in hydrologic cycling because of the differences in sensitivities for solar vs. greenhouse-induced surface warming. We conclude that the sensitivity of the hydrologic cycle to surface temperature can be understood and predicted with very simple physical considerations but this needs to reflect on the different roles that solar and terrestrial radiation play in forcing the hydrologic cycle.

scholarly journals Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

2018 ◽  
Vol 22 (4) ◽  
pp. 2311-2341 ◽  
Author(s):  
Nishan Bhattarai ◽  
Kaniska Mallick ◽  
Nathaniel A. Brunsell ◽  
Ge Sun ◽  
Meha Jain
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Regional Scale ◽  
Absolute Error ◽  
Error Statistics ◽  
Aridity Gradient ◽  
Balance System

Abstract. Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (gA and T0) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of −4 %. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (zOM), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28 %) and MOD16 was found to underestimate ET (PBIAS = −26 %). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with gA and associated roughness length estimation uncertainties which are intrinsically connected to TR uncertainties, vapor pressure deficit (DA), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

scholarly journals Impacts of topographic shading on direct solar radiation for valley glaciers in complex topography

2018 ◽  
Author(s):  
Matthew H. Olson ◽  
Summer B. Rupper
Keyword(s):  
Energy Balance ◽  
Solar Radiation ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Direct Solar Radiation ◽  
High Mountain ◽  
Clear Sky ◽  
Glacier Ice ◽  
North And South ◽  
Predictable Characteristics

Abstract. Topographic shading, including both shaded relief and cast shadowing, plays a fundamental role in determining direct solar radiation on glacier ice. However, this parameter has been oversimplified or incorrectly incorporated in surface energy balance models in some past studies. Here we develop a topographic solar radiation model to examine the variability in irradiance throughout the glacier melt season due to topographic shading and combined slope and aspect. We apply the model to multiple glaciers in High Mountain Asia (HMA), and test the sensitivity of shading to valley-aspect and latitude. Our results show that topographic shading significantly alters the potential direct clear-sky solar radiation received at the surface for valley glaciers in HMA, particularly for north- and south-facing glaciers. Additionally, we find that shading can be extremely impactful in the ablation zone. Cast shadowing is the dominant mechanism in determining total shading for valley glaciers in parts of HMA, especially at lower elevations. Although shading has some predictable characteristics, it is overall extremely variable between glacial valleys. Our results suggest that topographic shading is not only an important factor contributing to surface energy balance, but could also influence glacier response and mass balance estimates throughout HMA.

scholarly journals Variational Assimilation of the Impervious Surfaces Temperature

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 380
Author(s):  
Chunlei Meng
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Surface Energy Balance ◽  
Urban Canopy ◽  
Impervious Surface ◽  
Urban Land ◽  
High Temporal Resolution ◽  
Observation Data ◽  
Variational Assimilation

Impervious surface temperature is a key parameter in impervious surface energy balance. Urban canopy models are now widely used to simulate impervious surface temperatures, but the physical assimilation method for the urban canopy model is still under development and the use of high temporal resolution observation data are limited. In this paper, a physical assimilation method was used to improve the simulation of the impervious surface temperature for the first time. A variational assimilation method was developed and coupled with the integrated urban land model, using the impervious surface energy balance equation as the adjoint physical constraint. The results showed that when the observed impervious surface temperature data of every timestep were assimilated into the integrated urban land model, the bias of the impervious surface temperature was reduced about 86 %. For the operational run, the observed data were assimilated twice per day, and the bias of the impervious surface temperature was reduced by about 78%.

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