Increase In Surface Albedo Research Articles

Arctic sea‐ice export as a mechanism for cold climate events during the last deglaciation

ABSTRACTRecently it was proposed that a sudden drainage of accumulated Arctic sea ice could have caused cold climate events during the last deglaciation. To explore this mechanism, we performed numerical experiments with an atmosphere–ocean–sea ice model. In these experiments, the impact of a large flush of Arctic sea ice was compared to a reference glacial state of the climate. In our results, the sea ice flush produces a major surface freshening of the North Atlantic Ocean and a 17% weakening of the strength of the Atlantic Meridional Overturning Circulation. Together with an increase in surface albedo, this weakening in ocean circulation leads to a cooling over the North Atlantic, extending to the downwind continents. Compared to our reference glacial state, the cooling reaches 5°C and lasts about 80 years. This climate anomaly is similar in magnitude and duration to relatively short cooling events during the last deglaciation, such as the Older Dryas, the Inter‐Allerød cold period and the Preboreal Oscillation. We thus conclude that the sea‐ice flush mechanism is consistent with the occurrence of such cooling events in the North Atlantic region. However, longer cooling events such as the Younger Dryas would require additional mechanisms.

Decreased cloud cover partially offsets the cooling effects of surface albedo change due to deforestation

Biophysical processes of forests affect climate through the regulation of surface water and heat fluxes, which leads to further effects through the adjustment of clouds and water cycles. These indirect biophysical effects of forests on clouds and their radiative forcing are poorly understood but highly relevant in the context of large-scale deforestation or afforestation, respectively. Here, we provide evidence for local decreases in global low-level clouds and tropical high-level clouds from deforestation through both idealized deforestation simulations with climate models and from observations-driven reanalysis using space-for-time substitution. The decreased cloud cover can be explained by alterations in surface turbulent heat flux, which diminishes uplift and moisture to varying extents. Deforestation-induced reduction in cloud cover warms the climate, partially counteracting the cooling effects of increased surface albedo. The findings from idealized deforestation experiments and space-for-time substitution exhibit disparities, with global average offsets of, respectively, approximately 44% and 26%, suggesting the necessity for further constraints.

Accounting for the effect of aerosols in GHGSat methane retrieval

Abstract. GHGSat comprises a constellation of satellites with high spatial and spectral resolution that specialize in monitoring methane emissions at 1.65 µm. This study investigates the ability to accurately retrieve both the methane mixing-ratio enhancement (ΔXCH4) and the aerosol optical depth (AOD) simultaneously from simulated GHGSat observations that incorporate angle-dependent scattering information. Results indicate that the sign of the ΔXCH4 bias when neglecting aerosols changes from negative to positive as surface albedo increases, which is consistent with previous studies. The bias in ΔXCH4 is most pronounced when AOD is not simultaneously retrieved, ranging from −3.0 % to 6.3 % with an AOD of 0.1, a 60° solar zenith angle, and a surface albedo of 0.2 for the nadir-only retrieval. Using multiple satellite viewing angles during the GHGSat observation sequence with a scattering angle ranging from 100 to 140°, the study shows that the mean bias and standard deviation of ΔXCH4 are within 0.3 % and 2.8 % relative to the background. The correlation between simultaneously retrieved ΔXCH4 and AOD shifts from being positive to negative as surface albedo increases and the aerosol asymmetry factor decreases, signifying a transition of the dominant aerosol effect from aerosol-only scattering to aerosol–surface multiple scattering. The variety of scattering angle ranges has little impact on the performance of the multi-angle viewing method. This study improves the understanding of the impact of aerosols on the GHGSat ΔXCH4 retrieval and provides guidance for improving future GHGSat-like point-source imagers.

The contrasting trend of global urbanization-induced impacts on day and night land surface temperature from a time-series perspective

Understanding the warming effect of the impervious surface area (ISA) quantitively is crucial to alleviate the urban heat island effect. However, the quantitative analyses of urbanization-induced land surface temperature (LST) change globally remain to be determined during the global warming hiatus. Here, we first characterized the response of LST to ISA (i.e., δLST) in 369 global cities using MODIS LST product (1 km) and the global artificial impervious area dataset (30 m). We then investigated the spatiotemporal changes of δLST and its associated driving factors, including enhanced vegetation index (1 km), albedo (ALB, 500 m), population (100 m), air temperature (AT, 0.1°), and precipitation (0.1°). The analysis was conducted using linear regression models from 2000 to 2010 at the pixel level. The results illustrate that (1) the daytime δLST in urban areas shows a negative trend with –0.2971 °C/% and –0.0870 °C/% in arid and temperate regions, and the nighttime δLSTs were 0.0938 °C/% and 0.0048 °C/%, respectively. In tropical regions, the δLST remains positive throughout the day, while it exhibits an opposite trend in snow regions. (2) The magnitude of nighttime δLST is stronger compared to daytime globally, which is more significant in arid regions with the largest ΔδLST values (i.e., diurnal variations) in urban (0.3909 °C/%) and rural (0.3262 °C/%) areas. (3) In temperate regions, the response of ALB to ISA (δALB, negative effect) and the response of AT to ISA (δAT, positive effect) are dominant factors in regulating δLST during daytime and nighttime, respectively However, in arid regions, the daytime and nighttime δLSTs are negatively correlated by urban population and vegetation, respectively. These findings provide a quantitative understanding on long-term LST variations and driving factors behind at the pixel level, suggesting that urban greening and increasing surface albedo are effective strategies to mitigate the urbanization-induced surface warming.

Arctic Sea Ice Albedo Estimation from Fengyun-3C/Visible and Infra-Red Radiometer

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases.

Unraveling the complexities of the Last Glacial Maximum climate: the role of individual boundary conditions and forcings

Abstract. In order to quantify the relative importance of individual boundary conditions and forcings, including greenhouse gases, ice sheets, and Earth's orbital parameters, on determining Last Glacial Maximum (LGM) climate, we have performed a series of LGM experiments using a state-of-the-art climate model AWI-ESM, in which different combinations of boundary conditions and forcings have been applied following the protocol of Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). In good agreement with observational proxy records, a general colder and drier climate is simulated in our full-forced LGM experiment as compared to the present-day simulation. Our simulated results from non-full-forced sensitivity simulations reveal that both the greenhouse gases and ice sheets play a major role in defining the anomalous LGM surface temperature compared to today. Decreased greenhouse gases in LGM as compared to present day leads to a non-uniform global cooling with polar amplification effect. The presence of LGM ice sheets favors a warming over the Arctic and northern Atlantic oceans in boreal winter, as well as a cooling over regions with the presence of ice sheets. The former is induced by a strengthening in the Atlantic meridional overturning circulation (AMOC) transporting more heat to high latitudes, whilst the latter is due to the increased surface albedo and elevation of ice sheets. We find that the Northern Hemisphere monsoon precipitation is influenced by the opposing effects of LGM greenhouse gases and ice sheets. Specifically, the presence of ice sheets leads to significant drying in the Northern Hemisphere monsoon regions, while a reduction in greenhouse gases results in increased monsoon rainfall. Based on our model results, continental ice sheets exert a major control on atmospheric dynamics and the variability of El Niño–Southern Oscillation (ENSO). Moreover, our analysis also implies a nonlinearity in climate response to LGM boundary conditions and forcings.

Observed and simulated local climate responses to tropical deforestation

Tropical deforestation has local and regional effects on climate, but the sign and magnitude of these effects are still poorly constrained. Here we used satellite observations to evaluate the local land surface temperature and precipitation response to tropical deforestation in historical simulations from 24 CMIP6 models. We found tropical forest loss leads to an observed local dry season warming and reduced wet and dry season precipitation across the range of scales (0.25°-2°) analysed. At the largest scale analysed (2°), we observed a warming of 0.018 ± 0.001 °C per percentage point of forest loss (°C %−1), broadly captured in the multi-model mean response of 0.017 ± 0.005 °C %−1. The multi-model mean correctly simulates reduced precipitation due to forest loss in the dry season but simulates increased precipitation due to forest loss in the wet season, opposite to the observed response. We found that the simulated dry season surface temperature and precipitation changes due to forest loss depend on the simulated surface albedo change, with less warming and less drying in models with greater increases in surface albedo due to forest loss. Increased recognition of the local and regional climate benefits of tropical forests is needed to support sustainable land use policy.

A Functionalized Monte Carlo 3D Radiative Transfer Model: Radiative Effects of Clouds Over Reflecting Surfaces

AbstractIn the Earth Sciences, the 3D radiative transfer equation is often solved for by Monte Carlo (MC) methods. They can, however, be computationally taxing, and that can narrow their range of application and limit their use in explorations of model parameter spaces. A novel family of MC algorithms is investigated here in which single simulations provide estimates of both radiative quantities A for a set of parameters , as usual, as well as the overarching functional (x) that can be evaluated, extremely efficiently, at any x. One such algorithm is developed and demonstrated for horizontally averaged broadband solar radiative fluxes as functions of surface albedo for uniform Lambertian surfaces beneath inhomogeneous cloudy atmospheres. Simulations for a high‐resolution synthetic cloud field, at various solar zenith angles, illustrate the potential of the method to gain insights into the nature of 3D radiative effects for complicated atmosphere‐surface conditions using information specially derived from the MC simulation. For simulations performed with a single surface albedo it is found that as surface albedo increases, 3D radiative effects increase, too, with maxima occurring at middling to large values, and then decrease. By utilizing the derived coefficients that describe it was established that these 3D effects stem from differences in fractions of radiation entrapped at successive orders of internal multiple reflections for 1D and 3D transfer.

About the Assessment of Cover Crop Albedo Potential Cooling Effect: Risk of the Darkening Feedback Loop Effects

Today societies face an unprecedented challenge to limit global warming and restore agricultural soils. Recent studies show that the introduction of cover crops over Europe could result in a cooling impact due to an increase in soil organic carbon stocks, a decrease in the use of fertilizers, and an increase in surface albedo of the croplands. Based on the use of remote sensing data, land cover database, meteorological data, national agricultural statistics, and ground measurements, a generic model was developed to simulate the radiative forcing following the change in surface albedo. This article analyzes the impact of the introduction of cover crops in Europe during the fallow periods. Compared to previous studies, this work discusses: (i) The maximum greening potential in Europe and the associated indirect surface properties changes (ii) for snowfall episodes, and (iii) due to an increase in organic matter. This study shows that the mitigation potential of cover crops through albedo effects could reach 6.74 MtCO2-eq.yr−1 by extending the periods of the introduction of the cover crops to all possible fallow periods. This mitigation could be limited to 5.68 MtCO2-eq.yr−1 if the impact of snowfalls is considered. This would be equivalent to 9.12 gCO2.m−2.yr−1. Finally, this study investigates the feedback loop due to soil darkening with soil organic carbon content increase when cover crops are introduced, considering two scenarios. The first considers the soil organic carbon content increase following repeated incorporation of cover crop biomass into the soil, simulated with the DayCent model. The second, more conceptual and extreme scenario aims at alerting on the possible impact of a combination of carbon farming practices, such as biochar or organic amendments. Our results show that this effect could lead to a loss of 20% of the climate benefit (i.e., 5.39 MtCO2-eq.yr−1). In conclusion, this study shows that cover crops have a strong potential for climate mitigation through direct albedo effects (soil coverage). However, once introduced, cropland should be permanently covered by vegetation or straws in order to avoid this darkening feedback loop effect.

Unequal exposure to heatwaves in Los Angeles: Impact of uneven green spaces.

Cities worldwide are experiencing record-breaking summer temperatures. Urban environments exacerbate extreme heat, resulting in not only the urban heat island but also intracity variations in heat exposure. Understanding these disparities is crucial to support equitable climate mitigation and adaptation efforts. We found persistent negative correlations between daytime land surface temperature (LST) and median household income across the Los Angeles metropolitan area based on Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station observations from 2018 to 2021. Lower evapotranspiration resulting from the unequal distribution of vegetation cover is a major factor leading to higher LST in low-income neighborhoods. Disparities worsen with higher regional mean surface temperature, with a $10,000 decrease in income leading to ~0.2°C LST increase at 20°C and up to ~0.7°C at 45°C. With more frequent and intense heat waves projected in the future, equitable mitigation measures, such as increasing surface albedo and tree cover in low-income neighborhoods, are necessary to address these disparities.

Artificial neural networks for power output forecasting from bifacial solar PV system with enhanced building roof surface Albedo

The main objective of this research study is to evaluate the performance of bifacial solar PV systems (bPV) installed on flat roof buildings with controlled surface albedo and to develop forecasting models to anticipate the power output from bifacial solar PV systems due to the enhancement of surface albedo. The originality of this study and the novelty include integrating innovative bifacial solar PV and cool roof technologies to increase solar PV panel power output and anticipate electricity generation in advance to balance supply and demand. For the methodology, modeling and simulation analysis was used to test the performance of bPV system installed on a building with a surface albedo of 0.2–0.8. An Artificial Neural Network was used as a machine learning approach for bifacial solar PV power and energy forecasting. The significant findings show that an increase in surface albedo from 0.2 to 0.5 and 0.2 to 0.8 will help to boost the annual bifacial solar PV power production by 7.75% and 14.96%, respectively. The predictive models are exceptionally accurate in anticipating the bifacial solar PV power. The monthly power from bPV rose from 10.87 to 21.54%, with a 0.3 (from 0.2 to 0.5) to 0.6 (from 0.2 to 0.8) albedo increase. The coefficient of correlation R values for all of the power data ranges from 0.99145 to 0.99382 for the roof surface albedo, ranging from 0.2 to 0.8. The ANN models illustrate how effectively the model mimics the modeling and simulation data. For the research implications, the developed forecast models will assist the industry in predicting ahead of the power production, building operations and maintenance, demand-side management, and advanced energy purchases.

Spatiotemporal Dynamics of Land Surface Albedo and Its Influencing Factors in the Qilian Mountains, Northeastern Tibetan Plateau

Land surface albedo directly determines the distribution of radiant energy between the surface and the atmosphere, and it is a key parameter affecting the energy balance on the land surface. However, the spatiotemporal dynamics of land surface albedo and associated influencing factors in the Qilian Mountains (QM) have been rarely reported. By using the long-time series data products of MODIS shortwave albedo, normalized difference vegetation index (NDVI), and snow cover with a spatial resolution of 0.05° from 2001 to 2020, this paper analyzes the temporal and spatial variations of land surface albedo in the QM over the past 20 years and its influencing factors. The analysis results show that the multi-year average surface albedo in the QM has obvious differences in spatial distribution: it increases with the altitude, and it is high in the west (at the west of 98° E) and low in the east. Meanwhile, the surface albedo has different distribution characteristics in different seasons: the spatial distribution of surface albedo is similar in spring and autumn; the areas with a high surface albedo in summer are significantly fewer than those in other seasons. Besides, in the past 20 years, the annual average surface albedo has shown a weak growth trend in the QM, with a change rate of 5 × 10−3/10a, and the minimum and maximum values were reached in 2001 and 2019, respectively. In addition, the annual variation of the surface albedo in the QM showed a “U” shape, with the largest variation in January and the smallest variation in August. The annual variation of surface albedo is significantly positively correlated with snow cover (r = 0.96) and significantly negatively correlated with NDVI (r = −0.91). Moreover, the interannual variation of the surface albedo in the QM is closely related to land surface cover and is greatly affected by snow cover. Spatially, the annual variation of surface albedo in most areas of the QM is dominated by the change of snow cover, and the increase of surface albedo in the middle area is consistent with the increase of snow cover, while the decrease of albedo in the edge area is related to the improvement of vegetation cover. The results of this study provide a scientific basis for studying the climate and environmental changes caused by changes in the surface of the QM and making ecological environment restoration strategies.

Latitudinal land–sea distributions and global surface albedo since the Cretaceous

We estimate global surface albedo from the areal proportion of land to sea in climatically-significant latitudinal belts at ten million-year intervals for the Late Cretaceous and Cenozoic (120 million years ago to Present) using modern plate tectonic reconstructions and a composite apparent polar path designed to minimize known biases in the determination of paleolatitude. We find that global surface albedo stayed almost constant until it shifted 30% higher to the modern value of around 0.15 with the inception of the Late Cenozoic Ice Age 34 million years ago, reflecting polar ice-albedo amplification of global cooling resulting from the reduction of greenhouse gases below a critical threshold, most probably as the culmination of enhanced CO 2 weathering consumption of continental mafic rocks in the tropical humid belt. The contribution from cloud cover toward a planetary albedo is unclear in the absence of measurable proxies but might eventually be gauged from the role cloudiness evidently plays in maintaining radiative balance with the increasing land bias between northern and southern hemispheres over the Cenozoic. • Changes in land–sea area were small in equatorial and polar climate belts from 120 Ma • Land area decreased in temperate belts and increased in subtropical arid belts • Global surface albedo was low from 120 to 40 Ma and shifted to modern value by 30 Ma • Increase in surface albedo due to polar ice cover with Late Cenozoic Ice Age at 34 Ma • Ice age reflects polar amplification of global cooling triggered by drawdown of CO 2

Sea Breeze Geoengineering to Increase Rainfall over the Arabian Red Sea Coastal Plains

Abstract The Red Sea (RS) has a high evaporation rate, exceeding 2 m of water per year. The water vapor is transported from the shorelines by sea breezes as far as 200 km landward. Relative humidity in the vicinity of the RS exceeds 80% in summer. Nevertheless, precipitation is scarce in most of the Arabian RS coastal plain. In this work we use the Weather Research and Forecasting (WRF) regional model to assess how deliberate changes (geoengineering) in the surface albedo or conversion of bare land to wide-leaf forests over a vast coastal plain region affect precipitation over the Arabian RS coast. Our simulations show that geoengineering of land surface characteristics perturbs coastal circulation; alters temperature, moisture, and momentum exchange between the land surface and atmosphere; and changes the breeze intensity, cloud cover, and eventually the amount of precipitation. We find that extended afforestation and increased surface albedo are not effective in triggering rainfall over the RS coastal plains. Conversely, decreasing surface albedo to 0.2, assuming installation of solar panels over the coastal plains, increases surface air temperature by 1–2 K, strengthens horizontal surface temperature differences between sea and land, intensifies breezes, increases water vapor mixing ratio in the boundary layer above 3 km by about 0.5 g kg−1, enhances vertical mixing within the planetary boundary layer, and generates 1.5 Gt of extra rainwater, equivalent to the annual consumption of five million people. Thus, this form of regional land surface geoengineering, along with advanced methods of collection and underground storage of freshwater, provides a feasible solution to mitigation of the existing water crisis in the arid coastal regions.

Lab-Controlled Experimental Evaluation of Heat-Reflective Coatings by Increasing Surface Albedo for Cool Pavements in Urban Areas

Many studies were conducted to find possible strategies for reducing the urban heat island (UHI) effect during the hot summer months. One of the largest contributors to UHI is the role that paved surfaces play in the warming of urban areas. Solar-reflective cool pavements stay cooler in the sun than traditional pavements. Pavement reflectance can be enhanced by using a reflective surface coating. The use of heat-reflective coatings to combat the effects of pavements on UHI was pre-viously studied but no consistent conclusions were drawn. To find a conclusive solution, this work focuses on the abilities of heat-reflective pavement coatings to reduce UHI in varying weather conditions. Within this context, both concrete and asphalt samples were subject to a series of per-formance tests when applied to a heat-reflective coating, under the influence of normal, windy, and humid conditions. During these tests, the samples were heated with a halogen lamp and the surface temperature profile was measured using an infrared thermal camera. The air temperature was recorded with a thermometer, and the body temperature at multiple depths of the samples was measured using thermocouples. The results from these tests show that the effectiveness of the heat-reflective coating varies under different weather conditions. For instance, the coated samples were about 1 °C cooler for concrete and nearly 5 °C cooler for asphalt, on average. However, this temperature difference was reduced significantly under windy conditions. As such, the findings from this work conclude that the heat-reflective coatings can effectively cool down the pavement by increasing the surface albedo, and thus might be a viable solution to mitigate UHI impacts in the city/urban areas.

STEMMUS-UEB v1.0.0: integrated modeling of snowpack and soil water and energy transfer with three complexity levels of soil physical processes

Abstract. A snowpack has a profound effect on the hydrology and surface energy conditions of an area through its effects on surface albedo and roughness and its insulating properties. The modeling of a snowpack, soil water dynamics, and the coupling of the snowpack and underlying soil layer has been widely reported. However, the coupled liquid–vapor–air flow mechanisms considering the snowpack effect have not been investigated in detail. In this study, we incorporated the snowpack effect (Utah energy balance snowpack model, UEB) into a common modeling framework (Simultaneous Transfer of Energy, Mass, and Momentum in Unsaturated Soils with Freeze-Thaw, STEMMUS-FT), i.e., STEMMUS-UEB. It considers soil water and energy transfer physics with three complexity levels (basic coupled, advanced coupled water and heat transfer, and finally explicit consideration of airflow, termed BCD, ACD, and ACD-air, respectively). We then utilized in situ observations and numerical experiments to investigate the effect of snowpack on soil moisture and heat transfer with the abovementioned model complexities. Results indicated that the proposed model with snowpack can reproduce the abrupt increase of surface albedo after precipitation events while this was not the case for the model without snowpack. The BCD model tended to overestimate the land surface latent heat flux (LE). Such overestimations were largely reduced by ACD and ACD-air models. Compared with the simulations considering snowpack, there is less LE from no-snow simulations due to the neglect of snow sublimation. The enhancement of LE was found after winter precipitation events, which is sourced from the surface ice sublimation, snow sublimation, and increased surface soil moisture. The relative role of the mentioned three sources depends on the timing and magnitude of precipitation and the pre-precipitation soil hydrothermal regimes. The simple BCD model cannot provide a realistic partition of mass transfer flux. The ACD model, with its physical consideration of vapor flow, thermal effect on water flow, and snowpack, can identify the relative contributions of different components (e.g., thermal or isothermal liquid and vapor flow) to the total mass transfer fluxes. With the ACD-air model, the relative contribution of each component (mainly the isothermal liquid and vapor flows) to the mass transfer was significantly altered during the soil thawing period. It was found that the snowpack affects not only the soil surface moisture conditions (surface ice and soil water content in the liquid phase) and energy-related states (albedo, LE) but also the transfer patterns of subsurface soil liquid and vapor flow.

Assessing the performance of geothermal pavement constructed using demolition wastes by experimental and CFD simulation techniques

This paper studies the possibility of harnessing renewable thermal energy from road pavement constructed using construction and demolition (C&D) materials in Australia. This research study aims to evaluate the efficiency and heat gain capacity of geothermal pavement system with constant inlet water temperature and closed-loop approach. An experimental model was developed using copper pipe and C&D materials as pavement structure and the tests were conducted during summer-time in Melbourne, Australia. Numerical computational fluid dynamic (CFD) simulation was used to study the capacity of simulation in modeling heat transfer and the temperature field in the geothermal pavement. The results showed that the geothermal pavement system with constant inlet water temperature can gain almost 450 (kJ/m2) of thermal energy while subsequently decreasing the surface temperature of the pavement, hence increasing the service life of the geothermal pavement. The pipe burial depth of 40 mm to 60 mm was found to lead to the best efficiency of the geothermal pavement. The thermal efficiency of the geothermal pavement could increase and reach 25% during the day for a geothermal pavement system with constant inlet water temperature. Thermal conductivity and surface albedo would also increase the thermal efficiency of the system. Results showed that increasing thermal conductivity from 1 (W/m.K) to 3.5 (W/m.K) led to an increase in thermal efficiency from 20% to 34%. Also, increasing surface albedo magnitude equal to 0.1 would decrease efficiency by approximately 5%. The experimental results of the closed-loop geothermal pavement system demonstrated that the maximum hourly heat gain capacity of the system was 1000 (kJ/m2), which is twice higher than this value for a system with a constant inlet water temperature. The thermal efficiency of geothermal pavement system increased to its peak value equal to 30% throughout the day.

Northwestward shift of the northern boundary of the East Asian summer monsoon during the mid-Holocene caused by orbital forcing and vegetation feedbacks

The East Asian summer monsoon (EASM) northern boundary is a critical indicator of EASM variations. Movement of the boundary is modulated by both the EASM and the mid-latitude westerlies. Here, we use the Earth system model EC-Earth to quantify the contribution of orbital forcing and vegetation feedbacks in modulating the movement of EASM northern boundary. The results show that the simulated EASM northern boundary during the mid-Holocene shifts by a maximum of ∼213 km northwestward due to orbital forcing. When the model was coupled with a dynamic vegetation module LPJ-GUESS, the northern boundary shifts further northwestward by a maximum of ∼90 km, indicating the importance of vegetation feedbacks.During the mid-Holocene, temperature increased in the mid-latitude during the boreal summer due to insolation, leading to increased meridional air temperature differences (MTDs) over the region north of 45°N and to decreased MTDs to the south. The changes in the temperature gradient weakened the East Asian Westly Jet (EAWJ) and displaced it northward, resulting in an earlier transition of the Meiyu stage and a more prolonged Midsummer stage. The northward movement of EAWJ, combined with the enhanced southerly moisture flow from South China, caused more precipitation in North China and eventually to a northwestward shift of the northern boundary of the EASM. The coupled dynamic vegetation module LPJ-GUESS simulated more grassland and less forest over Northeast Asia during the mid-Holocene. The increased surface albedo tended to lower the temperature in the region, and further enhanced the MTDs in mid-latitude East Asia, leading to the further northward movement of the EAWJ and a northwestward shift of the EASM northern boundary. Although the simulated vegetation distribution in several regions may be not accurate, it reflects the substantial contribution of climate-vegetation interaction on modulating the EASM.

Impacts of forest loss on local climate across the conterminous United States: Evidence from satellite time-series observations

Forest disturbances alter land biophysics. Their impacts on local climate and land surface temperature (LST) cannot be directly measured by comparing pre- and post-disturbance observations of the same site over time (e.g., due to confounding such as background climate fluctuations); a common remedy is to compare spatially-adjacent undisturbed sites instead. This space-for-time substitution ignores the inherent biases in vegetation between two paired sites, interannual variations, and temporal dynamics of forest recovery. Besides, there is a lack of observation-based analyses at fine spatial resolutions capable of capturing spatial heterogeneity of small-scale forest disturbances. To address these limitations, here we report new satellite analyses on local climate impacts of forest loss at 30 m resolution. Our analyses combined multiple long-term satellite products (e.g., albedo and evapotranspiration [ET]) at 700 sites across major climate zones in the conterminous United States, using time-series trend and changepoint detection methods. Our method helped isolate the biophysical changes attributed to disturbances from those attributed to climate backgrounds and natural growth. On average, forest loss increased surface albedo, decreased ET, and reduced leaf area index (LAI). Net annual warming—an increase in LST—was observed after forest loss in the arid/semiarid, northern, tropical, and temperate regions, dominated by the warming from decreased ET and attenuated by the cooling from increased albedo. The magnitude of post-disturbance warming was related to precipitation; climate zones with greater precipitation showed stronger and longer warming. Reduction in leaf or LAI was larger in evergreen than deciduous forests, but the recovery in LAI did not always synchronize with those of albedo and ET. Overall, this study presents new evidence of biophysical effects of forest loss on LST at finer spatial resolutions; our time-series method can be further leveraged to derive local policy-relevant ecosystem climate regulation metrics or support model-based climate-biosphere studies.

Quantitative Analysis of Terrain Reflected Solar Radiation in Snow‐Covered Mountains: A Case Study in Southeastern Tibetan Plateau

AbstractTerrain reflected solar radiation in snow‐covered mountains is nonnegligible in investigations of the energy budget. However, it has so far not been investigated thoroughly, especially with regard to the influence of snow cover. Several parameterization approaches have been raised but not yet evaluated in a more uniform and quantitative manner. Based on the three‐dimensional (3‐D) ray‐tracing simulation, we explored the temporal and spatial characteristics of the terrain reflected radiation in 15 domains on the southeastern Tibetan Plateau, and comprehensively evaluated different parameterization approaches. The results indicate that the ratio of reflected radiation to total daily radiation ranges from 0.25% to 10.85% at the scale of 5 × 5 km2 in a winter clear day, and it is 57% higher at noon in spring and autumn due to the higher snow cover fraction. Snow cover not only enhances the magnitude of reflected radiation by increasing surface albedo but also changes the spatial distribution pattern of radiation in partial snow‐covered mountains, causing more snow‐reflected radiation to be received by the surrounding surfaces. Three forms of terrain configuration factors in common parameterization approaches were evaluated by the ray‐tracing model. The complementary of sky view factor shows good consistency with ray‐tracing model at domain‐averaged scales, with a root mean square error (RMSE) of 2.55 (14%) W/m2, while the other two both underestimate the radiation. The parameterization approach involving the multi‐reflection shows better performance with the normalized RMSE decreasing by 5%. However, the uncertainty of it increases with the surface spatial heterogeneity caused by the partial snow cover, especially at high resolution.