scholarly journals Radiative forcing bias of surface albedo modifications linked to simulated forest cover changes at northern latitudes

2014 ◽  
Vol 11 (12) ◽  
pp. 17339-17360
Author(s):  
R. M. Bright ◽  
G. Myhre ◽  
R. Astrup ◽  
C. Antón-Fernández ◽  
A. H. Strømman
Keyword(s):  
Land Surface ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Forest Cover ◽  
Climate Models ◽  
Land Use Land Cover ◽  
Radiative Forcings ◽  
Northern Latitudes ◽  
Forest Cover Changes ◽  
Model Improvement

Abstract. Simulated land use/land cover change (LULCC) radiative forcings (RF) from changes in surface albedo (Δα) predicted by land surface schemes of six leading climate models were compared to those based on daily MODIS retrievals for three regions in Norway and for three winter–spring seasons. As expected, the magnitude and sign of the albedo biases varied considerably for forests; unexpectedly, however, biases of equal magnitude were evident in predictions at open area sites. The latter were mostly positive and exacerbated the strength of vegetation masking effects and hence the simulated LULCC Δα RF. RF bias was considerably small across models (-0.08 ± 0.04 W m-2; 21 ± 11%); 4 of 6 models had normalized mean absolute errors less than 20% (3-year regional mean). Identifying systematic sources of the albedo prediction biases proved challenging, although for some schemes clear sources were identified. Our study should provide some reassurance that model improvement efforts of recent years are leading to enhanced LULCC climate predictions.

scholarly journals Radiative forcing bias of simulated surface albedo modifications linked to forest cover changes at northern latitudes

2015 ◽  
Vol 12 (7) ◽  
pp. 2195-2205 ◽  
Author(s):  
R. M. Bright ◽  
G. Myhre ◽  
R. Astrup ◽  
C. Antón-Fernández ◽  
A. H. Strømman
Keyword(s):  
Radiative Forcing ◽  
Surface Albedo ◽  
Forest Cover ◽  
Climate Models ◽  
Open Area ◽  
Data Set ◽  
Radiative Forcings ◽  
Open Forest ◽  
Northern Latitudes ◽  
Analytical Time

Abstract. In the presence of snow, the bias in the prediction of surface albedo by many climate models remains difficult to correct due to the difficulties of separating the albedo parameterizations from those describing snow and vegetation cover and structure. This can be overcome by extracting the albedo parameterizations in isolation, by executing them with observed meteorology and information on vegetation structure, and by comparing the resulting predictions to observations. Here, we employ an empirical data set of forest structure and daily meteorology for three snow cover seasons and for three case regions in boreal Norway to compute and evaluate predicted albedo to those based on daily MODIS retrievals. Forest and adjacent open area albedos are subsequently used to estimate bias in top-of-the-atmosphere (TOA) radiative forcings (RF) from albedo changes (Δα, Open–Forest) connected to land use and land cover changes (LULCC). As expected, given the diversity of approaches by which snow masking by tall-statured vegetation is parameterized, the magnitude and sign of the albedo biases varied considerably for forests. Large biases at the open sites were also detected, which was unexpected given that these sites were snow-covered throughout most of the analytical time period, therefore eliminating potential biases linked to snow-masking parameterizations. Biases at the open sites were mostly positive, exacerbating the strength of vegetation masking effects and hence the simulated LULCC Δα RF. Despite the large biases in both forest and open area albedos by some schemes in some months and years, the mean Δα RF bias over the 3-year period (November–May) was considerably small across models (−2.1 ± 1.04 Wm−2; 21 ± 11%); four of six models had normalized mean absolute errors less than 20%. Identifying systematic sources of the albedo prediction biases proved challenging, although for some schemes clear sources were identified.

scholarly journals Complexity of Snow Schemes in a Climate Model and Its Impact on Surface Energy and Hydrology

2012 ◽  
Vol 13 (2) ◽  
pp. 521-538 ◽  
Author(s):  
Emanuel Dutra ◽  
Pedro Viterbo ◽  
Pedro M. A. Miranda ◽  
Gianpaolo Balsamo
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Climate Models ◽  
Climate Model ◽  
Single Layer ◽  
Atmospheric Temperature ◽  
Soil Freezing ◽  
Near Surface ◽  
Northern Latitudes ◽  
Tightly Coupled

Abstract Three different complexity snow schemes implemented in the ECMWF land surface scheme Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) are evaluated within the EC-EARTH climate model. The snow schemes are (i) the original HTESSEL single-bulk-layer snow scheme, (ii) a new snow scheme in operations at ECMWF since September 2009, and (iii) a multilayer version of the previous. In offline site simulations, the multilayer scheme outperforms the single-layer schemes in deep snowpack conditions through its ability to simulate sporadic melting events thanks to the lower thermal inertial of the uppermost layer. Coupled atmosphere–land/snow simulations performed by the EC-EARTH climate model are validated against remote sensed snow cover and surface albedo. The original snow scheme has a systematic early melting linked to an underestimation of surface albedo during spring that was partially reduced with the new snow schemes. A key process to improve the realism of the near-surface atmospheric temperature and at the same time the soil freezing is the thermal insulation of the snowpack (tightly coupled with the accuracy of snow mass and density simulations). The multilayer snow scheme outperforms the single-layer schemes in open deep snowpack (such as prairies or tundra in northern latitudes) and is instead comparable in shallow snowpack conditions. However, the representation of orography in current climate models implies limitations for accurately simulating the snowpack, particularly over complex terrain regions such as the Rockies and the Himalayas.

scholarly journals Inferring past land use-induced changes in surface albedo from satellite observations: a useful tool to evaluate model simulations

2013 ◽  
Vol 10 (3) ◽  
pp. 1501-1516 ◽  
Author(s):  
J. P. Boisier ◽  
N. de Noblet-Ducoudré ◽  
P. Ciais
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Surface Albedo ◽  
Climate Models ◽  
Vegetation Type ◽  
Seasonal Pattern ◽  
Satellite Observations ◽  
Secondary Importance ◽  
Past Land Use

Abstract. Regional cooling resulting from increases in surface albedo has been identified in several studies as the main biogeophysical effect of past land use-induced land cover changes (LCC) on climate. However, the amplitude of this effect remains quite uncertain due to, among other factors, (a) uncertainties in the extent of historical LCC and, (b) differences in the way various models simulate surface albedo and more specifically its dependency on vegetation type and snow cover. We derived monthly albedo climatologies for croplands and four other land cover types from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. We then reconstructed the changes in surface albedo between preindustrial times and present-day by combining these climatologies with the land cover maps of 1870 and 1992 used by seven land surface models (LSMs) in the context of the LUCID ("Land Use and Climate: identification of robust Impacts") intercomparison project. These reconstructions show surface albedo increases larger than 10% (absolute) in winter, and larger than 2% in summer between 1870 and 1992 over areas that experienced intense deforestation in the northern temperate regions. The historical surface albedo changes estimated with MODIS data were then compared to those simulated by the various climate models participating in LUCID. The inter-model mean albedo response to LCC shows a similar spatial and seasonal pattern to the one resulting from the MODIS-based reconstructions, that is, larger albedo increases in winter than in summer, driven by the presence of snow. However, individual models show significant differences between the simulated albedo changes and the corresponding reconstructions, despite the fact that land cover change maps are the same. Our analyses suggest that the primary reason for those discrepancies is how LSMs parameterize albedo. Another reason, of secondary importance, results from differences in their simulated snow extent. Our methodology is a useful tool not only to infer observations-based historical changes in land surface variables impacted by LCC, but also to point out deficiencies of the models. We therefore suggest that it could be more widely developed and used in conjunction with other tools in order to evaluate LSMs.

scholarly journals Total aerosol effect: radiative forcing or radiative flux perturbation?

2009 ◽  
Vol 9 (6) ◽  
pp. 25633-25661 ◽  
Author(s):  
U. Lohmann ◽  
L. Rotstayn ◽  
T. Storelvmo ◽  
A. Jones ◽  
S. Menon ◽  
...  
Keyword(s):  
Global Warming ◽  
Radiative Forcing ◽  
Climate Models ◽  
Radiative Flux ◽  
Radiative Forcings ◽  
Microphysical Properties ◽  
Aerosol Effect ◽  
Rain Formation ◽  
Aerosol Radiative ◽  
Flux Perturbation

Abstract. Uncertainties in aerosol radiative forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. In former assessments of aerosol radiative forcings, these effects have not been quantified. Also, with global aerosol-climate models simulating interactively aerosols and cloud microphysical properties, a quantification of the aerosol forcings in the traditional way is difficult to properly define. Here we argue that fast feedbacks should be included because they act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Based on our results, we recommend RFP as a valid option to compare different forcing agents, and to compare the effects of particular forcing agents in different models.

scholarly journals Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

2019 ◽  
Vol 10 (2) ◽  
pp. 333-345 ◽  
Author(s):  
Lennert B. Stap ◽  
Peter Köhler ◽  
Gerrit Lohmann
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Co2 Concentration ◽  
Global Temperature ◽  
Maximum Temperature ◽  
Radiative Forcings ◽  
The Impact ◽  
The Last Glacial

Abstract. The equilibrium climate sensitivity (ECS) of climate models is calculated as the equilibrium global mean surface air warming resulting from a simulated doubling of the atmospheric CO2 concentration. In these simulations, long-term processes in the climate system, such as land ice changes, are not incorporated. Hence, climate sensitivity derived from paleodata has to be compensated for these processes, when comparing it to the ECS of climate models. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the prevailing approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI] that relates the impact of land ice changes on global temperature to that of CO2 changes in our calculation of climate sensitivity from paleodata. We apply our refined approach to a proxy-inferred paleoclimate dataset, using ε[LI]=0.45-0.20+0.34 based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum temperature anomaly. The implemented ε[LI] is smaller than unity, meaning that per unit of radiative, forcing the impact on global temperature is less strong for land ice changes than for CO2 changes. Consequently, our obtained ECS estimate of 5.8±1.3 K, where the uncertainty reflects the implemented range in ε[LI], is ∼50 % higher than when differences in efficacy are not considered.

scholarly journals Spatiotemporal Variability of Land Surface Albedo over the Tibet Plateau from 2001 to 2019

2020 ◽  
Vol 12 (7) ◽  
pp. 1188
Author(s):  
Xingwen Lin ◽  
Jianguang Wen ◽  
Qinhuo Liu ◽  
Dongqin You ◽  
Shengbiao Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Land Cover ◽  
Snow Cover ◽  
Land Surface ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Tibet Plateau ◽  
Land Cover Types ◽  
Yearly Average

As an essential climate variable (ECV), land surface albedo plays an important role in the Earth surface radiation budget and regional or global climate change. The Tibetan Plateau (TP) is a sensitive environment to climate change, and understanding its albedo seasonal and inter-annual variations is thus important to help capture the climate change rules. In this paper, we analyzed the large-scale spatial patterns, temporal trends, and seasonal variability of land surface albedo overall the TP, based on the moderate resolution imaging spectroradiometer (MODIS) MCD43 albedo products from 2001 to 2019. Specifically, we assessed the correlations between the albedo anomaly and the anomalies of normalized difference vegetation index (NDVI), the fraction of snow cover (snow cover), and land surface temperature (LST). The results show that there are larger albedo variations distributed in the mountainous terrain of the TP. Approximately 10.06% of the land surface is identified to have been influenced by the significant albedo variation from the year 2001 to 2019. The yearly averaged albedo was decreased significantly at a rate of 0.0007 (Sen’s slope) over the TP. Additionally, the yearly average snow cover was decreased at a rate of 0.0756. However, the yearly average NDVI and LST were increased with slopes of 0.0004 and 0.0253 over the TP, respectively. The relative radiative forcing (RRF) caused by the land cover change (LCC) is larger than that caused by gradual albedo variation in steady land cover types. Overall, the RRF due to gradual albedo variation varied from 0.0005 to 0.0170 W/m2, and the RRF due to LCC variation varied from 0.0037 to 0.0243 W/m2 during the years 2001 to 2019. The positive RRF caused by gradual albedo variation or the LCC can strengthen the warming effects in the TP. The impact of the gradual albedo variations occurring in the steady land cover types was very low between 2001 and 2019 because the time series was short, and it therefore cannot be neglected when examining radiative forcing for a long time series regarding climate change.

scholarly journals Coupling Diffuse Sky Radiation and Surface Albedo

2005 ◽  
Vol 62 (7) ◽  
pp. 2580-2591 ◽  
Author(s):  
Bernard Pinty ◽  
Alessio Lattanzio ◽  
John V. Martonchik ◽  
Michel M. Verstraete ◽  
Nadine Gobron ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Land Surface ◽  
Surface Albedo ◽  
Climate Models ◽  
Diffuse Radiation ◽  
Atmospheric Model ◽  
Time Of Day ◽  
Mathematical Form ◽  
Diffuse Solar Radiation ◽  
Atmospheric Scattering

Abstract New satellite instruments have been delivering a wealth of information regarding land surface albedo. This basic quantity describes what fraction of solar radiation is reflected from the earth’s surface. However, its concept and measurements have some ambiguity resulting from its dependence on the incidence angles of both the direct and diffuse solar radiation. At any time of day, a surface receives direct radiation in the direction of the sun, and diffuse radiation from the various other directions in which it may have been scattered by air molecules, aerosols, and cloud droplets. This contribution proposes a complete description of the distribution of incident radiation with angles, and the implications in terms of surface albedo are given in a mathematical form, which is suitable for climate models that require evaluating surface albedo many times. The different definitions of observed albedos are explained in terms of the coupling between surface and atmospheric scattering properties. The analytical development in this paper relates the various quantities that are retrieved from orbiting platforms to what is needed by an atmospheric model. It provides a physically simple and practical approach to evaluation of land surface albedo values at any condition of sun illumination irrespective of the current range of surface anisotropic conditions and atmospheric aerosol load. The numerical differences between the various definitions of albedo for a set of typical atmospheric and surface scattering conditions are illustrated through numerical computation.

scholarly journals Intercomparison of the Surface Energy Partitioning in CMIP5 Simulations

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 602 ◽  
Author(s):  
Yang ◽  
Wang ◽  
Huang
Keyword(s):  
Soil Moisture ◽  
Surface Energy ◽  
Land Surface ◽  
Radiative Forcing ◽  
Climate Models ◽  
Water Cycle ◽  
Potential Evapotranspiration ◽  
Sensible Heat Flux ◽  
Coupled Model ◽  
Energy Partitioning

The warming climate significantly modifies the global water cycle. Global evapotranspiration has increased over the past decades, yet climate models agree on the drying trend of land surface. In this study, we conducted an intercomparison analysis of the surface energy partitioning across Coupled Model Intercomparison Phase 5 (CMIP5) simulations and evaluated its behaviour with surface temperature and soil moisture anomalies, against the theoretically derived thermodynamic formula. Different responses over land and sea surfaces to elevated greenhouse gas emissions were found. Under the Representative Concentration Pathway of +8.5 W m−2 (RCP8.5) warming scenario, the multi-model mean relative efficiency anomaly from CMIP5 simulations is 3.83 and −0.12 over global sea and land, respectively. The significant anomaly over sea was captured by the thermodynamic solution based on the principle of maximum entropy production, with a mean relative error of 14.6%. The declining trend over land was also reproduced, but an accurate prediction of its small anomaly will require the inclusions of complex physical processes in future work. Despite increased potential evapotranspiration under rising temperatures, both CMIP5 simulations and thermodynamic principles suggest that the soil moisture-temperature feedback cannot support long-term enhanced evapotranspiration at the global scale. The dissipation of radiative forcing eventually shifts towards sensible heat flux and accelerates the warming over land, especially over South America and Europe.

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