Global high-resolution land surface albedo monthly maps from NOAA/AVHRR for use in climate models

Abstract. Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980–2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

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

Biogeosciences ◽

10.5194/bg-10-1501-2013 ◽

2013 ◽

Vol 10 (3) ◽

pp. 1501-1516 ◽

Cited By ~ 29

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.

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Time Series High-Resolution Land Surface Albedo Estimation Based on the Ensemble Kalman Filter Algorithm

Remote Sensing ◽

10.3390/rs11070753 ◽

2019 ◽

Vol 11 (7) ◽

pp. 753 ◽

Cited By ~ 4

Author(s):

Guodong Zhang ◽

Hongmin Zhou ◽

Changjing Wang ◽

Huazhu Xue ◽

Jindi Wang ◽

...

Keyword(s):

Time Series ◽

Kalman Filter ◽

High Resolution ◽

Spatial Resolution ◽

Ensemble Kalman Filter ◽

Land Surface ◽

Surface Albedo ◽

Data Sets ◽

Broadleaf Forest ◽

Kalman Filter Algorithm

Continuous, long-term sequence, land surface albedo data have crucial significance for climate simulations and land surface process research. Sensors such as the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer (VIIRS) provide global albedo product data sets with a spatial resolution of 500 m over long time periods. There is demand for new high-resolution albedo data for regional applications. High-resolution observations are often unavailable due to cloud contamination, which makes it difficult to obtain time series albedo estimations. This paper proposes an “amalgamation albedo“ approach to generate daily land surface shortwave albedo with 30 m spatial resolution using Landsat data and the MODIS Bidirectional Reflectance Distribution Functions (BRDF)/Albedo product MCD43A3 (V006). Historical MODIS land surface albedo products were averaged to obtain an albedo estimation background, which was used to construct the albedo dynamic model . The Thematic Mapper (TM) albedo derived via direct estimation approach was then introduced to generate high spatial-temporal resolution albedo data based on the Ensemble Kalman Filter algorithm (EnKF). Estimation results were compared to field observations for cropland, deciduous broadleaf forest, evergreen needleleaf forest, grassland, and evergreen broadleaf forest domains. The results indicated that for all land cover types, the estimated albedos coincided with ground measurements at a root mean squared error (RMSE) of 0.0085–0.0152. The proposed algorithm was then applied to regional time series albedo estimation; the results indicated that it captured spatial and temporal variation patterns for each site. Taken together, our results suggest that the amalgamation albedo approach is a feasible solution to generate albedo data sets with high spatio-temporal resolution.

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

Journal of Hydrometeorology ◽

10.1175/jhm-d-11-072.1 ◽

2012 ◽

Vol 13 (2) ◽

pp. 521-538 ◽

Cited By ~ 43

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.

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Coupling Diffuse Sky Radiation and Surface Albedo

Journal of the Atmospheric Sciences ◽

10.1175/jas3479.1 ◽

2005 ◽

Vol 62 (7) ◽

pp. 2580-2591 ◽

Cited By ~ 49

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.

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TopoSCALE: deriving surface fluxes from gridded climate data

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-3381-2013 ◽

2013 ◽

Vol 6 (2) ◽

pp. 3381-3426 ◽

Cited By ~ 1

Author(s):

J. Fiddes ◽

S. Gruber

Keyword(s):

High Resolution ◽

Land Surface ◽

Climate Models ◽

Good Description ◽

Longwave Radiation ◽

Surface Fluxes ◽

Swiss Alps ◽

Climate Data ◽

Heterogeneous Terrain ◽

Reference Methods

Abstract. Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by e.g. topography and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that leverages the good description of the atmospheric column provided by climate models, together with high resolution DEM's, to derive a consistent topography-based, scaling of coarse grid climate variables to fine-scale. We test the method together with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure-levels: air temperature, relative humidity, wind speed and incoming longwave radiation. It is expected that this method can be used to improve inputs to numerical simulations in complex and/or remote terrain especially when statistical methods are not possible due to lack of observations i.e. remote areas or future periods.

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Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

10.5194/hess-2016-349 ◽

2016 ◽

Cited By ~ 3

Author(s):

Pere Quintana-Seguí ◽

Marco Turco ◽

Sixto Herrera ◽

Gonzalo Miguez-Macho

Keyword(s):

High Resolution ◽

Land Surface ◽

Climate Models ◽

Hydrological Cycle ◽

Interpolation Method ◽

Surface Model ◽

Low Resolution ◽

Skill Scores ◽

Precipitation Events

Abstract. Offline Land-Surface Model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/80–2013/14). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate Regional Climate Models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The results show that SAFRAN and Spain02 have very similar skill scores, although the later has better scores in general. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well, in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

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Towards a Climatology of Australian Land Surface Albedo for use in Climate Models

Advances in Global Change Research - Remote Sensing and Climate Modeling: Synergies and Limitations ◽

10.1007/0-306-48149-9_4 ◽

2001 ◽

pp. 69-84

Author(s):

Ian F. Grant

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Climate Models

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Understanding differences in land-atmosphere interactions between pan-European convection-permitting and parametrised climate models

10.5194/egusphere-egu21-14859 ◽

2021 ◽

Author(s):

Kate Halladay ◽

Segolene Berthou ◽

Elizabeth Kendon

Keyword(s):

Soil Moisture ◽

High Resolution ◽

Eastern Europe ◽

Land Surface ◽

Climate Models ◽

Climate Projections ◽

Land Cover Type ◽

Sensitivity Tests ◽

Soil Hydraulics ◽

Runoff Model

<p>Increasingly, we are using high-resolution convection-permitting models for climate projections but these models are less well understood in terms of the interaction between soil moisture, precipitation and evapotranspiration. The work was motivated by the discovery of warm, dry biases in summer in the 2.2 km convection-permitting model over France and eastern Europe compared to the 12 km convection-parametrised model that were associated with drier soils. We analyse several 12 km and 2.2 km versions of the Met Office Unified Model including sensitivity tests relating to soil hydraulics, land cover type and runoff model. We conduct similar tests using the land surface only to compare results between online and offline versions as the absence of some feedbacks can also produce differences.&#160;&#160;</p>

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