Albedo climatology for European land surfaces retrieved from AVHRR data (1990–2014) and its spatial and temporal analysis from green‐up to vegetation senescence

Abstract

Satellite‐based, long‐term records of surface albedo characterization that accurately capture spatial and temporal patterns are essential to develop climate models and to monitor the impact of land use changes on the terrestrial energy and water balance. This study presents the first Bidirectional Reflectance Distribution Function (BRDF) and albedo data set derived from the Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage reflectance data acquired on board National Oceanic and Atmospheric Administration and Meteorological Operational platforms from 1990 to 2014 over Europe. The objectives of this paper are to describe the data set's surface albedo climatology and anomalies in the visible, near‐infrared, and shortwave broadbands for the growing season months of May to September in order to facilitate utilization of the data by the climate modeling communities. The results demonstrate that the AVHRR BRDF and albedo data have temporal and spatial patterns that are appropriate for the underlying predominant land cover type and accurately reflect the associated climate variation. Visible and near‐infrared broadband albedo anomalies are found to be contrasting in most years, and their spatial distributions depict responses of vegetation to climate events (e.g., heat waves). Visible albedo of crops and near‐infrared albedo of pastures show a higher interannual variation than respective albedos of other snow‐free land covers, while the interannual standard deviations are found to be lower than 0.015. Our findings indicate the importance of taking into account the spectrally distinct variability of surface albedo when analyzing its complex spatiotemporal dynamics in climate‐related research.

Total column water vapor retrieval for GOME-2 visible blue observations

“…Sütterlin et al (2016) analyzed the Advanced Very High Resolution Radiometer (AVHRR) BRDF product from 1990 -2014 and the result shows the inter-annual variability of the land surface albedo is in general less than 0.01 for snow-free vegetation cover but possibly larger than 0.06 for regions covered by snow or ice. We performed a sensitivity analysis to quantify the uncertainty TCWV caused by inter-annual variation of albedo by using the numbers provided in Sütterlin et al (2016). The result shows that the uncertainty of TCWV due to inter-annual variations of surface albedo is in general <2 % while the uncertainty increased to ∼9 % for areas covered by snow and ice.…”

The Spatial-temporal Variation of Land Surface Albedo in Hengshui During 2001-2015 by Blending Landsat and GLASS Data

“…(6) In order to reflect the temporal change trend of the albedo, we first calculated the anomaly of the surface albedo. Anomaly is the difference between the albedo of one scene and the average image of the corresponding phase, which reveals the variation of the surface albedo in the study area, relative to the multi-year average, and eliminates the effects of seasonal changes [22]. It can be described by: (7) ∆α t , α t represents the anomaly, surface albedo in phase i (i=1,2,3,...,644) in the time series of all images from 2001 to 2015, and is average albedo of the same phase t(t=1,2,3,...,46) from 2001-2015.…”

“…Remote sensing has the capability of providing consistent estimates of albedo at regular temporal intervals [22]. With the development of satellite observation and information processing technologies, the use of remote sensing technology to obtain the albedo has been widely used [23].…”