An Algorithm for the Retrieval of High Temporal-Spatial Resolution Shortwave Albedo from Landsat-8 Surface Reflectance and MODIS BRDF

Variations in surface physicochemical properties and spatial structures can prominently transform surface albedo which conversely influence surface energy balances and global climate, making it crucial to continuously monitor and quantify surface dynamics at fine scales. Here, we made two improvements to propose an algorithm for the simultaneous retrieval of 30-m Landsat albedo, based on the coupling of Landsat-8 and MODIS BRDF. First, two kinds of prior knowledge were added to disaggregate BRDF, including the Anisotropic Flat Index (AFX) and the Albedo-to-Nadir reflectance ratio (AN ratio), from MODIS scales into Landsat scales. Second, a simplified data fusion method was used to simulate albedo for the same, subsequent, or antecedent dates. Finally, we validated the reliability and correlations of the algorithm at six sites of the Surface Radiation (SURFRAD) budget network and intercompared the results with another algorithm called the ‘concurrent approach’. The results showed that the proposed algorithm had favorable usability and robustness, with a root mean square error (RMSE) of 0.015 (8%) and a mean bias of −0.005; while the concurrent approach had a RMSE of 0.026 (14%) and a mean bias of −0.018. The results emphasized that the proposed algorithm has captured subtle changes in albedo over a 16-day period.

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Validation of Space-Based Albedo Products from Upscaled Tower-Based Measurements Over Heterogeneous and Homogeneous Landscapes

Remote Sensing ◽

10.3390/rs12050833 ◽

2020 ◽

Vol 12 (5) ◽

pp. 833

Author(s):

Rui Song ◽

Jan-Peter Muller ◽

Said Kharbouche ◽

Feng Yin ◽

William Woodgate ◽

...

Keyword(s):

High Resolution ◽

Surface Albedo ◽

Spatial Scales ◽

Atmospheric Correction ◽

Landsat 8 ◽

Surface Reflectance ◽

Hemispherical Reflectance ◽

Land Surfaces ◽

Sentinel 2

Surface albedo is a fundamental radiative parameter as it controls the Earth’s energy budget and directly affects the Earth’s climate. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their continuous global coverage. However, space-based albedo products are often affected by errors in the atmospheric correction, multi-angular bi-directional reflectance distribution function (BRDF) modelling, as well as spectral conversions. To validate space-based albedo products, an in situ tower albedometer is often used to provide continuous “ground truth” measurements of surface albedo over an extended area. Since space-based albedo and tower-measured albedo are produced at different spatial scales, they can be directly compared only for specific homogeneous land surfaces. However, most land surfaces are inherently heterogeneous with surface properties that vary over a wide range of spatial scales. In this work, tower-measured albedo products, including both directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), are upscaled to coarse satellite spatial resolutions using a new method. This strategy uses high-resolution satellite derived surface albedos to fill the gaps between the albedometer’s field-of-view (FoV) and coarse satellite scales. The high-resolution surface albedo is generated from a combination of surface reflectance retrieved from high-resolution Earth Observation (HR-EO) data and moderate resolution imaging spectroradiometer (MODIS) BRDF climatology over a larger area. We implemented a recently developed atmospheric correction method, the Sensor Invariant Atmospheric Correction (SIAC), to retrieve surface reflectance from HR-EO (e.g., Sentinel-2 and Landsat-8) top-of-atmosphere (TOA) reflectance measurements. This SIAC processing provides an estimated uncertainty for the retrieved surface spectral reflectance at the HR-EO pixel level and shows excellent agreement with the standard Landsat 8 Surface Reflectance Code (LaSRC) in retrieving Landsat-8 surface reflectance. Atmospheric correction of Sentinel-2 data is vastly improved by SIAC when compared against the use of in situ AErosol RObotic NETwork (AERONET) data. Based on this, we can trace the uncertainty of tower-measured albedo during its propagation through high-resolution EO measurements up to coarse satellite scales. These upscaled albedo products can then be compared with space-based albedo products over heterogeneous land surfaces. In this study, both tower-measured albedo and upscaled albedo products are examined at Ground Based Observation for Validation (GbOV) stations (https://land.copernicus.eu/global/gbov/), and used to compare with satellite observations, including Copernicus Global Land Service (CGLS) based on ProbaV and VEGETATION 2 data, MODIS and multi-angle imaging spectroradiometer (MISR).

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Modelos da Produtividade Primária Bruta em área de floresta tropical em sazonalmente seca, usando dados reflectância da vegetação de caatinga

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v14.6.p3775-3784 ◽

2021 ◽

Vol 14 (6) ◽

pp. 3775

Author(s):

Joélia Natália Bezerra da Silva ◽

Josiclêda Domiciano Galvíncio ◽

Rodrigo De Queiroga Miranda ◽

Magna Soelma Besera de Moura

Keyword(s):

Tropical Forest ◽

Global Climate ◽

Gross Primary Production ◽

Landsat 8 ◽

Surface Reflectance ◽

Similar Data ◽

Seasonally Dry Tropical Forest ◽

Dry Tropical Forest ◽

Seasonally Dry ◽

The Face

R E S U M OArtigo recebido em XX/XX/2021 e aceito em XX/XX/2021 Os estudos da troca de energia nos ecossistemas fornecem informações importantes para a compreensão da Produtividade nos ecossistemas. A vegetação é um dos principais elementos da biosfera terrestre sendo responsável pela avaliação e funcionamento da atividade fotossintética bem como para as trocas de carbono entre os ecossistemas e a atmosfera. Neste contexto, a PPB é utilizada para avaliar, planejar e gerenciar os recursos ambientais frente as mudanças climáticas globais. Esse estudo tem por objetivo avaliar a Produção Primária Bruta no Bioma da Caatinga em Pernambuco. O estudo foi realizado na área de Floresta Tropical Sazonalmente Seca, a Caatinga no Estado de Pernambuco. Utilizou-se a refletância da superfície do produto (MOD09) a partir do MODIS/TERRA satélite do sensor, a refletância de superfície (SR) Landsat-8 e a reflectancia a superficie do fieldspec. Foram adquiridas nove cenas para o produto (MOD09), seis cenas para a refletância de superfície (SR) Landsat-8 e as mesmas datas das imagens foram utilizados os espectros de campo (filedspec). Foi realizada a seleção de amostras espectrais na imagem (espectros de referência), considerando o ponto espectral do local de coleta. Os modelos foram construídos a partir das combinações das bandas (ρ_350, ρ_351, ρ_352, ..., ρ_2500) suas transformações (ρ, 1/ρ, ln⁡(ρ), log_10⁡(ρ), √ρ, ρ^2, e^ρ). Os desempenhos dos modelos foram avaliados utilizando dois índices estatísticos, um de tendência (coeficiente de Pearson– r) e outro de desvio (Erro médio quadrático (RMSE– RMSE), e o PBIAS. Os resultados apontaram que os modelos calibrados demostraram bom desempenho na previsão com o uso das bandas do sensor OLI/Landsat 8 e do MODIS/Terra (MOD09GA). Models of Gross Primary Productivity in a seasonally dry tropical forest area using reflectance data from the Caatinga vegetationA B S T R A C TThe studies of energy exchange in ecosystems provide important information for the understanding of Productivity in ecosystems. Vegetation is one of the main elements of the terrestrial biosphere and is responsible for the evaluation and functioning of photosynthetic activity as well as for carbon exchanges between ecosystems and the atmosphere. In this context, a PPB is used to assess, plan and manage environmental resources in the face of global climate change. This study aims to evaluate a Gross Primary Production in the Caatinga Biome in Pernambuco. The study was carried out in the Seasonally Dry Tropical Forest, a Caatinga in the State of Pernambuco. Use the product's surface reflectance (MOD09) from the sensor's MODIS / TERRA satellite and the Landsat-8 surface reflectance (SR), nine scenes for the product (MOD09), six scenes for surface reflectance (SR) Landsat-8 and similar data with fieldspec. A selection of spectral members in the image (reference spectra) was carried out, considering the spectral point of the collection site. The models were built from the combinations of the bands (ρ_350, ρ_351, ρ_352, ..., ρ_2500) their transformations (ρ, 1/ρ, ln⁡(ρ), log_10⁡(ρ), √ρ, ρ^2, e^ρ). The performances of the models were taken using two statistical indices, one of trend (Pearson's coefficient - r) and another of deviation (Mean square error (RMSE - RMSE), and PBIAS. The results showed that the calibrated models showed good performance in prediction using the OLI / Landsat 8 and MODIS / Terra (MOD09GA) bands.Keyword: Remote sensing, FieldSpec®3, Caatinga

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Surface Albedo and Temperature Models for Surface Energy Balance Fluxes and Evapotranspiration Using SEBAL and Landsat 8 over Cerrado-Pantanal, Brazil

Sensors ◽

10.3390/s21217196 ◽

2021 ◽

Vol 21 (21) ◽

pp. 7196

Author(s):

Lucas Peres Angelini ◽

Marcelo Sacardi Biudes ◽

Nadja Gomes Machado ◽

Hatim M. E. Geli ◽

George Louis Vourlitis ◽

...

Keyword(s):

Energy Balance ◽

Surface Energy ◽

Surface Temperature ◽

Transition Region ◽

Surface Albedo ◽

Surface Energy Balance ◽

Landsat 8 ◽

Surface Reflectance ◽

Mato Grosso ◽

Better Than

The determination of the surface energy balance fluxes (SEBFs) and evapotranspiration (ET) is fundamental in environmental studies involving the effects of land use change on the water requirement of crops. SEBFs and ET have been estimated by remote sensing techniques, but with the operation of new sensors, some variables need to be parameterized to improve their accuracy. Thus, the objective of this study is to evaluate the performance of algorithms used to calculate surface albedo and surface temperature on the estimation of SEBFs and ET in the Cerrado-Pantanal transition region of Mato Grosso, Brazil. Surface reflectance images of the Operational Land Imager (OLI) and brightness temperature (Tb) of the Thermal Infrared Sensor (TIRS) of the Landsat 8, and surface reflectance images of the MODIS MOD09A1 product from 2013 to 2016 were combined to estimate SEBF and ET by the surface energy balance algorithm for land (SEBAL), which were validated with measurements from two flux towers. The surface temperature (Ts) was recovered by different models from the Tb and by parameters calculated in the atmospheric correction parameter calculator (ATMCORR). A model of surface albedo (asup) with surface reflectance OLI Landsat 8 developed in this study performed better than the conventional model (acon) SEBFs and ET in the Cerrado-Pantanal transition region estimated with asup combined with Ts and Tb performed better than estimates with acon. Among all the evaluated combinations, SEBAL performed better when combining asup with the model developed in this study and the surface temperature recovered by the Barsi model (Tsbarsi). This demonstrates the importance of an asup model based on surface reflectance and atmospheric surface temperature correction in estimating SEBFs and ET by SEBAL.

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MAPPING GLOBAL OCEAN SURFACE ALBEDO FROM SATELLITE OBSERVATIONS: MODELS, ALGORITHMS, AND DATASETS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-967-2018 ◽

2018 ◽

Vol XLII-3 ◽

pp. 967-970

Author(s):

X. Li ◽

X. Fan ◽

H. Yan ◽

A. Li ◽

M. Wang ◽

...

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Global Climate ◽

Estimation Method ◽

Ocean Surface ◽

Satellite Observations ◽

Surface Radiation ◽

Radiation Budget ◽

Global Ocean ◽

Ocean Water

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

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Operational Validation of Space-based Albedo Products from Upscaled Tower-based Albedometer Measurements

10.5194/egusphere-egu2020-2731 ◽

2020 ◽

Author(s):

Rui Song ◽

Jan-Peter Muller

Keyword(s):

High Resolution ◽

Surface Albedo ◽

Atmospheric Correction ◽

Ground Level ◽

Correction Method ◽

Landsat 8 ◽

Surface Reflectance ◽

Moderate Resolution Imaging Spectroradiometer ◽

Land Surfaces ◽

Sentinel 2

Surface albedo is a fundamental radiative parameter which controls the Earth&#8217;s energy budget by determining the amount of solar radiation which is either absorbed by the surface or reflected back to atmosphere. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their repeated global coverage. In this work, a new method of upscaling surface albedo from ground level footprints of a few tens of metres to coarse satellite scales (&#8776;1km) is reported [1]. Tower-mounted albedometer measurements are upscaled and used to validate global space-based albedo products, including Copernicus Global Land Service (CGLS) 1km albedo data (from Proba-V and previously form VEGETATION-2), MODerate resolution Imaging Spectroradiometer (MODIS) 500m albedo data, and Multi-angle Imaging SpectroRadiometer (MISR) 1.1km albedo data. MODIS albedo retrievals show the closest agreement with tower measurements, followed by the MISR retrievals, and then followed by the CGLS retrievals. The upscaling method uses high-resolution surface reflectance retrievals (from Landsat-8, Sentinel-2) to fill the spatial gaps between the albedometer&#8217;s field-of-view (FoV) and coarse satellite scales. High-resolution surface albedo products are generated by combining high-resolution surface reflectance data and MODIS bi-directional reflectance distribution function (BRDF) climatology data. This upscaling framework also uses a novel Sensor Invariant Atmospheric Correction (SIAC) method [2] to improve the accuracy of upscaled tower albedo values. Total uncertainties of upscaled albedo products are estimated by considering uncertainties from both the tower albedometer raw measurements and SIAC atmospheric corrections. This surface albedo upscaling method can be used over both heterogenous and homogenous land surfaces, and has been examined at the SURFRAD, BSRN and FLUXNET tower sites.Keywords: surface albedo, upscale, CGLS, MODIS, MISR, SIAC[1] Song, R.; Muller, J.-P.; Kharbouche, S.; Woodgate, W. Intercomparison of Surface Albedo Retrievals from MISR, MODIS, CGLS Using Tower and Upscaled Tower Measurements. Remote Sens. 2019, 11, 644, doi:10.3390/rs11060644.[2] Yin, F., Lewis, P. E., Gomez-Dans, J., & Wu, Q. A sensor-invariant atmospheric correction method: application to Sentinel-2/MSI and Landsat 8/OLI. EarthArXiv 2019, https://doi.org/10.31223/osf.io/ps957.

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PEMETAAN SEBARAN PADANG LAMUN MENGGUNAKAN CITRA SATELIT LANDSAT 8 DI KEPULAUAN TANIMBAR KABUPATEN MALUKU TENGGARA BARAT PROVINSI MALUKU

Seminar Nasional Geomatika ◽

10.24895/sng.2018.3-0.1078 ◽

2019 ◽

Vol 3 ◽

pp. 871

Author(s):

Desita Anggraeni ◽

M. Nurkholis Fauzi ◽

Christian Novia Ngesti H.

Keyword(s):

Landsat 8 ◽

Surface Reflectance ◽

Halophila Ovalis ◽

Halodule Uninervis ◽

Gap Data

Padang lamun merupakan habitat penting pesisir yang memiliki peran kunci dalam ekosistem pesisir. Kawasan ini merupakan area asuhan bagi ikan-ikan kecil, udang, persembunyian biota dari predatornya, pendaur zat hara, serta penyerap nutrien dari limpasan air laut yang dapat membantu menstabilkan sedimen dan kejernihan air. Kepulauan Tanimbar merupakan salah satu lokasi di Provinsi Maluku dengan potensi sebaran lamun yang cukup luas, namun informasi mengenai sebaran lamun di kawasan ini tidak terdata dengan baik. Teknologi penginderaan jauh merupakan salah satu alternatif untuk mengisi gap data di area yang luas dan sulit dijangkau, termasuk untuk memetakan sebaran lamun di Kepulauan Tanimbar. Penelitian ini bertujuan untuk menyediakan data dasar sebaran dan luas habitat lamun di pesisir Kepulauan Tanimbar. Metode yang digunakan adalah analisis citra penginderaan jauh Landsat 8, menerapkan penajaman citra untuk perairan dangkal menggunakan algoritma Lyzenga. Citra Landsat yang digunakan Landsat Surface Reflectance liputan path/row 106/65 dan 106/66 tahun perekaman 2017. Pengambilan data lapangan dilakukan pada tanggal 1-10 November 2017. Metode pengambilan data lamun dilakukan menggunakan metode seagrass watch . Hasil pengolahan citra menunjukkan lamun terdistribusi merata di seluruh pesisir Kepulauan Tanimbar dengan luas total 5.615,63 hektar dengan tutupan terpadat di sekitar Pulau Seira. Hasil survei lapangan menunjukkan tutupan lamun terpadat dijumpai di Formusan dengan tutupan lamun rata-rata 95%. Kondisi lamun paling baik berada di daerah Sabal, didukung kondisi air yang sangat jernih dengan substrat utama pasir. Berdasarkan hasil pengamatan lapangan, jenis lamun yang ditemukan antara lain: E n h alu s a c o r oid e s , T h ala s sia h e m p ric hii, C y m o d o c e a s e r r ula t a , C y m o d o c e a rotundata, Syringodi um isoetifolium, Halodule uninervis, Halophila ovalis, dan Halophila minor .

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Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

Journal of Geographical Studies ◽

10.21523/gcj5.19030102 ◽

2020 ◽

Vol 3 (1) ◽

pp. 11-23 ◽

Cited By ~ 3

Author(s):

Abdulla Al Kafy ◽

Abdullah Al-Faisal ◽

Mohammad Mahmudul Hasan ◽

Md. Soumik Sikdar ◽

Mohammad Hasib Hasan Khan ◽

...

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Land Surface ◽

Agricultural Land ◽

Global Climate ◽

Urban Expansion ◽

Water Bodies ◽

Landsat 8 ◽

Lulc Changes ◽

The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

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Consequences of the 2019 Greenland Ice Sheet Melt Episode on Albedo

Remote Sensing ◽

10.3390/rs13020227 ◽

2021 ◽

Vol 13 (2) ◽

pp. 227

Author(s):

Arthur Elmes ◽

Charlotte Levy ◽

Angela Erb ◽

Dorothy K. Hall ◽

Ted A. Scambos ◽

...

Keyword(s):

Radiative Forcing ◽

Surface Albedo ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Surface Energy Budget ◽

Landsat 8 ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Seasonal Snow Cover

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm−2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.

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Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses

Remote Sensing ◽

10.3390/rs12122015 ◽

2020 ◽

Vol 12 (12) ◽

pp. 2015 ◽

Cited By ~ 2

Author(s):

Manuel Ángel Aguilar ◽

Rafael Jiménez-Lao ◽

Abderrahim Nemmaoui ◽

Fernando José Aguilar ◽

Dilek Koc-San ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Coefficient Of Determination ◽

Landsat 8 ◽

Surface Reflectance ◽

Remote Sensing Techniques ◽

Image Pairs ◽

Study Sites ◽

High Level ◽

Sentinel 2

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.

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CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-5809-2017 ◽

2017 ◽

Vol 17 (9) ◽

pp. 5809-5828 ◽

Cited By ~ 88

Author(s):

Karl-Göran Karlsson ◽

Kati Anttila ◽

Jörg Trentmann ◽

Martin Stengel ◽

Jan Fokke Meirink ◽

...

Keyword(s):

Surface Albedo ◽

Surface Radiation ◽

Radiation Budget ◽

Climate Data ◽

Ground Segment ◽

Surface Radiation Budget ◽

Avhrr Data ◽

Data Record ◽

Development And Validation ◽

Climate Data Record

Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided.

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