European Climate Data Records

Climate change is one of the biggest challenges in the history of humankind. The global distribution of aerosol radiative forcing is a large uncertainty in present climate models. Aerosol retrieval from spaceborne sensors could help to fill this gap over the ocean and land. For present satellite sensors like AVHRR/MetOp, MODIS, MERIS, SeaWiFS or POLDER and future sensors, algorithms have been developed to derive optical and physical aerosol parameters like optical depth, particle size distribution or aerosol type.

In order to provide the consistent long term Earth observation data, MetOp, Europe's first polar-orbiting satellite dedicated to operational meteorology, represents the European contribution to a new co-operative venture with the United States providing data to monitor climate and improve weather forecasting. Sentinel-5 is a payload that will be embarked on a MetOp Second Generation satellite, also known as Post-EPS, to be launched in 2020. Sentinel-5 is dedicated to atmospheric monitoring. MetOp carries a set of 'heritage' instruments, such as AVHRR, provided by the United States and a new generation of European instruments that offer improved remote sensing capabilities to both meteorologists and climatologists.

Different authors proposed to derive the climatically important aerosol effect on the upward radiative flux directly from satellite measurements of upward radiance instead of deriving aerosol parameters subsequently used for the assessment of the aerosol radiative forcing (Xu et al. 2014). In this article, we intend to calculate the consistent long term aerosol radiative forcing by using the AVHRR/MetOp data. First, we have re-calibrated all AVHRR data dated back to 1980s using the new calibration coefficients proposed by Li et al. (2014). The advanced algorithm for the land aerosol and bidirectional reflectance inversion by times series technique (LABITS) is proposed and applied to data from the National Oceanic and Atmospheric Administration (NOAA) advanced very high resolution radiometer (AVHRR). The algorithm can retrieve several parameters of the earth-atmosphere system, including AOD, BRF and albedo. Aerosol radiative forcing is calculated with AOD and albedo datasets from AVHRR with auxiliary ECMWF data.

Evaluation of the AOD versus data from the Aerosol Robotic Network (AERONET) provides a correlation coefficient R² of 0.88 and a root-mean-square error (RMSE) of approximately 0.07; and the uncertainty is approximatelyΔτ=±0.05±0.20τ. The surface albedo values calculated from the retrieved BRF parameters are similar to those provided by the MODIS albedo product (MCD43). The preliminary analysis of time series daily and monthly averaged results over selected AERONET sites shows that the temporal variations of the aerosol radiative forcing values retrieved by application of LABITS to AVHRR data are overall similar to temporal variations of radiative forcing provided by the MODIS and AERONET.

References:

[1.]      Hui Xu; Xavier Ceamanos; Jean-Louis Roujean; Dominique Carrer; Yong Xue, 2014, Can satellite-derived AOD quantify the surface aerosol radiative forcing (SARF)? Evaluation of AOD products and application to calculate direct SARF. Atmospheric Research, 150, Pages 151–167.

[2.]      Yong Xue, Xingwei He, Hui Xu, Jie Guang, Jianping Guo, and Linlu Mei, 2014, CHINA COLLECTION 2.0: The Aerosol Optical Depth Dataset from the Synergetic Retrieval of Aerosol Properties Algorithm. Atmospheric Environment, 95, Pages 45–58.

[3.]      Chi Li, Yong Xue, Quanhua Liu, Jie Guang, Xingwei He, Jiahua Zhang, Tingkai Wang, Xinjie Liu, 2014, Post Calibration of Channels 1 and 2 of Long-term AVHRR Data Record Based on SeaWiFS Data and Pseudo-invariant Targets. Remote Sensing of Environment, 150, Pages 104–119.

[4.]      Yingjie Li, Yong Xue, Gerrit de Leeuw, Chi Li, Leiku Yang, Tingting Hou, Farhi Marir, 2013, Retrieval of aerosol optical depth and surface reflectance over land from NOAA AVHRR data. Remote Sensing of Environment, 133, pages 1-20.

Global radiation is the main driver of nearly every dynamic process on Earth. It drives both air and ocean circulations, thereby influencing weather and climate. It has a direct climatic impact and it is the main energy source for nearly all life on Earth. From research and society there is an increasingly growing demand of high resolution global radiation maps.

The aim of this research is to see if it is possible to obtain high resolution global radiation maps for the Netherlands by assimilating in-situ observations with Meteosat Second Generation (MSG) satellite measurements and improving the existing maps based on solely in-situ measurements and satellite measurements.

Two satellite products were used :  the Climate Monitoring Satellite Application Facility (CM-SAF) product and the Surface Insolation under Clear and Cloudy Skies (SICCS) product from the KNMI. Both products were available for the period of January 2006 to December 2011 and came in the form of images with monthly and daily averages. To combine the satellite images with 32 KNMI weather stations different interpolation methods were used:  Thin Plate Splines (TPS), Mean Bias interpolation (MB), interpolated Bias interpolation (IB) and Kriging with External Drift (KED). Interpolations were made for the average of the six year period and on monthly measurements, for each month, in each year. Daily interpolations were made for April 2010 until July 2010. A set of different validation methods were used to analyze the output results. The analysis was performed in R, a language and environment for statistical computing and graphics .

         The results showed that for the six year average and monthly averages both products and all interpolation methods performed well on predicting global radiation.

         It turned out that for the daily data KED and the IB interpolations performed significantly better than the TPS or MB interpolation. KED adjusts the values in the satellite images to match those of the in-situ measurements thereby reducing the errors in the product without reducing spatial resolution.

Land surface albedo is a key forcing parameter for the climate system controlling the radiative energy budget. Thus, its monitoring is of primary importance for an understanding of the climate system. Its value changes in space and time, depending on both natural processes (vegetation growth, rain and snowfall and snow melting, wildfires, etc.) and human activities (forestation and deforestation, harvesting crops, anthropogenic fires, etc.). Ground-based measurements are of great importance for the assessment and evaluation of local and regional variability and change, while satellite remote sensing offers a unique opportunity for documenting and monitoring the spatial surface albedo distribution, its variability and change at continental scales. Observations acquired by geostationary satellites have the advantages of offering both a long-term dataset and an angular sampling of the surface as well as providing diurnal sampling of key parameters influencing the retrieval such as cloud cover and aerosol load. EUMETSAT generated the Meteosat Surface Albedo (MSA) Climate Data Record (CDR). The MSA CDR covers the period from 1982 to 2006 for an area comprising Africa, most of Europe and the Middle East, as well as parts of South America. This CDR has been created within the Sustained and Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) framework. The long-term consistency of the MSA CDR is high and meets the Global Climate Observing System (GCOS) stability requirements for desert reference sites. EUMETSAT coordinated a study (ALBEOVAL-1) for the validation of the surface albedo dataset in 2012. The study was performed by a group of independent researchers in Europe and the USA. A second external validation study (ALBEDOVAL-2) was carried out in 2014 to enhance the understanding of the MSA performance based on in-depth product examination at selected reference sites meeting strict homogeneity requirements. In this context, an online database covering more than 2000 potential surface reference sites worldwide has been established. Statistical parameters have been produced for each site, including homogeneity measures and land cover information, allowing the selection of site subsets for problem-specific analyses. Both validation studies have resulted in a number of recommendations with a view to further improving the MSA climate data record. Clouds not removed by the embedded cloud screening procedure have been identified as the most relevant weakness in the retrieval process. A twofold strategy is therefore applied to efficiently improve the cloud detection and removal. A first step consists on the application of a robust and reliable cloud mask taking advantage of the information contained in the measurements of the infrared and visible bands. Due to the limited information available from old radiometers some clouds can still remain undetected. A second step relies on a post processing analysis of the albedo seasonal variation together with the usage of a background albedo map in order to detect and screen out such outliers. The usage of a reliable cloud mask has a double effect. It enhances the number of high quality retrievals for tropical forest areas sensed under low view angles and removes the most frequently unrealistic retrievals on similar surfaces sensed under high view angles. As expected, the usage of a cloud mask has a negligible impact on desert areas where clear conditions dominate. The exploitation of the albedo seasonal variation for cloud removal has good potentialities but it needs to be carefully addressed. Nevertheless it is shown that the inclusion of cloud masking and removal strategy is a key point for the generation of the next MSA CDR Release.

Climate change, in particular change in its variability, is one of the greatest challenges facing mankind in the twenty-first century. An improved understanding of the Earth System – of its weather, climate, oceans, land, geology, natural resources, ecosystems, and natural and human-induced hazards – is essential if we want to increase our ability to predict and mitigate/adapt against the expected global changes and the impacts on human civilisation. Data collected by, and information created from, Earth observation satellites constitute critical inputs in the development of this understanding.

The use of satellite data for assessing the status of past climate is still in its early stages. Satellite data became only available in the mid 1960s from some experimental research missions and first operational missions such as the fleet of geostationary satellites and also satellites in polar orbit were built for the purpose of monitoring and forecasting the weather. These data can well support environmental monitoring applications, however, it is recognised, that higher level applications such as climate variability and change analysis require well calibrated observations and long-term homogeneity of long time series. Satellite data of such kind are referred to as Climate Data Records(CDR) and are generated through careful recalibration and reprocessing activities.

EUMETSAT addresses climate monitoring from operations to the planning of future satellite systems, and involves specific scientific and technical efforts for the re-calibration of historical data and the extraction of climate data records. In particular, the scientific analysis of raw satellite data leading to corrections of artefacts, improved calibration of individual instruments and inter-calibration of several satellite instruments in a time series is fundamental to serve the generation of physically consistent data records of geophysical variables by reanalysis or the application of retrieval methods.

Once the re-calibration process has been completed, instrument measurements can be reprocessed to extract basic physical parameters (e.g., reflectance, radiance, radar backscatter) and to produce long-time series known as Fundamental Climate Data Records (FCDR). These present the material from which geophyscial parameters, e.g., GCOS Essential Climate Variables (ECVs) can be extracted. Production and continuous improvement of FCDRs are therefore a top priority for EUMETSAT. This demands in-depth undertstanding of instruments, resuing calibration and characterisation data, algorithm research and complex techniques to determine uncertainty of the data.   

This presentation will inform on EUMETSAT's recent advances and prospects for providing useful satellite-based climate data records for major applications in climate science and services.

Operational and researchspace agencies participating in CEOS and CGMS established the Joint CEOS/CGMS Working Group on Climate was established in 2014 to implement the so-called architecture for climate monitoring from space.

The working group also involving WMO has three major objectives:

Provision of a structured, comprehensive and accessible view as to which Climate Data Records are currently available from satellite missions of CEOS and CGMS members or their combination;

Creation of the conditions for delivering further Climate Data Records. This includes multi-mission Climate Data Records, through best use of available data to fulfil GCOS requirements (e.g., by identifying and targeting cross-calibration or reprocessing gaps/shortfalls);

Optimisation of the planning of future satellite missions and constellations to expand existing and planned Climate Data Records, in terms of coverage, record length and quality adressing possible gaps with respect to GCOS requirements.

A major activity addressing the first objective is the establishment and maintainance of an ECV Inventory, a rolling inventory of existing and planned CDRs, that serves as the basis to trace the CDRs to contributing Fundamnetal Climate Data Records and space missions.

Primary examples for the second objective are the WMO initiatives GSICS (Global Space Based Inter-calibration System) and SCOPE-CM (Sustained Co-ordinated Processing of Environmental Satellite Data for Climate Monitoring) to which both agencies make contributions.

Under the third objective, CEOS and CGMS agencies plan for future missions required to expand CDRs capatilising on the work of the CEOS Virtual Constellations.

ESA and EUMETSAT will lead the joint WG Climate during the next 4 years and this presentation will outline the major aims of and the needs for the participation of the scientific and operational communities in the activities of the WG Climate.