Aku Riihelä

Validation of CM SAF Surface Solar Radiation Datasets over Finland and Sweden

Accurate determination of the amount of incoming solar radiation at Earth’s surface is important for both climate studies and solar power applications. Satellite-based datasets of solar radiation offer wide spatial and temporal coverage, but careful validation of their quality is a necessary prerequisite for reliable utilization. Here we study the retrieval quality of one polar-orbiting satellite-based dataset (CLARA-A1) and one geostationary satellite-based dataset (SARAH), using in situ observations of solar radiation from the Finnish and Swedish meteorological measurement networks as reference. Our focus is on determining dataset quality over high latitudes as well as evaluating daily mean retrievals, both of which are aspects that have drawn little focus in previous studies. We find that both datasets are generally capable of retrieving the levels and seasonal cycles of solar radiation in Finland and Sweden well, with some limitations. SARAH exhibits a slight negative bias and increased retrieval uncertainty near the coverage edge, but in turn offers better precision (less scatter) in the daily mean retrievals owing to the high sampling rate of geostationary imaging.

Land Surface Albedos Computed from BRF Measurements with a Study of Conversion Formulae

Land surface hemispherical albedos of several targets have been resolved using the bidirectional reflectance factor (BRF) library of the Finnish Geodetic Institute (FGI). The library contains BRF data measured by FGI during the years 2003–2009. Surface albedos are calculated using selected BRF datasets from the library. Polynomial interpolation and extrapolation have been used in computations. Several broadband conversion formulae generally used for satellite based surface albedo retrieval have been tested. The albedos were typically found to monotonically increase with increasing zenith angle of the Sun. The surface albedo variance was significant even within each target category / surface type. In general, the albedo estimates derived using diverse broadband conversion formulas and estimates obtained by direct integration of the measured spectra were in line.

Extensive validation of CM SAF surface radiation products over Europe

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8–13 W/m2, whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRCs accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.

SNORTEX (Snow Reflectance Transition Experiment): Remote sensing measurement of the dynamic properties of the boreal snow-forest in support to climate and weather forecast: Report of IOP-2008

Large discrepancies are observed between snow albedo in Numerical Weather Prediction (NWP) models and from satellite observations in the case of high vegetation. Knowledge of the Bidirectional Reflectance Distribution Function (BRDF) of snow-forest system is required to solve the problem. The 3-years SNORTEX (Snow Reflectance Transition Experiment) campaign acquires from 2008 in situ measurements of snow and forest properties in support to the development of modelling tools and to validate coarse resolution satellite products (POLDER, MODIS, MERIS, METOP). The measurement scheme and some first example results are presented from the Intensive Observing Period (IOP) of 2008, which can be decomposed into airborne and ground operations. Multi-temporal BRDF at a metric resolution were acquired from OSIRIS (airPOLDER) onboard a helicopter and from ground with FigiFiGo spectrogoniometer. The same helicopter embarked a pair of UV sensors, pyranometers and a wide-optics camera. Ground component includes exhaustive snow measurements.

Boreal forest albedo and LAI in SNORTEX 2008–2010

Airborne broadband albedo and leaf area index (LAI) measurements were carried out simultaneously in the subarctic area of Sodankylä during the SNORTEX campaign in springs 2008 - 2010. Two pairs of pyranometers were attached to the helicopter on either side and a wide-optics camera was looking orthogonally downwards for LAI retrieval. The albedo depended on the LAI according to a previously developed model. The measurement altitude did not affect the albedo vs. LAI relationship. The winter time albedo value of snow varied in a wide range both seasonally and diurnally. The albedo values of open areas could also differ from each other distinctly during the same day depending on the land cover class.

Subarctic Boreal Forest Albedo Estimation Using Envisat ASAR for BRDF Determination

Surface albedo estimates based on optical and microwave satellite data were compared to corresponding ground based values in a Subarctic boreal forest test site. The ground based albedo values were derived from radiation measurements carried out at the forest floor using an albedo model and measured global and diffuse radiation data. The use of both optical and microwave satellite data turned out to produce more accurate surface albedo estimates than using only optical satellite data. The relative accuracy of the optical/microwave based near infrared and broad band albedo estimation was better than 10% for clear sky cases. The inclusion of microwave data improved the satellite based surface albedo estimation accuracy.

Estimation of the bidirectional reflectance distribution function of subarctic boreal forest using C-band SAR

Surface albedo is acknowledged as an important variable in climate research. Monitoring of Earths surface albedo in a global scale is practical only with satellite observations. However, satellite-based albedo research in the boreal regions is hampered by continual cloud contamination in the optical wavelengths, as well as long periods of low sun elevation. As the surface albedo can be calculated from the Bidirectional Reflectance Distribution Function (BRDF) of an area, new methods to improve the accuracy of BRDF calculation and remove cloud contamination effects are needed to enhance the accuracy of future climate studies. This study explores the possibility of estimating the BRDF of boreal forest using C-band synthetic aperture radar (SAR) data. The principle of the estimation is based on the knowledge that the BRDF of boreal forests depends on structural parameters such as NDVI or LAI, and that similar structural information can be derived from SAR imagery. The results of the study show that the estimation of BRDF from C-band SAR is possible at least under certain conditions, the proposed estimation method yielded a coefficient of determination of 0.68 for the small-scale study area in Northern Finland.

The temporal and spatial variability in submeter scale surface roughness of seasonal snow in Sodankylä Finnish Lapland in 2009–2010

Seasonal snow surface roughness is an important parameter for remote sensing data analysis since it affects the scattering properties of the snow surface. To understand the phenomenon, snow surface roughness was measured near the town of Sodankyla, in Finnish Lapland, during winters 2009 and 2010 using a photogrammetry-based plate method. The images were automatically processed so that an approximately 1 m long horizontal profile was extracted from each image. The data set consists of 669 plate profiles from different times and canopy types. This large data set was used to study the temporal and spatial variability of seasonal snow surface roughness. The profiles were analyzed using parameters derived from the root mean square height (σ) and correlation length (L) as functions of measured length. Also, the autocorrelation functions were calculated and analyzed. The (σ) and (L) were found to be so strongly correlated (R2 ~ 0.97) that a more detailed analysis was made using only the scaling parameters derived from σ. These parameters are related to the distance dependence of the rms height. The results show that they react to different characteristics of the profiles and are therefore well able to distinguish between different types of snow. They also show a clear difference between midwinter snow and melting snow, and the effects of snowfall events and slower melting in forested areas are evident in the data.

Validation of the SARAH-E Satellite-Based Surface Solar Radiation Estimates over India

We evaluate the accuracy of the satellite-based surface solar radiation dataset called Surface Solar Radiation Data Set - Heliosat (SARAH-E) against in situ measurements over a variety of sites in India between 1999 and 2014. We primarily evaluate the daily means of surface solar radiation. The results indicate that SARAH-E consistently overestimates surface solar radiation, with a mean bias of 21.9 W/m2. The results are complicated by the fact that the estimation bias is stable between 1999 and 2009 with a mean of 19.6 W/m2 but increases sharply thereafter as a result of rapidly decreasing (dimming) surface measurements of solar radiation. In addition, between 1999 and 2009, both in situ measurements and SARAH-E estimates described a statistically significant (at 95% confidence interval) trend of approximately −0.6 W/m2/year, but diverged strongly afterward. We investigated the cause of decreasing solar radiation at one site (Pune) by simulating clear-sky irradiance with local measurements of water vapor and aerosols as input to a radiative transfer model. The relationship between simulated and measured irradiance appeared to change post-2009, indicating that measured changes in the clear-sky aerosol loading are not sufficient to explain the rapid dimming in measured total irradiance. Besides instrumentation biases, possible explanations in the diverging measurements and retrievals of solar radiation may be found in the aerosol climatology used for SARAH-E generation. However, at present, we have insufficient data to conclusively identify the cause of the increasing retrieval bias. Users of the datasets are advised to be aware of the increasing bias when using the post-2009 data.

Intercalibration of Polar-Orbiting Spectral Radiometers Without Simultaneous Observations

A new intercalibration method for two polar-orbiting satellite instruments or two instrument constellations’ Fundamental Climate Data Records (FCDRs) is presented. It is based on statistical fitting of reflectance data from the two instruments covering the same area during the same period, but not simultaneously. A Deming regression with iterative weights is used. The accuracy of the intercalibration method itself was better than 0.5% for the Moderate Resolution Imaging Spectroradiometer (MODIS) versus MODIS and Advanced Very High Resolution Radiometer (AVHRR) versus AVHRR test data sets. The intercalibration of an AVHRR FCDR generated by NOAA versus a combined MODIS Terra and Aqua data set of red and near-infrared (NIR) channels was carried out and showed a difference in the reflectance values of about 2% (red) and 6% (NIR). The presented intercalibration method can be used for checking the calibration of two instruments or FCDRs in all viewing angles used separately.