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Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in Utqiaġvik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the US Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator–heater performance overall was skillful with the average of the systems mitigating ice formation 77 % (many >90 %) of the time during which icing conditions were present. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ∼0.6 ∘C of warming, enough to subsaturate the air up to a relative humidity (with respect to ice) of ∼105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes was assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources in both the shortwave and longwave.

Cloud cover estimates of single-layer shallow cumuli obtained from narrow field-of-view (FOV) lidar–radar and wide-FOV total sky imager (TSI) data are compared over an extended period (2000–2017 summers) at the established United States Atmospheric Radiation Measurement mid-continental Southern Great Plains site. We quantify the impacts of two factors on hourly and sub-hourly cloud cover estimates: (1) instrument-dependent cloud detection and data merging criteria and (2) FOV configuration. Enhanced observations at this site combine the advantages of the ceilometer, micropulse lidar (MPL) and cloud radar in merged data products. Data collected by these three instruments are used to calculate narrow-FOV cloud fraction (CF) as a temporal fraction of cloudy returns within a given period. Sky images provided by TSI are used to calculate the wide-FOV fractional sky cover (FSC) as a fraction of cloudy pixels within a given image. To assess the impact of the first factor on CF obtained from the merged data products, we consider two additional subperiods (2000–2010 and 2011–2017 summers) that mark significant instrumentation and algorithmic advances in the cloud detection and data merging. We demonstrate that CF obtained from ceilometer data alone and FSC obtained from sky images provide the most similar and consistent cloud cover estimates; hourly bias and root-mean-square difference (RMSD) are within 0.04 and 0.12, respectively. However, CF from merged MPL–ceilometer data provides the largest estimates of the multiyear mean cloud cover, about 0.12 (35 %) and 0.08 (24 %) greater than FSC for the first and second subperiods, respectively. CF from merged ceilometer–MPL–radar data has the strongest subperiod dependence with a bias of 0.08 (24 %) compared to FSC for the first subperiod and shows no bias for the second subperiod. The strong period dependence of CF obtained from the combined ceilometer–MPL–radar data is likely results from a change in what sensors are relied on to detect clouds below 3 km. After 2011, the MPL stopped being used for cloud top height detection below 3 km, leaving the radar as the only sensor used in cloud top height retrievals. To quantify the FOV impact, a narrow-FOV FSC is derived from the TSI images. We demonstrate that FOV configuration does not modify the bias but impacts the RMSD (0.1 hourly, 0.15 sub-hourly). In particular, the FOV impact is significant for sub-hourly observations, where 41 % of narrow- and wide-FOV FSC differ by more than 0.1. A new “quick-look” tool is introduced to visualize impacts of these two factors through integration of CF and FSC data with novel TSI-based images of the spatial variability in cloud cover. The influence of cloud field organization, such cloud streets parallel to the wind direction, on narrow- and wide-FOV cloud cover estimates can be visually assessed.

The indirect effect of atmospheric aerosol particles on the Earth's radiation balance remains one of the most uncertain components affecting climate change throughout the industrial period. The large uncertainty is partly due to the incomplete understanding of aerosol–cloud interactions. One objective of the GoAmazon2014/5 and the ACRIDICON (Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems)-CHUVA (Cloud Processes of the Main Precipitation Systems in Brazil) projects was to understand the influence of emissions from the tropical megacity of Manaus (Brazil) on the surrounding atmospheric environment of the rainforest and to investigate its role in the life cycle of convective clouds. During one of the intensive observation periods (IOPs) in the dry season from 1 September to 10 October 2014, comprehensive measurements of trace gases and aerosol properties were carried out at several ground sites. In a coordinated way, the advanced suites of sophisticated in situ instruments were deployed aboard both the US Department of Energy Gulfstream-1 (G1) aircraft and the German High Altitude and Long-Range Research Aircraft (HALO) during three coordinated flights on 9 and 21 September and 1 October. Here, we report on the comparison of measurements collected by the two aircraft during these three flights. Such comparisons are challenging but essential for assessing the data quality from the individual platforms and quantifying their uncertainty sources. Similar instruments mounted on the G1 and HALO collected vertical profile measurements of aerosol particle number concentrations and size distribution, cloud condensation nuclei concentrations, ozone and carbon monoxide mixing ratios, cloud droplet size distributions, and downward solar irradiance. We find that the above measurements from the two aircraft agreed within the measurement uncertainties. The relative fraction of the aerosol chemical composition measured by instruments on HALO agreed with the corresponding G1 data, although the total mass loadings only have a good agreement at high altitudes. Furthermore, possible causes of the discrepancies between measurements on the G1 and HALO are examined in this paper. Based on these results, criteria for meaningful aircraft measurement comparisons are discussed.

Small changes in the radiation budget at the earth's surface can lead to large climatological responses when persistent over time. With the increasing debate on anthropogenic influences on climatic processes during the 1980s the need for accurate radiometric measurements with higher temporal resolution was identified, and it was determined that the existing measurement networks did not have the resolution or accuracy required to meet this need. In 1988 the WMO therefore proposed the establishment of a new international Baseline Surface Radiation Network (BSRN), which should collect and centrally archive high-quality ground-based radiation measurements in 1 min resolution. BSRN began its work in 1992 with 9 stations; currently (status 2018-01-01), the network comprises 59 stations (delivering data to the archive) and 9 candidates (stations recently accepted into the network with data forthcoming to the archive) distributed over all continents and oceanic environments. The BSRN database is the World Radiation Monitoring Center (WRMC). It is hosted at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany, and now offers more than 10 300 months of data from the years 1992 to 2017. All data are available at https://doi.org/10.1594/PANGAEA.880000 free of charge.

Surface ultraviolet radiation (SUR) is not an increasing concern after the implementation of the Montreal Protocol and the recovery of the ozone layer Morgenstern et al.(2008). However, large uncertainties remain in the prediction of future changes of SUR Bais et al.(2015). Several studies pointed out that UV-B impacts the biosphere Erickson et al.(2015), especially the aquatic system, which plays a central part in the biogeochemical cycle Hader et al.(2007). It can affect phytoplankton productivity Smith and Cullen(1995). This influence can result in either positive or negative feedback on climate (Zepp et al., 2007). Global circulation model simulations predict an acceleration of the Brewer-Dobson circulation over the next century (Butchart, 2014), which would lead to a decrease in ozone levels in the tropics and an enhancement at higher latitudes (Hegglin and Shepherd, 2009). Reunion Island is located in the tropics (21° S, 55° E), in a part of the world where the amount of ozone in the ozone column is naturally low. In addition, this island is mountainous and the marine atmosphere is often clean with low aerosol concentrations. Thus, measurements show much higher SUR than at other sites at the same latitude or at midlatitudes. Ground-based measurements of SUR have been taken on Reunion Island by a Bentham DTMc300 spectroradiometer since 2009. This instrument is affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC). In order to quantify the future evolution of SUR in the tropics, it is necessary to validate a model against present observations. This study is designed to be a preliminary parametric and sensitivity study of SUR modelling in the tropics. We developed a local parameterisation using the Tropospheric Ultraviolet and Visible Model (TUV; Madronich, 1993) and compared the output of TUV to multiple years of Bentham spectral measurements. This comparison started in early 2009 and continued until 2016. Only clear-sky SUR was modelled, so we needed to sort out the clear-sky measurements. We used two methods to detect cloudy conditions: the first was based on an observer's hourly report on the sky cover, while the second was based on applying Long and Ackerman(2000)'s algorithm to broadband pyranometer data to obtain the cloud fraction and then discriminating clear-sky windows on SUR measurements. Long et al. (2006)'s algorithm, with the co-located pyranometer data, gave better results for clear-sky filtering than the observer's report. Multiple model inputs were tested to evaluate the model sensitivity to different parameters such as total ozone column, aerosol optical properties, extraterrestrial spectrum or ozone cross section. For total column ozone, we used ground-based measurements from the SAOZ (Système d'Analyse par Observation Zénithale) spectrometer and satellite measurements from the OMI and SBUV instruments, while ozone profiles were derived from radio-soundings and the MLS ozone product. Aerosol optical properties came from a local aerosol climatology established using a Cimel photometer. Since the mean difference between various inputs of total ozone column was small, the corresponding response on UVI modelling was also quite small, at about 1 %. The radiative amplification factor of total ozone column on UVI was also compared for observations and the model. Finally, we were able to estimate UVI on Reunion Island with, at best, a mean relative difference of about 0.5 %, compared to clear-sky observations.

This paper presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.

Long-term simulations with the coupled WRF–CMAQ (Weather Research and Forecasting–Community Multi-scale Air Quality) model have been conducted to systematically investigate the changes in anthropogenic emissions of SO2 and NOx over the past 16 years (1995–2010) across the United States (US), their impacts on anthropogenic aerosol loading over North America, and subsequent impacts on regional radiation budgets. In particular, this study attempts to determine the consequences of the changes in tropospheric aerosol burden arising from substantial reductions in emissions of SO2 and NOx associated with control measures under the Clean Air Act (CAA) especially on trends in solar radiation. Extensive analyses conducted by Gan et al. (2014a) utilizing observations (e.g., SURFRAD, CASTNET, IMPROVE, and ARM) over the past 16 years (1995–2010) indicate a shortwave (SW) radiation (both all-sky and clear-sky) "brightening" in the US. The relationship of the radiation brightening trend with decreases in the aerosol burden is less apparent in the western US. One of the main reasons for this is that the emission controls under the CAA were aimed primarily at reducing pollutants in areas violating national air quality standards, most of which were located in the eastern US, while the relatively less populated areas in the western US were less polluted at the beginning of this study period. Comparisons of model results with observations of aerosol optical depth (AOD), aerosol concentration, and radiation demonstrate that the coupled WRF–CMAQ model is capable of replicating the trends well even though it tends to underestimate the AOD. In particular, the sulfate concentration predictions were well matched with the observations. The discrepancies found in the clear-sky diffuse SW radiation are likely due to several factors such as the potential increase of ice particles associated with increasing air traffic, the definition of "clear-sky" in the radiation retrieval methodology, and aerosol semi-direct and/or indirect effects which cannot be readily isolated from the observed data.

The fast development of solar radiation and energy applications, such as photovoltaic and solar thermodynamic systems, has increased the need for solar radiation measurement and monitoring, for not only the global but also the diffuse and direct components. End users look for the best compromise between getting close to state-of-the-art measurements and keeping low capital, maintenance and operating costs. Among the existing commercial options, SPN1 is a relatively low cost solar radiometer that estimates global and diffuse solar irradiances from seven thermopile sensors under a shading mask and without moving parts. This work presents a comprehensive study of SPN1 accuracy and sources of uncertainty, drawing on laboratory experiments, numerical modelling and comparison studies between measurements from this sensor and state-of-the art instruments for six diverse sites. Several clues are provided for improving the SPN1 accuracy and agreement with state-of-the art measurements.

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64%; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41%. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67% (plus 25% of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

Long-term data sets of all-sky and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction, and aerosol optical depth (AOD) were analyzed together with surface concentrations from several networks (e.g., Surface Radiation Budget Network (SURFRAD), Clean Air Status and Trend Network (CASTNET), Interagency Monitoring of Protection Visual Environments (IMPROVE) and Atmospheric Radiation Measurement (ARM)) in the United States (US). Seven states with varying climatology were selected to better understand the effects of aerosols and clouds on SW radiation. This analysis aims to assess the effects of reductions in anthropogenic aerosol burden resulting from substantial reductions in emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) over the past 16 yr across the US, based on trends in SW radiation. The SO2 and NOx emission data show decreasing trends from 1995 to 2010, which indirectly validates the effects of the Clean Air Act (CAA) in the US. Meanwhile, the total column AOD and surface total PM2.5 observations also show decreasing trends in the eastern US but slightly increasing trends in the western US. Moreover, measured surface concentrations of several other pollutants (i.e., SO2, SO4 and NOx) have similar behavior to AOD and total PM2.5. Analysis of the observed data shows strong increasing trends in all-sky downwelling SW radiation with decreasing trends in cloud cover. However, since observations of both all-sky direct and diffuse SW radiation show increasing trends, there may be other factors contributing to the radiation trends in addition to the decreasing trends in overall cloud cover. To investigate the role of direct radiative effects of aerosols, clear-sky downwelling radiation is analyzed so that cloud effects are eliminated. However, similar increasing trends in clear-sky total and diffuse SW radiation are observed. While significantly decreasing trends in AOD and surface PM2.5 concentrations along with increasing SW radiation (both all-sky and clear-sky) in the eastern US during 1995–2010 imply the occurrence of direct aerosol mediated "brightening", the increasing trends of both all-sky and clear-sky diffuse SW radiation contradicts this conclusion since diffuse radiation would be expected to decrease as aerosols direct effects decrease and cloud cover decreases. After investigating several confounding factors, the increasing trend in clear-sky diffuse SW may be due to more high-level cirrus from increasing air traffic over the US. The clear-sky radiation observations in the western US also show indications of "brightening" even though the AOD, PM2.5 and surface concentration do not vary drastically. This outcome was not unexpected because the CAA controls were mainly aimed at reducing air pollutant emissions in the eastern US and air pollutant levels in the western US were much lower at the onset. This suggests other factors affect the "brightening" especially in the western US.

The Arctic is a challenging environment for making in-situ surface radiation measurements. A standard suite of radiation sensors is typically designed to measure incoming and outgoing shortwave (SW) and thermal infrared, or longwave (LW), radiation. Enhancements may include various sensors for measuring irradiance in narrower bandwidths. Many solar radiation/thermal infrared flux sensors utilize protective glass domes and some are mounted on complex mechanical platforms (solar trackers) that keep sensors and shading devices trained on the sun along its diurnal path. High quality measurements require striking a balance between locating stations in a pristine undisturbed setting free of artificial blockage (such as from buildings and towers) and providing accessibility to allow operators to clean and maintain the instruments. Three significant sources of erroneous data in the Arctic include solar tracker malfunctions, rime/frost/snow deposition on the protective glass domes of the radiometers and operational problems due to limited operator access in extreme weather conditions. In this study, comparisons are made between the global and component sum (direct [vertical component] + diffuse) SW measurements. The difference between these two quantities (that theoretically should be zero) is used to illustrate the magnitude and seasonality of arctic radiation flux measurement problems. The problem of rime/frost/snow deposition is investigated in more detail for one case study utilizing both SW and LW measurements. Solutions to these operational problems that utilize measurement redundancy, more sophisticated heating and ventilation strategies and a more systematic program of operational support and subsequent data quality protocols are proposed.

Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulated in the IPCC AR4 GCMs against ARM long-term ground-based measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity. Comparisons are performed for three climate regimes as represented by the Department of Energy Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). Our intercomparisons of three independent measurements of CF or sky-cover reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The total sky imager (TSI) produces smaller total cloud fraction (TCF) compared to a radar/lidar dataset for highly cloudy days (CF > 0.8), but produces a larger TCF value than the radar/lidar for less cloudy conditions (CF < 0.3). The compensating errors in lower and higher CF days result in small biases of TCF between the vertically pointing radar/lidar dataset and the hemispheric TSI measurements as multi-year data is averaged. The unique radar/lidar CF measurements enable us to evaluate seasonal variation of cloud vertical structures in the GCMs. Both inter-model deviation and model bias against observation are investigated in this study. Another unique aspect of this study is that we use simultaneous measurements of CF and surface radiative fluxes to diagnose potential discrepancies among the GCMs in representing other cloud optical properties than TCF. The results show that the model-observation and inter-model deviations have similar magnitudes for the TCF and the normalized cloud effect, and these deviations are larger than those in surface downward solar radiation and cloud transmissivity. This implies that other dimensions of cloud in addition to cloud amount, such as cloud optical thickness and/or cloud height, have a similar magnitude of disparity as TCF within the GCMs, and suggests that the better agreement among GCMs in solar radiative fluxes could be a result of compensating effects from errors in cloud vertical structure, overlap assumption, cloud optical depth and/or cloud fraction. The internal variability of CF simulated in ensemble runs with the same model is minimal. Similar deviation patterns between inter-model and model-measurement comparisons suggest that the climate models tend to generate larger biases against observations for those variables with larger inter-model deviation. The GCM performance in simulating the probability distribution, transmissivity and vertical profiles of cloud are comprehensively evaluated over the three ARM sites. The GCMs perform better at SGP than at the other two sites in simulating the seasonal variation and probability distribution of TCF. However, the models remarkably underpredict the TCF at SGP and cloud transmissivity is less susceptible to the change of TCF than observed. In the tropics, most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels. The high-level CF is much larger in the GCMs than the observations and the inter-model variability of CF also reaches a maximum at high levels in the tropics, indicating discrepancies in the representation of ice cloud associated with convection in the models. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near the surface over the Arctic.

Measurements from ground-based cloud radar, high spectral resolution lidar and microwave radiometer are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) and radiosonde measurements to derive the surface radiative properties under mixed-phase cloud conditions. These clouds were observed during the United States Department of Energy (US DOE) Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Clouds Experiment (M-PACE) between September and November of 2004. In total, sixteen half hour time periods are reviewed due to their coincidence with radiosonde launches. Cloud liquid (ice) water paths are found to range between 11.0–366.4 (0.5–114.1) gm−2, and cloud physical thicknesses fall between 286–2075 m. Combined with temperature and hydrometeor size estimates, this information is used to calculate surface radiative flux densities using RRTMG, which are demonstrated to generally agree with measured flux densities from surface-based radiometric instrumentation. Errors in longwave flux density estimates are found to be largest for thin clouds, while shortwave flux density errors are generally largest for thicker clouds. A sensitivity study is performed to understand the impact of retrieval assumptions and uncertainties on derived surface radiation estimates. Cloud radiative forcing is calculated for all profiles, illustrating longwave dominance during this time of year, with net cloud forcing generally between 50 and 90 Wm−2.

We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

The diffuse all-sky surface irradiances measured at two nearby wavelengths in the visible spectral range and their modeled clear-sky counterparts are the main components of a new method for estimating the fractional sky cover of different cloud types, including cumuli. The performance of this method is illustrated using 1-min resolution data from a ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR). The MFRSR data are collected at the US Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site during the summer of 2007 and represent 13 days with cumuli. Good agreement is obtained between estimated values of the fractional sky cover and those provided by a well-established independent method based on broadband observations.

The integrity of the Baseline Surface Radiation Network (BSRN) radiation monthly averages are assessed by investigating the impact on monthly means due to the frequency of data gaps caused by missing or discarded high time resolution data. The monthly statistics, especially means, are considered to be important and useful values for climate research, model performance evaluations and for assessing the quality of satellite (time- and space-averaged) data products. The study investigates the spread in different algorithms that have been applied for the computation of monthly means from 1-min values. The paper reveals that the computation of monthly means from 1-min observations distinctly depends on the method utilized to account for the missing data. The intra-method difference generally increases with an increasing fraction of missing data. We found that a substantial fraction of the radiation fluxes observed at BSRN sites is either missing or flagged as questionable. The percentage of missing data is 4.4%, 13.0%, and 6.5% for global radiation, direct shortwave radiation, and downwelling longwave radiation, respectively. Most flagged data in the shortwave are due to nighttime instrumental noise and can reasonably be set to zero after correcting for thermal offsets in the daytime data. The study demonstrates that the handling of flagged data clearly impacts on monthly mean estimates obtained with different methods. We showed that the spread of monthly shortwave fluxes is generally clearly higher than for downwelling longwave radiation. Overall, BSRN observations provide sufficient accuracy and completeness for reliable estimates of monthly mean values. However, the value of future data could be further increased by reducing the frequency of data gaps and the number of outliers. It is shown that two independent methods for accounting for the diurnal and seasonal variations in the missing data permit consistent monthly means to within less than 1 W m−2 in most cases. The authors suggest using a standardized method for the computation of monthly means which addresses diurnal variations in the missing data in order to avoid a mismatch of future published monthly mean radiation fluxes from BSRN. The application of robust statistics would probably lead to less biased results for data records with frequent gaps and/or flagged data and outliers. The currently applied empirical methods should, therefore, be completed by the development of robust methods.

A recent World Meteorological Organisation report discussed the importance of continued study of the effect of clouds on the solar UV radiation reaching the earth's surface. The report mentions that the use of all-sky imagery offers the potential to understand and quantify cloud effects more accurately. There are an increasing number of studies investigating the enhancement of surface solar, UV irradiance, and UV actinic flux, using automated CCD and sky imagers. This paper describes new algorithms applicable to a commercially available all-sky imager (TSI-440), for research investigating cloud enhanced spectral UV irradiance. Specifically, these include three new algorithms relating to cloud amount at different spatial positions from 1) zenith and 2) from the solar position and 3) the visible brightness of clouds surrounding the sun. A possible relationship between UV enhancement and the occurrence of near-sun cloud brightness is reported based on this preliminary data. It is found that a range of wavelength dependent intensities, from 306 to 400 nm, can occur in one day for UV enhancements. Evidence for a possible decreasing variation of intensity with longer wavelengths is also presented.

No abstract available.