The Earth Radiation Budget (ERB) at the top of the atmosphere describes how the Earth gains energy from the Sun and loses energy to space through the reflection of solar radiation and the emission of thermal radiation. The ERB is measured from space with dedicated remote sensing instruments. Its long-term monitoring is of fundamental importance for understanding climate change. This Special Issue contains contributions focusing on ERB remote sensing instruments for either (1) the establishment of past and current ERB Climate Data Records (CDRs), (2) insights in climate change gained from the analysis of ERB CDRs, and 3) the outlook for continued or improved future ERB monitoring. Full article

Decadal changes of the Reflected Solar Radiation (RSR) as measured by CERES from 2000 to 2018 are analysed. For both polar regions, changes of the clear-sky RSR correlate well with changes of the Sea Ice Extent. In the Arctic, sea ice is clearly melting, and as a result the earth is becoming darker under clear-sky conditions. However, the correlation between the global all-sky RSR and the polar clear-sky RSR changes is low. Moreover, the RSR and the Outgoing Longwave Radiation (OLR) changes are negatively correlated, so they partly cancel each other. The increase of the OLR is higher then the decrease of the RSR. Also the incoming solar radiation is decreasing. As a result, over the 2000–2018 period the Earth Energy Imbalance (EEI) appears to have a downward trend of −0.16 ± 0.11 W/m²dec. The EEI trend agrees with a trend of the Ocean Heat Content Time Derivative of −0.26 ± 0.06 (1 $\sigma$ ) W/m²dec. Full article

The Earth Radiation Budget (ERB) at the top of the atmosphere quantifies how the earth gains energy from the sun and loses energy to space. Its monitoring is of fundamental importance for understanding ongoing climate change. In this paper, decadal changes of the Outgoing Longwave Radiation (OLR) as measured by the Clouds and Earth’s Radiant Energy System from 2000 to 2018, the Earth Radiation Budget Experiment from 1985 to 1998, and the High-resolution Infrared Radiation Sounder from 1985 to 2018 are analysed. The OLR has been rising since 1985, and correlates well with the rising global temperature. An observational estimate of the derivative of the OLR with respect to temperature of 2.93 +/− 0.3 W/m ${}^2$ K is obtained. The regional patterns of the observed OLR change from 1985–2000 to 2001–2017 show a warming pattern in the Northern Hemisphere in particular in the Arctic, as well as tropical cloudiness changes related to a strengthening of La Niña. Full article

Data from the Advanced Very High Resolution Radiometer (AVHRR) have been used to create several long-duration data records of geophysical variables describing the atmosphere and land and water surfaces. In the Climate Monitoring Satellite Application Facility (CM SAF) project, AVHRR data are used to derive the Cloud, Albedo, and Radiation (CLARA) climate data records of radiation components (i.a., surface albedo) and cloud properties (i.a., cloud cover). This work describes the methodology implemented for the additional estimation of the Outgoing Longwave Radiation (OLR), an important Earth radiation budget component, that is consistent with the other CLARA variables. A first step is the estimation of the instantaneous OLR from the AVHRR observations. This is done by regressions on a large database of collocated observations between AVHRR Channel 4 (10.8 µm) and 5 (12 µm) and the OLR from the Clouds and Earth’s Radiant Energy System (CERES) instruments. We investigate the applicability of this method to the first generation of AVHRR instrument (AVHRR/1) for which no Channel 5 observation is available. A second step concerns the estimation of daily and monthly OLR from the instantaneous AVHRR overpasses. This step is especially important given the changes in the local time of the observations due to the orbital drift of the NOAA satellites. We investigate the use of OLR in the ERA5 reanalysis to estimate the diurnal variation. The developed approach proves to be valuable to model the diurnal change in OLR due to day/night time warming/cooling over clear land. Finally, the resulting monthly mean AVHRR OLR product is intercompared with the CERES monthly mean product. For a typical configuration with one morning and one afternoon AVHRR observation, the Root Mean Square (RMS) difference with CERES monthly mean OLR is about 2 Wm⁻² at 1° × 1° resolution. We quantify the degradation of the OLR product when only one AVHRR instrument is available (as is the case for some periods in the 1980s) and also the improvement when more instruments are available (e.g., using METOP-A, NOAA-15, NOAA-18, and NOAA-19 in 2012). The degradation of the OLR product from AVHRR/1 instruments is also quantified, which is done by “masking” the Channel 5 observations. Full article

Climate on Earth is determined by the Earth Radiation Budget (ERB), which quantifies the incoming and outgoing radiative energy fluxes. The ERB can be monitored by non-scanning wide field-of-view radiometers, or by scanning narrow field-of-view radiometers. We propose an enhanced design for the wide field-of-view radiometer, with as key features the use of a near-spherical cavity to obtain a uniform angular sensitivity and the integration of the shuttered electrical substitution principle, eliminating long term drifts of the radiometer and improving its time response. The target absolute accuracy is 1 W/m ${}^2$ and the target stability is 0.1 W/m ${}^2$ per decade for the measurement of the total outgoing Earth’s radiation. In order to increase the spatial resolution and to separate the total outgoing radiation into reflected Solar and emitted thermal radiation, we propose the joint use of the radiometer with wide field-of-view Shortwave (400–900 nm) and Longwave (8–14 μm) cameras. This paper presents the concept and design of the novel wide field-of-view radiometer, including simulations and analyses of its expected performance. We focus on mechanical design and the measurement characteristics based on optical and thermal analyses. In combination with the cameras, we obtain an estimated accuracy of 0.44 W/m ${}^2$ . Full article

The current lack of a long, 30+ year, global climate data record of reflected shortwave top-of-atmosphere (TOA) radiation could be tackled by relying on existing narrowband records from the Advanced Very High Resolution Radiometer (AVHRR) instruments, and transform these measurements into broadband quantities like provided by the Clouds and the Earth’s Radiant Energy System (CERES). This paper presents the methodology of an AVHRR-to-CERES narrowband-to-broadband conversion for shortwave TOA reflectance, including the ready-to-use results in the form of scene-type dependent regression coefficients, allowing a calculation of CERES-like shortwave broadband reflectance from AVHRR channels 1 and 2. The coefficients are obtained using empirical relations in a large data set of collocated, coangular and simultaneous AVHRR-CERES observations, requiring specific orbital conditions for the AVHRR- and CERES-carrying satellites, from which our data analysis uses all available data for an unprecedented observation matching between both instruments. The multivariate linear regressions were found to be robust and well-fitting, as demonstrated by the regression statistics on the calibration subset (80% of data): adjusted $R^2$ higher than 0.9 and relative RMS residual mostly below 3%, which is a significant improvement compared to previous regressions. Regression models are validated by applying them on a validation subset (20% of data), indicating a good performance overall, roughly similar to the calibration subset, and a negligible mean bias. A second validation approach uses an expanded data set with global coverage, allowing regional analyses. In the error analysis, instantaneous accuracy is quantified at regional scale between 1.8 Wm ${}^{-2}$ and 2.3 Wm ${}^{-2}$ (resp. clear-sky and overcast conditions) at 1 standard deviation (RMS bias). On daily and monthly time scales, these errors correspond to 0.7 and 0.9 Wm ${}^{-2}$ , which is compliant with the GCOS requirement of 1 Wm ${}^{-2}$ . Full article

As an important indicator to characterize the surface vegetation, fractional vegetation cover (FVC) with high spatio-temporal resolution is essential for earth surface process simulation. However, due to technical limitations and the influence of weather, it is difficult to generate temporally continuous FVC with high spatio-temporal resolution based on a single remote-sensing data source. Therefore, the objective of this study is to explore the feasibility of generating high spatio-temporal resolution FVC based on the fusion of GaoFen-1 Wide Field View (GF-1 WFV) data and Moderate-resolution Imaging Spectroradiometer (MODIS) data. Two fusion strategies were employed to identify a suitable fusion method: (i) fusing reflectance data from GF-1 WFV and MODIS firstly and then estimating FVC from the reflectance fusion result (strategy FC, Fusion_then_FVC). (ii) fusing the FVC estimated from GF-1 WFV and MODIS reflectance data directly (strategy CF, FVC_then_Fusion). The FVC generated using strategies FC and CF were evaluated based on FVC estimated from the real GF-1 WFV data and the field survey FVC, respectively. The results indicated that strategy CF achieved higher accuracies with less computational cost than those of strategy FC both in the comparisons with FVC estimated from the real GF-1 WFV (CF:R² = 0.9580, RMSE = 0.0576; FC: R² = 0.9345, RMSE = 0.0719) and the field survey FVC data (CF: R² = 0.8138, RMSE = 0.0985; FC: R² = 0.7173, RMSE = 0.1214). Strategy CF preserved spatial details more accurately than strategy FC and had a lower probability of generating abnormal values. It could be concluded that fusing GF-1 WFV and MODIS data for generating high spatio-temporal resolution FVC with good quality was feasible, and strategy CF was more suitable for generating FVC given its advantages in estimation accuracy and computational efficiency. Full article

The Radiometer Assessment using Vertically Aligned Nanotubes (RAVAN) 3U CubeSat mission is a pathfinder to demonstrate technologies for the measurement of Earth’s radiation budget, the quantification of which is critical for predicting the future course of climate change. A specific motivation is the need for lower-cost technology alternatives that could be used for multi-point constellation measurements of Earth outgoing radiation. RAVAN launched 11 November 2016, into a nearly 600-km, Sun-synchronous orbit, and collected data for over 20 months. RAVAN successfully demonstrates two key technologies. The first is the use of vertically aligned carbon nanotubes (VACNTs) as absorbers in broadband radiometers for measuring Earth’s outgoing radiation and the total solar irradiance. VACNT forests are arguably the blackest material known and have an extremely flat spectral response over a wide wavelength range, from the ultraviolet to the far infrared. As radiometer absorbers, they have greater sensitivity for a given time constant and are more compact than traditional cavity absorbers. The second technology demonstrated is a pair of gallium phase-change black body cells that are used as a stable reference to monitor the degradation of RAVAN’s radiometer sensors on orbit. Four radiometers (two VACNT, two cavity), the pair of gallium black bodies, and associated electronics are accommodated in the payload of an agile 3U CubeSat bus that allows for routine solar and deep-space attitude maneuvers, which are essential for calibrating the Earth irradiance measurements. The radiometers show excellent long-term stability over the course of the mission and a high correlation between the VACNT and cavity radiometer technologies. Short-term variability—at greater than the tenths-of-a-Watt/m² needed for climate accuracy—is a challenge that remains, consistent with insufficient thermal knowledge and control on a 3U CubeSat. There are also VACNT–cavity biases of 3% and 6% in the Total and SW channels, respectively, which would have to be overcome in a future mission. Although one of the black bodies failed after four months, the other provided a repeatable standard for the duration of the project. We present representative measurements from the mission and demonstrate how the radiometer time series can be used to reconstruct outgoing radiation spatial information. Improvements to the technology and approach that would lead to better performance and greater accuracy in future missions are discussed. Full article

A Moon-based Earth radiation observatory (MERO) could provide a longer-term continuous measurement of radiation exiting the Earth system compared to current satellite-based observatories. In order to parameterize the detector for such a newly-proposed MERO, the evaluation of the instrument’s entrance pupil irradiance (EPI) is of great importance. The motivation of this work is to build an EPI estimating model for a simplified single-pixel MERO instrument. The rationale of this model is to sum the contributions of every location in the MERO-viewed region on the Earth’s top of atmosphere (TOA) to the MERO sensor’s EPI, taking into account the anisotropy in the longwave radiance at the Earth TOA. Such anisotropy could be characterized by the TOA anisotropic factors, which can be derived from the Clouds and the Earth’s Radiant Energy System (CERES) angular distribution models (ADMs). As an application, we estimated the shortwave (SW) (0.3–5 µm) and longwave (LW) (5–200 µm) EPIs for a hypothetic MERO instrument located at the Apollo 15 landing site. Results show that the SW EPI varied from 0 to 0.065 W/m², while the LW EPI ranged between 0.061 and 0.075 W/m² from 1 to 29 October, 2017. We also utilized this model to predict the SW and LW EPIs for any given location within the MERO-deployable region (region of 80.5°W–80.5°E and 81.5°S–81.5°N on the nearside of the Moon) for the future 18.6 years from October 2017 to June 2036. Results suggest that the SW EPI will vary between 0 and 0.118 W/m², while the LW EPI will range from 0.056 to 0.081 W/m². Though the EPI estimating model in this study was built for a simplistic single-pixel instrument, it could eventually be extended and improved in order to estimate the EPI for a multi-pixel MERO sensor. Full article

The Mongolian Plateau (MP) and Tibetan Plateau (TP) have experienced higher-than-global average warming in recent decades, resulting in many significant changes in ecosystem structure and function. Among them are the leaf area index (LAI) and albedo, which play a fundamental role in understanding many causes and consequences of land surface processes and climate. Here, we focused on the spatiotemporal changes of LAI, albedo, and their spatiotemporal relationships on the two roofing landscapes in Eurasia. Based on the MODIS products, we investigated the spatiotemporal changes of albedo_{(VIS, NIR and SHO)} and LAI from 2000 through 2016. We found that there existed a general negative logarithmic relationship between LAI and three measures of albedo on both plateaus. No significant relationship was found for LAI-albedo_NIR on the TP, due to more complex land surface canopy characteristics affected by the NIR reflection there. During 2000–2016, overall, annual mean LAI increased significantly by 119.40 × 10³ km² on the MP and by 28.35 × 10³ km² on the TP, while the decreased areas for annual mean albedo_VIS were 585.59 × 10³ km² and 235.73 × 10³ km² on the MP and TP, respectively. More importantly, the LAI-albedo relationships varied substantially across the space and over time, with mismatches found in some parts of the landscapes. Substantial additional efforts with observational and/or experimental investigations are needed to explore the underlying mechanisms responsible for these relationships, including the influences of vegetation characteristics and disturbances. Full article

In this study, a radiation component calculation algorithm was developed using channel data from the Himawari-8 Advanced Himawari Imager (AHI) and meteorological data from the Unified Model (UM) Local Data Assimilation and Prediction System (LDAPS). In addition, the energy budget of the Korean Peninsula region in 2016 was calculated and its regional differences were analyzed. Radiation components derived using the algorithm were calibrated using the broadband radiation component data from the Clouds and the Earth’s Radiant Energy System (CERES) to improve their accuracy. The calculated radiation components and the CERES data showed an annual mean percent bias of less than 3.5% and a high correlation coefficient of over 0.98. The energy budget of the Korean Peninsula region was −2.4 Wm⁻² at the top of the atmosphere ($R_T$), −14.5 Wm⁻² at the surface ($R_S$), and 12.1 Wm⁻² in the atmosphere ($R_A$), with regional energy budget differences. The Seoul region had a high surface temperature (289.5 K) and a $R_S$ of −33.4 Wm⁻² (surface emission), whereas the Sokcho region had a low surface temperature (284.7 K) and a $R_S$ of 5.0 Wm⁻² (surface absorption), for a difference of 38.5 Wm⁻². In short, regions with relatively high surface temperatures tended to show energy emission, and regions with relatively low surface temperatures tended to show energy absorption. Such regional energy imbalances can cause weather and climate changes and bring about meteorological disasters, and thus research on detecting energy budget changes must be continued. Full article