A global long-term ocean surface daily/0.05° net radiation product from 1983–2020

The all-wave net radiation (Rn) on the ocean surface characterizes the available radiative energy balance and is important to understand the Earth’s climate system. Considering the shortcomings of available ocean surface Rn datasets (e.g., coarse spatial resolutions, discrepancy in accuracy, inconsistency, and short duration), a new long-term global daily Rn product at a spatial resolution of 0.05° from 1983 to 2020, as part of the Global High Resolution Ocean Surface Energy (GHOSE) products suite, was generated in this study by fusing several existing datasets including satellite and reanalysis products based on the comprehensive in situ measurements from 68 globally distributed moored buoy sites. Evaluation against in-situ measurements shows the root mean square difference, mean bias error and correlation coefficient squared of 23.56 Wm−2, 0.88 Wm−2 and 0.878. The global average ocean surface Rn over 1983–2020 is estimated to be 119.71 ± 2.78 Wm−2 with a significant increasing rate of 0.16 Wm−2 per year. GHOSE Rn product can be valuable for oceanic and climatic studies.

Spatiotemporal variations of land surface albedo and associated influencing factors on the Tibetan Plateau

Land surface albedo plays a crucial role in the land surface energy budget and climate. This paper identified the spatiotemporal variations of surface albedo on the Tibetan Plateau (TP) from 1982 to 2015, and quantified the relationships between the spatial and temporal patterns of the albedo and associated influencing factors (snow cover, vegetation, and soil moisture) on the seasonal and interannual basis using satellite products and reanalysis data. It was determined that the albedo presented a distinct spatial variability, with high values in mountainous areas and low values on the southeastern TP. Spatially, average albedo exhibited a positive correlation with snow cover and negative correlations with vegetation and soil moisture. Average albedo over the whole TP had a clear seasonal cycle with a peak in winter and a minimum value in summer, which is dictated by seasonal changes in snow and vegetation covers. Annual average albedo exhibited a weakly downward trend, which was mainly contributed by a significant decrease in summer, pointing to the important role in vegetation dynamics for temporal change of the albedo. On the regional basis, interannual variation of albedo was more responsive to snow cover over the snow- and vegetation-coexisting area than the snow-covered area, and to changes in Normalized Difference Vegetation Index (NDVI) over the vegetation-covered area than the snow- and vegetation-coexisting area; albedo had a weakly negative correlation with soil moisture over bare soil. Furthermore, our results indicated that snow cover was the dominant factor for albedo change on mountainous areas, and vegetation change predominated the variation of albedo on the eastern, southern, and northwestern TP. Specifically, variations in snow cover contributed more than those of vegetation to the interannual albedo variation over the Three Rivers Headwater Region. These results would be beneficial for better understanding the climate and eco-environment changes over the TP.

Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

A UAV-Based Sensor System for Measuring Land Surface Albedo: Tested over a Boreal Peatland Ecosystem

A multiple sensor payload for a multi-rotor based UAV platform was developed and tested for measuring land surface albedo and spectral measurements at user-defined spatial, temporal, and spectral resolutions. The system includes a Matrice 600 UAV with an RGB camera and a set of four downward pointing radiation sensors including a pyranometer, quantum sensor, and VIS and NIR spectrometers, measuring surface reflected radiation. A companion ground unit consisting of a second set of identical sensors simultaneously measure downwelling radiation. The reflected and downwelling radiation measured by the four sensors are used for calculating albedo for the total shortwave broadband, visible band and any narrowband at a 1.5 nm spectral resolution within the range of 350–1100 nm. The UAV-derived albedo was compared with those derived from Landsat 8 and Sentinel-2 satellite observations. Results show the agreement between total shortwave albedo from UAV pyranometer and Landsat 8 (R2 = 0.73) and Sentinel-2 (R2 = 0.68). Further, total shortwave albedo was estimated from spectral measurements and compared with the satellite-derived albedo. This UAV-based sensor system promises to provide high-resolution multi-sensors data acquisition. It also provides maximal flexibility for data collection at low cost with minimal atmosphere influence, minimal site disturbance, flexibility in measurement planning, and ease of access to study sites (e.g., wetlands) in contrast with traditional data collection methods.