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Abstract Though the partitioning of shortwave radiation ( K ↓ ) at the surface into its diffuse ( K ↓,d ) and direct beam ( K ↓,b ) components is relevant for, among other things, the terrestrial energy and carbon budgets, there is a dearth of large-scale comparisons of this partitioning across reanalysis and satellite-derived products. Here we evaluate K ↓ , K ↓,d , and K ↓,b , as well as the diffuse fraction ( k d ) of solar radiation in four current-generation reanalysis (NOAA-CIRES-DOE, NCEP/NCAR, MERRA-2, ERA5) datasets and one satellite-derived product (CERES) using ≈1400 site years of observations. Although the systematic positive biases in K ↓ is consistent with previous studies, the biases in gridded K ↓,d and K ↓,b vary in direction and magnitude, both annually and across seasons. The inter-model variability in cloud cover strongly explains the biases in both K ↓,d and K ↓,b . Over Europe and China, the long-term (10-year plus) trends in K ↓,d in the gridded products are noticeably differ from corresponding observations and the grid-averaged 35-year trends show an order of magnitude variability. In the MERRA-2 reanalysis, which includes both clouds and assimilated aerosols, the reduction in both clouds and aerosols reinforce each other to establish brightening trends over Europe, while the effect of increasing aerosols overwhelm the effect of decreasing cloud cover over China. The inter-model variability in k d seen here (0.27 to 0.50 from CERES to MERRA-2) suggests substantial differences in shortwave parameterization schemes and their inputs in climate models and can contribute to inter-model variability in coupled simulations. Based on these results, we call for systematic evaluations of K ↓,d and K ↓,b in CMIP6 models. 

The diffuse radiation fertilization effect—the increase in plant productivity in the presence of higher diffuse radiation (K_↓,d)—is an important yet understudied aspect of atmosphere‐biosphere interactions and can modify the terrestrial carbon, energy, and water budgets. TheK_↓,dfertilization effect links the carbon cycle with clouds and aerosols, all of which are large sources of uncertainties for our current understanding of the Earth system and for future climate projections. Here we establish to what extent observational and modeling uncertainty in sunlight's diffuse fraction (k_d) affects simulated gross primary productivity (GPP) and terrestrial evapotranspiration (λE). We find only 48 eddy covariance sites with simultaneous sufficient measurements ofK_↓,dwith none in the tropical climate zone, making it difficult to constrain this mechanism globally using observations. Using a land modeling framework based on the latest version of the Community Land Model, we find that global GPP ranges from 114 Pg C year⁻¹when usingk_dforcing from the Modern‐Era Retrospective analysis for Research and Applications, version 2 reanalysis to a ∼7% higher value of 122 Pg C year⁻¹when using the Clouds and the Earth's Radiant Energy System satellite product, with especially strong differences apparent over the tropical region (mean increase ∼9%). The differences inλE, although smaller (−0.4%) due to competing changes in shaded and sunlit leaf transpiration, can be greater than regional impacts of individual forcing agents like aerosols. Our results demonstrate the importance of comprehensively and systematically validating the simulatedk_dby atmosphere modules as well as the response to differences ink_dwithin land modules across Earth System Models.

 

Atmospheric ammonia (NH3) is the primary form of reactive nitrogen (Nr) and a precursor ofammonium (NH4+) aerosols. Ammonia has been linked to adverse impacts on human health, the loss ofecosystem biodiversity, and plays a key role in aerosol radiative forcing. The midwestern United States is themajor NH3source in North America because of dense livestock operations and the high use of syntheticnitrogen fertilizers. Here, we combine tall‐tower (100 m) observations in Minnesota and Weather Researchand Forecasting model coupled with Chemistry (WRF‐Chem) modeling to investigate high and low NH3emission episodes within the U.S. Corn Belt to improve our understanding of the distribution of emissionsources and transport processes. We examined observations and performed model simulations for cases inFebruary through November of 2017 and 2018. The results showed the following: (1) Peak emissions inNovember 2017 were enhanced by above‐normal air temperatures, implying aQ10(i.e., the change in NH3emissions for a temperature increase of 10°C) of 2.5 for emissions. (2) The intensive livestock emissionsrom northern Iowa, approximately 400 km away from the tall tower, accounted for 17.6% of theabundance in tall‐tower NH3mixing ratios. (3) Ammonia mixing ratios in the innermost domain 3frequently (i.e., 336 hr, 48% of November 2017) exceeded 5.3 ppb, an important air quality health standard.(4) In November 2017, simulated NH3net ecosystem exchange (the difference between NH3emissionsand dry deposition) accounted for 60–65% of gross NH3emissions for agricultural areas and was2.8–3.1 times the emissions of forested areas. (5) We estimated a mean annual NH3net ecosystem exchangeof 1.60 ± 0.06 nmol · m−2·s−1for agricultural lands and−0.07 ± 0.02 nmol · m−2·s−1for forested lands.These results imply that future warmer fall temperatures will enhance agricultural NH3emissions, increasethe frequency of dangerous NH3episodes, and enhance dry NH3deposition in adjacent forested lands.