Accurate multidecadal radiative flux records are vital to understand Arctic amplification and constrain climate model uncertainties. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. The year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes was conducted using in situ measurements from MOSAiC flux stations. The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by +11.40 Wm–2 and underestimates the upwelling shortwave flux by –15.70 Wm–2 and downwelling longwave fluxes by –12.58 Wm–2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0°C). The biases in downwelling shortwave and longwave fluxes suggest that the atmosphere represented in CERES is too optically thin. The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. Additionally, the results show that the spectral surface albedo used in SYN1deg overestimates albedo in visible and mid-infrared bands. A series of radiative transfer model perturbation experiments are performed to quantify the factors contributing to the differences. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm–2) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm–2). In addition, the differences between perturbation experiments using hourly and monthly MOSAiC surface albedo suggest that approximately 25% of the sea ice surface albedo variability is explained by factors not correlated with daily sea ice concentration variability. Biases in net shortwave and longwave flux can be reduced to less than half by adjusting both albedo and cloud inputs toward observed values. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products.
more »
« less
Large Differences in Diffuse Solar Radiation Among Current-Generation Reanalysis and Satellite-Derived Products
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.
more »
« less
- Award ID(s):
- 1933630
- NSF-PAR ID:
- 10314617
- Date Published:
- Journal Name:
- Journal of Climate
- ISSN:
- 0894-8755
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
During the Cloud System Evolution in the Trades (CSET) field study, 14 research flights of the National Science Foundation G-V sampled the stratocumulus–cumulus transition between Northern California and Hawaii and its synoptic variability. The G-V made vertically resolved measurements of turbulence, cloud microphysics, aerosol characteristics, and trace gases. It also carried dropsondes and a vertically pointing W-band radar and lidar. This paper summarizes these observations with the goals of fostering novel comparisons with theory, models and reanalyses, and satellite-derived products. A longitude–height binning and compositing strategy mitigates limitations of sparse sampling and spatiotemporal variability. Typically, a 1-km-deep decoupled stratocumulus-capped boundary layer near California evolved into 2-km-deep precipitating cumulus clusters surrounded by patches of thin stratus that dissipated toward Hawaii. Low cloud cover was correlated with estimated inversion strength more than with cloud droplet number, even though the thickest clouds were generally precipitating and ultraclean layers indicative of aerosol–cloud–precipitation interaction were common west of 140°W. Accumulation-mode aerosol concentration correlated well with collocated cloud droplet number concentration and was typically largest near the surface. Aitken mode aerosol concentration was typically larger in the free troposphere. Wildfire smoke produced spikes of aerosol and trace gases on some flights. CSET data are compared with space–time collocated output from MERRA-2 reanalysis and from the CAM6 climate model run with winds and temperature nudged toward this reanalysis. The reanalysis compares better with the observed relative humidity than does nudged CAM6. Both vertically diffuse the stratocumulus cloud layer versus observations. MERRA-2 slightly underestimates in situ carbon monoxide measurements and underestimates ozone depletion within the boundary layer.
-
more » « less
Abstract Cloud diurnal variation (CDV) affects cloud radiative effects significantly as clouds reflect shortwave radiation only during the daytime but trap outgoing longwave radiation in both daytime and nighttime. Meanwhile, CDV also rectifies atmospheric variations of longer time scales via interactions with other physical and dynamic processes. These make CDV a valuable aspect for diagnosing climate model performance. Here, we evaluate the accuracy of simulated CDV in state‐of‐the‐art global climate models (GCMs) by comparing CDV in the historical simulation of 32 GCMs from 20 institutes participating the Coupled Model Intercomparison Project Phase 6 (CMIP6) with observations from the International Satellite and Cloud Climatology Project‐H product. While good agreement is found over the oceans, significant biases exist over land (notably deserts and plateaus), where the models simulate excessive nighttime clouds and insufficient daytime clouds and miss the observed peak of cloud fraction in the early afternoon. These biases persist throughout the year. It is illustrated that correcting the CDV biases tends to reduce the known model biases of smaller shortwave cloud radiative effect over the midlatitude Africa‐Europe‐Asia continent, South America, and vast ocean areas. Inter‐model comparisons show that the CDV biases vary significantly among models from different institutes and present similar characteristics among models from the same institutes, and suggests that the biases are more likely to be attributed to deficiencies in cloud‐related physical parameterizations rather than the model treatment of resolution, ocean, and chemistry. The improvement of CMIP6 models against their CMIP5 counterparts in simulating CDV is also discussed.
-
Abstract The Southern Ocean is covered by a large amount of clouds with high cloud albedo. However, as reported by previous climate model intercomparison projects, underestimated cloudiness and overestimated absorption of solar radiation (ASR) over the Southern Ocean lead to substantial biases in climate sensitivity. The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models. We employ 10-year satellite observations to evaluate cloud radiative effect (CRE) and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud, radiation, and aerosol. The simulated longwave, shortwave, and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations. Total cloud fraction (CF) is also reasonably simulated in CMIP6, but the comparison of liquid cloud fraction (LCF) reveals marked biases in spatial pattern and seasonal variations. The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macro- and micro-physical properties, including liquid water path (LWP), cloud optical depth (COD), and cloud effective radius, as well as aerosol optical depth (AOD). However, the large underestimation of both LWP and cloud effective radius (regional means ∼20% and 11%, respectively) results in relatively smaller bias in COD, and the impacts of the biases in COD and LCF also cancel out with each other, leaving CRE and ASR reasonably predicted in CMIP6. An error estimation framework is employed, and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE. Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations, while the modeled CRE is too sensitive to LWP and COD. The relationships between cloud effective radius, LWP, and COD are also analyzed to explore the possible uncertainty sources in different models. Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection.more » « less
-
more » « less
Abstract In clouds containing both liquid and ice with temperatures between −3°C and −8°C, liquid droplets collide with large ice crystals, freeze, and shatter, producing a plethora of small ice splinters. This process, known as Hallett‐Mossop rime splintering, and other forms of secondary ice production, can cause clouds to reflect less sunlight and to have shorter lifetimes. We show its impact on Southern Ocean shallow cumuli using a novel suite of five global storm‐resolving simulations, which partition the Earth's atmosphere into 2–4 km wide columns. We evaluate simulated clouds and radiation over the Southern Ocean with aircraft observations from the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES), and satellite observations from Clouds and the Earth's Radiant Energy System (CERES) and Himawari. Simulations with large concentrations of ice crystals in boundary layer clouds, which agree better with SOCRATES observations, have reduced mixed‐phase cumulus cloud cover and weaker shortwave cloud radiative effects (CREs) that are less biased compared with CERES. Using a pair of simulations differing only in their treatment of Hallett‐Mossop rime splintering, we show that including this process increases ice crystal concentrations in cumulus clouds and weakens shortwave CREs over the Southern Ocean by 10 W m−2. We also demonstrate the key role that global storm‐resolving models can play in detangling the effects of clouds on Earth's climate across scales, making it possible to trace the impact of changes in individual cumulus cloud anvils (10 km2) on the radiative budget of the massive Southern Ocean basin (107 km2).
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/JCLI-D-20-0979.1
