Search

Frost is damaging to plants when air temperature drops below their tolerance threshold. The set of mechanisms used by cold-tolerant plants to withstand freezing is called “hardening” and typically take place in autumn to protect against winter damage. The recent incorporation of a hardening scheme in the demographic vegetation model FATES opens up the possibility to investigate frost mortality to vegetation. Previously, the hardening scheme was used to improve hydraulic processes in cold-tolerant plants. In this study, we expand upon the existing hardening scheme by implementing hardiness-dependent frost mortality into CLM5.0-FATES to study the impacts of frost on vegetation in temperate and boreal sites from 1950 to 2015. Our results show that the original freezing mortality approach of FATES, where each plant type had a fixed freezing tolerance threshold—an approach common to many other dynamic vegetation models, was restricted to predicting plant type distribution. The main results emerging from the new scheme are a high autumn and spring frost mortality, especially at colder sites, and increasing mid-winter frost mortality due to global warming, especially at warmer sites. We demonstrate that the new frost scheme is a major step forward in dynamically representing vegetation in ESMs by for the first time including a level of frost tolerance that is responding to the environment and includes some level of cost (implicitly) and benefit. By linking hardening and frost mortality in a land surface model, we open new ways to explore the impact of frost events in the context of global warming.

The Chinese Loess Plateau (CLP) in northern China is home to one of the most prominent loess records in the world, reflecting past eolian dust activity in East Asia. However, their interpretation is hampered by ambiguity in the origin of loess‐forming dust and an incomplete understanding of the circulation forcing dust accumulation. In this study, we used a novel modeling approach combining a dust emission model FLEXDUST with simulated back trajectories from FLEXPART to trace the dust back to where it was emitted. Over 21 years (1999–2019), we modeled back trajectories for fine (∼2 μm) and super‐coarse (∼20 μm) dust particles at six CLP sites during the peak dust storm season from March to May. FLEXPART source‐receptor relationships are combined with the dust emission inventory from FLEXDUST to create site‐dependent high‐resolution maps of the source contribution of deposited dust. The nearby dust emission areas were found to be the main source of dust to the CLP. Dust deposition across the CLP was found to predominantly occur via wet removal, with also some super‐coarse dust from distant emission regions being wet deposited following high‐level tropospheric transport. The high topography located on the downwind side of the emission area plays an essential role in forcing the emitted super‐coarse dust upward. On an interannual scale, the phase of the Arctic Oscillation in the preceding winter was found to have a strong association with the spring deposition rate on the CLP, while the strength of the East Asian Winter Monsoon was less influential. Plain Language Summary: The dust deposits on the Chinese Loess Plateau (CLP) in northern China provide an extensive record of changes in past dust activity in East Asia. In this work, we combine an atmosphere transport model with a dust emission model to trace the dust backward to where it was emitted. Choosing six locations at the CLP where we traced the dust back to emissions over a 21‐year period during the most active dust months from March until May, for which we investigated how different parts of the CLP were influenced by the different dust emission areas, transport mechanisms, and wind patterns. We find that dust is mainly brought from the emission areas located near the CLP, and that dust from far‐away emission areas in Central Asia has the potential to reach the CLP in smaller amounts. Furthermore, our results show that wet removal of dust by precipitation is important for dust deposition on the CLP, a mechanism that is often overlooked when explaining variations in past dust activity. On a year‐to‐year basis the dust deposition rate over the CLP was found to be connected to the high‐latitude northern hemisphere's climate oscillation (Arctic Oscillation) rather than the regional East Asian winter monsoon. Key Points: The source contribution of emitted dust aerosols to the Chinese Loess Plateau (CLP) is mapped using backward trajectory modelingDistant dust emission regions in Central Asia have a non‐negligible impact on the CLP, with wet deposited dust showing a clearer connectionStrong dust deposition years over the CLP are associated with the negative phase of the Arctic Oscillation [ABSTRACT FROM AUTHOR]

Results from the Intergovernmental Panel on Climatic Change (IPCC) tropospheric photochemical model intercomparison (PhotoComp) are presented with a brief discussion of the factors that may contribute to differences in the modeled behaviors of HOx cycling and the accompanying O3 tendencies. PhotoComp was a tightly controlled model experiment in which the IPCC 1994 assessment sought to determine the consistency among models that are used to predict changes in tropospheric ozone, an important greenhouse gas. Calculated tropospheric photodissociation rates displayed significant differences, with a root-mean-square (rms) error of the reported model results ranging from about ±6–9% of the mean (for O3 and NO2) to up to ±15% (H2O2 and CH2O). Models using multistream methods in radiative transfer calculations showed distinctly higher rates for photodissociation of NO2 and CH2O compared to models using two-stream methods, and this difference accounted for up to one third of the rms error for these two rates. In general, some small but systematic differences between models were noted for the predicted chemical tendencies in cases that did not include reactions of nomnethane hydrocarbons (NMHC). These differences in modeled O3 tendencies in some cases could be identified, for example, as being due to differences in photodissociation rates, but in others they could not and must be ascribed to unidentified errors. O3tendencies showed rms errors of about ±10% in the moist, surface level cases with NOx concentrations equal to a few tens of parts per trillion by volume. Most of these model to model differences can be traced to differences in the destruction of O3 due to reaction with HO2. Differences in HO2, in turn, are likely due to (1) inconsistent reaction rates used by the models for the conversion of HO2 to H2O2 and (2) differences in the model-calculated photolysis of H2O2 and CH2O. In the middle tropospheric “polluted” scenario with NOx concentrations larger than a few parts per billion by volume, O3 tendencies showed rms errors of ±10–30%. These model to model differences most likely stem from differences in the calculated rates of O3 photolysis to O(1 D), which provides about 80% of the HOx source under these conditions. The introduction of hydrocarbons dramatically increased both the rate of NOx loss and its model to model differences, which, in turn, are reflected in an increased spread of predicted O3. Including NMHC in the simulation approximately doubled the rms error for O3concentration.

For an 8-month period aerosol optical depth (AOD) is compared, derived over global oceans with five different retrieval algorithms applied to four satellite instruments flown on board three satellite platforms. The Advanced Very High Resolution Radiometer (AVHRR) was flown on hoard NOAA-14, the Ocean Color and Temperature Scanner (OCTS) and the Polarization and Directionality of the Earth's Reflectances (POLDER) on board the Advanced Earth Observing Satellite (ADEOS), and the Total Ozone Mapping Spectrometer (TOMS) on board the Earth Probe satellites. The aerosol data are presented on the same format and converted to the same wavelength in the comparison and can therefore be a useful tool in validation of global aerosol models, in particular models that can be driven with meteorological data for the November 1996 to June 1997 period studied here. Large uncertainties in the global mean AOD are found. There is at least a factor of 2 difference between the AOD from the retrievals. The largest uncertainties are found in the Southern Hemisphere, and the smallest differences mostly near the continents in the Northern Hemisphere. The largest relative differences are probably caused by differences in cloud screening.