The Sub-Daily Variability of Aerosol Loading and Associated Radiative Forcing Over the Indian Region

The sub-daily variability of aerosols affects the estimates of daily mean aerosol loading. However, large spatial scale estimates of their climate effects are mostly based on snapshots from low orbit satellites that may bias the mean estimate for daily, monthly, or annual timescales. In this study, an attempt is made to estimate the magnitude of such bias based on ground and satellite-based datasets. Using ground-based measurements, we show an apparent asymmetry (of the order of 10–50%) in the sub-daily variability of aerosol loading over the Indian region. For the first time, it is reported that this sub-daily variability has a spatial pattern with an increasing amplitude toward the east of the subcontinent. We also find this variability in aerosol loading is well-captured by the satellites but with a lower amplitude. Our study shows that such differences could alter the annual surface radiative forcing estimates by more than ∼15 W m−2 over this region. We find that NASA’s Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), a state-of-the-art model-based chemical reanalysis, is unable to capture these sub-daily variabilities. This implies that both model and satellite-based radiative forcing estimates for large spatial scales should improve aerosol sub-daily information/variabilities for obtaining reliable radiative forcing estimates.

Mean Daily Variability of Energy Fluxes Above Alexandria Eastern Harbor

Mean daily variability of latent heat (E), sensible heat (H), net long wave (Lwnet), net short wave, and net flux of surface heat balance were estimated from hourly sea surface water temperature (SST) and meteorological time series obtained for three months during summer season (2019) in Alexandria Eastern Harbor (AEH), Egypt. Latent and sensible heat were not in phase and had their maximum 181.12 W/m2 (5:00 PM), 16.5 W/m2 (5:00 AM) and minimum 103.64 W/m2 (8:00 AM), -12.14 W/m2 (3:00 PM), resulting in Bowen ration of -0.11 and 0.09, respectively. The loss of heat by evaporation therefore predominates than sensible heat utilized to warm surface atmosphere. The instability of the atmosphere was existing nearly most of the time period, rising exchange coefficients of sensible and latent heat flux by about 24.26% over estimated neutral values (from 1.15 × 10−3 to 1.43 × 10−3). Mean Lwnet changed from 165.63 at early morning to 173.52 W/m2 at late afternoon, point out its significant importance in the total balance of heat flux of eastern harbor surface. Latent heat flux and Lwnet were positive (energy losing from eastern harbor), throughout the day. The daily average of net energy budget (S) was 38.52 W/m2; daytime gain exceeded nighttime loss, with consequent heating the eastern harbor. Qualitatively, daily variations of net energy budget (S) were nearly consistent with time delay to the variability of sea surface temperature, indicating the predominant role of the heat budget of the surface layer in modulating surface temperatures of the Eastern Harbor. Keywords: heat flux, shortwave, long wave, latent heat, sensible heat, Eastern Harbor

Footprint of greenhouse forcing in daily temperature variability

Changes in mean climatic conditions will affect natural and societal systems profoundly under continued anthropogenic global warming. Changes in the high-frequency variability of temperature exert additional pressures, yet the effect of greenhouse forcing thereon has not been fully assessed or identified in observational data. Here, we show that the intramonthly variability of daily surface temperature changes with distinct global patterns as greenhouse gas concentrations rise. In both reanalyses of historical observations and state-of-the-art projections, variability increases at low to mid latitudes and decreases at northern mid to high latitudes with enhanced greenhouse forcing. These latitudinally polarized daily variability changes are identified from internal climate variability using a recently developed signal-to-noise-maximizing pattern-filtering technique. Analysis of a multimodel ensemble from the Coupled Model Intercomparison Project Phase 6 shows that these changes are attributable to enhanced greenhouse forcing. By the end of the century under a business-as-usual emissions scenario, daily temperature variability would continue to increase by up to a further 100% at low latitudes and decrease by 40% at northern high latitudes. Alternative scenarios demonstrate that these changes would be limited by mitigation of greenhouse gases. Moreover, global changes in daily variability exhibit strong covariation with warming across climate models, suggesting that the equilibrium climate sensitivity will also play a role in determining the extent of future variability changes. This global response of the high-frequency climate system to enhanced greenhouse forcing is likely to have strong and unequal effects on societies, economies, and ecosystems if mitigation and protection measures are not taken.

Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO₂ measurements

We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

Cloud Detection Over Sunglint Regions With Observations From the Earth Polychromatic Imaging Camera

With the ability to observe the entire sunlit side of the Earth, EPIC data have become an important resource for studying cloud daily variability. Inaccurate cloud masking is a great source of uncertainty. One main region that is prone to error in cloud masking is the sunglint area over ocean surfaces. Cloud detection over these regions is challenging for the EPIC instrument because of its limited spectral channels. Clear sky ocean surface reflectance from visible channels over sunglint is much larger than that over the non-glint areas and can exceed reflectance from thin clouds. This paper presents an improved EPIC ocean cloud masking algorithm (Version 3). Over sunglint regions (glint angle ≤25°), the algorithm utilizes EPIC’s oxygen (O2) A-band ratio (764/780 nm) in addition to the 780 nm reflectance observations in masking tests. Outside the sunglint regions, a dynamic reflectance threshold for the Rayleigh corrected 780 nm reflectance is applied. The thresholds are derived as a function of glint angle. When compared with co-located data from the geosynchronous Earth orbit (GEO) and the low Earth orbit (LEO) observations, the consistency of the new ocean cloud mask algorithm has increased by 4∼10% and 4∼6% in the glint center and granule edges respectively. The false positive rate is reduced by 10∼17%. Overall global ocean cloud detection consistency increases by 2%. This algorithm, along with other improvements to the EPIC cloud masks, has been implemented in the EPIC cloud products Version 3. This algorithm will improve the cloud daily variability analysis by removing the artificial peak at local noon time in the glint center latitudes and reducing biases in the early morning and late afternoon cloud fraction over ocean surfaces.

Peculiarities of temporal variability of dissolved oxygen content in eelgrass Zostera marina Linnaeus, 1753 meadows in the Voevoda Bay (the Amur Bay, the Sea of Japan)

Currently, the shallow basins with Zostera marina L. meadows are considered as absorbers of atmospheric carbon dioxide, capable of restraining an increase in its concentration. Due to its high primary productivity, eelgrass releases a large amount of oxygen into the environment. To establish the peculiarities of production activity in shallow-water basins, covered with Z. marina meadows, we conducted monitoring of hydrological and production indicators with different measurement intervals on the example of the Voevoda Bay (the Amur Bay, the Sea of Japan). Observations were carried out for eight and a half months (22.09.2012–07.06.2013). Measurements of temperature, salinity, chlorophyll fluorescence, and turbidity were carried out in Z. marina meadows at a depth of 4 m every three hours by a Water Quality Monitor hydrological station. Dissolved oxygen content was determined every hour by an optical oxygen sensor ARO-USB. Two types of oxygen concentration variability were established: 1) seasonal variability, mostly resulting from seasonal variations in the environment; 2) daily variability during the freeze-up period, mostly determined by the intensity of photosynthetically active radiation penetration into sub-ice water. In the autumn season, low oxygen concentrations, up to hypoxic level, were recorded. In the winter and spring seasons, the oxygen content was, as a rule, at 100–130 % of saturation. High daily variability was observed during the freeze-up period, with no snow coverage. In February, the range of daily fluctuations of oxygen concentration reached 730 μmol·kg−1, with 3-fold supersaturation regarding atmospheric O2. As established, the maximum rate of oxygen production, relative to 1 g of Z. marina wet weight, is 6.5 mg O2·h−1·g−1. High daily dynamics of oxygen in seawater is analyzed in relation to eelgrass physiological peculiarities (air lacunae play an important role in oxygen dynamics in the environment), as well as to short-period tides. .

Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO₂ measurements

We present high spatial resolution (up to 2.2 × 2.2 km2 simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMR) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability, and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS measurements performed at Mainz (49.99° N, 8.23° E) were used to evaluate the simulated tropospheric vertical column densities (VCD) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles ≤ 8°), small biases in the range of −14 to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when the atmospheric lifetime of NO2 is relatively long.