Climate Data Records of soil moisture are fundamental for improving our understanding of long-term dynamics in the coupled water, energy, and carbon cycles over land. To respond to this need, in 2012 ...the European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program. This product, named ESA CCI SM, combines various single-sensor active and passive microwave soil moisture products into three harmonised products: a merged ACTIVE, a merged PASSIVE, and a COMBINED active+passive microwave product. Compared to the first product release, the latest version of ESA CCI SM includes a large number of enhancements, incorporates various new satellite sensors, and extends its temporal coverage to the period 1978–2015. In this study, we first provide a comprehensive overview of the characteristics, evolution, and performance of the ESA CCI SM products. Based on original research and a review of existing literature we show that the product quality has steadily increased with each successive release and that the merged products generally outperform the single-sensor input products. Although ESA CCI SM generally agrees well with the spatial and temporal patterns estimated by land surface models and observed in-situ, we identify surface conditions (e.g., dense vegetation, organic soils) for which it still has large uncertainties. Second, capitalising on the results of >100 research studies that made use of the ESA CCI SM data we provide a synopsis of how it has contributed to improved process understanding in the following Earth system domains: climate variability and change, land-atmosphere interactions, global biogeochemical cycles and ecology, hydrological and land surface modelling, drought applications, and meteorology. While in some disciplines the use of ESA CCI SM is already widespread (e.g. in the evaluation of model soil moisture states) in others (e.g. in numerical weather prediction or flood forecasting) it is still in its infancy. The latter is partly related to current shortcomings of the product, e.g., the lack of near-real-time availability and data gaps in time and space. This study discloses the discrepancies between current ESA CCI SM product characteristics and the preferred characteristics of long-term satellite soil moisture products as outlined by the Global Climate Observing System (GCOS), and provides important directions for future ESA CCI SM product improvements to bridge these gaps.
•State-of-the-art of the ESA CCI soil moisture (ESA CCI SM) product specifications•A comprehensive assessment of the ESA CCI SM error characteristics•A unique synthesis of studies using ESA CCI SM to improve Earth system understanding.•Identification of future algorithmic and programmatic priorities
Due to its comparatively high spatial resolution and its daily repeat frequency, the tropospheric nitrogen dioxide product provided by the TROPOspheric Monitoring Instrument (TROPOMI) onboard the ...Sentinel-5 Precursor platform has attracted significant attention for its potential for urban-scale monitoring of air quality. However, the exploitation of such data in, for example, operational assimilation of local-scale dispersion models is often complicated by substantial data gaps due to cloud cover or other retrieval limitations. These challenges are particularly prominent in high-latitude regions where significant cloud cover and high solar zenith angles are often prevalent. Using the example of Norway as a representative case for a high-latitude region, we here evaluate the spatiotemporal patterns in the availability of valid data from the operational TROPOMI tropospheric nitrogen dioxide (NO2) product over five urban areas (Oslo, Bergen, Trondheim, Stavanger, and Kristiansand) and a 2.5 year period from July 2018 through November 2020. Our results indicate that even for relatively clean environments such as small Norwegian cities, distinct spatial patterns of tropospheric NO2 are visible in long-term average datasets from TROPOMI. However, the availability of valid data on a daily level is limited by both cloud cover and solar zenith angle (during the winter months), causing the fraction of valid retrievals in each study site to vary from 20% to 50% on average. A temporal analysis shows that for our study sites and the selected period, the fraction of valid pixels in each domain shows a clear seasonal cycle reaching a maximum of 50% to 75% in the summer months and 0% to 20% in winter. The seasonal cycle in data availability shows the inverse behavior of NO2 pollution in Norway, which typically has its peak in the winter months. However, outside of the mid-winter period we find the TROPOMI NO2 product to provide sufficient data availability for detailed mapping and monitoring of NO2 pollution in the major urban areas in Norway and see potential for the use of the data in local-scale data assimilation and emission inversions applications.
The increased availability of commercially-available low-cost air quality sensors combined with increased interest in their use by citizen scientists, community groups, and professionals is resulting ...in rapid adoption, despite data quality concerns. We have characterized three out-the-box PM sensor systems under different environmental conditions, using field colocation against reference equipment. The sensor systems integrate Plantower 5003, Sensirion SPS30 and Alphasense OCP-N3 PM sensors. The first two use photometry as a measuring technique, while the third one is an optical particle counter. For the performance evaluation, we co-located 3 units of each manufacturer and compared the results against optical (FIDAS) and gravimetric (KFG) methods for a period of 7 weeks (28 August to 19 October 2020). During the period from 2nd and 5th October, unusually high PM concentrations were observed due to a long-range transport episode. The results show that the highest correlations between the sensor systems and the optical reference are observed for PM1, with coefficients of determination above 0.9, followed by PM2.5. All the sensor units struggle to correctly measure PM10, and the coefficients of determination vary between 0.45 and 0.64. This behavior is also corroborated when using the gravimetric method, where correlations are significantly higher for PM2.5 than for PM10, especially for the sensor systems based on photometry. During the long range transport event the performance of the photometric sensors was heavily affected, and PM10 was largely underestimated. The sensor systems evaluated in this study had good agreement with the reference instrumentation for PM1 and PM2.5; however, they struggled to correctly measure PM10. The sensors also showed a decrease in accuracy when the ambient size distribution was different from the one for which the manufacturer had calibrated the sensor, and during weather conditions with high relative humidity. When interpreting and communicating air quality data measured using low-cost sensor systems, it is important to consider such limitations in order not to risk misinterpretation of the resulting data.
This paper presents a modelling study on the fate of CHBr3 and its
product gases in the troposphere within the context of tropical deep
convection. A cloud-scale case study was conducted along the ...west coast of
Borneo, where several deep convective systems were triggered on the afternoon and
early evening of 19 November 2011. These systems were sampled by the Falcon
aircraft during the field campaign of the SHIVA project and analysed using a
simulation with the cloud-resolving meteorological model C-CATT-BRAMS at 2×2 km resolution that represents the emissions, transport by
large-scale flow, convection, photochemistry, and washout of CHBr3
and its product gases (PGs). We find that simulated CHBr3 mixing
ratios and the observed values in the boundary layer and the outflow of the
convective systems agree. However, the model underestimates the background
CHBr3 mixing ratios in the upper troposphere, which suggests a
missing source at the regional scale. An analysis of the simulated chemical
speciation of bromine within and around each simulated convective system
during the mature convective stage reveals that >85 % of the
bromine derived from CHBr3 and its PGs is transported vertically to
the point of convective detrainment in the form of CHBr3 and that
the remaining small fraction is in the form of organic PGs, principally
insoluble brominated carbonyls produced from the photo-oxidation of
CHBr3. The model simulates that within the boundary layer and free
troposphere, the inorganic PGs are only present in soluble forms, i.e. HBr,
HOBr, and BrONO2, and, consequently, within the convective clouds,
the inorganic PGs are almost entirely removed by wet scavenging. We find that
HBr is the most abundant PG in background lower-tropospheric air and that this
prevalence of HBr is a result of the relatively low background tropospheric
ozone levels at the regional scale. Contrary to a previous study in a
different environment, for the conditions in the simulation, the insoluble
Br2 species is hardly formed within the convective systems and
therefore plays no significant role in the vertical transport of bromine. This
likely results from the relatively small quantities of simulated inorganic
bromine involved, the presence of HBr in large excess compared to HOBr and
BrO, and the relatively efficient removal of soluble compounds within the
convective column.
We review the status of marine shellfish ecosystems formed primarily by bivalves in Australia, including: identifying ecosystem-forming species, assessing their historical and current extent, causes ...for decline and past and present management. Fourteen species of bivalves were identified as developing complex, three-dimensional reef or bed ecosystems in intertidal and subtidal areas across tropical, subtropical and temperate Australia. A dramatic decline in the extent and condition of Australia's two most common shellfish ecosystems, developed by Saccostrea glomerata and Ostrea angasi oysters, occurred during the mid-1800s to early 1900s in concurrence with extensive harvesting for food and lime production, ecosystem modification, disease outbreaks and a decline in water quality. Out of 118 historical locations containing O. angasi-developed ecosystems, only one location still contains the ecosystem whilst only six locations are known to still contain S. glomerata-developed ecosystems out of 60 historical locations. Ecosystems developed by the introduced oyster Crasostrea gigas are likely to be increasing in extent, whilst data on the remaining 11 ecosystem-forming species are limited, preventing a detailed assessment of their current ecosystem-forming status. Our analysis identifies that current knowledge on extent, physical characteristics, biodiversity and ecosystem services of Australian shellfish ecosystems is extremely limited. Despite the limited information on shellfish ecosystems, a number of restoration projects have recently been initiated across Australia and we propose a number of existing government policies and conservation mechanisms, if enacted, would readily serve to support the future conservation and recovery of Australia's shellfish ecosystems.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. ...However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error–covariance in the EnOI is sampled in two ways: (i) by using the stochastic spread from an ensemble open-loop run, and (ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore, the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in situ observations at a 95 % significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in situ data at the same significance level; however this improvement is dependent on which in situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95 % significance level. The study also suggests that assimilation of satellite derived surface soil moisture using the EnOI can correct random errors in the atmospheric forcing and give an analysed surface soil moisture close to that of an open-loop run using observation derived precipitation. Importantly, this shows that estimates of soil moisture could be improved using a combination of assimilating SMAP using the computationally cheap EnOI while using model derived precipitation as forcing. Finally, we assimilate three different Level-2 satellite derived soil moisture products from the European Space Agency Climate Change Initiative (ESA CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.
Spawning sources of King George whiting
Sillaginodes punctatus
populations in the states of South Australia and Victoria (south-eastern Australia) were analysed using otolith chemistry and ...microstructure from post-larvae sampled from 3 nursery areas in each state in the spring of 2011 and 2012. Univariate and multivariate analysis of the chemistry of the core region of otoliths showed differences between states, particularly for the 2011 cohort, primarily related to higher Mg in South Australian samples, while differences in Sr and Zn also made a contribution. Even though spawning times overlapped, early larval growth rates were higher for post-larvae from South Australia than Victoria. Differences in microchemistry were most evident for elements influenced by physiological processes and were potentially influenced by the different larval growth rates. Overall, otolith chemical and microstructure analyses for post-larvae in Victoria and South Australia indicated that spawning sources for the 2 states were different, qualified by results from otolith microchemistry that were less clear for the 2012 cohort. Even though genetic analyses do not indicate genetic differentiation across the 2 states, and therefore would support cross-jurisdictional management, the results of this study give qualified support to the current arrangement wherein the
S. punctatus
fishery is managed separately by the individual jurisdictions, subject to further information on stock structure coming to light in the future.
Mapping drought from space using, e.g., surface soil moisture (SSM), has become viable in the last decade. However, state of the art SSM retrieval products suffer from very poor coverage over ...northern latitudes. In this study, we propose an innovative drought indicator with a wider spatial and temporal coverage than that obtained from satellite SSM retrievals. We evaluate passive microwave brightness temperature observations from the Soil Moisture and Ocean Salinity (SMOS) satellite as a surrogate drought metric, and introduce a Standardized Brightness Temperature Index (STBI). We compute the STBI by fitting a Gaussian distribution using monthly brightness temperature data from SMOS; the normal assumption is tested using the Shapior-Wilk test. Our results indicate that the assumption of normally distributed brightness temperature data is valid at the 0.05 significance level. The STBI is validated against drought indices from a land surface data assimilation system (LDAS-Monde), two satellite derived SSM indices, one from SMOS and one from the ESA CCI soil moisture project and a standardized precipitation index based on in situ data from the European Climate Assessment & Dataset (ECA&D) project. When comparing the temporal dynamics of the STBI to the LDAS-Monde drought index we find that it has equal correlation skill to that of the ESA CCI soil moisture product ( 0.71 ). However, in addition the STBI provides improved spatial coverage because no masking has been applied over regions with dense boreal forest. Finally, we evaluate the STBI in a case study of the 2018 Nordic drought. The STBI is found to provide improved spatial and temporal coverage when compared to the drought index created from satellite derived SSM over the Nordic region. Our results indicate that when compared to drought indices from precipitation data and a land data assimilation system, the STBI is qualitatively able to capture the 2018 drought onset, severity and spatial extent. We did see that the STBI was unable to detect the 2018 drought recovery for some areas in the Nordic countries. This false drought detection is likely linked to the recovery of vegetation after the drought, which causes an increase in the passive microwave brightness temperature, hence the STBI shows a dry anomaly instead of normal conditions, as seen for the other drought indices. We argue that the STBI could provide additional information for drought monitoring in regions where the SSM retrieval problem is not well defined. However, it then needs to be accompanied by a vegetation index to account for the recovery of the vegetation which could cause false drought detection.
Larval snapper (
Chrysophrys auratus
, Sparidae) sampled over 7 years had different diets and feeding strategies between years with lower versus higher larval and 0+ abundances. We analysed stomach ...contents of snapper larvae from each year to determine diet composition, prey selectivity, prey quality, and trophic niche breadth and compared larval diet with prey availability. Snapper larvae from higher abundance years were specialized foragers selecting for calanoid nauplii at 2–4 mm standard length (SL) and calanoid copepodites and cladocerans at >4 mm SL. These larvae were characterized by either a constant or dome-shaped trophic niche breadth and an increase in prey quality (size of consumed prey) with increasing larval size. Snapper larvae from lower abundance years were generalist foragers characterized by an increase in trophic niche breadth, but not prey quality, with increasing larval size. Changes in foraging strategies were concordant with changes in the prey environment, with low zooplankton densities corresponding with generalist diet (lower larval abundance) years and high zooplankton densities with specialist diet (higher larval abundance) years. These findings suggest that snapper larval survival and juvenile recruitment strength is linked to changes in larval diet that relate to prey abundance and composition.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This paper describes the Eulerian urban dispersion model EPISODE. EPISODE was developed to address a need for an urban air quality model in support of policy, planning, and air quality management in ...the Nordic, specifically Norwegian, setting. It can be used for the calculation of a variety of airborne pollutant concentrations, but we focus here on the implementation and application of the model for NO2 pollution. EPISODE consists of an Eulerian 3D grid model with embedded sub-grid dispersion models (e.g. a Gaussian plume model) for dispersion of pollution from line (i.e. roads) and point sources (e.g. chimney stacks). It considers the atmospheric processes advection, diffusion, and an NO2 photochemistry represented using the photostationary steady-state approximation for NO2. EPISODE calculates hourly air concentrations representative of the grids and at receptor points. The latter allow EPISODE to estimate concentrations representative of the levels experienced by the population and to estimate their exposure. This methodological framework makes it suitable for simulating NO2 concentrations at fine-scale resolution (<100 m) in Nordic environments. The model can be run in an offline nested mode using output concentrations from a global or regional chemical transport model and forced by meteorology from an external numerical weather prediction model; it also can be driven by meteorological observations. We give a full description of the overall model function and its individual components. We then present a case study for six Norwegian cities whereby we simulate NO2 pollution for the entire year of 2015. The model is evaluated against in situ observations for the entire year and for specific episodes of enhanced pollution during winter. We evaluate the model performance using the FAIRMODE DELTA Tool that utilises traditional statistical metrics, e.g. root mean square error (RMSE), Pearson correlation R, and bias, along with some specialised tests for air quality model evaluation. We find that EPISODE attains the DELTA Tool model quality objective in all of the stations we evaluate against. Further, the other statistical evaluations show adequate model performance but that the model scores greatly improved correlations during winter and autumn compared to the summer. We attribute this to the use of the photostationary steady-state scheme for NO2, which should perform best in the absence of local ozone photochemical production. Oslo does not comply with the NO2 annual limit set in the 2008/50/EC directive (AQD). NO2 pollution episodes with the highest NO2 concentrations, which lead to the occurrence of exceedances of the AQD hourly limit for NO2, occur primarily in the winter and autumn in Oslo, so this strongly supports the use of EPISODE for application to these wintertime events. Overall, we conclude that the model is suitable for an assessment of annual mean NO2 concentrations and also for the study of hourly NO2 concentrations in the Nordic winter and autumn environment. Further, in this work we conclude that it is suitable for a range of policy applications specific to NO2 that include pollution episode analysis, evaluation of seasonal statistics, policy and planning support, and air quality management. Lastly, we identify a series of model developments specifically designed to address the limitations of the current model assumptions. Part 2 of this two-part paper discusses the CityChem extension to EPISODE, which includes a number of implementations such as a more comprehensive photochemical scheme suitable for describing more chemical species and a more diverse range of photochemical environments, as well as a more advanced treatment of the sub-grid dispersion.
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