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Quality assurance and quality control procedure for national and Union GHG projections 2019
The quality assurance and quality control (QA/QC) procedure is an element of the QA/QC programme of the Union system for policies and measures and projections to be established in 2019 according to Article 12 of the MMR. The European Environment Agency (EEA) is responsible for the annual implementation of the QA/QC procedures and is assisted by the European Topic Centre on Climate change mitigation and energy (ETC/CME). The QA/QC procedure document describes QA/QC checks carried out at EU level on the national reported projections from Member States and on the compiled Union GHG projections. QA/QC procedures are performed at several different stages during the preparation of the national and Union GHG projections in order to aim to ensure the timeliness, transparency, accuracy, consistency, comparability and completeness of the reported information. The results of the 2019 QA/QC procedure are presented in the related paper ETC/CME Eionet Report 2019/6.
ETC/CME
2019
Monitoring of greenhouse gases and aerosols at Svalbard and Birkenes in 2018. Annual report.
The report summaries the activities and results of the greenhouse gas monitoring at the Zeppelin Observatory situated on Svalbard in Arctic Norway during the period 2001-2018, and the greenhouse gas monitoring and aerosol observations from Birkenes for 2009-2018.
NILU
2019
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2019
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.
2019
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Using meteor wind data from the Super Dual Auroral Radar Network (SuperDARN) in the Northern Hemisphere, we (1) demonstrate that the migrating (Sun‐synchronous) tides can be separated from the nonmigrating components in the mesosphere and lower thermosphere (MLT) region and (2) use this to determine the response of the different components of the semidiurnal tide (SDT) to sudden stratospheric warming (SSW) conditions. The radars span a limited range of latitudes around 60°N and are located over nearly 180° of longitude. The migrating tide is extracted from the nonmigrating components observed in the meridional wind recorded from meteor ablation drift velocities around 95‐km altitude, and a 20‐year climatology of the different components is presented. The well‐documented late summer and wintertime maxima in the semidiurnal winds are shown to be due primarily to the migrating SDT, whereas during late autumn and spring the nonmigrating components are at least as strong as the migrating SDT. The robust behavior of the SDT components during SSWs is then examined by compositing 13 SSW events associated with an elevated stratopause recorded between 1995 and 2013. The migrating SDT is seen to reduce in amplitude immediately after SSW onset and then return anomalously strongly around 10–17 days after the SSW onset. We conclude that changes in the underlying wind direction play a role in modulating the tidal amplitude during the evolution of SSWs and that the enhancement in the midlatitude migrating SDT (previously reported in modeling studies) is observed in the MLT at least up to 60°N.
2019
2019
Polycyclic Aromatic Hydrocarbons Not Declining in Arctic Air Despite Global Emission Reduction
Two decades of atmospheric measurements of polycyclic aromatic hydrocarbons (PAHs) were conducted at three Arctic sites, i.e., Alert, Canada; Zeppelin, Svalbard; and Pallas, Finland. PAH concentrations decrease with increasing latitude in the order of Pallas > Zeppelin > Alert. Forest fire was identified as an important contributing source. Three representative PAHs, phenanthrene (PHE), pyrene (PYR), and benzo[a]pyrene (BaP) were selected for the assessment of their long-term trends. Significant decline of these PAHs was not observed contradicting the expected decline due to PAH emission reductions. A global 3-D transport model was employed to simulate the concentrations of these three PAHs at the three sites. The model predicted that warming in the Arctic would cause the air concentrations of PHE and PYR to increase in the Arctic atmosphere, while that of BaP, which tends to be particle-bound, is less affected by temperature. The expected decline due to the reduction of global PAH emissions is offset by the increment of volatilization caused by warming. This work shows that this phenomenon may affect the environmental occurrence of other anthropogenic substances, such as more volatile flame retardants and pesticides.
2019