The diurnal cycle throughout the stratosphere is analyzed by applying Bayesian interpolation to Constellation Observing System for Meteorology, Ionosp…The diurnal cycle throughout the stratosphere is analyzed by applying Bayesian interpolation to Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) Global Positioning System radio occultation (RO) data and three scientific applications of the analysis are introduced. First, the migrating thermal tides are analyzed with unprecedented accuracy and precision, with an uncertainty in the analysis of the vertically propagating tides ranging from 0.1 in the lower stratosphere to 0.6 K in the upper stratosphere for an individual month of RO data and with an uncertainty in a 10-year climatological diurnal cycle a factor of 10 less. Moreover, the midlatitude trapped tide is found to be smaller than what is produced by an atmospheric model and lags the model in phase, a likely consequence of a faulty parameterization of eddy diffusivity in the upper stratosphere. Second, a clear signal of solar cycle influence on the diurnal cycle is evident in this analysis, but whether the cause is the systematic bias of ionospheric residual associated with RO retrieval or it is an actual atmospheric phenomenon is less clear. Third, RO satellites and missions that obtain inadequate coverage of the diurnal cycle will be biased by under-sampling it, whether or not subsampling weather forecasts is used to removal sampling error. The analysis of the diurnal cycle in COSMIC RO data can be used to diagnose the systematic sampling error incurred by incomplete coverage of the diurnal cycle, which is of the order of 0.2 K for a Metop-based RO climatology.more
Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on…Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on the open-source software package Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For this purpose, the MOZART (Model for Ozone and Related chemical Tracers)-MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) chemical reaction mechanism is extended by bromine and chlorine reactions as well as an emission mechanism for reactive bromine via heterogeneous reactions on snow surfaces. The simulation domain covers an area of 5040km x 4960km, centered north of Utqiagvik (formerly Barrow), Alaska, and the time interval from February through May 2009. Several simulations for different strengths of the bromine emission are conducted and evaluated by comparison with in situ and ozone sonde measurements of ozone mixing ratios as well as by comparison with tropospheric BrO vertical column densities (VCDs) from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instrument. The base bromine emission scheme includes the direct emission of bromine due to bromide oxidation by ozone. Results of simulations with the base emission rate agree well with the observations; however, a simulation with 50% faster emissions performs somewhat better. The bromine emission due to bromide oxidation by ozone is found to be important to provide an initial seed for the bromine explosion. Bromine release due to N2O5 was found to be important from February to mid March but irrelevant thereafter. A comparison of modeled BrO with in situ and multi-axis differential optical absorption spectroscopy (MAX-DOAS) data hints at missing bromine release and recycling mechanisms on land or near coasts. A consideration of halogen chemistry substantially improves the prediction of the ozone mixing ratio with respect to the observations. Meteorological nudging is essential for a good prediction of ODEs over the 3-month period.more
When using neural networks (NNs), the lack of input information characterizing the radiative transfer can result in regional biases, especially when r…When using neural networks (NNs), the lack of input information characterizing the radiative transfer can result in regional biases, especially when retrieving surface properties. In the Part I companion article we explored localization techniques in an attempt to help the NN adjust its behaviour to local conditions. In this article we analyze results from an image-processing approach, the novel localized convolutional NN (CNN) model for the retrieval of surface temperature (TS) over a fixed domain using infrared atmospheric sounding interferometer (IASI) observations. An in-depth evaluation is performed. The localized-CNN architecture is a promising artificial intelligence solution that provides retrievals similar to, if not better than, those of the European Organisation for the Exploitation of Meteorological Satellites' PWLR3 retrieval algorithm that also uses IASI observations, collocated with microwave data too. This shows the benefits of localizing the CNN retrieval. This image-processing retrieval scheme allows interpolation of the TS below the clouds, and thus a preliminary analysis of the cloud impact on the TS is performed. The possibility to estimate retrieval uncertainties is investigated, and a practical solution, based on the binning of the input space, is proposed for CNN architectures. The best strategy for a global-scale retrieval is yet to be found for such an image-processing scheme, but potential solutions and their respective advantages and disadvantages are discussed.more
Climate services are becoming the backbone to translate climate knowledge, data & information into climate-informed decision-making at all levels, fro…Climate services are becoming the backbone to translate climate knowledge, data & information into climate-informed decision-making at all levels, from public administrations to business operators. It is essential to assess the technical and scientific quality of the provided climate data and information products, including their value to users, to establish the relation of trust between providers of climate data and information and various downstream users. The climate data and information products (i.e., from satellite, in-situ and reanalysis) shall be fully traceable, adequately documented and uncertainty quantified and can provide sufficient guidance for users to address their specific needs and feedbacks. This paper discusses details on how to apply the quality assurance framework to deliver timely assessments of the quality and usability of Essential Climate Variable (ECV) products. It identifies an overarching structure for the quality assessment of single product ECVs (i.e., consists of only one single variable), multi-product ECVs (i.e., more than one single parameter), thematic products (i.e., water, energy and carbon cycles), as well as the usability assessment. To support a traceable climate service, other than rigorously evaluating the technical and scientific quality of ECV products, which represent the upstream of climate services, how the uncertainty propagates into the resulting benefit (utility) for the users of the climate service needs to be detailed.more
We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (G…We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.more