The Impact of GPS RO Data on the Prediction of Tropical Cyclogenesis Using a Nonlocal Observation Operator: An Initial Assessment

In this study, the impact of global positioning system (GPS) radio occultation (RO) data on the prediction of the genesis of 10 tropical cyclones over the western North Pacific Ocean is assessed. With the use of a nonlocal excess phase observation operator in cycling data assimilation, the probability of detection for tropical cyclogenesis is increased from 30% to 70% for the cases considered, all of which developed into typhoons. However, the probability of detection is only increased to 40% when a local observation operator is used, indicating that the observation operator can significantly influence the performance of RO data assimilation in capturing tropical cyclogenesis. A nonlocal excess phase operator, which considers the atmospheric horizontal gradients by integrating the refractivity along a ray path, gives superior performance over the local observation operator. Additional sensitivity experiments on 3 of the 10 typhoon cases show that the RO data in the vicinity of the incipient cyclones (within 500 km of the cyclone center) are most critical to successful cyclogenesis prediction. This reflects the fact that having good RO observations at the right time and place is critical for RO to have beneficial impacts on tropical cyclogenesis. Further analyses for Typhoon Nuri (2008) show that assimilation of RO data using the nonlocal operator leads to moistening of the lower and middle troposphere, organized convection, robust grid-scale vertical motions, and the development of midlevel relative vorticity, all of which are favorable for tropical cyclogenesis.

Mineralogy of the deep lower mantle in the presence of H2O

Understanding the mineralogy of the Earth's interior is a prerequisite for unravelling the evolution and dynamics of our planet. Here, we conducted high pressure-temperature experiments mimicking the conditions of the deep lower mantle (DLM, 1800–2890 km in depth) and observed surprising mineralogical transformations in the presence of water. Ferropericlase, (Mg, Fe)O, which is the most abundant oxide mineral in Earth, reacts with H2O to form a previously unknown (Mg, Fe)O2Hx (x ≤ 1) phase. The (Mg, Fe)O2Hx has a pyrite structure and it coexists with the dominant silicate phases, bridgmanite and post-perovskite. Depending on Mg content and geotherm temperatures, the transformation may occur at 1800 km for (Mg0.6Fe0.4)O or beyond 2300 km for (Mg0.7Fe0.3)O. The (Mg, Fe)O2Hx is an oxygen excess phase that stores an excessive amount of oxygen beyond the charge balance of maximum cation valences (Mg2+, Fe3+ and H+). This important phase has a number of far-reaching implications including extreme redox inhomogeneity, deep-oxygen reservoirs in the DLM and an internal source for modulating oxygen in the atmosphere.

Evidence for oxygenation of Fe-Mg oxides at mid-mantle conditions and the rise of deep oxygen

As the reaction product of subducted water and the iron core, FeO2 with more oxygen than hematite (Fe2O3) has been recently recognized as an important component in the D” layer just above the Earth's core-mantle boundary. Here, we report a new oxygen-excess phase (Mg, Fe)2O3+δ (0 < δ < 1, denoted as ‘OE-phase’). It forms at pressures greater than 40 gigapascal when (Mg, Fe)-bearing hydrous materials are heated over 1500 kelvin. The OE-phase is fully recoverable to ambient conditions for ex situ investigation using transmission electron microscopy, which indicates that the OE-phase contains ferric iron (Fe3+) as in Fe2O3 but holds excess oxygen through interactions between oxygen atoms. The new OE-phase provides strong evidence that H2O has extraordinary oxidation power at high pressure. Unlike the formation of pyrite-type FeO2Hx which usually requires saturated water, the OE-phase can be formed with under-saturated water at mid-mantle conditions, and is expected to be more ubiquitous at depths greater than 1000 km in the Earth's mantle. The emergence of oxygen-excess reservoirs out of primordial or subducted (Mg, Fe)-bearing hydrous materials may revise our view on the deep-mantle redox chemistry.

Assessment of global navigation satellite system (GNSS) radio occultation refractivity under heavy precipitation

A positive bias at heights between 3 and 8 km has been observed when comparing the radio-occultation (RO)-retrieved refractivity with that of meteorological analyses and reanalyses in cases where heavy precipitation is present. The effect of precipitation in RO retrievals has been investigated as a potential cause of the bias, using precipitation measurements interpolated into the actual three-dimensional RO ray paths to calculate the excess phase induced by precipitation. The study consisted of comparing the retrievals when such extra delay is removed from the actual measurement and when it is not. The results show how precipitation itself is not the cause of the positive bias. Instead, we show that the positive bias is linked to high specific-humidity conditions regardless of precipitation. This study also shows a regional dependence of the bias. Furthermore, different analyses and reanalyses show a disagreement under high specific-humidity conditions and, in consequence, heavy precipitation.

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere – such as pressure, temperature, and tropospheric water vapor profiles (involving background information) – can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications.

Assessment of GNSS radio occultation refractivity under heavy precipitation

A positive bias at heights between 3 and 8 km has been observed when comparing the radio occultation retrieved refractivity with that of meteorological analyses and re-analyses, in cases where heavy precipitation is present. The effect of precipitation in RO retrievals has been investigated as a potential cause of the bias, using precipitation measurements interpolated into the actual three dimensional RO raypaths to calculate the excess phase induced by precipitation. The study consisted in comparing the retrievals when such extra delay is removed from the actual measurement and when it is not. The results show how precipitation itself is not the cause of the positive bias. Instead, we show that the positive bias is linked to high specific humidity conditions regardless of precipitation. This study also shows a regional dependence of the bias. Furthermore, different analyses and re-analyses show a disagreement under high specific humidity conditions and in consequence, heavy precipitation.