Refractivity and temperature climate records from multiple radio occultation satellites consistent within 0.05%

Data consistency is an important prerequisite to build radio occultation (RO) climatologies based on a combined record of data from different satellites. The presence of multiple RO receiving satellites in orbit over the same time period allows for testing this consistency. We used RO data from CHAMP (CHAllenging Minisatellite Payload for geoscientific research), six FORMOSAT-3/COSMIC satellites (Formosa Satellite Mission 3/Constellation Observing System for Meteorology, Ionosphere and Climate, F3C), and GRACE-A (Gravity Recovery and Climate Experiment). We show latitude-altitude-resolved results for an example month (October 2007) and the temporal evolution of differences in a climate record of global and monthly means from January 2007 to December 2009. Latitude- and altitude-resolved refractivity and dry temperature climatologies clearly show the influence of different sampling characteristics; monthly mean deviations from the multi-satellite mean over the altitude domain 10 km to 30 km typically reach 0.1% and 0.2 K, respectively. Nevertheless, the 3-yr average deviations (shorter for CHAMP) are less than 0.03% and 0.05 K, respectively. We find no indications for instrument degradation, temporal inhomogeneities in the RO records, or temporal trends in sampling patterns. Based on analysis fields from ECMWF (European Centre for Medium-Range Weather Forecasts), we can estimate – and subtract – the sampling error from each monthly climatology. After such subtraction, refractivity deviations are found reduced to <0.05% in almost any month and dry temperature deviations to <0.05 K (<0.02% relative) for almost every satellite and month. 3-yr average deviations are even reduced to <0.01% and <0.01 K (CHAMP: −0.05 K), respectively, establishing an amazing consistency of RO climatologies from different satellites. If applying the same processing scheme for all data, refractivity and dry temperature records from individual satellites with similar bending angle noise can be safely combined up to 30 km altitude (refractivity also up to 35 km) to a consistent single climate record of substantial value for climate monitoring in the upper troposphere and lower stratosphere

Quantifying uncertainty in climatological fields from GPS radio occultation: an empirical-analytical error model

Due to the measurement principle of the radio occultation (RO) technique, RO data are highly suitable for climate studies. RO profiles can be used to build climatological fields of different atmospheric parameters like bending angle, refractivity, density, pressure, geopotential height, and temperature. RO climatologies are affected by random (statistical) errors, sampling errors, and systematic errors, yielding a total climatological error. Based on empirical error estimates, we provide a simple analytical error model for these error components, which accounts for vertical, latitudinal, and seasonal variations. The vertical structure of each error component is modeled constant around the tropopause region. Above this region the error increases exponentially, below the increase follows an inverse height power-law. The statistical error strongly depends on the number of measurements. It is found to be the smallest error component for monthly mean 10° zonal mean climatologies with more than 600 measurements per bin. Due to smallest atmospheric variability, the sampling error is found to be smallest at low latitudes equatorwards of 40°. Beyond 40°, this error increases roughly linearly, with a stronger increase in hemispheric winter than in hemispheric summer. The sampling error model accounts for this hemispheric asymmetry. However, we recommend to subtract the sampling error when using RO climatologies for climate research since the residual sampling error remaining after such subtraction is estimated to be only about 30% of the original one or less. The systematic error accounts for potential residual biases in the measurements as well as in the retrieval process and generally dominates the total climatological error. Overall the total error in monthly means is estimated to be smaller than 0.07% in refractivity and 0.15 K in temperature at low to mid latitudes, increasing towards higher latitudes. This study focuses on dry atmospheric parameters as retrieved from RO measurements so for context we also quantitatively explain the difference between dry and physical atmospheric parameters, which can be significant at altitudes below about 6 km (high latitudes) to 10 km (low latitudes)

A tailored multi-model ensemble for air traffic management: Demonstration and evaluation for the Eyjafjallajökull eruption in May 2010

High quality volcanic ash forecasts are crucial to minimize the economic impact of volcanic hazards on air traffic. Decision-making is usually based on numerical dispersion modeling with only one model realization. Given the inherent uncertainty of such approach, a multi-model multi-source term ensemble has been designed and evaluated for the Eyjafjallaj&ouml;kull eruption in May 2010. Its use for air traffic management is discussed. Two multi-model ensembles were built: the first is based on the output of four dispersion models and their own implementation of ash ejection. All a priori model source terms were constrained by observational evidence of the volcanic ash cloud top as a function of time. The second ensemble is based on the same four dispersion models, which were run with three additional source terms: (i) a source term obtained with background modeling constrained with satellite data (a posteriori source term), (ii) its lower bound estimate, and (iii) its upper bound estimate. The a priori ensemble gives valuable information about the probability of ash dispersion during the early phase of the eruption, when observational evidence is limited. However, its evaluation with observational data reveals lower quality compared to the second ensemble. While the second ensemble ash column load and ash horizontal location compare well to satellite observations, 3D ash concentrations are negatively biased. This might be caused by the vertical distribution of ash, which is too much diluted in all model runs, probably due to defaults in the a posteriori source term and vertical transport and/or diffusion processes in all models. Relevant products for the air traffic management are horizontal maps of ash concentration quantiles (median, 75 %, 99 %) at a fine-resolved flight level grid. These maps can be used for route optimization in the areas where ash does not pose a direct and urgent threat to aviation. Cost-optimized consideration of such hazards will result in much less impact on flight cancellations, reroutings, and traffic flow congestions.</p

Quantification of structural uncertainty in climate data records from GPS radio occultation

Global Positioning System (GPS) radio occultation (RO) has provided continuous observations of the Earth's atmosphere since 2001 with global coverage, all-weather capability, and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS). Precise time measurements enable long-term stability but careful processing is needed. Here we provide climate-oriented atmospheric scientists with multicenter-based results on the long-term stability of RO climatological fields for trend studies. We quantify the structural uncertainty of atmospheric trends estimated from the RO record, which arises from current processing schemes of six international RO processing centers, DMI Copenhagen, EUM Darmstadt, GFZ Potsdam, JPL Pasadena, UCAR Boulder, and WEGC Graz. Monthly-mean zonal-mean fields of bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature from the CHAMP mission are compared for September 2001 to September 2008. We find that structural uncertainty is lowest in the tropics and mid-latitudes (50° S to 50° N) from 8 km to 25 km for all inspected RO variables. In this region, the structural uncertainty in trends over 7 yr is &lt;0.03% for bending angle, refractivity, and pressure, &lt;3 m for geopotential height of pressure levels, and &lt;0.06 K for temperature; low enough for detecting a climate change signal within about a decade. Larger structural uncertainty above about 25 km and at high latitudes is attributable to differences in the processing schemes, which undergo continuous improvements. Though current use of RO for reliable climate trend assessment is bound to 50° S to 50° N, our results show that quality, consistency, and reproducibility are favorable in the UTLS for the establishment of a climate benchmark record

Observed temperature changes in the troposphere and stratosphere from 1979 to 2018

Temperature observations of the upper-air atmosphere are now available for more than 40 years from both ground- and satellite-based observing systems. Recent years have seen substantial improvements in reducing long-standing discrepancies among datasets through major reprocessing efforts. The advent of radio occultation (RO) observations in 2001 has led to further improvements in vertically resolved temperature measurements, enabling a detailed analysis of upper-troposphere/lower-stratosphere trends. This paper presents the current state of atmospheric temperature trends from the latest available observational records. We analyze observations from merged operational satellite measurements, radiosondes, lidars, and RO, spanning a vertical range from the lower troposphere to the upper stratosphere. The focus is on assessing climate trends and on identifying the degree of consistency among the observational systems. The results show a robust cooling of the stratosphere of about 1–3 K, and a robust warming of the troposphere of about 0.6–0.8 K over the last four decades (1979– 2018). Consistent results are found between the satellite-based layer-average temperatures and vertically resolved radiosonde records. The overall latitude–altitude trend patterns are consistent between RO and radiosonde records. Significant warming of the troposphere is evident in the RO measurements available after 2001, with trends of 0.25–0.35 K per decade. Amplified warming in the tropical upper-troposphere compared to surface trends for 2002–18 is found based on RO and radiosonde records, in approximate agreement with moist adiabatic lapse rate theory. The consistency of trend results from the latest upper-air datasets will help to improve understanding of climate changes and their drivers

Characteristics of tropopause parameters as observed with GPS radio occultation

Characteristics of the lapse rate tropopause are analyzed globally for tropopause altitude and temperature using global positioning system (GPS) radio occultation (RO) data from late 2001 to the end of 2013. RO profiles feature high vertical resolution and excellent quality in the upper troposphere and lower stratosphere, which are key factors for tropopause determination, including multiple ones. RO data provide measurements globally and allow examination of both temporal and spatial tropopause characteristics based entirely on observational measurements. To investigate latitudinal and longitudinal tropopause characteristics, the mean annual cycle, and inter-annual variability, we use tropopauses from individual profiles as well as their statistical measures for zonal bands and 5° × 10° bins. The latitudinal structure of first tropopauses shows the well-known distribution with high (cold) tropical tropopauses and low (warm) extra-tropical tropopauses. In the transition zones (20 to 40° N/S), individual profiles reveal varying tropopause altitudes from less than 7 km to more than 17 km due to variability in the subtropical tropopause break. In this region, we also find multiple tropopauses throughout the year. Longitudinal variability is strongest at northern hemispheric mid latitudes and in the Asian monsoon region. The mean annual cycle features changes in amplitude and phase, depending on latitude. This is caused by different underlying physical processes (such as the Brewer–Dobson circulation – BDC) and atmospheric dynamics (such as the strong polar vortex in the southern hemispheric winter). Inter-annual anomalies of tropopause parameters show signatures of El Niño–Southern Oscillation (ENSO), the quasi–biennial oscillation (QBO), and the varying strength of\ud the polar vortex, including sudden stratospheric warming (SSW) events. These results are in good agreement with previous studies and underpin the high utility of the entire RO record for investigating latitudinal, longitudinal, and temporal tropopause characteristics globally

Systematic residual ionospheric errors in radio occultation data and a potential way to minimize them

Radio occultation (RO) sensing is used to probe the earth's atmosphere in order to obtain information about its physical properties. With a main interest in the parameters of the neutral atmosphere, there is the need to perform a correction of the ionospheric contribution to the bending angle. Since this correction is an approximation to first order, there exists an ionospheric residual, which can be expected to be larger when the ionization is high (day versus night, high versus low solar activity). The ionospheric residual systematically affects the accuracy of the atmospheric parameters at low altitudes, at high altitudes (above 25–30 km) it even is an important error source. In climate applications this could lead to a time dependent bias which induces wrong trends in atmospheric parameters at high altitudes. The first goal of our work was to study and characterize this systematic residual error. In a second step we developed a simple correction method, based purely on observational data, to reduce this residual for large ensembles of RO profiles. In order to tackle this problem, we analyzed the bending angle bias of CHAMP and COSMIC RO data from 2001–2011. We could observe that the nighttime bending angle bias stays constant over the whole period of 11 yr, while the daytime bias increases from low to high solar activity. As a result, the difference between nighttime and daytime bias increases from about &minus;0.05 &mu;rad to &minus;0.4 &mu;rad. This behavior paves the way to correct the solar cycle dependent bias of daytime RO profiles. In order to test the newly developed correction method we performed a simulation study, which allowed to separate the influence of the ionosphere and the neutral atmosphere. Also in the simulated data we observed a similar increase in the bias in times from low to high solar activity. In this simulation we performed the climatological ionospheric correction of the bending angle data, by using the bending angle bias characteristics of a solar cycle as a correction factor. After the climatological ionospheric correction the bias of the simulated data improved significantly, not only in the bending angle but also in the retrieved temperature profiles

Generation of a bending angle radio occultation climatology (BAROCLIM) and its use in radio occultation retrievals

In this paper, we introduce a bending angle radio occultation climatology (BAROCLIM) based on Formosat-3/COSMIC (F3C) data. This climatology represents the monthly-mean atmospheric state from 2006 to 2012. Bending angles from radio occultation (RO) measurements are obtained from the accumulation of the change in the raypath direction of Global Positioning System (GPS) signals. Best quality of these near-vertical profiles is found from the middle troposphere up to the mesosphere. Beside RO bending angles we also use data from the Mass Spectrometer and Incoherent Scatter Radar (MSIS) model (modified for RO purposes) to expand BAROCLIM in a spectral model, which (theoretically) reaches from the surface up to infinity. Due to the very high quality of BAROCLIM up to the mesosphere, it can be used to detect deficiencies in current state-of-the-art analysis and reanalysis products from numerical weather prediction (NWP) centers. For bending angles derived from European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields from 2006 to 2012, e.g., we find a positive bias of 0.5 to 1% at 40 km, which increases to more than 2% at 50 km. BAROCLIM can also be used as a priori information in RO profile retrievals. In contrast to other a priori information (i.e., MSIS) we find that the use of BAROCLIM better preserves the mean of raw RO measurements. Global statistics of statistically optimized bending angle and refractivity profiles also confirm that BAROCLIM outperforms MSIS. These results clearly demonstrate the utility of BAROCLIM

Exploring atmospheric blocking with GPS radio occultation observations

Atmospheric blocking has been closely investigated in recent years due to its impact on weather and climate, such as heat waves, droughts, and flooding. We use, for the first time, satellite-based observations from Global Positioning System (GPS) radio occultation (RO) and explore their ability to resolve blocking in order to potentially open up new avenues complementing models and reanalyses. RO delivers globally available and vertically highly resolved profiles of atmospheric variables such as temperature and geopotential height (GPH). Applying a standard blocking detection algorithm, we find that RO data robustly capture blocking as demonstrated for two well-known blocking events over Russia in summer 2010 and over Greenland in late winter 2013. During blocking episodes, vertically resolved GPH gradients show a distinct anomalous behavior compared to climatological conditions up to 300 hPa and sometimes even further up into the tropopause. The accompanying increase in GPH of up to 300 m in the upper troposphere yields a pronounced tropopause height increase. Corresponding temperatures rise up to 10 K in the middle and lower troposphere. These results demonstrate the feasibility and potential of RO to detect and resolve blocking and in particular to explore the vertical structure of the atmosphere during blocking episodes. This new observation-based view is available globally at the same quality so that blocking in the Southern Hemisphere can also be studied with the same reliability as in the Northern Hemisphere