Seasonal and regional variations of long-term changes in upper-tropospheric jets from reanalyses

Long-term changes in upper-tropospheric jet latitude, altitude, and strength are assessed using five modern reanalyses: MERRA, MERRA-2, ERA-Interim, JRA-55, and NCEP CFSR. Changes are computed from jet locations evaluated daily at each longitude to analyze regional and seasonal variations. The changes in subtropical and polar (eddy driven) jets are evaluated separately. Good agreement among the reanalyses in many regions and seasons provides confidence in the robustness of the diagnosed trends. Jet shifts show strong regional and seasonal variations, resulting in changes that are not robust in zonal or annual means. Robust changes in the subtropical jet indicate tropical widening over Africa except during Northern Hemisphere (NH) spring, and tropical narrowing over the eastern Pacific in NH winter. The Southern Hemisphere (SH) polar jet shows a robust poleward shift, while the NH polar jet shifts equatorward in most regions/seasons. Both subtropical and polar jet altitudes typically increase; these changes are more robust in theNHthan in the SH. Subtropical jet wind speeds have generally increased in winter and decreased in summer, while polar jet wind speeds have weakened (strengthened) over Africa and eastern Asia (elsewhere) during winter in both hemispheres. The Asian monsoon has increased in area and appears to have shifted slightly westward toward Africa. Our results highlight the importance of understanding regional and seasonal variations when quantifying long-term changes in jet locations, the mechanisms for those changes, and their potential human impacts. Comparison of multiple reanalyses is a valuable tool for assessing the robustness of jet changes

Statistical characterization of arctic polar-night jet oscillation events

A novel diagnostic tool is presented, based on polar-cap temperature anomalies, for visualizing daily variability of the Arctic stratospheric polar vortex over multiple decades. This visualization illustrates the ubiquity of extended-time-scale recoveries from stratospheric sudden warmings, termed here polar-night jet oscillation (PJO) events. These are characterized by an anomalously warm polar lower stratosphere that persists for several months. Following the initial warming, a cold anomaly forms in the middle stratosphere, as does an anomalously high stratopause, both of which descend while the lower-stratospheric anomaly persists. These events are characterized in four datasets: Microwave Limb Sounder (MLS) temperature observations; the 40-yr ECMWF Re-Analysis (ERA-40) and Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalyses; and an ensemble of three 150-yr simulations from the Canadian Middle Atmosphere Model. The statistics of PJO events in the model are found to agree very closely with those of the observations and reanalyses. The time scale for the recovery of the polar vortex following sudden warmings correlates strongly with the depth to which the warming initially descends. PJO events occur following roughly half of all major sudden warmings and are associated with an extended period of suppressed wave-activity fluxes entering the polar vortex. They follow vortex splits more frequently than they do vortex displacements. They are also related to weak vortex events as identified by the northern annular mode; in particular, those weak vortex events followed by a PJO event show a stronger tropospheric response. The long time scales, predominantly radiative dynamics, and tropospheric influence of PJO events suggest that they represent an important source of conditional skill in seasonal forecasting

Cyclone-induced surface ozone and HDO depletion in the Arctic

Ground-based, satellite, and reanalysis datasets were used to identify two similar cyclone-induced surface ozone depletion events at Eureka, Canada (80.1° N, 86.4° W), in March 2007 and April 2011. These two events were coincident with observations of hydrogen deuterium oxide (HDO) depletion, indicating that condensation and sublimation occurred during the transport of the ozone-depleted air masses. Ice clouds (vapour and crystals) and aerosols were detected by lidar and radar when the ozone- and HDO-depleted air masses arrived over Eureka. For the 2007 event, an ice cloud layer was coincident with an aloft ozone depletion layer at 870 m altitude on 2–3 March, indicating this ice cloud layer contained bromine-enriched blowing-snow particles. Over the following 3 days, a shallow surface ozone depletion event (ODE) was observed at Eureka after the precipitation of bromine-enriched particles onto the local snowpack. A chemistry–climate model (UKCA) and a chemical transport model (pTOMCAT) were used to simulate the surface ozone depletion events. Incorporating the latest surface snow salinity data obtained for the Weddell Sea into the models resulted in improved agreement between the modelled and measured BrO concentrations above Eureka. MERRA-2 global reanalysis data and the FLEXPART particle dispersion model were used to study the link between the ozone and HDO depletion. In general, the modelled ozone and BrO showed good agreement with the ground-based observations; however, the modelled BrO and ozone in the near-surface layer are quite sensitive to the snow salinity. HDO depletion observed during these two blowing-snow ODEs was found to be weaker than pure Rayleigh fractionation. This work provides evidence of a blowing-snow sublimation process, which is a key step in producing bromine-enriched sea-salt aerosol

Retrieval of temperature profiles from CHAMP for climate monitoring: intercomparison with Envisat MIPAS and GOMOS and different atmospheric analyses

International audienceThis study describes and evaluates a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval scheme particularly aimed at delivering bias-free atmospheric parameters for climate monitoring and research. The focus of the retrieval is on the sensible use of a priori information for careful high-altitude initialisation in order to maximise the usable altitude range. The RO retrieval scheme has been meanwhile applied to more than five years of data (September 2001 to present) from the German CHAllenging Minisatellite Payload for geoscientific research (CHAMP) satellite. In this study it was validated against various correlative datasets including the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars (GOMOS) sensors on Envisat, five different atmospheric analyses, and the operational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam. In the global mean within 10 to 30 km altitude we find that the present validation observationally constrains the potential RO temperature bias to be <0.2 K. Latitudinally resolved analyses show biases to be observationally constrained to <0.2?0.5 K up to 35 km in most cases, and up to 30 km in any case, even if severely biased (about 10 K or more) a priori information is used in the high altitude initialisation of the retrieval. No evidence is found for the 10?35 km altitude range of residual RO bias sources other than those potentially propagated downward from initialisation, indicating that the widely quoted RO promise of "unbiasedness and long-term stability due to intrinsic self-calibration" can indeed be realised given care in the data processing to strictly limit structural uncertainty. The results thus reinforce that adequate high-altitude initialisation is crucial for accurate stratospheric RO retrievals. The common method of initialising, at some altitude in the upper stratosphere, the hydrostatic integral with an upper boundary temperature or pressure value derived from meteorological analyses is prone to introduce biases from the upper boundary down to below 25 km. Also above 30 to 35 km, GNSS RO delivers a considerable amount of observed information up to around 40 km, which is particularly interesting for numerical weather prediction (NWP) systems, where direct assimilation of non-initialised observed RO bending angles (free of a priori) is thus the method of choice. The results underline the value of RO for climate applications

Intercomparison between Aura MLS and ground-based millimeter-wave observations of stratospheric O3 and HNO3 from Thule (76.5° N, 68.7° W)

The Ground-Based Millimeter-wave Spectrometer (GBMS) measures rotational emission spectra of middle atmospheric trace gases, with a spectral window of 600 MHz tunable between approximately 230 and 280 GHz and a resolution of up to 65 kHz. It was designed and built at the State University of New York at Stony Brook in the early 90’s and since then has been regularly upgraded and operated at a variety of sites in both hemispheres, at polar and mid-latitudes. In view of a growing need for long-term data sets of stratospheric constituents, in January 2009 we resolved to establish a long-term GBMS observation site at the Arctic station of Thule Air Base (76.5°N, 68.8°W), Greenland, in order to track the long- and short-term interactions between the changing climate and the seasonal processes tied to the ozone depletion phenomenon. Since then three winter campaigns were carried out from Thule during the period January-March 2009, 2010 and 2011. Observations of O3, HNO3, CO and N2O were performed, mostly on a daily basis, except during periods characterized by poor weather conditions. In this study we compare GBMS stratospheric O3 and HNO3 measurements obtained during these three winter periods at Thule with colocated satellite observations from the Aura Microwave Limb Sounder (MLS) experiment. The Version 3.3 Aura MLS O3 and HNO3 data sets have a resolution of about 2.5 km and 3-4 km, respectively, in the stratosphere. The MLS precisions range from 0.1 to 0.6 ppmv for O3 and about 0.6-0.7 ppbv for HNO3 throughout the stratosphere. Based on preliminary comparisons with correlative data sets and on results obtained for v2.2, systematic uncertainties are estimated to lead to HNO3 measurements biases that vary between ±0.5 and ±2 ppbv and multiplicative errors of ±5 –15% throughout most of the stratosphere. Similarly, a systematic uncertainty of the order of 5-10% has been assessed for O3 data. As for the GBMS, the O3 pure rotational transition line at 276.923 GHz is observed with a ~1.5-hour integration, while the weaker HNO3 spectrum, represented by a cluster of superimposed emission lines centered at 269.1 GHz, needs about 4 hours of integration. Taking advantage of the dependence of the line broadening on atmospheric pressure, inversion techniques allow the retrieval of vertical profiles from approximately 15 to 50 km. In the past, GBMS O3 and HNO3 spectra were deconvolved using a Chahine-Twomey (C-T) and an iterative constrained Matrix Inversion (MI) technique, respectively. More recently, the GBMS retrieval algorithm has been updated to an Optimal Estimation Method (OEM) in order to conform to the standard of the NDACC microwave group, and to easily provide retrievals with a set of averaging kernels that grants more straightforward comparisons with other data sets. The nominal vertical resolution of the retrieved profiles (defined as the FWHM of averaging kernels) is ~8 km for O3 and ~ 12 km for HNO3, although the inversion technique locates the maximum of the mixing ratio profile of both species with a much better accuracy (i.e., ~ ±1 km). The 1σ uncertainty of O3 and HNO3 mixing ratio vertical profiles depends on altitude and is estimated at ~15% or 0.3 ppbv, whichever is larger. Each GBMS profile is compared to the closest MLS profile, with coincidence criteria of ±10° longitude, ±2.5° latitude and ±12 h. In order to avoid of severely compromising the comparison between GBMS and Aura MLS observations due to the much higher resolution of the satellite-derived data sets, we ‘convolved’ the MLS profiles using the GBMS averaging kernels before directly comparing the two data sets. For both species a fairly good agreement between MLS and GBMS profiles is observed, with the GBMS showing, however, a ~10-15% low bias at the mixing ratio peak

EOS MLS observations of dehydration in the 2004-2005 polar winters

We prove various estimates for the first eigenvalue of the magnetic Dirichlet Laplacian on a bounded domain in two dimensions. When the magnetic field is constant, we give lower and upper bounds in terms of geometric quantities of the domain. We furthermore prove a lower bound for the first magnetic Neumann eigenvalue in the case of constant field.Comment: 19 page

2002-2003 Arctic ozone loss deduced from POAM III satellite observations and the SLIMCAT chemical transport model

The SLIMCAT three-dimensional chemical transport model (CTM) is used to infer chemical ozone loss from Polar Ozone and Aerosol Measurement (POAM) III observations of stratospheric ozone during the Arctic winter of 2002-2003. Inferring chemical ozone loss from satellite data requires quantifying ozone variations due to dynamical processes. To accomplish this, the SLIMCAT model was run in a 'passive' mode from early December until the middle of March. In these runs, ozone is treated as an inert, dynamical tracer. Chemical ozone loss is inferred by subtracting the model passive ozone, evaluated at the time and location of the POAM observations, from the POAM measurements themselves. This 'CTM Passive Subtraction' technique relies on accurate initialization of the CTM and a realistic description of vertical/horizontal transport, both of which are explored in this work. The analysis suggests that chemical ozone loss during the 2002-2003 winter began in late December. This loss followed a prolonged period in which many polar stratospheric clouds were detected, and during which vortex air had been transported to sunlit latitudes. A series of stratospheric warming events starting in January hindered chemical ozone loss later in the winter of 2003. Nevertheless, by 15 March, the final date of the analysis, ozone loss maximized at 425K at a value of about 1.2ppmv, a moderate amount of loss compared to loss during the unusually cold winters in the late-1990s. SLIMCAT was also run with a detailed stratospheric chemistry scheme to obtain the model-predicted loss. The SLIMCAT model simulation also shows a maximum ozone loss of 1.2ppmv at 425K, and the morphology of the loss calculated by SLIMCAT was similar to that inferred from the POAM data. These results from the recently updated version of SLIMCAT therefore give a much better quantitative description of polar chemical ozone loss than older versions of the same model. Both the inferred and modeled loss calculations show the early destruction in late December and the region of maximum loss descending in altitude through the remainder of the winter and early spring

Reanalysis intercomparisons of stratospheric polar processing diagnostics

We compare herein polar processing diagnostics derived from the four most recent full-input reanalysis datasets: the National Centers for Environmental Prediction Climate Forecast System Reanalysis/Climate Forecast System, version 2 (CFSR/CFSv2), the European Centre for Medium-Range Weather Forecasts Interim (ERA-Interim) reanalysis, the Japanese Meteorological Agency's 55-year (JRA-55) reanalysis, and the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). We focus on diagnostics based on temperatures and potential vorticity (PV) in the lower-to-middle stratosphere that are related to formation of polar stratospheric clouds (PSCs), chlorine activation, and the strength, size, and longevity of the stratospheric polar vortex.Polar minimum temperatures (Tmin) and the area of regions having temperatures below PSC formation thresholds (APSC) show large persistent differences between the reanalyses, especially in the Southern Hemisphere (SH), for years prior to 1999. Average absolute differences of the reanalyses from the reanalysis ensemble mean (REM) in Tmin are as large as 3&thinsp;K at some levels in the SH (1.5&thinsp;K in the Northern Hemisphere – NH), and absolute differences of reanalysis APSC from the REM up to 1.5&thinsp;% of a hemisphere (0.75&thinsp;% of a hemisphere in the NH). After 1999, the reanalyses converge toward better agreement in both hemispheres, dramatically so in the SH: average Tmin differences from the REM are generally less than 1&thinsp;K in both hemispheres, and average APSC differences less than 0.3&thinsp;% of a hemisphere.The comparisons of diagnostics based on isentropic PV for assessing polar vortex characteristics, including maximum PV gradients (MPVGs) and the area of the vortex in sunlight (or sunlit vortex area, SVA), show more complex behavior: SH MPVGs showed convergence toward better agreement with the REM after 1999, while NH MPVGs differences remained largely constant over time; differences in SVA remained relatively constant in both hemispheres. While the average differences from the REM are generally small for these vortex diagnostics, understanding such differences among the reanalyses is complicated by the need to use different methods to obtain vertically resolved PV for the different reanalyses.We also evaluated other winter season summary diagnostics, including the winter mean volume of air below PSC thresholds, and vortex decay dates. For the volume of air below PSC thresholds, the reanalyses generally agree best in the SH, where relatively small interannual variability has led to many winter seasons with similar polar processing potential and duration, and thus low sensitivity to differences in meteorological conditions among the reanalyses. In contrast, the large interannual variability of NH winters has given rise to many seasons with marginal conditions that are more sensitive to reanalysis differences. For vortex decay dates, larger differences are seen in the SH than in the NH; in general, the differences in decay dates among the reanalyses follow from persistent differences in their vortex areas.Our results indicate that the transition from the reanalyses assimilating Tiros Operational Vertical Sounder (TOVS) data to advanced TOVS and other data around 1998–2000 resulted in a profound improvement in the agreement of the temperature diagnostics presented (especially in the SH) and to a lesser extent the agreement of the vortex diagnostics. We present several recommendations for using reanalyses in polar processing studies, particularly related to the sensitivity to changes in data inputs and assimilation. Because of these sensitivities, we urge great caution for studies aiming to assess trends derived from reanalysis temperatures. We also argue that one of the best ways to assess the sensitivity of scientific results on polar processing is to use multiple reanalysis datasets.</p