The GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) data processing for the Vaisala RS92 radiosonde was developed to meet the criteria for reference measurements. These criteria stipulate the collection of metadata, the use of well-documented correction algorithms, and estimates of the measurement uncertainty. An important and novel aspect of the GRUAN processing is that the uncertainty estimates are vertically resolved. This paper describes the algorithms that are applied in version 2 of the GRUAN processing to correct for systematic errors in radiosonde measurements of pressure, temperature, humidity, and wind, as well as how the uncertainties related to these error sources are derived. Currently, the RS92 is launched on a regular basis at 13 out of 15 GRUAN sites. An additional GRUAN requirement for performing reference measurements with the RS92 is that the manufacturer-prescribed procedure for the radiosonde's preparation, i.e. heated reconditioning of the sensors and recalibration during ground check, is followed. In the GRUAN processing however, the recalibration of the humidity sensors that is applied during ground check is removed. For the dominant error source, solar radiation, laboratory experiments were performed to investigate and model its effect on the RS92's temperature and humidity measurements. GRUAN uncertainty estimates are 0.15 K for night-time temperature measurements and approximately 0.6 K at 25 km during daytime. The other uncertainty estimates are up to 6% relative humidity for humidity, 10–50 m for geopotential height, 0.6 hPa for pressure, 0.4–1 m s−1 for wind speed, and 1° for wind direction. Daytime temperature profiles for GRUAN and Vaisala processing are comparable and consistent within the estimated uncertainty. GRUAN daytime humidity profiles are up to 15% moister than Vaisala processed profiles, of which two-thirds is due to the radiation dry bias correction and one-third is due to an additional calibration correction. Redundant measurements with frost point hygrometers (CFH and NOAA FPH) show that GRUAN-processed RS92 humidity profiles and frost point data agree within 15% in the troposphere. No systematic biases occur, apart from a 5% dry bias for GRUAN data around −40 °C at night.

We compare a full-year (2006) record of surface air NO₂ concentrations measured in Israeli cities to coinciding retrievals of tropospheric NO₂ columns from satellite sensors (SCIAMACHY aboard ENVISAT and OMI aboard Aura). This provides a large statistical data set for validation of NO₂ satellite measurements in urban air, where validation is difficult yet crucial for using these measurements to infer NO_x emissions by inverse modeling. Assuming that NO₂ is well-mixed throughout the boundary layer (BL), and using observed average seasonal boundary layer heights, near-surface NO₂ concentrations are converted into BL NO₂ columns. The agreement between OMI and (13:45) BL NO₂ columns (slope=0.93, n=542), and the comparable results at 10:00 h for SCIAMACHY, allow a validation of the seasonal, weekly, and diurnal cycles in satellite-derived NO₂. OMI and BL NO₂ columns show consistent seasonal cycles (winter NO₂ 1.6–2.7× higher than summer). BL and coinciding OMI columns both show a strong weekly cycle with 45–50% smaller NO₂ columns on Saturday relative to the weekday mean, reflecting the reduced weekend activity, and validating the weekly cycle observed from space. The diurnal difference between SCIAMACHY (10:00) and OMI (13:45) NO₂ is maximum in summer when SCIAMACHY is up to 40% higher than OMI, and minimum in winter when OMI slightly exceeds SCIAMACHY. A similar seasonal variation in the diurnal difference is found in the source region of Cairo. The surface measurements in Israel cities confirm this seasonal variation in the diurnal cycle. Using simulations from a global 3-D chemical transport model (GEOS-Chem), we show that this seasonal cycle can be explained by a much stronger photochemical loss of NO₂ in summer than in winter.

We examine the seasonal variation in lower tropospheric nitrogen oxides (NO_x = NO + NO₂) at northern midlatitudes by evaluating tropospheric NO₂ columns observed from the Ozone Monitoring Instrument (OMI) satellite instrument with surface NO₂ measurements (SouthEastern Aerosol Research and Characterization and Air Quality System) and current bottom‐up NO_x emission inventories, using a global model of tropospheric chemistry (GEOS‐Chem). The standard (SP) and DOMINO (DP) tropospheric NO₂ column products from OMI exhibit broadly similar spatial and seasonal variation, but differ substantially over continental source regions. A comparison of the two OMI tropospheric NO₂ products with in situ surface NO₂ concentrations and bottom‐up NO_x emissions over the southeast United States indicates that annual mean NO₂ columns from the DP are biased high by 21%–33% and those from the SP are biased high by 27%–43%. The bias in SP columns is highly seasonal, 67%–74% in summer compared with −6% to −1% in winter. Similar seasonal differences exist between top‐down and bottom‐up NO_x emission inventories over North America, Europe, and East Asia. The air mass factor largely explains the observed seasonal difference between the DP and SP, and in turn the seasonal SP bias. We develop a third product (DP_GC) using averaging kernel information from the DP and NO₂ vertical profiles from GEOS‐Chem. This product reduces to 5%–21% the annual mean bias over the southeast United States. We use the seasonal variation in the DP_GC to estimate the seasonal variation in the lifetime of lower tropospheric NO_x against oxidation to HNO₃ over the eastern United States. The effective NO_x lifetime at OMI overpass time (early afternoon) ranges from 7.6 h in summer to 17.8 h in winter, consistent within 3 h of the simulated lifetime. GEOS‐Chem calculations reveal that the seasonal variation in OMI NO₂ columns largely reflects gas‐phase oxidation of NO₂ in summer with an increasing role for heterogenous chemistry in winter.

The Asian summer monsoon anticyclone (ASMA) is a major meteorological system of the upper troposphere–lower stratosphere (UTLS) during boreal summer. It is known to contain enhanced tropospheric trace gases and aerosols, due to rapid lifting from the boundary layer by deep convection and subsequent horizontal confinement. Given its dynamical structure, the ASMA represents an efficient pathway for the transport of pollutants to the global stratosphere. A detailed understanding of the thermal structure and processes in the ASMA requires accurate in situ measurements. Within the StratoClim project we performed state-of-the-art balloon-borne measurements of temperature, water vapor, ozone and aerosol backscatter from two stations on the southern slopes of the Himalayas. In total, 63 balloon soundings were conducted during two extensive monsoon-season campaigns, in August 2016 in Nainital, India (29.4∘ N, 79.5∘ E), and in July–August 2017 in Dhulikhel, Nepal (27.6∘ N, 85.5∘ E); one shorter post-monsoon campaign was also carried out in November 2016 in Nainital. These measurements provide unprecedented insights into the UTLS thermal structure, the vertical distributions of water vapor, ozone and aerosols, cirrus cloud properties and interannual variability in the ASMA. Here we provide an overview of all of the data collected during the three campaign periods, with focus on the UTLS region and the monsoon season. We analyze the vertical structure of the ASMA in terms of significant levels and layers, identified from the temperature and potential temperature lapse rates and Lagrangian backward trajectories, which provides a framework for relating the measurements to local thermodynamic properties and the large-scale anticyclonic flow. Both the monsoon-season campaigns show evidence of deep convection and confinement extending up to 1.5–2 km above the cold-point tropopause (CPT), yielding a body of air with high water vapor and low ozone which is prone to being lifted further and mixed into the free stratosphere. Enhanced aerosol backscatter also reveals the signature of the Asian tropopause aerosol layer (ATAL) over the same region of altitudes. The Dhulikhel 2017 campaign was characterized by a 5 K colder CPT on average than in Nainital 2016 and a local water vapor maximum in the confined lower stratosphere, about 1 km above the CPT. Data assessment and modeling studies are currently ongoing with the aim of fully exploring this dataset and its implications with respect to stratospheric moistening via the ASMA system and related processes.

The Ozone Monitoring Instrument (OMI) was launched on July 15, 2004 on the National Aeronautics and Space Administration's Earth Observing System Aura satellite. The OMI instrument is an ultraviolet-visible imaging spectrograph that uses two-dimensional charge-coupled device detectors to register both the spectrum and the swath perpendicular to the flight direction with a 115/spl deg/ wide swath, which enables global daily ground coverage with high spatial resolution. This paper presents the OMI design and discusses the main performance and calibration features and results.