Development and application of an airborne differential absorption lidar for the simultaneous measurement of ozone and water vapor profiles in the tropopause region

A new, combined, lidar system has been developed that is able to simultaneously measure profiles of ozone and water vapor onboard aircraft. The concurrent measurement of these complementary trace species in the upper troposphere and lower stratosphere allows inferring exchange processes in the tropopause region. Whereas an advanced H2O differential absorption lidar at 935 nm has successfully been developed and extensively tested at DLR in the past, we describe here an amendment of this lidar by the addition of an ultraviolet (UV) channel to measure ozone. The transmitter of the ozone differential absorption lidar (DIAL) is based on a near-IR optical parametric oscillator that is frequency-converted into the UV spectral range by intracavity sum frequency mixing. Hereby, a continuous UV tuning range of ∼297–317  nm has been achieved. The average output power in this range is higher than 1 W corresponding to more than 10 mJ per pulse at a repetition rate of 100 Hz. The ozone DIAL system has been carefully characterized both on the ground and in flight. The first simultaneously measured two-dimensional cross-sections of ozone and water vapor in the upper troposphere and lower stratosphere have been recorded during the Wave-driven Isentropic Exchange (WISE) field campaign in 2017 demonstrating the high potential of this system for studying exchange processes in this region of the atmosphere

Influence of radiosonde observations on the sharpness and altitude of the midlatitude tropopause in the ECMWF IFS

Initial conditions of current numerical weather prediction models insufficiently represent the sharp vertical gradients across the midlatitude tropopause. Observation-space data assimilation output is used to study the influence of assimilated radiosondes on the tropopause. The radiosondes reduce systematic biases of the model background and sharpen temperature and wind gradients in the analysis. Tropopause sharpness is still underestimated in the analysis, which may impact weather forecasts

Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes

Numerical weather prediction (NWP) models are known to possess a distinct moist bias in the mid�latitude lower stratosphere, which is expected to affect the ability to accurately predict weather and climate. This paper investigates the vertical structure of the moist bias in the European Centre for Medium-Range Weather Forecasts (ECMWF) latest global reanalysis ERA5 using a unique multi-campaign data set of highly resolved water vapour profiles observed with a differential absorption lidar (DIAL) on board the High Altitude and LOng range research aircraft (HALO). In total, 41 flights in the mid-latitudes from six field campaigns provide roughly 33 000 profiles with humidity varying by 4 orders of magnitude. The observations cover different synoptic sit�uations and seasons and thus are suitable to characterize the strong vertical gradients of moisture in the upper troposphere and lower stratosphere (UTLS). The comparison to ERA5 indicates high positive and negative devi�ations in the UT, which on average lead to a slightly positive bias (15 %–20 %). In the LS, the moist bias rapidly increases up to a maximum of 55 % at 1.3 km altitude above the thermal tropopause (tTP) and decreases again to 15 %–20 % at 4 km altitude. Such a vertical structure is frequently observed, although the magnitude varies from flight to flight. The layer depth of increased moist bias is smaller at high tropopause altitudes and larger when the tropopause is low. Our results also suggest a seasonality of the moist bias, with the maximum in summer exceeding autumn by up to a factor of 3. During one field campaign, collocated ozone and water vapour profile observations enable a classification of tropospheric, stratospheric, and mixed air using water vapour–ozone correlations. It is revealed that the moist bias is high in the mixed air while being small in tropospheric and stratospheric air, which highlights that excessive transport of moisture into the LS plays a decisive role for the formation of the moist bias. Our results suggest that a better representation of mixing processes in NWP models could lead to a reduced LS moist bias that, in turn, may lead to more accurate weather and climate forecasts. The lower-stratospheric moist bias should be borne in mind for climatological studies using reanalysis data

Vertical structure of the lower stratospheric bias in ERA5 reanalyses and its relation to mixing processes

Current NWP analyses and reanalyses are known to possess a moist bias in the lower stratosphere of the mid-latitudes. An accurate representation of water vapor in the extratropical upper troposphere and lower stratosphere (UTLS), however, is crucial to correctly predict weather but also when climate models are verified against reanalysis products. This presentation uses a unique airborne multi-campaign water vapor profile data set to better characterize the vertical structure of this bias and to investigate its connection to mixing processes. Highly-resolved water vapor profiles have been recorded with the differential absorption lidar (DIAL) WALES onboard the research aircraft HALO on various field campaigns since 2013. The high-resolution humidity profiles along the flight path provide high data availability across the entire UTLS in cloud-free situations. We analyzed mid-latitude data from more than 40 flights over the Northern Atlantic and Europe that cover a broad spectrum of synoptic situations and different seasons. This comprehensive data set is used for a comparison with the European Centre for Medium-Range Weather Forecast’s (ECMWF) ERA5 reanalysis. First, we show an example specific humidity distribution along a cross-section in the surrounding of an extratropical cyclone. The comparison to ERA5 indicates the largest positive and negative deviations in the UT, but on average no systematic differences. In contrast, we find a coherent layer of strongly overestimated humidity above the thermal tropopause (TP) persisting along the whole flight path. Second, the vertical structure of deviations is verified for all flights. On average, deviations in the UT are relatively weak (+15%) and the minimum bias (+10%) is found at the thermal tropopause. Above the TP, within a layer of 1-1.5 km the bias rapidly increases up to a maximum of +52% while it decreases again to 15-20 % by 4 km. Although the shape of the vertical structure is similar for each flight, variations of the moist bias are observed for different seasons. For instance, the overestimation in summer is more than twice as high as for autumn observations. A possible explanation for this systematic moist bias is overestimation of mixing of water vapor into the LS. During one field campaign, WALES additionally observed ozone profiles which allow a classification of the observations into tropospheric, stratospheric and mixed air using H2O-O3 correlations in tracer-tracer space [2]. We demonstrate that the bias is particularly increased in air that was mixed in its history which indicates that mixing processes are not sufficiently well represented by ERA5. References [1]Bland, J., Gray, S., Methven, J. and Forbes, R.: Characterising the extratropical near-tropopause analysis humidity biases and their radiative effects on temperature forecasts, Q.J.R. Met. Soc., 147(741), 3878-3898, https://doi.org/10.1002/qj.4150, 2021. [2]Schäfler, A., Fix, A., and Wirth, M.: Mixing at the extratropical tropopause as characterized by collocated airborne H2O and O3 lidar observations, Atmos. Chem. Phys., 21, 5217–5234, https://doi.org/10.5194/acp-21-5217-2021, 2021

Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign

Since the start of the European Space Agency's Aeolus mission in 2018, various studies were dedicated to the evaluation of its wind data quality and particularly to the determination of the systematic and random errors in the Rayleigh-clear and Mie-cloudy wind results provided in the Aeolus Level-2B (L2B) product. The quality control (QC) schemes applied in the analyses mostly rely on the estimated error (EE), reported in the L2B data, using different and often subjectively chosen thresholds for rejecting data outliers, thus hampering the comparability of different validation studies. This work gives insight into the calculation of the EE for the two receiver channels and reveals its limitations as a measure of the actual wind error due to its spatial and temporal variability. It is demonstrated that a precise error assessment of the Aeolus winds necessitates a careful statistical analysis, including a rigorous screening for gross errors to be compliant with the error definitions formulated in the Aeolus mission requirements. To this end, the modified Z score and normal quantile plots are shown to be useful statistical tools for effectively eliminating gross errors and for evaluating the normality of the wind error distribution in dependence on the applied QC scheme, respectively. The influence of different QC approaches and thresholds on key statistical parameters is discussed in the context of the Joint Aeolus Tropical Atlantic Campaign (JATAC), which was conducted in Cabo Verde in September 2021. Aeolus winds are compared against model background data from the European Centre for Medium-Range Weather Forecasts (ECMWF) before the assimilation of Aeolus winds and against wind data measured with the 2 µm heterodyne detection Doppler wind lidar (DWL) aboard the Falcon aircraft. The two studies make evident that the error distribution of the Mie-cloudy winds is strongly skewed with a preponderance of positively biased wind results distorting the statistics if not filtered out properly. Effective outlier removal is accomplished by applying a two-step QC based on the EE and the modified Z score, thereby ensuring an error distribution with a high degree of normality while retaining a large portion of wind results from the original dataset. After the utilization of the described QC approach, the systematic errors in the L2B Rayleigh-clear and Mie-cloudy winds are determined to be below 0.3 m s−1 with respect to both the ECMWF model background and the 2 µm DWL. Differences in the random errors relative to the two reference datasets (Mie vs. model is 5.3 m s−1, Mie vs. DWL is 4.1 m s−1, Rayleigh vs. model is 7.8 m s−1, and Rayleigh vs. DWL is 8.2 m s−1) are elaborated in the text.</p

Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes

A comprehensive data set of airborne lidar water vapor profiles is compared with ERA5 reanalyses for a robust characterization of the vertical structure of the mid-latitude lower-stratospheric moist bias. We confirm a moist bias of up to 55 % at 1.3 km altitude above the tropopause and uncover a decreasing bias beyond. Collocated O3 and H2O observations reveal a particularly strong bias in the mixing layer providing indication for insufficiently modelled transport processes fostering the bias

Airborne temperature profiling in the troposphere during daytime by lidar utilizing Rayleigh–Brillouin scattering

The airborne measurement of a temperature profile from 10.5 km down towards ground (about 1.4 km above sea level) during daytime by means of a lidar utilizing Rayleigh-Brillouin (RB) scattering is demonstrated for the first time, to our knowledge. The spectra of the scattered light were measured by tuning the laser (Lambda=354.9 nm) over a 11 GHz frequency range with a step size of 250 MHz while using a Fabry Perot interferometer as a spectral filter. The measurement took 14 min and was conducted over a remote area in Iceland with the ALADIN Airborne Demonstrator on-board the DLR Falcon aircraft. The temperature profile was derived by applying an analytical RB line shape model to the backscatter spectra, which were measured at different altitudes with a vertical resolution of 630 m. A comparison with temperature profiles from radiosonde observations and model temperatures shows reasonable agreement with biases of less than +/-2K. Based on Poisson statistics, the random error of the derived temperatures is estimated to vary between 0.1 K and 0.4 K. The work provides insight into the possible realization of airborne lidar temperature profilers based on RB scattering

Lagrangian matches between observations from aircraft, lidar and radar in a warm conveyor belt crossing orography

Warm conveyor belts (WCBs) are important airstreams in extratropical cyclones, often leading to the formation of intense precipitation and the amplification of upper-level ridges. This study presents a case study that involves aircraft, lidar and radar observations in a WCB ascending from western Europe towards the Baltic Sea during the Hydrological Cycle in the Mediterranean Experiment (HyMeX) and T-NAWDEX-Falcon in October 2012, a preparatory campaign for the THORPEX North Atlantic Waveguide and Downstream Impact Experiment (T-NAWDEX). Trajectories were used to link different observations along the WCB, that is, to establish so-called Lagrangian matches between observations. To this aim, an ensemble of wind fields from the global analyses produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble of Data Assimilations (EDA) system were used, which allowed for a probabilistic quantification of the WCB occurrence and the Lagrangian matches. Despite severe air traffic limitations for performing research flights over Europe, the German Aerospace Center (DLR) Falcon successfully sampled WCB air masses during different phases of the WCB ascent. The WCB trajectories revealed measurements in two distinct WCB branches: one branch ascended from the eastern North Atlantic over southwestern France, while the other had its inflow in the western Mediterranean. Both branches passed across the Alps, and for both branches Lagrangian matches coincidentally occurred between lidar water vapour measurements in the inflow of the WCB south of the Alps, radar measurements during the ascent at the Alps and in situ aircraft measurements by Falcon in the WCB outflow north of the Alps. An airborne release experiment with an inert tracer could confirm the long pathway of the WCB from the inflow in the Mediterranean boundary layer to the outflow in the upper troposphere near the Baltic Sea several hours later. The comparison of observations and ensemble analyses reveals a moist bias in the analyses in parts of the WCB inflow but a good agreement of cloud water species in the WCB during ascent. In between these two observations, a precipitation radar measured strongly precipitating WCB air located directly above the melting layer while ascending at the southern slopes of the Alps. The trajectories illustrate the complexity of a continental and orographically influenced WCB, which leads to (i) WCB moisture sources from both the Atlantic and Mediterranean, (ii) different pathways of WCB ascent affected by orography, and (iii) locally steep WCB ascent with high radar reflectivity values that might result in enhanced precipitation where the WCB flows over the Alps. The linkage of observational data by ensemble-based WCB trajectory calculations, the confirmation of the WCB transport by an inert tracer and the model evaluation using the multi-platform observations are the central elements of this study and reveal important aspects of orographically modified WCBs.</p

Observation of jet stream winds during NAWDEX and characterization of systematic meteorological analysis errors

Observations across the North Atlantic jet stream with high vertical resolution are used to explore the structure of the jet stream, including the sharpness of vertical wind shear changes across the tropopause and the wind speed. Data was obtained during the North Atlantic Waveguide and Downstream impact EXperiment (NAWDEX) by an airborne Doppler wind lidar, dropsondes and a ground-based Stratosphere-Troposphere radar. During the campaign small wind speed biases throughout the troposphere and lower stratosphere of only -0.41 m s-1 and -0.15 m s-1 are found respectively in the ECMWF and UK Met Office analyses and short-term forecasts. However, this study finds large and spatially coherent wind errors up to ±10 m s-1 for individual cases, with the strongest errors occurring above the tropopause in upper-level ridges. ECMWF and Met Office analyses indicate similar spatial structures in wind errors, even though their forecast models and data assimilation schemes differ greatly. The assimilation of operational observational data brings the analyses closer to the independent verifying observations but it cannot fully compensate the forecast error. Models tend to underestimate the peak jet stream wind, the vertical wind shear (by a factor of 2-5) and the abruptness of the change in wind shear across the tropopause, which is a major contribution to the meridional potential vorticity gradient. The differences are large enough to influence forecasts of Rossby wave disturbances to the jet stream with an anticipated effect on weather forecast skill even on large scales