The ESA MIPAS/Envisat level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22

The observations acquired during the full mission of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument, aboard the European Space Agency Environmental Satellite (Envisat), have been analysed with version 8.22 of the Optimised Retrieval Model (ORM), originally developed as the scientific prototype of the ESA level-2 processor for MIPAS observations. The results of the analyses have been included into the MIPAS level-2 version 8 (level2-v8) database containing atmospheric fields of pressure, temperature, and volume mixing ratio (VMR) of MIPAS main targets H2O, O3, HNO3, CH4, N2O, and NO2, along with the minor gases CFC-11, ClONO2, N2O5, CFC-12, COF2, CCl4, CF4, HCFC-22, C2H2, CH3Cl, COCl2, C2H6, OCS, and HDO. The database covers all the measurements acquired by MIPAS in the nominal measurement mode of the full resolution (FR) part of the mission (from July 2002 to March 2004) and all the observation modes of the optimised resolution (OR) part (from January 2005 to April 2012). The number of species included in the MIPAS level2-v8 dataset makes it of particular importance for the studies of stratospheric chemistry. The database is considered by ESA the final release of the MIPAS level-2 products. The ORM algorithm is operated at the vertical grid coincident to the tangent altitudes of the observations or to a subset of them, spanning (in the nominal mode) the altitude range from 6 to 68 km in the FR phase and from 6 to 70 km in the OR period. In the latitude domain, FR profiles are spaced by about 4.7∘, while the OR profiles are spaced by about 3.7∘. For each retrieved species, the auxiliary data and the retrieval choices are described. Each product is characterised in terms of the retrieval error, spatial resolution, and “useful” vertical range in both phases of the MIPAS mission. These depend on the characteristics of the measurements (spectral and vertical resolution of the measurements), the retrieval choices (number of spectral points included in the analyses, number of altitudes included in the vertical retrieval grid), and the information content of the measurements for each trace species. For temperature, water vapour, ozone, and nitric acid, the number of degrees of freedom is significantly larger in the OR phase than in the FR one, mainly due to the finer vertical measurement grid. In the FR phase, some trace species are characterised by a smaller retrieval error with respect to the OR phase, mainly due to the larger number of spectral points used in the analyses, along with the reduced vertical resolution. The way of handling possible caveats (negative VMR, vertical grid representation) is discussed. The quality of the retrieved profiles is assessed through four criteria, two providing information on the successful convergence of the retrieval iterations, one on the capability of the retrieval to reproduce the measurements, and one on the presence of outliers. An easy way to identify and filter the problematic profiles with the information contained in the output files is provided. MIPAS level2-v8 data are available to the scientific community through the ESA portal (https://doi.org/10.5270/EN1-c8hgqx4).

A process-oriented evaluation of CAMS reanalysis ozone during tropopause folds over Europe for the period 2003–2018

Tropopause folds are the key process underlying stratosphere-to-troposphere transport (STT) of ozone, thus, affecting tropospheric ozone levels and variability. In the present study we perform a process-oriented evaluation of Copernicus Atmosphere Monitoring Service (CAMS) reanalysis (CAMSRA) O3 during folding events, over Europe and for the time period from 2003 to 2018. A 3-D labeling algorithm is applied to detect tropopause folds in CAMSRA, while ozonesonde data from WOUDC (World Ozone and Ultraviolet Radiation Data Centre) and aircraft measurements from IAGOS (In-service Aircraft for a Global Observing System) are used for CAMSRA O3 evaluation. The profiles of observed and CAMSRA O3 concentrations indicate that CAMSRA reproduces the observed O3 increases in the troposphere during the examined folding events. Nevertheless, at some of the examined sites, CAMSRA overestimates the observed O3 concentrations, mostly at the upper portion of the observed increases, with a median fractional gross error (FGE) among the examined sites > 0.2 above 400 hPa. The use of a control run without data assimilation, reveals that the aforementioned overestimation of CAMSRA O3 arises from the data assimilation implementation. Overall, although data assimilation assists CAMSRA O3 to follow the observed O3 enhancements in the troposphere during the STT events, it introduces biases in the upper troposphere resulting in no clear quantitative improvement compared to the control run without data assimilation. Less biased assimilated O3 products, with finer vertical resolution in the troposphere, in addition to higher IFS (Integrated Forecasting System) vertical resolution, are expected to provide a better representation of O3 variability during tropopause folds.

Combined UV and IR ozone profile retrieval from TROPOMI and CrIS measurements

Vertical ozone profiles from combined spectral measurements in the ultraviolet and infrared spectral range were retrieved by using data from TROPOMI/S5P and CrIS/Suomi-NPP, which are flying in loose formation three minutes apart in the same orbit. A previous study of ozone profiles retrieved exclusively from TROPOMI UV spectra showed that the vertical resolution in the troposphere is clearly limited (Mettig et al, 2021). The vertical resolution and the vertical extent of the ozone profiles is improved by combining both wavelength ranges compared to retrievals limited to UV or IR spectral data only. The combined retrieval particularly improves the accuracy of the retrieved tropospheric ozone and to a lesser degree stratospheric ozone up to 30 km. An increase in the degree-of-freedom by one was found in the UV+IR retrieval compared to the UV-only retrieval. Compared to previous publications, which investigated combinations of UV and IR observations from the pairs OMI/TES and GOME-2/IASI, the degree of freedom is lower, which is attributed to the reduced spectral resolution of CrIS compared to TES or IASI. Tropospheric lidar and ozonesondes were used to validate the ozone profiles and tropospheric ozone column (TOC). From the comparison with tropospheric lidars both ozone profiles and TOCs show smaller biases for the retrieved data from the combined UV+IR observation than the UV observations alone. While the TOCs show good agreement, the profiles have a positive bias of more than 20 % between 10 and 15 km. The reason is probably a positive stratospheric bias from the IR retrieval. The comparison of the UV+IR and UV ozone profiles up to 30 km with MLS (Microwave Limb Sounder) demonstrates the improvement of the UV+IR profile in the stratosphere.

Embedding a One-column Ocean Model (SIT 1.06) in the Community Atmosphere Model 5.3 (CAM5.3; CAM5–SIT v1.0) to Improve Madden–Julian Oscillation Simulation in Boreal Winter

The effect of the air–sea interaction on the Madden–Julian Oscillation (MJO) was investigated using the one-column ocean model Snow–Ice–Thermocline (SIT 1.06) embedded in the Community Atmosphere Model 5.3 (CAM5.3; hereafter CAM5–SIT v1.0). The SIT model with 41 vertical layers was developed to simulate sea surface temperature (SST) and upper-ocean temperature variations with a high vertical resolution that resolves the cool skin and diurnal warm layer and the upper oceanic mixed layer. A series of 30-year sensitivity experiments were conducted in which various model configurations (e.g., coupled versus uncoupled, vertical resolution and depth of the SIT model, coupling domains, and absence of the diurnal cycle) were considered to evaluate the effect of air–sea coupling on MJO simulation. Most of the CAM5–SIT experiments exhibited higher fidelity than the CAM5-alone experiment in characterizing the basic features of the MJO such as spatiotemporal variability and the eastward propagation in boreal winter. The overall MJO simulation performance of CAM5–SIT benefited from (1) better resolving the fine structure of upper-ocean temperature and therefore the air–sea interaction that resulted in more realistic intraseasonal variability in both SST and atmospheric circulation and (2) the adequate thickness and vertical resolution of the oceanic mixed layer. The sensitivity experiments demonstrated the necessity of coupling the tropical eastern Pacific in addition to the tropical Indian Ocean and the tropical western Pacific. Enhanced MJO could be obtained without considering the diurnal cycle in coupling.

Methodology to obtain highly resolved SO₂ vertical profiles for representation of volcanic emissions in climate models

In this study we describe a methodology to create high-vertical-resolution SO2 profiles from volcanic emissions. We demonstrate the method's performance for the volcanic clouds following the eruption of Sarychev in June 2009. The resulting profiles are based on a combination of satellite SO2 and aerosol retrievals together with trajectory modelling. We use satellite-based measurements, namely lidar backscattering profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instrument, to create vertical profiles for SO2 swaths from the Atmospheric Infrared Sounder (AIRS) aboard the Aqua satellite. Vertical profiles are created by transporting the air containing volcanic aerosol seen in CALIOP observations using the FLEXible PARTicle dispersion model (FLEXPART) while preserving the high vertical resolution using the potential temperatures from the MERRA-2 (Modern-Era Retrospective analysis for Research and Application) meteorological data for the original CALIOP swaths. For the Sarychev eruption, air tracers from 75 CALIOP swaths within 9 d after the eruption are transported forwards and backwards and then combined at a point in time when AIRS swaths cover the complete volcanic SO2 cloud. Our method creates vertical distributions for column density observations of SO2 for individual AIRS swaths, using height information from multiple CALIOP swaths. The resulting dataset gives insight into the height distribution in the different sub-clouds of SO2 within the stratosphere. We have compiled a gridded high-vertical-resolution SO2 inventory that can be used in Earth system models, with a vertical resolution of 1 K in potential temperature, 61 ± 56 m, or 1.8 ± 2.9 mbar.

Monsoonal precipitation over Peninsular Malaysia in the CMIP6 HighResMIP experiments: the role of model resolution

This study investigates the ability of 20 model simulations which contributed to the CMIP6 HighResMIP to simulate precipitation in different monsoon seasons and extreme precipitation events over Peninsular Malaysia. The model experiments utilize common forcing but are run with different horizontal and vertical resolutions. The impact of resolution on the models’ abilities to simulate precipitation and associated environmental fields is assessed by comparing multi-model ensembles at different resolutions with three observed precipitation datasets and four climate reanalyses. Model simulations with relatively high horizontal and vertical resolution exhibit better performance in simulating the annual cycle of precipitation and extreme precipitation over Peninsular Malaysia and the coastal regions. Improvements associated with the increase in horizontal and vertical resolutions are also found in the statistical relationship between precipitation and monsoon intensity in different seasons. However, the increase in vertical resolution can lead to a reduction of annual mean precipitation compared to that from the models with low vertical resolutions, associated with an overestimation of moisture divergence and underestimation of lower-tropospheric vertical ascent in the different monsoon seasons. This limits any improvement in the simulation of precipitation in the high vertical resolution experiments, particularly for the Southwest monsoon season.

Integrated Work Flow Delivers Precise Properties Input for Unconventional Simulation

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203374, “Is My Completions Engineer Provided With the Correct Petrophysical and Geomechanical Properties Inputs?” by Philippe Gaillot, Brian Crawford, and Yueming Liang, SPE, ExxonMobil, et al., prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. To simulate the performance of unconventional wells effectively, incorporating sufficient geological complexity is essential to allow for realistic variability in the petrophysical and mechanical properties controlling the productivity of the effective stimulated rock volume (ESRV). The complete paper presents an integrated work flow to model mechanical properties at sufficiently high resolution (centimeter scale) to accurately honor rock fabric and its height and complexity effects on hydraulic fracturing and, therefore, on production. Once upscaled, outputs of this work flow enable a more-realistic borehole view of reservoir quality, fluid-flow units, and geomechanical stratigraphy, all information key to optimal asset development. Introduction Simulating hydraulic fractures with pre-existing natural mechanical discontinuities remains an important challenge. In most cases, the trend is to include more details in the simulations and apply more computational power to solve the problem. While these complex numerical simulations allow simultaneous interaction between multiple phenomena, the validity of the predicted hydraulic fractures, and thus ESRV productivity, may be questionable if inputs to the hydraulic-fracturing and production models do not capture the effective fine-scale complexity of the formation properties, namely the minimum in-situ horizontal stress contrast between layers, the changing layer properties, and the mechanical and flow properties of the interfaces. The complete paper presents a seven-step work flow wherein core poroelastic anisotropies derived from quantitative mineralogy and well-established micro-mechanical theory are integrated into a high-vertical-resolution multiphysics petrophysical model able to capture the centimeter-scale level of heterogeneity observed from cores. The resulting high-vertical-resolution well frame-work enables a detailed well-scale calibration and recognition of facies and stacking patterns; an accurate and core-calibrated geochemical, petrophysical, and geomechanical characterization of individual beds; and an identification and characterization of the interfaces between beds.

Impact of Radio Occultation Data on the Prediction of Typhoon Haishen (2020) with WRFDA Hybrid Assimilation

FORMOSAT-7/COSMIC-2 (FS7/C2) satellite was successfully launched in June 2019. The satellite provides about 5000 radio occultation (RO) soundings daily over the tropical and partial subtropical regions. Such plentiful RO soundings with high accuracy and vertical resolution could be used to improve model initial analysis for typhoon prediction. In this study, assimilation experiments with and without the RO data were conducted with the WRFDA hybrid system for the prediction of Typhoon Haishen (2020). The experimental results show a remarkable improvement in typhoon track prediction with RO data assimilation, especially when using a nonlocal refractivity operator. Results in cycling DA and forecast are analyzed and verified for the RO data impact. Diagnostics of potential vorticity (PV) tendency budget helps explain the typhoon translation induced by different physical processes in the budget. The typhoon translation is essentially dominated by horizontal PV advection, but the track deviation can increase due to the vertical PV advection with opposite effects in the absence of RO data. Sensitivity experiments for different model initial times, physics schemes, and RO observation amounts show positive RO data impacts on typhoon prediction, mainly contributed from FS7. Complementary, an improved forecast of Typhoon Hagupit (2020) is also illustrated for the RO data impact.

Impact of measured and simulated tundra snowpack properties on heat transfer

Snowpack microstructure controls the transfer of heat to, and the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two different winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow MicroPenetrometer profiles allowed snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n = 1050) compared to traditional snowpit observations (3 cm vertical resolution; n = 115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE = 5.8 °C). Bias-correction of the simulated thermal conductivity (relative to field measurements) improved simulated soil temperatures (RMSE = 2.1 °C). Multiple linear regression shows the required correction factor is strongly related to snow depth (R2 = 0.77, RMSE = 0.066) particularly early in the winter. Furthermore, CLM simulations did not adequately represent the observed high proportions of depth hoar. Addressing uncertainty in simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures act as a control on subnivean soil respiration, and hence impact Arctic winter carbon fluxes and budgets.