Vertical Profiles Of Water Vapor Research Articles

Relationships Between HCl, H2O, Aerosols, and Temperature in the Martian Atmosphere: 2. Quantitative Correlations

AbstractThe detection of hydrogen chloride (HCl) in the atmosphere of Mars was among the primary objectives of the ExoMars Trace Gas Orbiter (TGO) mission. Its discovery using the Atmospheric Chemistry Suite mid‐infrared channel (ACS MIR) showed a distinct seasonality and possible link to dust activity. This paper is part 2 of a study investigating the link between HCl and aerosols by comparing gas measurements made with TGO to dust and water ice opacities measured with the Mars Climate Sounder (MCS). In part 1, we showed, and compared, the seasonal evolution of vertical profiles of HCl, water vapor, temperature, dust opacity, and water ice opacity over the dusty periods around perihelion (solar longitudes 180°–360°) across Mars years 34–36. In part 2, we investigated the quantitative correlations in the vertical distribution between each quantity, as well as ozone. We show that there is a strong positive correlation between HCl and water vapor, which is expected due to fast photochemical production rates for HCl when reacting with water vapor photolysis products. We also show a strong positive correlation between water vapor and temperature, but are unable to show any correlation between temperature and HCl. There are weak correlations between the opacities of dust and water ice, and dust and water vapor, but only very low correlations between dust and HCl. We close with a discussion of possible sources and sinks and that interactions between HCl and water ice are the most likely for both, given the inter‐comparison.

The investigation of retrieval method for aerosol and water vapor profiles based on MAX-DOAS technology

Simultaneously obtaining the vertical distribution and profile of aerosol and water vapor is crucial for in-depth understanding of the Earth's radiation balance, regional water cycle, and the causes of frequent haze weather in China. This study developed a system and inversion method based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) to simultaneously retrieve tropospheric aerosol and water vapor profiles. The absorption of dioxy (O4) was obtained by multi-elevation measurement using the developed ground-based MAX-DOAS system. By minimizing a cost function combining an atmospheric radiative transfer model, aerosol extinction profiles were first inverted, followed by water vapor profiles. Optimized parameter selection in the look-up table method reduced reliance on prior profile information, enhancing pollutant distribution retrieval accuracy. In the monitoring period in Huaibei region, aerosols were mainly below 1.5 km, while water vapor concentrations decreased with altitude. Comparisons of water vapor vertical column densities (VCDs) retrieved through the look-up table method with the European Centre for Medium-Range Weather Forecasts(ECMWF) ERA5 model and geometric approximation showed good agreement, with correlation coefficients of 0.93 and 0.98, respectively. To comprehend water vapor sources at various vertical layers, a 24-h backward trajectory clustering analysis was conducted using the HYSPLIT model based on observed wind fields. Findings revealed that at 500 m altitude, water vapor primarily emanated from the southeast, whereas at 1 km and 2 km altitudes, it predominantly originated from the southwest. The study advances simultaneous tropospheric aerosol and water vapor profile retrieval, providing reliable technical support for the investigation of regional pollution.

Characterization of Surface Spectral Emissivity Retrieved from EE9-FORUM Simulated Measurements

FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) has been approved to be the ninth Earth Explorer mission of the European Space Agency and is scheduled for launch in 2027. The core FORUM instrument is a Fourier transform spectrometer, which will, for the first time, measure the upwelling spectral radiance in the far-infrared (FIR) and mid-infrared (MIR) portions of the Earth’s spectrum. These radiances will be processed up to level 2, to determine mainly the vertical profile of water vapor, surface spectral emissivity, and cloud parameters. In this paper, we assess the performance of the FORUM surface spectral emissivity product based on all-sky sensitivity study. In the FIR, we find that the retrieval error is mainly driven by the precipitable water vapor (PWV) in clear-sky conditions. In dry atmospheres, FIR emissivity can be retrieved with an error less than 0.01. In cloudy conditions, small errors can be achieved for optically thin clouds, especially for small values of the PWV. In the MIR, we observe that a large thermal contrast between the surface and the lowest atmospheric layers increases the sensitivity of the measurements to the surface emissivity in clear-sky conditions and an emissivity retrieval error less than 0.01 can usually be achieved. In cloudy conditions, small errors can be achieved for optically thin clouds, especially for large values of the surface temperature. Applying a coarser retrieval grid further reduces retrieval error, at the expense of an increased emissivity smoothing error.

A Microwave Radiometer Residual Inversion Neural Network Based on a Deadband Conditioning Model

Microwave radiometers are passive remote sensing devices that are widely used in marine atmospheric observations. The accuracy of its inversion of temperature and humidity profiles is an important indicator of its performance. Back Propagation (BP) neural networks are widely used in the study of microwave radiometer inversion problems. However, the BP network which is carried by the radiometer inversion suffers from profile data collapse. To address this, this study introduced a residual network to improve the accuracy of water vapor vertical profiles. Aiming at the problem of large inversion temperature error due to the effect of turbulence on the light-travel phase induced by stationary fronts along the seashore in the subtropical monsoon climate region, we used historical data to establish the seasonal a priori mean profile and design a dead-zone residual adjustment model. The accuracy of the residual network and the deadband-adjusted residual network was verified using the meteorological records of the Taizhou region from 2013–2018, with the experimental data and BP hierarchical network as the comparison term. We found no data collapse in the temperature and humidity profile inversion results of the residual network. Relative to the initial BP hierarchical algorithm, where the error of water vapor in the range 6–10 km was reduced by 80%, the dead zone residual adjustment model in the inverse-temperature phenomenon reduced the sum of squares error by 21%, compared with the ordinary residual network inversion results. Our findings provide new insights into the accuracy improvement of radiometer remote sensing.

Evaluating Mixing Height Estimations in the Western United States Using Satellite Observations

Wildfire smoke can be transported far from its origin, adversely impacting human health. The height of the atmospheric mixing layer, the near-surface layer of the troposphere in which turbulent convection leads to vertical mixing, is called the mixing height. Mixing height is a critical input in the smoke dispersion and air quality models used by agencies that monitor wildfires and air pollution. These models, coupled with forecaster expertise, are also used to determine if it is safe to execute a prescribed burn. In this paper, we derive mixing heights from two satellite datasets in order to assess mixing height forecasts produced by the National Weather Service (NWS) Fire Weather Program. Namely, we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) Vertical Feature Masks (VFM) and vertical water vapor profiles from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our comparison indicates that NWS forecasts tend to underestimate CALIOP mixing heights with a median relative error of –13% and a mean relative error of –3.34%. Although MODIS and NWS mixing heights showed some agreement below 3 km, the lower vertical resolution of the MODIS estimates hindered a full comparison. We examine the discrepancies among mixing heights over wildfire smoke plumes determined by these methods and discuss biases and limitations. This work provides insight into potential bias patterns present in current mixing height forecasts and provides directions for future improvements in both NWS mixing height forecasts and satellite-based measurements of mixing height.

Synergistic retrieval and complete data fusion methods applied to simulated FORUM and IASI-NG measurements

Abstract. In the frame of Earth observation remote-sensing data analysis, synergistic retrieval (SR) and complete data fusion (CDF) are techniques used to exploit the complementarity of the information carried by different measurements sounding the same air mass and/or ground pixel. While more difficult to implement due to the required simultaneous access to measurements originating from different instruments, the SR method is sometimes preferred over the CDF method as the latter relies on a linear approximation of the retrieved states as functions of the true atmospheric and/or surface state. In this work, we study the performance of the SR and CDF techniques when applied to simulated measurements of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) and the Infrared Atmospheric Sounding Interferometer – New Generation (IASI-NG) missions that will be operational in a few years, from two polar-orbiting satellites. The study is based on synthetic measurements generated for the two missions in clear-sky atmospheres. The target parameters of the inversion are the vertical profiles of temperature, water vapor and ozone mixing ratios, surface temperature, and spectral emissivity. We find that for exact matching of the measurements, the results of the SR and CDF techniques differ by less than 1/10 of their errors estimated through the propagation of measurement noise. For measurements with a realistic mismatch in space and time, the two methods provide more different results. Still in this case, however, the differences between the results are within the error bars due to measurement noise. We conclude that, when applied to FORUM and IASI-NG missions, the two methods are equivalent from an accuracy point of view.

Seasonal Changes in the Vertical Structure of Ozone in the Martian Lower Atmosphere and Its Relationship to Water Vapor

AbstractThe mid‐infrared channel of the Atmospheric Chemistry Suite (ACS MIR) onboard the ExoMars Trace Gas Orbiter is capable of observing the infrared absorption of ozone (O3) in the atmosphere of Mars. During solar occulations, the 003←000 band (3,000‐3,060 cm−1) is observed with spectral sampling of ∼0.045 cm−1. Around the equinoxes in both hemispheres and over the southern winters, we regularly observe around 200–500 ppbv of O3 below 30 km. The warm southern summers, near perihelion, produce enough atmospheric moisture that O3 is not detectable at all, and observations are rare even at high northern latitudes. During the northern summers, water vapor is restricted to below 10 km, and an O3 layer (100–300 ppbv) is visible between 20 and 30 km. At this same time, the aphelion cloud belt forms, condensing water vapor and allowing O3 to build up between 30 and 40 km. A comparison to vertical profiles of water vapor and temperature in each season reveals that water vapor abundance is controlled by atmospheric temperature, and H2O and O3 are anti‐correlated as expected. When the atmosphere cools, over time or over altitude, water vapor condenses (observed as a reduction in its mixing ratio) and the production of odd hydrogen species is reduced, which allows O3 to build up. Conversely, warmer temperatures lead to water vapor enhancements and ozone loss. The LMD Mars Global Climate Model is able to reproduce vertical structure and seasonal changes of temperature, H2O, and O3 that we observe. However, the observed O3 abundance is larger by factors between 2 and 6, indicating important differences in the rate of odd‐hydrogen photochemistry.

An OSSE Study of the Impact of Micropulse Differential Absorption Lidar (MPD) Water Vapor Profiles on Convective Weather Forecasting

Abstract The National Center for Atmospheric Research (NCAR) and Montana State University jointly developed water vapor micropulse differential absorption lidars (MPDs) that are a significant advance in eye-safe, unattended, lidar-based water vapor remote sensing. MPD is designed to provide continuous vertical water vapor profiles with high vertical (150 m) and temporal resolution (5 min) in the lower troposphere. This study aims to investigate MPD observation impacts and the scientific significance of MPDs for convective weather analyses and predictions using observation system simulation experiments (OSSEs). In this study, the Data Assimilation Research Testbed (DART) and the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model are used to conduct OSSEs for a case study of a mesoscale convective system (MCS) observed during the Plains Elevated Convection At Night (PECAN) experiment. A poor-performing control simulation that was drawn from a 40-member ensemble at 3-km resolution is markedly improved by assimilation of simulated observations drawn from a more skillful simulation that served as the nature run at 1-km resolution. In particular, assimilating surface observations corrected surface warm front structure errors, while MPD observations remedied errors in low- to midlevel moisture ahead of the MCS. Collectively, these analyses changes led to markedly improved short-term predictions of convection initiation, evolution, and precipitation of the MCS in the simulations on 15 July 2015. For this case study, the OSSE results indicate that a more dense MPD network results in better prediction performance for convective precipitation while degrading light precipitation prediction performance due to an imbalance of the analysis at large scales.

Vertical distribution of water vapour for Martian northern hemisphere summer in Mars Year 28 from Mars Climate Sounder

We present, for the first time, retrievals of the vertical distribution of water vapour from Mars Climate Sounder (MCS) aboard Mars Reconnaissance Orbiter (MRO), an original goal of the mission compromised by channel filter performance issues. To work around this problem a two-stage retrieval has been developed and was applied to MCS observations for MY28 NH summer (Ls=111–173°, 26 September 2006 to 27 January 2007). Retrievals were consistent with observations by other instruments for both column abundances (e.g., peak NH summer column abundance of 70 pr. μm compared with 50 pr. μm in the literature) and vertical profiles. Other key results are nightside vertical profiles of water vapour (retrieved for the first time) and interaction of atmospheric water vapour with the aphelion cloud belt. Seasonal changes in the hygropause (a proxy for condensation level) are reflected in changes in the cloud belt. During late northern summer, when the hygropause level is high at the equator and tropics, the cloudbase is higher (increasing by ≈10 km from 25 to 35 km) and the belt is weaker.

Design and Verification of a Double-Grating Spectrometer System (DGSS) for Simultaneous Observation of Aerosols, Water Vapor and Clouds

Simultaneous observation of aerosols, water vapor, and clouds is conducive to the analysis of their interactions, and the consistency of observation equipment, instrument performance, and observation time is crucial. Molecular oxygen A-band (758–778 nm) and water vapor absorption band (758–880 nm) are two bands with similar wavelengths, and the hyperspectral remote sensing information of these two bands can be exploited to invert the vertical profile of aerosol and water vapor. In this paper, a double-grating spectrometer system (DGSS) was developed. DGSS uses a telescope system and fiber to introduce multi-angle, double-band sunlight, and it splits light synchronously (non-sequentially) to different positions of the detector through a slit plate and two gratings. The DGSS was calibrated in the laboratory and observed in the external field. The results indicated that the spectral resolution reached 0.06 nm (molecular oxygen A-band, 758–778 nm) and 0.24 nm (water vapor absorption band, 758–880 nm). Meanwhile, the spectra of the two bands (three angles in each band) are not aliased on the detector. Besides, the multi-angle simultaneous observation of the high-resolution spectra of the two bands is realized, which proves the effectiveness of this method. This study will provide a scientific basis for the observation of aerosol, water vapor, and cloud ground-based networks.

Explaining NOMAD D/H Observations by Cloud‐Induced Fractionation of Water Vapor on Mars

AbstractThe vertical profiles of water vapor and its semi‐heavy hydrogen isotope HDO provided by instruments on ExoMars Trace Gas Orbiter constitute a unique new data set to understand the Martian water cycle including its isotopic composition. As water vapor undergoes hydrogen isotopic fractionation upon deposition (but not sublimation), the D/H isotopic ratio in water is a tracer of phase transitions, and a key quantity to understand the long‐term history of water on Mars. Here, we present 3D global simulations of D/H in water vapor and compare them to the vertically resolved observations of D/H and water ice clouds taken by NOMAD during the second half of Mars year 34. D/H is predicted to be constant with height up to the main cloud level, above which it drops because of strong fractionation, explaining the upper cut‐off in the NOMAD observations when HDO drops below detectability. During the global and regional dust storms of 2018/2019, we find that HDO ascends with H2O, and that the D/H ratio is constant and detectable up to larger heights. The simulations are within the provided observational uncertainties over wide ranges in season, latitude and height. Our work provides evidence that the variability of the D/H ratio in the lower and middle atmosphere of Mars is controlled by fractionation on water ice clouds, and thus modulated by diurnally and seasonally varying cloud formation. We find no evidence of other processes or reservoirs that would have a significant impact on the D/H ratio in water vapor.

Data Fusion of GEO FY-4A GIIRS and LEO Hyperspectral Infrared Sounders with Surface Observations: A Hong Kong Case Study

Abstract Hyperspectral infrared satellite observations from geostationary platforms allow for the retrieval of temperature and water vapor measurements with higher temporal and vertical resolution than was previously available. The Chinese satellite Fengyun-4A (FY-4A) includes the Geostationary Interferometric Infrared Sounder (GIIRS), which has the ability to measure vertical profiles of temperature and water vapor from space at times when ground-based upper-air soundings are not available and can fill an important need in short-range weather prediction. In this study, convective available potential energy (CAPE) and lifted index (LI), which are used for forecasting atmospheric instability, were computed using the SHARPpy algorithm used by the NWS Storm Prediction Center. However, remote infrared and microwave sensing is lacking detailed information in the boundary layer, so the addition of the NOAA Meteorological Assimilation and Data Ingest System (MADIS) surface data may be necessary in order to get accurate temperature and moisture measurement near the surface. This study uses 10–16 May 2019 in the coastal region near Hong Kong for evaluating the use of hourly surface observations combined with satellite soundings from FY-4A GIIRS at 2-h intervals. The GIIRS plus MADIS surface-based CAPE and LI estimates are compared to estimates derived from low-Earth-orbiting (LEO) SNPP and NOAA-20 from NOAA, MetOp from EUMETSAT, NWP reanalysis, and local radiosondes. In the case study, the 2-h sampling interval of the GIIRS geostationary sounder was able to capture the rapid transition (16 h) from a stable to an unstable atmosphere in both CAPE and LI. The use of surface observations with satellite soundings gave mixed results, possibly due to the complex terrain near Hong Kong.

Multi‐GNSS Airborne Radio Occultation Observations as a Complement to Dropsondes in Atmospheric River Reconnaissance

AbstractVariations in the water vapor that atmospheric rivers (ARs) carry toward North America within Pacific storms strongly modulates the spatiotemporal distribution of west‐coast precipitation. The “AR Recon” program was established to improve forecasts of landfalling Pacific‐coast ARs and their associated precipitation. Dropsondes are deployed from weather reconnaissance aircraft and pressure sensors have been added to drifting ocean buoys to fill a major gap in standard weather observations, while research is being conducted on the potential for airborne Global Navigation Satellite System (GNSS) radio occultation (ARO) to also contribute to forecast improvement. ARO further expands the spatial coverage of the data collected during AR Recon flights. This study provides the first description of these data, which provide water vapor and temperature information typically as far as 300 km to the side of the aircraft. The first refractivity profiles from European Galileo satellites are provided and their accuracy is evaluated using the dropsondes. It is shown that spatial variations in the refractivity anomaly (difference from the climatological background) are modulated by AR features, including the low‐level jet and tropopause fold, illustrating the potential for RO measurements to represent key AR characteristics. It is demonstrated that assimilation of ARO refractivity profiles can influence the moisture used as initial conditions in a high‐resolution model. While the dropsonde measurements provide precise, in situ wind, temperature and water vapor vertical profiles beneath the aircraft, and the buoys provide surface pressure, ARO provides complementary thermodynamic information aloft in broad areas not otherwise sampled at no additional expendable cost.

Estimation of the Precipitable Water and Water Vapor Fluxes in the Coastal and Inland Cities of China Using MAX-DOAS

Water vapor transport affects regional precipitation and climate change. The measurement of precipitable water (PW) and water vapor flux (WVF) is of great importance for the study of precipitation and water vapor transport. This study presented a new method of computing PW and estimating WVF using the water vapor vertical column density (VCD) and profile retrieved from multi-axis differential optical absorption spectroscopy (MAX-DOAS), combined with the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 wind profiles. We applied our method to MAX-DOAS observations in the coastal (Qingdao) and inland (Xi’an) cities of China from June 2019 to May 2020 and compared the results to the ERA5 reanalysis datasets. Good agreement with ERA5 datasets was found; the correlation coefficient (r) of the PW and the zonal and meridional WVFs were r ≥ 0.92, r = 0.77, and r ≥ 0.89, respectively. The comparison results showed the feasibility and reliability of estimating PW and WVF using MAX-DOAS. Then, we analyzed the seasonal and diurnal climatology of the PW and WVFs in Qingdao and Xi’an. The results indicated that the seasonal and diurnal variations of the PW in the two cities were similar. The zonal water vapor transport of the two cities mainly involved eastward transport, Qingdao’s meridional water vapor mainly involved southward transport, and that of Xi’an mainly involved northward transport. The WVFs of the two cities were higher in the afternoon than in the morning, which may be related to wind speed. The results also indicated that the WVF transmitting belts appeared at around 2 and 1.4 km above the surface in Qingdao and around 2.8, 2.6, 1.6, and 1.0 km above the surface in Xi’an. Before precipitation, the WVF transmitting belt moved from near the ground to a high level, reaching its maximum at about 2 km, and the PW and meridional vertically integrated WVF increased. Finally, the sources and transports of water vapor during continuous precipitation and torrential rain were analyzed according to a 24 h backward trajectory. The air mass from the southeast accounted for more than 84% during continuous precipitation in Xi’an, while the air mass from the ocean accounted for more than 75% during torrential rain in Qingdao and was accompanied by a high-level ocean jet stream. As an optical remote sensing instrument, MAX-DOAS has the advantages of high spatiotemporal resolution, low cost, and easy maintenance. The application of MAX-DOAS to meteorological remote sensing provides a better method for evaluating the PW and WVF.

Evaluation of Arctic Water Vapor Profile Observations from a Differential Absorption Lidar

The continuous measuring of the vertical profile of water vapor in the boundary layer using a commercially available differential absorption lidar (DIAL) has only recently been made possible. Since September 2018, a new pre-production version of the Vaisala DIAL system has operated at the Iqaluit supersite (63.74°N, 68.51°W), commissioned by Environment and Climate Change Canada (ECCC) as part of the Canadian Arctic Weather Science project. This study presents its evaluation during the extremely dry conditions experienced in the Arctic by comparing it with coincident radiosonde and Raman lidar observations. Comparisons over a one year period were strongly correlated (r > 0.8 at almost all heights) and exhibited an average bias of +0.13 ± 0.01 g/kg (DIAL-sonde) and +0.18 ± 0.02 g/kg (DIAL-Raman). Larger differences exhibiting distinct artifacts were found between 250 and 400 m above ground level (AGL). The DIAL’s observations were also used to conduct a verification case study of operational numerical weather prediction (NWP) models during the World Meteorological Organization’s Year of Polar Prediction. Comparisons to ECCC’s global environmental multiscale model (GEM-2.5 km and GEM-10 km) indicate good agreement with an average bias < 0.16 g/kg for the higher-resolution (GEM-2.5 km) models. All models performed significantly better during the winter than the summer, likely due to the winter’s lower water vapor concentrations and decreased variability. This study provides evidence in favor of using high temporal resolution lidar water vapor profile measurements to complement radiosonde observations and for NWP model verification and process studies.

An observational study of the boundary-layer entrainment and impact of aerosol radiative effect under aerosol-polluted conditions

Aerosols exert a profound impact on the atmospheric boundary layer (ABL) structures and entrainment processes. However, observational analysis of entrainment under heavily polluted condition is rarely documented due to insufficient measurements. In this study, vertical profiles of potential temperature, water vapor, and particulate matter with aerodynamic diameter smaller than 2.5 μm (PM2.5) measured by unmanned aerial vehicle (UAV), LiDAR-measured extinction coefficients, as well as surface observations are presented to investigate the impact of aerosol radiative effect on entrainment processes under heavy aerosol pollution conditions. Results show that aerosol radiative effect reduces surface heat fluxes and influences entrainment substantially. Observations indicate that the column-like plume rise structure is the instigator accounting for the entrainment processes observed during daytime. A well-established entrainment zone identified in the nighttime (e.g., 02:00 local standard time, LST) is mainly due to strong wind shear generating turbulence. The parameters describing entrainment processes are largely modified by aerosol radiative effect. Specifically, the jumps of scalars on the heavy pollution day are much larger than that on the clean day. Entrainment zone thickness enlarges substantially as PM2.5 concentrations increase. The bin-averaged ratios of entrainment to surface heat fluxes are close to a constant (about 0.21) but show a large standard deviation with aerosol pollution conditions. The dimensionless entrainment velocity does not follow the −1 power-law relationship with Richardson number for the heavily polluted conditions, which is consistent with the previous large-eddy simulation (LES) results. This observational study provides valuable evidence in support of high-resolution modeling studies of entrainment with heavily-polluted aerosol conditions.

Characterization of the Far Infrared Properties and Radiative Forcing of Antarctic Ice and Water Clouds Exploiting the Spectrometer-LiDAR Synergy

Optical and microphysical cloud properties are retrieved from measurements acquired in 2013 and 2014 at the Concordia base station in the Antarctic Plateau. Two sensors are used synergistically: a Fourier transform spectroradiometer named REFIR-PAD (Radiation Explorer in Far Infrared-Prototype for Applications and Developments) and a backscattering-depolarization LiDAR. First, in order to identify the cloudy scenes and assess the cloud thermodynamic phase, the REFIR-PAD spectral radiances are ingested by a machine learning algorithm called Cloud Identification and Classification (CIC). For each of the identified cloudy scenes, the nearest (in time) LiDAR backscattering profile is processed by the Polar Threshold (PT) algorithm that allows derivation of the cloud top and bottom heights. Subsequently, using the CIC and PT results as external constraints, the Simultaneous Atmospheric and Clouds Retrieval (SACR) code is applied to the REFIR-PAD spectral radiances. SACR simultaneously retrieves cloud optical depth and effective dimensions and atmospheric vertical profiles of water vapor and temperature. The analysis determines an average effective diameter of 28 μm with an optical depth of 0.76 for the ice clouds. Water clouds are only detected during the austral Summer, and the retrieved properties provide an average droplet diameter of 9 μm and average optical depth equal to four. The estimated retrieval error is about 1% for the ice crystal/droplet size and 2% for the cloud optical depth. The sensitivity of the retrieved parameters to the assumed crystal shape is also assessed. New parametrizations of the optical depth and the longwave downwelling forcing for Antarctic ice and water clouds, as a function of the ice/liquid water path, are presented. The longwave downwelling flux, computed from the top of the atmosphere to the surface, ranges between 70 and 220 W/m2. The estimated cloud longwave forcing at the surface is (31 ± 7) W/m2 and (29 ± 6) W/m2 for ice clouds and (64 ± 12) and (62 ± 11) W/m2 for water clouds, in 2013 and 2014, respectively. The total average cloud forcing for the two years investigated is (46 ± 9) W/m2.

Gridded Satellite Sounding Retrievals in Operational Weather Forecasting: Product Description and Emerging Applications

The National Aeronautics and Space Administration (NASA) Short-term Prediction Research and Transition Center (SPoRT) has been part of a collaborative effort within the National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) Proving Ground and Risk Reduction (PGRR) Program to develop gridded satellite sounding retrievals for the operational weather forecasting community. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) retrieves vertical profiles of temperature, water vapor, trace gases, and cloud properties derived from infrared and microwave sounder measurements. A new, optimized method for deriving NUCAPS level 2 horizontally and vertically gridded products is described here. This work represents the development of approaches to better synthesize remote sensing observations that ultimately increase the availability and usability of NUCAPS observations. This approach, known as “Gridded NUCAPS”, was developed to more effectively visualize NUCAPS observations to aid in the quick identification of thermodynamic spatial gradients. Gridded NUCAPS development was based on operations-to-research feedback and is now part of the operational National Weather Service display system. In this paper, we discuss how Gridded NUCAPS was designed, how relevant atmospheric fields are derived, its operational application in pre-convective weather forecasting, and several emerging applications that expand the utility of NUCAPS for monitoring phenomena such as fire weather, the Saharan Air Layer, and stratospheric air intrusions.

Validation of Water Vapor Vertical Distributions Retrieved from MAX-DOAS over Beijing, China

Water vapor vertical profiles are important in numerical weather prediction, moisture transport, and vertical flux calculation. This study presents the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) retrieval algorithm for water vapor vertical profiles and the retrieved results are validated with corresponding independent datasets under clear sky. The retrieved Vertical Column Densities (VCDs) and surface concentrations are validated with the Aerosol Robotic Network (AERONET) and National Climatic Data Centre (NCDC) datasets, achieving good correlation coefficients (R) of 0.922 and 0.876, respectively. The retrieved vertical profiles agree well with weekly balloon-borne radiosonde measurements. Furthermore, the retrieved water vapor concentrations at different altitudes (100–2000 m) are validated with the corresponding European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim datasets, achieving a correlation coefficient (R) varying from 0.695 to 0.857. The total error budgets for the surface concentrations and VCDs are 31% and 38%, respectively. Finally, the retrieval performance of the MAX-DOAS algorithm under different aerosol loads is evaluated. High aerosol loads obstruct the retrieval of surface concentrations and VCDs, with surface concentrations more liable to severe interference from such aerosol loads. To summarize, the feasibility of detecting water vapor profiles using MAX-DOAS under clear sky is confirmed in this work.

Toronto Water Vapor Lidar Inter-Comparison Campaign

This study presents comparisons between vertical water vapor profile measurements from a Raman lidar and a new pre-production broadband differential absorption lidar (DIAL). Vaisala’s novel DIAL system operates autonomously outdoors and measures the vertical profile of water vapor within the boundary layer 24 h a day during all weather conditions. Eight nights of measurements in June and July 2018 were used for the Toronto water vapor lidar inter-comparison field campaign. Both lidars provided reliable atmospheric backscatter and water vapor profile measurements. Comparisons were performed during night-time observations only, when the York Raman lidar could measure the water vapor profile. The purpose was to validate the water vapor profile measurements retrieved by the new DIAL system. The results indicate good agreement between the two lidars, with a mean difference (DIAL–Raman) of 0.17 ± 0.14 g/kg. There were two main causes for differences in their measurements: horizontal displacement between the two lidar sites (3.2 km) and vertical gradients in the water vapor profile. A case study analyzed during the campaign demonstrates the ability for both lidars to measure sudden changes and large gradients in the water vapor’s vertical structure due to a passing frontal system. These results provide an initial validation of the DIAL’s measurements and its ability to be implemented as part of an operational program.