Water Vapor Band Research Articles

Assimilation of GOES-13 Imager Clear-Sky Water Vapor (6.5 μm) Radiances into a Warn-on-Forecast System

A prototype convection-allowing system using the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model and employing an ensemble Kalman filter (EnKF) data assimilation technique has been developed and used during the spring 2016 and 2017 Hazardous Weather Testbeds. This system assimilates WSR-88D reflectivity and radial velocity, geostationary satellite cloud water path (CWP) retrievals, and available surface observations over a regional domain with a 3-km horizontal resolution at 15-min intervals, with 3-km initial conditions provided by an experimental High-Resolution Rapid Refresh ensemble (HRRR-e). However, no information on upper-level thermodynamic conditions in cloud-free regions is currently assimilated, as few timely observations exist. One potential solution is to also assimilate clear-sky satellite radiances, which provide information on mid- and upper-tropospheric temperature and moisture conditions. This research assimilates GOES-13 imager water vapor band (6.5 μm) radiances using the GSI-EnKF system to take advantage of the Community Radiative Transfer Model (CRTM) integration. Results using four cases from May 2016 showed that assimilating radiances generally had a neutral-to-positive impact on the model analysis, reducing humidity bias and/or errors at the appropriate model levels where verification observations were present. The effects on high-impact weather forecasts, as verified against forecast reflectivity and updraft helicity, were mixed. Three cases (9, 22, and 24 May) showed some improvement in skill, while the other (25 May) performed worse, despite the improved environment. This research represents the first step in designing a high-resolution ensemble data assimilation system to use GOES-16 Advanced Baseline Imager data, which provides additional water vapor bands and increased spatial and temporal resolution.

Spectral model for clear sky atmospheric longwave radiation

An efficient spectrally resolved radiative model is used to calculate surface downwelling longwave (DLW) radiation (0 ∼ 2500 cm−1) under clear sky (cloud free) conditions at the ground level. The wavenumber spectral resolution of the model is 0.01 cm−1 and the atmosphere is represented by 18 non-uniform plane-parallel layers with pressure in each layer determined on a pressure-based coordinate system. The model utilizes the most up-to-date (2016) HITRAN molecular spectral data for 7 atmospheric gases: H2O, CO2, O3, CH4, N2O, O2 and N2. The MT_CKD model is used to calculate water vapor and CO2 continuum absorption coefficients. Longwave absorption and scattering coefficients for aerosols are modeled using Mie theory. For the non-scattering atmosphere (aerosol free), the surface DLW agrees within 2.91% with mean values from the InterComparison of Radiation Codes in Climate Models (ICRCCM) program, with spectral deviations below 0.035 W cm m−2. For a scattering atmosphere with typical aerosol loading, the DLW calculated by the proposed model agrees within 3.08% relative error when compared to measured values at 7 climatologically diverse SURFRAD stations. This relative error is smaller than a calibrated parametric model regressed from data for those same 7 stations, and within the uncertainty (+/− 5 W m−2) of pyrgeometers commonly used for meteorological and climatological applications. The DLW increases by 1.86 ∼ 6.57 W m−2 when compared with aerosol-free conditions, and this increment decreases with increased water vapor content due to overlap with water vapor bands. As expected, the water vapor content at the layers closest to the surface contributes the most to the surface DLW, especially in the spectral region 0 ∼ 700 cm−1. Additional water vapor content (mostly from the lowest 1 km of the atmosphere) contributes to the spectral range of 400 ∼ 650 cm−1. Low altitude aerosols ( ∼ 3.46 km or less) contribute to the surface value of DLW mostly in the spectral range 750 ∼ 1400 cm−1.

Dimensionality-varied deep convolutional neural network for spectral–spatial classification of hyperspectral data

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral–spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral–spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral–spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

Discriminating satellite IR anomalies associated with the MS 7.1 Yushu earthquake in China

In the process of exploring pre-earthquake thermal anomalies using satellite infrared data, Blackett et al. (2011) found that the previously reported anomalies before the 2001 Mw 7.7 Gujarat earthquake, in India, were related to positive biases caused by data gaps due to cloud cover and mosaicing of neighboring orbits of MODIS satellite data. They supposed that such effects could also be responsible for other cases. We noted a strip-shaped TIR anomaly on March 17th, 2010, 28 days before the Ms. 7.1 Yushu earthquake (Qin et al., 2011). Here we again investigate multi-year infrared satellite data in different bands to discriminate whether the anomaly is associated with the earthquake, or is only bias caused by the data gaps. From the water vapor images, we find lots of clouds that have TIR anomalies. However, on the cloudiness background, there is an obvious strip-shaped gap matching the tectonic faults almost perfectly. In particular, the animation loops of hourly water vapor images show that the cloud kept moving from west to east, while they never covered the strip-shaped gap. We consider that the cloud with this special spatial pattern should have implied the abnormal signals associated with the seismogenic process. Based on current physical models, the satellite IR anomalies both on TIR and water vapor bands can qualitatively be explained using synthetic mechanisms.

Dispersion-Induced Distortions of a Rectangular Radio Pulse with Linear Chirp in a Resonantly Absorbing Gas Medium

Existing analytical results on the propagation of electromagnetic pulse in resonantly absorbing gas medium are used to analyze possible character and features of the dispersion-induced distortions of an ultrashort frequency-modulated radio pulse with the initial rectangular shape and the carrier frequency that is close to the resonance frequency of a single strong absorption band of water vapor in the millimeter-wavelength range (183.36 GHz).

Improving the Algorithm of Extracting Regional Total Precipitable Water Vapor Over Land From MODIS Images

Precise estimation of total precipitable water vapor (TPW) with high temporal and spatial resolutions is of great importance in different disciplines. Moderate-Resolution Imaging Spectroradiometer (MODIS) is one of the sensors which have absorption and nonabsorption bands of water vapor. There is a standard algorithm to produce TPW product of MODIS (MOD05/MYD05) which uses the ratios of reflectances in strong, moderate, and weak absorption bands of water vapor to nonabsorption ones (transmission). This paper aims to present a method based on this algorithm to optimize TPW estimation in local scale. To do so, the western part of Iran was chosen as the study region. Terra MODIS images and MOD05 in clear-sky conditions related to the 100 days in four seasons of 2015–2016 were provided as the selected data. To validate and improve the results, TPW measured in six radiosonde stations and interpolated for overpass time of Terra was utilized. Four procedures were performed. In the first procedure, the coefficients of transmissions were extracted using linear least-squares technique, separately. For the second procedure, the coefficients were calculated in terms of the highest atmospheric transmission sensitivity to TPW for each absorption band separately, and in the third procedure, they were calculated simultaneously. In the last procedure, the errors from third one were modeled with a linear relationship between reflectance ratios of absorption bands. Based on the results, in highest accuracy, the coefficient of determination ${{{\text{R}}}}^{2}$ and Root Mean Square Error was 0.878 and 2.702 mm, respectively, which were acceptable comparing those of other researchers.

Search for water vapor in the high-resolution transmission spectrum of HD 189733b in the visible

Ground-based telescopes equipped with state-of-the-art spectrographs are able to obtain high-resolution transmission and emission spectra of exoplanets that probe the structure and composition of their atmospheres. Various atomic and molecular species, such as Na, CO, H2O have been already detected. Molecular species have been observed only in the near-infrared while atomic species have been observed in the visible. In particular, the detection and abundance determination of water vapor bring important constraints to the planet formation process. We search for water vapor in the atmosphere of the exoplanet HD189733b using a high-resolution transmission spectrum in the visible obtained with HARPS. We use Molecfit to correct for telluric absorption features. Then we compute the high-resolution transmission spectrum of the planet using 3 transit datasets. We finally search for water vapor absorption using a cross-correlation technique that combines the signal of 800 individual lines. Telluric features are corrected to the noise level. We place a 5-sigma upper limit of 100 ppm on the strength of the 6500 A water vapor band. The 1-sigma precision of 20 ppm on the transmission spectrum demonstrates that space-like sensitivity can be achieved from the ground. This approach opens new perspectives to detect various atomic and molecular species with future instruments such as ESPRESSO at the VLT. Extrapolating from our results, we show that only 1 transit with ESPRESSO would be sufficient to detect water vapor on HD189733b-like hot Jupiter with a cloud-free atmosphere. Upcoming near-IR spectrographs will be even more efficient and sensitive to a wider range of molecular species. Moreover, the detection of the same molecular species in different bands (e.g. visible and IR) is key to constrain the structure and composition of the atmosphere, such as the presence of Rayleigh scattering or aerosols.

In-Orbit Spectral Response Function Correction and Its Impact on Operational Calibration for the Long-Wave Split-Window Infrared Band (12.0 μm) of FY-2G Satellite

During the early stage of the G satellite of the Fengyun-2 series (FY-2G), severe cold biases up to ~2.3 K occur in its measurements in the 12.0 μm (IR2) band, which demonstrate time- and scene-dependent characteristics. Similar cold biases in water vapor and carbon dioxide absorption bands of other satellites are considered to be caused by either ice contamination (physical method) or spectral response function (SRF) shift (empirical method). Simulations indicate that this cold bias of FY-2G indeed suffers from equivalent SRF shift as a whole towards the longer wavelength direction. To overcome it, a novel approach combining both physical and empirical methods is proposed. With the possible ice thicknesses tested before launch, the ice contamination effect is alleviated, while the shape of the SRF can be modified in a physical way. The remaining unknown factors for cold bias are removed by shifting the convolved SRF with an ice transmittance spectrum. Two parameters, i.e., the ice thickness (5 μm) and the shifted value (+0.15 μm), are estimated by inter-calibration with reference instruments, and the modification coefficient is also calculated (0.9885) for the onboard blackbody calibration. Meanwhile, the updated SRF was released online on 23 March 2016. For the period between July 2015 and December 2016, the monthly biases of the FY-2G IR2 band remain oscillating around zero, the majorities (~89%) of which are within ±1.0 K, while its mean monthly absolute bias is around 0.6 K. Nevertheless, the cold bias phenomenon of the IR2 band no longer exists. The combination method can be referred by other corrections for cold biases.

Impact of Megha-Tropiques SAPHIR radiances in T574L64 global data assimilation and forecasting system at NCMRWF

ABSTRACTThe Sounder for Probing Vertical Profiles of Humidity (SAPHIR) is a sounding instrument of Megha-Tropiques (Indo-French joint satellite); launched by the Indian Space Research Organization on 12 October 2011 with six channels near the absorption band of water vapour at 183 GHz. In the framework of this work, the assimilation scheme has been first modified to enable the SAPHIR radiance observations being used as additional observation type, and second, a methodology has been prepared to remove the radiance pixels significantly affected by clouds. The impact of SAPHIR radiances on analysis as well as forecasts of the National Centre for Medium Range Weather Forecasting-Global Forecast System (NGFS) at T574L64 resolution has been investigated through data assimilation. Measurements from SAPHIR are incorporated into the Gridpoint Statistical Interpolation three-dimensional variational assimilation system to provide the improved initial conditions. To find out the impact, analysis/forecast cycling experiments with and without SAPHIR radiances are performed during the period 10–29 November 2013. The impact of the improvement in term of root mean square error has been clearly evaluated for five parameters, namely, relative humidity, temperature, wind, geopotential height, and specific humidity. It is demonstrated that the assimilation of SAPHIR observations results in a considerable improvement for the five parameters over the global region. During the study period, two tropical cyclones (HELEN, 19–22 November and LEHAR, 23–28 November) were formed over the North Indian Ocean. Impact on specific humidity and track forecast errors of tropical cyclone are also examined. Overall, initial results show the usefulness of SAPHIR radiances in the NGFS.

Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data

An algorithm is proposed for making charts of the distribution of water vapor in the atmosphere based on multispectral images of the earth by the Ocean and Land Color Instrument (OLCI) on board of the European research satellite Sentinel-3. The algorithm is based on multiple regression fits of the spectral brightness coefficients at the upper boundary of the atmosphere, the geometric parameters of the satellite location (solar and viewing angles), and the total water vapor content in the atmosphere. A regression equation is derived from experimental data on the variation in the optical characteristics of the atmosphere and underlying surface, together with Monte-Carlo calculations of the radiative transfer characteristics. The equation includes the brightness coefficients in the near IR channels of the OLCI for the absorption bands of water vapor and oxygen, as well as for the transparency windows of the atmosphere. Together these make it possible to eliminate the effect of the reflection spectrum of the underlying surface and air pressure on the accuracy of the measurements. The algorithm is tested using data from a prototype OLCI, the medium resolution imaging spectrometer (MERIS). A sample chart of the distribution of water vapor in the atmosphere over Eastern Europe is constructed without using subsatellite data and digital models of the surface relief. The water vapor contents in the atmosphere determined using MERIS images and data provided by earthbound measurements with the aerosol robotic network (AERONET) are compared with a mean square deviation of 1.24 kg/m2.

Atmospheric characterization of Proxima b by coupling the SPHERE high-contrast imager to the ESPRESSO spectrograph

Context. The temperate Earth-mass planet Proxima b is the closest exoplanet to Earth and represents what may be our best ever opportunity to search for life outside the Solar System. Aims. We aim at directly detecting Proxima b and characterizing its atmosphere by spatially resolving the planet and obtaining high-resolution reflected-light spectra. Methods. We propose to develop a coupling interface between the SPHERE high-contrast imager and the new ESPRESSO spectrograph, both installed at ESO VLT. The angular separation of 37 mas between Proxima b and its host star requires the use of visible wavelengths to spatially resolve the planet on a 8.2-m telescope. At an estimated planet-to-star contrast of ~10^-7 in reflected light, Proxima b is extremely challenging to detect with SPHERE alone. However, the combination of a ~10^3-10^4 contrast enhancement from SPHERE to the high spectral resolution of ESPRESSO can reveal the planetary spectral features and disentangle them from the stellar ones. Results. We find that significant but realistic upgrades to SPHERE and ESPRESSO would enable a 5-sigma detection of the planet and yield a measurement of its true mass and albedo in 20-40 nights of telescope time, assuming an Earth-like atmospheric composition. Moreover, it will be possible to probe the O2 bands at 627, 686 and 760 nm, the water vapour band at 717 nm, and the methane band at 715 nm. In particular, a 3.6-sigma detection of O2 could be made in about 60 nights of telescope time. Those would need to be spread over 3 years considering optimal observability conditions for the planet. Conclusions. The very existence of Proxima b and the SPHERE-ESPRESSO synergy represent a unique opportunity to detect biosignatures on an exoplanet in the near future. It is also a crucial pathfinder experiment for the development of Extremely Large Telescopes and their instruments (abridged).

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

A global, monthly averaged time series of Sun-induced Fluorescence (SiF), spanning January 2007 to June 2015, was derived from Metop-A Global Ozone Monitoring Experiment 2 (GOME-2) spectral measurements. Far-red SiF was retrieved using the filling-in of deep solar Fraunhofer lines and atmospheric absorption bands based on the general methodology described by Joiner et al, AMT, 2013. A Principal Component (PC) analysis of spectra over non-vegetated areas was performed to describe the effects of atmospheric absorption. Our implementation (SiF KNMI) is an independent algorithm and differs from the latest implementation of Joiner et al, AMT, 2013 (SiF NASA, v26), because we used desert reference areas for determining PCs (as opposed to cloudy ocean and some desert) and a wider fit window that covers water vapour and oxygen absorption bands (as opposed to only Fraunhofer lines). As a consequence, more PCs were needed (35 as opposed to 12). The two time series (SiF KNMI and SiF NASA, v26) correlate well (overall R of 0.78) except for tropical rain forests. Sensitivity experiments suggest the strong impact of the water vapour absorption band on retrieved SiF values. Furthermore, we evaluated the SiF time series with Gross Primary Productivity (GPP) derived from twelve flux towers in Australia. Correlations for individual towers range from 0.37 to 0.84. They are particularly high for managed biome types. In the de-seasonalized Australian SiF time series, the break of the Millennium Drought during local summer of 2010/2011 is clearly observed.

Continuous Vernier filtering of an optical frequency comb for broadband cavity-enhanced molecular spectroscopy

We have recently introduced the Vernier-based Direct Frequency Comb Cavity-Enhanced Spectroscopy technique which allows us to record broadband spectra at high sensitivity and GHz resolution (Rutkowski and Morville, 2014) [1]. We discuss here the effect of Vernier filtering on the observed lineshapes in the 3ν+δ band of water vapor and the entire A-band of oxygen around 800nm in ambient air. We derive expressions for the absorption profiles resulting from the continuous Vernier filtering method, testing them on spectra covering more than 2000cm−1 around 12,500cm−1. With 31,300 independent spectral elements acquired at the second time scale, an absorption baseline noise of 2×10−8cm−1 is obtained, providing a figure of merit of 1.1×10−10cm−1/Hz per spectral element with a cavity finesse of 3000 and a cavity round-trip length around 3.3m.

The Zugspitze radiative closure experiment for quantifying water vapor absorption over the terrestrial and solar infrared – Part 1: Setup, uncertainty analysis, and assessment of far-infrared water vapor continuum

Abstract. Quantitative knowledge of water vapor radiative processes in the atmosphere throughout the terrestrial and solar infrared spectrum is still incomplete even though this is crucial input to the radiation codes forming the core of both remote sensing methods and climate simulations. Beside laboratory spectroscopy, ground-based remote sensing field studies in the context of so-called radiative closure experiments are a powerful approach because this is the only way to quantify water absorption under cold atmospheric conditions. For this purpose, we have set up at the Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.) a long-term radiative closure experiment designed to cover the infrared spectrum between 400 and 7800 cm−1 (1.28–25 µm). As a benefit for such experiments, the atmospheric states at the Zugspitze frequently comprise very low integrated water vapor (IWV; minimum = 0.1 mm, median = 2.3 mm) and very low aerosol optical depth (AOD = 0.0024–0.0032 at 7800 cm−1 at air mass 1). All instruments for radiance measurements and atmospheric-state measurements are described along with their measurement uncertainties. Based on all parameter uncertainties and the corresponding radiance Jacobians, a systematic residual radiance uncertainty budget has been set up to characterize the sensitivity of the radiative closure over the whole infrared spectral range. The dominant uncertainty contribution in the spectral windows used for far-infrared (FIR) continuum quantification is from IWV uncertainties, while T profile uncertainties dominate in the mid-infrared (MIR). Uncertainty contributions to near-infrared (NIR) radiance residuals are dominated by water vapor line parameters in the vicinity of the strong water vapor bands. The window regions in between these bands are dominated by solar Fourier transform infrared (FTIR) calibration uncertainties at low NIR wavenumbers, while uncertainties due to AOD become an increasing and dominant contribution towards higher NIR wavenumbers. Exceptions are methane or nitrous oxide bands in the NIR, where the associated line parameter uncertainties dominate the overall uncertainty. As a first demonstration of the Zugspitze closure experiment, a water vapor continuum quantification in the FIR spectral region (400–580 cm−1) has been performed. The resulting FIR foreign-continuum coefficients are consistent with the MT_CKD 2.5.2 continuum model and also agree with the most recent atmospheric closure study carried out in Antarctica. Results from the first determination of the NIR water vapor continuum in a field experiment are detailed in a companion paper (Reichert and Sussmann, 2016) while a novel NIR calibration scheme for the underlying FTIR measurements of incoming solar radiance is presented in another companion paper (Reichert et al., 2016).

Internal‐blackbody calibration (IBBC) approach and its operational application in FY‐2 meteorological satellites

Fengyun‐2 (FY‐2) are the first‐generation geostationary meteorological satellites (GEOMS) in China, two of which, FY‐2E and FY‐2G, are the operating workforce to support the dual‐satellite observation mode. The on‐board blackbody preliminarily used for stability monitoring of the instrument's radiometric response was equipped behind its fore‐optics due to the technical limitations in the 1990s with what was referred to as an internal‐blackbody (IBB) and operated at a unique pre‐set temperature. In this article, a novel IBB calibration (IBBC) approach is proposed and the radiometric contributions of the main optical elements as well as the IBB itself are modelled and extracted. This is the most distinguishing difference from the traditional full‐path blackbody calibration. The IBBC software has been in service for more than 2 years. Compared with the high spectral resolution reference instruments recommended by the Global Space‐based Inter‐Calibration System, the monthly mean calibration biases of the long‐wave infrared band (IR1: 10.8 µm) and water vapour band (IR3: 6.95 µm) are shown to be lower than 1.5 K for FY‐2E and lower than 1.0 K for FY‐2G (for ∼90% of cases). In particular, the annual mean biases for the FY‐2G IR3 band can maintain a good state of 0.4 K, which is nearly identical to that of other high‐class in‐orbit satellites, e.g. MTSAT‐2 and MSG‐1. Likely impacted by ice contamination, the calibration biases of the long‐wave split‐window infrared band (IR2: 12 µm) of FY‐2G could be as large as −2.3 K and similar phenomena once occurred in GOES‐13 and MSG‐1. This is expected to improve in the near future. In general, the calibration accuracies of FY‐2G IR1 and IR3 bands have become lower than 1 K, which is significantly superior to those of other first‐generation GEOMS, such as GMS‐5, Meteosat‐7 and GOES 4‐7, whose calibration accuracies are around 2–3 K. The quality of the data could be greatly enhanced so as to benefit the global observation system.

Validation of a weather forecast model at radiance level against satellite observations allowing quantification of temperature, humidity, and cloud‐related biases

AbstractAn established radiative transfer model (RTM) is adapted for simulating all‐sky infrared radiance spectra from the Canadian Global Environmental Multiscale (GEM) model in order to validate its forecasts at the radiance level against Atmospheric InfraRed Sounder (AIRS) observations. Synthetic spectra are generated for 2 months from short‐term (3–9 h) GEM forecasts. The RTM uses a monthly climatological land surface emissivity/reflectivity atlas. An updated ice particle optical property library was introduced for cloudy radiance calculations. Forward model brightness temperature (BT) biases are assessed to be of the order of ∼1 K for both clear‐sky and overcast conditions. To quantify GEM forecast meteorological variables biases, spectral sensitivity kernels are generated and used to attribute radiance biases to surface and atmospheric temperatures, atmospheric humidity, and clouds biases. The kernel method, supplemented with retrieved profiles based on AIRS observations in collocation with a microwave sounder, achieves good closure in explaining clear‐sky radiance biases, which are attributed mostly to surface temperature and upper tropospheric water vapor biases. Cloudy‐sky radiance biases are dominated by cloud‐induced radiance biases. Prominent GEM biases are identified as: (1) too low surface temperature over land, causing about −5 K bias in the atmospheric window region; (2) too high upper tropospheric water vapor, inducing about −3 K bias in the water vapor absorption band; (3) too few high clouds in the convective regions, generating about +10 K bias in window band and about +6 K bias in the water vapor band.

RTTOV-gb – adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations

Abstract. Ground-based microwave radiometers (MWRs) offer a new capability to provide continuous observations of the atmospheric thermodynamic state in the planetary boundary layer. Thus, they are potential candidates to supplement radiosonde network and satellite data to improve numerical weather prediction (NWP) models through a variational assimilation of their data. However in order to assimilate MWR observations, a fast radiative transfer model is required and such a model is not currently available. This is necessary for going from the model state vector space to the observation space at every observation point. The fast radiative transfer model RTTOV is well accepted in the NWP community, though it was developed to simulate satellite observations only. In this work, the RTTOV code has been modified to allow for simulations of ground-based upward-looking microwave sensors. In addition, the tangent linear, adjoint, and K-modules of RTTOV have been adapted to provide Jacobians (i.e., the sensitivity of observations to the atmospheric thermodynamical state) for ground-based geometry. These modules are necessary for the fast minimization of the cost function in a variational assimilation scheme. The proposed ground-based version of RTTOV, called RTTOV-gb, has been validated against accurate and less time-efficient line-by-line radiative transfer models. In the frequency range commonly used for temperature and humidity profiling (22–60 GHz), root-mean-square brightness temperature differences are smaller than typical MWR uncertainties (∼ 0.5 K) at all channels used in this analysis. Brightness temperatures (TBs) computed with RTTOV-gb from radiosonde profiles have been compared with nearly simultaneous and co-located ground-based MWR observations. Differences between simulated and measured TBs are below 0.5 K for all channels except for the water vapor band, where most of the uncertainty comes from instrumental errors. The Jacobians calculated with the K-module of RTTOV-gb have been compared with those calculated with the brute force technique and those from the line-by-line model ARTS. Jacobians are found to be almost identical, except for liquid water content Jacobians for which a 10 % difference between ARTS and RTTOV-gb at transparent channels around 450 hPa is attributed to differences in liquid water absorption models. Finally, RTTOV-gb has been applied as the forward model operator within a one-dimensional variational (1D-Var) software tool in an Observing System Simulation Experiment (OSSE). For both temperature and humidity profiles, the 1D-Var with RTTOV-gb improves the retrievals with respect to the NWP model in the first few kilometers from the ground.

Geostationary satellite‐based 6.7 μm band best water vapor information layer analysis over the Tibetan Plateau

AbstractThe best water vapor information layer (BWIL) of the 6.7 μm water vapor absorption infrared (IR) band for the FengYun‐2E is investigated over the Tibetan Plateau with standard atmospheric profile and European Centre for Medium‐Range Weather Forecasts (ECMWF) operational model analysis data. The sensitivity tests show that surface characteristics over the Tibetan Plateau have a significant influence on the BWIL. To be specific, topographic elevation, colder skin temperature, and lower emissivity tend to lift the altitude of the BWIL, decrease its magnitude, and narrow the half‐width range. The results from statistical analysis indicate that the altitude of the BWIL reaches the highest in summer and the lowest in winter. Meanwhile, the altitude of the BWIL is highly correlated with the water vapor amount above 500 hPa over the Tibetan Plateau and above 300 hPa over the East China Plain, respectively. The diurnal variation in the BWIL is synchronous with the diurnal variation in the surface skin temperature. It can be concluded from the study that surface characteristics over high terrain in dry and cold atmospheres have more significant impacts on the BWIL. With multiple water vapor absorption IR bands, the imagers on board the new generation of geostationary satellites will provide crucial improvement in water vapor remote sensing over the current single water vapor band on board the FY‐2 series according to the analysis in this study.

On the effect of stratification of atmospheric optical characteristics on the sky radiance in the solar principal plane

The detailed information on the “in situ” vertical distribution of optical characteristics of atmospheric aerosol is frequently absent because of the complexity and high cost of environmental monitoring from aircraft. This paper presents estimates of the atmospheric optical characteristic stratification effects on downward scattered radiation measured by a sun photometer at the Earth’s surface for two basic viewing geometries: in the solar almucantar and in the solar principal plane. We obtained estimates on the basis of numerical experiments, key parameters of which imitate both background (areas with low anthropogenic load) and extreme atmospheric situations (urban smog, dust haze over land, and dust outflow over water surface). In the visible spectral region, outside the oxygen, ozone, water vapor, and nitrogen dioxide absorption bands, the stratification of the atmospheric optical characteristics is shown to have no significant effect on the sky radiance in solar almucantar, however becoming important in the solar principal plane. The main factor is the vertical behavior of the aerosol extinction coefficient. The radiance calculation errors can be substantially reduced by using the simplest vertical profiles and, in particular, the exponential distribution of the extinction coefficient over height.

Near-infrared spectro-interferometry of Mira variables and comparisons to 1D dynamic model atmospheres and 3D convection simulations

We obtained a total of 20 near-infrared K-band spectro-interferometric snapshot observations of the Mira variables o Cet, R Leo, R Aqr, X Hya, W Vel, and R Cnc with a spectral resolution of about 1500. We compared observed flux and visibility spectra with predictions by CODEX 1D dynamic model atmospheres and with azimuthally averaged intensities based on CO5BOLD 3D dynamic model atmospheres including convection. Our visibility data confirm the presence of spatially extended molecular atmospheres located above the continuum radii with large-scale inhomogeneities or clumps that contribute a few percent of the total flux. The detailed structure of the inhomogeneities or clumps show a variability on time scales of 3 months and above. Both modeling attempts provided satisfactory fits to our data. In particular, they are both consistent with the observed decrease in the visibility function at molecular bands of water vapor and CO, indicating a spatially extended molecular atmosphere. Observational variability phases are mostly consistent with those of the best-fit CODEX models, except for near-maximum phases, where data are better described by near-minimum models. Rosseland angular diameters derived from the model fits are broadly consistent between those based on the 1D and the 3D models and with earlier observations. We derived fundamental parameters including absolute radii, effective temperatures, and luminosities for our sources. Our results provide a first observational support for theoretical results that shocks induced by convection and pulsation in the 3D CO5BOLD models of AGB stars are roughly spherically expanding and of similar nature to those of self-excited pulsations in 1D CODEX models. Unlike for red supergiants, the pulsation- and shock-induced dynamics can levitate the molecular atmospheres of Mira variables to extensions that are consistent with observations.