Search Results (29)

Submillimeter wave radiometers are promising remote sensing tools for sounding ice cloud parameters. The Ice Cloud Imager (ICI) aboard the second generation of the EUMETSAT Polar System (EPS−SG) is the first operational submillimeter wave radiometer used for ice cloud remote sensing. Ice clouds simultaneously contain three species of ice hydrometeors—ice, snow, and graupel—the physical distributions and submillimeter wave radiation characteristics of which differ. Therefore, jointly retrieving the mass parameters of the three ice hydrometeors from submillimeter brightness temperatures is very challenging. In this paper, we propose a multiple species of ice hydrometeor parameters retrieval algorithm based on convolutional neural networks (CNNs) that can jointly retrieve the total content and vertical profiles of ice, snow, and graupel particles from submillimeter brightness temperatures. The training dataset is generated by a numerical weather prediction (NWP) model and a submillimeter wave radiative transfer (RT) model. In this study, an end to end ICI simulation experiment involving forward modeling of the brightness temperature and retrieval of ice cloud parameters was conducted to verify the effectiveness of the proposed CNN retrieval algorithm. Compared with the classical Unet, the average relative errors of the improved RCNN–ResUnet are reduced by 11%, 25%, and 18% in GWP, IWP, and SWP retrieval, respectively. Compared with Bayesian Monte Carlo integration algorithm, the average relative error of the total content retrieved by RCNN–ResUnet is reduced by 71%. Compared with BP neural network algorithm, the average relative error of the vertical profiles retrieved by RCNN–ResUnet is reduced by 69%. In addition, this algorithm was applied to actual Advanced Technology Microwave Sounder (ATMS) 183 GHz observed brightness temperatures to retrieve graupel particle parameters with a relative error in the total content of less than 25% and a relative error in the profile of less than 35%. The results show that the proposed CNN algorithm can be applied to future space borne submillimeter wave radiometers to jointly retrieve mass parameters of ice, snow, and graupel. Full article

A U-Net algorithm was used to retrieve surface pressure and wind speed over the ocean within tropical cyclones (TCs) and their neighboring areas using NOAA-20 Advanced Technology Microwave Sounder (ATMS) reprocessed Sensor Data Record (SDR) brightness temperatures (TBs) and geolocation information. For TC locations, International Best Track Archive for Climate Stewardship (IBTrACS) data have been used over the North Atlantic Ocean and West Pacific Ocean between 2018 and 2021. The European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) surface pressure and wind speed were employed as reference labels. Preliminary results demonstrated that the visualizations for wind speed and pressure matched the prediction and ERA5 location. The residual biases and standard deviations between the predicted and reference labels were about 0.15 m/s and 1.95 m/s, respectively, for wind speed and 0.48 hPa and 2.67 hPa, respectively, for surface pressure, after applying cloud screening for each ATMS pixel. This indicates that the U-Net model is effective for surface wind speed and surface pressure estimates over general ocean conditions. Full article

Global Navigation Satellite System (GNSS) Radio Occultation (RO) data play an essential role in improving numerical weather prediction (NWP) and monitoring climate change. The NOAA Commercial RO Purchase Program (CDP) purchased RO data provided by Spire Global Inc. To ensure the data quality from Spire Global Inc. is consistent with other RO missions, we need to quantify their accuracy and retrieval uncertainty carefully. In this work, Spire Wet Profile (wet temperature profile) data from 7 September 2021 to 31 October 2022, processed by the University Corporation for Atmospheric Research (UCAR), and COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere, and Climate-2/Formosa Satellite Mission 7) data are evaluated through comparison with NOAA-20 Advanced Technology Microwave Sounder (ATMS) microwave sounder measurements and collocated RS41 radiosonde measurements. Through the Community Radiative Transfer Model (CRTM) simulation, we convert the Spire and COSMIC-2 RO retrievals to ATMS brightness temperature (BT) at sounding channels CH07 to CH14 (temperature channels), with weighting function peak heights from 8 km to 35 km, and CH19 to CH22 (water vapor channels), with weighting function peak heights ranging from 3.2 km to 6.7 km, and compare the simulations with the collocated NOAA-20 ATMS measurements over ocean. Using ATMS observations as references, Spire and COSMIC-2 BTs agree well with ATMS within 0.07 K for CH07-14 and 0.20 K for CH19-22. The trends between Spire and COSMIC-2 are consistent within 0.07 K/year over the oceans for ATMS CH07-CH13 and CH19-22, indicating that Spire/COSMIC-2 wet profiles are, in general, compatible with each other over oceans. The RO retrievals and RS41 radiosonde observation (RAOB) comparison shows that above 0.2 km altitude, RS41 RAOB matches Spire/COSMIC-2 temperature profiles well with a temperature difference of <0.13 K, and the trends between Spire and COSMIC-2 are consistent within 0.08 K/year over land, indicating that Spire/COSMIC-2 wet profiles are overall compatible with each other through RS41 RAOB measurements over land. In addition, the consistency of Spire and COSMIC-2 based on different latitude intervals, local times, and signal-to-noise ratios (SNRs) through ATMS was evaluated. The results show that the performance of Spire is comparable to COSMIC-2, even though COSMIC-2 has a higher SNR. The high quality of RO profiles from Spire is expected to improve short- and medium-range global numerical weather predictions and help construct consistent climate temperature records. Full article

Among the monitored telemetry raw data record (RDR) parameters with the STAR Integrated/Validation System (ICVS), the Advanced Technology Microwave Sounder (ATMS) scan motor mechanism temperature is especially important because the instrument might be unavoidably damaged if the mechanism temperature exceeds 50 °C. In the current operational flight processing software, the instrument automatically enters safe mode and stops collecting scientific data whenever the mechanism temperature exceeds 40 °C. This approach inevitably leads to the instrument entering safe mode unnecessarily at a premature time, causing the loss of scientific data before the mechanism temperature reaches 50 °C. This study seeks to leverage the influence the main motor current, compensation motor current, and main motor loop integral error have on mechanism temperature to forecast the maximum mechanism temperature over the upcoming 6 min. A long short-term memory (LSTM) neural network predicts maximum mechanism temperature using ATMS RDR telemetry data as the input. The performance of the LSTM is compared with observed maximum mechanism temperatures by applying the LSTM coefficients to several cases. In all cases studied, the mean average error (MAE) of the forecast remained under 1.1 °C, and the correlation between forecasts and measurements remained above 0.96. These forecasts of maximum mechanism temperature are expected to be able to provide information on when the ATMS instrument should enter safe mode without needlessly losing valuable data for the ATMS flight operational team. Full article

The Joint Polar Satellite System (JPSS) mission has provided over ten years of high-quality data products for environment forecasting and monitoring through the current Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. Particularly, the sensor data record (SDR) and the derived environmental data record (EDR) products from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), and the Ozone Mapping and Profiler Suite (OMPS) offer an unprecedented opportunity to observe severe weather and environmental events over the Earth. This paper presents the observations about atmospheric features of the Hunga Tonga Volcanic eruption of January 2022, e.g., the gravity wave, volcanic cloud, and aerosol (sulfate) plume phenomena, by using the ATMS, CrIS, OMPS, and VIIRS SDR and EDR products. Powerful gravity waves ringing through the atmosphere after the eruption of the Hunga Tonga volcano are discovered at two CrIS upper sounding channels (670 cm⁻¹ and 2320 cm⁻¹) in the deviations of the observed brightness temperature (O) from the simulated baseline brightness temperature (B) using the Community Radiative Transfer Model (CRTM), i.e., O—B. A similar pattern is also observed in the ATMS global maps at channel 15, whose peak weighting function is around 40 km, showing the atmospheric disturbance caused by the eruption that reached 40 km above the surface. The Tonga volcanic cloud (plume) was also captured by the OMPS SO₂ EDR product. The gravity wave features were also captured in the native resolution image of the S-NPP VIIRS I-5 band nighttime observations. In addition, the VIIRS Aerosol Optical Depth (AOD) captured and tracked the volcanic aerosol (sulfate) plume successfully. These discoveries demonstrate the scientific potential of the JPSS SDR and EDR products in monitoring and tracking the eruption of the Hunga Tonga volcano and its severe environmental impacts. This paper presents the atmospheric features of the Hunga Tonga volcano eruption that is uniquely captured by all four advanced sensors onboard JPSS satellites, with different spectral coverages and spatial resolutions. Full article

FengYun-3E (FY-3E), the fifth satellite in China’s second-generation polar-orbiting satellite FY-3 series, was launched on 5 July 2021. FY-3E carries a third-generation microwave temperature sounder (MWTS-3). For the first time, this study demonstrates that MWTS-3 radiances data assimilation can improve the China Meteorological Administration Global Forecast System (CMA-GFS). By establishing a cloud detection module based on the retrieval results of the new channels of MWTS-3, a quality control module according to the error characteristics of MWTS-3 data, and a bias correction module considering the scanning position of satellite and weather systems, the effective assimilation of MWTS-3 data in the CMA-GFS has been realized. Through one-month cycling experiments of assimilation and forecasts, the error characteristics and assimilation effects of MWTS-3 data are carefully evaluated. The results show that the observation errors in MWTS-3 data are similar to those in advanced technology microwave sounder (ATMS) data within the same frequency channel, are slightly larger than those in the advanced microwave-sounding unit-A (AMSU-A) data, and are much better than those in the MWTS-2 data. The validation of the assimilation and prediction results demonstrate the positive contribution of MWTS-3 data assimilation, which can remarkably reduce the analysis errors in the Northern and Southern Hemispheres. Specifically, the error growth on the upper layer of the model is obviously suppressed. When all other operational satellite observations are included, the assimilation of MWTS-3 data has a neutral or slightly positive contribution to the analysis and forecast results, and the improvement is mainly found in the Southern Hemisphere. The relevant evaluation results indicate that the MWTS-3 data assimilation has good application prospects for operation. Full article

The global navigation satellite system (GNSS) radio occultation (RO) is becoming an essential component of National Oceanic and Atmospheric Administration (NOAA) observation systems. The constellation observing system for meteorology, ionosphere, and climate (COSMIC) 2 mission and the Formosa satellite mission 7, a COSMIC follow-on mission, is now the NOAA’s backbone RO mission. The NOAA’s dedicated GNSS RO SAtellite processing and science Application Center (RO-SAAC) was established at the Center for Satellite Applications and Research (STAR). To better quantify how the observation uncertainty from clock error and geometry determination may propagate to bending angle and refractivity profiles, STAR has developed the GNSS RO data processing and validation system. This study describes the COSMIC-2 neutral atmospheric temperature and moisture profile inversion algorithms at STAR. We used RS41 and ERA5, and UCAR 1D-Var products (wetPrf2) to validate the accuracy and uncertainty of the STAR 1D-Var thermal profiles. The STAR-RS41 temperature differences are less than a few tenths of 1 K from 8 km to 30 km altitude with a standard deviation (std) of 1.5–2 K. The mean STAR-RS41 water vapor specific humidity difference and the standard deviation are −0.35 g/kg and 1.2 g/kg, respectively. We also used the 1D-Var-derived temperature and water vapor profiles to compute the simulated brightness temperature (BTs) for advanced technology microwave sounder (ATMS) and cross-track infrared sounder (CrIS) channels and compared them to the collocated ATMS and CrIS measurements. The BT differences of STAR COSMIC-2-simulated BTs relative to SNPP ATMS are less than 0.1 K over all ATMS channels. Full article

As a potential external calibration reference for spaceborne microwave sounding instruments, accurate and reliable information of lunar disk-averaged radiance at millimeter band are important and fundamental. Based on study for 2-D lunar scans of the Advanced Technology Microwave Sounder (ATMS) on board the NOAA-20 satellite, the lunar radiance spectrum from 23 to 183 GHz at full moon phase has been reported in our previous work. In this study, the performance of a lunar microwave radiative transfer model (RTM) developed by Keihm was investigated (cited as Keihm model in this paper) . By taking the ATMS observations as the reference truth, the surface emissivity in the lunar RTM can be calibrated. The calibrated RTM model was then evaluated by independent satellite observation data sets from AMSU (Advanced Microwave Sounding Unit) and MHS (Microwave Humidity Sounder) instruments on several NOAA satellites. Results show that with the calibrated model, significant improvement can be made to reduce the uncertainties in the lunar microwave RTM simulations at millimeter wavelengths. Full article

In this study, the polarization characteristics of the newly launched Fengyun-3E (FY-3E) microwave sounding instruments are discussed, and its data quality is also assessed using one month of observation by the double-difference method. By comparison with the equivalent channels onboard Fengyun-3D (FY-3D) and advanced technology microwave sounder (ATMS), the data quality of FY-3E Microwave Humidity Sounder-II (MWHS-II) is improved and comparable to ATMS, while the data of FY-3E Microwave Temperature Sounder-III (MWTS-III) are slightly worse than data of FY-3D. The data of FY-3E MWTS-III are more susceptible to the early-morning orbit than the data of MWHS-II. In addition, striping noise is still present in channels 5–10 of MWTS-III. After the assessments, FY-3E microwave data are preprocessed and assimilated in the global forecast system for the Chinese Meteorology Administration (CMA-GFS). A total of six individual experiments over the period from 16 July to 15 August 2021 were conducted and the impact was evaluated with the composite score used in operation. It is shown that not only the forecasts for the southern hemisphere and tropics are improved significantly, but also the predictions for the northern hemisphere show some improvements in an overall neutral change from adding FY-3E microwave sounding instruments. The impact of FY-3E microwave radiance is equivalent to ATMS as they are assimilated individually. Furthermore, we note that the forecast impact is affected by the cloud detection scheme to a large extent. Full article

The integrated Multi-satellitE Retrievals for GPM (IMERG) Version V05B and V06B precipitation products from the Global Precipitation Measurement (GPM) mission are validated against ground-based observations from the Kwajalein Polarimetric S-band Weather Radar (KPOL) deployed at Kwajalein Atoll in the central Pacific Ocean. Such a validation is particularly important as comprehensive surface measurements over the oceans are practically infeasible, which hampers the identification of possible errors, and improvement of future versions of IMERG and other satellite-based retrieval algorithms. The V05B and V06B IMERG products are validated at their native 0.1°, 30 min resolution from 2014 to 2018 based on both volumetric and categorical metrics. This validation study indicates that precipitation rates from both IMERG V05B and V06B are underestimated with respect to radar surface estimates, but the underestimation is much reduced from V05B to V06B. IMERG V06B outperforms V05B with reduced systematic bias and improved precipitation detectability. The IMERG performance is further traced back to its individual sensors and morphing-based algorithms. The overall underestimation in V05B is mainly driven by the negative relative biases from morphing-based algorithms which are largely corrected in V06B. Imagers perform generally better than sounders because of the usage of low-frequency channels in imagers which can better detect emission signals by the hydrometeors. Among imagers, the GPM Microwave Imager (GMI) and Advanced Microwave Scanning Radiometer Version 2 (AMSR2) are the best, followed by Special Sensor Microwave Imager/Sounder (SSMIS). Among sounders, the Microwave Humidity Sounder (MHS) is the best, followed by Advanced Technology Microwave Sounder (ATMS) and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR) for V06B. Among all categories, morph-only and IR + morph only perform better than SAPHIR. SAPHIR shows the worst performance among all categories, likely due to its limited channel selection. It is envisaged that these results will improve our understanding of IMERG performance over oceans and aid in the improvement of future versions of IMERG. Full article

This study investigated the impact of the assimilation of satellite radiance observations in a three-dimensional variational data assimilation system (3DVAR) that could improve the tracking and intensity forecasts of the Tropical Storm Dianmu in 2021, which occurred over parts of southeast mainland Asia. The weather research and forecasting (WRF) model was used to conduct the assimilation experiments of the storm. Four sets of numerical experiments were performed using the WRF. In the first, the control experiment, only conventional data in Binary Universal Form for the Representation of Meteorological Data (PREPBUFR) observations from the National Centers for Environmental Prediction (NCEP) were assimilated. The second experiment (RDA1) was performed with PREPBUFR observations and satellite radiance data from the Advanced Microwave Unit-A (AMSU-A), and the Advanced Technology Microwave Sounder (ATMS). PREPBUFR observations and the High-resolution Infrared Radiation Sounder (HIRS-4) were used in the third experiment (RDA2). The fourth experiment (ALL-OBS) used the assimilation of PREPBUFR observations and all satellite radiance data (AMSU-A, ATMS, and HIRS-4). The community radiative transfer model was used on the forward operator for the satellite radiance assimilation, along with quality control and bias correction procedures, before assimilating the radiance data. To evaluate the impact of the assimilation experiments, a forecast starting on 00 UTC 23 September 2021, was produced for 72 h. The results showed that the ALL-OBS experiment improved the short-term forecast up to ~24 h lead time, as compared to the assimilation considering only PREPBUFR observations. When all observations were assimilated into the model, the storm’s landfall position, intensity, and structure were accurately predicted. In the deterministic forecast, the tracking errors of the ALL-OBS experiment was consistently less than 40 km within 24 h. The case study of Tropical Storm Dianmu exhibited the significant positive impact of all observations in the numerical model, which could improve updates for initial conditions and storm forecasting. Full article

The observations from satellite microwave-sounding instruments have been widely used in weather and climate studies. Since the data resolution varies with frequency and satellite viewing angle, it is normally required that the measurements at each frequency be resampled to obtain a uniform resolution prior to various applications. In this study, the ATOVS and AVHRR pre-processing package (AAPP) Fourier transform algorithm is modified for ATMS data and the results are compared with those derived from Backus–Gilbert inversion (BGI) and the original AAPP. From the simulated and observed ATMS data, we demonstrated the new algorithm has better results in terms of imaging quality and noise suppression, compared with BGI and AAPP. In general, our modified AAPP algorithm reduces the error by at least about 0.5 K in ATMS channels 2 and 6 and at all the viewing angles. Full article

Radio occultation (RO) sensor measurements have critical roles in numerical weather prediction (NWP) by complementing microwave and infrared sounder measurements with information of the atmospheric profiles at high accuracy, precision, and vertical resolution. This study evaluates Constellation Observing System for Meteorology, Ionosphere, and Climate 2 (COSMIC-2) wet temperature and humidity data products’ consistency and stability through inter-comparison with SNPP advanced technology microwave sounder (ATMS) measurements. Through the community radiative transfer model (CRTM), brightness temperature (BT) at SNPP ATMS channels are simulated with COSMIC-2 retrieved atmospheric profiles from two versions of the University Corporation for Atmospheric Research (UCAR) wet profiles (WETprf and WETpf2) as inputs to the CRTM simulation. The analysis was focused on ATMS sounding channels CH07–14 and CH19–22 with sounding weighting function peak heights from 3.2 to 35 km. The COSMIC-2 vs. ATMS inter-comparison indicates that their BT biases are consistent, and the latitudinal difference is <0.3 K over three latitudinal regions. The differences between the two versions of UCAR COSMIC-2 wet profiles are identified and attributed to the differences in the implementation of 1DVAR retrieval algorithms. The stability between UCAR near real-time COSMIC-2 wet profile data and ATMS measurements is also well-maintained. It is demonstrated that the well-sustained quality of COSMIC-2 RO data makes itself a well-suited reference sensor to capture the calibration update of SNPP ATMS. Furthermore, the impacts of the assimilation of COSMIC-2 data into the European Centre for Medium-Range Weather Forecasts (ECMWF) model after 25 March 2020, are evaluated by trending observation-minus-background (O-B) biases, which confirms the statistically significant positive impacts of COSMIC-2 on the ECMWF reanalysis. The validation of stability and consistency between COSMIC-2 and SNPP ATMS ensures the quality of RO and microwave sounder data assimilated into the NWP models. Full article

Two existing double-difference (DD) methods, using either a 3rdSensor or Radiative Transfer Modeling (RTM) as a transfer, are applicable primarily for limited regions and channels, and, thus critical in capturing inter-sensor calibration radiometric bias features. A supplementary method is also desirable for estimating inter-sensor calibration biases at the window and lower sounding channels where the DD methods have non-negligible errors. In this study, using the Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System (JPSS)-1 (alias NOAA-20) as an example, we present a new inter-sensor bias statistical method by calculating 32-day averaged differences (32D-AD) of radiometric measurements between the same instrument onboard two satellites. In the new method, a quality control (QC) scheme using one-sigma (for radiance difference), or two-sigma (for radiance) thresholds are established to remove outliers that are significantly affected by diurnal biases within the 32-day temporal coverage. The performance of the method is assessed by applying it to estimate inter-sensor calibration radiometric biases for four instruments onboard SNPP and NOAA-20, i.e., Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS), Nadir Profiler (NP) within the Ozone Mapping and Profiler Suite (OMPS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Our analyses indicate that the globally-averaged inter-sensor differences using the 32D-AD method agree with those using the existing DD methods for available channels, with margins partially due to remaining diurnal errors. In addition, the new method shows its capability in assessing zonal mean features of inter-sensor calibration biases at upper sounding channels. It also detects the solar intrusion anomaly occurring on NOAA-20 OMPS NP at wavelengths below 300 nm over the Northern Hemisphere. Currently, the new method is being operationally adopted to monitor the long-term trends of (globally-averaged) inter-sensor calibration radiometric biases at all channels for the above sensors in the Integrated Calibration/Validation System (ICVS). It is valuable in demonstrating the quality consistencies of the SDR data at the four instruments between SNPP and NOAA-20 in long-term statistics. The methodology is also applicable for other POES cross-sensor calibration bias assessments with minor changes. Full article

Satellite observations of brightness temperature from the Advanced Technology Microwave Sounder (ATMS) and Microwave Humidity Sounder (MHS) humidity sounding channels can provide relatively high horizontal resolution information about cloud and atmospheric moisture in the troposphere, thus revealing the structures of tropical cyclones (TCs). There is usually a high brightness temperature in a TC eye region and low brightness temperature reflecting spiral rain bands. An azimuthal spectral analysis method is used as a center-fixing algorithm to determine the TC center objectively using the brightness temperature observations of the ATMS humidity-sounding channel 18 (183.31 ± 7.0 GHz) and MHS humidity-sounding channel 5 (190.31 GHz). The position in the brightness temperature field encompassing a TC that achieves the largest symmetric component is regarded as the TC center. Two Atlantic hurricanes in 2012, Hurricanes Sandy and Isaac, are first used to analyze the performance of the TC center-fixing technique. Compared with the National Hurricane Center best track, the root-mean-square differences of the center fixing results for Hurricanes Sandy and Isaac are less than 47.3 and 34.3 km, respectively. It is found that the uncertainty of the TC center-fixing algorithm and thus the difference from the best track increases when the brightness temperature distribution within a TC is significantly asymmetric. Then, the TC center-fixing technique is validated for all tropical storms and hurricanes over Northern Atlantic and Western Pacific in 2019. Compared with the best track data, the root-mean-square differences for tropical storms and hurricanes are 33.81 and 26.20 km, respectively. The demonstrated successful performance of the proposed TC center-fixing algorithm to use the single channel of microwave humidity sounders for TC positioning is important for vortex initialization in operational hurricane forecasts. Full article