Advanced Technology Microwave Sounder Research Articles

Joint Retrieval of Multiple Species of Ice Hydrometeor Parameters from Millimeter and Submillimeter Wave Brightness Temperature Based on Convolutional Neural Networks

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.

Comparison of tropical cyclone thermal structures derived from ATMS and synthetic AMSU-A/MHS

The warm core of a tropical cyclone (TC) reflects its intensity and evolution. In the past, microwave sounding data have been widely used for detecting the TC warm core. However, the observed magnitude of the TC warm core can vary with instruments. This study utilizes the oversampling data from the Advanced Technology Microwave Sounder (ATMS) to reconstruct the brightness temperature data consistent with the data from Advanced Microwave Sounding Unit-A (AMSU-A), which is referred to as AMSU-like data. Through comparisons, it is found that brightness temperature from the original ATMS has more detailed structures, depicting well the TC eye region and cloud bands. Both ATMS and AMSU-like data are used as inputs to the Global Scene-Dependent Atmospheric Retrieval Testbed (GSDART) to retrieve the warm cores of multiple TCs. At 250 hPa, the warm-core intensity retrieved using ATMS data is about 1–2 K higher than that from AMSU-like data and the warm-core structure from ATMS is more detailed. It is recommended that the warm-core intensity retrieved from AMSU-A be corrected to the ATMS values for multi-sensor monitoring of TCs using our newly defined relationship.摘要热带气旋(TC)的暖心反映了其强度和变化. 微波探测数据被广泛用于探测TC暖心, 但观测到的 TC 暖心强度可能因仪器而异. 本研究利用先进技术微波探测仪 (ATMS) 的过采样数据重采样至与先进微波探测仪 (AMSU-A) 一致的亮温, 称为类-AMSU数据. 通过对比发现, ATMS的观测更加细致, 较好地刻画了TC眼区和云带. 使用ATMS和类-AMSU数据反演多个TC的暖心发现, 在250 hPa, 使用ATMS数据反演的暖心强度比类-AMSU高约1–2K, 并且其暖心结构更详细.

Retrieval of temperature profiles in tropical cyclone Nanmadol from resampled advanced technology microwave sounder observations

In the past, satellite microwave sounding data are often utilized for retrieving the thermal structure of tropical cyclones (TCs). However, the spatial resolutions and scan pattern of the instruments vary from one to another and can affect the retrievals of TC structures. In this study, Backus-Gilbert Inversion (BGI), ATOVS and AVHRR Pre-processing Package (AAPP) filter and N × N field-of-views (FOVs) average algorithms are utilized to resample the Advanced Technology Microwave Sounder (ATMS) data and the impacts from different resampling algorithms on brightness temperature structures and retrieved atmospheric temperature are analyzed. It is shown that for ATMS channel 1 to 2, the larger differences between original and resampled brightness temperatures are found in cloudy areas and at the land-ocean boundary. When ATMS channels 1–16 data are resampled to the AMSU-like resolution, the brightness temperatures become less noisy at channel 3 to 16 and can lead to a higher convergence rate in the one-dimension variational (1DVAR) algorithm. Furthermore, the warm core intensity of a tropical storm of Nanmadol is reduced by about 2.5 K and its size becomes smaller after the ATMS data is resampled to the AMSU resolution.

Machine Learning-Based Estimation of Tropical Cyclone Intensity from Advanced Technology Microwave Sounder Using a U-Net Algorithm

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.

The Hunga Tonga‐Hunga Ha'apai Volcanic Eruption as Seen in Satellite Microwave Observations and MiRS Temperature Retrievals

AbstractThe strongest volcanic eruption since the 19th century occurred on 15 January 2022 at Hunga Tonga‐Hunga Ha'apai, generating unprecedented atmospheric waves not seen before in observations. We used satellite microwave observations from (a) Advanced Technology Microwave Sounder (ATMS) on board the National Oceanic and Atmospheric Administration (NOAA)‐20 and the Suomi‐National Polar‐orbiting Partnership (SNPP) and (b) Advanced Microwave Sounding Unit (AMSU)‐A on board Meteorological operational satellite (MetOp)‐B/MetOp‐C to study these waves in the stratosphere immediately after the eruption. The NOAA Microwave Integrated Retrieval System (MiRS) was applied to these microwave observations to produce atmospheric temperature profiles. The atmospheric Lamb wave and fast‐traveling gravity waves are clearly revealed in both the brightness temperatures and the MiRS retrieved temperatures, revealing their vertical phase structures. This study is the first attempt to perform a detailed analysis of the stratospheric impact of the Tonga eruption on operational satellite microwave observations and the corresponding MiRS retrievals.

Single field-of-view sounder atmospheric product retrieval algorithm: establishing radiometric consistency for hyper-spectral sounder retrievals

Abstract. The single field-of-view (SFOV) sounder atmospheric product (SiFSAP) retrieval algorithm has been developed to address the need to retrieve high-spatial-resolution atmospheric data products from hyper-spectral sounders and ensure the radiometric consistency between the retrieved properties and measured spectral radiances. It is based on an integrated optimal-estimation inversion scheme that processes data from the satellite-based synergistic microwave (MW) and infrared (IR) spectral measurements from advanced sounders. The retrieval system utilizes the principal component radiative transfer model (PCRTM), which performs radiative transfer calculations monochromatically and includes accurate cloud-scattering simulations. SiFSAP includes temperature, water vapor, surface skin temperature and emissivity, cloud height and microphysical properties, and concentrations of essential trace gases for each SFOV at a native instrument spatial resolution. Error estimations are provided based on a rigorous analysis for uncertainty propagation from the top-of-atmosphere (TOA) spectral radiances to the retrieved geophysical properties. As a comparison, the spatial resolution for the traditional hyper-spectral sounder retrieval products is much coarser than the native resolution of the instruments due to the common use of the “cloud-clearing” technique to compensate for the lack of cloud-scattering simulation in the forward model. The degraded spatial resolution in traditional cloud-clearing sounder retrieval products limits their applications for capturing meteorological or climate signals at finer spatial scales. Moreover, a rigorous uncertainty propagation estimation needed for long-term climate trend studies cannot be given due to the lack of direct radiative transfer relationships between the observed TOA radiances and the retrieved geophysical properties. With the advantages of the higher spatial resolution; the simultaneous retrieval of atmospheric, cloud, and surface properties using all available spectral information; and the establishment of “radiance closure” in the sounder spectral measurements, the SiFSAP provides additional information needed for various weather and climate studies and applications using sounding observations. This paper gives an overview of the SiFSAP retrieval algorithm and assessment of SiFSAP atmospheric temperature, water vapor, clouds, and surface products derived from the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) data.

Evaluating and Improving TROPICS Millimeter‐Wave Sounder's Precipitation Estimate Over Ocean

AbstractThis paper examines precipitation retrievals from Kidd et al. (2022, https://doi.org/10.3390/rs14132992) by applying the Precipitation Retrieval and Profiling Scheme to data observed by the NASA Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter‐wave Sounder (TMS) onboard the TROPICS Pathfinder satellite, a precursor to the TROPICS mission. We first compare the TMS precipitation retrieval performance over ocean with those from seven current operational passive microwave radiometers, including four conical scanning sensors [Special Sensor Microwave Imager/Sounders (SSMISs) onboard F16/F17/F18 satellites, and Advanced Microwave Scanning Radiometer 2 (AMSR2)] and three cross track scanning sensors [Microwave Humidity Sounders onboard NOAA19 and MetOpB satellites, and the Advanced Technology Microwave Sounder onboard the National Polar‐orbiting Partnership satellite], using precipitation estimates from Global Precipitation Measurement Mission Microwave Imager (GMI) as the reference. We show that TMS performs similarly to the current operational cross track scanning sensors, while worse than conical scanning sensors largely due to the lack of low frequency channels (e.g., 19 GHz). Second, we create an adjusted TMS precipitation retrievals by combining the original TMS precipitation and the precipitation propagated from AMSR2 and SSMISs to the time/location of the TMS overpass, using our previously developed microwave‐to‐microwave propagation technique. Results show that the adjusted TMS precipitation performs better than the original TMS estimates. For example, the correlation of the original TMS and GMI estimates is 0.35 but increases to 0.49 when the adjusted TMS result is compared to GMI. The propagation technique lays the foundation to improve TMS precipitation when incorporating them into level‐3 merged products.

Spire RO Thermal Profiles for Climate Studies: Initial Comparisons of the Measurements from Spire, NOAA-20 ATMS, Radiosonde, and COSMIC-2

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.

Efficient collocation of global navigation satellite system radio occultation soundings with passive nadir microwave soundings

Abstract. Radio occultation (RO) using the global navigation satellite system (GNSS) can be used to infer atmospheric profiles of microwave refractivity in the Earth's atmosphere. GNSS RO data are now assimilated into numerical weather prediction models and used for climate monitoring. New remote sensing applications are being considered that fuse GNSS RO soundings and passive nadir-scanned radiance soundings. Collocating RO soundings and nadir-scanned radiance soundings, however, is computationally expensive, especially as new commercial GNSS RO constellations greatly increase the number of global daily RO soundings. This paper develops a new and efficient technique, called the “rotation–collocation method”, for collocating RO and nadir-scanned radiance soundings in which all soundings are rotated into the time-dependent reference frame in which the nadir sounder's scan pattern is stationary. Collocations with RO soundings are then found when the track of an RO sounding crosses the line corresponding to the nadir sounder's scan pattern. When applied to finding collocations between RO soundings from COSMIC-2, Metop-B-GRAS, and Metop-C-GRAS and the passive microwave (MW) soundings of the Advanced Technology Microwave Sounder (ATMS) on NOAA-20 and Suomi-NPP and the Advanced Microwave Sounding Unit (AMSU-A) on Metop-B and Metop-C for the month of January 2021, the rotation–collocation method proves to be 99.0 % accurate and is hundreds to thousands of times faster than traditional approaches to finding collocations.

Mid‐Tropospheric Layer Temperature Record Derived From Satellite Microwave Sounder Observations With Backward Merging Approach

AbstractWe present a new version (v5.0) of the NOAA Center for Satellite Applications and Research (STAR) mid‐tropospheric temperature (TMT) time series. This data set uses a backward‐merging approach to intercalibrate 16 satellite‐based microwave sounding records. The instrument observations included those from the Microwave Sounding Unit (MSU) during 1979–2004, Advanced Microwave Sounding Unit‐A (AMSU‐A) during 1998–2017, and Advanced Technology Microwave Sounder (ATMS) from 2011 to present. A TMT time series during 2002–present based on satellite microwave observations in stable sun‐synchronous orbits was used as a reference in the backward merging process in which earlier satellites were adjusted and merged to the reference. Observations from earlier satellites were recalibrated to remove their calibration drifting errors relative to the reference using sequential overlapping observations. This included removal of spurious warming drifts in the MSU observations onboard NOAA‐11, NOAA‐12, and NOAA‐14 and a spurious cooling drift in the NOAA‐15 AMSU‐A observations. Temperature changes resulting from diurnal sampling drifts were corrected using an observation‐based semi‐physical model developed in this study. Other adjustments included channel frequency differences between MSU and AMSU‐A companion channels and instrument blackbody warm target effect on observed radiances. These adjustments resulted in inter‐consistent TMT records spanning MSU, AMSU‐A, and ATMS. The merged time series produced a global mean TMT trend of 0.092 ± 0.043 K/decade during 1979–2021 and a total tropospheric trend of 0.142 ± 0.045 K/decade after removal of a stratospheric cooling effect in TMT. Remarkably, the total tropospheric trends during the latest half period were nearly doubled the earlier half period over the global ocean.

Forecasting Maximum Mechanism Temperature in Advanced Technology Microwave Sounder (ATMS) Data Using a Long Short-Term Memory (LSTM) Neural Network

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.

Evaluation of Snowfall Retrieval Performance of GPM Constellation Radiometers Relative to Spaceborne Radars

Abstract This study assesses the level-2 snowfall retrieval results from 11 passive microwave radiometers generated by the version 5 Goddard profiling algorithm (GPROF) relative to two spaceborne radars: CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Measurement (GPM) Ku-band Precipitation Radar (KuPR). These 11 radiometers include six conical scanning radiometers [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), its successor sensor AMSR2, GPM Microwave Imager (GMI), and three Special Sensor Microwave Imager/Sounders (SSMIS)] and five cross-track scanning radiometers [Advanced Technology Microwave Sounder (ATMS) and four Microwave Humidity Sounders (MHS)]. Results show that over ocean conical scanning radiometers have better detection and intensity estimation skills than cross-track sensors, likely due to the availability and usage of the low-frequency channels (e.g., 19 and 37 GHz). Over land, AMSR-E and AMSR2 have noticeably worse performance than other sensors, primarily due to the lack of higher than 89-GHz channels (e.g., 150, 166, and 183 GHz). Over both land and ocean, all 11 sensors severely underestimate the snowfall intensity, which propagates to the widely used level 3 precipitation product [i.e., Integrated Multi-satelliteE Retrievals for GPM (IMERG)]. These conclusions hold regardless of using either KuPR or CPR as the reference, though the statistical metrics vary quantitatively. The conclusions drawn from these comparisons apply solely to the GPROF version 5 algorithm.

Observed Atmospheric Features for the 2022 Hunga Tonga Volcanic Eruption from Joint Polar Satellite System Science Data Products

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.

Optimal Channel Selection of Spaceborne Microwave Radiometer for Surface Pressure Retrieval over Oceans

Abstract The O2-band channel configuration of existing microwave radiometers is not optimal for surface pressure retrieval, which limits the surface pressure retrieval accuracy. In this study, we present the results of theoretically what might be the optimal microwave channels for surface pressure retrieval. An improved iterative selection method is used to select the channels that contain the highest cumulative content of surface pressure information. The selected optimal channel set comprises 16 channels, among which 10 channels are centered at the 50–60 GHz oxygen absorption band and 6 channels are centered around the 118.75 GHz oxygen absorption line. Two representative spaceborne microwave radiometers are used for comparisons, the Advanced Technology Microwave Sounder (ATMS) on board the Suomi National Polar-Orbiting Partnership (SNPP) satellite and the Microwave Humidity and Temperature Sounder (MWHTS) on board the Chinese Fengyun-3C (FY-3C) satellite. The results of information content analysis show that the optimal channel set contains more surface pressure information than that of the combination of SNPP/ATMS and FY-3C/MWHTS (SNPP/ATMS+FY-3C/MWHTS) channels. A representative dataset from the ERA5 data is input into the plane-parallel Microwave Radiative Transfer model to obtain the simulated brightness temperature observations of the selected optimal channels and the SNPP/ATMS+FY-3C/MWHTS channels. Using the simulated observations, retrieval experiments are performed. Experimental results show that retrieval accuracies of the optimal channel set are 1.09 and 1.64 hPa for clear-sky and cloudy conditions, respectively. The retrieval accuracies are 0.60 and 0.65 hPa better than that of the SNPP/ATMS+FY-3C/MWHTS channels for clear-sky and cloudy conditions, respectively.

Direct Assimilation of Chinese FY-3E Microwave Temperature Sounder-3 Radiances in the CMA-GFS: An Initial Study

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.

Characteristics of Strong Storms at the Pre‐Convection Stage From Satellite Microwave Sounder Observations

AbstractHigh‐temporal‐resolution geostationary satellite infrared measurements are always used to capture and predict typical characteristics at the cloud top of rapidly developing strong storms at the pre‐convection or convection initiation (CI) stage. However, the large false alarm rate of CI nowcasting is difficult to avoid due to the complex and unpredictable trigger factors. Although the microwave measurement technique can observe thick clouds and even the precipitation within clouds due to the weaker atmospheric extinction effect on microwave, microwave data from polar‐orbiting satellites are rarely used to observe the CI due to their relatively low temporal resolution. In this study, we analyze several previously unknown CI characteristics over the East Asia region from 2016 to 2019 based on spatially and temporally matched Advanced Technology Microwave Sounder data. These typical CI samples are initially identified by using continuous infrared images from the Himawari‐8 geostationary satellite. The results show that there is a distinct cloud optical depth at the pre‐convection stage in the western (deep cloud clusters) and eastern (shallow cloud clusters) Tibetan Plateau (TP). The shallow precipitating cloud clusters of the CI over the eastern TP are possibly attributed to the favorable local dynamic and thermal conditions stem from the Asian monsoon. Another notable finding shows that the fast‐developing CI over the ocean has thick clouds compared with the samples over the land. Overall, the unique CI characteristics found from microwave observations in this study indicate that the future geostationary microwave sounder technologies will almost certainly provide some new findings and enhance early warning capabilities about convection.

Processing and Validation of the STAR COSMIC-2 Temperature and Water Vapor Profiles in the Neutral Atmosphere

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.

A Calibrated Lunar Microwave Radiative Transfer Model Based on Satellite Observations

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.

Impact of Fengyun-3E Microwave Temperature and Humidity Sounder Data on CMA Global Medium Range Weather Forecasts

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.

Validation of IMERG Oceanic Precipitation over Kwajalein

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.