Advanced Microwave Sounding Unit Research Articles

Quantifying the impact of assimilating sensitive observations on heavy precipitation forecast with ensemble-based forecast sensitivity to observations technique

In this study, the Ensemble-based Forecast Sensitivity to Observations (EFSO) technique was used to examine the impact of assimilated sensitive observations on the forecast of heavy rainfall through three data assimilation strategies, i.e., running without observation assimilation (CNTL); with assimilation of all observations (CNTL_DA); with assimilation of sensitive observations (SEN_DA). The Infrared Atmospheric Sounder Interferometer presented the largest positive impact on the forecast, followed by the Advanced Microwave Sounding Unit A and surface land reports. The top 10% of observations contributing the largest positive impact on the forecast were located in the upstream ocean of the low-level winds associated with precipitation maximum. Compared to ensemble CNTL and CNTL_DA experiments, ensemble SEN_DA exhibited better precipitation probability, in which the representative member in ensemble SEN_DA successfully predicted the precipitation magnitude and location. Based upon the representative experiments of the ensemble CNTL, CNTL_DA, and SEN_DA, synoptic conditions were examined to understand how the SEN_DA improves the forecast of heavy precipitation. The three representative experiments exhibited similar characteristics and variations in large-scale circulation, horizontal water vapor transport, and wind fields. However, compared to the representative experiments of CNTL and CNTL_DA, the advection and barotropic components of potential divergence contributed to the increase and persistence of convective instability throughout heavy rainfall in SEN_DA. Heavy precipitation was closely associated with the intensity, duration, and location of the maximum convective instability. Furthermore, the release of convective instability depended on the mesoscale ascent, which determined the maximum and location of the precipitation. These results help to understand the optimization of observational design and assimilation strategy.

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.

Evaluating the Representations of Atmospheric Rivers and Their Associated Precipitation in Reanalyses With Satellite Observations

AbstractAtmospheric rivers (ARs) are filaments of enhanced horizontal moisture transport in the atmosphere. Due to their prominent role in the meridional moisture transport and regional weather extremes, ARs have been studied extensively in recent years. Yet, the representations of ARs and their associated precipitation on a global scale remains largely unknown. In this study, we developed an AR detection algorithm specifically for satellite observations using moisture and the geostrophic winds derived from 3D geopotential height field from the combined retrievals of the Atmospheric Infrared Sounder and the Advanced Microwave Sounding Unit on NASA Aqua satellite. This algorithm enables us to develop the first global AR catalog based solely on satellite observations. The satellite‐based AR catalog is then combined with the satellite‐based precipitation (Integrated Muti‐SatellitE Retrievals for GPM) to evaluate the representations of ARs and AR‐induced precipitation in reanalysis products. Our results show that the spreads in AR frequency and AR length distribution are generally small across data sets, while the spread in AR width is relatively larger. Reanalysis products are found to consistently underestimate both mean and extreme AR‐related precipitation. However, all reanalyses tend to precipitate too often under AR conditions, especially over low latitude regions. This finding is consistent with the “drizzling” bias which has plagued generations of climate models. Overall, the findings of this study can help to improve the representations of ARs and associated precipitation in reanalyses and climate models.

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.

Detail Enhancement of AIRS/AMSU Temperature and Moisture Profiles Using a 3D Deep Neural Network

Abstract In recent decades, spaceborne microwave and hyperspectral infrared sounding instruments have significantly benefited weather forecasting and climate science. However, existing retrievals of lower-troposphere temperature and humidity profiles have limitations in vertical resolution, and often cannot accurately represent key features such as the mixed-layer thermodynamic structure and the inversion at the planetary boundary layer (PBL) top. Because of the existing limitations in PBL remote sensing from space, there is a compelling need to improve routine, global observations of the PBL and enable advances in scientific understanding and weather and climate prediction. To address this, we have developed a new 3D deep neural network (DNN) that enhances detail and reduces noise in level 2 granules of temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) sounder instruments aboard NASA’s Aqua spacecraft. We show that the enhancement improves accuracy and detail including key features such as capping inversions at the top of the PBL over land, resulting in improved accuracy in estimations of PBL height.

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.

Accounting for Lambertian reflection in the assimilation of microwave sounding radiances over snow and sea‐ice

AbstractThis article investigates two aspects aimed at an increased use of surface‐sensitive microwave sounding radiances for numerical weather prediction (NWP), namely the assimilation of humidity‐sounding radiances from the Advanced Technology Microwave Sounder (ATMS) over snow, as well as the use of Lambertian reflection in radiative‐transfer modelling over snow and sea‐ice surfaces for temperature‐ and humidity‐sounding radiances. The Lambertian characteristics are modelled through a parameterisation of the effective zenith angle used to calculate the downwelling radiation in the radiative‐transfer model. Using Lambertian rather than specular reflection improves the forward modelling significantly for 183‐GHz humidity‐sounding channels over snow and sea‐ice in comparisons with observations, including a reduction of significant zenith‐angle‐dependent biases. For temperature‐sounding channels in the 50‐GHz band, comparisons between observations and background equivalents also suggest improvements from treating snow and sea‐ice surfaces as Lambertian or semi‐Lambertian, but the characteristics appear more variable and there are indications of other sources of error, such as biases in the skin temperature. For both spectral regions, the improvement from using nonspecular reflection is clearest for snow‐covered land surfaces. Assimilation experiments show that the addition of 183‐GHz humidity‐sounding channels from ATMS over snow‐covered land leads to a slight positive impact over higher latitudes in winter. On top of this, replacing the specular surface assumption over snow and sea‐ice with a fully Lambertian one for 183‐GHz channels on ATMS and semi‐Lambertian one for 50‐GHz channels on ATMS and the Advanced Microwave Sounding Unit–A (AMSU‐A) means that more observations pass quality control, giving a neutral to slightly positive impact at higher latitudes in winter. Combining the two changes leads to small forecast benefits that are statistically significant up to day 3 at higher latitudes.

Diurnal Cycles of Synthetic Microwave Sounding Lower-Stratospheric Temperatures from Radio Occultation Observations, Reanalysis, and Model Simulations

Abstract An observationally based global climatology of the temperature diurnal cycle in the lower stratosphere is derived from 11 different satellites with global positioning system–radio occultation (GPS-RO) measurements from 2006 to 2020. Methods used in our analysis allow for accurate characterization of global stratospheric temperature diurnal cycles, even in the high latitudes where the diurnal signal is small but longer time-scale variability is large. A climatology of the synthetic Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) Temperature in the Lower Stratosphere (TLS) is presented to assess the accuracy of diurnal cycle climatologies for the MSU and AMSU TLS observations, which have traditionally been generated by model data. The TLS diurnal ranges are typically less than 0.4 K in all latitude bands and seasons investigated. It is shown that the diurnal range (maximum minus minimum temperature) of TLS is largest over Southern Hemisphere tropical land in the boreal winter season, indicating the important role of deep convection. The range, phase, and seasonality of the TLS diurnal cycle are generally well captured by the WACCM6 simulation and ERA5 dataset. We also present an observationally based diurnal cycle climatology of temperature profiles from 300 to 10 hPa for various latitude bands and seasons and compare the ERA5 data with the observations.

All-sky Data Assimilation of MWTS-2 and MWHS-2 in the Met Office Global NWP System

Microwave radiances from passive polar-orbiting radiometers have been, until recently, assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded. Recent system upgrades have seen the introduction of a scattering-permitting observation operator and the development of a variable observation error using both liquid and ice water paths as proxies of scattering-induced bias. Applied to the Fengyun 3 Microwave Temperature Sounder 2 (MWTS-2) and the Microwave Humidity Sounder 2 (MWHS-2), this methodology increases the data usage by up to 8% at 183 GHz. It also allows for the investigation into the assimilation of MWHS-2 118 GHz channels, sensitive to temperature and lower tropospheric humidity, but whose large sensitivity to ice cloud have prevented their use thus far. While the impact on the forecast is mostly neutral with small but significant short-range improvements, 0.3% in terms of root mean square error, for southern winds and low-level temperature, balanced by 0.2% degradations of short-range northern and tropical low-level temperature, benefits are observed in the background fit of independent instruments used in the system. The lower tropospheric temperature sounding Infrared Atmospheric Sounding Interferometer (IASI) channels see a reduction of the standard deviation in the background departure of up to 1.2%. The Advanced Microwave Sounding Unit A (AMSU-A) stratospheric sounding channels improve by up to 0.5% and the Microwave Humidity Sounder (MHS) humidity sounding channels improve by up to 0.4%.

Assessing precipitation extremes (1981–2018) and deep convective activity (2002–2018) in the Amazon region with CHIRPS and AMSU data

The frequency and spatial distributions of precipitation extremes (PEs) and deep convective clouds (DCC) across the Amazon region were assessed using satellite-derived data. For PEs, CHIRPS dataset for the period 1981–2018 were used to calculate a set of absolute, threshold, duration, and percentile-based threshold indices defined by the Expert Team on Climate Change Detection and Indices. DCC occurrence was assessed based on the Advanced Microwave Sounding Unit data for the period 2002–2018. In northern Amazon (north of $$5^\circ \hbox {S}$$ ) PEs and DCC are more frequent ( $$\ge 60\%$$ frequency) during February–June. Averaged trends over these months have shown increase in daily rainfall above 20 mm of near 3 days over the 1981–2018 period, and an increase of 2 consecutive wet days (P $$\ge 1\,\hbox {mm}$$ ) in the same period. South of $$5^\circ \hbox {S}$$ prevalence of PEs and DCC is largely observed during November–March ( $$\ge 60\%$$ frequency), whereas the longest persistence of dry days is observed during June–August. Though all PE trends point to an intensification of rainfall in November–March, only consecutive dry days in winter (JJA) and spring (SON) show significant trends, pointing to an increase of 7 days over the 38-yr winters. Rainfall extremes over the entire Amazon region were found to be moderate to strongly correlated with the mean vertically integrated moisture divergence, and in southern Amazon also to upper level divergence and upward vertical velocity. Increased frequency of DCC were found over the whole basin ( $$\sim 18\% \,\, \hbox {yr}^{-1}$$ ), in contrast to decreased convective overshooting (up to $$\sim 15.4\% \,\, \hbox {yr}^{-1}$$ ).

Temperature decadal trends, and their relation to diurnal variations in the lower thermosphere, stratosphere, and mesosphere, based on measurements from SABER on TIMED

Abstract. We have derived the behavior of decadal temperature trends over the 24 h of local time, based on zonal averages of SABER data, for the years 2012 to 2014, from 20 to 100 km, within 48∘ of the Equator. Similar results have not been available previously. We find that the temperature trends, based on zonal mean measurements at a fixed local time, can be different from those based on measurements made at a different fixed local time. The trends can vary significantly in local time, even from hour to hour. This agrees with some findings based on nighttime lidar measurements. This knowledge is relevant because the large majority of temperature measurements, especially in the stratosphere, are made by instruments on sun-synchronous operational satellites which measure at only one or two fixed local times, for the duration of their missions. In these cases, the zonal mean trends derived from various satellite data are tied to the specific local times at which each instrument samples the data, and the trends are then also biased by the local time. Consequently, care is needed in comparing trends based on various measurements with each other, unless the data are all measured at the same local time. Similar caution is needed when comparing with models, since the zonal means from 3D models reflect averages over both longitude and the 24 h of local time. Consideration is also needed in merging data from various sources to produce generic, continuous, longer-term records. Diurnal variations of temperature themselves, in the form of thermal tides, are well known and are due to absorption of solar radiation. We find that at least part of the reason that temperature trends are different for different local times is that the amplitudes and phases of the tides themselves follow trends over the same time span of the data. Many of the past efforts have focused on the temperature values with local time when merging data from various sources and on the effect of unintended satellite orbital drifts, which result in drifting local times at which the temperatures are measured. However, the effect of local time on trends has not been well researched. We also derive estimates of trends by simulating the drift of local time due to drifting orbits. Our comparisons with results found by others (Advanced Microwave Sounding Unit, AMSU; lidar) are favorable and informative. They may explain, at least in part, the bridge between results based on daytime AMSU data and nighttime lidar measurements. However, these examples do not form a pattern, and more comparisons and study are needed.

Advancing Satellite Precipitation Retrievals With Data Driven Approaches: Is Black Box Model Explainable?

AbstractSatellite‐based precipitation retrieval is an essential and long‐standing scientific problem. With an increase of observational satellite data, the advances of data‐driven approaches such as machine learning (ML)/deep learning (DL) are favored to deal with large data sets and potentially improve the accuracy of precipitation estimates. In this study, we took advantage of new technologies by wrapping up a ML/DL‐based model pipeline (LinkNet segmentation + tree ensemble). This approach is applied to the Advanced Microwave Sounding Unit (AMSU) on National Oceanic and Atmospheric Administration 18 and 19 flight, and compared with the MultiRadar MultiSensor. Four simulations were configured to examine the performance gain by incorporating three components: (1) precipitation identification, (2) nonlocal features, and (3) precipitation classification. More importantly, we examined the interpretability of the “black box” model to get a better understanding of the underlying physical connections. First, the results by this model pipeline suggest the advantages of the ML model by reducing the systematic error and instantaneous error to a factor of two. Second, identifying precipitation pixels helps to reduce the systematic error by 130%, and predicting precipitation classification benefits improved correlations by 32%. Last, channels at higher frequencies (beyond 150 GHz) are favored to identify precipitation regions, and also channels at 89 and 150 GHz are ranked as the two most important features to precipitation retrieval. This study explores the potentials of AMSU precipitation estimates with ML algorithms and provides means of interpreting the models to facilitate the better prediction of precipitation.

Assessment of Sampling Sufficiency for Low-Cost Satellite Missions: Application to PREFIRE

AbstractThe Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will, for the first time, systematically document the far-infrared (15–54 µm) spectral region from space. The environmental sampling characteristics of the PREFIRE CubeSats, defined in terms of surface temperature (Tsfc) and column water vapor (CWV) are evaluated for a range of possible orbit scenarios for both clear-sky and all-sky conditions over a variety of surface types (land, ocean, sea ice, snow, glacier ice) at both poles. Using NASA Aqua’s Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) retrievals to define the climatological ranges of Tsfc and CWV, the fraction of environmental regimes observed by distinct PREFIRE configurations are evaluated. The sampling rates within any single year for two-orbit CubeSat launches spanning both polar regions are ~75% for clear-sky and ~85% for all-sky compared to the AIRS/AMSU climatology. Decreasing mission duration from 12 to 3 months decreases sampling much more (10%–20%) than decreasing the swath width from 15 to 8 footprints (6%–9%). For a single CubeSat launch, a 98° orbital inclination provides slightly better sampling than either 93° or 103°. For a two-orbit CubeSat launch, a combination of 93° + 98° is somewhat preferable to 103° + 98°. Finally, a 50% data loss rate simulated by dropping out every other orbit leads to only a modest 7%–8% reduction in sampling from full data coverage. This statistical analysis demonstrates that low-cost platforms could offer similar coverage as present-day flagship missions for sampling wide-ranging Tsfc and CWV states over polar regions.

Impact of the One-Stream Cloud Detection Method on the Assimilation of AMSU-A Data in GRAPES

Clouds affect the assimilation of microwave data from satellites and therefore the detection of clouds is important under both clear sky and cloudy conditions. We introduce a new cloud detection method based on the assimilation of data from the advanced microwave sounder unit A (AMSU-A) and the microwave humidity sounder (MHS) into the global and regional assimilation and prediction system (GRAPES) and use forecast experiments to evaluate its impact. The new cloud detection method can retain more observational data than the current method in GRAPES, thereby improving the assimilation of AMSU-A data. Verification of the method showed that, by improving the forecast of the lower-level air temperature and geopotential height, the new cloud detection method improved the forecast of the track of two typhoons. The forecast of a large-scale weather system in GRAPES was also improved by the new method in the later period of the forecast.

A new climate data record of upper-tropospheric humidity from microwave observations

We generated a new Climate Data Record (CDR) of Upper Tropospheric Humidity (UTH) based on observations from the microwave sounders Special Sensor Microwave Temperature - 2 (SSMT-2), Advanced Microwave Sounding Unit - B (AMSU-B) and Microwave Humidity Sounder (MHS). The data record covers the time period between 1994 and 2017 and provides monthly mean 183.31 ± 1 GHz brightness temperatures and derived UTH along with estimates of measurement uncertainty on a 1° × 1° latitude-longitude grid covering the tropical region (30° S to 30° N). For the UTH retrieval we introduce a new definition of UTH. Forgoing the use of the humidity Jacobian as a weighting function, it is easier to apply than the traditional definition without compromising the retrieval accuracy. The same definition can be used to derive UTH from infrared observations, allowing for a more synergistic use of infrared and microwave UTH in the future. The new UTH CDR is validated against an existing UTH data record.

Diurnal Variation in Cloud Liquid Water Path Derived from Five Cross-Track Microwave Radiometers Onboard Polar-Orbiting Satellites

The Advanced Microwave Sounding Unit (AMSU)-A/Advanced Technology Microwave Sounder (ATMS) onboard the National Oceanic Atmospheric Administration (NOAA)-18/-19, MetOp-A/-B, and Suomi National Polar-orbiting Partnership satellites provide global observations of the cloud Liquid Water Path (LWP) almost 10 times a day. This study explores the possibility of capturing the diurnal cycle of the LWP. An inter-satellite cross-calibration is first carried out using a double-difference method. A remapping is then used to obtain the AMSU-A-like LWP to account for beam shape discrepancies between the ATMS and AMSU-A. We finally examine the diurnal cycle of the LWP over the Southeast Pacific Ocean using the ATMS and AMSU-A data from the five satellites mentioned above. Results show that the remapped ATMS results agree well with the AMSU-A results at the same local time over a stratocumulus region. LWP retrievals from multiple satellite cross-track microwave radiometers can well reproduce the diurnal variation characteristics of LWP in 2015 over the East Pacific Ocean, including the seasonal variation of the diurnal variation. This study presents the first step toward merging LWP data from all ATMS and AMSU-A radiometers and will be of interest to many researchers studying LWP-related weather and climate changes, especially considering the possible loss of higher-resolution microwave-frequency conical-scanning sensors in the coming years.

Rapid Intensification of Tropical Cyclones Observed by AMSU Satellites

AbstractThis study examines the vertical structures of temperature and convection associated with rapid intensification of tropical cyclones using collocated Advanced Microwave Sounding Unit (AMSU) and HURSAT‐B1 satellite observations for 2003–2015. We used AMSU measurements from six satellites: AQUA, MetOp, NOAA‐15, NOAA‐16, NOAA‐17, and NOAA‐18. Eighteen thousand three hundred sixty nine collocated satellite overpasses of tropical cyclones were obtained. Vertical structures of temperature and convection are analyzed for different categories of tropical cyclone intensity, for the composite lifecycles of tropical cyclones in different ocean basins, and for the rapid intensification events. Tropical cyclones reaching hurricane intensity are generally associated with warm core above eyewall cloud top extending into the stratosphere, suggesting the existence of warm stratospheric downdrafts penetrating into the central eye. Rapid intensification of tropical cyclones are generally associated with strong warming rate above eyewall cloud top that extends into the stratosphere, suggesting that stratospheric downdrafts are involved in rapid intensification of tropical cyclones.

Tropical cyclones over the Arabian Sea and Bay of Bengal tracked by Megha-Tropiques SAPHIR during 2011–2018

Monitoring of tropical cyclones (TCs) using the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) sounder on-board the Megha-Tropiques satellite is attempted on a qualitative basis. The sounder with a high resolution of 10 km at nadir, combined with its high temporal observation ability, 4–6 times a day, and with six channels at 183.31 ± 11.0 GHz, is used for tracking the cyclones. The study has been performed by applying SAPHIR brightness temperature datasets to the cyclonic regions. In this study, 25 TCs from 2011 to 2018 in the Arabian Sea and the Bay of Bengal over the North Indian Ocean have been observed. A comparison of six channels of SAPHIR shows the clear variations of the eye of the cyclone under various conditions. Furthermore, the positional variations obtained by multiple linear regression models are used to observe the evolution of the cyclone storm from its genesis to dissipation/landfall for all the 25 cyclones. The location accuracy is found to be 0.2–0.3\(^{\circ }\), as observed from the SAPHIR dataset that agrees reasonably well with the India Meteorological Department dataset and Advanced Microwave Sounding Unit sounder dataset in cyclone tracking. This study attempts at using the unique features of high temporal resolution, good spatial resolution and more channels and is expected to complement other methods of cyclone tracking.

A 13-Year Global Climatology of Tropical Cyclone Warm-Core Structures from AIRS Data

Abstract There is uncertainty as to whether the typical warm-core structure of tropical cyclones (TCs) is featured as an upper-level warm core or not. It has been hypothesized that data from the satellite-borne Advanced Microwave Sounding Unit (AMSU) are inadequate to resolve a realistic TC warm-core structure. This study first evaluates 13 years of Atmospheric Infrared Sounder (AIRS) temperature retrieval against recent dropsonde measurements in TCs. AIRS can resolve the TC warm-core structure well, comparable to the dropsonde observations, although the AMSU-A retrievals fail to do so. Using 13-yr AIRS data in global TCs, a global climatology of the TC warm-core structure is generated in this study. The typical warm-core height is at the upper level around 300–400 hPa for all TCs and increases with TC intensity: 400 hPa (~8 km) for tropical storms, 300 hPa (~10 km) for category 1–3 hurricanes, 250–300 hPa (~10–11 km) for category 4 hurricanes, and 150 hPa (~14 km) for category 5 hurricanes. The range of warm-core height varies with TC intensity as well. A strong correlation between TC intensity and warm-core strength is found. A weaker but still significant correlation between TC intensity and warm-core height is also found.

The Atmospheric Infrared Sounder Obs4MIPs Version 2 Data Set

AbstractThe Atmospheric Infrared Sounder (AIRS) Obs4MIPs (Observations for Model Intercomparison Projects) Version 2 data set includes monthly mean tropospheric air temperature, specific humidity, and relative humidity for each calendar month from September 2002 to September 2016, on a global 1° × 1° latitude‐longitude spatial grid and on the Coupled Model Intercomparison Project eight mandatory vertical pressure levels from 1,000 to 300 hPa. It also includes standard error and number of observations, for an estimate of AIRS data retrieval error and sampling uncertainty. Three new technical notes describe the data set. This data set is designed for Coupled Model Intercomparison Project climate model evaluation and has been published at Earth System Grid Federation data centers since April 2018. It adds new monthly mean tropospheric relative humidity data to Obs4MIPs and updates and extends the monthly mean tropospheric air temperature and specific humidity data in AIRS Obs4MIPs Version 1 data set. The data source for this data set is the AIRS Version 6 Level 3 standard monthly mean air temperature, specific humidity, and relative humidity data products in the “TqJoint” grids from the AIRS and Advanced Microwave Sounding Unit A combined physical retrievals. This paper documents this data set in terms of motivation for this data set, data description, data origin and processing procedures, major improvements from the previous version, and caveats for its use in climate model evaluation.