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Biases in Total Precipitable Water Vapor Climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer

We examine differences in total precipitable water vapor (PWV) from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Scanning Radiometer (AMSR-E) experiments sharing the Aqua spacecraft platform. Both systems provide estimates of PWV over water surfaces. We compare AIRS and AMSR-E PWV to constrain AIRS retrieval uncertainties as functions of AIRS retrieved infrared cloud fraction. PWV differences between the two instruments vary only weakly with infrared cloud fraction up to about 70%. Maps of AIRS-AMSR-E PWV differences vary with location and season. Observational biases, when both instruments observe identical scenes, are generally less than 5%. Exceptions are in cold air outbreaks where AIRS is biased moist by 10-20% or 10-60% (depending on retrieval processing) and at high latitudes in winter where AIRS is dry by 5-10%. Sampling biases, from different sampling characteristics of AIRS and AMSR-E, vary in sign and magnitude. AIRS sampling is dry by up to 30% in most high-latitude regions but moist by 5-15% in subtropical stratus cloud belts. Over the northwest Pacific, AIRS samples conditions more moist than AMSR-E by a much as 60%. We hypothesize that both wet and dry sampling biases are due to the effects of clouds on the AIRS retrieval methodology. The sign and magnitude of these biases depend upon the types of cloud present and on the relationship between clouds and PWV. These results for PWV imply that climatologies of height-resolved water vapor from AIRS must take into consideration local meteorological processes affecting AIRS sampling.

Atmospheric Infrared Sounder (AIRS)↗

NPP ATMS Snowfall Rate Product

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2015). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. NCEP CMORPH analysis has shown that integration of ATMS SFR has improved the performance of CMORPH‐Snow. The ATMS SFR product is also being assessed at several NWS Weather Forecast Offices for its usefulness in weather forecast.

Forecasting↗

Snowfall Rate Retrieval using NPP ATMS Passive Microwave Measurements

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2014). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The ATMS SFR product is validated against radar and gauge snowfall data and shows that the ATMS algorithm outperforms the AMSU/MHS SFR.

Meng, Huan↗

Snowfall Rate Retrieval Using Passive Microwave Measurements and Its Applications in Weather Forecast and Hydrology

(AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has also been developed. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. It employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derives the probability of snowfall. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model. A method adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The SFR products are being used mainly in two communities: hydrology and weather forecast. Global blended precipitation products traditionally do not include snowfall derived from satellites because such products were not available operationally in the past. The ATMS and AMSU/MHS SFR now provide the winter precipitation information for these blended precipitation products. Weather forecasters mainly rely on radar and station observations for snowfall forecast. The SFR products can fill in gaps where no conventional snowfall data are available to forecasters. The products can also be used to confirm radar and gauge snowfall data and increase forecasters' confidence in their prediction.

Meng, Huan↗

TPSAS-NF1676L-10574-DND

The Infrared Atmospheric Sounding Interferometer (IASI) aboard of MetOP-A was successfully launched on 19 October 2006 and has been providing excellent data for more than 3 years. The IASI spectra can be converted into proxy data for the NPOESS Crosstrack Infrared Sounder (CrIS) through a rigorous mathematical transformation by taking into account of instrument characteristics of both the IASI and the CrIS. The 15-channel AMSU temperature sounder, and the 5-channel and Microwave Humidity Sounder (MHS) aboard of MetOP-A can be used to generate proxy data for the NPOESS Advanced Technology Mircrowave Sounder (ATMS). The CrIS and ATMS make up the Cross-track Infrared and Microwave Sounder Suite (CrIMSS). CrIMSS will primarily provide global temperature, moisture, and pressure profiles. We will describe the method used in generating the proxy data and show results of using the proxy data for evaluation of the NPOESS CrIMSS Environmental Data Record (EDR) retrieval algorithm.

Xu Liu↗

TPSAS-NF1676L-10898-DND

The Infrared Atmospheric Sounding Interferometer (IASI) aboard of MetOP-A was successfully launched on 19 October 2006 and has been providing excellent data for more than 3 years. The IASI spectra can be converted into proxy data for the NPOESS Crosstrack Infrared Sounder (CrIS) through a rigorous mathematical transformation by taking into account of instrument characteristics of both the IASI and the CrIS. The 15-channel AMSU temperature sounder, and the 5-channel and Microwave Humidity Sounder (MHS) aboard of MetOP-A can be used to generate proxy data for the NPOESS Advanced Technology Mircrowave Sounder (ATMS). The CrIS and ATMS make up the Cross-track Infrared and Microwave Sounder Suite (CrIMSS). CrIMSS will primarily provide global temperature, moisture, and pressure profiles. We will describe the method used in generating the proxy data and show results of using the proxy data for evaluation of the NPOESS CrIMSS Environmental Data Record (EDR) retrieval algorithm.

Xu Liu↗

Global Precipitation Measurement (GPM) Mission: Overview and Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. NASA and JAXA will deploy a Core Observatory in 2014 to serve as a reference satellite to unify precipitation measurements from the constellation of sensors. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1 satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian MeghaTropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), and (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites. Data from Chinese and Russian microwave radiometers may also become available through international collaboration under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). The current generation of global rainfall products combines observations from a network of uncoordinated satellite missions using a variety of merging techniques. GPM will provide "next-generation" precipitation products characterized by: (1) more accurate instantaneous precipitation estimate (especially for light rain and cold-season solid precipitation), (2) intercalibrated microwave brightness temperatures from constellation radiometers within a consistent framework, and (3) unified precipitation retrievals from constellation radiometers using a common a priori hydrometeor database constrained by combined radar/radiometer measurements provided by the GPM Core Observatory. GPM is a science mission with integrated applications goals. GPM will provide a key measurement to improve understanding of global water cycle variability and freshwater availability in a changing climate. The DPR and GMI measurements will offer insights into 3-dimensional structures of hurricanes and midlatitude storms, microphysical properties of precipitating particles, and latent heat associated with precipitation processes. The GPM mission will also make data available in near realtime (within 3 hours of observations) forocietal applications ranging from position fixes of storm centers, numerical weather prediction, flood forecasting, freshwater management, landslide warning, crop prediction, to tracking of water-borne diseases. An overview of the GPM mission design, retrieval strategy, ground validation activities, and international science collaboration will be presented.

Hou, Arthur Y.↗

Visualization, Analysis and Subsetting Tools for EOS Aura Data Products in HDF-EOS5

Aura data products are among the first to use the new version 5 of the Hierarchical Data Format for the Earth Observing System, or HDF-EOS5. This presentation discusses the common HDF-EOS5 file layout that is adopted for most of the EOS Aura standard data products. Details of the various tools that can be used to access, visualize and subset these data will also be provided. Aura, the NASA Earth Observing System's atmospheric chemistry mission, was successfully launched July 15, 2004. The Aura spacecraft includes four instruments: the High Resolution Dynamics Limb Sounder (HIRDLS), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Tropospheric Emission Spectrometer (TES). Data from the HIRDLS, MLS and OMI will be archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC), while TES data will be archived at the NASA Langley Research Center DAAC. For more information see http://daac.gsfc.nasa.gov/.

Johnson, J.↗

Mesospheric Temperature Inversion Layers: Recent Observations from UARS ISAMS and MLS

This paper presents an observational study of the mesospheric temperature inversion layer with Upper Atmosphere Research Satellite (UARS) Improved Stratospheric and Mesospheric Sounder (ISAMS) and Microwave Limb Sounder (MLS). The satellite data show that the temperature inversion layer can be generated from deep penetration of planetary waves in the mesosphere.

mesospheric temperature inversion layers UARS ISAM↗

Land and Atmosphere Near-Real-Time Capability for Earth Observing System

The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.

Murphy, Kevin J.↗

Implementation of the Land, Atmosphere Near Real-Time Capability for EOS (LANCE)

The past decade has seen a rapid increase in availability and usage of near real-time data from satellite sensors. Applications have demonstrated the utility of timely data in a number of areas ranging from numerical weather prediction and forecasting, to monitoring of natural hazards, disaster relief, agriculture and homeland security. As applications mature, the need to transition from prototypes to operational capabilities presents an opportunity to improve current near real-time systems and inform future capabilities. This paper presents NASA s effort to implement a near real-time capability for land and atmosphere data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments on the Terra, Aqua, and Aura satellites. Index Terms- Real time systems, Satellite applications

Michael, Karen↗

Learning from GES DISC's MLS and OMI Data Users: Metrics Matter

It has been over 15 years since Aura research satellite launched in 2004 to observe the Earth's ozone layer, air quality, and climate from four different instruments - the High Resolution Dynamics Limb Sounder (HIRDLS), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Tropospheric Emission Spectrometer (TES). Observations from the Aura mission have established a concrete understanding of the changing chemistry of our atmosphere.The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the official archive and distribution center for the HIRDLS, MLS, and OMI instruments. This presentation will report metrics of data usage and services on these instruments. Key to GES DISC's mission to provide better data support is gaining a better understanding of our users' needs and behaviors as they discover, access and utilize these data. We will summarize the users' needs from these instruments based on user inquiry information collected over the Aura mission lifetime and present findings from this ensemble metrics.

Metrics↗

Precipitation Estimation Using Combined Radar/Radiometer Measurements Within the GPM Framework

The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. The GPM mission centers upon the deployment of a Core Observatory in a 65o non-Sun-synchronous orbit to serve as a physics observatory and a transfer standard for intersatellite calibration of constellation radiometers. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles needed for improving precipitation retrievals from microwave sensors. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1 satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian Megha- Tropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), and (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites. Data from Chinese and Russian microwave radiometers may also become available through international collaboration under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). The current generation of global rainfall products combines observations from a network of uncoordinated satellite missions using a variety of merging techniques. GPM will provide next-generation precipitation products characterized by: (1) more accurate instantaneous precipitation estimate (especially for light rain and cold-season solid precipitation), (2) intercalibrated microwave brightness temperatures from constellation radiometers within a consistent framework, and (3) unified precipitation retrievals from constellation radiometers using a common a priori hydrometeor database constrained by combined radar/radiometer measurements provided by the GPM Core Observatory.

Hou, Arthur↗

The Global Precipitation Measurement (GPM) Mission: Overview and U.S. Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. Building upon the success of the U.S.-Japan Tropical Rainfall Measuring Mission (TRMM), the National Aeronautics and Space Administration (NASA) of the United States and the Japan Aerospace and Exploration Agency (JAXA) will deploy in 2013 a GPM "Core" satellite carrying a KulKa-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Imager (GMI) to establish a new reference standard for precipitation measurements from space. The combined active/passive sensor measurements will also be used to provide common database for precipitation retrievals from constellation sensors. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer- 2 (AMSR-2) on the GCOM-Wl satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian Megha-Tropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites, and (8) a microwave imager under planning for the Defense Weather Satellite System (DWSS).

Hou, Arthur Y.↗

Second Time-Resolved Observations of Precipitation Structure and Storm Intensity With a Constellation of Smallsats (TROPICS) Mission Applications Workshop

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of state-of-the-science observing platforms that will measure temperature and humidity soundings and precipitation with spatial resolution comparable to current operational passive microwave (PMW) sounders but with unprecedented temporal resolution (Mission Website).1 TROPICS is a cost-capped ($30.2 million), Venture-class mission funded by the NASA Earth Science Division (ESD) and led by Principal Investigator Dr. William Blackwell from the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). The mission consists of a constellation of six, three-unit (3U) CubeSats (approximately 10×10×34 cm), each hosting a 12-channel PMW spectrometer based on the Micro-sized Microwave Atmospheric Satellite-2 (MicroMAS-2) developed at MIT LL, but with a substantially improved design. TROPICS will provide imagery near 91 and 205 GHz, temperature sounding near 118 GHz, and moisture sounding near 183 GHz. Spatial resolution at nadir will be around 27 km for temperature and 17 km for moisture and precipitation with a swath width of approximately 2,000 km from a 550-km orbit altitude. Both the spatial resolution and swath width are similar to the Advanced Technology Microwave Sounder (ATMS) that is being flown as part of the Suomi National Polar-orbiting Partnership (SNPP) and National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS). In addition, TROPICS meets many of the requirements outlined in the 2007 Decadal Survey for the Precision and All-Weather Tempera-ture and Humidity (PATH) mission, which was originally envisioned as a microwave instrument in geostationary orbit. TROPICS enables temporal resolution approaching that of geostationary orbit but at a much lower cost, demonstrating a technology that could impact the design of future Earth-observing missions. The satellites for the TROPICS mission were delivered to NASA in 2019 for launches planned in the 2021–2022 timeframe. The primary mission objective of TROPICS is to relate temperature, humidity, and precipitation structure to the evolution of tropical cyclone (TC) intensity.

remote sensing↗

The Atmospheric Infrared Sounder on EOS

Recent breakthroughs in infrared detector array and cryocooler technology have made it possible to convert the concepts of optimum, passive, infrared sounding to a practical satellite-borne instrument.

Atmospheric Infrared Sounder Microwave Humidity So↗

The Effect of the Saharan Air Layer on the Formation of Hurricane Isabel (2003) Simulated with AIRS Data

The crucial physics of how the atmosphere really accomplishes the tropical cyclogenesis process is still poorly understood. The presence of the Saharan Air Layer (SAL), an elevated mixed layer of warm and dry air that extends from Africa to the tropical Atlantic and contains a substantial amount of mineral dust, adds more complexity to the tropical cyclogenesis process in the Atlantic basin. The impact of the SAL on tropical cyclogenesis is still uncertain. Karyampudi and Carlson (1988) conclude that a strong SAL can potentially aid tropical cyclone development while Dunion and Velden (2004) argue that the SAL generally inhibits tropical cyclogenesis and intensification. Advancing our understanding of the physical mechanisms of tropical cyclogenesis and the associated roles of the SAL strongly depends on the improvement in the observations over the data-sparse ocean areas. After the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the microwave Humidity Sounder of Brazil (HSB) were launched with the NASA Aqua satellite in 2002, new data products retrieved from the AIRS suite became available for studying the effect of the warm, dry air mass associated with the SAL (referred to as the thermodynamic effect). The vertical profiles of the AIRS retrieved temperature and humidity provide an unprecedented opportunity to examine the thermodynamic effect of the SAL. The observational data can be analyzed and assimilated into numerical models, in which the model thermodynamic state is allowed to relax to the observed state from AIRS data. The objective of this study is to numerically demonstrate that the thermodynamic effect of the SAL on the formation of Hurricane Isabel (2003) can be largely simulated through nudging of the AIRS data.

Wu, iguang↗

The Vertical Structure of Relative Humidity and Ozone in the Tropical Upper Troposphere: Intercomparisons Among In Situ Observations, A-Train Measurements and Large-Scale Models

In situ measurements in the tropics have shown that in regions of active convection, relative humidity with respect to ice in the upper troposphere is typically close to saturation on average, and supersaturations greater than 20% are not uncommon. Balloon soundings with the cryogenic frost point hygrometer (CFH) at Costa Rica during northern summer, for example, show this tendency to be strongest between 11 and 15.5 km (345-360 K potential temperature, or approximately 250-120 hPa). this is the altitude range of deep convective detrainment. Additionally, simultaneous ozonesonde measurements show that stratospheric air (O3 greater than 150 ppbv) can be found as low as approximately 14 km (350 K/150 hPa). In contrast, results from northern winter show a much drier upper troposphere and little penetration of stratospheric air below the tropopause at 17.5 km (approximately 383 K). We show that these results are consistent with in situ measurements from the Measurement of Ozone and water vapor by Airbus In-service airCraft (MOZAIC) program which samples a wider, though still limited, range of tropical locations. To generalize to the tropics as a whole, we compare our insitu results to data from two A-Train satellite instruments, the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS) on the Aqua and Aura satellites respectively. Finally, we examine the vertical structure of water vapor, relative humidity and ozone in the NASA Goddard MERRA analysis, an assimilation dataset, and a new version of the GEOS CCM, a free-running chemistry-climate model. We demonstrate that conditional probability distributions of relative humidity and ozone are a sensitive diagnostic for assessing the representation of deep convection and upper troposphere/lower stratosphere mixing processes in large-scale analyses and climate models.

Selkirk, Henry B.↗