GPSRO and GNSS in the Context of NASA s Earth Science Program

Transcription

1 GPSRO and GNSS in the Context of NASA s Earth Science Program Dr. Jack Kaye* Associate Director for Research Earth Science Division Science Mission Directorate NASA Headquarters * This talk is prepared with input and assistance from numerous colleagues at NASA HQ, NASA centers, and the broader research community! March 9,

2 Earth in Daytime from S-NPP VIIRS 2

3 Earth at Night from S-NPP VIIRS ting_earth_360p.mp4 3

4 Overview of Talk How NASA Studies the Earth with Remote Sensing What We re Seeing and Learning GPSRO and NASA What We ll be Doing in the Future Conclusion

5 How is Remote Sensing Done? Space-based remote sensors allow us to observe & quantify Earth s environments in regions of the electromagnetic spectrum to which our eyes are not sensitive Remote Sensing can be based on signals that nature gives us or signals that we create ourselves either on the detecting spacecraft (radar, lidar) or from other spacecraft

6 Formulation Implementation Primary Ops Extended Ops Sentinel-6A/B Earth Science Instruments on ISS: RapidScat, CATS, LIS, SAGE III (on ISS), TSIS-1, OCO-3, ECOSTRESS, GEDI, CLARREO-PF Science Missions and Instruments ISS CYGNSS SORCE, TCTE (NOAA) ICESat-2 TEMPO JPSS-2 (NOAA) RBI, OMPS-Limb GRACE-FO (2) NISTAR, EPIC (NOAA S DSCOVR) QuikSCAT NI-SAR SWOT PACE Landsat 9 Suomi NPP (NOAA) SMAP Aqua Terra Landsat 7 (USGS) EO-1 Landsat 8 (USGS) GPM CloudSat CALIPS O Aura OCO-2 GRACE (2) OSTM/Jason 2 (NOAA)

7 NASA Earth Science Satellite Constellation 2014

8 SMAP Satllite Launch 1/31/15 8

9 Formulation Implementation Primary Ops Extended Ops Sentinel-6A/B Earth Science Instruments on ISS: RapidScat, CATS, LIS, SAGE III (on ISS), TSIS-1, OCO-3, ECOSTRESS, GEDI, CLARREO-PF Science Missions and Instruments ISS CYGNSS SORCE, TCTE (NOAA) ICESat-2 TEMPO JPSS-2 (NOAA) RBI, OMPS-Limb GRACE-FO (2) NISTAR, EPIC (NOAA S DSCOVR) QuikSCAT NI-SAR SWOT PACE Landsat 9 Suomi NPP (NOAA) SMAP Aqua Terra Landsat 7 (USGS) EO-1 Landsat 8 (USGS) GPM CloudSat CALIPS O Aura OCO-2 GRACE (2) OSTM/Jason 2 (NOAA)

10 A-Train

11 Atmospheric Observations from A-Train: Partial List Parameter Mission Instrument T Profile Aqua AIRS Aura MLS H 2 O Profile Aqua AIRS Aura MLS Cloud Profile CloudSat Radar CALIPSO CALIOP Aerosol Distributions Aqua MODIS Aura OMI CALIPSO CALIOP Ozone Aura OMI CO 2 Distributions OCO-2 OCO-2 Aqua AIRS Other Constituents Aura TES Aura MLS Aura OMI Aqua AIRS 11

12 Overview of Talk How NASA Studies the Earth with Remote Sensing What We re Seeing and Learning GPSRO and NASA What We ll be Doing in the Future Conclusion

13 Satellite-derived sea surface temperature anomalies (departure from normal conditions) in November near the peak of the 1997 & 2015 El Niño The 2015 event has larger zonal extent of warming in the equatorial Pacific, and is associated with much more extensive warming off North America. Nov Image credit: PO.DAAC, NASA JPL Nov. 2015

14 GPM IMERG Development 14

15 OCO-2 A Quick Look at the First 13 Months of Operations Provided by David Crisp, NASA/JPL

16 GRACE Observations of Time Evolution of Greenland Ice Mass Distributions 16

17 Long-Term Trends Stratospheric Ozone Trends Long-Term Trends in Stratospheric Aerosols Global Sea Level Trend (mm) (and spatial variability) Arctic Sea Ice Extent Changes 17

18 NASA Aura Nitrogen Dioxide (NO 2 ) data NO 2 is a pollutant that leads to the formation of unhealthy levels of ozone. Air quality agencies use NASA satellite data to track US pollution levels. Recent efforts to control NO 2 from power plants and cars are working! NO 2 pollution has decreased 30-40% in the last decade & ozone by 14%.

19 OMI Observations of NO 2 Show Impacts of Pollution Controls A~40% decrease in Japanese cities furthest away from China, but much less for cities closest. Local emission controls led to decreases for Beijing & Shanghai, but likely damped by pollution import. Impact of substantial pollution control efforts in Seoul & other Korean cities likely damped. Beijing -10% Tianjin +22% Seoul -17% Change in NO 2 Levels since 2005 CHINA Nanjing +14% Qingdao +23% Shanghai -32% SOUTH KOREA JAPAN Osaka -39% Fukuoka -20% Nagasaki -1% Decrease in NO 2 Pollution Increase in NO 2 Pollution

20 Eastern China Emissions Offset 43% of the Expected Reduction in Mid- Tropospheric Ozone over the Western US from Verstraeten et al., Nature Geosci., 2015 Over the past decade, China has undergone rapid population growth and industrialization. At the same time, the US experienced an economic recession and implemented increasingly strict emissions controls. What do satellite measurements tell us about how these differences in development and policy have manifested in terms of changes in tropospheric ozone, a harmful pollutant and potent greenhouse gas? Aura s Tropospheric Emission Spectrometer (TES): 7% Increase in midtropospheric ozone Explains 50% of the ozone increase We combine Aura measurements with a model to quantify and attribute observed ozone changes to: Regional emissions; Long-range transport; and downward transport from the stratosphere. We find that natural stratospheric variability played a surprisingly large role in tropospheric ozone trends and that Chinese emissions offset a large portion of the reduction in mid-tropospheric ozone that should have occurred over the Western US due to emission reduction policies. The absolute impact of Chinese emissions has thus far been small, but its future trajectory is highly uncertain. Aura s Microwave Limb Sounder: Temporary increase in downward transport from the stratosphere partly due to El Nino. Offset 57% of expected ozone decrease TES: No change in mid-tropospheric ozone OMI: 21% increase in NO x emissions. Explains 50% of the ozone increase. Model-derived increases in surface ozone are ~2x mid-tropospheric ozone changes Transport from China offset 43% of expected decrease OMI: 21% decrease in NO x emissions. Should have given a 2% decrease in ozone Model-derived impact of Chinese emissions at the surface <1/2 their impact in the mid-troposphere

21 Overview of Talk How NASA Studies the Earth with Remote Sensing What We re Seeing and Learning GPSRO and NASA What We ll be Doing in the Future Conclusion

22 NASA and GPSRO (and GNSS ) NASA s Involvement in GPSRO Supporting Analysis and Interpretation of Data from GPSRO observations (esp. JPL, COSMIC) Advancing technology for GPSRO (BlackJack, TRiG) Providing instruments for partner satellites Operating Missions that use GPSRO (e.g., GRACE) Providing competitive opportunities for community participation (GNSS Remote Sensing Science Team) Intercomparing GPSRO and complementary data Support for laboratory measurements of refractivity Involvemernt in CGMS IROWG NASA s Involvement in non-gpsro GNSS-related activity Flying CYGNSS satellite using GNSS Reflection Supporting other studies on possibilities for GNSS reflection Supporting ground-based GPS network for application to a broad range of environmental issues, precise positioning, the TRF, and s/c navigation Advancing (developing and testing) technology based on GNSS approach 22

23 2015 GNSS Remote Sensing Science Team 10 new projects for$6.8 over four years GPSRO across a range of topics including: 1. Diagnosing fine-scale variability in the dynamics of the upper troposphere and stratosphere 2. Algorithm development for investigating ionospheric disturbances 3. Vertical profiling of the planetary boundary layer 4. Investigating precipitation effects on GNSS-RO signals 5. Adding capabilities to GIPSY-OASIS software for GNSSRO and reflections analysis 6. Utilizing GNSS-RO over Greenland and Antarctica to improve corrections for ICESat/ICESat-2 observations GPS reflection for: 7. Advancing novel methods to remotely sense water and ice on freshwater surfaces 8. Assimilation of GNSS-R Delay-Doppler Maps into Hurricane Models 9. Studying estuary hydrodynamics Coupling GNSS with GRACE 10.Improving spatial resolution of hydrologic and cryospheric mass change

24 RO Synergy Across NASA Research Making Earth Science Data Records for use in Research Environments (MEASURES) A Multi-Sensor Water Vapor, Temperature and Cloud Climate Data Record, Eric Fetzer PI GPS RO used to estimate water vapor in very cloudy conditions GPS RO complementary to observations affected by hydrometeors (AIRS, MLS and AMSR-E) Cloud state observations from Aqua MODIS matched to GPS RO water vapor estimates over several years A Data Record of the Cloudy Boundary Layer, Joao Teixeira, PI Boundary layer height from GPS RO Combined with cloud/radiation/water path observations from Calipso, MISR, MODIS, CERES Remote Sensing Theory Advanced Retrieval of Cloudy Boundary Layer with MODIS, AMSR-E and GPS Radio Occultation s Direct and Reflected Measurements, Feiqin Xie, PI (TAMCC) High-accuracy boundary layer refractivity or moisture profiles through introduction of inversion constraints from other sensors (e.g., MODIS cloud top temperature) AJM/ JPL

25 Dynamic variations in tropical temperature measured by GPS RO Large changes in tropical variance derived from high resolution GPS data, linked to variations in tropical deep convection, background winds and stability QBO winds (contour) GPS zonal temp variance 10 o N-S ❸ increased variance > 30 km tropopause ~ 17 km ❶ annual maximum near the tropopause tied to deep convection W. Randel, T. Birner, J. Kim et al. ❷ asymmetry between easterly and westerly shear zones suggest asymmetric wave source spectra Kelvin waves and gravity waves

26 Gravity Waves concurrently observed by COSMIC and GRUAN Tae-Kwon Wee, UCAR High-resolution (1-s sampling; ~5 m) GRUAN (GCOS Reference Upper-Air Network) radiosonde data collocated with COSMIC soundings (< 50km and 30 min.) are used Independent two observing systems show a remarkable agreement in the small-scale temperature structure, confirming each other s strength Such high-quality RO soundings along with upcoming increase in the number (e.g., TRiG) will revolutionize stratospheric research Variational RO data processing (Wee and Kuo, 2013; 2014, JGR) show a significant improvement over the standard processing The improvement is due to 1) effective separation of signal components from noises based on signals inter-frequency coherency and 2) precise correction of ionospheric effects via the variational method

27 PBL height climatology at 1 deg x 1 deg resolution from ~ 10 years of GPS RO profiles from COSMIC and TerraSAR-X Detailed picture of global PBL height, clearly showing the extent of the shallow PBLs in subtropical Eastern oceans, deep PBLs over the subtropical deserts, and strong variability over the ITCZ and SPCZ. Mean Standard Deviation [km] [km] Chi Ao, JPL

28 Hurricane intensity estimation: The GPS perspective GPS-based vs National Hurricane Center intensity First estimates of hurricane intensities (maximum wind speed) from GPS radio occultations (GPSRO) and the Wong and Emanuel [2007] Eyewall hurricane Moat model. GPSRO-derived hurricane intensities show 0.9 linear correlation with respect to NHC intensities with a small bias. GPSRO shows great potential in augmenting current hurricane datasets, with possible applications to the initial vortex parameterization and intensity forecasting. Accuracy of the GPSRO-retrieved hurricane intensities: Temperature sensitivity Precise measurements of the eyewall temperature is the key to hurricane intensity estimation GPSRO observations penetrate clouds and heavy precipitation. Eyewall temperature at the tropopause height is a sensitive indicator of hurricane intensity. GPSRO temperature accuracy is ~ K (black rectangle). This translates to a 1 4 m/s hurricane intensity error. Vergados P., Z. Luo, K. Emanuel, and A. J. Mannucci (2014), Observation tests of hurricane intensity estimations using GPS radio occultations, J. Geophys. Res. Atmospheres., 13 p., doi: /2013jd GPS temperature accuracy is ~ K, suggesting that GPS can introduce only a 1 4 m/s hurricane intensity error.

29 Assimilating GPS RO in Polar WRF to improve surface pressure estimation over Antarctica Top (based on observations): Southern Ocean near Adélie Land Dominant SH cyclone formation zone (black box) resulting in numerous cyclones that travel east across the South Pacific (red tracks) Bottom: Assimilating GPS RO into Polar WRF: Enhances cyclone formation in the Adélie Land region Resulting in a greater number of cyclones moving toward the east Demonstrated by a decrease in surface pressure across the South Pacific (blue shading) BIAS Bromwich et al. (2011): Tellus A. RMSE

30 GPS Radio Occultation (RO) valuable for polar boundary layer studies Manisha Ganeshan 1 and Dong L. Wu 2, Code 613, NASA/GSFC and GESTAR/USRA. With its high vertical resolution, GPS RO is a valuable technique for studying the polar atmospheric boundary layer (ABL). Over the frozen Arctic Ocean, the ABL inversion height from a refractivitybased RO retrieval method is found to be sensitive to the underlying surface temperature. Our results help model validation as well as monitoring ABL changes over the dynamic new Arctic Ocean. Earth Sciences Division - Atmospheres

31 MiRaTA: Microwave Radiometer Technology Acceleration Microwave radiometer measurements and GPS radio occultation (GPSRO) measurements of all-weather temperature and humidity provide key contributions toward improved weather forecasting. The Microwave Radiometer Technology Acceleration (MiRaTA) is a 3-unit (3U) Cubesat that will validate multiple technologies in both passive microwave radiometry and GPS radio occultation, including a space demonstration of new miniature microwave radiometers operating near 52-58, , and GHz. With a launch scheduled for November 2016 as a secondary payload with JPSS-1, MiRaTA will execute periodic pitch-up maneuvers so that the radiometer and GPSRO observations sound overlapping volumes of atmosphere through the Earth's limb. To validate system performance, observations will be compared to radiosondes, global high-resolution analysis fields, and other satellite observations. PI: Kerri Cahoy, MIT Top: mechanical drawing of the MiRaTA spacecraft. Bottom: nominal operations sequence for joint atmospheric GPSRO and microwave radiometer observations. MiRaTA will execute a slow pitch (~ 0.5 o /sec) maneuver once per orbit with a goal of > 100 spatially and temporally coincident radiometer and GPSRO scans of Earth s limb over a 90-day mission. (These pitchups can be considered a wheelie in terms of a car or

32 Overview of Talk How NASA Studies the Earth with Remote Sensing What We re Seeing and Learning GPSRO and NASA What We ll be Doing in the Future Conclusion

33 Formulation Implementation Primary Ops Extended Ops Sentinel-6A/B Earth Science Instruments on ISS: RapidScat, CATS, LIS, SAGE III (on ISS), TSIS-1, OCO-3, ECOSTRESS, GEDI, CLARREO-PF Science Missions and Instruments ISS CYGNSS SORCE, TCTE (NOAA) ICESat-2 TEMPO JPSS-2 (NOAA) RBI, OMPS-Limb GRACE-FO (2) NISTAR, EPIC (NOAA S DSCOVR) QuikSCAT NI-SAR SWOT PACE Landsat 9 Suomi NPP (NOAA) SMAP Aqua Terra Landsat 7 (USGS) EO-1 Landsat 8 (USGS) GPM CloudSat CALIPS O Aura OCO-2 GRACE (2) OSTM/Jason 2 (NOAA)

34 LIS (2016) SAGE III (6/2016) ISERV ( ) RapidSCAT (2014-) CLARREO Pathfinders (CY2019) CATS (2015-) HICO ( ) GEDI (2019) ECOSTRESS (2019) OCO-3 (2018)

35 CYGNSS Objectives and Mission Design CYGNSS Objectives Measure ocean surface wind speed in all precipitating conditions, including those experienced in the tropical cyclone (TC) eyewall Measure ocean surface wind speed in the TC inner core with sufficient frequency to resolve genesis and rapid intensification CYGNSS Mission Design Eight satellites in low earth orbit at 35 inclination, each carrying a four-channel modified GPS receiver capable of bi-static radar measurements of GPS signals reflected by the ocean surface

36 Key Mission Parameters Constellation: 8 LEO microsats Single Pegasus Altitude: 510 km Inclination: 35 degrees CYGNSS Observatory

37 National Aeronautics and Space Administration KDP-D DPMC May 16, 2013

38 CYGNSS Earth Coverage 90 min (one orbit) coverage showing all specular reflection contacts by each of 8 s/c 24 hr coverage provides nearly gap free spatial sampling within +/- 35 deg orbit inclination 38

39 In-Space Validation of Earth Science Technology (InVEST) 2012 U-Class satellites advancing TRLs for Earth science measurements (all 3-unit CubeSats) MiRaTA MIT / MIT-LL RAVAN APL/JHU ICECube GSFC HARP UMBC LMPC The Aerospace Corporation 3 Frequency Radiometer and GPSRO Vertically Aligned Carbon Nanotubes (VACNTs) 883 GHz submm- Wave radiometer Wide FOV Rainbow Polarimeter Photon Counting InfraRed Detector Validation of new microwave radiometer and GPSRO technology for allweather sounding Validate VACNTs as radiometer absorbing material and calibration standard for total outgoing radiation Validation of submm radiometer for spaceborne cloud ice remote sensing Validation of 2-4 km wide FOV hyperangular polarimeter for cloud & aerosol characterization Validation of linear mode single photon detector at 1, 1.5, and 2 microns in space environment Targeting launch dates for all in timeframe primarily utilizing the CubeSat Launch Initiative

40 In-Space Validation of Earth Science Technology (InVEST) 2015 U-Class satellites advancing TRLs for Earth science measurements (all 6- unit CubeSats) CIRAS JPL RainCube JPL CubeRRT The Ohio State University CIRiS Ball Aerospace Infrared Atmospheric Sounder Precipitation Profiling Radar Radiometer Radio Frequency Interference Infrared Radiometer Demonstrate ability to measure spectrum of upwelling infrared radiation in 4-5 micron spectral region Validate Ka-band (35.75 GHz) radar payload using new deployable antenna and processing technologies Demonstrate wideband RFI mitigation technologies vital for future space-based microwave radiometers Validation of an uncooled imaging infrared ( um) radiometer for high radiometric performance in LEO

41 Overview of Talk How NASA Studies the Earth with Remote Sensing What We re Seeing and Learning GPSRO and NASA What We ll be Doing in the Future Conclusion

42 Concluding Messages The vantage point of space provides a good approach to watch the whole planet evolve and explore the interconnections between physics, chemistry, and biology The current and projected suite of space-based environmental measurement capability enables scientific discovery and (for many parameters) monitoring, and is being enhanced by introduction of new technology GPSRO and related GNSS-based technologies have important contributions to make to the study of the Earth system Collaborations between scientists working on GPSRO/GNSS-based techniques and complementary ones will be important to achieving full success from both, especially as technology advances and the scope of the participating community increases 42

43 DSCOVR Earth View with Lunar Transit July 16,