1. G O D D A R D S P A C E F L I G H T C E N T E R 1 GPM and HF PMW Observations Arthur Y. Hou, GPM Project Scientist Gail Skofronick-Jackson, PMM Science Staff October 11, 2005 Global Precipitation Measurement GPM Global Precipitation Measurement

2. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 2 NASA HQ formally approved the incorporation of high frequency (HF) capability on both GMI instruments in September, 2005. Channel specifications: 165.5 GHz and 183.31 GHz. The ability to measure light rain and detect snowfall at mid and high latitudes in cold seasons makes GPM truly a global measurement mission. GPM is looking to this community to build upon HF research to make effective use of DPR and GMI to improve GPM precipitation products over both land and oceans. ** NEWS FLASH **

3. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 3 Global Water and Energy Cycle: Observation Strategy and Context GPM is flagship mission for NASA’s Global Water and Energy Cycle (GWEC) research and applications & key measuring element in Weather Science Focus Area

4. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 4 Precipitation regimes /Constellations

5. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 5 GPM science objectives  Precipitation measurement technology : advancing precipitation measurement capability from space - through combined use of active and passive remote-sensing techniques to calibrate dedicated & operational PMW sensors to achieve global coverage  Water/energy cycle variability : advancing understanding of global water/energy cycle and fresh water availability - through better measurement of the space-time variability of global precipitation  Weather prediction : improving NWP skills - through more accurate and frequent measurement of instantaneous rain rates  Hydrometeorological prediction : advancing flood-hazard and fresh- water-resource prediction capabilities - through improved temporal sampling and spatial coverage  Climate prediction : improving climate prediction capability - through better understanding of precipitation microphysics, surface water fluxes, soil moisture storage, and latent heating

6. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 6  Applications - Making GPM data products and resources accessible to users and stakeholders beyond the traditional precipitation science community - by establishing broader and more effective use of space-based precipitation data products in decision-support of a wide variety of societal applications – Freshwater Utilization and Resource Management – Natural Hazard Monitoring/Prediction (Flood Warnings, Hurricane and Cyclone Observation, Winter Weather Events ) – Operational Weather Forecasting – Climate Change Assessment – Agriculture – Transportation – Policy and Planning  Outreach - Making immediate precipitation data products available to: – Students, teachers, and researchers in educational institutions via direct network access to GPM data products – Commercial and public television enterprises via near-real time graphic rain imagery – Any government, industrial, and academic data user agencies as well as private homes GPM applications & outreach Accomplishing science objectives will directly feed into applications.

7. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 7 Core Satellite TRMM-like spacecraft (NASA) H2-A rocket launch (JAXA) Non-sun-synchronous orbit ~ 65° inclination ~407 km altitude Dual frequency radar (JAXA) Ku-Ka Bands (13.6-35 GHz) ~ 4 km horizontal resolution ~250 m vertical resolution Multifrequency radiometer (NASA) (Conically-Scanning) 10.65, 18.7, 23.8, 36.5, 89.0 GHz 166, 183.3±~3, 183.3±7 or 9 GHz Constellation Satellites Pre-existing operational- experimental & dedicated satellites with PMW radiometers Revisit time 3-hour goal at ~90% of time Sun-synch & non-sun- synch orbits 600-900 km altitudes OBJECTIVES Understand horizontal & vertical structure of rainfall, its macro- & micro-physical nature, & its associated latent heating Train & calibrate retrieval algorithms for constellation radiometers OBJECTIVES Provide sufficient global sampling to significantly reduce uncertainties in short- term rainfall accumulations Extend scientific and societal applications Precipitation Processing System Global precipitation products from diverse sensors and sources Cooperative international partnerships Core Constellation GPM Reference Concept Ground Validation Sites Ground truth and calibration Cooperative international partners High Frequencies Approved Sept. 2005

8. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 8 GPM Dual Precipitation Radar (DPR) Increased sensitivity for light rain and snow detection – Addition of Ka band (35.5 GHz) to Ku band (13.6 GHz) improves the detection threshold from 0.5 to 0.17 mm/h, significantly improving measurements of rain occurrences in light rain and snow events Better overall measurement accuracy - replacing the surface reference technique for path-integrated-attenuation correction with dual-frequency methods More detailed microphysical information – detection of drop size distribution and identification of liquid, frozen, and mixed phase precipitation, leading to an improved cloud database for rain & snow retrievals for both the Core and constellation radiometers Courtesy of Z. Haddad Error Std Dev in Rain Retrieval as Function of Rain Rate Percent GPM TRMM ~12.5 mm hr -1 ~1.5 mm hr -1 Rain Rate (mm/h) Simulated retrievals based on synthetic noises added to Hurricane Bonnie observations and an assumed drop size distribution

9. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 9 GPM Microwave Imager (GMI) Ball Aerospace and Technology Corporation (BATC) design: 2.4 m 1.0 m 1.2 m GMI Key Parameters Mass:~100 kg Power:~90 W Data Rate:~25 kbps Antenna Size:~1.2 m Diameter Channel Set: 10.65 GHz, H & V Pol 18.7 GHz, H & V Pol 23.8 GHz, V Pol 36.5 GHz, H & V Pol 89.0 GHz, H & V Pol 166 GHz, H & V Pol, 183±~3 GHz, V (or H) Pol 183±~7 (or 9) GHz, V (or H) GMI Key Parameters Mass:~100 kg Power:~90 W Data Rate:~25 kbps Antenna Size:~1.2 m Diameter Channel Set: 10.65 GHz, H & V Pol 18.7 GHz, H & V Pol 23.8 GHz, V Pol 36.5 GHz, H & V Pol 89.0 GHz, H & V Pol 166 GHz, H & V Pol, 183±~3 GHz, V (or H) Pol 183±~7 (or 9) GHz, V (or H)

10. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 10 GMI Instantaneous Field-of-Views GPM / GMI at 407 km TRMM / TMI at 350 km

11. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 11 GPM Validation Concept P PMW P DPR P GM Applications context Size of Uncertainty P DPR P GM P PMW Meas. & Ancillary Data Microphysical Meas. Microphysical GV goal is to provide ground observations for direct satellite product assessment and for algorithm/application improvements GPM validation goes beyond direct comparisons of surface precipitation rates between ground and satellite measurements

12. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 12 US GV strategy & Plan Surface precipitation statistical validation sites for direct assessment of GPM satellite data products: – Co-located with existing or upgraded national network (NEXRAD etc.) and dense gauge networks Precipitation process sites for improving understanding of precipitation physics, modeling, and satellite retrieval algorithms: – Continental tropical, mid- and high-latitude sites (including orographic/coastal sites and targeted sites for resolving discrepancies between satellite algorithms) – May include aircraft measurements and mobile instrument assets Integrated hydrological sites for improving hydrological applications: – Co-located with existing watersheds maintained by other US agencies and international research programs These sites can be designed to overlap. US GPM Ground Measurement Advisory Panel (Chair: Chris Kummerow) recommends:

13. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 13 Science value of HF channels on GMI Measurement of frozen precipitation Measurement of light rain Improved PMW retrieval algorithms over land Improved precipitation measurements in mid- and high-latitudes in cold seasons HF channels on GPM Core enabling the testing and evaluation of constellation PMW algorithms using the DPR Radar reflectivity composite of the March 5-6, 2001 New England blizzard (75 cm of snow fell on Burlington, VT) Surface effects evident over the Great Lakes, the St. Lawrence River, and along the Atlantic coast. Cannot distinguish surface from cloud effects. Surface effects screened by water vapor. Snowfall appears over New England as low brightness temperatures G. Skofronick-Jackson et al. (GSFC) TGARS 2004 183.3±1 GHz Weighting Functions 183.3±3 GHz 183.3±7 GHz 150 GHz 89 GHz SENSITIVITY HEIGHT (km) AMSU-B 89 GHz AMSU-B 183.3 ± 7 GHz NOAA NEXRAD Data Snow Retrieval g m 3 Feasibility demonstration of snowfall retrieval using HF channels 4 in/h

14. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 14 Falling Snow Retrieval Algorithms Physically Based March 2001 NASA Goddard/U. Wash. Kim, 2004 Thesis Neural Networks March 2001 MIT Chen and Staelin Trans Geosci Remote Sens 2003 NOAA Kongoli, et al Geophys Res. Letters 2003 & Ferraro et al TGARS 2005 Algorithm development & improvement for GMI core and constellation satellites Neural Nets/Polar 25 January 2004 Snow Detection MIT, Staelin ocean 5.5mm/hr (Melted)

15. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 15 Temporal Sampling Risk Mitigation using AMSU Satellites Observations Per Day TRMM + 2 DMSP SSM/I’s TRMM Reference GPM Core + DMSP F18 + DMSP F19 + NPP + NPOESS1 + NASA1 (optimized) GPM Base Configuration GPM Core + 3 NPOESS’s + GCOM-W + EGPM + Megha-Tropiques + NASA1 (optimized) Expected GPM Constellation GPM Core + 3 NPOESS’s + GCOM-W + EGPM + NASA1 + Megha-Tropiques + 3 NOAA AMSU’s GPM + 3 AMSU

16. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 16 Conclusions Challenges Pathway from HF sounders to HF imager products – Quantitative assessment of different products over land and oceans. – Evaluation of sounder retrieval methodologies and error estimates – Development of improved retrieval algorithms, especially over land Algorithm development – Assessment of precipitating snowfall and light rain retrieval methodologies – Development and enhancement of reliable algorithms appropriate to DPR, GMI, and DPR+GMI observations Validation – Appraisal of GV and in situ requirements for snow and light rain – Statistical, process, and hydrological needs The GPM Core satellite provides an unprecedented opportunity to measure falling snow and light rain to calibrate and improve PMW precipitation algorithms

17. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 17 Backup slides

18. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 18 Light Rain From TRMM/GPM workshop, October 2003

19. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 19 Challenges Frozen Particle Variability CPI in situ images, Andy Heymsfield Non-Linear and Under-Constrained Relationships between physical characteristics of ice particles and microwave observations Surface Variability

20. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 20 Courtesy of Min-Jeong Kim For simplicity, spheres and dielectric mixing theories have been used. Methodologies such as the Discrete Dipole Approximation (DDA) allow the computation of radiative properties for various idealized shapes of snow crystals. These DDA calculations are in progress with results to be archived in a database open to scientific community for related remote sensing studies. (Contact Min-Jeong Kim at mjkim@neptune.gsfc.nasa.gov)mjkim@neptune.gsfc.nasa.gov From Heymsfield et al. (2001) 89 GHz 183.3±3 GHz 183.3±7 GHz 183.3±1 GHz 150 GHz Continuing Work Spherical versus Non-Spherical Assumptions Complex Atmospheric Snow Particle Shapes

21. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 21 GMI High Frequency Channel Characteristics Chan. CenterFreq. [GHz] Pol. Band- width [MHz] Cent. Freq. Stab. [MHz] Samp. Interv. [ms] NE  T [K] Beam- width [deg.] 10166.0V40002003.61.20.40 11166.0H40002003.61.20.40 12183.31 ± 3.0V IF 2500 RF 5000 1003.61.20.40 13183.31 ± 9.0V IF 3000 RF 6000 1003.61.30.40

22. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 22 MODIS Snow Cover Assimilation Observations Model output Assimilated output Observations Model output Assimilated output Observations Model output Assimilated output Western Montana Midwestern United States Central Atlantic Locations of averaging regions and Cooperative Network snow observation sites Rodell, M., and P. R. Houser, Updating a land surface model with MODIS derived snow cover, J. Hydromet., 5 (6), 1064-1075, 2004. Control GLDAS SWE (mm) MODIS Snow Cover (%) Assimilated SWE (mm) IMS Snow Cover Observed SWE (mm) SWE Improvement (mm) 21Z 17 January 2003 MODIS snow cover fields used to update land surface models driven by the Global Land Data Assimilation System (GLDAS) Models fill spatial and temporal gaps in data, provide continuity and quality control Assimilated output agrees more closely with IMS snow cover fields and ground observations (figures) Assimilated output contains more information (~hourly SWE) than MODIS (~daily snow cover) alone

23. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 23 Science drivers for precipitation measurement Precipitation and latent heating drive the Earth’s weather/climate system through their coupling with the large-scale circulation to redistribute heat, momentum, and moisture. Deep convection is the source of upper-troposphere water vapor – thus controlling the primary greenhouse gas in a radiatively responsive region. (Influence of precipitation is not confined to cloudy/rainy regions) Cloud-scale microphysics and dynamics control the partition between rain and clouds, crucial for understanding climate sensitivity and feedback processes to improve climate prediction. Accurate knowledge of precipitation is needed for monitoring freshwater availability and for closing the water/energy budget. Frequency and intensity of extreme precipitation events may be a signal of natural or anthropogenic change. WPACCPACEPAC Key measurement for understanding and predicting freshwater availability, the water/energy cycle, and the weather/climate system

24. IPWG/GPM/GRP Workshop/Madison, WI, Oct 11, 2005 G O D D A R D S P A C E F L I G H T C E N T E R 24 Traceability to NASA’s GWEC research plan Variability: Is the water cycle accelerating in a warmer climate? Response: How does precipitation variability influence surface hydrology, global transport, and weather/climate states? Forcing: How do precipitation processes affect atmospheric moisture (the primary greenhouse gas), clouds, and cloud/radiation feedback? Consequence: Are there more extreme weather events in a warmer climate? Prediction: How do we use more accurate knowledge of global precipitation to improve weather, climate and hydrological modeling and prediction? GPM addresses science questions from NASA’s GWEC research themes