Riko Oki

The Global Precipitation Measurement Mission

Precipitation affects many aspects of our everyday life. It is the primary source of freshwater and has significant socioeconomic impacts resulting from natural hazards such as hurricanes, floods, droughts, and landslides. Fundamentally, precipitation is a critical component of the global water and energy cycle that governs the weather, climate, and ecological systems. Accurate and timely knowledge of when, where, and how much it rains or snows is essential for understanding how the Earth system functions and for improving the prediction of weather, climate, freshwater resources, and natural hazard events. The Global Precipitation Measurement (GPM) mission is an international satellite mission specifically designed to set a new standard for the measurement of precipitation from space and to provide a new generation of global rainfall and snowfall observations in all parts of the world every 3 h. The National Aeronautics and Space Administration (NASA) and the Japan Aerospace and Exploration Agency (JAXA) ...

The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation

AbstractThe collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s c...

International Global Precipitation Measurement (GPM) Program and Mission: An Overview

Eric A. Smith , Ghassem Asrar , Yoji Furuhama , Amnon Ginati , Christian Kummerow , Vincenzo Levizzani , Alberto Mugnai , Kenji Nakamura , Robert Adler , Vincent Casse , Mary Cleave , Michele Debois , John Durning , Jared Entin , Paul Houser , Toshio Iguchi , Ramesh Kakar , Jack Kaye , Masahiro Kojima , Dennis Lettenmaier , Michael Luther , Amita Mehta , Pierre Morel , Tetsuo Nakazawa , Steven Neeck , Ken’ichi Okamoto , Riko Oki , Garudachar Raju , Marshall Shepherd , Erich Stocker , Jacques Testud , and Eric Wood 19

Comparison of Rainfall Products Derived from TRMM Microwave Imager and Precipitation Radar

Satellite remote sensing is an indispensable means of measuring and monitoring precipitation on a global scale. The Tropical Rainfall Measuring Mission (TRMM) is continuing to make significant progress in helping the global features of precipitation to be understood, particularly with the help of a pair of spaceborne microwave sensors, the TRMM Microwave Imager (TMI) and precipitation radar (PR). The TRMM version-5 standard products, however, are known to have a systematic inconsistency in mean monthly rainfall. To clarify the origin of this inconsistency, the authors investigate the zonal mean precipitation and the regional trends in the hydrometeor profiles in terms of the precipitation water content (PWC) and the precipitation water path (PWP) derived from the TMI profiling algorithm (2A12) and the PR profile (2A25). An excess of PR over TMI in near-surface PWC is identified in the midlatitudes (especially in winter), whereas PWP exhibits a striking excess of TMI over PR around the tropical rainfall maximum. It is shown that these inconsistencies arise from TMI underestimating the near-surface PWC in midlatitude winter and PR underestimating PWP in the Tropics. This conclusion is supported by the contoured-frequency-by-altitude diagrams as a function of PWC. Correlations between rain rate and PWC/ PWP indicate that the TMI profiling algorithm tends to provide a larger rain rate than the PR profile under a given PWC or PWP, which exaggerates the excess by TMI and cancels the excess by PR through the conversion from precipitation water to rain rate. As a consequence, the disagreement in the rainfall products between TMI and PR is a combined result of the intrinsic bias originating from the different physical principles between TMI and PR measurements and the purely algorithmic bias inherent in the conversion from precipitation water to rain rate.

The Global Precipitation Measurement (GPM) Mission for Science and Society

The GPM mission collects essential rain and snow data for scientific studies and societal benefit.

Finescale Diurnal Rainfall Statistics Refined from Eight Years of TRMM PR Data

Abstract The adequacy of hourly rainfall sampling was examined in terms of the detection of diurnal variations using 8 yr (1998–2005) of data observed by the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM) satellite. It was found that the monthly and hourly rain samples for each 0.2° grid point over the 8-yr period are composed of multiple precipitation systems. In this study, a “3-h-significant diurnal peak” was defined as the time of maximum rainfall with consecutive positive anomalies for more than 3 h. The fraction of the analyzed area with a 3-h-significant diurnal peak increased annually and accounted for 43% of the total global tropics at 0.2° resolution over the 8-yr period. The diurnal signature over Tibet and the Amazon showed a high degree of spatial uniformity (at >10° scale). The degree of similarity and locations of the regional diurnal characteristics are described in terms of seasonal variations and at multiple resolutions based on spatial uniformity. For example, uni...

Evaluation of Precipitation Estimates by at-Launch Codes of GPM/DPR Algorithms Using Synthetic Data from TRMM/PR Observations

The Global Precipitation Measurement (GPM) Core Observatory will carry a Dual-frequency Precipitation Radar (DPR) consisting of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). In this study, “at-launch” codes of DPR precipitation algorithms, which will be used in GPM ground systems at launch, were evaluated using synthetic data based upon the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. Results from the codes (Version 4.20131010) of the KuPR-only, KaPR-only, and DPR algorithms were compared with “true values” calculated based upon drop size distributions assumed in the synthetic data and standard results from the TRMM algorithms at an altitude of 2 km over the ocean. The results indicate that the total precipitation amounts during April 2011 from the KuPR and DPR algorithms are similar to the true values, whereas the estimates from the KaPR data are underestimated. Moreover, the DPR estimates yielded smaller precipitation rates for rates less than about 10 mm/h and greater precipitation rates above 10 mm/h. Underestimation of the KaPR estimates was analyzed in terms of measured radar reflectivity (Zm) of the KaPR at an altitude of 2 km. The underestimation of the KaPR data was most pronounced during strong precipitation events of Zm <; 18 dBZ (high attenuation cases) over heavy precipitation areas in the Tropics, whereas the underestimation was less pronounced when the Zm > 26 (moderate attenuation cases). The results suggest that the underestimation is caused by a problem in the attenuation correction method, which was verified by the improved codes.

Incidence-Angle Dependency of TRMM PR Rain Estimates

AbstractThe incidence-angle differences of estimated surface rainfall obtained from the precipitation radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM) satellite were investigated. The bias before the orbit boost in August 2001 relative to the near-nadir statistics was 2.7% over the ocean and −5.8% over land. After the boost, the bias was −3.2% and −9.5%, respectively. These biases were further quantified with respect to error sources, that is, the beam mismatch correction error, detection capability of storms with low-level storm-top height, and residual effects. For shallow storms lower than 3 km, most incidence-angle differences were caused by main lobe contamination. For nonshallow storms, several error factors resulted in 5.3% overestimates over the ocean and 5.1% underestimates over land for the period before the boost. The remaining uncertainty in local low-level profiles was identified as a controversial issue.The bias-corrected dataset updates the interannual variation in rainfal...

TRMM Sampling of Radar–AMeDAS Rainfall Using the Threshold Method

Abstract It is known that spatially averaged rainfall rate 〈R〉 is highly correlated with the fractional area (F) of rain rate exceeding a preset threshold (τ), when the area is large enough to include numerous convective systems in various stages of their life cycles. Using this fact, a method to estimate area-averaged rain rate from F(τ), which is obtained from satellite observations, is proposed for Tropical Rainfall Measuring Mission (TRMM). There have been numerous studies investigating F–〈R〉 relationships and optimal thresholds at several radar observation sites around the world but no studies to confirm the performance of the method within Japan. In this study an analysis of radar–AMeDAS (Automatic Meteorological Data Acquisition System) precipitation data is presented. The F–〈R〉 relationships of radar–AMeDAS rain data have been examined systematically, with the result that the optimum threshold that maximizes the correlation between 〈R〉 and F(τ) is near 3.5 mm h−1 in every year and season of availa...

Comparison of Global and Seasonal Characteristics of Cloud Phase and Horizontal Ice Plates Derived from CALIPSO with MODIS and ECMWF

AbstractThis study analyzed the global and seasonal characteristics of cloud phase and ice crystal orientation (CTYPE-lidar) by using the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). A dataset from September 2006 to August 2007 was used to derive the seasonal characteristics. The discrimination scheme was originally developed by Yoshida et al., who classified clouds mainly into warm water, supercooled water, and randomly oriented ice crystals or horizontally oriented ice plates. This study used the following products for the comparison with CTYPE-lidar: (i) the vertical feature mask (VFM) of the National Aeronautics and Space Administration (NASA), (ii) the Moderate Resolution Imaging Spectroradiometer (MODIS), and (iii) European Centre for Medium-Range Weather Forecasts (ECMWF). Overall, the results showed that the CTYPE-lidar discrimination scheme was consistent with the outputs from VFM, MODIS, and E...