Robert Joyce

CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution

Abstract A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors derived from geostationary satellite infrared data. The Climate Prediction Center morphing method (CMORPH) uses motion vectors derived from half-hourly interval geostationary satellite IR imagery to propagate the relatively high quality precipitation estimates derived from passive microwave data. In addition, the shape and intensity of the precipitation features are modified (morphed) during the time between microwave sensor scans by performing a time-weighted linear interpolation. This process yields spatially and temporally complete microwave-derived precipitation analyses, independent of the infrared temperature field. CMORPH showed substantial improvements over both simple averaging of the microwave estimates and over techniques that blend microwave and infrared information but that derive estimates of precipitation from infrared data...

Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations

Abstract The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1° × 1° lat/long grid from currently available observational data. Where possible (40°N–40°S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR Tb) are compared with a threshold and all “cold” pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite Precipitation Index, but for the TMPI the IR Tb threshold and conditional rain rate are set locally by month from Special Sensor Microwave Imager–based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite–gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television and Infrared Observation Satellite Operational Vertical Sounder (TOVS) precipitation. The frequency...

A Real–Time Global Half–Hourly Pixel–Resolution Infrared Dataset and Its Applications

A system has been developed and implemented that merges pixel resolution (~4 km) infrared (IR) satellite data from all available geostationary meteorological satellites into a global (60°N–60°S) product. The resulting research-quality, nearly seamless global array of information is made possible by recent work by Joyce et al., who developed a technique to correct IR temperatures at targets far from satellite nadir. At such locations, IR temperatures are colder than if identical features were measured at a target near satellite nadir. This correction procedure yields a dataset that is considerably more amenable to quantitative manipulation than if the data from the individual satellites were merely spliced together. Several unique features of this product exist. First, the data from individual geostationary satellites have been merged to form nearly seamless maps after correcting the IR brightness temperatures for viewing angle effects. Second, with the availability of IR data from the Meteosat-5 satellite...

Intercomparison of High-Resolution Precipitation Products over Northwest Europe

AbstractSatellite-derived high-resolution precipitation products (HRPP) have been developed to address the needs of the user community and are now available with 0.25° × 0.25° (or less) subdaily resolutions. This paper evaluates a number of commonly available satellite-derived HRPPs covering northwest Europe over a 6-yr period. Precipitation products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing (CMORPH) technique, the CPC merged microwave technique, the Naval Research Laboratory (NRL) blended technique, and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) technique. In addition, the Geosynchronous Operational Environmental Satellite (GOES) precipitation index (GPI) and the European Centre for Medium-Range Weather Forecasting (ECMWF) operational forecast model products are included for comparison. Surface reference data from the European radar network...

Kalman Filter–Based CMORPH

AbstractA Kalman filter (KF)-based Climate Prediction Center (CPC) morphing technique (CMORPH) algorithm is developed to integrate the passive microwave (PMW) precipitation estimates from low-Earth-orbit (LEO) satellites and infrared (IR) observations from geostationary (GEO) platforms. With the new algorithm, the precipitation analysis at a grid box of 8 × 8 km2 is defined in three steps. First, PMW estimates of instantaneous rain rates closest to the target analysis time in both the forward and backward directions are propagated from their observation times to the analysis time using the cloud system advection vectors (CSAVs) computed from the GEO–IR images. The “prediction” of the precipitation analysis is then defined by averaging the forward- and backward-propagated PMW estimates with weights inversely proportional to their error variance. The IR-based precipitation estimates are incorporated if the gap between the two PMW observations is longer than 90 min. Validation tests showed substantial improv...

Improved Estimates of Tropical and Subtropical Precipitation Using the GOES Precipitation Index

Abstract Nine years (1986–94) of tropical and subtropical precipitation estimates based on the GOES precipitation index (GPI) are examined. The GPI, based on the results of studies relating fractional coverage of cold cloud to convective rainfall, uses IR observations gathered by geostationary and polar-orbiting satellites. Longitudinal discontinuities in mean GPI coincident with the boundaries of satellite coverage led to a comparison of GPI derived from each geostationary satellite in overlap regions. This study revealed both intersatellite calibration differences and satellite zenith angle dependence. Its goals are to remove these sources of systematic error within the GPI, investigate the climatology of the corrected GPI, and compare against other estimated rainfall datasets. To correct calibration differences, Global Precipitation Climatology Project geostationary satellite IR data are standardized to one satellite by temperature adjustments deduced by the International Satellite Cloud Climatology Pr...

Evaluation of the High-Resolution CMORPH Satellite Rainfall Product Using Dense Rain Gauge Observations and Radar-Based Estimates

AbstractThis study focuses on the evaluation of the NOAA–NCEP Climate Prediction Center (CPC) morphing technique (CMORPH) satellite-based rainfall product at fine space–time resolutions (1 h and 8 km). The evaluation was conducted during a 28-month period from 2004 to 2006 using a high-quality experimental rain gauge network in southern Louisiana, United States. The dense arrangement of rain gauges allowed for multiple gauges to be located within a single CMORPH pixel and provided a relatively reliable approximation of pixel-average surface rainfall. The results suggest that the CMORPH product has high detection skills: the probability of successful detection is ~80% for surface rain rates >2 mm h−1 and probability of false detection <3%. However, significant and alarming missed-rain and false-rain volumes of 21% and 22%, respectively, were reported. The CMORPH product has a negligible bias when assessed for the entire study period. On an event scale it has significant biases that exceed 100%. The fine-re...

Latitudinally and Seasonally Dependent Zenith-Angle Corrections for Geostationary Satellite IR Brightness Temperatures

Abstract The equivalent brightness temperature Tb recorded by geosynchronous infrared (geo-IR) “window” channel (10.7–11.5 μm) satellite sensors is shown to depend on the zenith angle (local angle from the zenith to the satellite for a pixel’s ground location) in addition to the mix of clouds and surface that would be observed from a direct overhead viewpoint (nadir view). This zenith-angle dependence is characterized, and two corrections are developed from a collection of half-hourly geo-IR pixel data that have been parallax corrected and averaged to a 0.5° × 0.5° latitude/longitude grid for each geosynchronous satellite separately. First, composites of collocated Tb over tropical regions from the Geostationary Operational Environmental Satellite (GOES)-8/GOES-10 and the Meteosat-5/Meteosat-7 satellite pairs are used to produce robust estimates of isotropic zenith-angle corrections as a function of zenith angle and grid-box-averaged Tb. The corrections range from zero for a zenith angle of ∼26.5° to incr...

The estimation of global monthly mean rainfall using infrared satellite data: The GOES precipitation index (GPI)

Abstract Algorithms for deriving estimates of monthly mean rainfall from infrared satellite observations are described and a classification scheme based on the amount of spatial and temporal information used is discussed. Estimates from a simple IR‐only algorithm averaged over the period 1986–92 are compared with two long‐term averages (climatologies). While the intensity and location of mean annual features are quite similar in all of these, the estimates are found to be systematically higher over land. Over the oceans, the differences between the estimates and the other data sets are similar in magnitude to the differences between the climatologies themselves. Tropical Pacific precipitation exhibited large interannual changes during the period, with greater/lesser amounts near the dateline during the warm/cold ENSO episodes that occurred during the period. The estimated tropical rainfall during this period exhibited most of the features found in historical studies based on rain gauge observations. Compa...

An Examination of Precipitation in Observations and Model Forecasts during NAME with Emphasis on the Diurnal Cycle

Abstract Summertime rainfall over the United States and Mexico is examined and is compared with forecasts from operational numerical prediction models. In particular, the distribution of rainfall amounts is examined and the diurnal cycle of rainfall is investigated and compared with the model forecasts. This study focuses on a 35-day period (12 July–15 August 2004) that occurred amid the North American Monsoon Experiment (NAME) field campaign. Three-hour precipitation forecasts from the numerical models were validated against satellite-derived estimates of rainfall that were adjusted by daily rain gauge data to remove bias from the remotely sensed estimates. The model forecasts that are evaluated are for the 36–60-h period after the model initial run time so that the effects of updated observational data are reduced substantially and a more direct evaluation of the model precipitation parameterization can be accomplished. The main findings of this study show that the effective spatial resolution of the mo...