Brian R. Nelson

PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies

AbstractA new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S–60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset ...

An evaluation of NEXRAD precipitation estimates in complex terrain

Next Generation Weather Radar (NEXRAD) precipitation estimates are used for hydrological, meteorological, and climatological studies at a wide range of spatial and temporal scales. The utility of radar-based precipitation estimates in such applications hinges on an understanding of the sources and magnitude of estimation error. This study examines precipitation estimation in the complex mountainous terrain of the northern Appalachian Mountains. Hourly digital precipitation (HDP) products for two WSR-88D radars in New York state are evaluated for a 2-year period. This analysis includes evaluation of range dependence and spatial distribution of estimates, radar intercomparisons for the overlap region, and radar-gage comparisons. The results indicate that there are unique challenges for radar-rainfall estimation in mountainous terrain. Beam blockage is a serious problem that is not corrected by existing NEXRAD algorithms. Underestimation and nondetection of precipitation are also significant concerns. Improved algorithms are needed for merging estimates from multiple radars with spatially variable biases.

An Experimental Study of Small-Scale Variability of Radar Reflectivity Using Disdrometer Observations

Abstract Analysis of data collected by four disdrometers deployed in a 1-km2 area is presented with the intent of quantifying the spatial variability of radar reflectivity at small spatial scales. Spatial variability of radar reflectivity within the radar beam is a key source of error in radar-rainfall estimation because of the assumption that drops are uniformly distributed within the radar-sensing volume. Common experience tells one that, in fact, drops are not uniformly distributed, and, although some work has been done to examine the small-scale spatial variability of rain rates, little experimental work has been done to explore the variability of radar reflectivity. The four disdrometers used for this study include a two-dimensional video disdrometer, an X-band radar-based disdrometer, an impact-type disdrometer, and an optical spectropluviometer. Although instrumental differences were expected, the magnitude of these differences clouds the natural variability of interest. An algorithm is applied to ...

Precipitation Contribution of Tropical Cyclones in the Southeastern United States from 1998 to 2009 Using TRMM Satellite Data

AbstractThe objective of this paper is to characterize the precipitation amounts originating from tropical cyclones (TCs) in the southeastern United States during the tropical storm season from June to November. Using 12 years of precipitation data from the Tropical Rainfall Measurement Mission (TRMM), the authors estimate the TC contribution on the seasonal, interannual, and monthly precipitation budget using TC information derived from the International Best Track Archive for Climate Stewardship (IBTrACS). Results derived from the TRMM Multisatellite Precipitation Analysis (TMPA) 3B42 showed that TCs accounted for about 7% of the seasonal precipitation total from 1998 to 2009. Rainfall attributable to TCs was found to contribute as much as 8%–12% for inland areas located between 150 and 300 km from the coast and up to 15%–20% for coastal areas from Louisiana to the Florida Panhandle, southern Florida, and coastal Carolinas. The interannual contribution varied from 1.3% to 13.8% for the period 1998–2009 ...

Multisensor Precipitation Reanalysis

Abstract Temporally consistent high-quality, high-resolution multisensor precipitation reanalysis (MPR) products are needed for a wide range of quantitative climatological and hydroclimatological applications. Therefore, the authors have reengineered the multisensor precipitation estimator (MPE) algorithms of the NWS into the MPR package. Owing to the retrospective nature of the analysis, MPR allows for the utilization of additional rain gauge data, more rigorous automatic quality control, and post factum correction of radar quantitative precipitation estimation (QPE) and optimization of key parameters in multisensor estimation. To evaluate and demonstrate the value of MPR, the authors designed and carried out a set of cross-validation experiments in the pilot domain of North Carolina and South Carolina. The rain gauge data are from the reprocessed Hydrometeorological Automated Data System (HADS) and the daily Cooperative Observer Program (COOP). The radar QPE data are the operationally produced Weather S...

Assessment and Implications of NCEP Stage IV Quantitative Precipitation Estimates for Product Intercomparisons

AbstractThe National Centers for Environmental Prediction (NCEP) stage IV quantitative precipitation estimates (QPEs) are used in many studies for intercomparisons including those for satellite QPEs. An overview of the National Weather Service precipitation processing system is provided here so as to set the stage IV product in context and to provide users with some knowledge as to how it is developed. Then, an assessment of the stage IV product over the period 2002–12 is provided. The assessment shows that the stage IV product can be useful for conditional comparisons of moderate-to-heavy rainfall for select seasons and locations. When evaluating the product at the daily scale, there are many discontinuities due to the operational processing at the radar site as well as discontinuities due to the merging of data from different River Forecast Centers (RFCs) that use much different processing algorithms for generating their precipitation estimates. An assessment of the daily precipitation estimates is prov...

Independent assessment of incremental complexity in NWS multisensor precipitation estimator algorithms

AbstractThis paper presents a comprehensive intercomparison analysis of different radar-based multisensor precipitation products generated operationally by the National Weather Service (NWS) Multisensor Precipitation Estimator (MPE) algorithm from the Weather Surveillance Radar–1988 Doppler version and concurrent rain gauge data. The analysis provides close insight into different effects of the increasing degree of complexitzy in the MPE algorithms. First, a gauge-only product produced by the MPE algorithm was assessed. Then six MPE products were analyzed: a radar-only product, a mean-field bias-adjusted product, a local bias-adjusted product, two products that are based on merging the bias-adjusted products with gauge observations, and a final product that includes human intervention by NWS forecasters. Data from a dense, carefully maintained experimental rain gauge cluster are used as an independent surface reference. A number of summary and conditional statistics are applied to the product intercompari...

Characteristics of Reprocessed Hydrometeorological Automated Data System (HADS) Hourly Precipitation Data

The Hydrometeorological Automated Data System (HADS) is a real-time data acquisition, processing, and distribution system operated by the Office of Hydrologic Development (OHD) of NOAA’s National Weather Service (NWS). The initial reprocessing of HADS data from its original format since its inception in July 1996 has been completed at NOAA’s National Climatic Data Center (NCDC). The quality of the reprocessed HADS hourly precipitation data from rain gauges is assessed by two objective metrics: the average fraction of missing values and the percentage of top-of-the-hour observations for a 3-yr period (2003‐05). Pairwise comparisons between the reprocessed product and the real-time product are made using representative samples (about 13%) from the 48 contiguous United States. The monthly average of missing values varies from 0.5% to 2% in the reprocessed product and from 1.7% to 10.1% in the real-time product. Except for January2003,thereprocessedproductconsistently reducedmissingvalues,by asmuch as9.4%in October 2004.Theavailabilityof top-of-the-hourobservations is about85%in thereprocessedproduct,whiletherealtime product has top-of-the-hour observations only about 50% of the time. This paper discusses real-time product quality issues, additional quality assurance algorithms used in the reprocessing environment, and the design of system-wide performance comparisons. Thus, the benefits to users of reprocessing the HADS data are the correction of 4-h observation time errors during 1 July‐11 August 2005 and the demonstration of diurnalspatternofprecipitationfrequenciesinregionaldomains.AWeb-basedinteractivequalityassessment tool for reprocessed HADS hourly precipitation data and access to the data are also presented.

Archival precipitation data set for the Mississippi river basin: development of a GIS-based data browser

To aid in modeling studies over the Mississippi River Basin, we have developed an archival precipitation data set for the GEWEX Continental-Scale International Project. The data set spans from 1996-2000, a 5-year continuous period of record. Inputs for the data set are the National Reflectivity Composite that we obtained in Hierarchical Data Format. The size of the input data is 40 GB. In order to significantly reduce the size of the data set, we have developed an efficient data formal that can be read from a disc faster than the input Hierarchical Data Format. We have also developed browsing tools for users of the data set. The data browser allows for fast and efficient viewing of the precipitation data and was produced using a common Geographic Information System software. Peripheral data are also included in the browser as an aid to the user.

On the Link between Tropical Cyclones and Daily Rainfall Extremes Derived from Global Satellite Observations

AbstractThe authors evaluate the contribution of tropical cyclones (TCs) to daily precipitation extremes over land for TC-active regions around the world. From 1998 to 2012, data from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B42) showed that TCs account for an average of 3.5% ± 1% of the total number of rainy days over land areas experiencing cyclonic activity regardless of the basin considered. TC days represent between 13% and 31% of daily extremes above 4 in. day−1, but can account locally for the large majority (>70%) or almost all (≈100%) of extreme rainfall even over higher-latitude areas marginally affected by cyclonic activity. Moreover, regardless of the TC basin, TC-related extremes occur preferably later in the TC season after the peak of cyclonic activity.