@article{prat_nelson_2023, title={Evaluation of Seasonal Differences among Three NOAA Climate Data Records of Precipitation}, volume={24}, ISSN={["1525-7541"]}, DOI={10.1175/JHM-D-22-0108.1}, abstractNote={Abstract}, number={9}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Prat, Olivier P. and Nelson, Brian R.}, year={2023}, month={Sep}, pages={1527–1548} }
 @article{leeper_bilotta_petersen_stiles_heim_fuchs_prat_palecki_ansari_2022, title={Characterizing US drought over the past 20 years using the US drought monitor}, volume={4}, ISSN={["1097-0088"]}, DOI={10.1002/joc.7653}, abstractNote={Abstract}, journal={INTERNATIONAL JOURNAL OF CLIMATOLOGY}, author={Leeper, Ronald D. and Bilotta, Rocky and Petersen, Bryan and Stiles, Crystal J. and Heim, Richard and Fuchs, Brian and Prat, Olivier P. and Palecki, Michael and Ansari, Steve}, year={2022}, month={Apr} }
 @misc{kumjian_prat_reimel_van lier-walqui_morrison_2022, title={Dual-Polarization Radar Fingerprints of Precipitation Physics: A Review}, volume={14}, ISSN={["2072-4292"]}, DOI={10.3390/rs14153706}, abstractNote={This article reviews how precipitation microphysics processes are observed in dual-polarization radar observations. These so-called “fingerprints” of precipitation processes are observed as vertical gradients in radar observables. Fingerprints of rain processes are first reviewed, followed by processes involving snow and ice. Then, emerging research is introduced, which includes more quantitative analysis of these dual-polarization radar fingerprints to obtain microphysics model parameters and microphysical process rates. New results based on a detailed rain shaft bin microphysical model are presented, and we conclude with an outlook of potentially fruitful future research directions.}, number={15}, journal={REMOTE SENSING}, author={Kumjian, Matthew R. and Prat, Olivier P. and Reimel, Karly J. and Van Lier-Walqui, Marcus and Morrison, Hughbert C.}, year={2022}, month={Aug} }
 @article{nelson_prat_leeper_2021, title={An Investigation of NEXRAD-Based Quantitative Precipitation Estimates in Alaska}, volume={13}, ISSN={["2072-4292"]}, url={https://www.mdpi.com/2072-4292/13/16/3202}, DOI={10.3390/rs13163202}, abstractNote={Precipitation estimation by weather radars in Alaska is challenging. In this study, we investigate National Weather Service (NWS) precipitation products that are produced from the seven NEXRAD radar sites in Alaska. The NWS precipitation processing subsystem generates stages of data at each NEXRAD site which are then input to the weather forecast office to generate a regionwide precipitation product. Data from the NEXRAD sites and the operational rain gauges in the weather forecast region are used to produce this regionwide product that is then sent to the National Centers for Environmental Prediction (NCEP) to be included in the NCEP Stage IV distribution. The NCEP Stage IV product for Alaska has been available since 2017. We use the United States Climate Reference Network (USCRN) data from Alaska to compare to the NCEP Stage IV data. Given that the USCRN can be used in the production of the NCEP Stage IV data for Alaska, we also used the NEXRAD Digital Precipitation Array (DPA) that is generated at the site for comparison of the radar-only products. Comparing the NEXRAD-based data from Alaska to the USCRN gauge estimates using the USCRN site information on air temperature, we are able to condition the analysis based on the hourly or 6-hourly average air temperature. The estimates in the frozen phase of precipitation largely underestimate as compared to the gauge, and the correlation is low with larger errors as compared to other phases of precipitation. In the mixed phase the underestimation of precipitation improves, but the correlation is still low with relatively large errors as compared to the rain phases of precipitation. The difficulties in precipitation estimation in cold temperatures are well known and we show the evaluation for the NCEP Stage IV regional data for Alaska and the NEXRAD site specific Digital Precipitation Array (DPA) data. Results show the challenges of estimating mixed-phase and frozen precipitation. However, the DPA data shows somewhat better performance in the mixed precipitation phase, which suggests that the NWS Precipitation Processing Subsystem (PPS) is tuned to the climatology as it relates to precipitation in Alaska.}, number={16}, journal={REMOTE SENSING}, author={Nelson, Brian R. and Prat, Olivier P. and Leeper, Ronald D.}, year={2021}, month={Aug} }
 @article{prat_nelson_nickl_leeper_2021, title={Global Evaluation of Gridded Satellite Precipitation Products from the NOAA Climate Data Record Program}, volume={22}, ISSN={["1525-7541"]}, DOI={10.1175/JHM-D-20-0246.1}, abstractNote={Abstract}, number={9}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Prat, Olivier P. and Nelson, Brian R. and Nickl, Elsa and Leeper, Ronald D.}, year={2021}, month={Sep}, pages={2291–2310} }
 @article{nelson_prat_leeper_2021, title={Using Ancillary Information from Radar-Based Observations and Rain Gauges to Identify Error and Bias}, volume={22}, ISSN={["1525-7541"]}, DOI={10.1175/JHM-D-20-0193.1}, abstractNote={Abstract}, number={5}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Nelson, Brian R. and Prat, Olivier P. and Leeper, Ronald D.}, year={2021}, month={May}, pages={1249–1258} }
 @article{a bayesian approach for statistical-physical bulk parameterization of rain microphysics. part i: scheme description_2020, DOI={10.1175/JAS-D-19-0070.1}, abstractNote={Abstract}, journal={Journal of the Atmospheric Sciences}, year={2020}, month={Mar} }
 @article{a bayesian approach for statistical-physical bulk parameterization of rain microphysics. part ii: idealized markov chain monte carlo experiments_2020, DOI={10.1175/JAS-D-19-0071.1}, abstractNote={Abstract}, journal={Journal of the Atmospheric Sciences}, year={2020}, month={Mar} }
 @article{morrison_lier-walqui_fridlind_grabowski_harrington_hoose_korolev_kumjian_milbrandt_pawlowska_et al._2020, title={Confronting the Challenge of Modeling Cloud and Precipitation Microphysics}, volume={12}, ISSN={["1942-2466"]}, DOI={10.1029/2019MS001689}, abstractNote={Abstract}, number={8}, journal={JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS}, author={Morrison, Hugh and Lier-Walqui, Marcus and Fridlind, Ann M. and Grabowski, Wojciech W. and Harrington, Jerry Y. and Hoose, Corinna and Korolev, Alexei and Kumjian, Matthew R. and Milbrandt, Jason A. and Pawlowska, Hanna and et al.}, year={2020}, month={Aug} }
 @article{morrison_kumjian_martinkus_prat_lier-walqui_2019, title={A General N-Moment Normalization Method for Deriving Raindrop Size Distribution Scaling Relationships}, volume={58}, ISSN={["1558-8432"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000458394300001&KeyUID=WOS:000458394300001}, DOI={10.1175/JAMC-D-18-0060.1}, abstractNote={Abstract}, number={2}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Morrison, Hugh and Kumjian, Matthew R. and Martinkus, Charlotte P. and Prat, Olivier P. and Lier-Walqui, Marcus}, year={2019}, month={Feb}, pages={247–267} }
 @article{kumjian_martinkus_prat_collis_lier-walqui_morrison_2019, title={A Moment-Based Polarimetric Radar Forward Operator for Rain Microphysics}, volume={58}, ISSN={["1558-8432"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000457313600001&KeyUID=WOS:000457313600001}, DOI={10.1175/JAMC-D-18-0121.1}, abstractNote={Abstract}, number={1}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Kumjian, Matthew R. and Martinkus, Charlotte P. and Prat, Olivier P. and Collis, Scott and Lier-Walqui, Marcus and Morrison, Hugh C.}, year={2019}, month={Jan}, pages={113–130} }
 @article{kim_seo_noh_prat_nelson_2018, title={Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation}, volume={556}, ISSN={["1879-2707"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000423641300085&KeyUID=WOS:000423641300085}, DOI={10.1016/j.jhydrol.2016.10.052}, abstractNote={A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.}, journal={JOURNAL OF HYDROLOGY}, author={Kim, Beomgeun and Seo, Dong-Jun and Noh, Seong Jin and Prat, Olivier P. and Nelson, Brian R.}, year={2018}, month={Jan}, pages={1096–1109} }
 @article{ferraro_nelson_smith_prat_2018, title={The AMSU-Based Hydrological Bundle Climate Data RecordDescription and Comparison with Other Data Sets}, volume={10}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000448555800140&KeyUID=WOS:000448555800140}, DOI={10.3390/rs10101640}, abstractNote={Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences.}, number={10}, journal={Remote Sensing}, author={Ferraro, R. R. and Nelson, B. R. and Smith, T. and Prat, O. P.}, year={2018}, pages={18} }
 @article{nelson_prat_seo_habib_2016, title={Assessment and Implications of NCEP Stage IV Quantitative Precipitation Estimates for Product Intercomparisons}, volume={31}, ISSN={["1520-0434"]}, DOI={10.1175/waf-d-14-00112.1}, abstractNote={Abstract}, number={2}, journal={WEATHER AND FORECASTING}, author={Nelson, Brian R. and Prat, Olivier P. and Seo, D. -J. and Habib, Emad}, year={2016}, month={Apr}, pages={371–394} }
 @article{prat_nelson_2016, title={On the Link between Tropical Cyclones and Daily Rainfall Extremes Derived from Global Satellite Observations}, volume={29}, ISSN={["1520-0442"]}, DOI={10.1175/jcli-d-16-0289.1}, abstractNote={Abstract}, number={17}, journal={JOURNAL OF CLIMATE}, author={Prat, Olivier P. and Nelson, Brian R.}, year={2016}, month={Sep}, pages={6127–6135} }
 @article{prat_nelson_2015, title={Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)}, volume={19}, ISSN={["1607-7938"]}, DOI={10.5194/hess-19-2037-2015}, abstractNote={Abstract. We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002–2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (−33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day−1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day−1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.
                    }, number={4}, journal={HYDROLOGY AND EARTH SYSTEM SCIENCES}, author={Prat, O. P. and Nelson, B. R.}, year={2015}, pages={2037–2056} }
 @article{ashouri_hsu_sorooshian_braithwaite_knapp_cecil_nelson_prat_2015, title={PERSIANN-CDR Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies}, volume={96}, ISSN={["1520-0477"]}, DOI={10.1175/bams-d-13-00068.1}, abstractNote={Abstract}, number={1}, journal={BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY}, author={Ashouri, Hamed and Hsu, Kuo-Lin and Sorooshian, Soroosh and Braithwaite, Dan K. and Knapp, Kenneth R. and Cecil, L. Dewayne and Nelson, Brian R. and Prat, Olivier P.}, year={2015}, month={Jan}, pages={69-+} }
 @article{prat_nelson_2014, title={Characteristics of annual, seasonal, and diurnal precipitation in the Southeastern United States derived from long-term remotely sensed data}, volume={144}, ISSN={["1873-2895"]}, DOI={10.1016/j.atmosres.2013.07.022}, abstractNote={The objective of this paper is to investigate long-term inter-annual, seasonal, and diurnal rainfall characteristics in the Southeastern United States. In order to capture precipitation features at high resolution, we use precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM); the TRMM Precipitation Radar (TPR 2A25: 0.05° × 0.05°/daily) and the TRMM Multi-satellite Precipitation Analysis (TMPA 3B42: 0.25° × 0.25°/3-h) datasets to create a 13-year rainfall climatology. The higher resolution climatology (2A25) displays a greater ability to capture more localized landform precipitation features when compared with 3B42. On an annual basis, the Southeastern US is characterized by a succession of cold and warm precipitation regimes. The cold season is characterized by higher rain intensity West of 82°W (roughly Atlanta, GA) and the warm season is characterized by higher rain intensity over the coastal areas. The cold/warm rainfall regime duality is modulated by local topographic characteristics that prevail along a W–E direction. During the cold season, the diurnal cycle of precipitation is characterized by a quasi-constant repartition of rain events throughout the day and an absence of land/ocean contrast. On the contrary for summertime there is a strong land/ocean signature with a predominance of late morning/early afternoon (12:00–15:00LST) rainfall over ocean and afternoon/early evening (15:00–18:00LST) precipitation events over land that account for more than 25% of the daily events along the coasts. Differences are observed for the Florida peninsula, where the diurnal cycle displays an afternoon maximum of variable intensity due to sea breeze effects regardless of the season.}, journal={ATMOSPHERIC RESEARCH}, author={Prat, Olivier P. and Nelson, Brian R.}, year={2014}, month={Jul}, pages={4–20} }
 @article{kumjian_prat_2014, title={The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables}, volume={71}, ISSN={["1520-0469"]}, DOI={10.1175/jas-d-13-0357.1}, abstractNote={Abstract}, number={8}, journal={JOURNAL OF THE ATMOSPHERIC SCIENCES}, author={Kumjian, Matthew R. and Prat, Olivier P.}, year={2014}, month={Aug}, pages={3052–3067} }
 @article{prat_nelson_2013, title={Mapping the world's tropical cyclone rainfall contribution over land using the TRMM Multi-satellite Precipitation Analysis}, volume={49}, DOI={10.1002/wrcr.20527}, abstractNote={A study was performed to characterize over land precipitation associated with tropical cyclones (TCs) for basins around the world based upon the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2009, data from the Tropical Rainfall Measuring Mission (TRMM) Multi‐satellite Precipitation Analysis (TMPA) product 3B42, showed that TCs accounted for 5.5%, 7.5%, 6%, 9.5%, and 8.9% of the annual precipitation for impacted over land areas of the Americas, East Asia, South and West Asia, Oceania, and East Africa respectively, and that TC contribution decreased significantly within the first 150 km from the coast. Locally, TCs contributed on average to more than 25% and up to 61% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. East Asia represented the higher and most constant TC rain (118 mm yr−1±19%) normalized over the area impacted, while East Africa presented the highest variability (108 mm yr−1±60%), and the Americas displayed the lowest average TC rain (65 mm yr−1±24%) despite a higher TC activity. Furthermore, the maximum monthly TC contribution (8–11%) was found later in the TC season and depended on the peak of TC activity, TC rainfall, and the domain transition between dry and wet regimes if any. Finally, because of their importance in terms of rainfall amount, the contribution of TCs was provided for a selection of 50 urban areas experiencing cyclonic activity. Results showed that for particularly intense years, urban areas prone to cyclonic activity received more than half of their annual rainfall from TCs.}, number={11}, journal={Water Resources Research}, author={Prat, Olivier and Nelson, B. R.}, year={2013}, pages={7236–7254} }
 @article{prat_nelson_2013, title={Precipitation Contribution of Tropical Cyclones in the Southeastern United States from 1998 to 2009 Using TRMM Satellite Data}, volume={26}, ISSN={["1520-0442"]}, DOI={10.1175/jcli-d-11-00736.1}, abstractNote={Abstract}, number={3}, journal={JOURNAL OF CLIMATE}, author={Prat, Olivier P. and Nelson, Brian R.}, year={2013}, month={Feb}, pages={1047–1062} }
 @article{prat_barros_testik_2012, title={On the Influence of Raindrop Collision Outcomes on Equilibrium Drop Size Distributions}, volume={69}, ISSN={["0022-4928"]}, DOI={10.1175/jas-d-11-0192.1}, abstractNote={Abstract}, number={5}, journal={JOURNAL OF THE ATMOSPHERIC SCIENCES}, author={Prat, Olivier P. and Barros, Ana P. and Testik, Firat Y.}, year={2012}, month={May}, pages={1534–1546} }
 @article{prat_barros_2010, title={Assessing satellite-based precipitation estimates in the Southern Appalachian mountains using rain gauges and TRMM PR}, volume={25}, DOI={10.5194/adgeo-25-143-2010}, abstractNote={Abstract. A study was performed using the first full year of rain gauge records from a newly deployed network in the Southern Appalachian mountains. This is a region characterized by complex topography with orographic rainfall enhancement up to 300% over small distances (<8 km). Rain gauge observations were used to assess precipitation estimates from the Precipitation Radar (PR) on board of the TRMM satellite, specifically the TRMM PR 2A25 precipitation product. Results show substantial differences between annual records and isolated events (e.g. tropical storm Fay). An overall bias of −27% was found between TRMM PR 2A25 rain rate and rain gauge rain rates for the complete one year of study (−59% for tropical storm Fay). Besides differences observed for concurrent observations by the satellite and the rain gauges, a large number of rainfall events is detected independently by either one of the observing systems alone (rain gauges: 50% of events are missed by TRMM PR; TRMM PR: 20% of events are not detected by the rain gauges), especially for light rainfall conditions (0.1–2mm/h) that account for more than 80% of all the missed satellite events. An exploratory investigation using a microphysical model along with TRMM reflectivity factors at selected heights was conducted to determine the shape of the drop size distribution (DSD) that can be applied to reduce the difference between TRMM estimates and rain gauge observations. The results suggest that the critical DSD parameter is the number concentration of very small drops. For tropical storm Fay an increase of one order of magnitude in the number of small drops is apparently needed to capture the observed rainfall rate regardless of the value of the measured reflectivity. This is consistent with DSD observations that report high concentrations of small and/or midsize drops in the case of tropical storms.}, journal={Adv. Geosci.}, author={Prat, O. P. and Barros, A. P.}, year={2010}, pages={143–153} }
 @article{prat_barros_2010, title={Ground observations to characterize the spatial gradients and vertical structure of orographic precipitation - Experiments in the inner region of the Great Smoky Mountains}, volume={391}, DOI={10.1016/j.jhydrol.2010.07.013}, abstractNote={A new rain gauge network was installed in the Great Smoky Mountains National Park (GSMNP) in the Southern Appalachians since 2007 to investigate the space–time distribution of precipitation in the inner mountain region. Exploratory Intense Observing Periods (IOPs) have been conducted in the summer and fall seasons to devise optimal long-term monitoring strategies, and Micro Rain Radars (MRR) were deployed twice in July/August and October/November 2008 at a mountain ridge location and a nearby valley. Rain gauge and MRR observations were analyzed to characterize seasonal (summer/fall) and orographic (valley/ridge) precipitation features. The data show that summer precipitation is characterized by large event-to-event variability including both stratiform and convective properties. During fall, stratiform precipitation dominates and rainfall is two times more frequent at the ridge than in the valley, corresponding to a 100% increase in cumulative rainfall at high elevation. For concurrent rain events, the orographic enhancement effect is on the order of 60%. Evidence of a seasonal signature in the drop size distribution (DSD) was found with significantly heavier tails (larger raindrops) for summer DSDs at higher elevations, whereas no significant differences were observed between ridge and valley locations during fall deployment. However, physically-based modeling experiments suggest that there are inconsistencies between the reflectivity profiles and MRR DSD estimates when large raindrop sizes are present. The number of very small drops is very high (up to two orders of magnitude) at high elevations as compared to the typical values in the literature, which cannot be explained only by fog and drizzle and suggest an important role for mixed phase processes in determining the shape of the DSD below the brightband. Because numerical modeling experiments show that coalescence is the dominant microphysical mechanism for DSD evolution for the relatively low to moderate observed rain rates characteristic of mountainous regions, it is therefore critical to clarify the shape and parameters that characterize the left-hand side of the DSD in mountainous regions. Finally, whereas low cost Micro Rain Radars (MRR) were found particularly useful for qualitative description of precipitation events and to identify rain/snow melting conditions, when compared against collocated rain gauges, MRR Quantitative Precipitation Estimation (QPE) is not reliable. Place-based calibration and reliance upon physically-based QPE retrieval algorithms can improve their utility.}, number={1-2}, journal={Journal of Hydrology}, author={Prat, OP and Barros, AP}, year={2010}, pages={143–158} }
 @article{barros_prat_testik_2010, title={Size distribution of raindrops}, volume={6}, number={4}, journal={Nature Physics}, author={BARROS, AP and PRAT, OP and TESTIK, FY}, year={2010}, pages={232} }
 @article{prat_barros_2009, title={Combining a Rain Microphysical Model and Observations: Implications for Radar Rainfall Estimation}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000268721800162&KeyUID=WOS:000268721800162}, journal={2009 IEEE RADAR CONFERENCE, VOLS 1 AND 2}, author={PRAT, OP and BARROS, AP}, year={2009}, pages={805–808} }
 @article{prat_barros_2009, title={Exploring the Transient Behavior of Z-R Relationships: Implications for Radar Rainfall Estimation}, volume={48}, DOI={10.1175/2009JAMC2165.1}, abstractNote={Abstract}, number={10}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={PRAT, OP and BARROS, AP}, year={2009}, pages={2127–2143} }
 @article{prat_barros_williams_2008, title={An Intercomparison of Model Simulations and VPR Estimates of the Vertical Structure of Warm Stratiform Rainfall during TWP-ICE}, volume={47}, DOI={10.1175/2008JAMC1801.1}, abstractNote={Abstract}, number={11}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={PRAT, OP and BARROS, AP and WILLIAMS, CR}, year={2008}, pages={2797–2815} }
 @article{barros_prat_shrestha_al._2008, title={Revisiting Low and List (1982): Evaluation of raindrop collision parameterizations using laboratory observations and modeling}, volume={65}, DOI={10.1175/2008JAS2630.1}, abstractNote={Abstract}, number={9}, journal={JOURNAL OF THE ATMOSPHERIC SCIENCES}, author={BARROS, AP and PRAT, OP and SHRESTHA, P and al.}, year={2008}, pages={2983–2993} }
 @article{prat_barros_2007, title={A robust numerical solution of the Stochastic collection-breakup equation for warm rain}, volume={46}, DOI={10.1175/JAM2544.1}, abstractNote={Abstract}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={PRAT, OP and BARROS, AP}, year={2007}, pages={1480–1497} }
 @article{prat_barros_2007, title={Exploring the use of a column model for the characterization of microphysical processes in warm rain: results from a homogeneous rainshaft model}, volume={10}, DOI={10.5194/adgeo-10-145-2007}, abstractNote={Abstract. A study of the evolution of raindrop spectra (raindrop size distribution, DSD) between cloud base and the ground surface was conducted using a column model of stochastic coalescense-breakup dynamics. Numerical results show that, under steady-state boundary conditions (i.e. constant rainfall rate and DSD at the top of the rainshaft), the equilibrium DSD is achieved only for high rain rates produced by midlevel or higher clouds and after long simulation times (~30 min or greater). Because these conditions are not typical of most rainfall, the results suggest that the theoretical equilibrium DSD might not be attainable for the duration of individual rain events, and thus DSD observations from field experiments should be analyzed conditional on the specific storm environment under which they were obtained.
                    }, journal={Adv. Geosci.}, author={Prat, O. P. and Barros, A. P.}, year={2007}, pages={145–152} }
 @article{prat_ducoste_2007, title={Simulation of flocculation in stirred vessels - Lagrangian versus Eulerian}, volume={85}, ISSN={["1744-3563"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-33947272599&partnerID=MN8TOARS}, DOI={10.1205/cherd05001}, abstractNote={Abstract A study has been performed to evaluate Lagrangian and Eulerian approaches for simulating flocculation in stirred vessels. The prediction of the transient floc size evolution was performed using the quadrature method of moments (QMOM) while flow field characteristics within the turbulent stirred vessel were obtained using computational fluid dynamics (CFD). The Eulerian and Lagrangian CFD/QMOM models were applied to a 28 l square tank using either a Rushton turbine or a fluid foil impeller. Simulations were performed with an initial concentration of 100 mg L −1 of 1 μm nominal clay particles for several average characteristic velocity gradients (40-, 70-, 90-, 150-s −1 ). For the Lagrangian approach, the results showed that the average floc size transient evolution curve does not predict a peak followed by a lower steady-state size as observed for higher shear rates with the Eulerian approach. However, the overall good agreement between the Eulerian and Lagrangian CFD/QMOM models, indicates that a Lagrangian approach combined with a QMOM model would be an efficient method to quantify the impact of non-fluid flow experimental conditions on the flocculation process. In addition, the Lagrangian CFD/QMOM approach may be a useful tool to study the dynamics of flocculation and determine appropriate coalescence/breakup kernels when performing an inverse problem technique.}, number={A2}, journal={CHEMICAL ENGINEERING RESEARCH & DESIGN}, author={Prat, O. P. and Ducoste, J. J.}, year={2007}, month={Feb}, pages={207–219} }
 @article{prat_cloitre_aulombard_2007, title={Thermal and mechanical properties of silicon tetrachloride (SiCl4) and germanium tetrachloride (GeCl4) in their vapor and liquid phases}, volume={13}, DOI={10.1002/cvde.200604242}, abstractNote={The most‐common physical properties of the precursor species SiCl4 and GeCl4 in their vapor and liquid phases are compiled from several sources in the literature. General expressions over a large range of temperature are proposed either by the use of referenced expressions or by the use of suitable empirical models.}, number={5}, journal={CHEMICAL VAPOR DEPOSITION}, author={PRAT, OP and CLOITRE, T and AULOMBARD, RL}, year={2007}, pages={199-+} }
 @article{prat_ducoste_2006, title={Modeling spatial distribution of floc size in turbulent processes using the quadrature method of moment and computational fluid dynamics}, volume={61}, ISSN={["1873-4405"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-25644438483&partnerID=MN8TOARS}, DOI={10.1016/j.ces.2004.11.070}, abstractNote={A study was performed that utilizes the quadrature method of moments (QMOM) to model the transient spatial evolution of the floc size in a heterogeneous turbulent stirred reactor. The QMOM approach was combined with a commercial computational fluid dynamics (CFD) code (PHOENICS), which was used to simulate the turbulent flow and transport of these aggregates in the reactor. The CFD/QMOM model was applied to a 28 l square reactor containing an axial flow impeller and 100 mg/l concentration of 1 μm nominal clay particles. Simulations were performed for different average characteristic velocity gradients (40,70,90, and 150 s-1). The average floc size and growth rate were compared with experimental measurements performed in the bulk region and the impeller discharge region. The CFD/QMOM results confirmed the experimentally measured spatial heterogeneity in the floc size and growth rate. In addition, the model predicts spatial variations in the aggregation and breakup rates. Finally, the model also predicts that the transport of flocs into the high shear impeller discharge zone was responsible for the transient evolution of the average floc size curve displaying a maximum before decreasing to a steady-state floc size.}, number={1}, journal={CHEMICAL ENGINEERING SCIENCE}, author={Prat, OP and Ducoste, JJ}, year={2006}, month={Jan}, pages={75–86} }