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Puerto Rico African Dust and Clouds Study (PRADACS) - Introduction

Puerto Rico African Dust and Clouds Study (PRADACS) - Introduction. Olga L. Mayol-Bracero Institute for Tropical Ecosystem Studies University of Puerto Rico, Río Piedras Campus Planning Meeting for IFP 2011 4.February.2011.

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Puerto Rico African Dust and Clouds Study (PRADACS) - Introduction

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  1. Puerto Rico African Dust and Clouds Study (PRADACS) - Introduction Olga L. Mayol-Bracero Institute for Tropical Ecosystem Studies University of Puerto Rico, Río Piedras Campus Planning Meeting for IFP 2011 4.February.2011

  2. For details about Motivation and Introduction to PRADACS see presentation entitled “Overview of the Project” – Olga L. Mayol-Bracero https://sites.google.com/a/ites.upr.edu/pradacs/

  3. Scientific Question How the physico-chemical properties of long-range transported African dust (LRTAD) aerosols influence Caribbean cloud properties and precipitation levels in a unique Puerto Rican tropical montane cloud forest (TMCF)?

  4. Hypotheses H1: Cloud properties in the TMCF are different during intense LRTAD periods. H2: LRTAD has unique chemical and physical properties which influence cloud properties and precipitation processes.

  5. Why the Caribbean (Puerto Rico) is so Attractive for These Studies? Located in the subtropics, 18’15 N, 66’30 W Heavily influenced by the trade winds, by hurricane storm tracks, and by long-range transported African dust (LRTAD) (also volcanic ash) Key convergence zone between 2 continental landmasses, thus, plays a role in hemispheric climate Highly undersampled/understudied region Highly vulnerable to the Earth’s climate change Presence of tropical montane cloud forests Two ideal sampling locations: the natural reserve of Cabezas de San Juan, Fajardo (CSJ) and El Yunque National Forest (Pico del Este , cloud forest - 1051 masl) Large university research center (UPR-RP) within ~60 min drive.

  6. Online Measurements: CN counter, SMPS, aethalometer, nephelometer, CIMEL sunphotometer, PSAP, OPC, APS, APSD, disdrometer, CCN counter ATOFMS, AMS LWC, CVI, visibility sensor, FM-100, webcam system for cloud base height Analyses: Gravimetric Thermal/optical analysis (TC, OC, EC) Total Organic Carbon and Total Nitrogen Analyzer (TOC, DOC, TN) Ion Chromatography (Na+, NH4+, Ca2+, K+, Mg2+, Cl-, NO3- SO42-, acetate, formate, oxalate, and MSA) ICP (P, K, Mn, Fe, Ca, Mg, Na, Al) H-NMR pH, cloud and rain water volumes Samplers: Aerosols – Stacked-filter units, low-pressure impactors (DLPI, MOUDI), Hi volume sampler Cloud water - Caltech Active Strand Cloud Water Collector (CASCC) and size fractionating CASCC. Rainwater - Bottle and funnel Meteorological data Daily Aerosol Optical Thickness Satellite Images from NOAA / NESDIS Air Mass Backward Trajectories NOAA ARL HYSPLIT model (HYbrid Single-Particle Lagrangian Integrated Trajectory) NADP Data Measurements and Analyses (see attachments for details)

  7. Experimental Design H1:Cloud properties in the TMCF are different during intense LRTAD periods (we need someone to help us in working this Hypothesis) Measurements: Cloud properties (e.g., droplet concentration (Ndrops), drop size distribution, cloud drop effective radius (Reff), cloud albedo, liquid water content (LWC), cloud base height, composition). These properties are influenced by the characteristics of the aerosol they form upon, thus we would expect cloud properties to be different during LRTAD events. AVHRR and MODIS satellite images together with HYSPLIT back trajectories and aerosol properties will be used to classify samples according to the presence or absence of LRTAD. We will use this classification to compare cloud properties, wet deposition, and precipitation for LRTAD periods with non-LRTAD periods. FM-100, LWC-100, Satellite data from CALIPSO, CloudSat, MISR and TRMMM Cloud properties combined with cloud occurrence and frequency in the presence and absence of LRTAD will also give an indication of the impact LRTAD is having on climate. These results will allow us to begin understanding the relative effects of LRTAD on cloud formation and precipitation.

  8. Experimental Design H2:LRTAD has unique chemical and physical properties which influence cloud properties and precipitation processes. First, we will identify the chemical, physical, and optical properties of LRTAD and differentiate this dust from local aerosol sources. (LRTAD vs non-LRTAD) ATOFMS, AMS, MOUDI, DLPI, SFUs, CN, CCN, aethalometer, Neph, PSAP, sunphotometer, hygroscopicity,… Second, we will determine how those unique LRTAD properties affect cloud properties and precipitation processes, and how those properties might explain the observed differences in cloud or rain properties for LRTAD periods found in H1. use of statistical correlations of residual particles of cloud droplets and interstitial particles with various cloud parameters Aerosols, clouds, and rainwater samples CCN-pCVI-ATOFMS …

  9. Sampling Strategy See more details in Work Plan and Tables (later on) Year 1 (Oct 2009 to Sept 2010) Test, calibration, and diagnosis year that will allow to begin developing procedures for data analysis and archiving of combined data sets without distractions of a full blown intensive field campaign. Sampling logistics (e.g., shipping, transport, power, and installations). Running things side by side to find out the right sampling times, if we need other measurements,... Train students and technician Short intensive field period (end of July 2010) to test and fine tune instruments and methods ATOFMS, nephelometers with the humidification system, new SMPS, OPC, CPC (see attached table of instruments to be deployed). In summary, Y1 was a test run that will allow us to run a much stronger large intensive field period in Y2, ensuring the success of the intensive field phase and of the project.

  10. Sampling Strategy Year 2 (Oct 2010 – Sept 2011) The summer intensive field phase of the project will take place in Y2. June-July (dust period) and Oct-Nov from Y3 (non-dust period) sampling periods (we need to fine tune specific dates today). See attached table of instruments to be deployed. Starting in Y2, we would like to start the search for additional funds to support the completion of the data analyses, as well as to be able to use the data already generated to support the modeling component. Year 3 (Oct 2011 – Sept 2012) Data analysis, presentations and publications Modeling PRADACS Symposium African Dust Workshop sponsored by IGAC (Oct 3-7, 2011, Puerto Rico)

  11. Announcement First Symposium on Transport, Evolution and Impacts of African Dust into the Western Hemisphere, sponsored by IGAC (International Global Atmosphere Chemistry) Date: October 3-7, 2011 (together with the SSC IGAC Meeting) Location: San Juan, Puerto Rico Mark this date in your calendar so that you can attend. More details in the near future.

  12. ProposedWork Plan T1: ONDJ T2: FMAM T3: JJAS

  13. Deployment of Instruments duringthe Project

  14. Aerosol and Cloud Instrumentation to be Deployed at Study Sites (see “attached” Table)

  15. CollaborationwithOtherSimultaneousProjects “The FENNEC project: Dust processes and the Western Sahara ‘heat low’” – Paola Formenti – LISA Univ of Paris 7 and 12 (JUNE) ICE-T (“The Ice in Clouds Experiment. - Tropical Field Campaign”) - Andy Heymsfield (aircraft measurements from the C-130) – NCAR (JULY)

  16. Education and Outreach Teen’s University – intermediate and high school students (S. Borrmann) – date to be decided PISCAS program – university students Short Course at UPR-RP in May 2011 – Chemistry of Precipitation, Clouds, and Aerosols – Prof. Jeff Collett, CSU GK-12 Birch Aquarium (Scripps) – general public Others?

  17. List of Participants (2010-2011) • PI: O. L. Mayol-Bracero - UPR-RP ITES • CoPI: E. Andrews - UC Boulder and NOAA ESRL, • CoPI: K. Prather, E. Fitzgerald, M. Zauscher - UCSD and Scripps • F. Zurcher, A. McFadden – ITES, UPR-RP • C. Valle, P. Vallejo, G. Santos, A. Carrion, J. Morales, H. Rivera – UPR-RP Grad students (ITES, Chemistry, Physics) • S. Raizada, C. Tepley – Arecibo Observatory, PR • I. Matos – NWS San Juan, PR • P. Diaz, M. Rosario – USGS, PR • R. Morales – UPR-RP • J. Collett, L. Taehyoung - CSU, Colorado • D. Rosenfeld -Hebrew University, Israel • B. McDowell – Univ of New Hampshire • W. Eugster, J. Spiegel – ETH, Switzerland • M. Scholl – USGS, Virginia • P. Formenti – LISA University of Paris 12, France • S. Borrmann, J. Schneider -Max Planck Institute for Chemistry – Germany • A. Heymsfield – NCAR, Colorado • D. Baumgardner – UNAM, Mexico • S. Mertes – Institute for Tropospheric Research – Germany • F. Scatena – UPenn • A. Lugo, T. Heartsill – IITF, PR

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