CLIMATE PROCESSES OF THE ATLANTIC MARINE ITCZ (AMI-2007) Experimental Design Overview (EDO) for the National Science Foundation

Transcription

1 CLIMATE PROCESSES OF THE ATLANTIC MARINE ITCZ (AMI-2007) Experimental Design Overview (EDO) for the National Science Foundation Principal Investigators: Chris Fairall 1, Yochanan Kushnir 2, Brian Mapes 3, Athanasios Nenes 4, David Parsons 5, Joeseph Prospero 3, Jens Redemann 6, Wayne Schubert 7, Adam Sobel 2, Chien Wang 8, Chidong Zhang 3, Minghua Zhang 9, and Paquita Zuidema 3 April 20, NOAA/ETL 2 Columbia University 3 University of Miami 4 Georgia Institute of Technology 5 National Center for Atmospheric Research 6 Bay Area Environmental Research Institute 7 Colorado State University 8 Massachusetts Institute of Technology 9 State University of New York at Stony Brook 1

2 B. EXECUTIVE SUMMARY To advance our understanding of critical climatic processes of the Atlantic marine ITCZ (AMI) and to improve its representation in global climate models (see AMI Scientific Program Overview), we propose to conduct a field program in the eastern tropical Atlantic for a period of four weeks between mid June and mid September, The general strategy of the AMI 2007 field campaign is to have R/V Ron Brown stationed in the AMI (roughly 10 N and 23 W) with continuous measurements of surface fluxes, atmospheric boundary properties, cloud microphysics and structures, precipitation, mesoscale circulations, and tropospheric profiles of temperature, humidity, and wind for the four-week period. The NCAR HIAPER will cruise at the 12 km level from 0 to 15 N across the AMI, launching dropsondes at every degree latitude to measure large-scale meridional circulations that interact with the AMI and its associated thermodynamic fields. The HIAPER measurements will be augmented by two surface barometric pressure gauges on enhanced PIRATA moorings at 23 W. The NCAR C-130 will fly several patterns in the vicinity of and within the AMI near the location of the R/V Ron Brown, measuring the vertical profiles of aerosol microphysical, optical and chemical properties, and radiative fluxes to the north and south of the AMI, as well as cloud microphysics within the AMI. The flight missions of the HIAPER and C-130 will be coordinated so that the simultaneous thermodynamic and radiometric measurements in the AMI will maximize the scientific value of the data collected on the two platforms. The simultaneous in situ observations of the vertical structures of AMI convection and its immediate and large-scale environment will be used to address three issues: (1) mechanisms determining the vertical structure of AMI convection; (2) interaction of the AMI convection with the large-scale atmospheric circulation, and (3) the interactions of the AMI with African aerosol, especially the Saharan Air Layer (SAL) which carries extremely dry air and high concentrations of dust, and the consequent impact on AMI convection. In addition to data analyses, observations from the AMI field campaign will greatly benefit modeling activities. Observed surface fluxes, radar-estimated rainfall, profiles of aerosols, radiation, wind, temperature, and humidity will be used to constrain model reanalysis products in derivation of forcing for cloud-resolving models (CRM) and single-column models (SCM), which have proven useful tools for the study of convection and its treatment in global climate models. Vertical profiles of aerosol (both size distributions and chemical compositions) will be used in SRMs and SCMs to realistically quantify interactions of aerosol with AMI convection. The timing is crucial because of opportunities afforded by the ongoing African Monsoon Multidisciplinary Analyses (AMMA) program, which will be in progress in the summer of These include the availability of ship time on the R/V Ron Brown, supported by NOAA, the presence of the augmented AMMA sounding network in West Africa, and the AMMA oceanographic campaign, which will deploy enhanced PIRATA moorings along 23 W. The proposed duration of AMI, is the minimum required to yield sufficient data to enable meaningful interpretation, both in terms of record length and sample density. The aircrasft base will be Saõ Vicente, Cape Verde Islands. UCAR/JOSS will provide field and data management support. 2

3 This document describes the experimental design of the AMI Program. Detailed scientific background, hypotheses, and objectives of the AMI Program are described in the AMI Scientific Program Overview. 3

4 C. TABLE OF CONTENTS Page A. TITLE PAGE B. EXECUTIVE SUMMARY C. TABLE OF CONTENTS D. PROJECT DESCRIPTION Scientific Rationale and Hypotheses Scientific Objectives Experimental Design and Observational Requirements R/V Ronald H. Brown HIAPER C Surface barometric pressure gauges Other observations Modeling Project Management Management in the Field Data Policy and Management Plan References Appendix C-130 Instrumentation Package for AMI List of Acronyms Results from prior NSF support......? 9. Facilities ? 10. Scientific Participants And Sponsors.....?. 4

5 1. Scientific Rationale and Hypotheses The AMI Program is motivated by the following issues: (1) While air-sea coupling is central to climate variability of the tropical Atlantic, atmospheric processes crucial to the air-sea interaction are poorly understood. This is reflected by the fact that many atmospheric GCMs with observed SST cannot accurately simulate the position and strength of the AMI. The systematic bias in heating profiles simulated by global climate model in the tropics suggests the treatment of tropical convection in the models suffers from substantial deficiencies. Reasons for the deficiencies are, however, unclear. (2) The EPIC field experiment in 2001 has revealed previously unknown features of the ITCZ (e.g., mid-upper tropospheric dry air inflow, the low-level return flow) in the eastern Pacific. These features, even though not yet well understood, provide new insights into the climate processes of the ITCZ that could be important to its seasonal and interannual variability. But current global model analysis products suffer from large discrepancies among themselves in their representations of the shallow circulation. (3) Both the ITCZ and African aerosols undergo substantial seasonal, interannual and decadal variability in the tropical Atlantic. But their possible interaction has yet to be explored, even though aerosols are known to affect convection in various ways. Understanding aerosols effects on AMI convection would help to address the intriguing question: Does the Saharan Air Layer (SAL) and African aerosols affect the AMI as an external stochastic forcing or as an integral component of the tropical land-ocean-atmosphere climate system. The AMI Program address these issues by proposing the following hypotheses: (a) The vertical structure of AMI convection is closely related to its meso- and large-scale dynamic and thermodynamic environment and such a relationship can be quantitative established through observations using modern instruments and platform in wellthought coordination. (b) Two important processes relating AMI convection and the large-scale meridional circulation are: a) the import of moist static energy by the shallow meridional circulation that regulates shallow vs. deep convection in the AMI, and b) the modulation of the AMI surface inflow by AMI deep convection through an entrainment braking mechanism. (c) African aerosols and dry air outbreaks have substantial effects on AMI convection and thereby modulate the position and strength of the AMI on seasonal to decadal timescales. 2. Scientific Objectives The overall goal of the AMI Program is to advance our knowledge of the AMI, with emphases on the processes critical to convection in the AMI, its interaction with the large-scale circulation and African aerosols and dry air. One major obstacle to improving our understanding of the issues and to test the hypotheses discussed in section 1 is the lack of in situ observations. GATE data have been the only source of information for the AMI. While tremendous knowledge has been and is still being gained from the GATE data, the data themselves are limited in certain ways because of, for instance, the quality of instruments and limited spatial coverage. 5

6 The scientific objectives of the AMI Program are (1) to collect an unprecedented array of in situ observations of convection in the AMI and the interactions of the AMI with the large-scale dynamic and thermodynamic environment (including meridional overturning circulation, African aerosols and dry air), (2) to use these observations to quantify the uncertainties in current global data reanalyses in their representations of the meridional large-scale circulation associated with the AMI, and (3) to use these observations in data analysis and modeling studies to address the scientific issues and test hypotheses discussed briefly in section 1 of this document and in more detail in the AMI Scientific Program Overview. 3. Experimental Design and Observational Requirements The scientific hypotheses proposed above can be sufficiently addressed only with simultaneous observations of vertical structures of AMI convection and its immediate and large-scale environment. Such simultaneous data are required for establishing coherent dynamic and thermodynamic relationships between AMI convection and its environment and will provide the observational basis for accurate computation of CRM and SCM forcing fields. To acquire in situ observations that meet such data analysis and modeling requirements, we propose deploying both shipborne and airborne measurements during the AMI field campaign of The shipborne measurements will take place aboard the R/V Ron Brown. The airborne measurements will be made aboard the NCAR HIAPER and C-130 aircraft. In addition, surface barometric pressure gauges will be mounted on two enhanced PIRATA moorings along 23 W to facilitate calibration of pressure measurements from dropsondes of the HIAPER. The general design of the AMI field campaign is sketched in Figs. 1 and 2. The AMI field measurements will be augmented by oceanographic measurements and the AMMA sounding network over West Africa that will take place also during the period of AMI field campaign in 2007 (section 3.5a). The AMI field campaign is planned to take place during four weeks between mid June and mid September. This timing of the field campaign is determined by three factors. First, summer is the peak season of the AMI: its convection and precipitation are the strongest, the associated low-level return flow is the most evident (in some global reanalyses), and African SAL (dust/dry-air) outbreaks are the most active. This is, therefore, an ideal season to study climatic processes critical to AMI convection, and its interaction with the large-scale circulation and African aerosol. Second, the R/V Ronald H. Brown, supported by NOAA, will be in the tropical eastern Atlantic in the summer of 2007 making oceanographic observations as a part of AMMA and will be available for the AMI field campaign. R/V Ronald H. Brown, with the onboard precipitation and cloud radar capability, is an essential component of the AMI field campaign and cannot be replaced by other research vessels. Third, the AMMA sounding network in West Africa will operate from 2005 through 2007, covering the planned AMI field campaign period. Even though such a sounding network is not critical to the AMI field campaign, the network data will provide invaluable upstream information to better interpret AMI observations and to facilitate comparison studies of AMI convection under simultaneous land and marine environments. Such comparison studies will no doubt increase the values of both AMI and AMMA observations and benefit both programs in many ways. 6

7 In short, summer 2007 is an ideal opportunity for the AMI field campaign. Any other alternative time must be limited by the availability of R/V Ronald H. Brown along with the NCAR HIAPER and C-130 aircraft. 3.1 R/V Ronald H. Brown The R/V Ronald H. Brown (Fig. 3a) will be stationed in the center of the AMI (roughly 8 10 N) and underneath the path of HIAPER flight tracks (23 W, see section 3.1b) for four weeks during the AMI field campaign. Observations aboard the R/V Ron Brown for the AMI field campaign will include direct measurements of air-sea fluxes, a continuously scanning C-band Doppler radar to provide quantitative precipitation estimates and horizontal-vertical structure information on precipitation features, 6-times daily rawinsonde, a high resolution wind and precipitation profiler to provide continuous measurements of the wind and drop size distribution characteristics through the lower and mid troposphere, and near-surface bulk meteorological variables. The instruments and measurement aboard the R/V Ron Brown are summarized in Table 1. Table 1. Instruments and measurements onboard R/V Ronald H. Brown for the AMI field program Item System Measurement 1 Vaisala Rawinsonde system Local profiles Ta, RH, wind speed/direction 2 Near-surface bulk meteorology Ts, Ta, RH, wind speed/direction; bulk fluxes 3 ETL flux system Direct motion-corrected covariance fluxes of momentum, sensible heat, and latent heat; downward IR and solar radiative fluxes 4 Lasair II Aerosol spectrometer Aerosol size spectra m 5 Ceilometer Cloud-base height, statistics GHz Doppler radar wind profiler Wind & turbulence profiles; calibrated dbz , GHz wave radiometer Integrated column vapor and cloud liquid water 8 Scanning C-band Doppler radar Spatial fields of precipitation and air motion 9 94 GHz Cloud Radar Vertical profiles cloud microphysics, LWC, cloud motions 7

8 The principal strategy of this suite of observations is to provide detailed time series of profiles of wind, thermodynamics, and precipitation structure relevant to role of air-sea interaction in controlling SST and driving deep convection in the ITCZ. The ship is an ideal platform for collecting a breadth of observations which will allow single-column investigations of atmospheric physics in great depth. Shipboard measurement of atmospheric soundings, surface fluxes, and radar estimates of precipitation are irreplaceable in constraining reanalysis product in the process of deriving forcing fields for CRMs and SCMs. The combination of the C-band radar (convective surveillance at a radius of 200 km) will allow unusual flexibility in sampling a region around the ship. Vertical structures of cloud estimated by ship cloud radar (Zuidema et al. 2005) are crucial to the study of convection-circulation interaction in combination with dropsonde data of the HIAPER (section 3.2). The ship will be anchored in the center of the AMI (roughly 8 10 N) and underneath the path of the HIAPER flight tracks (23 W, see section 3.1b) for four weeks during the AMI field campaign. In addition to those measurements listed in Table 1, we expect that a wide range of additional measurements will be made of aerosol, precipitation, chemistry, and radiation. These studies will be carried out by other groups (e.g., the PMEL aerosol group and various university researchers) who will take advantage of this opportunity. 3.1a Radar operation and data analysis The scanning C-band Doppler radar on the R/V Ron Brown will be operated continuously, in a manner almost identical to its operation in EPIC. Volume scans will attempt to cover the 3-dimensional (3D) structure of precipitation around the ship, out to a distance where beamwidth limits on vertical resolution become problematic. Several volumes per hour can be obtained, ideally with interleaved tilt angles from one volume to the next, so that temporally pooled data yield very fine vertical resolution, while the volume sampling time remains short enough to track convective evolution. These volume scans will be interspersed with occasional quick low-angle, low-prf surveillance scans to map the 2D rainfall field out to larger ranges. The combination of the precipitation radar and cloud radar aboard the R/V Ron Brown have proven invaluable for capturing the fine resolution and sensitivity of interactions between large-scale dynamics and microphysics of cloud in the ITCZ (Zuidema 2005). The large-scale divergences calculated from the precipitation radar Doppler velocities, and the point measurements of cloud structures observed by the vertically pointing cloud radar, are remarkably consistent in the EPIC data. These two instruments allow independent but quantitatively approximate calculations of cirrus anvil ice water content and its flux, a result of comparing a large-scale value to a time series at a point. With the addition of aircraft sampling the cloud/aerosol/dry layer interface, the more detailed, precise, but low-sampling-rate aircraft data can be combined with the cloud and precipitation radar data to gain both a more detailed assessment of microphysical changes, and their large-scale feedbacks. The three instruments combined (aircraft, cloud radar, and precipitation radar) provide a pathway for bridging scales, towards best capturing the physical processes that can ultimately test and improve model parameterizations. 8

9 The vertical structure of AMI convection measured by the combination of the precipitation and cloud radars will be irreplaceably important to the analysis of the dropsonde data from the HIAPER (section 3.2) in the study of interaction between AMI convection and the large-scale meridional circulation. The RHB C-band data will be analyzed in three main ways: (1) by regridding the surveillance scans to 2D maps to show the overall space-time structure of rainfall; (2) by regridding volume scan data to 3D Cartesian volumes, mainly for reflectivity structure investigations; and (3) by the Velocity-Azimuth Display (VAD) methods of Mapes and Lin (2005), which yield profiles of wind divergence, mean wind, and echo sample statistics in cylindrical domains centered on the radar. With these three products, case studies as well as statistics of all kinds can be assembled. Detailed profiling information from the vertically-pointing sensors, as well as from aircraft on overflight days, can thus be placed in a horizontal context, both in individual cases and statistically. 3.1b Surface flux measurement Surface fluxes of latent and sensible heat in the AMI are crucial for constraining global data assimilation products in deriving forcing for CRM and SCM (see section 3.6c). Accurate measurement and parameterization of surface fluxes of sensible and latent heat has been a challenge for a long time, especially in a convective environment. It is important to remember that present state-of-the-art bulk flux parameterizations are derived from point measurements that resolve variations in bulk surface properties at very fine scales. When implemented in numerical models with grid resolutions that do not resolve the fine scales, errors occur unless we account for the contribution by subgrid variability. Random variability is usually treated with a gustiness parameter. Bulk algorithms are widely used to estimate surface fluxes in numerical models and in applications (e.g., satellite retrievals) where highly detailed local information is not available. These are based upon similarity representations of the near-surface turbulent fluxes, <w x >, in terms of mean quantities <w x > = C x θδx S = C x θδx (U 2 +V 2 + U g 2 ) 1/2 where x can be the u,v wind components, the potential temperature, θ, the water vapor mixing ratio, q, and C x is the total transfer coefficient for x. ΔX is the sea-air difference in the mean value of x and S is the mean wind speed which is composed of a mean vector part (U and V components) and a gustiness part (U g ) to account for subgridscale variability. Fairall et al. (1996) linked U g to variability associated with local boundarylayer convection. The COARE bulk algorithm is still being improved and version 3.0 was just released (Fairall et al., 2003). Several mechanisms for convective forcing and variability which involve the air-sea fluxes are discussed by Young et al. (1992, 1995). Large scale models (i.e., ones that do not explicitly resolve convection), must account for variability associated with mesoscale convection (Vickers and Esbensen, 1998; Tong et al., 1998) to properly represent the balance of dynamics and thermodynamics. Numerical modeling work by Redelsperger et al. (2000) suggested that U g can be additionally parameterized in terms of rainrate while Krueger and Zulauf (1997) used cumulus convective mass flux. This approach deals 9

10 straightforwardly with the random gustiness effect. Coupling subgridscale variations with convective dynamics requires a treatment that deals specifically with the convective structures and their cold downdrafts, gust fronts, etc., which modify the surface fluxes locally. Examples include the convective wake parameterization of Rozbicki et al. (1999) and the cumulus ensemble approach (e.g., Chenet, 2004). AMI offers an opportunity for modeling and observational studies to examine these issues. The ideal observational data set (i.e., everything, everywhere, all the time) is not practical but satellite, aircraft, and ship-based measurements can be combined to provide useful constraints. The combination of the C-band Doppler radar, the vertically pointing precipitation profilers, and the direct flux measurements proposed for the NOAA R/V Ron Brown will provide a firm basis for a central time series combining spatial and temporal averages. In addition to providing the wide range of cloud-precipitation discussed above, the ship and aircraft data will contribute to our understanding of the removal processes acting on aerosols over the tropical Atlantic, which is most important for mineral dust. These data will also contribute to the development of global-scale aerosol transport-removal models. 3.2 HIAPER The NCAR HIAPER (Fig. 3b) will be used mainly to deploy dropsondes between 0 and 15 N across the AMI. During the HIAPER transverse flights, dropsondes will be launched from the altitude of 12 km for every degree of latitude. Such transverse dropsonde deployment will measure instantaneous (in the sense of the large-scale circulation) meridional and vertical cross-sections through the AMI and the entire troposphere. No such cross-section through the AMI has ever been observed before. This AMI transverse flight pattern is similar to that adapted during the EPIC 2001 field campaign, with two major improvements. Dropsondes were deployed by C-130 from the altitude of 5.5 km from 0 to 12 N during the EPIC field campaign. The EPIC data therefore missed the high-level (10 12 km) meridional return flow and cannot be used to test the hypothesis that the shallow and deep meridional circulation occur alternatively because of the dominance of shallow vs. deep convection in the AMI (see AMI SPO). The EPIC dropsonde data are also limited to the south side of the ITCZ and cannot be used to examine the possibility that a similar shallow meridional circulation also exists on its northern side. Dropsondes deployed from the AMI HIAPER transverse flight pattern will remedy these two shortcomings of the EPIC data and allow an expansion of the investigation on the newly discovered shallow meridional circulation associated with the ITCZ. The boundary layer measurements made by C-130 transverse flights during the EPIC field campaign will not be repeated during the AMI field campaign due mainly to limited resources. Another major difference between the AMI and EPIC transverse flights is that dropsondes will be launched by HIAPER during both outbound and inbound flights during the AMI field campaign, whereas dropsondes were launched only during inbound flights during EPIC field campaign. To increase the chance that dropsondes launched by HIAPER outbound and inbound flights are independent samples, the HIAPER outbound and inbound flights will follow different tracks (Fig. 1). A recent study by Mapes et al. (2003) concludes that for rawinsondes, spatial and temporal sample differences become about equal for 6 hours or 200 km apart. This is consistent with an advection speed of 10 m 10

11 s -1, which is the right order of magnitude for mean easterly wind in the eastern equatorial Atlantic. Based on this, a minimum distance between the outbound and inbound flights is about 200 km. The outbound and inbound flight tracks can, therefore, be at 25 W and 23 W, respectively. The detailed flight pattern for HIAPER 23 W dropsondes is the following (Fig. 1): (1) Take off from Cape Verde airbase at Sao Vicente (16.51 N, W) and fly due southwest to reach 25 W, 15 N at the altitude of 12 km. (2) Fly due south and reach 25 W, 0 N at the altitude of 12 km with dropsondes launched for every degree of latitude. (3) Fly from 25 W, 0 N due east and reach 23 W, 0 N at 12 km with no dropsondes launched. (4) From 23 W, 0 N fly due north and reach 23 W, 15 N at 12 km with dropsondes launched every degree latitude. (5) Return to base from 15 N and 23 W with no dropsondes launched. The estimated flight duration is 9 hr, with 32 dropsondes launched on each flight. In addition to the dropsonde measurements, the standard (funded) HIAPER radiometric facility instrumentation package (spectral solar fluxes, UV actinic fluxes) could provide valuable information on cloud microphysics (cloud effective radius, liquid water path) along the flight tracks across the AMI. A well-coordinated combination of radiometric measurements from the HIAPER and C-130 aircraft could provide unprecedented information on cloud properties. A total of 150 flight hours of the HIAPER is requested, which allows16 flights, launching 512 dropsondes. The sampling strategy is to cover all weather conditions in the AMI to obtain samples that are representative of the mean state during the month of the AMI field campaign. 3.3 C-130 The NCAR C-130 (Fig. 3c) will be used mainly to measure the vertical profiles of aerosol microphysical, optical, and chemical properties. In addition, we plan to carry out vertically resolved measurements of cloud condensation nuclei (CCN) and ice nuclei (IN) spectra, spectral solar radiative fluxes, as well as cloud microphysics in the AMI. In particular, the C-130 instrumentation will measure size-dependent aerosol chemical composition, particle number size distributions, aerosol light scattering and absorption, scattering humidification, particle hygroscopicity, cloud related properties, and remotelysensed aerosol backscattering, column spectral aerosol optical depth (AOD) and spectral solar irradiance. The combination of these measurements will be used for characterizing the properties of dust, urban/industrial pollution, and smoke that affect the radiative and microphysical environments of evolving convection in the AMI. Eddy correlation of DMS fluxes will be used to quantify the mixing of SAL air into the marine boundary layer. The main objective of the C-130 measurements is to understand the relationships between the microphysical, chemical, radiative, and cloud-nucleating properties of aerosols. This will require the size-dependent chemical and physical characterization of the aerosols to enable local closure experiments on aerosol mass and optical properties. Some measurements (gravimetric mass, size-dependent chemistry, carbonaceous aerosols, and total aerosol samples) will require integration times of 30 minutes or more to get an adequate amount of sample, but others (AMS, APS, CN, optical properties) 11

12 have a much faster response and can therefore be used to look at smaller-scale spatial variability and detailed layering during vertical soundings. In putting together the C-130 instrumentation package, we will emphasize the need for measurements of the aerosol, cloud and radiation fields to require and accommodate comparable time scales and flight plans. Fast-response trace-gas measurements could be used to help identify the thin layers in which aerosols are often found and to support eddy-correlation flux measurements to quantify mixing. During ACE-Asia, sharply-defined and complex layering of dust and pollution was frequently observed but are often unresolved in chemical transport models. A mounting body of evidence in the peer-reviewed literature suggests that the sampling of super-micron aerosols is best performed with a Low Turbulence Inlet, which allows the passage of large aerosol particles such as the mineral dust expected in the SAL. Therefore, we propose to use the NCAR LTI to feed all of the relevant in situ aerosol observations aboard the C-130. Several types of flight patterns will be used to address the question of the impact of aerosols on the AMI. Fig. 4 shows a generic transverse flight, in which a combination of vertical profiles and level legs is used to observe the horizontal and vertical variability of aerosol properties. Transverse flights will be used to examine the scales of variability in aerosol composition as well as optical and microphysical impacts. This kind of flight will be used to resolve the dispute over gradients of aerosol concentrations within the SAL (e.g., Karyampudi et al., 1999). We anticipate that the C-130 flights will be closely coordinated with satellite overpasses. In particular, the coordination with the A-Train constellation of satellites, including the CALIPSO lidar (the first space-borne lidar system dedicated to aerosol measurements) will provide opportunities to compare the suborbital measurements of vertically-resolved aerosol properties to the satellite retrievals of aerosol profiles. In this way the validated satellite aerosol measurements can provide a regional context to the more detailed but localized aircraft aerosol measurements. When possible, the C-130 flights will also be coordinated with the HIAPER flights to benefit from transverse dropsondes and a combination of the radiometric measurements made aboard the two aircraft. Column-closure studies of aerosol mass and extinction, tied to satellite overpasses, will be used to assess the quality and consistency of the various C-130 aerosol data sets. By combining the best aerosol products derived from the column closure studies with the profiles of spectral solar radiative fluxes, we will assess the direct aerosol radiative forcing and hence the aerosol-induced heating of the SAL (Fig. 5). The general flight plan for such closure studies will call for the C-130 to be near the surface before and at satellite overpass time, making direct measurements of the spatial variability in spectral aerosol optical depth using an airborne sun photometer. The low-level leg will be followed by a rapid ascent during which the profile of aerosol extinction will be measured in situ using multiple methods at a range of wavelengths. The aircraft will then descend to interesting layers identified on the climb, taking the time to characterize the aerosol properties on extended level legs. The closure profiles will permit us to compare the sunphotometer-derived extinction with in situ derived aerosol extinction either from a combination of aerosol scattering and absorption or from a combination of particle size distributions with size-resolved aerosol chemical composition. The measurement of spectral net irradiance during these profiles would provide a further constraint on the 12

13 closure studies and a test of radiative transfer models used in climate models. Coordination of radiometric measurements from the HIAPER would be of great value because it can climb above virtually all aerosol and cloud layers and hence provide measurements of the albedo of cloud and aerosol layers. An additional method to obtain the direct aerosol radiative forcing of climate by aerosols in the SAL is the simultaneous measurement of aerosol optical depth (AOD) gradients and corresponding irradiance changes, yielding the change of spectral net irradiance per unit AOD, the so-called spectral aerosol radiative forcing efficiency. We will make it a priority to find and follow such AOD gradients to assess the radiative effects of aerosols in the SAL. Cloud microphysical properties of aerosols will be measured using a cloud-chambertype CCN spectrometer and an ice-nuclei detector, which we will use in cloud inflow regions (Fig. 2). It is hypothesized that mineral dust will become a better CCN when it has mixed with more pollutants (nitrate and sulfate coatings increase its water uptake), but they may make it less effective at ice nucleation. Paired nephelometers and particle sizers will measure the growth of particles and their scattering with humidity, which we will also relate to chemical composition. We will then fly in clouds (Fig 2) and use a counterflow virtual impactor (CVI) to look at the cloud nuclei, to quantify what fraction of the mineral particles we identified in inflow air is actually present in the observed cloud droplets. The C-130 instrumentation package for the AMI field campaign is summarized in the appendix. 3.4 Surface barometric pressure gauges The purpose of having two surface pressure gauges (Paroscientific model Met1-2, accuracy of 0.1 hpa) at 23 W is to calibrate the meridional gradient of surface pressure between the equatorial cold tongue and the AMI measured by the HIAPER dropsondes. NOAA/PMEL will provide a service contract to enhanced two PIRATA (ATLAS) moorings in 2006 at 0 and 10 N, 23 W. Under this service contract NOAA/PMEL will be responsible for the purchase, preparation, and deployment of the gauges, and for realtime and delayed-mode data processing, quality control, archiving and integrating the data into the ATLAS data system for a one-year mooring deployment. PMEL will fully comply with the AMI data policy (section 4.4) and will make preliminary data available to AMI PIs during the field campaign and quality controlled data to the JOSS AMI data archive as required by the AMI data policy. After the one-year deployment, PMEL is responsible for retrieving the gauges. The service contract will be priced to cover only the costs of the pressure sensors, with all other costs covered by PMEL. In exchange, the sensors will remain PMEL inventory to be used at its discretion after the one-year deployment. 3.5 Other observations The AMI 2007 field campaign will be augmented by the following observations: (a) AMMA upper-air sounding network The upper-air sounding network for AMMA (Fig. 6) will operate during AMMA enhanced observation period. Sounding data from this network during the AMI 2007 filed campaign will provide invaluable information of upstream conditions for the AMI targeting region. Such information will help interpret AMI data in term of sources of dry air and aerosol and the larger-scale circulations. The sounding data will also provide a rare chance to 13

14 directly compare the meridional circulation over land and ocean. Forcing for CRM and SCM derived from the AMI and AMMA observations also allow comparison studies of convection over land and ocean under similar climate conditions. (b) AMMA enhanced PIRATA mooring array Additional ALTAS moorings will be deployed at 23 W, 10 N and 14 N. The additional PIRATA moorings will provide surface meteorology observations that can be used to compare with HIAPER dropsonde observations. But most importantly, the additional PIRATA moorings provide an opportunity to deploy two surface pressure gauges (section 3.4) that are needed to calibrate surface pressure observations from HIAPER dropsondes. (c) Satellites A wide array of satellite products will be incorporated in AMI. MODIS observations will provide information of African aerosol outbreaks. MISR will provide more detailed information on aerosol properties. AURA, launched in July 2004, will provide a detailed picture of dust storm activity over Africa and the subsequent transport over the Atlantic, in the same way the TOMS has been so successfully used for this purpose for the past 25years. The AURA dust storm data can be used to initiate dust models (see below) which will be used to predict dust transport in the study region so as to better plan flight paths and profiles. The lidar aboard CALIPSO will provide periodic altitude profiles of aerosols which can then be assimilated into models to provide a clear picture of transport across the region. These satellite observations will be used in-field to help decision making on aircraft operation and in post-field data analysis. The data obtained in AMI will also contribute to the improvement of the interpretation of satellite products in the region and to the further development of retrieval algorithms. 3.6 Modeling The AMI data will be directly used in modeling studies to advance our knowledge on aerosol-cloud interaction and our ability of parameterizing this interaction in global climate models. In particular, the AMI data will be used in the following ways: (a) A new aerosol activation parameterization has recently been developed that can address the complexities introduced by the presence of externally-mixed and chemically-complex aerosol, at a modest computational cost (Nenes and Seinfeld, 2003; Fountoukis and Nenes, 2004). It treats aerosol with a size-dependant chemical composition; the effects of surface active species (organics), insoluble species, and slightly soluble species can thus be treated, provided that there is such information available. A unique feature of our parameterization framework is the ability to treat film-forming compounds that potentially affect the growth rate of droplets by modifying the water vapor accommodation coefficient. The new parameterization displays superior performance, in both accuracy and robustness, without demanding significant computational resources. When compared to a detailed numerical parcel model [Nenes et al., 2001] for 200 cases of inorganic aerosols and updraft velocities that encompass the range expected to be encountered in a global model simulation, the agreement is excellent. This new parameterization has been incorporated into a number of GCMs and SCMs (e.g., the NASA GISS, Goddard GCM, NASA GMI, UK GCM, Goddard SCM). The new aerosol activation parameterization has been evaluated against a wide range of the observational data collected during the NASA s Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) and the stratus regime evaluation was carried out 14

15 using data from Coastal STRatocumulus Imposed Perturbation Experiment (CSTRIPE). In addition to evaluating the performance of the parameterization, the AMI data will also be used to constrain the kinetics of growth parameters of cloud droplet formation. The water vapor accommodation coefficient, which expresses the probability that a water molecule is incorporated into a droplet upon collision with it, is a highly uncertain parameter that can have a profound impact on cloud droplet number. (b) A three-dimensional, high-resolution cloud-resolving model with explicit descriptions of aerosols and cloud microphysics as well as chemistry has been developed in past decade (e.g., Wang and Chang, 1993; Wang and Prinn, 2000; Ekman et al., 2004; Wang 2004a&b). The dynamics-physics module of this model consists of nonhydrostatic momentum equations, the continuity equations for water vapor and air mass density, the thermodynamic equation, and the equation of state (Wang and Chang, 1993). Also included are prognostic equations for the mixing ratios as well as number concentrations of four to seven types of hydrometeors (2 in liquid phase; 1-4 small ice particles; and a graupel). The microphysical transformations are formulated based on a two-moment scheme incorporating the size spectra of particles (Wang and Chang, 1993; Wang et al., 1995). A δ-four-stream radiation module based on Fu and Liou (1993) is incorporated in the model and it uses predicted concentrations of H 2 O, O 3, and hydrometeors to calculate radiative fluxes and heating rates. The chemistry sub-model currently predicts atmospheric concentrations of 25 gaseous and 8 aqueous chemical species (in both cloud droplets and raindrops, and thus 16 prognostic variables), including important aerosol precursors such as sulfate and nitrate and undergoing more than 100 reactions as well as transport and microphysical conversions (Wang and Chang, 1993; Wang and Prinn, 2000). Recently, a module of heterogeneous chemistry on ice particles has been developed and included in the model (Wang, 2004b). In particularly relevant to this proposed project, a chemistrysize-resolving aerosol module has been incorporated into the cloud-resolving model with newly added dust mode. We expect that the AMI field campaign could provide above mentioned aerosols and cloud structure data for model validation and also to restrain the model runs. With these data compared between models and observations, we could also use the cloud-resolving model to understand various factors determine the radiation and precipitation of tropical Atlantic ITCZ under the influenced of aerosols in the sensitivity study. (c) One critical aspect of running cloud-resolving and single-column models is to have reliable large-scale forcing (vertical velocity and advective tendencies of temperature, moisture, and momentum at time scales of several hours). In the absence of an atmospheric sounding array that can provide in situ observations of divergence field, such forcing must be derived from data assimilation products, such as global model (re)analyses. It is known that such data (re)analyses often suffer from large biases. The use of in situ observations to constrain (re)analyses data is therefore a necessary step to derive forcing needed by cloud-resolving and single-column models. The constrained variational analysis method of Zhang and Lin (1997) and Zhang et al. (2001) will be used for derive large-scale forcing from the AMI data. In this method, initial analysis of atmospheric winds, water vapor, and temperature from soundings will be adjusted by the minimal possible amount to satisfy the observed column 15

16 budgets of mass, water vapor, energy, and momentum. CRM and SCM forcing data from this approach have been widely used to study the modeling and parameterization of convection (e.g., Ghan et al. 2000; Xie et al. 2004, Xu et al. 2002). This same strategy will be applied to the AMI interface with the modeling community. Since AMI soundings will be sparse, the initial analysis will be made based on both atmospheric soundings and operational product before the variational adjustments. Error characteristics of the operational products will be estimated based on the available soundings. This strategy has been used in the DOE Atmospheric Radiation Measurement Program (ARM) (Xie et al., 2004) to derive CRM and SCM forcing data at its Southern Great Plain (SGP) site. High temporal resolution measurements of radar rainfall, surface meteorological conditions, surface latent and sensible heat fluxes, and the surface radiation measurements from the AMI ship and buoys, provide the complete lower boundary condition of the atmospheric column budgets of moisture, energy and momentum. Satellite radiation fluxes from the combination CERES and GOES provide constraints at the top of the atmospheric column. The vertical distribution of the lateral atmospheric exchanges of atmospheric mass, energy, water vapor, and momentum will then be variationally derived based on the sounding data and operational analysis subject to the constraints of the observed surface and top-of-the-atmosphere measurements. (d) The AMI data and analyses will be interpreted in terms of simple dynamics such as the zonally symmetric Sawyer-Eliassen equation (e.g., Hack et al. 1989), the associated forced potential vorticity response (e.g., Schubert et al. 1991), and a recently derived three dimensional balanced model which involves a generalization of the Sawyer-Eliassen equation. This latter model will prove useful in understanding what causes the depth of the meridional overturning within the AMI. In particular, using the AMI enhanced observations to describe the large-scale flow and heating patterns in conjunction with this balanced model should allow us to determine the degree to which the shallow overturning is forced by conservative processes (i.e., divergence of Q-vectors) or nonconservative processes (i.e., frictional and diabatic effects). In addition, the three dimensional formulation of this model will allow us to investigate the sensitivity of the shallow overturning within the AMI to the spatial structure (e.g., the E-W extent) of the forcing. Furthermore, the high resolution N-S cross sections provided by HIAPER dropsondes will allow accurate calculation of the potential vorticity structure of the ITCZ, leading to a better understanding of the E-W oriented vorticity filaments that are frequently observed in vorticity analyses of the ITCZ region computed from QuikSCAT surface winds and seen in EPIC2001 data. (e) A wide variety of chemical-aerosol transport models are currently available. In recent years there has been much effort on the development of dust source-transport models. Most current models have used the Univ. of Miami dust data from Barbados to test their performance [e.g., Ginoux et al., Mahowald et al., Tegen et al., Zender et al., Alpert et al., Westphal et al., etc.]. We would expect that many of these modelers will want to take an active part in running their models in support of the AMI field program so as to better test the models and further improve their performance. The availability of a broad range of models will greatly assist in the planning of field operations and the data obtained will, in turn, contribute to the further development of the models. 16

17 4. Project Management Project management and coordination for the AMI Program will be carried out by the AMI PI team, an AMI Project Office, and an AMI Advisory Committee. The AMI PI team currently consists of 13 scientists (Table 2) with expertise ranging from observations, modeling and theories on microphysics of aerosols and their interaction with cloud, mesoscale convection, air-sea interaction and atmospheric boundary layer, large-scale circulation and distribution of aerosol, and climate variability of the AMI. The AMI Project Office will consist mainly of the support team from UCAR/JOSS. The AMI Advisory Committee will include AMI leading PIs for each observation platform, facility managers, the AMI Project Office director (Operations Director), and program managers from funding agencies. The specific responsibilities of these three teams are described in the following. Table 2. AMI PI Team PI Affiliation Responsibility Chris Fairall NOAA/ETL R/V Ron Brown surface fluxes, soundings, wind profiler measurement and analysis Yochanan Kushnir Columbia University PI Team leader Brian Mapes University of Miami R/V Ron Brown precipitation radar analysis Athanasios Nenes Georgia Institute of Technology R/V Ron Brown aerosol measurement; aerosol SCM simulations David Parsons NCAR HIAPER dropsonde measurement and analysis Joseph Prospero University of Miami C-130 & R/V Ron Brown aerosol measurement; satellite aerosol analysis Jens Redemann Bay Area Environmental Research Institute C-130 aerosol & radiation measurement and analysis Wayne Schubert Colorado State University HIAPER dropsonde analysis; dynamic modeling Adam Sobel Columbia University HIAPER dropsonde analysis Chien Wang MIT CRM modeling Chidong Zhang University of Miami HIAPER dropsonde measurement and analysis Minghua Zhang State University of New York at Stony Brook CRM and SCM forcing derivation using AMI data Paquita Zuidema University of Miami R/V Ron Brown precipitation and cloud radar analysis 4.1 Field Management The AMI PI team, led by the Science Director, will have primary responsibility for setting priorities for the use of facility resources (e.g. aircraft flight hours, dropsondes) to meet project science objectives and design specific mission plans. They will make decisions about the priorities for each mission and coordinate flight missions by the two 17

18 airplanes (HIAPER and C-130). The team will also be responsible for data quality control and provide data to the AMI data center as required by the AMI data policy (section 4.2). The AMI PI team will request that UCAR/JOSS provide extensive support in areas of experiment planning, operations coordination/implementation, and data management. Such support will be overseen by the AMI Project Office, led by the Operations Director. Specific roles of the AMI Project Office and its support team include: a. maintain AMI WWW pages and project documentation; b. work with the AMI PI team to finalize the implementation plan (including the data policy and management plan); c. provide logistical coordination at the foreign site for U.S. participants including site survey, space, services, lodging, travel, and shipping; d. coordinate with AMMA to ensure the ship (R. Brown) operation will meet the scientific objectives of both AMMA and AMI Programs. e. set up an AMI operations center to provide a focus for mission planning, weather forecasting support, real-time decision making, facility coordination, research data collection, in field analysis activities, internet access and other communication needs; f. provide advance notification information and other required coordination with air traffic authorities at Cape Verde to seek approval and develop notification strategies for conducting coordinated aircraft missions at multiple altitudes in the AMI domain; g. take all necessary measures for the heath and safety of all AMI field participants; h. support real-time operational requirements of the field phase (i.e. aircraft/ship coordination, execution of mission science objectives, data ingest, logistical support, communication etc.) utilizing NCAR/EOL RDCC (Real-time Display and Coordination Center) and the JOSS Field Catalog; i. keep track of facility resource utilization information and report regularly to the Science Director; coordinate the forecasting and nowcasting support for AMI, j. provide logistic support for pre-field and post-field meetings and workshops, and k. provide data management support (see section 4.2). The AMI Operations Center is expected to be located at an airport in the Cape Verde Islands. Site surveys will be required to assure the adequacy of the airport site for aircraft operations and operations center support services. AMI scientists recognize that there will be a major planning effort required to organize and prepare for the complex field deployment. Discussions will be required with regional air traffic authorities at Cape Verde and Dakar, Senegal to seek approval and develop notification strategies for conducting coordinated aircraft missions at multiple altitudes in the AMI domain. The Operations Director will lead a daily planning meeting to update all participants on operations and weather and discuss future missions. An AMI daily operations summary will be prepared and made available via the Internet for all project participants. The AMI Advisory Committee will oversee the preparation, implementation, and operation of the AMI field campaign. The AMI PI team and Project Office will report to the Advisory Committee. 4.2 Data policy and management 4.2a AMI data policy 18

19 1. All investigators participating in AMI must agree to promptly submit their data to the AMI Data Archive Center to facilitate intercomparison of results, quality control checks and inter-calibrations, as well as an integrated interpretation of the combined data set and preliminary use of the data for model simulations. 2. All data shall be promptly provided to other AMI investigators upon request. A list of AMI investigators will be maintained by the AMI Project Office and will include the Principle Investigators (PIs) directly participating in the field experiment as well as collaborating scientists who have provided guidance in the planning and analysis of AMI data. 3. During the initial data analysis period (one year following the end of the field phase), if data are provided to a third party (journal articles, presentations, research proposals, other investigators) the investigator who collected the data must be notified first. This initial analysis period is designed to provide an opportunity to quality control the combined data set as well as to provide the investigators ample time to publish their results. 4. All data will be considered public domain not more than one year following the end of the AMI field phase. Data can be opened to the public domain earlier depending on the discretion of the data provider. There will be exceptions where extensive data processing is required. 5. Any use of the data will include acknowledgment (i.e., citation). Co-authorship during the one-year analysis phase will be at the discretion of the investigator(s) who collected the data. 6. All data should be in common, platform independent format of ASCII or NetCDF. 4.2b AMI data management The development and maintenance of a comprehensive and accurate data archive is a critical step in meeting the science objectives of AMI with a major objective being to make as complete a dataset as possible available to the community as soon as possible following the field phase. Oversight of AMI data management will come from the AMI Scientific Steering Committee in collaboration with the AMI Project Office and the establishment of a Data Management Working Group (DMWG). The end-to-end approach to field program data management, coordinated by the DMWG, begins with the early planning that involves the AMI community (including questionnaires) to: (1) determine the data requirements; (2) survey the ancillary operational and research network data sources; and (3) determine any special processing and archive requirements. These requirements along with details about the key components of data collection, archival and distribution strategies to meet project objectives are compiled into the data management plan document. A thorough data management plan and strategy are paramount to effective data sharing, integrated analyses, and long-term data stewardship. Once real-time project data needs are established, arrangements are made with remote data sources and field facilities to provide data to the AMI Field Operations Center. For example, a web-based tool used to ingest and display these operational and preliminary research data products and project documentation for making decisions and evaluating project progress is the In-Field Catalog. Following the field phase, data 19

20 archive and distribution will follow the AMI data policy stated in section 4.4a. The operational network data will be submitted to the AMI archive, where appropriate reformatting, processing, and quality assurance are applied. Research (or experimental) datasets will be processed and submitted to the archive by the respective PIs after they complete their processing and quality control. All project related data will be disseminated to the AMI community through a one-stop web access utilizing distributed archive architecture. The final phase for data management strategy is long-term data stewardship. All metadata will be compiled using international standards (e.g. ISO19115) for inclusion into various data catalogs such as the Global Change Master Directory. Good stewardship ensures that AMI data will remain accessible and accurately documented for decades after the field program ends. The AMI Project Office will be responsible for the data management. 5. References Chenet, Sylvain, 2004: A multiple mass flux parameterization for the surface-generated convection. Part II: Cloudy Cores. J. Atmos. Sci., 61, Ekman, A. M. L., C. Wang, J. Wilson, and J. Strom, 2004: Explicit simulations of aerosol physics in a cloud-resolving model: A sensitivity study based on an observed convective cloud, Atmos. Chem. Phys., 4, Fairall, C. W., E. F. Bradley, D. P. Rogers, J. B. Edson, and G. S. Young, 1996: Bulk parameterization of air-sea fluxes for Tropical Ocean - Global Atmosphere Coupled-Ocean Atmosphere Response Experiment. J. Geophys. Res., 101, Fairall, C. W., E. F. Bradley, J. E., Hare, A. A. Grachev, and J. B. Edson, 2002: Bulk parameterization of air-sea fluxes: Updates and verification of the COARE algorithm. J. Clim., 16, Fountoukis, C. and Nenes, A., Continued Development of a Cloud Droplet Formation Parameterization for Global Climate Models, J.Geoph.Res., accepted for publication, 2005 Fu, Q., and K. N. Liou, 1993: Parameterization of the radiative properties of cirrus clouds. J. Atmos. Sci., 50, Ghan S., other co-authors, and M. H. Zhang, 2000: An intercomparison of single-column model simulations of summertime midlatituide continental convection. J. Geophys. Res., 105, D2, Hack, J. J., W. H. Schubert, D. E. Stevens, and H.-C. Kuo, 1989: Response of the Hadley circulation to convective forcing in the ITCZ. J. Atmos. Sci., 46, Karyampudi, VM, et al., 1999: Validation of the Saharan Dust Plume Conceptual Model Using Lidar, Meteosat, and ECMWF Data. Bull. Amer. Meteor. Soc., 80, Krueger, S. K., and M. Zulauf, 1997: Parameterization of mesoscale enhancement of large-scale surface fluxes over tropical oceans. Proceedings 12th Symposium on Boundary Layers and Turbulence, 28 July-1 August, Vancouver, BC, American Meteorological Society, Boston, MA.,

21 Mapes, B. E., P. E. Ciesielski, and R. H. Johnson, 2003: Sampling errors in rawinsondearray budgets. J. Atmos. Sci., 60, Nenes, A., and J. Seinfeld, 2003: A new parameterization of aerosol activation appropriate for climate models, J. Geophys. Res., 108, art. no Nenes, A., et al., Kinetic limitations on cloud droplet formation and impact on cloud albedo, Tellus, 53, , Redelsperger, J. L. F. Guichard, and S. Mondon, 1998: Parameterization of mesoscale enhancement of surface fluxes for regional and large scale models. J. Clim., 13, Rozbicki, J.J., G. S. Young, L.Y. Qian, 1999: Test of a convective wake parameterization in the single-column version of CCM3. Mon. Wea. Rev., 127, Schubert, W. H., P. E. Ciesielski, D. E. Stevens, and H.-C. Kuo, 1991: Potential vorticity modeling of the ITCZ and the Hadley circulation. J. Atmos. Sci., 48, Siebesma, A. P. and 16 coauthors, 2004: Cloud representation in general circulation models over the norther Pacifc Ocewan : A EUROCS intercomparisons study. Tong, C., J. C. Wyngaard, S. Khanna, and J. G. Brasseur, 1998: Resolvable and subgridscale measurement in the atmospheric surface layer: Techniques and issues. J. Atmos. Sci., 55, Vickers, D. and S. K. Esbensen, 1998: Subgrid surface fluxes in fair weather conditions during TOGA COARE: Observational estimates and parameterization. Mon. Wea. Rev., 126, Xie S., R. T. Cederwall, M. Zhang, 2004: Developing long-term single-column model/cloud system resolving model forcing data using numerical weather prediction products constrained by surface and top of the atmosphere observations, J. Geophys. Res., 109, D01104, doi: /2003jd Xie et al., 2002: Intercomparison and evaluation of cumulus parameterization under summertime midlatitude continental conditions. Quarterly Journal of the Royal Meteorology Society, 128, Xu et al., 2002: An intercomparison of cloud-resolving models with the ARM summer 1997 IOP data. Quarterly Journal of the Royal Meteorology Society, 128, Young, G. S., D. V. Ledvina, and C. W. Fairall, 1992: Influence of precipitating convection on the surface energy budget observed during a TOGA pilot cruise in the tropical western Pacific Ocean. J. Geophys. Res., 97, Young, G. S., S. M. Perugini, and C. W. Fairall, 1995: Convective wakes in the equatorial Pacific during TOGA. Mon. Wea. Rev., 123, Wang, C., 2004a: A modeling study of the response of tropical deep convection to the increase of CCN concentration. 1. Dynamics and microphysics, submitted to J. Geophys. Res.. Wang, C., 2004b: A modeling study on the response of tropical deep convection to the increase of CCN concentration. 2. Radiation and chemistry, submitted to J. Geophys. Res. Wang, C., and J. S. Chang, 1993: A three-dimensional numerical model of cloud dynamics, microphysics, and chemistry, 1. Concepts and formulation, J. Geophys. Res., 98, Wang, C., and R. G. Prinn, 2000: On the roles of deep convective clouds in tropospheric chemistry. J. Geophys. Res. 105,

22 Wang, C., P. J. Crutzen, V. Ramanathan, and S. F. Williams, 1995: The role of a deep convective storm over the tropical Pacific Ocean in the redistribution of atmospheric chemical species. J. Geophys. Res., 100(D6), Zhang, M. H., and J. L. Lin, 1997: Constrained variational analysis of sounding data based on column-integrated budgets of mass, heat, moisture and momentum: approach and application to ARM measurements, J. Atmos. Sci., 54, Zhang, M. H., J. L. Lin, R. T. Cederwall, J. J. Yio, and S. C. Xie, 2001: Objective analysis of the ARM IOP data: method and sensitivity. Monthly Weather Review. 129, Zuidema, P., B. Mapes, J. Lin, and C. Fairall, submitted (April, 2005): Cloud vertical structure in the eastern tropical Pacific. J. Atmos. Sci., Available through 22

23 Appendix C-130 Instrumentation Package for AMI Measurement Method/Instrument Derivable quantities (in addition to primary measurement) 1) Aerosol 1) a) Aerosol Microphysics Total particle number concentration, between and 0.01µ m (ultrafine CN), fractional volatility Volatile and refractory sizes below 0.5µm, size selected mixing states Particle size, morphology, internal structure Size-resolved hygroscopicity / submicron size distribution Aerosol size distribution (~ µm) Aerosol particle size distributions TSI condensation particle counters coupled with heaters operated at 300 C Thermal differential mobility analyzer (DMA) Ambient aerosol filter samples + electron microscopy (SEM, TEM) High flow DMA / TDMA TSI 3321 aerodynamic particle sizer (APS) PCASP, FSSP-300, FSSP- 100 RH-dependent optical properties, CCN spectra, submicron dust size distribution Supermicron scattering coefficient, supermicron dust size distribution Total and nonvolatile aerosol size distribution, 0.1 to 7 µm Optical particle counter (OPC) 1) b) Aerosol optics Aerosol light scattering, sub-µ and total, at 450, 550 and 700nm Scattering Humidification (i.e., Scattering at multiple RH - e.g., dry, 50 and 80%) Aerosol light extinction and scattering, 675 and 1550nm (possibly 375 and 410nm) Aerosol light absorption, sub-µ and total, at 468, 535, and 655nm 3-wavelengths TSI nephelometer, impactor for separation of sub-µ fraction Custom f(rh) system (based on Radiance Research nephelometers) Cavity Ring Down (CRD) 3-wavelengths Particle Soot Absorption Photometer (PSAP), impactor for separation of sub-µ fraction Spectral aerosol single scattering albedo (in connection with PSAP), aerosol hemispheric backscattering Aerosol absorption, aerosol single scattering albedo 23

24 Aerosol light scattering and absorption at 405, 532, and 870 nm Profiles of aerosol backscattering (300, 578, 600, 1064 nm), aerosol depolarization, zenith and nadir PASS (photoacoustic absorption and scattering spectrometer) Multi-wavelength UV- DIAL/backscatter lidar Aerosol extinction, aerosol single scattering albedo, estimate of black carbon conc. Profiles of aerosol backscattering and extinction (532 nm, at 1064nm backscatter only), aerosol depolarization, zenith or nadir Column aerosol optical depth, AOD High-spectral resolution lidar (HSRL) 14-channel Ames Airborne Tracking Sunphotometer, AATS-14 Lidar ratio (extinction/backscatter) at 532 nm AOD at 13 discrete wavelengths ( nm), water vapor column, spectral aerosol extinction profiles 1) c) Aerosol chemistry Total gravimetric aerosol mass, major anions and cations Total Aerosol Sampler (TAS), IC analysis, Nuclepore filters for SEM analyses Size resolved aerosol mass, major anions and cations 5-stage MOUDI cascade impactor ( µm), IC analysis Total organic and elemental carbon Sunset Labs semicontinuous EC/OC analyzer, quartz filters, EGA analysis Submicron Organic Functional Groups Single Particle Organic Functional Groups Particle composition Submicron Aerosol Size- Resolved Chemical Composition FTIR submicron filters NEXAFS on particles 0.2 to 10 micron Ambient aerosol filter samples + electron microscopy (SEM, TEM) Time-of-Flight Aerosol Mass Spectrometer (ToF-AMS) Organic functional group and OC composition of submicron particles Single particle and size dependent composition of organic functional groups, formation mechanisms/rates Mass concentrations and size distributions of non-refractory sulfate, nitrate, ammonium, chloride, and organics 2) Clouds 2) a) Cloud microphysics 24

25 CCN concentration at multiple supersaturations DMT CCN counter Cloud particle size distributions FSSP-300, FSSP-100 (modified sampling to prevent drop breakup) Cloud particle and hydrometeor images OAP 2D-C, OAP 2D-P, CPI Hygroscopic growth, if coupled to TDMA, [CCN] as fn(supersaturation) Ice nuclei (IN) concentration Liquid water content Continuous flow diffusion chamber (CFDC) PMS/King Probe (PLWCC) Gerber PVM-100 [IN] as fn(t,rh) 2) b) Cloud chemistry Cloud droplet residue Filter samples + Counterflow Virtual Impactor (CVI) + electron microspcopy (SEM, TEM) 3) Radiation 3) a) Solar Solar Spectral Irradiance Direct Solar Beam Transmission Solar Spectral Flux Radiometers, up- and downwelling, nm, preferably on stabilized platform 14-channel Ames Airborne Tracking Sunphotometer, AATS-14 Solar spectral net irradiance, cloud albedo, cloud effective radius and liquid water path (LWP), profiles of net flux divergence, hence heating rates AOD at 13 discrete wavelengths ( nm), water vapor column, spectral aerosol extinction profiles 25

26 7. List of Acronyms AMI Atlantic Marine ITCZ AMMA African Monsoon Multidisciplinary Analysis AMS - AOD aerosol optical depth APS ATLAS Autonomous Temperature Line Acquisition System CALIPSO - Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation CCN cloud condensation nuclei COARE Coupled Ocean-Atmospehere Response Experiment CN cloud nucleation CRM cloud resolving model CVI - counterflow virtual impactor DMWG Data Management Working Group DMS EOL Earth Observational Laboratory EPIC Eastern Pacific Investiation of Climate GATE GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment GCM global climate model HIAPER High-Performance Instrumented Airborne Platform for Environment Research IN ice nuclei ITCZ Intertropical Convergence Zone JOSS Joint Office of Science Support LTI MODIS - Moderate Resolution Imaging Spectroradiometer NCAR National Center for Atmospheric Research NOAA National Oceanic and Atmospheric Administation PIRATA Pilot Research Moored Array in the Tropical Atlantic PMEL Pacific Marine Environment Laboratory QuikSCAT - microwave scatterometer SeaWinds on the QuikBird satellite SAL Saharan Air Layer SCM single-column model SST sea surface temperature TOMS total ozone measurement sensor UCAR University Corperation for Atmospheric Research 26

27 Figure 1 Horizontal schematic diagram of the general design of the AMI Field Campaign (2007). Red arrows mark HIAPER flight tracks (at 12-km altitude). Blue dashed box indicates the area of C130 flight missions (see Figs 2, 5 and 6). The GATE hexagon is included for reference. C130 Aerosol Flights HIAPER Dropsonde Flights Ronald H. Brown * o o Surface gauges GATE (June 15 - September 23, 1974)

28 12 km 6 km 1 km surface Equator 10 N 15 N Figure 2 Vertical-meridional diagram (at 23 W) of the general design of the AMI field campaign Tall cloud represents deep convection in the AMI. Thin black arrows illustrate envisioned meridional overturning circulations associated with the AMI. Thick red arrow marks the altitude and latitudinal range of HIAPER flight. Thin vertical dashed lines indicate the coverage of HIAPER dropsondes. Thick blue lines mark 30 minute C- 130 aerosol sampling legs. The position of R/V Ron Brown is marked by the ship symbol; dark yellow circle and lines indicate C-band radar coverage. Triangles indicate the latitudes of the enhanced PIRATA mooring array; the two with surface pressure gauges are marked by green.

29 Figure 3 Main observational platform for the AMI field campaign (a) NOAA R/V Ronold H. Brown. (b) NCAR HIAPER aircraft. (c) NCAR C- 130 aircraft. (a) (b) (c)

30 Figure 4 C-130 wall flight profile: In this LITE objectively analyzed lidar backscatter image of the SAL along 22W (from Karyampudi et al., BAMS, 80, , 1999), warmer colors represent higher aerosol backscatter. The black lines represent proposed C-130 legs, starting with a profile to 6 km, then a lidar leg above the SAL, and a sounding to the surface. It ends with characterization legs at three altitudes (each spanning about 6 degrees of latitude) to characterize the variability within interesting levels identified by the lidar and the profile. A final profile would be appended if time permits. The dashed white line represents an overflight by HIAPER, dropping radiosondes.

31 Figure 5 Oblique view of a rapid vertical profile with the level legs for charachterizing layers.

32 Figure 6 Map of AMMA upper-air sounding network ( ). Courtesy of Christopher Thorncroft.