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309 records · Page 18

Convection and Easterly Wave Structure Observed in the Eastern Pacific Warm-Pool during EPIC-2001

During September-October 2001, the East Pacific Investigation of Climate Processes in the Coupled Ocean-Atmosphere System (EPIC-2001) ITCZ field campaign focused on studies of deep convection in the warm-pool region of the East Pacific. In addition to the TAO mooring array, observational platforms deployed during the field phase included the NOAA ship RN Ronald H. Brown, the NSF ship RN Horizon, and the NOAA P-3 and NCAR C-130 aircraft. This study combines C-band Doppler radar, rawinsonde, and surface heat flux data collected aboard the RN Brown to describe ITCZ convective structure and rainfall statistics in the eastern Pacific as a function of 3-5 day easterly wave phase. Three distinct easterly wave passages occurred during EPIC-2001. Wind and thermodynamic data reveal that the wave trough axes exhibited positively correlated U and V winds and a slight westward phase tilt with height. A relatively strong (weak) northeasterly deep tropospheric shear followed the trough (ridge) axis. Temperature and humidity perturbations exhibited mid-to upper level cooling (warming) and drying (moistening) in the northerly (trough and southerly) phase. At low levels warming (cooling) occurred in the northerly (southerly) phase with little change in the relative humidity, though mixed layer mixing ratios were larger during the northerly phase. When composited, radar, sounding, lightning and surface heat flux observations suggest the following systematic behavior as a function of wave phase: approximately zero to one quarter wavelength ahead of (behind) the wave trough in northerly (southerly) flow, larger (smaller) CAPE, lower (higher) CIN, weaker (stronger) tropospheric shear, higher (lower) conditional mean rain rates, higher (lower) lightning flash densities, and more (less) robust convective vertical structure occurred. Latent and sensible heat fluxes reached a minimum in the northerly phase and then increased through the trough, reaching a peak during the ridge phase (leading the peak in CAPE). From a radar echo coverage perspective, larger areas of light rain and slightly larger (10%) area averaged rain rates occurred in the vicinity of, and just behind, the trough axes in southerly flow. Importantly, the transition in convective structure observed across the trough axis when considered with the relatively small change in area mean rain rates suggests the presence of a transition in the vertical structure of diabatic heating across the easterly waves examined. The inferred transition in heating structure is supported by radar diagnosed divergence profiles that exhibit convective (stratiform) characteristics ahead of (behind) the trough.

Peterson, Walter A.↗

Evaluation of the MODIS Collection 6 Multilayer Cloud Detection Algorithm Through Comparisons with Cloudsat Cloud Profiling Radar and CALIPSO CALIOP Products

Since multilayer cloud scenes are common in the atmosphere and can be an important source of uncertainty in passive satellite sensor cloud retrievals, the MODIS MOD06 and MYD06 standard cloud optical property products include a multilayer cloud detection algorithm to assist with data quality assessment. This paper presents an evaluation of the Aqua MODIS MYD06 Collection 6 multilayer cloud detection algorithm through comparisons with active Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products that have the ability to provide cloud vertical distributions and directly classify multilayer cloud scenes and layer properties. To compare active sensor products with an imager such as MODIS, it is first necessary to define multilayer clouds in the context of their radiative impact on cloud retrievals. Three main parameters have thus been considered in this evaluation: (1) the maximum separation distance between two cloud layers, (2) the thermodynamic phase of those layers and (3) the upper-layer cloud optical thickness. The impact of including the Pavolonis–Heidinger multilayer cloud detection algorithm, introduced in Collection 6, to assist with multilayer cloud detection has also been assessed. For the year 2008, the MYD06 C6 multilayer cloud detection algorithm identifies roughly 20% of all cloudy pixels as multilayer (decreasing to about 13% if the Pavolonis–Heidinger algorithm output is not used). Evaluation against the merged CPR and CALIOP2B-CLDCLASS-lidar product shows that the MODIS multilayer detection results are quite sensitive to how multilayer clouds are defined in the radar and lidar product and that the algorithm performs better when the optical thickness of the upper cloud layer is greater than about 1.2 with a minimum layer separation distance of 1 km. Finally, we find that filtering the MYD06 cloud optical properties retrievals using the multilayer cloud flag improves aggregated statistics, particularly for ice cloud effective radius.

MODIS↗

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗