4DWX TAMDAR Evaluation

Projects

Overview

Objective

The purpose of this effort is to evaluate the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) system data for the advancement of mesoscale weather analyses and short-term (0 - 48 hour) forecasts, and to explore opportunities for applying the data and the modeling system to various weather-critical governmental and industrial practices.

Description

Mesoscale (10 - 2000 km) meteorological data assimilation and prediction are challenging, partly due to the sparseness of observations, especially in the upper atmosphere. In the past 15 years, a number of measurement platforms, e.g. wind profilers, commercial aircraft reports, satellite measurements, and others, have been developed to enhance upper-air observations. Despite these advances, the present systems are not sufficient for mesoscale data assimilation and prediction. Recently, AirDat LLC., a Denver-based company, has been working with NASA, to develop and implement a new sensor, called TAMDAR.

The TAMDAR system uses the regional airlines to produce weather observations in the lower troposphere. These data provide more accurate and complete mesoscale weather information with much higher time and space density than other data sources. In collaboration with AirDat LLC., NCAR/RAL developed a TAMDAR-based mesoscale forecasting system. This system is built around the NCAR/ATEC (Army Test and Evaluation Command) real-time multiscale, rapid-cycling, four-dimensional data assimilation and forecast (RTFDDA) system. The NCAR-RTFDDA system has been employed to support AirDat's TAMDAR implementation and data operation through real-time data assimilation and forecasting. The system is also used as a tool for studying new data assimilation strategies that optimize the TAMDAR data impact on mesoscale NWP.

Funding:

AirDat LLC | NASA | FAA

Operations

GLFE AND RTFDDA Modeling

To explore the potential of TAMDAR in improving regional short-term forecasts, a RTFDDA system was developed and has been operational on an AirDat Linux cluster. The forecast system has three domains, with 36, 12 and 4-km grid sizes respectively. The 12-km mesh covers all Mesaba Airlines regional flight airports and the neighboring regions affected by TAMDAR data.

In order to better resolve the regions of interest, a movable 4-km domain is nested in the 12-km domains. Owing to the limitation of the computation capability of the available cluster, the model system has been operated mostly with the two coarse domains (36/12-km) during GLFE.

In the late 2004, a pilot demonstration TAMDAR field program over the Great Lakes area, named the Great Lakes Field Experiment (GLFE), was jointly conducted by NASA, NOAA/FSL, NWS (National Weather Services), FAA, NOAA, Mesaba Airlines and AirDat. During GLFE, AirDat equipped 63 Mesaba Airlines’ turboprop SAAB 340 aircrafts with TAMDAR sensors that measure both conventional meteorological variables including temperature, pressure, winds and humidity as well as icing, turbulence and GPS heights. In a typical day, these instrumented aircraft make about 400 flights a day, providing about 800 soundings at the regional and major airports in the region since Jan. 2005. At present, AirDat LLc, and NASA are in the process of enhancing TAMDAR sensors and implementing them onto more regional airlines.

Real-Time Modeling Products

Two identical forecast systems are running in parallel, with one system ingesting the extra TAMDAR data and the other using standard RTFDDA data only. Both systems are running in real-time with 3-hr cycles with 12-hr forecasts in each cycle. The boundary and the initial conditions at cold-starts are provided using NCEP NAM (North America Model) model data. A data quality control procedure based on Liu et al (2004) was adapted to assure TAMDAR data quality, which not only prescreened problematic and unrepresentative data, but also provided valuable information for real-time TAMDAR quality assurance upstream of the TAMDAR data collection and dissemination. The model products are provided in real-time to AirDat and others in the communities.

A comparison of the RTFDDA, RUC-13 and NAM 3-hour accumulation with the NCEP STAGE IV analysis, ending at 00Z 15 Aug. 2005. Dashed lines mark convective rain bands based on the STAGE IV rain analysis.

Technology

Real-Time Four Dimensional Data Assimilation (RTFDDA)

RT-FDDA refers to the real-time assimilation of 4DWX weather data. RT-FDDA was developed to provide short-term, high-resolution forecasts using the most recent input data from sensors. This quick turnaround from input to output is essential for creating and delivering timely weather forecasts. RT-FDDA takes input from surface observations, satellite reports, automated weather stations, and other sources. RT-FDDA is deployed and in use at White Sands Missile Range in New Mexico and Yuma Proving Ground in Arizona.

AIRDAT Linux Cluster

AirDat LLc provides three rack-mounted PC clusters for the modeling research and operations. Two parallel RTFDDA systems have been running on a 20-node cluster since December 2004. A 5-node mini-cluster was set up in the spring of 2006 to run a RTFDDA modeling system in support of TAMDAR data quality control. Recently, a third 20-node cluster was purchased and installed at AirDat LLc, which will support various extended TAMDAR-related modeling research and development activities.

NCEP NAM (North American Model)

NCEP NAM information provided by NOAA.

Resources

Conference Publications and Presentations

Daniels, T. S., W. R. Moninger and R. D. Mamrosh, 2006: Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Review. 10th IOAS-AOLS, AMS, Atlanta, 29 Jan – 2 Feb. 2006. (pdf) (html)

Liu, Y., W. Yu, F. Vandenberghe, A. Hahmann, T. Warner and S. Swerdlin, 2006: Assimilation of diverse meteorological datasets with a four-dimensional mesoscale analysis and forecast system. 10th IOAS-AOLS, AMS, Atlanta, 29 Jan – 2 Feb. 2006. Paper 2.8. (pdf) (html)

Jacobs, N., Y. Liu, and C. Druse, 2006: Evaluation of temporal and spatial distribution of TAMDAR data in short-range mesoscale forecasts. 10th IOAS-AOLS, AMS, Atlanta, 29 Jan – 2 Feb. 2006. (pdf) (html)

Liu, Y., M. Anderson, S. Swerdlin, L. Carson, M. Ge, W. Yu and T. Warner, 2005: Mesoscale data assimilation and prediction with commercial aircraft (TAMDAR) observations. BACIMO-2005, 10-12 Oct. 2005. Monterey, CA. (pdf)(html)

Liu, Y., F. Vandenberghe, S. Low-Nam, T. Warner and S. Swerdlin, 2004: Observation-quality estimation and its application in the NCAR/ATEC real-time FDDA and forecast (RTFDDA) system. 16th Conference on Numerical Weather Prediction, Seattle, Washington. January, 2004. (pdf) (html)

Liu, Y., S. Low-Nam, R.-S. Sheu, L. Carson, C. Davis, T. Warner, J. Bowers, M. Xu, H.-M. Hsu and D. Rife, 2002: Performance and enhancement of the NCAR/ATEC mesoscale FDDA and forecast system. 15th Conference on Numerical Weather Prediction, 12-16 August 2002, San Antonio, Taxes, 399-402. (pdf) (html)

Participants

Sponsor

AirDat LLC
AirDat operates a sensor network for collecting upper air data in near real time. The aircraft-mounted sensor, called TAMDAR (Tropospheric Airborne Meteorological Data Reporting), transmits observations via satellite to AirDat's data center, where they are processed, archived and distributed. TAMDAR supplements existing data sources with improved temporal and spatial coverage and richer data sets for better weather reporting and forecasting. AirDat is now deploying TAMDAR sensors to provide upper air data for the continental United States and other parts of the world.

NASA
Weather Accident Prevention Project

FAA

Collaborator

NOAA/GSD
The Global Systems Division has performed several tasks to help evaluate the quality of this sensor suite and its impact on numerical weather prediction models.

NWS

Mesaba Airlines
Mesaba Airlines is a subsidiary of MAIR Holdings, Inc (NASDAQ-MAIR) and operates as a Northwest Airlink affiliate under code-sharing agreements with Northwest Airlines.

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