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NASA NTRS1984

Recent examples of mesoscale numerical forecasts of severe weather events along the east coast

Mesoscale numerical forecasts utilizing the Mesoscale Atmospheric Simulation System (MASS) are documented for two East Coast severe weather events. The two events are the thunderstorm and heavy snow bursts in the Washington, D.C. - Baltimore, MD region on 8 March 1984 and the devastating tornado outbreak across North and South Carolina on 28 March 1984. The forecasts are presented to demonstrate the ability of the model to simulate dynamical interactions and diabatic processes and to note some of the problems encountered when using mesoscale models for day-to-day forecasting.

Kocin, P. J.↗

NASA NTRS2009

Adjoint-Based Diagnostics in Atmospheric Data Assimilation

With the adjoint of a data assimilation system, the impact of any or all assimilated observations on measures of forecast or analysis skill can be estimated accurately and efficiently. The approach is especially well-suited for assessing the impact of hyper-spectral satellite instruments on numerical weather forecasts because it easily allows aggregation of results in terms of individual data types, channels or locations, all computed simultaneously based on a single pass of the Adjoint- system. This talk 'provides a general overview of the use of Adjoint-based diagnostic tools in data assimilation. We will focus on the theoretical basis and practical implementation of these tools, as well as their application to specific problems. Adjoint-based Impact calculations will be compared with results from standard observing system experiments (OSEs) and their application to related problems, such as the calibration of Observing System Simulation Experiments (OSSEs) will be discussed.

Gelaro, Ronald↗

NASA NTRS2002

Aircraft Icing Weather Data Reporting and Dissemination System

The long-term operational concept of this research is to develop an onboard aircraft system that assesses and reports atmospheric icing conditions automatically and in a timely manner in order to improve aviation safety and the efficiency of aircraft operations via improved real-time and forecast weather products. The idea is to use current measurement capabilities on aircraft equipped with icing sensors and in-flight data communication technologies as a reporting source. Without requiring expensive avionics upgrades, aircraft data must be processed and available for downlink. Ideally, the data from multiple aircraft can then be integrated (along with other real-time and modeled data) on the ground such that aviation-centered icing hazard metrics for volumes of airspace can be assessed. As the effect of icing on different aircraft types can vary, the information should be displayed in meaningful ways such that multiple types of users can understand the information. That is, information must be presented in a manner to allow users to understand the icing conditions with respect to individual concerns and aircraft capabilities. This research provides progress toward this operational concept by: identifying an aircraft platform capable of digitally capturing, processing, and downlinking icing data; identifying the required in situ icing data processing; investigating the requirements for routing the icing data for use by weather products; developing an icing case study in order to gain insight into major air carrier needs; developing and prototyping icing display concepts based on the National Center for Atmospheric Research's existing diagnostic and forecast experimental icing products; and conducting a usability study for the prototyped icing display concepts.

Bass, Ellen J.↗

NASA NTRS2007

Recent Theoretical Advances in Analysis of AIRS/AMSU Sounding Data

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major applications. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products. Version 5 also allows for accurate quality controlled AIRS only retrievals, called "Version 5 AO retrievals" which can be used as a backup methodology if AMSU fails. Examples of the accuracy of error estimates and quality controlled retrieval products of the AIRS/AMSU Version 5 and Version 5 AO algorithms are given, and shown to be significantly better than the previously used Version 4 algorithm. Assimilation of Version 5 retrievals are also shown to significantly improve forecast skill, especially when the case-by-case error estimates are utilized in the data assimilation process.

Susskind, Joel↗

NASA NTRS1976

Interactive applications of satellite observations and mesoscale numerical models

The impact of numerical weather prediction (NWP) and satellite meteorology on operational weather forecasting has become overwhelming in the past few years. The paper looks toward the merger of these technologies in making short range 6-18 h forecasts through the use of mesoscale NWP models. A short-range (2-18 h) mesoscale forecast system envisioned for the near future is described that includes four components: hydrodynamic numerical models, large-scale and mesoscale; satellites, polar orbiting for high latitudes and geostationary for low latitudes; mesoclimatology, derived in large part from satellite data; and special-purpose simple models and empirical relations. It is important that the components of the forecast system be developed in parallel rather than in series if the system is to be completed within five years. There is enough evidence to substantiate the revolution in the mesoscale weather prediction in the next five years.

Kreitzberg, C. W.↗

NASA NTRS1985

Observing system simulation experiments at NASA. Goddard Space Flight Center

A series of realistic simulation studies is being conducted as a cooperative effort between the European Centre for Medium Range Weather Forecasts (ECMWF), the National Meteorological Center (NMC), and the Goddard Laboratory for Atmospheres (GLA), to provide a quantitative assessment of the potential impact of future observing systems on large scale numerical weather prediction. A special objective is to avoid the unrealistic character of earlier simulation studies. Following a brief review of previous simulation studies and real data impact tests, the methodology for the current simulation system will be described. Results from an assessment of the realism of the simulation system and of the potential impact of advanced observing systems on numerical weather prediction and preliminary results utilizing this system will be presented at the conference.

Atlas, R.↗

NASA NTRS2013

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-13

Ms. Shafer completed the task to determine relationships between pressure gradients and peak winds at Vandenberg Air Force Base (VAFB), and began developing a climatology for the VAFB wind towers; Dr. Huddleston completed the task to develop a tool to help forecast the time of the first lightning strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) area; Dr. Bauman completed work on a severe weather forecast tool focused on the Eastern Range (ER), and also developed upper-winds analysis tools for VAFB and Wallops Fl ight Facility (WFF); Ms. Crawford processed and displayed radar data in the software she will use to create a dual-Doppler analysis over the east-central Florida and KSC/CCAFS areas; Mr. Decker completed developing a wind pairs database for the Launch Services Program to use when evaluating upper-level winds for launch vehicles; Dr. Watson continued work to assimilate observational data into the high-resolution model configurations she created for WFF and the ER.

Bauman, William↗

NASA NTRS1984

Simulation studies of proposed observing systems and their impact on numerical weather prediction

Atlas, R.↗

NASA NTRS1990

Tropical Pacific moisture variability

The objectives are to describe synoptic scale variability of moisture over the tropical Pacific Ocean and the systems leading to this variability; implement satellite analysis procedures in support of this effort, and to incorporate additional satellite information into operational analysis forecast systems at the National Meteorological Center (NMC). Composite satellite radiance patterns describe features detectable well before the development of synoptic scale tropical plumes. These typical features were extracted from historical files of Tiros Operational Vertical Sounder (TOVS) radiance observations for a pair of tropical plumes which developed during January 1989. Signals were inserted into the NMC operational medium range forecast model and a suite of model integrations were conducted. Many of the 48 h model errors of the historical forecasts were eliminated by the inclusion of more complete satellite observations. Three studies in satellite radiance analysis progressed. An analysis which blended TOVS moisture channels, OLR observations and European Center for Medium Weather Forecasts (ECMWF) model analysis to generate fields of total precipitable water comparable to those estimated from Scanning Multichannel Microwave Radiometer (SMMR) mu-wave observations. This study demonstrated that a 10 y climatology of precipitable water over the oceans is feasible, using available infrared observations (OLR and TOVS) and model analysis (ECMWF, NMC or similar quality). The estimates are sensitive to model quality and the estimating model must be updated with operational model changes. Coe developed a set of tropical plume and ITCZ composites from TOVS observations, and from NMC and ECMWF analyses which had been passed through a radiative transfer model to simulate TOVS radiances. The composites have been completed as well as many statistical diagnostics of individual TOVS channels. Analysis of the computations is commencing. Chung has initiated a study of the differences between TOVS observed vapor structure during El Nino Southern Oscillation (ENSO) (1983) and non-ENSO (1984) years. Preliminary diagnosis demonstrates gross moisture changes between warm and cold sea surface temperature episodes.

Mcguirk, James P.↗

NASA NTRS2007

Improved AIRS/AMSU Surface and Atmospheric Soundings Under Partial Cloud Cover Using an AIRS Only Cloud Clearing Approach

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the latest scientific advances made in the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major uses. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products.

Susskind, Dr. Joel↗

NASA NTRS2008

Deriving Tools from Real-time Runs: A New CCMC Support for SEC and AFWA

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions. the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models. and on the transition of appropriate models to space weather forecast centers. As part of the latter activity. the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. After consultations with NOA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

Hesse, Michael↗

NASA NTRS2002

Large Forecast Centers Using TRMM Real-Time Data

As a part of NASA's Earth System Enterprise, The Tropical Rainfall Measuring Mission (TRMM) seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Over the past 3 years, TRMM has contributed significantly towards reducing uncertainty in satellite estimates of rainfall in the Tropics, where almost 67% of the Earth's rain falls. TRMM has provided knowledge related to the climatology, seasonality, and variation of tropical rainfall; the mesoscale structure of rain-producing systems, and the physics of precipitation. As with many NASA missions, however, TRMM has provided surprising new knowledge and insight in scientific areas ranging from hurricane diagnosis/prediction to weather forecasting. Examples of current and future plans for use of TRMM data by operational weather centers will be discussed.

Shepherd, James Marshall↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

Keller, Christoph A.↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

Knowland, K. Emma↗

NASA NTRS2017

Air Quality Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (approximately 25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

Knowland, E. Emma↗

NASA NTRS1999

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

Hou, Arthur Y.↗

NASA NTRS2020

Subseasonal-to-Seasonal Hindcast Skill Assessment of Ridging Events Related to Drought Over the Western United States

Persistent atmospheric ridging events centered near the western United States are associated with widespread precipitation deficits and meteorological drought. Due to the relatively low skill of- dynamical models in forecasting precipitation on subseasonal‐to‐seasonal (S2S) time scales across this region, forecasts of ridging are explored in this study as a potential bridge for early warning drought prediction. To assess skill, we evaluate deterministic and probabilistic S2S hindcasts (out to 6 week lead time) of ridging events and geopotential height anomalies over the western United States in five ensemble hindcast systems. Prediction skill for ridging events is shown to be highly variable across models. For some models, longer‐time‐averaged patterns of geopotential height anomalies across the first 6 weeks can be skillfully simulated, when evaluated probabilistically against climatology. The most skillful models show modest skill in forecasting above normal ridging occurrences at lead times of Weeks 3–4 and Weeks 5–6,with some sensitivity to the specific ridge location and method for determining skill. Using the European Centre for Medium‐Range Weather Forecasts (ECMWF) model as a case study, longer lead time forecast busts are shown to often occur under extended periods of highly active La Nina‐like tropical convection. Model errors at simulating these tropical convection features may have a disproportionately large impact and degrade downstream forecasts over the western United States. Despite the documented model shortcomings, our results highlight an opportunity to target skillful ridging forecasts from dynamical models for improving early warning drought forecasting at S2S lead times.

S2S↗

NASA NTRS1999

The Kalman Filter and High Performance Computing at NASA's Data Assimilation Office (DAO)

Atmospheric data assimilation is a method of combining actual observations with model simulations to produce a more accurate description of the earth system than the observations alone provide. The output of data assimilation, sometimes called "the analysis", are accurate regular, gridded datasets of observed and unobserved variables. This is used not only for weather forecasting but is becoming increasingly important for climate research. For example, these datasets may be used to assess retrospectively energy budgets or the effects of trace gases such as ozone. This allows researchers to understand processes driving weather and climate, which have important scientific and policy implications. The primary goal of the NASA's Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. This presentation will: (1) describe ongoing work on the advanced Kalman/Lagrangian filter parallel algorithm for the assimilation of trace gases in the stratosphere; and (2) discuss the Kalman filter in relation to other presentations from the DAO on Four Dimensional Data Assimilation at this meeting. Although the designation "Kalman filter" is often used to describe the overarching work, the series of talks will show that the scientific software and the kind of parallelization techniques that are being developed at the DAO are very different depending on the type of problem being considered, the extent to which the problem is mission critical, and the degree of Software Engineering that has to be applied.

Lyster, Peter M.↗