Engineering topics
Waliser, Duane
Publications and source records attributed to Waliser, Duane.
Remote Sensing and Earth Science: Science, Engineering and Technology
No abstract available
Effects of Resolution and Spectral Nudging in Simulation the Effects of Wintertime Atmospheric River Landfalls in the Western US
Landfalling atmospheric rivers (ARs) play a crucial role in the climate of the US Pacific coast region as they are frequently related with heavy precipitation and flash flooding events. Thus, the capability of climate models to accurately simulate AR landfalls and their key hydrologic effects is an important practical concern for WUS, from flood forecasting to future water resources projections. In order to examine the effects of model configuration, including the resolution and spectral nudging, in simulating the climatology of key weather events in the conterminous US, a NASA team has performed a hindcast experiment using the GEOS5 global and the NU-WRF regional models for Nov 1999 - Oct 2010. This study examines the skill of these hindcasts, with different models and their configurations, in simulating key footprints of landfalling ARs in the WUS region. Using an AR-landfall chronology based on the vertically-integrated water vapor flux calculated from the MERRA2 reanalysis, we have analyzed the observed and simulated precipitation and temperature anomalies associated with wintertime AR landfalls along the US Pacific coast. Model skill is measured using metrics including regional means, a skill score based on correlations and mean-square errors, and Taylor diagrams in four WUS Bukovsky regions. Results show that the AR-related anomalies of precipitation is more reliable than of surface temperatures. Model skill also varies according to regions. The AR temperature anomalies are well simulated in most of the WUS region except PNW. For precipitation, simulations with finer spatial resolution tend to generate larger spatial variability and agree better with the PRISM data in most regions. Such a resolution dependence of spatial variability is not found for temperatures; e.g., the MERRA2 reanalysis often outperforms, with similar spatial variability and higher pattern correlations with the PRISM data, finer-resolution NU-WRF runs in simulating temperature variations within subregions. Results from this study will be summarized to assist future (regional) climate experiments for climate change impact assessments and developing adaptationmitigation strategies, the key elements of the National Climate Assessment.
Convective Momentum Transport Associated with the Madden-Julian Oscillation
No abstract available
Predictability of Tropical Intraseasonal Variability (ISV) in the ISV Hindcast Experiment (ISVHE)
No abstract available
Intraseasonal Variability and Predictability: An Overview of the Madden-Julian Oscillation
No abstract available
Converting NASA Satellite Datasets for the CMIP5/IPCC Assessment
No abstract available
Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations
Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.
NASA Giovanni Tool for Visualization and Analysis Support for the YOTC Program
The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been two folds: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. Because the goal of Overview of Year Of Tropical Convection (YOTC) involves examining a scientifically complex, multi-scale "process", rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 - April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO, and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO).
NASA Goddard Giovanni Support for YOTC
The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.
The Experimental MJO Prediction Project
Weather prediction is typically concerned with lead times of hours to days, while seasonal-to-interannual climate prediction is concerned with lead times of months to seasons. Recently, there has been growing interest in 'subseasonal' forecasts---those that have lead times on the order of weeks (e.g., Schubert et al. 2002; Waliser et al. 2003; Waliser et al. 2005). The basis for developing and exploiting subseasonal predictions largely resides with phenomena such as the Pacific North American (PNA) pattern, the North Atlantic oscillation (NAO), the Madden-Julian Oscillation (MJO), mid-latitude blocking, and the memory associated with soil moisture, as well as modeling techniques that rely on both initial conditions and slowly varying boundary conditions (e.g., tropical Pacific SST). An outgrowth of this interest has been the development of an Experimental MJO Prediction Project (EMPP). Th project provides real-time weather and climate information and predictions for a variety of applications, broadly encompassing the subseasonal weather-climate connection. Th focus is on the MJO because it represents a repeatable, low-frequency phenomenon. MJO's importance among the subseasonal phenomena is very similar to that of El Nino-Southern Oscillation(ENSO) among the interannual phenomena. This note describes the history and objectives of EMPP, its status,capabilities, and plans.
Predictability and forecast issues associated with the Madden-Julian Oscillation
Explore the source record for details and available documents.
Modeling, Simulation, and Forecasting of Subseasonal Variability
A planning workshop on "Modeling, Simulation and Forecasting of Subseasonal Variability" was held in June 2003. This workshop was the first of a number of meetings planned to follow the NASA-sponsored workshop entitled "Prospects For Improved Forecasts Of Weather And Short-Term Climate Variability On Sub-Seasonal Time Scales" that was held April 2002. The 2002 workshop highlighted a number of key sources of unrealized predictability on subseasonal time scales including tropical heating, soil wetness, the Madden Julian Oscillation (MJO) [a.k.a Intraseasonal Oscillation (ISO)], the Arctic Oscillation (AO) and the Pacific/North American (PNA) pattern. The overarching objective of the 2003 follow-up workshop was to proceed with a number of recommendations made from the 2002 workshop, as well as to set an agenda and collate efforts in the areas of modeling, simulation and forecasting intraseasonal and short-term climate variability. More specifically, the aims of the 2003 workshop were to: 1) develop a baseline of the "state of the art" in subseasonal prediction capabilities, 2) implement a program to carry out experimental subseasonal forecasts, and 3) develop strategies for tapping the above sources of predictability by focusing research, model development, and the development/acquisition of new observations on the subseasonal problem. The workshop was held over two days and was attended by over 80 scientists, modelers, forecasters and agency personnel. The agenda of the workshop focused on issues related to the MJO and tropicalextratropical interactions as they relate to the subseasonal simulation and prediction problem. This included the development of plans for a coordinated set of GCM hindcast experiments to assess current model subseasonal prediction capabilities and shortcomings, an emphasis on developing a strategy to rectify shortcomings associated with tropical intraseasonal variability, namely diabatic processes, and continuing the implementation of an experimental forecast and model development program that focuses on one of the key sources of untapped predictability, namely the MJO. The tangible outcomes of the meeting included: 1) the development of a recommended framework for a set of multi-year ensembles of 45-day hindcasts to be carried out by a number of GCMs so that they can be analyzed in regards to their representations of subseasonal variability, predictability and forecast skill, 2) an assessment of the present status of GCM representations of the MJO and recommendations for future steps to take in order to remedy the remaining shortcomings in these representations, and 3) a final implementation plan for a multi-institute/multi-nation Experimental MJO Prediction Program.
Prospects for Improved Forecasts of Weather and Short-Term Climate Variability on Subseasonal (2-Week to 2-Month) Times Scales
This workshop, held in April 2002, brought together various Earth Sciences experts to focus on the subseasonal prediction problem. While substantial advances have occurred over the last few decades in both weather and seasonal prediction, progress in improving predictions on these intermediate time scales (time scales ranging from about two weeks to two months) has been slow. The goals of the workshop were to get an assessment of the "state of the art" in predictive skill on these time scales, to determine the potential sources of "untapped" predictive skill, and to make recommendations for a course of action that will accelerate progress in this area. One of the key conclusions of the workshop was that there is compelling evidence for predictability at forecast lead times substantially longer than two weeks. Tropical diabatic heating and soil wetness were singled out as particularly important processes affecting predictability on these time scales. Predictability was also linked to various low-frequency atmospheric "phenomena" such as the annular modes in high latitudes (including their connections to the stratosphere), the Pacific/North American (PNA) pattern, and the Madden Julian Oscillation (MJO). The latter, in particular, was highlighted as a key source of untapped predictability in the tropics and subtropics, including the Asian and Australian monsoon regions.
Experiments with a Data Assimilation System to Diagnose AGCM Hindcasts of the MJO
The objectives of this study are to (1) develop a better understanding of how observations constrain/impact the MJO in a data assimilation system with the aim of improving the representation of the MJO, and (2) to carry out AGCM predictability/forecast experiments under various observational constraints to assess model errors and sensitivity to initial conditions. Our current focus is on the second objective.