2010 JCSDA Seminars

The National Center for Atmospheric Research (NCAR) is working with the Air Force Weather Agency (AFWA) on building an integrated AFWA Coupled Analysis and Prediction System (ACAPS). This will represent a significant improvement and redesign that requires state-of-the-art cloud analysis capabilities to include hydrometeors in the assimilation. A particular effort is directed toward the assimilation of cloud and rain-contaminated satellite radiances. Results will be presented from initial studies addressing cloud-related issues such as non-linear observation operators, representativeness error and the modeling of background error covariances for heterogeneous, flow-dependent fields.

With the launch of the European Space Agency's Atmospheric Dynamics Mission (ADM-Aeolus) in 2011 and the call for the 3D- Winds mission in National Research Council's decadal survey, direct spaceborne measurements of vertical wind profiles are imminent via Doppler wind lidar technology. Part of the preparedness for these missions is the development of the proper data assimilation methodology for handling such observations. As active measurements, the platforms will have largely predictable lifetimes. With ADM, the lifespan of the instrument is expected to be three years. To maximize the utility of the instrument, an Observing System Simulation Experiment (OSSE) framework is being utilized to generate a realistic proxy dataset for development of the Gridpoint Statistical Interpolation (GSI) data assimilation system utilized at a number of centers through the United States. This effort will be presented, including the methodology and status of proxy data generation, validation of necessary fields in the Joint OSSE Nature Run, and the assimilation of such measurements within the GSI.

The photometric and spectral accuracy of the current and future satellite spectral radiance instruments places stringent demands on the forward spectral radiance model. The line-by-line radiative transfer model (RTM) plays a key role in developing operational RTMs for the retrieval of atmospheric state and for the assimilation of radiances into general circulation models. The evolution and status of models with lblrtm heritage will be presented together with a general perspective of the programming concepts behind the model; this to provide background for the potential development of an updated model. The importance of utilizing a formalism that includes consistent physics from the microwave to the infrared on through the solar regime will be strongly emphasized. The concluding portion of the presentation will focus on model accuracy; general validation issues; a detailed model evaluation with a specific IASI dataset; recent model advances; and obvious model shortcomings that require improvement.

The operational data assimilation system of Météo-France uses a Four-Dimensional Variational scheme (4DVAR), performed on 6h time windows. The 4DVAR scheme provides the initial state of a global spectral forecasting model called "ARPEGE" with a T798 horizontal resolution, 70 levels in the vertical. The assimilation makes a massive use of satellite data, namely atmospheric motion vectors from geostationary platforms and from MODIS, radiances from HIRS, AMSU, AIRS, IASI and SEVIRI, scatterometer data, GPS radio- occultation bending angles. In the seminar, latest developments on the use of cloudy AIRS and IASI radiances, on the use of microwave radiances over land and sea-ice, and on the preparation for the use of SSMIS data will be presented. Furthermore, the Concordiasi field campaign planned over Antarctica for September- November 2010 will be presented. Its main scientific objectives are the validation of the use of satellite data and the understanding of ozone depletion linked with gravity-wave activity and Polar Stratospheric Clouds.

The next generation Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2015 includes an advanced imager and a new capability for total lightning detection (cloud and cloud-to-ground flashes). The Geostationary Lightning Mapper (GLM) will map total lightning activity continuously day and night with near-uniform spatial resolution of 8 km and with a product latency of less than 20 sec over the western hemisphere from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. Near global coverage will be possible by the end of the decade with operational lightning imagers planned by EUMETSAT and the Chinese Meteorological Agency. Cloud-resolving numerical models, such as the Weather Research and Forecasting (WRF) model, now have the capability of computing fields of mixing ratios of multiple species of hydrometeors, including several important ice-phase species known to be associated with lightning flash rate (graupel, hail, ice water content). In this presentation, we review the past decade of data assimilation experiments using proxy relationships for lightning and present new methodologies and opportunities to demonstrate how regional cloud-resolving forecast simulations can be exploited to create quantitatively calibrated, time-dependent and specific short-term forecasts of lightning flash rates in convective environments. Our prototype methods being tested at the NOAA Hazardous Weather Testbed and Storm Prediction Center this spring yield lightning forecast products that are straightforward, while avoiding the added expense and complexity of incorporating explicit cloud electrification algorithms into the models.

Speaker Bio:

Steve Goodman is the GOES-R Program Senior Scientist since 2008 and a past Acting Deputy Director of the JCSDA. Dr. Goodman's research specialization includes the remote sensing of thunderstorms, lightning, and precipitation processes, and the application of space-based remote sensing to improve short-range forecasts of convective weather hazards. In 2001 he received the NASA Medal for Exceptional Scientific Achievement for his research on severe storms. In support of current and planned missions Dr. Goodman is the Team Lead for the GOES-R Geostationary Lightning Mapper Lightning Applications Team and a Co-Investigator on the NASA Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS) Instrument Team. Dr. Goodman is currently a member of the AMS Committee on Satellite Meteorology and Oceanography, U.S. representative to the WMO World Weather Research Program Nowcasting Working Group, and an Associate Editor of the Journal of Geophysical Research-Atmospheres. He earned his PhD in Systems Engineering from the University of Alabama in Huntsville, MS in Meteorology from the University of Oklahoma, and BA in Atmospheric and Oceanic Science from the University of Wisconsin at Madison.

In the past decade, GPS/RO data have been operationally assimilated at NWP centers and have resulted in positive impacts on the global medium-range forecasts. This talk will cover: (i) GPS RO techniques and data processing, (ii) assimilation of GPS RO data in NWP and (iii) profiling clouds in the atmosphere using GPS data. In GPS RO techniques and data processing, I will introduce the GPS RO measurement principle, data processing chain and potential error sources. I'll then present and discuss numerical results from quality control, forward modeling, assimilation experiments, and comparison with large-scale analyses in cloudy and clear-sky conditions. Finally, I will discuss future directions for GPS RO research and applications in regional mesoscale forecasts, emphasizing the recognized GPS RO capability for profiling the atmosphere under cloudy and severe storm conditions.

Accurate modeling of atmospheric absorption and constraints on surface properties are needed to improve atmospheric retrievals and impact of assimilated satellite data on the weather forecasts. AER has developed line-by-line models (LBLRTM and MonoRTM) that have been used in many centers (including the JCSDA) as reference in the development of fast transmittance parameterizations as well as the Optimal Spectral Sampling (OSS) method for fast and numerically accurate parameterization of molecular absorption in the atmosphere. The line-by-line models are continuously validated and updated at AER. Recent updates have been made to the water vapor continuum in the microwave region and linemixing in the 4.3 micron CO₂ band, and improvements have been made in the modeling of the 2400 cm^-1 band head. The OSS model has been selected by EUMETSAT for the MTG-IRS L2 concept processor development and is among the candidate FRTM's for integration in the future MTG operational ground segment. The focus of current and future OSS development is on refining our generalized training capability. A status of the models will be discussed. A description of the work in progress on the use of our dynamically updated global atlas of microwave surface emissivities (sample hosted at the JCSDA) in the production of land surface temperatures under cloudy conditions will be provided.

The ECMWF forecasting system continues to be world leading in terms of forecast performance in the medium range. Both the deterministic and probabilistic forecast products are continuously improved; in early 2010 a new model version with an increased spatial resolution is being introduced, which will help to maintain the positive performance trends. Research is focused on new data assimilation techniques, improved description of physical processes and development of enhanced ensemble prediction methods. Monthly and seasonal forecasts are also produced; the current El Nino event was predicted more than a year ago. Re-analyses are regularly produced and updated. In recent years the re-analysis shows global temperature trends over land areas that are significantly warmer than results from other data sets suggest.

The seminar presents the current status of the Polar Communications and Weather (PCW) mission, led by the Canadian Space Agency. As the name indicates the dual goal of PCW is to provide continuous communications and Earth observation services over the Arctic, this with a near real time operational mandate. Environment Canada will take responsibility for the production and delivery of meteorological products. Currently in the middle of Phase A, the mission is planned for 2016. The seminar focuses on the meteorological component. PCW is defined by a constellation of two satellites in a highly elliptical 12-hour "Molniya" orbit with apogee at ~39,600 km and perigee at ~600 km. The constellation will provide for the first time seamless observations over the entire circumpolar domain above 55 N. The main meteorological instrument is an advanced imager with characteristics similar to those of the imager planned for GOES-R (2015) or Meteosat Third Generation (2016). The PCW imager has 20 channels covering the spectral range 0.45 µm to 14.4 µm, with pixel sizes ranging from 500 m to 1 km for visible channels to 2 km for infrared channels. The presentation will cover the following elements: imager definition and applications, orbital characteristics, critical technology issues, production of simulated datasets, data assimilation and impact studies, notably in relation to atmospheric wind vectors, and opportunities for other instruments. The international context will also be presented. For example the World Meteorological Organization (WMO) is supporting the highly elliptical observation concept, and several countries have indicated a marked interest for PCW. This interest stems from the fact that the mission allows extending the applications developed for geostationary satellites all the way to the North Pole.

A summary of research results on assimilation of GOES (Geostationary Operational Environmental Satellites) Imager observations into a cloud resolving model will be presented. The purpose of the research is to evaluate feasibility of atmospheric data analysis with clouds. The studies were performed using a research data assimilation algorithm designated Regional Atmospheric Modeling and Data Assimilation System (RAMDS) that was developed at CIRA (Cooperative Institute for Research in the Atmosphere) at CSU (Colorado State University) and at ATOC (department of ATmospheric and OCeanographic sciences) at CU (University of Colorado). In RAMDAS a fully nonlinear 4DVAR (4- dimensional variational) data assimilation approach is applied to the cloud resolving regional model RAMS (Regional Atmospheric Modeling System) that includes explicit bulk parameterization of cloud processes. The observational operator for GOES imager observations is a system for computing unpolarized radiative transfer for either collimated solar and/or thermal emission sources of radiation in both clear and cloudy plane-parallel conditions. Adjoint models of the cloud resolving and radiative transfer models include explicit linearization of these nonlinear models. Overall, the results with RAMDAS indicate that the data assimilation of the cloud affected geostationary observations is feasible. The results show improvement in the model representation of the cloudy atmosphere and consistent change in the dynamical cloud environment.