Recent technology advances in miniature microwave radiometers that can be hosted on very small satellites has made possible a new class of affordable constellation missions that provide very high revisit rates of tropical cyclones and other severe weather. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture–Instrument (EVI-3) program and is now in development with planned launch readiness in late 2019. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. TROPICS will comprise a constellation of at least six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 205 GHz that is more sensitive to precipitation-sized ice particles and low-level moisture. This observing system offers an unprecedented combination of horizontal and temporal resolution in the microwave spectrum to measure environmental and inner-core conditions for TCs on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data. Here, we provide an overview of the mission and an update on current status, with a focus on unique characteristics of the Cubesat system, recent performance simulations on a range of observables to be provided by the constellation, and a summary of science applications.
Geostationary Operational Environmental Satellite (GOES)-14 imager was operated by National Oceanic and Atmospheric Administration (NOAA) in an experimental rapid scan 1-min mode that emulates the high-temporal resolution sampling of the Advanced Baseline Imager (ABI) on the next generation GOES-R series. Imagery with a refresh rate of 1 min of many phenomena were acquired, including clouds, convection, fires, smoke, and hurricanes, including 6 days of Hurricane Sandy through landfall. NOAA had never before operated a GOES in a nearly continuous 1-min mode for such an extended period of time, thereby making these unique datasets to explore the future capabilities possible with GOES-R. The next generation GOES-R imager will be able to routinely take mesoscale (1000 km×1000 km) images every 30 s (or two separate locations every minute). These images can be acquired even while scanning continental United States and full disk images. These high time-resolution images from the GOES-14 imager are being used to prepare for the GOES-R era and its advanced imager. This includes both the imagery and quantitative derived products such as cloud-top cooling. Several animations are included to showcase the rapid change of the many phenomena observed during super rapid scan operations for GOES-R (SRSOR).
During the GEOSS era, a Doppler wind lidar (DWL) described in this paper will be able to measure
directly the 3-dimensional wind field. These observations can be used synergistically with traditional
imagers, passive radiometers and active scatterometers to improve significantly the weather and climate
missions.
Synergisms being explored include laser height assignment and layer wind calibration for Cloud Motion
Vectors (CMVs) and Water Vapor Motion Vectors (WVMVs), and the adjudication of directional
ambiguities in Ocean Vector Winds (OVW) retrievals. These synergistic links will be incorporated into
adaptive targeting schemes being evaluated within Observing System Simulation Experiments designed
to explore ways to optimize the utility of the DWL observations.
Traditional methods for deriving wind vectors from sequential geostationary satellite imagery involve the tracking of coherent clouds and moisture features in single channels (spectral bands). While this data source has proven to be important to global wind analyses, the approach is limited in two major ways: 1) The heights assigned to the vectors are not precise, leading to problems in data assimilation, and 2) Vertical profiles of the wind at a given geo-location are not provided, adding further stress to objective data assimilation (difficulty with single-level observations). A new approach to deriving winds from sequential satellite observations is being advanced at CIMSS. The method utilizes the same basic automated tracking code developed at CIMSS, however the input to the algorithm is in the form of constant-level moisture analyses derived from hyperspectral sounding information. Since the altitude of the features being tracked are already determined by the soundings/analyses, the height assignment ambiguities associated with the traditional approaches are ameliorated. Furthermore, the hyperspectral infrared (IR) information provides detailed vertical profiles of moisture where there are no clouds. This allows analyses of moisture at multiple vertical levels, which can then be used in
an attempt to retrieve vertical profiles of wind. To date, the new scheme has been trialed on simulated data from GIFTS, and on one case of real data from airborne observations provided by the NAST-I instrument. From these first attempts, the "proof of concept" is successfully illustrated, and will be shown in the presentation.
Automated procedures for deriving cloud-motion vectors from a series of geostationary images have been developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) and have been operational in NOAA since 1993. Since that time, CIMSS has continued work to improve the processing techniques, upgrade the quality of the product, and add further capabilities. Scientific improvements include the addition of the water-vapor intercept technique for assigning heights to semi-transparent clouds, a new version of the automated quality control algorithm which reduces the large mean slow bias observed in the initial system, and improved selection of suitable tracers. These improvements have been successfully applied to the 'Day 1' GOES-8/9 operational winds system in NOAA. Research has already begun to define 'Day 2' operations. Improved resolution and signal of the GOES-8/9 imager has made automated water-vapor motion vector production possible for the first time, enabling the measurement of wind velocities in clear air. Work has begun on an automated algorithm for imagery registration quality control and the optimal density for wind products as a function of coverage and computing power is being investigated.
Conference Committee Involvement (2)
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospheric Prediction and Environmental Monitoring
1 August 2005 | San Diego, California, United States
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective
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