Retrieving Decadal Climate Change from Satellite Radiance Observations-A 100-year CO2 Doubling OSSE Demonstration.

Preparing for climate change depends on the observation and prediction of decadal trends of the environmental variables, which have a direct impact on the sustainability of resources affecting the quality of life on our planet. The NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is proposed to provide climate quality benchmark spectral radiance observations for the purpose of determining the decadal trends of climate variables, and validating and improving the long-range climate model forecasts needed to prepare for the changing climate of the Earth. The CLARREO will serve as an in-orbit, absolute, radiometric standard for the cross-calibration of hyperspectral radiance spectra observed by the international system of polar operational satellite sounding sensors. Here, we demonstrate that the resulting accurately cross-calibrated polar satellite global infrared spectral radiance trends (e.g., from the Metop IASI instrument considered here) can be interpreted in terms of temperature and water vapor profile trends. This demonstration is performed using atmospheric state data generated for a 100-year period from 2000-2099, produced by a numerical climate model prediction that was forced by the doubling of the global average atmospheric CO2 over the 100-year period. The vertical profiles and spatial distribution of temperature decadal trends were successfully diagnosed by applying a linear regression profile retrieval algorithm to the simulated hyperspectral radiance spectra for the 100-year period. These results indicate that it is possible to detect decadal trends in atmospheric climate variables from high accuracy all-sky satellite infrared radiance spectra using the linear regression retrieval technique

Modeled vs. Actual Performance of the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS)

The NASA Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) has been completed as an Engineering Demonstration Unit (EDU) and has recently finished thermal vacuum testing and calibration. The GIFTS EDU was designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS EDU includes a cooled (150 K), imaging FTS designed to provide the radiometric accuracy and atmospheric sounding precision required to meet the next generation GOES sounder requirements. This paper discusses a GIFTS sensor response model and its validation during thermal vacuum testing and calibration. The GIFTS sensor response model presented here is a component-based simulation written in IDL with the model component characteristics updated as actual hardware has become available. We discuss our calibration approach, calibration hardware used, and preliminary system performance, including NESR, spectral radiance responsivity, and instrument line shape. A comparison of the model predictions and hardware performance provides useful insight into the fidelity of the design approach

Ground-Based Measurement Experiment and First Results with Geosynchronous-Imaging Fourier Transform Spectrometer Engineering Demonstration Unit

The geosynchronous-imaging Fourier transform spectrometer (GIFTS) engineering demonstration unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 microns, 6.0 to 4.4 microns) using two 128 x 128 detector arrays with a spectral resolution of 0.57 cm(exp -1) with a scan duration of approximately 11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which atmospheric status, cloud parameters, wind field profiles, and other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated its extensive capabilities and potential for geosynchronous and other applications (e.g., Earth observing environmental measurements). This paper addresses the experiment objectives and overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept

Climate Change Observation Accuracy: Requirements and Economic Value

This presentation will summarize a new quantitative approach to determining the required accuracy for climate change observations. Using this metric, most current global satellite observations struggle to meet this accuracy level. CLARREO (Climate Absolute Radiance and Refractivity Observatory) is a new satellite mission designed to resolve this challenge is by achieving advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra. The CLARREO spectrometers can serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, etc). A CLARREO Pathfinder mission for flight on the International Space Station is included in the U.S. President"TM"s fiscal year 2016 budget, with launch in 2019 or 2020. Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A new study has been carried out to quantify the economic benefits of such an advance and concludes that the economic value is ~ $9 Trillion U.S. dollars. The new value includes the cost of carbon emissions reductions

Final Report: High Spectral Resolution Atmospheric Emitted Radiance Studies with the ARM UAV

The active participation in the Atmospheric Radiation Measurement (ARM) Unmanned Airborne Vehicle (UAV) science team that was anticipated in the grant proposal was indefinitely delayed after the first year due to a programmatic decision to exclude the high spectral resolution observations from the existing ARM UAV program. However, this report shows that substantial progress toward the science objectives of this grant have made with the help of separate funding from NASA and other agencies. In the four year grant period (including time extensions), a new high spectral resolution instrument has been flown and has successfully demonstrated the ability to obtain measurements of the type needed in the conduct of this grant. In the near term, the third water vapor intensive observing period (WVIOP-3) in October 2000 will provide an opportunity to bring the high spectral resolution observations of upwelling radiance into the ARM program to complement the downwelling radiance observations from the existing ARM AERI instruments. We look forward to a time when the ARM-UAV program is able to extend its scope to include the capability for making these high spectral resolution measurements from a UAV platform

Retrieving Decadal Climate Change from Satellite Radiance Observations-A 100-year CO2 Doubling OSSE Demonstration.

Preparing for climate change depends on the observation and prediction of decadal trends of the environmental variables, which have a direct impact on the sustainability of resources affecting the quality of life on our planet. The NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is proposed to provide climate quality benchmark spectral radiance observations for the purpose of determining the decadal trends of climate variables, and validating and improving the long-range climate model forecasts needed to prepare for the changing climate of the Earth. The CLARREO will serve as an in-orbit, absolute, radiometric standard for the cross-calibration of hyperspectral radiance spectra observed by the international system of polar operational satellite sounding sensors. Here, we demonstrate that the resulting accurately cross-calibrated polar satellite global infrared spectral radiance trends (e.g., from the Metop IASI instrument considered here) can be interpreted in terms of temperature and water vapor profile trends. This demonstration is performed using atmospheric state data generated for a 100-year period from 2000-2099, produced by a numerical climate model prediction that was forced by the doubling of the global average atmospheric CO2 over the 100-year period. The vertical profiles and spatial distribution of temperature decadal trends were successfully diagnosed by applying a linear regression profile retrieval algorithm to the simulated hyperspectral radiance spectra for the 100-year period. These results indicate that it is possible to detect decadal trends in atmospheric climate variables from high accuracy all-sky satellite infrared radiance spectra using the linear regression retrieval technique

University of Wisconsin-Madison Participation in the International Water-Vapor Project (IHOP)

This is the final report for NASA grant NAG-1-02057/University of Wisconsin-Madison/Dr. Henry E Revercomb, PI. This grant supported the University of Wisconsin-Madison participation in the International Water-Vapor Project (IHOP) experiment in May-June 2002. The upwelling thermal infrared emission from the surface and atmosphere over the U. S. Southern Great Plains was obtained from the NASA DC-8 with the Scanning High-resolution Interferometer Sounder (S-HIS) instrument, Analysis of the S-HIS radiances were used to obtain atmospheric temperature profiles below the aircraft. In a complementary manner, the downwelling thermal infrared emission at the surface was obtained by the University of Wisconsin Atmospheric Emitted Radiance Interferometer (AERI) instrument from a mobile research vehicle and used to profile the atmospheric boundary layer at the Homestead site. This report summarizes the observations of the S-HIS and AERI instruments during IHOP including validation against in situ observations