Free Flyer Total and Spectral Solar Irradiance Sensor (TSIS) and Climate Services Mission

NOAA's planned Total and Spectral Solar Irradiance Sensor (TSIS) mission will fly along with the NOAA user service payloads Advanced Data Collection System (ADCS) and Search and Rescue Satellite Aided Tracking (SARSAT). In ' order to guarantee continuity in the 33-year solar irradiance climate data record, TSIS must be launched in time to overlap with current on-orbit solar irradiance instruments. Currently TSIS is moving towards a launch rcadin~ss date of January 2015. TSIS provides for continuation of the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM) ,currently onboard NASA's Solar Radiation and Climate Experiment (SORCE) platform, launched in January 2003. The difficulty of ensuring continuity has increased due to the launch failure of NASA's Glory mission with its improved TIM. Achieving the needed overlap must now rely on extending SORCE. and maintaining the TSIS schedule. TSIS is one component of a NASA-NOAA joint program (JPSS) planned to transition certain climate observations to operational mode. We summarize issues of continuity, improvements being made to the TIM and 81M sensors, and plans to provide for traceability of total and spectral irradiance measurements to ground-based cryogenic standards

Solar Spectral Irradiance and Climate

Spectrally resolved solar irradiance is recognized as being increasingly important to improving our understanding of the manner in which the Sun influences climate. There is strong empirical evidence linking total solar irradiance to surface temperature trends - even though the Sun has likely made only a small contribution to the last half-century's global temperature anomaly - but the amplitudes cannot be explained by direct solar heating alone. The wavelength and height dependence of solar radiation deposition, for example, ozone absorption in the stratosphere, absorption in the ocean mixed layer, and water vapor absorption in the lower troposphere, contribute to the "top-down" and "bottom-up" mechanisms that have been proposed as possible amplifiers of the solar signal. New observations and models of solar spectral irradiance are needed to study these processes and to quantify their impacts on climate. Some of the most recent observations of solar spectral variability from the mid-ultraviolet to the near-infrared have revealed some unexpected behavior that was not anticipated prior to their measurement, based on an understanding from model reconstructions. The atmospheric response to the observed spectral variability, as quantified in climate model simulations, have revealed similarly surprising and in some cases, conflicting results. This talk will provide an overview on the state of our understanding of the spectrally resolved solar irradiance, its variability over many time scales, potential climate impacts, and finally, a discussion on what is required for improving our understanding of Sun-climate connections, including a look forward to future observations

Direct Observations of Excess Solar Absorption by Clouds

Aircraft measurements of solar flux in the cloudy tropical atmosphere reveal that solar absorption by clouds is anomalously large when compared to theoretical estimates. The ratio of cloud forcing at an altitude of 20 kilometers to that at the surface is 1.58 rather than 1.0 as predicted by models. These results were derived from a cloud radiation experiment in which identical instrumentation was deployed on coordinated stacked aircraft. These findings indicate a significant difference between measurements and theory and imply that the interaction between clouds and solar radiation is poorly understood

Ground-based passive remote sensing during FIRE IFO 2

During the FIRE Cirrus IFO II, a set of passive radiometers were deployed at the Coffeyville, Kansas, Hub, site B, to compliment the Radiation Measurement System (RAMS) on board the NASA ER-2 and NCAR Sabreliner. The following three instruments were used at the surface: Narrow-field-of View IR Radiometer (NFOV); Total-Direct-Diffuse Radiometer (TDDR); and Near-Infrared Spectroradiometer (NIRS)

Radiative effects of convection in the tropical Pacific

The radiative effects of tropical clouds at the tropopause and the ocean surface have been estimated by using in situ measurements from the Central Equatorial Pacific Experiment (CEPEX). The effect of clouds is distinguished from the radiative effects of the surrounding atmosphere by calculating the shortwave and longwave cloud forcing. These terms give the reduction in insolation and the increase in absorption of terrestrial thermal emission associated with clouds. At the tropopause the shortwave and longwave cloud forcing are nearly equal and opposite, even on daily timescales. Therefore the net effect of an ensemble of convective clouds is small compared to other radiative terms in the surface-tropospheric heat budget. This confirms the statistical cancellation of cloud forcing observed in Earth radiation budget measurements from satellites. At the surface the net effect of clouds is to reduce the radiant energy absorbed by the ocean. Under deep convective clouds the diurnally averaged reduction exceeds 150 W m(-2). The divergence of flux in the cloudy atmosphere can be estimated from the difference in cloud forcing at the surface and tropopause. The CEPEX observations show that the atmospheric cloud forcing is nearly equal and opposite to the surface forcing. Based upon the frequency of convection, the atmospheric forcing approaches 100 W m(-2) when the surface temperature is 303 K. The cloud forcing is closely related to the frequency of convective cloud systems. This relation is used in conjunction with cloud population statistics derived from satellite to calculate the change in surface cloud forcing with sea surface temperature. The net radiative cooling of the surface by clouds increases at a rate of 20 W m(-2)K(-1)during the CEPEX observing period

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

We report a series of experiments to explore clima~ responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations

Optical properties of cirrus derived from airborne measurements during FIRE IFO 2

The Radiation Measurement System (RAMS) on board the NASA ER-2 was used to acquire several optical parameters of interest during the FIRE Cirrus IFO 2. In this abstract we present results from the 26 Nov. IFO when the ER-2 flew over the Coffeyville airport hub site. We show retrieved optical thickness and cloud temperature, along with optical thickness obtained from RAMS instruments on the NCAR Sabreliner and at the surface site B. Independent retrieval of optical thickness, from the ER-2 and at the surface, are in agreement during the overpasses. Cirrus optical depths, derived from each platform, ranged between 1 and 2

Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance

An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol-cloud-radiation interactions in the southeast Atlantic basin

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June&ndash;October), aerosol particles reaching 3&ndash;5&thinsp;km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September&nbsp;2016, August&nbsp;2017, and October&nbsp;2018 (totaling &sim;350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling &sim;100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol&ndash;cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced. </div