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NASA NTRS2013

Northern North Atlantic Sea Surface Height and Ocean Heat Content Variability

The evolution of nearly 20 years of altimetric sea surface height (SSH) is investigated to understand its association with decadal to multidecadal variability of the North Atlantic heat content. Altimetric SSH is dominated by an increase of about 14 cm in the Labrador and Irminger seas from 1993 to 2011, while the opposite has occurred over the Gulf Stream region over the same time period. During the altimeter period the observed 0-700 m ocean heat content (OHC) in the subpolar gyre mirrors the increased SSH by its dominantly positive trend. Over a longer period, 1955-2011, fluctuations in the subpolar OHC reflect Atlantic multidecadal variability (AMV) and can be attributed to advection driven by the wind stress ''gyre mode'' bringing more subtropical waters into the subpolar gyre. The extended subpolar warming evident in SSH and OHC during the altimeter period represents transition of the AMV from cold to warm phase. In addition to the dominant trend, the first empirical orthogonal function SSH time series shows an abrupt change 2009-2010 reaching a new minimum in 2010. The change coincides with the change in the meridional overturning circulation at 26.5N as observed by the RAPID (Rapid Climate Change) project, and with extreme behavior of the wind stress gyre mode and of atmospheric blocking. While the general relationship between northern warming and Atlantic meridional overturning circulation (AMOC) volume transport remains undetermined, the meridional heat and salt transport carried by AMOC's arteries are rich with decade-to-century timescale variability.

Sea-surface↗

NASA NTRS2014

Modifications of the Quasi-biennial Oscillation by a Geoengineering Perturbation of the Stratospheric Aerosol Layer

This paper examines the impact of geoengineering via stratospheric sulfate aerosol on the quasi-biennial oscillation (QBO) using the NASA Goddard Earth Observing System (GEOS-5) Chemistry Climate Model. We performed four 30-year simulations with a continuous injection of sulfur dioxide on the equator at 0 degree longitude. The four simulations differ by the amount of sulfur dioxide injected (5Tg per year and 2.5 Tg per year) and the altitude of the injection (16km-25km and 22km-25km). We find that such an injection dramatically alters the quasi-biennial oscillation, prolonging the phase of easterly shear with respect to the control simulation. In the case of maximum perturbation, i.e. highest stratospheric aerosol burden, the lower tropical stratosphere is locked into a permanent westerly QBO phase. This locked QBO westerly phase is caused by the increased aerosol heating and associated warming in the tropical lower stratosphere.

Geoengineering↗

NASA NTRS2013

Tethered Satellites as an Enabling Platform for Operational Space Weather Monitoring Systems

Tethered satellites offer the potential to be an important enabling technology to support operational space weather monitoring systems. Space weather "nowcasting" and forecasting models rely on assimilation of near-real-time (NRT) space environment data to provide warnings for storm events and deleterious effects on the global societal infrastructure. Typically, these models are initialized by a climatological model to provide "most probable distributions" of environmental parameters as a function of time and space. The process of NRT data assimilation gently pulls the climate model closer toward the observed state (e.g., via Kalman smoothing) for nowcasting, and forecasting is achieved through a set of iterative semi-empirical physics-based forward-prediction calculations. Many challenges are associated with the development of an operational system, from the top-level architecture (e.g., the required space weather observatories to meet the spatial and temporal requirements of these models) down to the individual instruments capable of making the NRT measurements. This study focuses on the latter challenge: we present some examples of how tethered satellites (from 100s of m to 20 km) are uniquely suited to address certain shortfalls in our ability to measure critical environmental parameters necessary to drive these space weather models. Examples include long baseline electric field measurements, magnetized ionospheric conductivity measurements, and the ability to separate temporal from spatial irregularities in environmental parameters. Tethered satellite functional requirements are presented for two examples of space environment observables.

Gilchrist, Brian E.↗

NASA NTRS2014

The Impact of the Atlantic Cold Tongue on West African Monsoon Onset in Regional Model Simulations for 1998-2002

The Atlantic cold tongue (ACT) develops during spring and early summer near the Equator in the Eastern Atlantic Ocean and Gulf of Guinea. The hypothesis that the ACT accelerates the timing of West African monsoon (WAM) onset is tested by comparing two regional climate model (RM3) simulation ensembles. Observed sea surface temperatures (SST) that include the ACT are used to force a control ensemble. An idealized, warm SST perturbation is designed to represent lower boundary forcing without the ACT for the experiment ensemble. Summer simulations forced by observed SST and reanalysis boundary conditions for each of five consecutive years are compared to five parallel runs forced by SST with the warm perturbation. The article summarizes the sequence of events leading to the onset of the WAM in the Sahel region. The representation of WAM onset in RM3 simulations is examined and compared to Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Climatology Project (GPCP) and reanalysis data. The study evaluates the sensitivity of WAM onset indicators to the presence of the ACT by analysing the differences between the two simulation ensembles. Results show that the timing of major rainfall events and therefore theWAM onset in the Sahel are not sensitive to the presence of the ACT. However, the warm SST perturbation does increase downstream rainfall rates over West Africa as a consequence of enhanced specific humidity and enhanced northward moisture flux in the lower troposphere.

Regional model simulation↗

NASA NTRS2017

The Relationships Between the Trends of Mean and Extreme Precipitation

This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

global warming↗

NASA NTRS2017

GEOS-5 Seasonal Forecast System

Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9 month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

GEOS-5↗

NASA NTRSDate not supplied

Extensible Traffic Management (xTM) - High-altitude Operations and Beyond

The technology development of balloons, airships, and high-altitude long-endurance (HALE) high-aspect-ratio wing aerial vehicles has expedited the deployment of high-altitude operations above Flight Level (FL) 600. It allows broader communication service area coverage than at ground level and enables efficient and precise earth observation to help address global climate change. Meanwhile, a record number of orbital launches were conducted in 2021. New mission concepts including those for small satellites, satellite constellations, suborbital tourism and point to point cargo transport are being developed. To enable efficient and safe operations of new-entrant vehicles and to alleviate the potential burden on air traffic controllers, the concept of Unmanned aircraft systems Traffic Management (UTM) explored a different approach requiring cooperative operations among operators/pilots through operational intent sharing and coordination. This concept has been extended and proposed by the community to handle traffic management for high-altitude operations. While the concept and basic system were tested in UTM, there are many critical capabilities needed for high-altitude operations. This talk will introduce the challenges brought by high-altitude operations and space operations and on-going research activities in developing critical capabilities for extensible traffic management at NASA.

Extensible Traffic Management↗

NASA NTRSDate not supplied

Global SO 2 Data Record from OMPS Instruments on the JPSS Constellation

NASA’s Earth Observing System (EOS) SO 2 climate data record (CDR) started in 2004, with the launch of the Aura/Ozone Monitoring Instrument (OMI) and is now being continued with the SNPP/Ozone Mapping and Profiler Suite (OMPS) launched in 2011. Both OMI and SNPP/OMPS SO 2 CDRs are produced with the Goddard principal component analysis (PCA) spectral fitting algorithm. An advantage of the data-driven PCA retrieval technique is that it enables highly consistent retrievals from different instruments, by inherently accounting for various instrumental factors. To further extend the EOS SO 2 CDR, we are implementing the PCA SO 2 retrieval algorithm with the L1B measurements from OMPS instruments flying on the Joint Polar Satellite System (JPSS) constellation. In this presentation, we will provide an update on our progress in NOAA-20 (launched in 2017) and NOAA-21 (launched in 2022) PCA SO2 retrievals. We will focus on our new NOAA-20/OMPS PCA SO 2 EOS continuity product, to be publicly released in fall of 2023. We will present statistical analyses on the quality of NOAA-20 PCA SO 2 product, including retrieval noise, biases over background areas, and long-term stability. We will compare our PCA SO 2 retrievals from NOAA-20 with those from OMI, SNPP/OMPS, and S5P/TROPOMI (TROPOspheric Monitoring Instrument) for anthropogenic sources as well as large volcanic plumes. We will also discuss the application of a new machine learning technique that helps to further reduce the noise of NOAA-20 SO 2 retrievals. In addition, we will present preliminary PCA SO 2 retrievals from NOAA-21/OMPS, including those from direct readout implementation for aviation disaster avoidance. Finally, we will share some first results applying the PCA algorithm to NASA’s geostationary TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument to obtain hourly, high resolution SO 2 data over North America.

SO2↗

NASA NTRSDate not supplied

Continuing Long-term Global SO 2 Data Record with JPSS OMPS Instruments

NASA’s long-term Earth Observing System (EOS) SO 2 climate data record (CDR) started with Aura/Ozone Monitoring Instrument (OMI, launched in 2004) and is now being continued with the SNPP/Ozone Mapping and Profiler Suite (OMPS, launched in 2011). Both OMI and SNPP/OMPS SO 2 CDRs are produced with the Goddard principal component analysis (PCA) spectral fitting algorithm. By inherently accounting for various instrumental factors, the PCA technique enables highly consistent retrievals between different instruments. In this presentation, we will provide an overview on our effort to further extend the EOS SO 2 CDR, by implementing the PCA SO 2 algorithm with multiple OMPS instruments flying on the Joint Polar Satellite System (JPSS) constellation, including NOAA-20 (launched in 2017) and NOAA-21 (launched in 2022). We will present results analyzing our new NOAA-20/OMPS PCA SO 2 EOS continuity product, to be publicly released in fall of 2023. We will show statistical analyses on the quality of NOAA-20 PCA SO 2 product, such as retrieval noise, biases over background areas, and long-term stability. We will employ a previously established top-down method to estimate SO2 emissions from selected large point sources, using NOAA-20 SO 2 retrievals and assimilated wind fields as input. The SO 2 emission estimates derived from NOAA-20 retrievals will be compared with those from OMI, SNPP/OMPS, and S5P/TROPOMI (TROPOspheric Monitoring Instrument). We will also demonstrate the application of a new machine learning technique that further reduces the noise of NOAA-20 SO 2 retrievals. Finally, we will present preliminary PCA SO 2 retrievals from recently launched satellite sensors, including NOAA-21/OMPS and NASA’s geostationary TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument.

SO2↗

NASA NTRS2024

Bridgeport Urban Development: Leveraging NASA Earth Observations and Sociodemographic Data to Assess Urban Heat Vulnerability and Inform Cool Corridors in Bridgeport, Connecticut

Urban environments face hotter temperatures than suburban and rural areas due to higher concentrations of impervious surfaces, heat-retaining buildings, and lack of green space. Bridgeport, Connecticut, which was formerly a national manufacturing hub, is now the densest and most populous city in the state. Bridgeport experiences hotter temperatures, exposing its residents to more extreme temperatures than the surrounding affluent suburbs. Extreme heat affects the health of those exposed to it and intensifies energy demands. Understanding temperature differences is the first step in effectively directing mitigation efforts. Our partner, Groundwork Bridgeport, along with the Yale Urban Design Workshop, are planning a “cool corridors” project, implementing cooling infrastructure to combat urban heat. We used Landsat 8 Thermal Infrared Sensor and Landsat 9 Thermal Infrared Sensor-2 data to conduct a Land Surface Temperature analysis in Google Earth Engine for the county of Fairfield. A Principal Component Analysis was performed to identify indicators of social vulnerability in Bridgeport. We used the SOlar and LongWave Environmental Irradiance Geometry model to identify felt heat on the block level to inform where the partner should locate their cooling interventions to ensure they are most effective and equitable. We focused on the East Side of Bridgeport, which we found was 10 degrees hotter than other areas of Bridgeport and the neighboring town of Fairfield. We integrated our findings using Earth observations and additional sociodemographic and climate data into final communication products for our partners which will facilitate their selection of candidate locations for their Cool Corridors project.

Silas Kirsch↗

NASA NTRS2024

Aerosol Size Distribution Properties Associated With Cold-Air Outbreaks in the Norwegian Arctic

The aerosol particles serving as cloud condensation and ice nuclei contribute to key cloud processes associated with cold-air outbreak (CAO) events but are poorly constrained in climate models due to sparse observations. Here we retrieve aerosol number size distribution modes from measurements at Andenes, Norway, during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) and at Zeppelin Observatory, approximately 1000 km upwind from Andenes at Svalbard. During CAO events at Andenes, the sea-spray-mode number concentration is correlated with strong over-ocean winds with a mean of 8±4 cm−3 that is 71 % higher than during non-CAO conditions. Additionally, during CAO events at Andenes, the mean Hoppel minimum diameter is 6 nm smaller than during non-CAO conditions, though the estimated supersaturation is lower, and the mean number concentration of particles that likely activated in-cloud is 109±61 cm−3 with no statistically significant difference from the non-CAO mean of 99±66 cm−3. For CAO trajectories between Zeppelin Observatory and Andenes, the upwind-to-downwind change in number concentration is the largest for the accumulation mode with a mean decrease of 93±95 cm−3, likely attributable primarily to precipitation scavenging. These characteristic properties of aerosol number size distributions during CAO events provide guidance for evaluating CAO aerosol–cloud interaction processes in models.

accumulation mode particle scavenging↗

NASA NTRS2022

An Evaluation of Biomass Burning Aerosol Mass, Extinction, and Size Distribution in Geos Using Observations From Camp2EX

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulphate and nitrate aerosol just above the boundary layer. Aside from aerosol mass, extinction within GEOS is a function of ambient relative humidity and an assumed particle size distribution. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too aggressive within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module with GEOS may be necessary.

Aerosol Mass↗

NASA NTRSDate not supplied

Evaluation of GEOS Aerosols Using CAMP2Ex Observations

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through direct and semi-direct effects, as well as influencing air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm from AERONET and MODIS to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulfate and nitrate aerosol just above the boundary layer. Aerosol extinction within GEOS is a function of the mass of different aerosol species, the ambient relative humidity, the assumed spectral optical properties, and particle size distribution per species. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too high within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a single mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module within GEOS may be necessary.

Allison Collow↗

NASA NTRS2010

A Study of Cirrus Ice Particle Size Distribution Using TC4 Observations

An analysis of two days of in situ observations of ice particle size spectra, in convectively generated cirrus, obtained during NASA s Tropical Composition, Cloud, and Climate Coupling (TC4) mission is presented. The observed spectra are examined for their fit to the exponential, gamma, and lognormal function distributions. Characteristic particle size and concentration density scales are determined using two (for the exponential) or three (for the gamma and lognormal functions) moments of the spectra. It is shown that transformed exponential, gamma, and lognormal distributions should collapse onto standard curves. An examination of the transformed spectra, and of deviations of the transformed spectra from the standard curves, shows that the lognormal function provides a better fit to the observed spectra.

Tian, Lin↗

NASA NTRS2010

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Sandford, Stephen P.↗

NASA NTRS2013

The Martian Dust Cycle: Observations and Modeling

The dust cycle is critically important for Mars' current climate system. Suspended atmospheric dust affects the radiative balance of the atmosphere, and thus greatly influences the thermal and dynamical state of the atmosphere. Evidence for the presence of dust in the Martian atmosphere can be traced back to yellow clouds telescopically observed as early as the early 19th century. The Mariner 9 orbiter arrived at Mars in November of 1971 to find a planet completely enshrouded in airborne dust. Since that time, the exchange of dust between the planet's surface and atmosphere and the role of airborne dust on Mars' weather and climate has been studied using observations and numerical models. The goal of this talk is to give an overview of the observations and to discuss the successes and challenges associated with modeling the dust cycle. Dust raising events on Mars range in size from meters to hundreds of kilometers. During some years, regional storms merge to produce hemispheric or planet encircling dust clouds that obscure the surface and raise atmospheric temperatures by tens of kelvin. The interannual variability of planet encircling dust storms is poorly understood. Although the occurrence and season of large regional and global dust storms are highly variable from one year to the next, there are many features of the dust cycle that occur year after year. A low-level dust haze is maintained during northern spring and summer, while elevated levels of atmospheric dust occur during northern autumn and winter. During years without global-scale dust storms, two peaks in total dust loading are generally observed: one peak occurs before northern winter solstice and one peak occurs after northern winter solstice. Numerical modeling studies attempting to interactively simulate the Martian dust cycle with general circulation models (GCMs) include the lifting, transport, and sedimentation of radiatively active dust. Two dust lifting processes are commonly represented in these models: wind-stress lifting (i.e., saltation) and dust devil lifting. Although the predicted patterns of dust lifting and atmospheric dust loading from these simulations capture some aspects of the observed dust cycle, there are many notable differences between the simulated and observed dust cycles. For example, it is common for models to predict one peak in global dust loading near northern winter solstice due to excessive dust lifting in the Hellas basin at this season. Additionally, it is difficult for models to realistically capture the observed interannual variability in global dust storms. New avenues of dust cycle modeling research include exploring the effects of finite surface dust reservoirs and the effects of coupling the dust and water cycles on the predicted dust cycle.

Kahre, Melinda A.↗

DOE OSTI2023

Observationally driven Resource Assessment with CoupLEd models (ORACLE)

This project seeks to carry out a multifaceted analysis combining buoy observations, machine learning, turbulence, satellite data and high-resolution modeling. Our analyses will investigate air–sea interaction physics governing the variation of the winds with height and influence of clouds, uncertainty in coupled ocean-wave-atmosphere mesoscale models to capture certain key atmospheric phenomenon observed over the U.S. West Coast, impact of climate change, and the fidelity with which resource characterization models describe the range of observed offshore wind conditions. This project will focus its efforts on characterizing and assessing the atmospheric and oceanographic conditions along the U.S. West Coast.

Wind, Energy↗

NASA NTRS2015

Implications for Climate Sensitivity from the Response to Individual Forcings

Climate sensitivity to doubled CO2 is a widely-used metric of the large-scale response to external forcing. Climate models predict a wide range for two commonly used definitions: the transient climate response (TCR: the warming after 70 years of CO2 concentrations that riseat 1 per year), and the equilibrium climate sensitivity (ECS: the equilibrium temperature change following a doubling of CO2 concentrations). Many observational datasets have been used to constrain these values, including temperature trends over the recent past 16, inferences from paleo-climate and process-based constraints from the modern satellite eras. However, as the IPCC recently reported different classes of observational constraints produce somewhat incongruent ranges. Here we show that climate sensitivity estimates derived from recent observations must account for the efficacy of each forcing active during the historical period. When we use single forcing experiments to estimate these efficacies and calculate climate sensitivity from the observed twentieth-century warming, our estimates of both TCR and ECS are revised upward compared to previous studies, improving the consistency with independent constraints.

Sensitivity↗