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NASA NTRS1987

The role of earth radiation budget studies in climate and general circulation research

The use of earth radiation budget (ERB) data for climate and general circulation research is studied. ERB measurements obtained in the 1960's and 1970's have provided data on planetary brightness, planetary global energy balances, the greenhouse effect, solar insolation, meridional heat transport by oceans and atmospheres, regional forcing, climate feedback processes, and the computation of albedo values in low latitudes. The role of clouds in governing climate, in influencing the general circulation, and in determining the sensitivity of climate to external perturbations needs to be researched; a procedure for analyzing the ERB data, which will address these problems, is described. The approach involves estimating the clear-sky fluxes from the high spatial resolution scanner measurement and defining a cloud radiative forcing; the global average of the sum of the solar and long-wave cloud forcing yields the net radiative effect of clouds on the climate.

Ramanathan, V.↗

NASA NTRS2012

A Tropospheric Emission Spectrometer HDO/H2O Retrieval Simulator for Climate Models

Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the model meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, categorical approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and model meteorology at short time scales. To test this approach, nudged simUlations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the D fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30 over the ocean and decreases of up to 40 over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had D biases of 8 over ocean and 34 over land compared to TES D, which were less than the biases using raw model D fields.

Field, R. D.↗

NASA NTRS2018

Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS): Final Report of the ASCENDS Ad Hoc Science Definition Team

Improved remote sensing observations of atmospheric carbon dioxide (CO2) are critically needed to quantify, monitor, and understand the Earth's carbon cycle and its evolution in a changing climate. The processes governing ocean and terrestrial carbon uptake remain poorly understood,especially in dynamic regions with large carbon stocks and strong vulnerability to climate change,for example, the tropical land biosphere, the northern hemisphere high latitudes, and the Southern Ocean. Because the passive spectrometers used by GOSAT (Greenhouse gases Observing SATellite) and OCO-2 (Orbiting Carbon Observatory-2) require sunlit and cloud-free conditions,current observations over these regions remain infrequent and are subject to biases. These short comings limit our ability to understand and predict the processes controlling the carbon cycle on regional to global scales.In contrast, active CO2 remote-sensing techniques allow accurate measurements to be taken day and night, over ocean and land surfaces, in the presence of thin or scattered clouds, and at all times of year. Because of these benefits, the National Research Council recommended the National Aeronautics and Space Administration (NASA) Active Sensing of CO2 Emissions over Nights,Days, and Seasons (ASCENDS) mission in the 2007 report Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. The ability of ASCENDS to collect low-bias observations in these key regions is expected to address important gaps in our knowledge of the contemporary carbon cycle.The ASCENDS ad hoc Science Definition Team (SDT), comprised of carbon cycle modeling and active remote sensing instrument teams throughout the United States (US), worked to develop the mission's requirements and advance its readiness from 2008 through 2018. Numerous scientific investigations were carried out to identify the benefit and feasibility of active CO2 remote sensing measurements for improving our understanding of CO2 sources and sinks. This report summarizes their findings and recommendations based on mission modeling studies, analysis of ancillary meteorological data products, development and demonstration of candidate technologies, anddesign studies of the ASCENDS mission concept.

Kawa, S. Randolph↗

NASA NTRS2004

A GEO Hyperspectral Mission For Continental-Scale Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, a hyperspectral geostationary sensor should enable the development of new remote sensing measurements for important but as yet unobservable variables, and with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere are needed to identify the geographical locations of carbon sources/sinks and to improve regional climate models and global climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage provided by most polar-orbiting satellites, and without benefit of spectral indices that capture vegetation responses to stress conditions that down-regulate photosynthesis. Physiological status can be better assessed with spectral indices based on continuous, narrow (5 nm) bands, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world s coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of Ocean carbon uptake and its role in climate change scenarios. The GSFC Carbon Team has been pursuing a geostationary hyperspectral instrument, which would revolutionize our knowledge of biological processes on land, in the ocean, and along the coast by providing multiple, diurnal coverage. Preliminary studies in Goddard's Instrument Synthesis and Analysis Laboratory (ISAL) indicate that we can meet many of our science requirements: full spectral coverage (360-1000 nm); narrow bandwidths (5-10 nm); adequate ground resolution (100-200 m); and continental-scale coverage 4-6 times per day; all the while achieving a signal to noise ratio of between 500 and 1000 to 1. However, an innovative and bold focal plane design and a large mirror (1.8 meter diameter) would be required. The development of our science requirements and the results of the initial design study will be presented as well as our most recent technological developments.

Gervin, Janette C.↗

NASA NTRS1994

Improvements to TOVS retrievals over sea ice and applications to estimating Arctic energy fluxes

Modeling studies suggest that polar regions play a major role in modulating the Earth's climate and that they may be more sensitive than lower latitudes to climate change. Until recently, however, data from meteorological stations poleward of 70 degs have been sparse, and consequently, our understanding of air-sea-ice interaction processes is relatively poor. Satellite-borne sensors now offer a promising opportunity to observe polar regions and ultimately to improve parameterizations of energy transfer processes in climate models. This study focuses on the application of the TIROS-N operational vertical sounder (TOVS) to sea-ice-covered regions in the nonmelt season. TOVS radiances are processed with the improved initialization inversion ('3I') algorithm, providng estimates of layer-average temperature and moisture, cloud conditions, and surface characteristics at a horizontal resolution of approximately 100 km x 100 km. Although TOVS has flown continuously on polar-orbiting satellites since 1978, its potential has not been realized in high latitudes because the quality of retrievals is often significantly lower over sea ice and snow than over the surfaces. The recent availability of three Arctic data sets has provided an opportunity to validate TOVS retrievals: the first from the Coordinated Eastern Arctic Experiment (CEAREX) in winter 1988/1989, the second from the LeadEx field program in spring 1992, and the third from Russian drifting ice stations. Comparisons with these data reveal deficiencies in TOVS retrievals over sea ice during the cold season; e.g., ice surface temperature is often 5 to 15 K too warm, microwave emissivity is approximately 15% too low at large view angles, clear/cloudy scenes are sometimes misidentified, and low-level inversions are often not captured. In this study, methods to reduce these errors are investigated. Improvements to the ice surface temperature retrieval have reduced rms errors from approximately 7 K to 3 K; correction of microwaves (50 GHz) brightness temperatures for view angle dependence now allows the surface type (open water versus sea ice) to be determined; modifications to the clear/cloud tests have improved cloud detection over sea ice, especially where it is inhomogeneous; and improved surface temperature estimates have resulted in more successful diagnoses of low-level stratification. Applications of improved retrievals to studies of the Arctic energy budget are encouraging. Preliminary calculations of air-ice stress vectors, 10-m wind speed, and horizontal advection of heat and moisture are presented.

Francis, Jennifer A.↗

NASA NTRS2018

Bringing Climate Scientist's Tools into Classrooms to Improve Conceptual Understandings

Efforts to address anthropogenic global climate change (AGCC) require public understanding of Earth and climate science. To meet this need, educational reforms and prominent scientists have called for instructional approaches that teach students how climate scientists examine AGCC. Yet, only a few educational studies have reported clear empirical results on what instructional approaches and climate education technologies best accomplish this goal. This manuscript presents detailed analysis and statistically significant results on the educational impact pre to post of students learning to use a National Aeronautics and Space Administration (NASA) global climate model (GCM). This series of case studies demonstrates that differing instructional approaches and climate education technologies result in differing levels of understanding of AGCC and ability to engage with policies addressing it. Students who learned the scientific process of climate modeling scored significantly higher pre to post on exams (quantitatively) and gained more complete conceptual understandings of the issue (qualitatively). Yet, teaching students to conduct research with complex technology can be difficult. This study also found lecture-based learning better improved recall of facts about GCMs tested by multiple-choice questions. Our findings indicate what educational systems and related technologies might provide the public with the conceptual understandings necessary to engage in the political debate over AGCC.

Public understanding↗

NASA NTRS2000

Remote Sensing of Global Wetland Dynamics

Although natural wetlands only cover about 4% of the earth's ice-free land surface, they are the world's largest methane (CH4) source and the only one dominated by climate. In addition, wetlands affect climate by modulating temperatures and heat fluxes, storing water, increasing evaporation, and altering the seasonality of runoff and river discharge to the oceans. Current CH4 emissions from wetlands are relatively well understood but the sensitivity of wetlands and their emissions to climate variations remains the largest uncertainty in the global CH4 cycle and could strongly influence predictions of future climate. Therefore, characterizing climate-sensitive processes prevailing in the world's wetlands is crucial to understanding and predicting physical and biogeochemical responses of wetlands to interannual and longer-term climate variations. Recent research has resulted in the first generation of models to predict methane emissions from wetlands but the models must still be applied to static data on wetland distributions. Moreover, no models currently exist to realistically predict the distribution and dynamics of wetlands themselves for the current, or any other, climate. The dominant obstacle to modeling wetland dynamics has been lack of remote sensing techniques and data useful for characterizing quantitatively the seasonal and interannual variations of wetlands. We report on initial remote sensing studies undertaken to validate a global hydrological model linking rivers, takes and wetlands. Using a combination of SSM/I microwave and TOPEX Poseidon altimetry data sets, we developed and applied techniques to quantify inundation extent and duration for several large wetlands in tropical Africa and South America. Our initial results indicate that seasonally-inundated wetlands can be well characterized over large spatial scales and at monthly time scales using these remote sensing data. The results also confirm that currently available remote sensing products can be applied to provide crucial data to the research community modeling global hydrological and biogeochemical cycles.

Matthews, Elaine↗

NASA NTRS2001

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Johnson, Donald R.↗

NASA NTRS2011

Impacts of Aerosol Direct Effects on the South Asian Climate: Assessment of Radiative Feedback Processes Using Model Simulations and Satellite/Surface Measurements

Current assessment of aerosol radiative effect is hindered by our incomplete knowledge of aerosol optical properties, especially absorption, and our current inability to quantify physical and microphysical processes. In this research, we investigate direct aerosol radiative effect over heavy aerosol loading areas (e.g., Indo-Gangetic Plains, South/East Asia) and its feedbacks on the South Asian climate during the pre-monsoon season (March-June) using the Purdue Regional Climate Model (PRCM) with prescribed aerosol data derived by the NASA Goddard Earth Observing System Model (GEOS-5). Our modeling domain covers South and East Asia (60-140E and 0-50N) with spatial resolutions of 45 km in horizontal and 28 layers in vertical. The model is integrated from 15 February to 30 June 2008 continuously without nudging (i.e., only forced by initial/boundary conditions). Two numerical experiments are conducted with and without the aerosol-radiation effects. Both simulations are successful in reproducing the synoptic patterns on seasonal-to-interannual time scales and capturing a pre-monsoon feature of the northward rainfall propagation over Indian region in early June which shown in Tropical Rainfall Measuring Mission (TRMM) observation. Preliminary result suggests aerosol-radiation interactions mainly alter surface-atmosphere energetics and further result in an adjustment of the vertical temperature distribution in lower atmosphere (below 700 hPa). The modifications of temperature and associated rainfall and circulation feedbacks on the regional climate will be discussed in the presentation.

Wang, Sheng-Hsiang↗

DOE OSTI2025

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R↗

NASA NTRS1992

Frequency variations of the earth's obliquity and the 100-kyr ice-age cycles

Changes in the earth's climate are induced by variations in the earth's orbital parameters which modulate the seasonal distribution of solar radiation. Periodicities in the geological climate record with cycles of 100, 41, and 23 kyr have been linked with changes in obliquity, eccentricity, and precession of the equinoxes. The effect of variations of eccentricity during a 100 kyr period is weak relative to the signals from obliquity and precession variations and it may therefore be expected that the 100 kyr signal in the climate record would be of low intensity. However, this signal dominates the climate record and internal nonlinear processes within the climate system have previously been proposed to account for this fact. The author shows that variations in the frequency of the obliquity cycle can give rise to strong 100-kyr forcing of climate.

Liu, Han-Shou↗

DOE OSTI2025

Conceptualizing Coproduced Climate Research as Care: Practical Lessons Learned With Women Farmland‐Owners in the Central Midwest United States

ABSTRACT This article's team of interdisciplinary researchers and conservation educator‐practitioners learned with, and from, a group of women farmland‐owners regarding how to conceptualize coproduced climate research by putting “care” at the center—care for the soil, for relationships, for data. We outline the creation and evolution of a storytelling‐based conservation program that allowed our diverse group to discover how the language of care could integrate climate analysis, conservation, and relationship‐building to foster tangible solutions. As a result of the project, the women landowners took actions that supported social‐environmental resilience—from planting cover crops to fostering watershed/neighborhood relationships. Our diverse group of women landowners and researchers had very different experiences with conservation and often very different views on climate change itself, but, through storytelling and the language of care, we not only coproduced knowledge but also created relationships and action. This article outlines specific practices for how to inflect a coproduced process for climate resilience with practices that promote care and yield action projects.

Shenk, Linda [Department of English Iowa State Uni↗

NASA NTRS2010

The Continual Intercomparison of Radiation Codes (CIRC) Assessing Anew the Quality of GCM Radiation Algorithms

The simulation of changes in the Earth's climate due to solar and thermal radiative processes with global climate models (GCMs) is highly complex, depending on the parameterization of a multitude of nonlinearly coupled physical processes. In contrast, the germ of global climate change, the radiative forcing from enhanced abundances of greenhouse gases, is relatively well understood. The impressive agreement between detailed radiation calculations and highly resolved spectral radiation measurements in the thermal infrared under cloudless conditions (see, for example, Fig. 1) instills confidence in our knowledge of the sources of gaseous absorption. That the agreement spans a broad range of temperature and humidity regimes using instruments mounted on surface, aircraft, and satellite platforms not only attests to our capability to accurately calculate radiative fluxes under present conditions, but also provides confidence in the spectroscopic basis for computation of fluxes under conditions that might characterize future global climate (e.g., radiative forcing). Alas, the computational costs of highly resolved spectral radiation calculations cannot be afforded presently in GCMs. Such calculations have instead been used as the foundation for approximations implemented in fast but generally less accurate algorithms performing the needed radiative transfer (RT) calculations in GCMs. Credible climate simulations by GCMs cannot be ensured without accurate solar and thermal radiative flux calculations under all types of sky conditions: pristine cloudless, aerosol-laden, and cloudy. The need for accuracy in RT calculations is not only important for greenhouse gas forcing scenarios, but is also profoundly needed for the robust simulation of many other atmospheric phenomena, such as convective processes.

Oreopoulos, Lazaros↗

NASA NTRS2015

Aerosol-Cloud Interactions in the South-East Atlantic: Knowledge Gaps, Planned Observations to Address Them, and Implications for Global Climate Change Modeling

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. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical Stratocumulus (Sc) cloud decks in the world. The stratocumulus "climate radiators" are critical to the regional and global climate system. They interact with dense layers of BB aerosols that initially overlay the cloud deck, but later subside and are mixed into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects. As emphasized in the latest IPCC report, the global representation of these aerosol-cloud interaction processes in climate models is one of the largest uncertainty in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for global climate change scenarios. We discuss the current knowledge of aerosol and cloud property distributions based on satellite observations and sparse suborbital sampling, and describe planned field campaigns in the region. Specifically, we describe the scientific objectives and implementation of the following four synergistic, international research activities aimed at providing a process-level understanding of aerosol-cloud interactions over the SE Atlantic: 1) ORACLES (Observations of Aerosols above Clouds and their interactions), a five-year investigation between 2015 and 2019 with three Intensive Observation Periods (IOP), recently funded by the NASA Earth-Venture Suborbital Program, 2) CLARIFY-2016 (Cloud-Aerosol-Radiation Interactions and Forcing: Year 2016), a comprehensive observational and modeling programme funded by the UK's Natural Environment Research Council (NERC), and supported by the UK Met Office. 3) LASIC (Layered Atlantic Smoke Interactions with Clouds), a funded deployment of the DOE (Department of Energy) ARM Mobile Facility (AMF1) to Ascension Island, nominally for April 1 2016 - March 31 2017, and 4) ONFIRE (Observations of Fire's Impact on the southeast Atlantic Region), a proposed deployment of the NCAR C-130 aircraft to Sao Tome Island in 2017.

Aerosol-cloud↗

NASA NTRS2016

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

uncertainty↗

NASA NTRS2021

Observations of Greenhouse Gases as Climate Indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO2GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

greenhouse gases↗

NASA NTRS1998

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

The goal of this research is the continued development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. This work involves a combination of modeling and analysis efforts involving 4DDA datasets and simulations from the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) coordinate model and the GEOS GCM.

Johnson, Donald R.↗

NASA NTRS2022

Megadroughts in the Common Era and the Anthropocene

Megadroughts, often lasting multiple decades, have caused major ecological and societal disturbances in the past. While most research has focused on megadroughts in North America, the concept has gained increased international attention in recent years. In this Review, we discuss shared causes and features of Common Era and future megadroughts. Paleoclimate reconstructions spanning the last 2,000 years document the occurrence of megadroughts on every continent, save Antarctica. Megadroughts are often linked to decadal variations in sea surface temperatures, with radiative forcing and land-atmosphere interactions acting as secondary factors. Anthropogenic climate change has already contributed to recent megadroughts in southwestern North America and Chile-Argentina and will likely increase future megadrought risk and severity in many regions. Notably, future megadroughts will be differentiated from past events through higher temperatures, which act as the main driver of increased risk, severity, and impacts. Major deficiencies in our understanding of natural and anthropogenic megadrought processes remain, however. These include 1) sparse high-resolution paleoclimate information over some regions, 2) incomplete representations of internal variability and land-surface processes in climate models, and 3) the undetermined capacity of water-resource management systems to manage megadrought impacts. Resolving these key uncertainties will be necessary to increase confidence in projections of future megadrought risk and resiliency planning.

Droughts↗