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Norman G Loeb

Publications and source records attributed to Norman G Loeb.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Evaluating Twenty-Year Trends in Earth’s Energy Flows from Observations and Reanalyses

Satellite, reanalysis, and ocean in situ data are analyzed to evaluate regional, hemispheric and global mean trends in Earth’s energy fluxes during the first twenty years of the 21st century. Regional trends in net top-of-atmosphere (TOA) radiation from the Clouds and the Earth’s Radiant Energy System (CERES), ECMWF Reanalysis 5 (ERA5), and a model similar to ERA5 with prescribed sea surface temperature (SST) and sea ice differ markedly, particularly over the Eastern Pacific Ocean, where CERES observes large positive trends. Hemispheric and global mean net TOA flux trends for the two reanalyses are smaller than CERES, and their climatological means are half those of CERES in the southern hemisphere (SH) and more than nine times larger in the northern hemisphere (NH). The regional trend pattern of the divergence of total atmospheric energy transport (TEDIV) over ocean determined using ERA5 analyzed fields is similar to that inferred from the difference between TOA and surface fluxes from ERA5 short-term forecasts. There is also agreement in the trend pattern over ocean for surface fluxes inferred as a residual between CERES net TOA flux and ERA5 analysis TEDIV and surface fluxes obtained directly from ERA5 forecasts. Robust trends are observed over the Gulf Stream associated with enhanced surface-to-atmosphere transfer of heat. Within the ocean, larger trends in ocean heating rate are found in the NH than the SH after 2005, but the magnitude of the trend varies greatly among datasets.

Norman G Loeb↗
NASA NTRS2020

Effects of electromagnetic wave interference on observations of the Earth radiation budget

This paper investigates conditions necessary to match the irradiance derived by integrating radiances measured by a narrow field of view scanning radiometer with the irradiance measured by a hemispherical radiometer, both placed at a satellite altitude for Earth radiation budget estimates. When all sources are similar and they are spatially distributed randomly, then integrating radiance for the irradiance does not introduce a bias. Although the exact magnitude of the bias in other conditions is unknown, a finite area of the aperture that is much larger than the coherence area of radiation contributing to the Earth radiation budget, and a finite time to take a single measurement that is longer than the coherence time are likely to make the difference of the irradiance integrated from radiances and the irradiance measured by a hemispherical instrument insignificant. This conclusion does not contradict the existence of spatial coherence of light from incoherent sources. Therefore, electromagnetic energy absorbed by Earth is derivable from radiances measured by a scanning radiometer integrated over the Earth-viewing hemisphere and then averaging across all locations on the satellite orbital sphere when combined with solar irradiance measurements. Comparisons made in earlier studies show that the difference is less than 1%. In addition, when surface irradiances computed by a radiative transfer model constrained by top-of-atmosphere irradiances derived from radiance measurements are compared with downward shortwave irradiances taken by combinations of a pyreheliometer and a shaded pyranometer, or pyranometers, and with longwave ir- radiances taken by pyrgeometers, the biases in monthly mean irradiances are less than the uncertainties in the surface observations.

Seiji Kato↗
NASA NTRS2020

CERES Energy Balanced and Filled (EBAF) from Afternoon-Only Satellite Orbits

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) data product uses a diurnal correction methodology to produce a shortwave (SW) top-of-atmosphere (TOA) radiative flux time series that accounts for diurnal cycle changes between CERES observation times while ensuring that the stability of the EBAF record is tied as closely as possible to CERES instrument calibration stability. The current EBAF Ed4.1 data product combines observations from Terra and Aqua after July 2002. However, the Terra satellite will start to drift in Mean Local Time (MLT) in early 2021, and Aqua’s MLT will start to drift in 2022. To ensure the EBAF record remains temporally stable, we explore the feasibility of using only CERES instruments from afternoon satellite orbits with a tight 1330 MLT after July 2002. We test this approach by directly comparing SW TOA fluxes generated after applying diurnal corrections to Aqua-only and to Terra + Aqua for 07/2002–06/2019. We find that global climatological mean SW TOA fluxes for these two cases are within 0.01 W/sq.m and the trend of the difference is < is 0.03 W/sq.m per decade.

Norman G Loeb↗
NASA NTRS2020

Toward a Consistent Definition between Satellite and Model Clear-Sky Radiative Fluxes

A new method of determining clear-sky radiative fluxes from satellite observations for climate model evaluation is presented. The method consists of applying adjustment factors to existing satellite clear-sky broadband radiative fluxes that make the observed and simulated clear-sky flux definitions more consistent. The adjustment factors are determined from the difference between observation-based radiative transfer model calculations of monthly mean clear-sky fluxes obtained by ignoring clouds in the atmospheric column and by weighting hourly mean clear-sky fluxes with imager-based clear-area fractions. The global mean longwave (LW) adjustment factor is −2.2 W m−2 at the top of the atmosphere and 2.7 W m−2 at the surface. The LW adjustment factors are pronounced at high latitudes during winter and in regions with high upper-tropospheric humidity and cirrus cloud cover, such as over the west tropical Pacific, and the South Pacific and intertropical convergence zones. In the shortwave (SW), global mean adjustment is 0.5 W m−2 at TOA and −1.9 W m−2 at the surface. It is most pronounced over sea ice off of Antarctica and over heavy aerosol regions, such as eastern China. However, interannual variations in the regional SW and LW adjustment factors are small compared to those in cloud radiative effect. After applying the LW adjustment factors, differences in zonal mean cloud radiative effect between observations and climate models decrease markedly between 60°S and 60°N and poleward of 65°N. The largest regional improvements occur over the west tropical Pacific and Indian Oceans. In contrast, the impact of the SW adjustment factors is much smaller.

Norman G Loeb↗
NASA NTRS2018

Changes in Earth’s Energy Budget during and after the “Pause” in Global Warming: An Observational Perspective

This study examines changes in Earth’s energy budget during and after the global warming “pause” (or “hiatus”) using observations from the Clouds and the Earth’s Radiant Energy System. We find a marked 0.83±0.41 Wm−2 reduction in global mean reflected shortwave (SW) top-of-atmosphere (TOA) flux during the three years following the hiatus that results in an increase in net energy into the climate system. A partial radiative perturbation analysis reveals that decreases in low cloud cover are the primary driver of the decrease in SW TOA flux. The regional distribution of the SW TOA flux changes associated with the decreases in low cloud cover closely matches that of sea-surface temperature warming, which shows a pattern typical of the positive phase of the Pacific Decadal Oscillation. Large reductions in clear-sky SW TOA flux are also found over much of the Pacific and Atlantic Oceans in the northern hemisphere. These are associated with a reduction in aerosol optical depth consistent with stricter pollution controls in China and North America. A simple energy budget framework is used to show that TOA radiation (particularly in the SW) likely played a dominant role in driving the marked increase in temperature tendency during the post-hiatus period.

Norman G Loeb↗
NASA NTRS2018

TPSAS-NF1676L-29978-DND

Energy within an atmospheric column changes due to absorption of shortwave irradiance, emission of longwave irradiance, enthalpy released by precipitation, convergence of dry static and kinetic energy flux, and surface sensible heat flux. When satellite derived irradiance, precipitation, and surface sensible heat flux data products, as well as tendency and horizontal advection of dry static and kinetic energy fluxes from reanalysis are used to compute the atmospheric energy balance, energy fluxes does not balance exactly, resulting in an energy balance residual. A study by Kato et al. (2016) shows that large residuals exist over tropical oceans. In this study, we examine how the energy balance residual changes with time. If the energy balance residual for a given region is constant every year, this implies that annual anomalies of energy flux components balance over the region. If, however, the energy balance residual changes with time, an analysis of the dependence on atmospheric or cloud properties may provide information to understand the reason for the residual. A preliminary result indicates that significant interannual variabilities in energy balance residual exist when annual energy balance residuals over the entire ocean is examined. Temporal variability of regional energy budget residual and covariability of the energy budget residual with the multivariate ENSO index and the occurrence of specific cloud types will further be investigated.

Seiji Kato↗
NASA NTRS2017

TPSAS-NF1676L-26925-DND

Observationally-based atmospheric energy balance is analyzed using Clouds and the Earth's Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over tropics and positive over mid-latitudes. A negative residual implies that precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over western Pacific are, respectively, 0.84, 0.95, and 0.93. However, when all energy components are added, the atmospheric energy residual over tropical Pacific temporally correlates well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus does not alter enough atmospheric energy compared to the residual, these suggest 1) if retrieval errors associated with deep convective clouds are causing the column integrated atmospheric energy residual, the errors vary among individual deep convective clouds, 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over tropical western Pacific, and 3) it is also possible that cumulus congestus present cirrostratus that missed in massive sensor retrieval contribute the residual. Cloud objects used in the study that leads to the above conclusions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS). In this investigation, we use Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data to evaluate and verify above findings. Specifically, we focus on 3) above and analyze frequency of occurrence of cumulus congestus present under cirrostratus and correlation to the energy balance residual.

Seiji Kato↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33231-DND

It is well established that clouds have a profound influence on Earth's energy budget and that cloud feedbacks are responsible for much of the uncertainty in climate model projections of global warming in response to radiative forcing by greenhouse gases. While most model evaluation efforts focus on model representation of the observed mean state. For example, the regional mean climatology of key climate variables there is also tremendous value in testing how a model represents observed internal variations of the climate system. Here we use CERES observations during and after the so-called global warming hiatus to evaluate a subset of CMIP6 climate models. The CERES data show a marked 0.83 Wm-2 reduction in global mean reflected SW TOA flux during the three years following the hiatus that results in an increase in net energy into the climate system. The primary driver of the decrease in SW TOA flux is a reduction in low cloud cover over the eastern Pacific Ocean that occurs in response to an unprecedented increase in SSTs in that region following the hiatus. The CMIP6 simulations consist of AMIP-style experiments in which SSTs and sea-ice boundary conditions are constrained by observations. For each model, the AMIP runs were extended through the end of 2017 from the official CMIP6 AMIP end period in 2014. Results show that the models do a good job at capturing the pattern of observed changes in TOA flux observed by CERES, but tend to underestimate the magnitude.

Norman G Loeb↗
NASA NTRSDate not supplied

TPSAS-NF1676L-22727-DND

Satellite based top-of-atmosphere (TOA) and surface radiation budget observations are combined with mass corrected vertically integrated atmospheric energy divergence and tendency from reanalysis to infer the regional distribution of the TOA, atmospheric and surface energy budget terms over the globe. Hemispheric contrasts in the energy budget terms are used to determine the radiative and combined sensible and latent heat contributions to the cross-equatorial heat transports in the atmosphere (AHTEQ) and ocean (OHTEQ). The contrast in net atmospheric radiation implies an AHTEQ from the northern hemisphere (NH) to the southern hemisphere (SH) (0.75 PW), while the hemispheric difference in sensible and latent heat implies an AHTEQ in the opposite direction (0.51 PW), resulting in a net NH to SH AHTEQ (0.24 PW). At the surface, the hemispheric contrast in the radiative component (0.95 PW) dominates, implying a 0.44 PW SH to NH OHTEQ. Coupled Model Intercomparison Project Phase 5 (CMIP5) models with excessive net downward surface radiation and surface-to-atmosphere sensible and latent heat transport in the SH relative to the NH exhibit anomalous northward AHTEQ and overestimate SH tropical precipitation. The hemispheric bias in net surface radiative flux is due to too much longwave surface radiative cooling in the NH tropics in both clear and all-sky conditions and excessive shortwave surface radiation in the SH subtropics and extratropics due to an underestimation in reflection by clouds.

Norman G Loeb↗
NASA NTRSDate not supplied

Diagnosing Changes In Earth's Top-Of-Atmosphere Radiation Budget Since 2000

Earth’s radiation budget (ERB) is a key indicator of the climate system as it describes the delicate balance between how much of the sun’s energy reaching Earth is absorbed and how much thermal infrared radiation is emitted back to space. It is now well established that there is a positive net imbalance in ERB of 0.5-1 Wm-2. This imbalance, referred to as Earth’s Energy Imbalance (EEI), is shaped by natural and anthropogenic climate forcings and the climate system’s response to the forcing.When averaged over a long period, a positive EEI leads to an increase in surface temperature, sea levelrise, ocean heat content, melting of snow and sea-ice, and an acceleration of the hydrological cycle.EEI is also influenced by internal climate variability at interannual (e.g., El Niño/Southern Oscillation(ENSO)) and longer timescales (e.g., Pacific Decadal Oscillation (PDO)). Here we use CERES data toshow that since 2000, EEI has been increasing at a rate of 0.04+-0.03 Wm-2 per yr, corresponding to 0.8 Wm-1 over the 20-year CERES record. To understand the underlying causes for this increase, we analyze the CERES data in the context of internal climate variability indices and regional pattern changes. We also perform a partial radiative perturbation analysis that decomposes the TOA SW and LW radiation variations in terms of contributions by clouds, aerosols, surface albedo, temperature,water vapor and other gases (e.g., ozone, carbon dioxide, methane, etc.).

Norman G Loeb↗
NASA NTRSDate not supplied

Cloud Macrophysical Changes Observed by MODIS, CALIPSO, and CloudSat for the 11-year Period

Using the Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSatsatellitemeasurements, cloud macrophysicalchanges are examined from 2007 to 2017(Ham et al., 2021). Particularly, we compare cloud changes derived from MODIS passive sensor and CALIPSO-CloudSat (CALCS) combined active sensor measurements. Both MODIS and CALCS well capture general features of the cloud changes related to El Niño–Southern Oscillation (ENSO) events. However, because of better detections of thin cirrus clouds, CALCS cloud volume anomalies are better correlated with relative humidity anomalies, compared to MODIS. In addition, MODIS observations show a stronger anticorrelation between low and mid/high cloud volume anomalies, compared to CALCS, mainly due to limitations in detecting overlapping clouds by MODIS passive sensor.In addition, the geometrical thickness of MODIS mid/high clouds is thinner than that from CALCS, less affecting cloud amounts at 0-3 km altitude.

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