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NASA NTRS1992

Chapman Conference on the Hydrologic Aspects of Global Climate Change, Lake Chelan, WA, June 12-14, 1990, Selected Papers

The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.

Lettenmaier, Dennis P.↗

NASA NTRS2002

A New Statistically based Autoconversion rate Parameterization for use in Large-Scale Models

The autoconversion rate is a key process for the formation of precipitation in warm clouds. In climate models, physical processes such as autoconversion rate, which are calculated from grid mean values, are biased, because they do not take subgrid variability into account. Recently, statistical cloud schemes have been introduced in large-scale models to account for partially cloud-covered grid boxes. However, these schemes do not include the in-cloud variability in their parameterizations. In this paper, a new statistically based autoconversion rate considering the in-cloud variability is introduced and tested in three cases using the Canadian Single Column Model (SCM) of the global climate model. The results show that the new autoconversion rate improves the model simulation, especially in terms of liquid water path in all three case studies.

Lin, Bing↗

NASA NTRS2016

The Viability of Trajectory Analysis for Diagnosing Dynamical and Chemical Influences on Ozone Concentrations in the UTLS

The viability of trajectory analysis for diagnosing the interplay between chemistry and dynamics is investigated by comparing ozone mixing ratios modelled using air-parcel pathways to values observed along flight tracks during ATTREX (Airborne Tropical TRopopause EXperiment). Trajectories are initiated at the locations of ozone observations and tracked backward in time to their sources at termini of backward trajectories. The modelled values of ozone utilize 3-dimensional analysis fields from WACCM (Whole Atmosphere Community Climate Model) (a chemical-climate model with dynamical fields nudged towards MERRA (Modern-Era Retrospective Analysis and Research Applications) reanalysis) and ERA-interim (product of ECMWF - the European Centre for Medium-Range Weather Forecasts) to determine source mixing ratios with chemical production and loss terms derived from the ozone chemistry used in WACCM. A statistical base of modelled ozone is constructed with 6 trajectory platforms (adiabatic, diabatic, and kinematic forced by ERA-interim and MERRA), two chemical models (WACCM chemistry and no chemistry), and 4 trajectory lengths (5, 10, 20, and 30 days). Linear regression is employed to separate systematic errors from random errors and to characterize the impact of source mixing ratios, path length, vertical motion, and chemistry on modelled ozone errors. Errors in the analysis ozone fields are large, if not dominant, contributors to model error. Random errors are particularly large for point-by-point comparisons, however averaging over 800 km (75 minutes) flight segments substantially reduces random error and exposes systematic errors. Of the two analysis ozone data sets, WACCM, which incorporates detailed chemistry, provides the smaller systematic errors while ERA-interim, which has crude chemistry but assimilates observational data, has the smaller random errors. Of the different trajectory platforms, adiabatic calculations produce the smaller random errors (irrespective of the use of chemistry) but both vertical motion and chemistry are required to optimally reduce systematic errors. These results suggest that meaningful analysis of dynamical and chemical interactions that control ozone mixing ratios are viable on spatial scales larger than a few reanalysis grid spaces, that errors in the analyzed ozone data sets are large but not prohibitively so, and that vertical velocities and heating rates from reanalysis data, while problematic, contain useful information [on the ozone concentrations in the UTLS (Upper Troposphere/Lower Stratosphere)].

ozone↗

NASA NTRSDate not supplied

Quantifying the Influence of Mechanistic Representation of Particle Dry Deposition on Historical Changes in Aerosol-Climate Interactions

Dry deposition removes short-lived climate forcers and their precursors from the atmosphere. The aerosol dry deposition schemes in many global climate models have been untouched for decades. Previous work hints that aerosol dry deposition is an uncertainty with respect to aerosol impacts on climate change. Here we demonstrate the impact of a more mechanistic aerosol dry deposition parameterization on the historical aerosol direct and cloud albedo effects using the NASA GISS global chemistry-climate model. We investigate two aerosol configurations – a “bulk” mass-based scheme and a modal scheme that more explicitly represents internal mixing and microphysics – of the global model. Both configurations show ~20% larger historical increases in non-dust aerosols globally with more mechanistic dry deposition. Changes to particle dry deposition, which are strongly a function of particle diameter, have a greater influence on the cloud albedo effect (up to 0.1 W m-2) when aerosols are more explicitly resolved in the modal scheme. On the other hand, impacts on the direct aerosol effect are small for both model configurations. In both aerosol configurations, the global climate effects are relatively insensitive to uncertainty in the strength of the uptake to dry deposition as suggested by (limited) measurements. In general, the low number of aerosol flux measurements and strong variability across existing observations challenge confidence in our understanding of dry depositional processes and changes with environmental conditions. Nonetheless, our work suggests that changes in dry deposition may be important for accurately estimating increases in aerosol abundances over the historical period, which is key for correct inferences about how cooling from aerosols has offset warming from greenhouse gases.

Dry deposition↗

NASA NTRS2014

Reply to Comment by Laprise on 'the Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: a Case Study over the Continental U.S. Using the GISS-ModelE2 and WRF Models'

In his comment, Laprise raises several points that we agree merit consideration. His primary critique is that our study [Racherla et al., 2012] tested the ability of the WRF regional climate model to reproduce historical temperature and precipitation change relative to the driving global climate model (GCM) using only a single simulation rather than an ensemble. He asserts that the observed changes are smaller than the internal variability in the climate system (i.e., not statistically significant) and that thus a single simulation should not necessarily be able to capture the observations. Laprise points out that the statistical signal is reduced for a multi-decadal trend such as the one we analyzed in comparison with mean climatology and cites two studies showing that for particular climate parameters it can take any years for a signal to be discerned over internal variability. He states that The results of theexperiment as designed were strongly influenced by the presence of internal variability and sampling errors,which masked the rather small climate changes that may have occurred as a consequence of changes inforcing during the period considered. While Laprise discusses statistics in general terms at some length, for the actual climate trends examined in our study, he offers no evidence that the forced signal was smallcompared with internal variability. The two studies he cites [de Ela et al., 2013; Maraun, 2013] do not provide convincing evidence as they concern climate variables averaged over different times and areas. One in fact examines extreme precipitation events, which by definition are rare and thus have a lower significance level. We accept the general point that it is important to consider internal variability, and as noted in our paper we agree that an ensemble of simulations is in principle an optimal, though computationally expensive, approach. While we did not present the statistical significance of the observations in our original paper, we have now evaluated those for the regional temperature trends used in our study to evaluate the added value of WRF and thus can analyze data as to the magnitude of the trends with respect to internal variability.

climate↗

NASA NTRS2002

Defining Top-of-Atmosphere Flux Reference Level for Earth Radiation Budget Studies

To estimate the earth's radiation budget at the top of the atmosphere (TOA) from satellite-measured radiances, it is necessary to account for the finite geometry of the earth and recognize that the earth is a solid body surrounded by a translucent atmosphere of finite thickness that attenuates solar radiation differently at different heights. As a result, in order to account for all of the reflected solar and emitted thermal radiation from the planet by direct integration of satellite-measured radiances, the measurement viewing geometry must be defined at a reference level well above the earth s surface (e.g., 100 km). This ensures that all radiation contributions, including radiation escaping the planet along slant paths above the earth s tangent point, are accounted for. By using a field-of- view (FOV) reference level that is too low (such as the surface reference level), TOA fluxes for most scene types are systematically underestimated by 1-2 W/sq m. In addition, since TOA flux represents a flow of radiant energy per unit area, and varies with distance from the earth according to the inverse-square law, a reference level is also needed to define satellite-based TOA fluxes. From theoretical radiative transfer calculations using a model that accounts for spherical geometry, the optimal reference level for defining TOA fluxes in radiation budget studies for the earth is estimated to be approximately 20 km. At this reference level, there is no need to explicitly account for horizontal transmission of solar radiation through the atmosphere in the earth radiation budget calculation. In this context, therefore, the 20-km reference level corresponds to the effective radiative top of atmosphere for the planet. Although the optimal flux reference level depends slightly on scene type due to differences in effective transmission of solar radiation with cloud height, the difference in flux caused by neglecting the scene-type dependence is less than 0.1%. If an inappropriate TOA flux reference level is used to define satellite TOA fluxes, and horizontal transmission of solar radiation through the planet is not accounted for in the radiation budget equation, systematic errors in net flux of up to 8 W/sq m can result. Since climate models generally use a plane-parallel model approximation to estimate TOA fluxes and the earth radiation budget, they implicitly assume zero horizontal transmission of solar radiation in the radiation budget equation, and do not need to specify a flux reference level. By defining satellite-based TOA flux estimates at a 20-km flux reference level, comparisons with plane-parallel climate model calculations are simplified since there is no need to explicitly correct plane-parallel climate model fluxes for horizontal transmission of solar radiation through a finite earth.

Loeb, N. G.↗

NASA NTRS2012

The Connection between Model Performance on the CCMVal Transport Diagnostics and Simulated Sensitivity of Ozone to Chlorine Change

The chemistry climate models that contributed simulations for past and future ozone evolution to the 2010 Scientific Assessment of Ozone Depletion were subject to extensive evaluation by the SPARC (Stratospheric Processes and their Role in Climate) CCMVal (Chemistry-Climate Model Validation) activity. The sensitivity of ozone to changes in composition and climate varies among the models, but the relationship between these variations and the model evaluations of CCMVal is not obvious. We have learned that the transport evaluation can be used to interpret the comparisons between observed and simulated columns of chlorine reservoirs, hydrochloric acid (HCl) and chlorine nitrate (ClONO2); these comparisons were part of the CCMVal evaluation of chemistry. The simulations with best performance on the transport diagnostics most faithfully reproduce the evolution and seasonal variation of the chlorine reservoirs as observed at NDACC (Network for Detection of Atmospheric Composition Change) stations (NyAlesund 78.9N, Kiruna 67.8N, Harestua 60.2N, Jungfraujoch 46.6N, Toronto 43.6N, Kitt Peak 31.9N, Izana 28.3N, Mauna Loa 19.5N, Lauder 45S and Arrival Heights 77.8S). In the simulations, the HCl in the lower stratosphere depends on total inorganic chlorine (Cly) and partitioning between HCl and ClON02. Total inorganic chlorine depends on the fractional release of chlorine from source gases, and ratio of ClON02 to HCl is inversely dependent on methane and varies quadratically with ozone. Simulated HCl from various models may agree with observations even though Cly is in error, partitioning is in error, or both. Simulated ozone sensitivity to chlorine is shown to be greater for models that produce larger values of chlorine nitrate for background chlorine levels, and vice versa. Comparisons with the NDACC data show why the models with 'best' transport have similar sensitivity to chlorine change. The realistic evolution of the simulated HCl and ClONO2 columns suggests realistic levels of Cly in the lower atmosphere. In addition, the wide range values for the sensitivity of ozone to chlorine obtained from the CCMVal simulations is explained by the wide range in lower atmospheric columns of ClONO2 and the concomitant wide range of levels for chlorine monoxide.

Douglass, Anne↗

NASA NTRS2013

Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate

Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

soil↗

NASA NTRS2013

Connections Between the Spring Breakup of the Southern Hemisphere Polar Vortex, Stationary Waves, and Air-sea Roughness

A robust connection between the drag on surface-layer winds and the stratospheric circulation is demonstrated in NASA's Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM). Specifically, an updated parameterization of roughness at the air-sea interface, in which surface roughness is increased for moderate wind speeds (4ms to 20ms), leads to a decrease in model biases in Southern Hemispheric ozone, polar cap temperature, stationary wave heat flux, and springtime vortex breakup. A dynamical mechanism is proposed whereby increased surface roughness leads to improved stationary waves. Increased surface roughness leads to anomalous eddy momentum flux convergence primarily in the Indian Ocean sector (where eddies are strongest climatologically) in September and October. The localization of the eddy momentum flux convergence anomaly in the Indian Ocean sector leads to a zonally asymmetric reduction in zonal wind and, by geostrophy, to a wavenumber-1 stationary wave pattern. This tropospheric stationary wave pattern leads to enhanced upwards wave activity entering the stratosphere. The net effect is an improved Southern Hemisphere vortex: the vortex breaks up earlier in spring (i.e., the spring late-breakup bias is partially ameliorated) yet is no weaker in mid-winter. More than half of the stratospheric biases appear to be related to the surface wind speed biases. As many other chemistry climate models use a similar scheme for their surface layer momentum exchange and have similar biases in the stratosphere, we expect that results from GEOSCCM may be relevant for other climate models.

air-sea interaction↗

NASA NTRS1981

The effects of surface evaporation parameterizations on climate sensitivity to solar constant variations

The effects of two different evaporation parameterizations on the sensitivity of simulated climate to solar constant variations are investigated by using a zonally averaged climate model. One parameterization is a nonlinear formulation in which the evaporation is nonlinearly proportional to the sensible heat flux, with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface (model A). The other is the formulation of Saltzman (1968) with the evaporation linearly proportional to the sensible heat flux (model B). The computed climates of models A and B are in good agreement except for the energy partition between sensible and latent heat at the earth's surface. The difference in evaporation parameterizations causes a difference in the response of temperature lapse rate to solar constant variations and a difference in the sensitivity of longwave radiation to surface temperature which leads to a smaller sensitivity of surface temperature to solar constant variations in model A than in model B. The results of model A are qualitatively in agreement with those of the general circulation model calculations of Wetherald and Manabe (1975).

Chou, S.-H.↗

NASA NTRS1981

Sensitivity of the Earth's climate to changes

Climate modeling is discussed with emphasis on the control of major parameters in such modeling. Possible feedbacks which operate on long time scales and are therefore not testable directly, are also discussed. Examples of simplified models are presented. The accuracy of several models is assessed and suggestions for improvements for climatic modeling are given.

North, G. R.↗

NASA NTRS1986

Theory of optimal weighting of data to detect climatic change

A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

Bell, T. L.↗

NASA NTRS2001

Modeling Feedbacks Between Water and Vegetation in the Climate System

Not only is water essential for life on earth, but life itself affects the global hydrologic cycle and consequently the climate of the planet. Whether the global feedbacks between life and the hydrologic cycle tend to stabilize the climate system about some equilibrium level is difficult to assess. We use a global climate model to examine how the presence of vegetation can affect the hydrologic cycle in a particular region. A control for the present climate is compared with a model experiment in which the Sahara Desert is replaced by vegetation in the form of trees and shrubs common to the Sahel region. A second model experiment is designed to identify the separate roles of two different effects of vegetation, namely the modified albedo and the presence of roots that can extract moisture from deeper soil layers. The results show that the presence of vegetation leads to increases in precipitation and soil moisture in western Sahara. In eastern Sahara, the changes are less clear. The increase in soil moisture is greater when the desert albedo is replaced by the vegetation albedo than when both the vegetation albedo and roots are added. The effect of roots is to withdraw water from deeper layers during the dry season. One implication of this study is that the insertion of vegetation into the Sahara modifies the hydrologic cycle so that the vegetation is more likely to persist than initially.

Miller, James R.↗

NASA NTRS2020

Seven Centuries of Reconstructed Brahmaputra River Discharge Demonstrate Underestimated High Discharge and Flood Hazard Frequency

The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309–2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956–1986 C.E.) ranks amongst the driest of the past seven centuries (13th percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24–38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.

tree-ring reconstruction↗

NASA NTRS2011

Understanding Effective Diameter and Its Application to Terrestrial Radiation in Ice Clouds

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, D(sub e), and their cloud water content (CWC), henceforth referred to as the D(sub e)-CWC assumption. This study challenges this assumption, showing that while the D(sub e)-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De less than ~60 m, which is where this D(sub e)-CWC assumption appears poorest. Treating optical properties solely in terms of D(sub e) and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the D(sub e)-CWC assumption breaks down, ice cloud optical properties appear to depend on D(sub e), IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al., 2005 database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the D(sub e)-IWC assumption was made possible by using MADA. MADA allows one to approximate the contribution of photon tunneling to absorption relative to other optical processes, which reveals that part of the error regarding the D(sub e)-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (DELTA L) due to absorption, the domain where the D(sub e)-IWC assumption is weakest was described in terms of D(sub e) and DELTA L.

Mitchell, D. L.↗

NASA NTRSDate not supplied

Estimating Future Changes of Energy Demand for Heating and Cooling Buildings at NASA Centers GC23J-1198

With its unique and trusted earth observations, NASA is a critical source in informing decisions that will help achieve the U.S. goal of Net-Zero Greenhouse Gas (GHG) Emissions by 2050. NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). As part of the development of new data products to support the energy and building heating/cooling design communities, we estimate the changes in energy required to heat and cool buildings in the future climate at 14 different NASA site locations spread throughout the continental United States, as projected by CMIP6 climate models under different emissions scenarios. Bias-corrected downscaled time series of meteorological variables are taken from NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP-CMIP6) downscaled climate model data. The spread between the different model projections is accounted for by analyzing both the ensemble average of 22 CMIP6 models and 6 representative models with different climate sensitivities and different interannual variability. Changes in energy use are estimated in two ways. First, changes in the total annual heating and cooling degree days (HDD and CDD, respectively) are calculated relative to the current climate. This is done at all 14 sites. Second, the downscaled time series are used as inputs into RETScreen(R), a clean energy management decision tool, to give an estimate of heating/cooling energy use for a typical office building. We use this estimation method with model data at Langley Research Center. In the next 50 years, the annual total of HDD (CDD) is projected to decrease by 8-38% (increase by 5-28%) at all sites, with the increase in CDD typically a larger magnitude the decrease in HDD. For a typical small office building at Langley Research Center, the amount of energy needed to cool increases by 33-54% and the amount of energy to heat decreases by 29-40%. POWER is working to develop long term climate data services based on these results to include in future data products to provide to users.

Bradley M. Hegyi↗

NASA NTRS2015

Connections Between the TTL and Sea Surface Temperatures: Interannual Variability and Trends

Comprehensive chemistry climate models and satellite data are used to investigate the forcing of variability in the tropical lower stratosphere and upper troposphere. As this region is the origination region for air parcels which enter the stratosphere, it is important to understand variability in this region on timescales ranging from the seasonal to decadal. The warming trend in the tropical upper troposphere over the past 30 years is strongest near the Indo Pacific warm pool, while the warming trend in the western and central Pacific is much weaker. In the lower stratosphere, these trends are reversed: the historical cooling trend is strongest over the Indo Pacific warm pool and is weakest in the western and central Pacific. These zonal variations are stronger than the zonal mean response in boreal winter. Targeted experiments with a chemistry climate model are used to demonstrate that sea surface temperature trends are driving the zonal asymmetry in upper tropospheric and lower stratospheric tropical temperature trends. The anomalous circulation set up by the changing SSTs has led to zonal structure in the ozone and water vapor trends near the tropopause, and subsequently to less water vapor entering the stratosphere. Projected future sea surface temperatures appear to drive a temperature and water vapor response whose zonal structure is similar to the historical response. In the lower stratosphere, the changes in water vapor and temperature due to projected future sea surface temperatures is of similar strength to, though slightly weaker than, that due directly to projected future CO2, ozone, and methane. Finally, targeted experiments with a chemistry climate model are used to demonstrate that seasonality and the location of the peak warming of sea surface temperatures dictate the response of stratospheric water vapor to El Nino. In spring, El Nino events in which sea surface temperature anomalies peak in the eastern Pacific lead to a warming at the tropopause above the warm pool region, and subsequently to more stratospheric water vapor (consistent with previous work). However, in fall and in early winter, and also during El Nino events in which the sea surface temperature anomaly is found mainly in the central Pacific, the response is qualitatively different: temperature changes in the warm pool region are nonuniform and less water vapor enters the stratosphere. The difference in water vapor in the lower stratosphere between the two variants of El Nino approaches 0.3 ppmv, while the difference between the winter and spring responses exceeds 0.5 ppmv.

Tropical Tropopause Layer↗

NASA NTRS2020

Effective radiative forcing and adjustments in CMIP6 models

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W/sq. m, comprised of 1.81 (±0.09) W/sq. m from CO2, 1.08 (± 0.21) W/sq. m from other well-mixed greenhouse gases, −1.01 (± 0.23) W/sq. m from aerosols and −0.09 (±0.13) W/sq. m from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W/sq. m. The majority of the remaining 0.21 W/sq. m is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W/sq. m, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

effective radiative forcing↗