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At least 145 records · Page 8

Short-term climatic fluctuations forced by thermal anomalies

A two level, global, spectral model using pressure as a vertical coordinate was developed. The system of equations describing the model is nonlinear and quasi-geostrophic (linear balance). Static stability is variable in the model. A moisture budget is calculated in the lower layer only. Convective adjustment is used to avoid supercritical temperature lapse rates. The mechanical forcing of topography is introduced as a vertical velocity at the lower boundary. Solar forcing is specified assuming a daily mean zenith angle. The differential diabatic heating between land and sea is parameterized. On land and sea ice surfaces, a steady state thermal energy equation is solved to calculate the surface temperature. On the oceans, the sea surface temperature is specified as the climatological average for January. The model is used to simulate the January, February and March circulations. Previously announced in STAR as N83-14822

Hanna, A. F.↗

Radiative forcing of climate by changes in the vertical distribution of ozone

Results from a one-dimensional radiative-convective equilibrium model (similar to that of Lacis et al., 1981) of surface-temperature changes induced by changes in the vertical distribution of O3 in the atmosphere are parameterized and applied to measurement data for the northern midlatitudes during the 1970s. The construction of the model is outlined, and the results are presented in tables and graphs and discussed in detail. It is found that decreases in O3 in the lower stratosphere in the 1970s caused atmospheric cooling greater than that due to CO2 (thus possibly obscuring the CO2 greenhouse effect) and surface cooling which outweighed the warming effect of increased O3 in the troposphere. The net surface cooling is shown to be equal to about half of the estimated CO2 warming effect for the period.

Lacis, Andrew A.↗

Aerosol Radiative Forcing of Climate Assessed Using Satellite Data and Ground Based Sun/Sky Radiometers

Aerosol and cloud impacts on the earth's climate become a recent hot topic in climate studies. Having near future earth observing satellites, EOS-AM1, ENVISAT (Environmental Satellite) and ADEOS-2 (Advanced Earth Observation Satellite-2), it will be a good timing to discuss how to obtain and use the microphysical parameters of aerosols and clouds for studying their climate impacts. Center for Climate System Research (CCSR) of the University of Tokyo invites you to 'Symposium on synergy between satellite- remote sensing and climate modeling in aerosol and cloud issues.' Here, we like to discuss the current and future issues in the remote sensing of aerosol and cloud microphysical parameters and their climate modeling studies. This workshop is also one of workshop series on aerosol remote sensing held in 1996, Washington D. C., and Meribel, France in 1999. It should be reminded that NASDA/ADEOS-1 & -2 Workshop will be held in the following week (Dec. 6-10, 1999), so that this opportunity will be a perfect period for you to attend two meetings for satellite remote sensing in Japan. A weekend in Kyoto, the old capital of Japan, will add a nice memory to your visiting Japan.

Kaufman, Yoram J.↗

Remote Sensing of Aerosol and Aerosol Radiative Forcing of Climate from EOS Terra MODIS Instrument

The recent launch of EOS-Terra into polar orbit has begun to revolutionize remote sensing of aerosol and their effect on climate. Terra has five instruments, two of them,Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectro-Radiometer (MISR) are designed to monitor global aerosol in two different complementary ways. Here we shall discuss the use of the multispectral measurements of MODIS to derive: (1) the global distribution of aerosol load (and optical thickness) over ocean and land; (2) to measure the impact of aerosol on reflection of sunlight to space; and (3) to measure the ability of aerosol to absorb solar radiation. These measurements have direct applications on the understanding of the effect of aerosol on climate, the ability to predict climate change, and on the monitoring of dust episodes and man-made pollution. Principles of remote sensing of aerosol from MODIS will be discussed and first examples of measurements from MODIS will be provided.

Kaufman, Yoram↗

On the Feasibility of Studying Shortwave Aerosol Radiative Forcing of Climate Using Dual-Wavelength Aerosol Backscatter Lidar

The current low confidence in the estimates of aerosol-induced perturbations of Earth's radiation balance is caused by the highly non-uniform compositional, spatial and temporal distributions of tropospheric aerosols on a global scale owing to their heterogeneous sources and short lifetimes. Nevertheless, recent studies have shown that the inclusion of aerosol effects in climate model calculations can improve agreement with observed spatial and temporal temperature distributions. In light of the short lifetimes of aerosols, determination of their global distribution with space-borne sensors seems to be a necessary approach. Until recently, satellite measurements of tropospheric aerosols have been approximate and did not provide the full set of information required to determine their radiative effects. With the advent of active aerosol remote sensing from space (e.g., PICASSO-CENA), the applicability fo lidar-derived aerosol 180 deg -backscatter data to radiative flux calculations and hence studies of aerosol effects on climate needs to be investigated.

Redemann, Jens↗

The Study of Biomass Emissions for Defining Radiative Forcing of Climate

Accurate quantification of the amounts of trace gases and particulate matter emitted from vegetation fires and other sources of biomass burning (agricultural waste and biofuels) on a regional and global basis is required by a number of users, including scientists studying a wide range of atmospheric processes, national governments who are required to report greenhouse gas emissions, and those interested in quantifying the sources of air pollution that affect human health at regional scales. Over the past decade, improvements in the ability to detect and map fires using a number of different satellite systems have been achieved, largely through efforts coordinated through working groups organized by the IGBP Data and Information System and Global Observation of Forest Cover (GOFC) projects. In addition, significant advances and improvement in or understanding of the emissions factors for biomass burning in different biomes has resulted through efforts by the Biomass Burning Experiment (BIBEX) organized through the International Global Atmospheric Chemistry project. A number of satellite-based fire data products have been generated, and a number of new products will shortly be available. These new data products will provide the basis for estimating emissions from biomass burning on a global basis. However, a number of issues remain concerning the availability of other data sets needed to generate these estimates. Recognizing these issues, the GOFC-Fire Satellite Validation Workshop (held in Lisbon, Portugal on 9-11 July 2001), recommended that a workshop focusing on Improving Global Estimates of Atmospheric Emissions from Biomass Burning be organized. This workshop was held from 17- 19 July 2002 on the campus of the University of Maryland, College Park, Maryland. This workshop served as the annual meeting of the GOFC/GOLD-Fire Program. The overall goals of the meeting were to review the information products generated from satellite imagery and other sources that are currently available for developing emission estimates from biomass burning, evaluate areas where improved or additional products would be beneficial, and recommend products for use by the atmospheric science community.

Penner, Joyce↗

The Global Aerosol System and its Direct Forcing of Climate: Results From MODIS, AERONET and GOCART

Space observations from the MODIS instrument on board the Terra satellite, show in great details the spatial and seasonal variability of the global aerosol system. These spaceborne instruments distinguish fine aerosol from man-made regional pollution and biomass burning from mostly natural coarse dust and sea salt aerosol. E.g. fine regional pollution in and around the Indian sub-continent, Europe and North America; smoke from biomass burning in Southern Africa and Southern America; coarse dust from West Africa and mixed dust pollution and smoke from West and central Africa and East Asia. These regions were also studied extensively in focused field experiments and by the distributed AERONET network. The results generate the first climatology of the aerosol system, are used to derive the aerosol radiative effects and to estimate the anthropogenic component. The measurements are also used to evaluate each other and constrain aerosol transport models.

Kaufman, Y. J.↗

A Mechanism For Solar Forcing of Climate: Did the Maunder Minimum Cause the Little Ice Age?

The mechanism we wish to demonstrate exploits chemical, radiative, and dynamical sensitivities in the stratosphere to affect the climate of the troposphere. The sun, while its variability in total radiative output over the course of the solar cycle is on the order of 0.1%, exhibits variability in the UV output on the order of 5%. We expect to show that a substantially decreased solar UV output lessened the heating of the Earth's stratosphere during the Maunder Minimum, through decreased radiative absorption by ozone and oxygen. These changes in stratospheric heating would lead to major changes in the stratospheric zonal wind pattern which would in turn affect the propagation characteristics of planetary-scale waves launched in the winter hemisphere. Until recently, there was no quantitative data to relate the changes in the stratosphere to those at the surface. There is now empirical evidence from the NCEP Reanalysis data that a definitive effect of the solar cycle on climate in the troposphere exists. Our recent work is summarized as follows (see complete list of publications in later part of this report).

Yung, Yuk L.↗

Changes in Stratiform Clouds of Mesoscale Convective Complex Introduced by Dust Aerosols

Aerosols influence the earth s climate through direct, indirect, and semi-direct effects. There are large uncertainties in quantifying these effects due to limited measurements and observations of aerosol-cloud-precipitation interactions. As a major terrestrial source of atmospheric aerosols, dusts may serve as a significant climate forcing for the changing climate because of its effect on solar and thermal radiation as well as on clouds and precipitation processes. Latest satellites measurements enable us to determine dust aerosol loadings and cloud distributions and can potentially be used to reduce the uncertainties in the estimations of aerosol effects on climate. This study uses sensors on various satellites to investigate the impact of mineral dust on cloud microphysical and precipitation processes in mesoscale convective complex (MCC). A trans-Atlantic dust outbreak of Saharan origin occurring in early March 2004 is considered. For the observed MCCs under a given convective strength, small hydrometeors were found more prevalent in the dusty stratiform regions than in those regions that were dust free. Evidence of abundant cloud ice particles in the dust regions, particularly at altitudes where heterogeneous nucleation of mineral dust prevails, further supports the observed changes of clouds and precipitation. The consequences of the microphysical effects of the dust aerosols were to shift the size spectrum of precipitation-sized hydrometeors from heavy precipitation to light precipitation and ultimately to suppress precipitation and increase the lifecycle of cloud systems, especially over stratiform areas.

Lin, B.↗

TPSAS-NF1676L-10947-DND

There are large uncertainties in quantifying dust effects on the climate because of the limitations on the measurements and observations of dust-cloud-precipitation-dynamics interactions. As a major terrestrial source of atmospheric aerosols, dusts may serve as a significant climate forcing for the changing climate due to its effect on solar and thermal radiation as well as on clouds and precipitation processes. Latest satellites measurements enable us to determine dust loadings and cloud distributions and can potentially be used to reduce the uncertainties in the estimations of aerosol effects on climate. This study uses sensors on various satellites to investigate the impact of mineral dust on cloud microphysical and precipitation processes in convective systems. A trans-Atlantic dust outbreak of Saharan origin occurring in early March 2004 is considered. For the observed convective systems under a given convective strength, small hydrometeors were found more prevalent in the dusty stratiform regions than in those regions that were dust free. Evidence of abundant cloud ice particles in the dust regions, particularly at altitudes where heterogeneous nucleation of mineral dust prevails, further supports the observed changes of clouds and precipitation. These microphysical effects of the dusts on clouds are to shift the size spectrum of precipitation-sized hydrometeors from heavy precipitation to light precipitation and ultimately to suppress precipitation and increase the lifecycle of cloud systems, especially for stratiform clouds.

B Lin↗

Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks

Abstract Assessing forced climate change requires the extraction of the forced signal from the background of climate noise. Traditionally, tools for extracting forced climate change signals have focused on one atmospheric variable at a time, however, using multiple variables can reduce noise and allow for easier detection of the forced response. Following previous work, we train artificial neural networks to predict the year of single‐ and multi‐variable maps from forced climate model simulations. To perform this task, the neural networks learn patterns that allow them to discriminate between maps from different years—that is, the neural networks learn the patterns of the forced signal amidst the shroud of internal variability and climate model disagreement. When presented with combined input fields (multiple seasons, variables, or both), the neural networks are able to detect the signal of forced change earlier than when given single fields alone by utilizing complex, nonlinear relationships between multiple variables and seasons. We use layer‐wise relevance propagation, a neural network explainability tool, to identify the multivariate patterns learned by the neural networks that serve as reliable indicators of the forced response. These “indicator patterns” vary in time and between climate models, providing a template for investigating inter‐model differences in the time evolution of the forced response. This work demonstrates how neural networks and their explainability tools can be harnessed to identify patterns of the forced signal within combined fields.

54 ENVIRONMENTAL SCIENCES↗

Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models

The radiative forcing of anthropogenic aerosols associated with aerosol–cloud interactions (RF(sub aci)) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RF(sub aci), is generally simplified in climate models. Here we employ outputs from long-term (30-years) simulations of a global size-resolved (sectional) aerosol microphysics model and a machine-learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS-ModelE2.1 with a mass-based One-Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS-ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RF(sub aci) from −1.46 W⋅m(exp −2) to −1.11 W⋅m(exp −2). This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RF(sub aci) without compromising their computing efficiency.

Radiative forcing↗

The Turning Point of the Aerosol Era

Over the CMIP6 historical period (1850–2014), aerosols provided the largest negative forcing compared to all other climate forcings via their ability to absorb or scatter solar radiation and alter clouds. Aerosols played an important role in counterbalancing warming by greenhouse gases (GHGs). Here we study aerosol forcing trends in the CMIP6 simulations of the NASA Goddard Institute for Space Studies (GISS) ocean-atmosphere ModelE version 2.1 (GISS-E2.1-G) using a fully coupled atmospheric composition configuration, including interactive gas-phase chemistry, and either an aerosol microphysical (MATRIX) or a mass-based aerosol (OMA) module. Simulations of the CMIP6 historical period are analyzed as well as four Shared Socioeconomic Pathway (SSP) future scenarios for 2015–2100: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The main conclusion of this study is that aerosol forcing in the GISS model has reached its turning point, switching from globally increasing to a decreasing trend in the first decade of the 21st century. This result is robust, independent of which aerosol module or SSP scenario is used. Non-linear aerosol-cloud interactions dominate as a forcing agent over aerosol-radiation interactions. Aerosols' ability to counterbalance GHG forcing on the global scale is today at a level comparable to that at the beginning of the last century. In the 1980s, the decade of largest global aerosol loads, aerosols balanced up to 80% of GHG forcing. As a consequence, global warming of the last decades, which is primarily driven by greenhouse gases, has been augmented by the effect of decreasing aerosol cooling in our model. By the end of this century, following the SSP scenarios, aerosols will only counterbalance 0%–20% of GHG forcing, depending on model and on scenario.

Aerosol forcing↗

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

Drivers of Precipitation Change: An Energetic Understanding

The response of the hydrological cycle to climate forcings can be understood within the atmospheric energy budget framework. In this study precipitation and energy budget responses to five forcing agents are analyzed using 10 climate models from the Precipitation Driver Response Model Intercomparison Project (PDRMIP). Precipitation changes are split into a forcing-dependent fast response and a temperature-driven hydrological sensitivity. Globally, when normalized by top-of-atmosphere (TOA) forcing, fast precipitation changes are most sensitive to strongly absorbing drivers (CO2, black carbon). However, over land fast precipitation changes are most sensitive to weakly absorbing drivers (sulfate, solar) and are linked to rapid circulation changes. Despite this, land-mean fast responses to CO2 and black carbon exhibit more intermodel spread. Globally, the hydrological sensitivity is consistent across forcings, mainly associated with increased longwave cooling, which is highly correlated with intermodel spread. The land-mean hydrological sensitivity is weaker, consistent with limited moisture availability. The PDRMIP results are used to construct a simple model for land-mean and sea-mean precipitation change based on sea surface temperature change and TOA forcing. The model matches well with CMIP5 ensemble mean historical and future projections, and is used to understand the contributions of different drivers. During the twentieth century, temperature-driven intensification of land-mean precipitation has been masked by fast precipitation responses to anthropogenic sulfate and volcanic forcing, consistent with the small observed trend. However, as projected sulfate forcing decreases, and warming continues, land-mean precipitation is expected to increase more rapidly, and may become clearly observable by the mid-twenty-first century.

Richardson, T. B.↗