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At least 271 records · Page 15

Changes in the Intensity and Frequency of Atmospheric Blocking and Associated Heat Waves During Northern Summer Over Eurasia in the CMIP5 Model Simulations

The Russia heat wave and wild fires of the summer of 2010 was the most extreme weather event in the history of the country. Studies show that the root cause of the 2010 Russia heat wave/wild fires was an atmospheric blocking event which started to develop at the end of June and peaked around late July and early August. Atmospheric blocking in the summer of 2010 was anomalous in terms of the size, duration, and the location, which shifted to the east from the normal location. This and other similar continental scale severe summertime heat waves and blocking events in recent years have raised the question of whether such events are occurring more frequently and with higher intensity in a warmer climate induced by greenhouse gases. We studied the spatial and temporal distributions of the occurrence and intensity of atmospheric blocking and associated heat waves for northern summer over Eurasia based on CMIPS model simulations. To examine the global warming induced change of atmospheric blocking and heat waves, experiments for a high emissions scenario (RCP8.S) and a medium mitigation scenario (RCP4.S) are compared to the 20th century simulations (historical). Most models simulate the mean distributions of blockings reasonably well, including major blocking centers over Eurasia, northern Pacific, and northern Atlantic. However, the models tend to underestimate the number of blockings compared to MERRA and NCEPIDOE reanalysis, especially in western Siberia. Models also reproduced associated heat waves in terms of the shifting in the probability distribution function of near surface temperature. Seven out of eight models used in this study show that the frequency of atmospheric blocking over the Europe will likely decrease in a warmer climate, but slightly increase over the western Siberia. This spatial pattern resembles the blocking in the summer of 2010, indicating the possibility of more frequent occurrences of heat waves in western Siberia. In this talk, we will also discuss the potential effect of atmosphere-land feedback, particularly how the wetter spring affects the frequency and intensity of atmospheric blocking and heat wave during summer.

Kim, Kyu-Myong↗

Decadal Prediction Skill in the GEOS-5 Forecast System

A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office?s GEOS-5 Atmosphere-Ocean General Circulation Model (AOGCM). The hindcasts are initialized every December from 1959 to 2010 following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multi-variate ensemble optimal interpolation ocean and sea-ice reanalysis, and from the atmospheric reanalysis (MERRA, the Modern-Era Retrospective Analysis for Research and Applications) generated using the GEOS-5 atmospheric model. The forecast skill of a three-member-ensemble mean is compared to that of an experiment without initialization but forced with observed CO2. The results show that initialization acts to increase the forecast skill of Northern Atlantic SST compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. The annual-mean Atlantic Meridional Overturning Circulation (AMOC) index is predictable up to a 5-year lead time, consistent with the predictable signal in upper ocean heat content over the Northern Atlantic. While the skill measured by Mean Squared Skill Score (MSSS) shows 50% improvement up to 10-year lead forecast over the subtropical and mid-latitude Atlantic, however, prediction skill is relatively low in the subpolar gyre, due in part to the fact that the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region appears to be unrealistic. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.

Ham, Yoo-Geun↗

Highlights of the First 15 Months of Aquarius Salinity Measurements

Aquarius satellite salinity measurements are resolving the major global and regional spatial patterns, and temporal variations, since the start of routine data collection on 25 August 2011. This description includes the principal seasonal variations over the first annual cycle as observed by the mission. In particular, we identify the evolution of low salinity anomalies associated with the Atlantic and Pacific intertropical convergence zones (ITCZ), major river outflows such as the Amazon, a seasonal low salinity anomaly in the Panama bight, and other features. We also explore the links that the salinity variations have with precipitation and surface currents. We then will describe the variations related to the presently evolving 2012 El Nino, now evident, as it progresses through the summer and fall 2012. We conclude with a brief summary of the Aquarius data products and validation

Lagerloef, Gary S. E.↗

The Mars Dust Cycle: Investigating the Effects of Radiatively Active Water Ice Clouds on Surface Stresses and Dust Lifting Potential with the NASA Ames Mars General Circulation Model

The dust cycle is a critically important component of Mars' current climate system. Dust is present in the atmosphere of Mars year-round but the dust loading varies with season in a generally repeatable manner. Dust has a significant influence on the thermal structure of the atmosphere and thus greatly affects atmospheric circulation. The dust cycle is the most difficult of the three climate cycles (CO2, water, and dust) to model realistically with general circulation models. Until recently, numerical modeling investigations of the dust cycle have typically not included the effects of couplings to the water cycle through cloud formation. In the Martian atmosphere, dust particles likely provide the seed nuclei for heterogeneous nucleation of water ice clouds. As ice coats atmospheric dust grains, the newly formed cloud particles exhibit different physical and radiative characteristics. Thus, the coupling between the dust and water cycles likely affects the distributions of dust, water vapor and water ice, and thus atmospheric heating and cooling and the resulting circulations. We use the NASA Ames Mars GCM to investigate the effects of radiatively active water ice clouds on surface stress and the potential for dust lifting. The model includes a state-of-the-art water ice cloud microphysics package and a radiative transfer scheme that accounts for the radiative effects of CO2 gas, dust, and water ice clouds. We focus on simulations that are radiatively forced by a prescribed dust map, and we compare simulations that do and do not include radiatively active clouds. Preliminary results suggest that the magnitude and spatial patterns of surface stress (and thus dust lifting potential) are substantial influenced by the radiative effects of water ice clouds.

Kahre, Melinda A.↗

Tropical Atlantic Dust and Smoke Aerosol Variabilities Related to the Madden-Julian Oscillation in MODIS and MISR Observations

In this study, MODIS fine mode fraction and MISR non-spherical fraction are 2used to derive dust and smoke AOT components (tau(sub dust) and tau(sub smoke)) over the tropical Atlantic, and their variabilities related to the Madden-Julian Oscillation (MJO) are then investigated. Both MODIS and MISR show a very similar dust and smoke winter climatology. tau(sub dust) is found to be the dominant aerosol component over the tropical Atlantic while tau(sub smoke) is significantly smaller than tau(sub dust). The daily MODIS and MISR tau(sub dust) are overall highly correlated, with the correlation coefficients typically about 0.7 over the North Atlantic. The consistency between the MODIS and MISR dust and smoke aerosol climatology and daily variations give us confidence to use these two data sets to investigate their relative contributions to the total AOT variation associated with the MJO. However, unlike the MISR dust discrimination, which is based on particle shape retrievals, the smoke discrimination is less certain, based on assumed partitioning of maritime aerosol for both MISR and MODIS. The temporal evolution and spatial patterns of the tau(sub dust) anomalies associated with the MJO are consistent between MODIS and MISR. The tau(sub dust) anomalies are very similar to those of tau anomalies, and are of comparable magnitude. In contrast, the MJO-related tau(sub smoke) anomalies are rather small, and the tau(sub mar) anomalies are negligible. The consistency between the MODIS and MISR results suggests that dust aerosol is the dominant component on the intra-seasonal time scale over the tropical Atlantic Ocean.

Guo, Yanjuan↗

Upper-Ocean Heat Balance Processes and the Walker Circulation in CMIP5 Model Projections

Considerable uncertainty remains as to the importance of mechanisms governing decadal and longer variability of the Walker Circulation, its connection to the tropical climate system, and prospects for tropical climate change in the face of anthropogenic forcing. Most contemporary climate models suggest that in response to elevated CO2 and a warmer but more stratified atmosphere, the required upward mass flux in tropical convection will diminish along with the Walker component of the tropical mean circulation as well. Alternatively, there is also evidence to suggest that the shoaling and increased vertical stratification of the thermocline in the eastern Pacific will enable a muted SST increase there-- preserving or even enhancing some of the dynamical forcing for the Walker cell flow. Over the past decade there have been observational indications of an acceleration in near-surface easterlies, a strengthened Pacific zonal SST gradient, and globally-teleconnected dislocations in precipitation. But is this evidence in support of an ocean dynamical thermostat process posited to accompany anthropogenic forcing, or just residual decadal fluctuations associated with variations in warm and cold ENSO events and other stochastic forcing? From a modeling perspective we try to make headway on this question by examining zonal variations in surface energy fluxes and dynamics governing tropical upper ocean heat content evolution in the WCRP CMIP5 model projections. There is some diversity among model simulations; for example, the CCSM4 indicates net ocean warming over the IndoPacific region while the CSIRO model concentrates separate warming responses over the central Pacific and Indian Ocean regions. The models, as with observations, demonstrate strong local coupling between variations in column water vapor, downward surface longwave radiation and SST; but the spatial patterns of changes in the sign of this relationship differ among models and, for models as a whole, with observations. Our analysis focuses initially on probing the inter-model differences in energy fluxes / transports and Walker Circulation response to forcing. We then attempt to identify statistically the El Nino- / La Nina-related ocean heat content variability unique to each model and regress out the associated energy flux, ocean heat transport and Walker response on these shorter time scales for comparison to that of the anthropogenic signals.

Robertson, F. R.↗

Global Distribution of Cloud Droplet Number Concentration, Autoconversion Rate, and Aerosol Indirect Effect Under Diabatic Droplet Activation

This study presents a global assessment of the sensitivity of droplet number to diabatic activation (i.e., including effects from entrainment of dry air) and its first-order tendency on indirect forcing and autoconversion. Simulations were carried out with the NASA Global Modeling Initiative (GMI) atmospheric and transport model using climatological metereorological fields derived from the former NASA Data Assimilation Office (DAO), the NASA Finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II (GISS) GCM. Cloud droplet number concentration (CDNC) is calculated using a physically based prognostic parameterization that explicitly includes entrainment effects on droplet formation. Diabatic activation results in lower CDNC, compared to adiabatic treatment of the process. The largest decrease in CDNC (by up to 75 percent) was found in the tropics and in zones of moderate CCN concentration. This leads to a global mean effective radius increase between 0.2-0.5 micrometers (up to 3.5 micrometers over the tropics), a global mean autoconversion rate increase by a factor of 1.1 to 1.7 (up to a factor of 4 in the tropics), and a 0.2-0.4 W m(exp -2) decrease in indirect forcing. The spatial patterns of entrainment effects on droplet activation tend to reduce biases in effective radius (particularly in the tropics) when compared to satellite retrievals. Considering the diabatic nature of ambient clouds, entrainment effects on CDNC need to be considered in GCM studies of the aerosol indirect effect.

Barahona, Donifan↗

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing U.S. land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha/yr of forests were disturbed annually, representing 1.09%/yr of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, while variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic since the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy.

Masek, Jeffrey G.↗

A Review of Global Satellite-derived Snow Products

Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

Frei, Allan↗

Regional Warming from Aerosol Removal over the United States: Results from a Transient 2010-2050 Climate Simulation

We use a general circulation model (NASA Goddard Institute for Space Studies GCM 3) to investigate the regional climate response to removal of aerosols over the United States. We perform a pair of transient 2010e2050 climate simulations following a scenario of increasing greenhouse gas concentrations, with and without aerosols over the United States and with present-day aerosols elsewhere. We find that removing U.S. aerosol significantly enhances the warming from greenhouse gases in a spatial pattern that strongly correlates with that of the aerosol. Warming is nearly negligible outside the United States, but annual mean surface temperatures increase by 0.4e0.6 K in the eastern United States. Temperatures during summer heat waves in the Northeast rise by as much as 1e2 K due to aerosol removal, driven in part by positive feedbacks involving soil moisture and low cloud cover. Reducing U.S. aerosol sources to achieve air quality objectives could thus have significant unintended regional warming consequences.

Mickley, L. J.↗

A Storm Surge and Inundation Model of the Back River Watershed at NASA Langley Research Center

This report on a Virginia Institute for Marine Science project demonstrates that the sub-grid modeling technology (now as part of Chesapeake Bay Inundation Prediction System, CIPS) can incorporate high-resolution Lidar measurements provided by NASA Langley Research Center into the sub-grid model framework to resolve detailed topographic features for use as a hydrological transport model for run-off simulations within NASA Langley and Langley Air Force Base. The rainfall over land accumulates in the ditches/channels resolved via the model sub-grid was tested to simulate the run-off induced by heavy precipitation. Possessing both the capabilities for storm surge and run-off simulations, the CIPS model was then applied to simulate real storm events starting with Hurricane Isabel in 2003. It will be shown that the model can generate highly accurate on-land inundation maps as demonstrated by excellent comparison of the Langley tidal gauge time series data (CAPABLE.larc.nasa.gov) and spatial patterns of real storm wrack line measurements with the model results simulated during Hurricanes Isabel (2003), Irene (2011), and a 2009 Nor'easter. With confidence built upon the model's performance, sea level rise scenarios from the ICCP (International Climate Change Partnership) were also included in the model scenario runs to simulate future inundation cases.

Loftis, Jon Derek↗

Global Characteristics of the Correlation and Time Lag Between Solar and Ionospheric Parameters in the 27-day Period

The 27-day variations of topside ionosphere are investigated using the in-situ electron density measurements from the CHAMP planar Langmuir probe and GRACE K-band ranging system. As the two satellite systems orbit at the altitudes of approx. 370 km and approx. 480 km, respectively, the satellite data sets are greatly valuable for examining the electron density variations in the vicinity of F2-peak. In a 27-day period, the electron density measurements from the satellites are in good agreements with the solar flux, except during the solar minimum period. The time delays are mostly 1-2 day and represent the hemispherical asymmetry. The globally-estimated spatial patterns of the correlation between solar flux and in-situ satellite measurements show poor correlations in the (magnetic) equatorial region, which are not found from the ground measurements of vertically-integrated electron content. We suggest that the most plausible cause for the poor correlation is the vertical movement of ionization due to atmospheric dynamic processes that is not controlled by the solar extreme ultraviolet radiation.

Global Characteristics↗

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

interference↗

Global Free Tropospheric NO2 Abundances Derived Using a Cloud Slicing Technique Applied to Satellite Observations from the Aura Ozone Monitoring Instrument (OMI)

We derive free-tropospheric NO2 volume mixing ratios (VMRs) and stratospheric column amounts of NO2 by applying a cloud slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top-of-the-atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. Estimates of stratospheric column NO2 are obtained by extrapolating the linear fits to the tropopause. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud slicing data indicates signatures of uplifted and transported anthropogenic NO2 in the middle troposphere as well as lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the Global Modeling Initiative (GMI) for cloudy conditions (cloud optical thicknesses > 10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx. Stratospheric column NO2 obtained from cloud slicing agrees well with other independently-generated estimates, providing further confidence in the free-tropospheric results.

NO2↗

Radiative Forcing in the ACCMIP Historical and Future Climate Simulations

A primary goal of the Atmospheric Chemistry and Climate Model IntercomparisonProject (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100climate change in the current generation of climate models. Here we evaluate historicaland 5 future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of whichalso participated in the Coupled Model Intercomparison Project phase 5 (CMIP5).The models generally reproduce present-day climatological total aerosol opticaldepth (AOD) relatively well. components to this total, however, and most appear to underestimate AOD over East10 Asia. The models generally capture 1980-2000 AOD trends fairly well, though theyunderpredict AOD increases over the YellowEastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, SouthAmerica and Southern Hemisphere Africa.We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing AF, including direct andindirect effects). The models calculated all aerosol all-sky 1850 to 2000 global meanannual average RF ranges from 0.06 to 0.49 W m(sup -2), with a mean of 0.26 W m(sup -2) and a median of 0.27 W m(sup -2. Adjusting for missing aerosol components in some modelsbrings the range to 0.12 to 0.62W m(sup -2), with a mean of 0.39W m(sup -2). Screen20ing the models based on their ability to capture spatial patterns and magnitudes ofAOD and AOD trends yields a quality-controlled mean of 0.42W m(sup -2) and range of0.33 to 0.50 W m(sup -2) (accounting for missing components). The CMIP5 subset of ACCMIPmodels spans 0.06 to 0.49W m(sup -2), suggesting some CMIP5 simulations likelyhave too little aerosol RF. A substantial, but not well quantified, contribution to histori25cal aerosol RF may come from climate feedbacks (35 to 58). The mean aerosol AF during this period is 1.12W m(sup -2) (median value 1.16W m(sup -2), range 0.72 to1.44W m(sup -2), indicating that adjustments to aerosols, which include cloud, water vaporand temperature, lead to stronger forcing than the aerosol direct RF.

Climate Models↗

Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (εn) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of εn suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.

Kazakhstan↗

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗

Chandra Contaminant Migration Model

High volatility cleans OBFs and low volatility produces a high build-up at OBF centers; only a narrow (factor of 2 or less) volatility range produces the observed spatial pattern. Simulations predict less accumulation above outer S-array CCDs; this may explain, in part, gratings/imaging C/MnL discrepancies. Simulations produce a change in center accumulation due solely to DH heater ON/OFF temperature change; but a 2nd contaminant and perhaps a change in source rate is also required. Emissivity E may depend on thickness; another model parameter. Additional physics, e.g., surface migration, is not warranted at this time. At t approx. 14 yrs, model produced 0.22 grams of contaminant, 0.085 grams remaining within ACIS cavity; 7 percent (6mg) on OBFs.

Swartz, Douglas A.↗