Mid-Western US heavy summer-precipitation in regional and global climate models: the impact on model skill and consensus through an analogue lens

NASA Astrophysics Data System (ADS)

Gao, Xiang; Schlosser, C. Adam

2018-04-01

Regional climate models (RCMs) can simulate heavy precipitation more accurately than general circulation models (GCMs) through more realistic representation of topography and mesoscale processes. Analogue methods of downscaling, which identify the large-scale atmospheric conditions associated with heavy precipitation, can also produce more accurate and precise heavy precipitation frequency in GCMs than the simulated precipitation. In this study, we examine the performances of the analogue method versus direct simulation, when applied to RCM and GCM simulations, in detecting present-day and future changes in summer (JJA) heavy precipitation over the Midwestern United States. We find analogue methods are comparable to MERRA-2 and its bias-corrected precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events, all significantly improving upon MERRA precipitation. For the late twentieth-century heavy precipitation frequency, RCM precipitation improves upon the corresponding driving GCM with greater accuracy yet comparable inter-model discrepancies, while both RCM- and GCM-based analogue results outperform their model-simulated precipitation counterparts in terms of accuracy and model consensus. For the projected trends in heavy precipitation frequency through the mid twenty-first century, analogue method also manifests its superiority to direct simulation with reduced intermodel disparities, while the RCM-based analogue and simulated precipitation do not demonstrate a salient improvement (in model consensus) over the GCM-based assessment. However, a number of caveats preclude any overall judgement, and further work—over any region of interest—should include a larger sample of GCMs and RCMs as well as ensemble simulations to comprehensively account for internal variability.

A Variable Resolution Stretched Grid General Circulation Model: Regional Climate Simulation

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.; Suarez, Max J.

2000-01-01

The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.

Importance of Winds and Soil Moistures to the US Summertime Drought of 1988: A GCM Simulation Study

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.; Lau, William K. M. (Technical Monitor)

2001-01-01

The climate version of NASA's GEOS 2 GCM did not simulate a realistic 1988 summertime drought in the central United States (Mocko et al., 1999). Despite several new upgrades to the model's parameterizations, as well as finer grid spacing from 4x5 degrees to 2x2.5 degrees, no significant improvements were noted in the model's simulation of the U.S. drought.

Climate model biases and statistical downscaling for application in hydrologic model

USDA-ARS?s Scientific Manuscript database

Climate change impact studies use global climate model (GCM) simulations to define future temperature and precipitation. The best available bias-corrected GCM output was obtained from Coupled Model Intercomparison Project phase 5 (CMIP5). CMIP5 data (temperature and precipitation) are available in d...

Global environmental effects of impact-generated aerosols: Results from a general circulation model, revision 1

NASA Technical Reports Server (NTRS)

Covey, Curt; Ghan, Steven J.; Walton, John J.; Weissman, Paul R.

1989-01-01

Interception of sunlight by the high altitude worldwide dust cloud generated by impact of a large asteroid or comet would lead to substantial land surface cooling, according to our three-dimensional atmospheric general circulation model (GCM). This result is qualitatively similar to conclusions drawn from an earlier study that employed a one-dimensional atmospheric model, but in the GCM simulation the heat capacity of the oceans substantially mitigates land surface cooling, an effect that one-dimensional models cannot quantify. On the other hand, the low heat capacity of the GCM's land surface allows temperatures to drop more rapidly in the initial stage of cooling than in the one-dimensional model study. These two differences between three-dimensional and one-dimensional model simulations were noted previously in studies of nuclear winter; GCM-simulated climatic changes in the Alvarez-inspired scenario of asteroid/comet winter, however, are more severe than in nuclear winter because the assumed aerosol amount is large enough to intercept all sunlight falling on earth. Impacts of smaller objects could also lead to dramatic, though less severe, climatic changes, according to our GCM. Our conclusion is that it is difficult to imagine an asteroid or comet impact leading to anything approaching complete global freezing, but quite reasonable to assume that impacts at the Alvarez level, or even smaller, dramatically alter the climate in at least a patchy sense.

The earth's radiation budget and its relation to atmospheric hydrology. III - Comparison of observations over the oceans with a GCM

NASA Technical Reports Server (NTRS)

Stephens, Graeme L.; Randall, David A.; Wittmeyer, Ian L.; Dazlich, Donald A.; Tjemkes, Stephen

1993-01-01

The ability of the Colorado State University general circulation model (GCM) to simulate interactions between the hydrological cycle and the radiative processes on earth was examined by comparing various sensitivity relationships established by the model with those observed on earth, and the observed and calculated seasonal cycles of the greenhouse effect and cloud radiative forcing. Results showed that, although the GCM model used was able to simulate well some aspects of the observed sensitivities, there were many serious quantitative differences, including problems in the simulation of the column vapor in the tropics and an excessively strong clear-sky greenhouse effect in the mid-latitudes. These differences led to an underestimation by the model of the sensitivity of the clear-sky greenhouse to changes in sea surface temperature.

Comparison of ocean surface solar irradiance in the GLA General Circulation Model and satellite-based calculations

NASA Technical Reports Server (NTRS)

Chertock, Beth; Sud, Y. C.

1993-01-01

A global, 7-year satellite-based record of ocean surface solar irradiance (SSI) is used to assess the realism of ocean SSI simulated by the nine-layer Goddard Laboratory for Atmospheres (GLA) General Circulation Model (GCM). January and July climatologies of net SSI produced by the model are compared with corresponding satellite climatologies for the world oceans between 54 deg N and 54 deg S. This comparison of climatologies indicates areas of strengths and weaknesses in the GCM treatment of cloud-radiation interactions, the major source of model uncertainty. Realism of ocean SSI is also important for applications such as incorporating the GLA GCM into a coupled ocean-atmosphere GCM. The results show that the GLA GCM simulates too much SSI in the extratropics and too little in the tropics, especially in the summer hemisphere. These discrepancies reach magnitudes of 60 W/sq m and more. The discrepancies are particularly large in the July case off the western coast of North America. Positive and negative discrepancies in SSI are shown to be consistent with discrepancies in planetary albedo.

Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2010-12-01

EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.

Using In Situ Observations and Satellite Retrievals to Constrain Large-Eddy Simulations and Single-Column Simulations: Implications for Boundary-Layer Cloud Parameterization in the NASA GISS GCM

NASA Astrophysics Data System (ADS)

Remillard, J.

2015-12-01

Two low-cloud periods from the CAP-MBL deployment of the ARM Mobile Facility at the Azores are selected through a cluster analysis of ISCCP cloud property matrices, so as to represent two low-cloud weather states that the GISS GCM severely underpredicts not only in that region but also globally. The two cases represent (1) shallow cumulus clouds occurring in a cold-air outbreak behind a cold front, and (2) stratocumulus clouds occurring when the region was dominated by a high-pressure system. Observations and MERRA reanalysis are used to derive specifications used for large-eddy simulations (LES) and single-column model (SCM) simulations. The LES captures the major differences in horizontal structure between the two low-cloud fields, but there are unconstrained uncertainties in cloud microphysics and challenges in reproducing W-band Doppler radar moments. The SCM run on the vertical grid used for CMIP-5 runs of the GCM does a poor job of representing the shallow cumulus case and is unable to maintain an overcast deck in the stratocumulus case, providing some clues regarding problems with low-cloud representation in the GCM. SCM sensitivity tests with a finer vertical grid in the boundary layer show substantial improvement in the representation of cloud amount for both cases. GCM simulations with CMIP-5 versus finer vertical gridding in the boundary layer are compared with observations. The adoption of a two-moment cloud microphysics scheme in the GCM is also tested in this framework. The methodology followed in this study, with the process-based examination of different time and space scales in both models and observations, represents a prototype for GCM cloud parameterization improvements.

Evaluation of CMIP5 and CORDEX Derived Wind Wave Climate in Arabian Sea and Bay of Bengal

NASA Astrophysics Data System (ADS)

Chowdhury, P.; Behera, M. R.

2017-12-01

Climate change impact on surface ocean wave parameters need robust assessment for effective coastal zone management. Climate model skill to simulate dynamical General Circulation Models (GCMs) and Regional Circulation Models (RCMs) forced wind-wave climate over northern Indian Ocean is assessed in the present work. The historical dynamical wave climate is simulated using surface winds derived from four GCMs and four RCMs, participating in the Coupled Model Inter-comparison Project (CMIP5) and Coordinated Regional Climate Downscaling Experiment (CORDEX-South Asia), respectively, and their ensemble are used to force a spectral wave model. The surface winds derived from GCMs and RCMs are corrected for bias, using Quantile Mapping method, before being forced to the spectral wave model. The climatological properties of wave parameters (significant wave height (Hs), mean wave period (Tp) and direction (θm)) are evaluated relative to ERA-Interim historical wave reanalysis datasets over Arabian Sea (AS) and Bay of Bengal (BoB) regions of the northern Indian Ocean for a period of 27 years. We identify that the nearshore wave climate of AS is better predicted than the BoB by both GCMs and RCMs. Ensemble GCM simulated Hs in AS has a better correlation with ERA-Interim ( 90%) than in BoB ( 80%), whereas ensemble RCM simulated Hs has a low correlation in both regions ( 50% in AS and 45% in BoB). In AS, ensemble GCM simulated Tp has better predictability ( 80%) compared to ensemble RCM ( 65%). However, neither GCM nor RCM could satisfactorily predict Tp in nearshore BoB. Wave direction is poorly simulated by GCMs and RCMs in both AS and BoB, with correlation around 50% with GCMs and 60% with RCMs wind derived simulations. However, upon comparing individual RCMs with their parent GCMs, it is found that few of the RCMs predict wave properties better than their parent GCMs. It may be concluded that there is no consistent added value by RCMs over GCMs forced wind-wave climate over northern Indian Ocean. We also identify that there is little to no significance of choosing a finer resolution GCM ( 1.4°) over a coarse GCM ( 2.8°) in improving skill of GCM forced dynamical wave simulations.

Coupling of a Simple 3-Layer Snow Model to GISS GCM

NASA Astrophysics Data System (ADS)

Aleinov, I.

2001-12-01

Appropriate simulation of the snow cover dynamics is an important issue for the General Circulation Models (GCMs). The presence of snow has a significant impact on ground albedo and on heat and moisture balance. A 3-layer snow model similar to the one proposed by Lynch-Stieglitz was developed with the purpose of using it inside the GCM developed in the NASA Goddard Institute for Space Studies (GISS). The water transport between the layers is modeled explicitly while the heat balance is computed implicitly between the snow layers and semi-implicitly on the surface. The processes of melting and refreezing and compactification of layers under the gravitational force are modeled appropriately. It was noticed that implicit computation of the heat transport can cause a significant under- or over-estimation of the incoming heat flux when the temperature of the upper snow layer is equal to 0 C. This may lead in particular to delayed snow melting in spring. To remedy this problem a special flux-control algorithm was added to the model, which checks computed flux for possible errors and if such are detected the heat transport is recomputed again with the appropriate corrections. The model was tested off-line with Sleepers River forcing data and exhibited a good agreement between simulated and observed quantities for snow depth, snow density and snow temperature. The model was then incorporated into the GISS GCM. Inside the GCM the model is driven completely by the data simulated by other parts of the GCM. The screening effect of the vegetation is introduced by means of masking depth. For a thin snowpack a fractional cover is implemented so that the total thickness of the the snow is never less then 10 cm (rather, the areal fraction of the snow cover decreases when it melts). The model was tested with 6 year long GCM speed-up runs. It proved to be stable and produced reasonable results for the global snow cover. In comparison to the old GISS GCM snow model (which was incorporating the snow into the first soil layer) the new snow model has better insulating properties, thus preventing the ground from overcooling in winter. It also provides better simulation for water retention and release by the snow which results in more physical ground water runoff.

A Ground-Based Doppler Radar and Micropulse Lidar Forward Simulator for GCM Evaluation of Arctic Mixed-Phase Clouds: Moving Forward Towards an Apples-to-apples Comparison of Hydrometeor Phase

NASA Astrophysics Data System (ADS)

Lamer, K.; Fridlind, A. M.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2017-12-01

An important aspect of evaluating Artic cloud representation in a general circulation model (GCM) consists of using observational benchmarks which are as equivalent as possible to model output in order to avoid methodological bias and focus on correctly diagnosing model dynamical and microphysical misrepresentations. However, current cloud observing systems are known to suffer from biases such as limited sensitivity, and stronger response to large or small hydrometeors. Fortunately, while these observational biases cannot be corrected, they are often well understood and can be reproduced in forward simulations. Here a ground-based millimeter wavelength Doppler radar and micropulse lidar forward simulator able to interface with output from the Goddard Institute for Space Studies (GISS) ModelE GCM is presented. ModelE stratiform hydrometeor fraction, mixing ratio, mass-weighted fall speed and effective radius are forward simulated to vertically-resolved profiles of radar reflectivity, Doppler velocity and spectrum width as well as lidar backscatter and depolarization ratio. These forward simulated fields are then compared to Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) ground-based observations to assess cloud vertical structure (CVS). Model evalution of Arctic mixed-phase cloud would also benefit from hydrometeor phase evaluation. While phase retrieval from synergetic observations often generates large uncertainties, the same retrieval algorithm can be applied to observed and forward-simulated radar-lidar fields, thereby producing retrieved hydrometeor properties with potentially the same uncertainties. Comparing hydrometeor properties retrieved in exactly the same way aims to produce the best apples-to-apples comparisons between GCM ouputs and observations. The use of a comprenhensive ground-based forward simulator coupled with a hydrometeor classification retrieval algorithm provides a new perspective for GCM evaluation of Arctic mixed-phase clouds from the ground where low-level supercooled liquid layer are more easily observed and where additional environmental properties such as cloud condensation nuclei are quantified. This should help assist in choosing between several possible diagnostic ice nucleation schemes for ModelE stratiform cloud.

Global environmental effects of impact-generated aerosols: Results from a general circulation model

NASA Technical Reports Server (NTRS)

Covey, Curt; Ghan, Steven J.; Walton, John J.; Weissman, Paul R.

1989-01-01

Interception of sunlight by the high altitude worldwide dust cloud generated by impact of a large asteroid or comet would lead to substantial land surface cooling, according to the three-dimensional atmospheric general circulation model (GCM). This result is qualitatively similar to conclusions drawn from an earlier study that employed a one-dimensional atmospheric model, but in the GCM simulation the heat capacity of the oceans, not included in the one-dimensional model, substantially mitigates land surface cooling. On the other hand, the low heat capacity of the GCM's land surface allows temperatures to drop more rapidly in the initial stages of cooling than in the one-dimensional model study. GCM-simulated climatic changes in the scenario of asteroid/comet winter are more severe than in nuclear winter because the assumed aerosol amount is large enough to intercept all sunlight falling on earth. Impacts of smaller objects could also lead to dramatic, though of course less severe, climatic changes, according to the GCM. An asteroid or comet impact would not lead to anything approaching complete global freezing, but quite reasonable to assume that impacts would dramatically alter the climate in at least a patchy sense.

Potential Predictability of U.S. Summer Climate with "Perfect" Soil Moisture

NASA Technical Reports Server (NTRS)

Yang, Fanglin; Kumar, Arun; Lau, K.-M.

2004-01-01

The potential predictability of surface-air temperature and precipitation over the United States continent was assessed for a GCM forced by observed sea surface temperatures and an estimate of observed ground soil moisture contents. The latter was obtained by substituting the GCM simulated precipitation, which is used to drive the GCM's land-surface component, with observed pentad-mean precipitation at each time step of the model's integration. With this substitution, the simulated soil moisture correlates well with an independent estimate of observed soil moisture in all seasons over the entire US continent. Significant enhancements on the predictability of surface-air temperature and precipitation were found in boreal late spring and summer over the US continent. Anomalous pattern correlations of precipitation and surface-air temperature over the US continent in the June-July-August season averaged for the 1979-2000 period increased from 0.01 and 0.06 for the GCM simulations without precipitation substitution to 0.23 and 0.3 1, respectively, for the simulations with precipitation substitution. Results provide an estimate for the limits of potential predictability if soil moisture variability is to be perfectly predicted. However, this estimate may be model dependent, and needs to be substantiated by other modeling groups.

Upper Atmospheric Response to the April 2010 Storm as Observed by GOCE, CHAMP, and GRACE and Modeled by TIME-GCM

NASA Astrophysics Data System (ADS)

Hagan, Maura; Häusler, Kathrin; Lu, Gang; Forbes, Jeffrey; Zhang, Xiaoli; Doornbos, Eelco; Bruinsma, Sean

2014-05-01

We present the results of an investigation of the upper atmosphere during April 2010 when it was disturbed by a fast-moving coronal mass ejection. Our study is based on comparative analysis of observations made by the Gravity field and steady-state Ocean Circulation Explorer (GOCE), Challenging Minisatellite Payload (CHAMP), and Gravity Recovery And Climate Experiment (GRACE) satellites and a set of simulations with the National Center for Atmospheric Research (NCAR) thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM). We compare and contrast the satellite observations with TIME-GCM results from a realistic simulation based on prevailing meteorological and solar geomagnetic conditions. We diagnose the comparative importance of the upper atmospheric signatures attributable to meteorological forcing with those attributable to storm effects by diagnosing a series of complementary control TIME-GCM simulations. These results also quantify the extent to which lower and middle atmospheric sources of upper atmospheric variability precondition its response to the solar geomagnetic storm.

Jets, eddies & waves in Saturn's troposphere and stratosphere from multi-annual high-resolution Global Climate Modeling

NASA Astrophysics Data System (ADS)

Spiga, Aymeric; Guerlet, Sandrine; Meurdesoif, Yann; Indurain, Mikel; Millour, Ehouarn; Sylvestre, Melody; Dubos, Thomas; Fouchet, Thierry

2016-10-01

A mission as richly instrumented as Cassini has brought a new impulse to the studies of Saturn's atmospheric fluid dynamics, to be further extended to Jupiter by the Juno mission.We recently built an innovative Global Climate Model (GCM) for giant planets by coupling our complete seasonal radiative model [Guerlet Icarus 2014] with a new hydrodynamical solver using an original icosahedral mapping of the planetary sphere to ensure excellent conservation and scalability properties in massively parallel computing resources [Dubos GMD 2015].Here we describe the insights gained from GCM simulations for Saturn with both unprecedented horizontal resolutions (reference at 1/2° latitude/longitude, and tests at 1/4° and 1/8°), integrated time (up to ten simulated Saturn years), and large vertical extent (from the troposphere to the stratosphere).Starting from a windless initial state, our 10-year-long GCM simulation for Saturn reproduce alterned tropospheric mid-latitude jets bearing similarities with the observed jet system (numbering, intensity, width). We demonstrate that those jets are eddy-driven with a conversion rate from eddies to mean flow in agreement with Cassini estimates. Before reaching equilibrium, mid-latitude jets experience poleward migration, which can be ascribed to a self-destabilization of the jets by barotropic and baroclinic instabilities.Our Saturn GCM also predicts in the equator the presence of eastward-propagating Rossby-gravity (Yanai) and westward-propagating Rossby waves, reminiscent of similar waves in the terrestrial tropics. Furthermore, our GCM simulations exhibit a stratospheric meridional circulation from one tropic to the other, with a seasonal reversal, which allows us to investigate the possible dynamical control on the observed variations of hydrocarbon species.In contrast to observations, in our GCM simulations the equatorial jet is only weakly super-rotating and the polar jet is strongly destabilized by meandering. Moreover, in spite of predicting stacked stratospheric eastward and westward jets, our GCM does not reproduce the observed propagation of the equatorial oscillation by Cassini. We will discuss how to address those remaining challenges in future simulations.

Evaluation on Asian Dust Aerosol and Simulated Processes in CanAM4.2 Using Satellite Measurements and Station Data

NASA Astrophysics Data System (ADS)

Yiran, P.; Li, J.; von Salzen, K.; Dai, T.; Liu, D.

2014-12-01

Mineral dust is a significant contributor to global and Asian aerosol burden. Currently, large uncertainties still exist in simulated aerosol processes in global climate models (GCMs), which lead to a diversity in dust mass loading and spatial distribution of GCM projections. In this study, satellite measurements from CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and observed aerosol data from Asian stations are compared with modelled aerosol in the Canadian Atmospheric Global Climate Model (CanAM4.2). Both seasonal and annual variations in Asian dust distribution are investigated. Vertical profile of simulated aerosol in troposphere is evaluated with CALIOP Level 3 products and local observed extinction for dust and total aerosols. Physical processes in GCM such as horizontal advection, vertical mixing, dry and wet removals are analyzed according to model simulation and available measurements of aerosol. This work aims to improve current understanding of Asian dust transport and vertical exchange on a large scale, which may help to increase the accuracy of GCM simulation on aerosols.

Downscaling of Global Climate Change Estimates to Regional Scales: An Application to Iberian Rainfall in Wintertime.

NASA Astrophysics Data System (ADS)

von Storch, Hans; Zorita, Eduardo; Cubasch, Ulrich

1993-06-01

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique.The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It is shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM).The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous `2 C02' doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of 1 mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the Iberian Peninsula, the change is 10 mm/month, with a minimum of 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ("business as usual") increase Of C02, the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different.

Tropical storm interannual and interdecadal variability in an ensemble of GCM integrations

NASA Astrophysics Data System (ADS)

Vitart, Frederic Pol.

1999-11-01

A T42L18 Atmospheric General Circulation Model forced by observed SSTs has been integrated for 10 years with 9 different initial conditions. An objective procedure for tracking model-generated tropical storms has been applied to this ensemble. Statistical tools have been applied to the ensemble frequency, intensity and location of tropical storms, leading to the conclusion that the potential predictability is particularly strong over the western North Pacific, the eastern North Pacific and the western North Atlantic. An EOF analysis of local SSts and a combined EOF analysis of vertical wind shear, 200 mb and 850 mb vorticity indicate that the simulated tropical storm interannual variability is mostly constrained by the large scale circulation as in observations. The model simulates a realistic interannual variability of tropical storms over the western North Atlantic, eastern North Pacific, western North Pacific and Australian basin where the model simulates a realistic large scale circulation. Several experiments with the atmospheric GCM forced by imposed SSTs demonstrate that the GCM simulates a realistic impact of ENSO on the simulated Atlantic tropical storms. In addition the GCM simulates fewer tropical storms over the western North Atlantic with SSTs of the 1950s than with SSTs of the 1970s in agreement with observations. Tropical storms simulated with RAS and with MCA have been compared to evaluate their sensitivity to a change in cumulus parameterization. Composites of tropical storm structure indicate stronger tropical storms with higher warm cores with MCA. An experiment using the GFDL hurricane model and several theoretical calculations indicate that the mean state may be responsible for the difference in intensity and in the height of the warm core. With the RAS scheme, increasing the threshold which determines when convection can occur increases the tropical storm frequency almost linearly. The increase of tropical storm frequency seems to be linked to an increase of CAPE. Tropical storms predicted by a coupled model produce a strong cooling of SSTs and their intensity is lower than in the simulations. An ensemble of coupled GCM integrations displays some skill in forecasting the tropical storm frequency when starting on July 1st.

Global environmental effects of impact-generated aerosols: Results from a general circulation model

NASA Technical Reports Server (NTRS)

Covey, C.; Ghan, S. J.; Weissman, Paul R.

1988-01-01

Cooling and darkening at Earth's surface are expected to result from the interception of sunlight by the high altitude worldwide dust cloud generated by impact of a large asteroid or comet, according to the one-dimensional radioactive-convective atmospheric model (RCM) of Pollack et al. An analogous three-dimensional general circulation model (GCM) simulation obtains the same basic result as the RCM but there are important differences in detail. In the GCM simulation the heat capacity of the oceans, not included in the RCM, substantially mitigates land surface cooling. On the other hand, the GCM's low heat capacity surface allows surface temperatures to drop much more rapidly than reported by Pollack et al. These two differences between RCM and GCM simulations were noted previously in studies of nuclear winter; GCM results for comet/asteroid winter, however, are much more severe than for nuclear winter because the assumed aerosol amount is large enough to intercept all sunlight falling on Earth. In the simulation the global average of land surface temperature drops to the freezing point in just 4.5 days, one-tenth the time required in the Pollack et al. simulation. In addition to the standard case of Pollack et al., which represents the collision of a 10-km diameter asteroid with Earth, additional scenarios are considered ranging from the statistically more frequent impacts of smaller asteroids to the collision of Halley's comet with Earth. In the latter case the kinetic energy of impact is extremely large due to the head-on collision resulting from Halley's retrograde orbit.

Hydrological changes in the Amur river basin: two approaches for assignment of climate projections into hydrological model

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Kalugin, Andrei; Motovilov, Yury

2017-04-01

A regional hydrological model was setup to assess possible impact of climate change on the hydrological regime of the Amur drainage basin (the catchment area is 1 855 000 km2). The model is based on the ECOMAG hydrological modeling platform and describes spatially distributed processes of water cycle in this great basin with account for flow regulation by the Russian and Chinese reservoirs. Earlier, the regional hydrological model was intensively evaluated against 20-year streamflow data over the whole Amur basin and, being driven by 252-station meteorological observations as input data, demonstrated good performance. In this study, we firstly assessed the reliability of the model to reproduce the historical streamflow series when Global Climate Model (GCM) simulation data are used as input into the hydrological model. Data of nine GCMs involved in CMIP5 project was utilized and we found that ensemble mean of annual flow is close to the observed flow (error is about 14%) while data of separate GCMs may result in much larger errors. Reproduction of seasonal flow for the historical period turned out weaker; first of all because of large errors in simulated seasonal precipitation, so hydrological consequences of climate change were estimated just in terms of annual flow. We analyzed the hydrological projections from the climate change scenarios. The impacts were assessed in four 20-year periods: early- (2020-2039), mid- (2040-2059) and two end-century (2060-2079; 2080-2099) periods using an ensemble of nine GCMs and four Representative Concentration Pathways (RCP) scenarios. Mean annual runoff anomalies calculated as percentages of the future runoff (simulated under 36 GCM-RCP combinations of climate scenarios) to the historical runoff (simulated under the corresponding GCM outputs for the reference 1986-2005 period) were estimated. Hydrological model gave small negative runoff anomalies for almost all GCM-RCP combinations of climate scenarios and for all 20-year periods. The largest ensemble mean anomaly was about minus 8% by the end of XXI century under the most severe RCP8.5 scenario. We compared the mean annual runoff anomalies projected under the GCM-based data for the XXI century with the corresponding anomalies projected under a modified observed climatology using the delta-change (DC) method. Use of the modified observed records as driving forces for hydrological model-based projections can be considered as an alternative to the GCM-based scenarios if the latter are uncertain. The main advantage of the DC approach is its simplicity: in its simplest version only differences between present and future climates (i.e. between the long-term means of the climatic variables) are considered as DC-factors. In this study, the DC-factors for the reference meteorological series (1986-2005) of climate parameters were calculated from the GCM-based scenarios. The modified historical data were used as input into the hydrological models. For each of four 20-year period, runoff anomalies simulated under the delta-changed historical time series were compared with runoff anomalies simulated under the corresponding GCM-data with the same mean. We found that the compared projections are closely correlated. Thus, for the Amur basin, the modified observed climatology can be used as driving force for hydrological model-based projections and considered as an alternative to the GCM-based scenarios if only annual flow projections are of the interest.

On Simulating the Mid-western-us Drought of 1988 with a GCM

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Mocko, D. M.; Lau, William K.-M.; Atlas, R.

2002-01-01

The primary cause of the midwestern North American drought in the summer of 1988 has been identified to be the La Nina SST anomalies. Yet with the SST anomalies prescribed, this drought has not been simulated satisfactorily by any general circulation model. Seven simulation-experiments, each containing an ensemble of 4-sets of simulations, were conducted with the GEOS GCM for both 1987 and 1988. All simulations started from January 1 and continued through the end of August. In the first baseline case, Case 1, only the SST anomalies and some vegetation parameters were prescribed, while everything else (such as soil moisture, snow-cover, and clouds) was interactive. The GCM did produce some of the circulation features of a drought over North America, but they could only be identified on the planetary scales. The 1988 minus 1987 precipitation differences show that the GCM was successful in simulating reduced precipitation in the mid-west, but the accompanying circulation anomalies were not well simulated, leading one to infer that the GCM has simulated the drought for the wrong reason. To isolate the causes for this unremarkable circulation, analyzed winds and soil moisture were prescribed in Case 2 and Case 3 as continuous updates by direct replacement of the GCM-predicted fields. These cases show that a large number of simulation biases emanate from wind biases that are carried into the North American region from surroundings regions. Inclusion of soil moisture also helps to ameliorate the strong feedback, perhaps even stronger than that of the real atmosphere, between soil moisture and precipitation. Case 2 simulated one type of surface temperature anomaly pattern, whereas Case 3 with the prescribed soil moisture produced another.

Assessment of NASA GISS CMIP5 ModelE simulated clouds and TOA radiation budgets using satellite observations over the southern mid-latitudes

NASA Astrophysics Data System (ADS)

Stanfield, Ryan Evan

Past, current, and future climates have been simulated by the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) ModelE Global Circulation Model (GCM) and summarized by the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC, AR4). New simulations from the updated CMIP5 version of the NASA GISS ModelE GCM were recently released to the public community during the summer of 2011 and will be included in the upcoming IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, they have not yet been extensively validated against observations. To assess the NASA GISS-E2-R GCM, model simulated clouds and cloud properties are compared to observational cloud properties derived from the Clouds and Earth's Radiant Energy System (CERES) project using MODerate Resolution Imaging Spectroradiometer (MODIS) data for the period of March 2000 through December 2005. Over the 6-year period, the global average modeled cloud fractions are within 1% of observations. However, further study however shows large regional biases between the GCM simulations and CERES-MODIS observations. The southern mid-latitudes (SML) were chosen as a focus region due to model errors across multiple GCMs within the recent phase 5 of the Coupled Model Intercomparison Project (CMIP5). Over the SML, the GISS GCM undersimulates total cloud fraction over 20%, but oversimulates total water path by 2 g m-2. Simulated vertical cloud distributions over the SML when compared to both CERES-MODIS and CloudSat/CALIPSO observations show a drastic undersimulation of low level clouds by the GISS GCM, but higher fractions of thicker clouds. To assess the impact of GISS simulated clouds on the TOA radiation budgets, the modeled TOA radiation budgets are compared to CERES EBAF observations. Because modeled low-level cloud fraction is much lower than observed over the SML, modeled reflected shortwave (SW) flux at the TOA is 13 W m -2 lower and outgoing longwave radiation (OLR) is 3 W m-2 higher than observations. Finally, cloud radiative effects (CRE) are calculated and compared with observations to fully assess the impact of clouds on the TOA radiation budgets. The difference in clear-sky reflected SW flux between model and observation is only +4 W m-2 while the SW CRE difference is up to 17 W m-2, indicating that most of the bias in SW CRE results from the all-sky bias between the model and observation. A sizeable negative bias of 10 W m-2 in simulated clear-sky OLR has been found due to a dry bias in calculating observed clear-sky OLR and lack of upper-level water vapor at the 100-mb level in the model. The dry bias impacts CRE LW, with the model undersimulating by 13 W m-2. The CRE NET difference is only 5 W m-2 due to the cancellation of SW and LW CRE biases.

A 12-year (1987-1998) Ensemble Simulation of the US Climate with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.

2002-01-01

The variable-resolution stretched-grid (SG) GEOS (Goddard Earth Observing System) GCM has been used for limited ensemble integrations with a relatively coarse, 60 to 100 km, regional resolution over the U.S. The experiments have been run for the 12-year period, 1987-1998, that includes the recent ENSO cycles. Initial conditions 1-2 days apart are used for ensemble members. The goal of the experiments is analyzing the long-term SG-GCM ensemble integrations in terms of their potential in reducing the uncertainties of regional climate simulation while producing realistic mesoscales. The ensemble integration results are analyzed for both prognostic and diagnostic fields. A special attention is devoted to analyzing the variability of precipitation over the U.S. The internal variability of the SG-GCM has been assessed. The ensemble means appear to be closer to the verifying analyses than the individual ensemble members. The ensemble means capture realistic mesoscale patterns, especially those of induced by orography. Two ENSO cycles have been analyzed in terms their impact on the U.S. climate, especially on precipitation. The ability of the SG-GCM simulations to produce regional climate anomalies has been confirmed. However, the optimal size of the ensembles depending on fine regional resolution used, is still to be determined. The SG-GCM ensemble simulations are performed as a preparation or a preliminary stage for the international SGMIP (Stretched-Grid Model Intercomparison Project) that is under way with participation of the major centers and groups employing the SG-approach for regional climate modeling.

Climate Simulations based on a different-grid nested and coupled model

NASA Astrophysics Data System (ADS)

Li, Dan; Ji, Jinjun; Li, Yinpeng

2002-05-01

An atmosphere-vegetation interaction model (A VIM) has been coupled with a nine-layer General Cir-culation Model (GCM) of Institute of Atmospheic Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. A VIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having lon-gitude 7.5° and latitude 4.5°, the vegetation is given a high resolution of 1.5° by 1.5° to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15 years and its last ten-year mean of outputs was chosen for analysis. Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteris-tics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simu-lated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.

Simulation of dense amorphous polymers by generating representative atomistic models

NASA Astrophysics Data System (ADS)

Curcó, David; Alemán, Carlos

2003-08-01

A method for generating atomistic models of dense amorphous polymers is presented. The generated models can be used as starting structures of Monte Carlo and molecular dynamics simulations, but also are suitable for the direct evaluation physical properties. The method is organized in a two-step procedure. First, structures are generated using an algorithm that minimizes the torsional strain. After this, an iterative algorithm is applied to relax the nonbonding interactions. In order to check the performance of the method we examined structure-dependent properties for three polymeric systems: polyethyelene (ρ=0.85 g/cm3), poly(L,D-lactic) acid (ρ=1.25 g/cm3), and polyglycolic acid (ρ=1.50 g/cm3). The method successfully generated representative packings for such dense systems using minimum computational resources.

The Response of a Spectral General Circulation Model to Refinements in Radiative Processes.

NASA Astrophysics Data System (ADS)

Ramanathan, V.; Pitcher, Eric J.; Malone, Robert C.; Blackmon, Maurice L.

1983-03-01

We present here results and analyses of a series of numerical experiments performed with a spectral general circulation model (GCM). The purpose of the GCM experiments is to examine the role of radiation/cloud processes in the general circulation of the troposphere and stratosphere. The experiments were primarily motivated by the significant improvements in the GCM zonal mean simulation as refinements were made in the model treatment of clear-sky radiation and cloud-radiative interactions. The GCM with the improved cloud/radiation model is able to reproduce many observed features, such as: a clear separation between the wintertime tropospheric jet and the polar night jet; winter polar stratospheric temperatures of about 200 K; interhemispheric and seasonal asymmetries in the zonal winds.In a set of sensitivity experiments, we have stripped the cloud/radiation model of its improvements, the result being a significant degradation of the zonal mean simulations by the GCM. Through these experiments we have been able to identify the processes that are responsible for the improved GCM simulations: (i) careful treatment of the upper boundary condition for O3 solar heating; (ii) temperature dependence of longwave cooling by CO2 15 m bands., (iii) vertical distribution of H2O that minimizes the lower stratospheric H2O longwave cooling; (iv) dependence of cirrus emissivity on cloud liquid water content.Comparison of the GCM simulations, with and without the cloud/radiation improvements, reveals the nature and magnitude of the following radiative-dynamical interactions: (i) the temperature decrease (due to errors in radiative heating) within the winter polar stratosphere is much larger than can be accounted for by purely radiative adjustment; (ii) the role of dynamics in maintaining the winter polar stratosphere thermal structure is greatly diminished in the GCM with the degraded treatment of radiation; (iii) the radiative and radiative-dynamical response times of the atmosphere vary from periods of less than two weeks in the lower troposphere to roughly three months in the polar lower stratosphere; (iv) within the stratosphere, the radiative response times vary significantly with temperature, with the winter polar values larger than the summer polar values by as much as a factor of 2.5.Cirrus clouds, if their emissivities are arbitrarily prescribed to be black, unrealistically enhance the radiative cooling of the polar troposphere above 8 km. This results in a meridional temperature gradient much stronger than that which is observed. We employ a more realistic parameterization that accounts for the non-blackness of cirrus, and we describe the resulting improvements in the model simulation of zonal winds, temperatures, and radiation budget.

Simulations of the HDO and H2O-18 atmospheric cycles using the NASA GISS general circulation model - Sensitivity experiments for present-day conditions

NASA Technical Reports Server (NTRS)

Jouzel, Jean; Koster, R. D.; Suozzo, R. J.; Russell, G. L.; White, J. W. C.

1991-01-01

Incorporating the full geochemical cycles of stable water isotopes (HDO and H2O-18) into an atmospheric general circulation model (GCM) allows an improved understanding of global delta-D and delta-O-18 distributions and might even allow an analysis of the GCM's hydrological cycle. A detailed sensitivity analysis using the NASA/Goddard Institute for Space Studies (GISS) model II GCM is presented that examines the nature of isotope modeling. The tests indicate that delta-D and delta-O-18 values in nonpolar regions are not strongly sensitive to details in the model precipitation parameterizations. This result, while implying that isotope modeling has limited potential use in the calibration of GCM convection schemes, also suggests that certain necessarily arbitrary aspects of these schemes are adequate for many isotope studies. Deuterium excess, a second-order variable, does show some sensitivity to precipitation parameterization and thus may be more useful for GCM calibration.

A Comprehensive Analysis of Clouds, Radiation, and Precipitation in the North Pacific ITCZ in the NASA GISS ModelE GCM and Satellite Observations

NASA Astrophysics Data System (ADS)

Stanfield, Ryan Evan

Global circulation/climate models (GCMs) remain as an invaluable tool to predict future potential climate change. To best advise policy makers, assessing and increasing the accuracy of climate models is paramount. The treatment of clouds, radiation and precipitation in climate models and their associated feedbacks have long been one of the largest sources of uncertainty in predicting any potential future climate changes. Three versions of the NASA GISS ModelE GCM (the frozen CMIP5 version [C5], a post-CMIP5 version with modifications to cumulus and boundary layer turbulence parameterizations [P5], and the most recent version of the GCM which builds on the post-CMIP5 version with further modifications to convective cloud ice and cold pool parameterizations [E5]) have been compared with various satellite observations to analyze how recent modifications to the GCM has impacted cloud, radiation, and precipitation properties. In addition to global comparisons, two areas are showcased in regional analyses: the Eastern Pacific Northern ITCZ (EP-ITCZ), and Indonesia and the Western Pacific (INDO-WP). Changes to the cumulus and boundary layer turbulence parameterizations in the P5 version of the GCM have improved cloud and radiation estimations in areas of descending motion, such as the Southern Mid-Latitudes. Ice particle size and fall speed modifications in the E5 version of the GCM have decreased ice cloud water contents and cloud fractions globally while increasing precipitable water vapor in the model. Comparisons of IWC profiles show that the GCM simulated IWCs increase with height and peak in the upper portions of the atmosphere, while 2C-ICE observations peak in the lower levels of the atmosphere and decrease with height, effectively opposite of each other. Profiles of CF peak at lower heights in the E5 simulation, which will potentially increase outgoing longwave radiation due to higher cloud top temperatures, which will counterbalance the decrease in reflected shortwave associated with lower CFs and the thinner optical depths associated with decreased IWC and LWC in the E5 simulation. Vertical motion within the newest E5 simulation is greatly weakened over the EP-ITCZ region, potentially due to atmospheric loading from enhanced ice particle fall speeds. Comparatively, E5 simulated upward motion in the INDO-WP is stronger than its predecessors. Changes in the E5 simulation have resulted in stronger/weaker upward motion over the ocean/land in the INDO-WP region in comparison with both the C5 and P5 predecessors. Multimodel precipitation analysis shows that most of the GCMs tend to produce a wider ITCZ with stronger precipitation compared to GPCP and TRMM precipitation products. E5-simulated precipitation decreases and shifts Southward over the Easter Pacific ITCZ, which warrants further investigation into meridional heat transport and radiation fields.

The quasi 2 day wave response in TIME-GCM nudged with NOGAPS-ALPHA

NASA Astrophysics Data System (ADS)

Wang, Jack C.; Chang, Loren C.; Yue, Jia; Wang, Wenbin; Siskind, D. E.

2017-05-01

The quasi 2 day wave (QTDW) is a traveling planetary wave that can be enhanced rapidly to large amplitudes in the mesosphere and lower thermosphere (MLT) region during the northern winter postsolstice period. In this study, we present five case studies of QTDW events during January and February 2005, 2006 and 2008-2010 by using the Thermosphere-Ionosphere-Mesosphere Electrodynamics-General Circulation Model (TIME-GCM) nudged with the Navy Operational Global Atmospheric Prediction System-Advanced Level Physics High Altitude (NOGAPS-ALPHA) Weather Forecast Model. With NOGAPS-ALPHA introducing more realistic lower atmospheric forcing in TIME-GCM, the QTDW events have successfully been reproduced in the TIME-GCM. The nudged TIME-GCM simulations show good agreement in zonal mean state with the NOGAPS-ALPHA 6 h reanalysis data and the horizontal wind model below the mesopause; however, it has large discrepancies in the tropics above the mesopause. The zonal mean zonal wind in the mesosphere has sharp vertical gradients in the nudged TIME-GCM. The results suggest that the parameterized gravity wave forcing may need to be retuned in the assimilative TIME-GCM.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

Liquid slip over gas nanofilms

NASA Astrophysics Data System (ADS)

Ramisetti, Srinivasa B.; Borg, Matthew K.; Lockerby, Duncan A.; Reese, Jason M.

2017-08-01

We propose the rarefied-gas-cushion model (r-GCM), as an extended version of the gas-cushion model (GCM), to estimate the apparent slip of water flowing over a gas layer trapped at a solid surface. Nanobubbles or gas nanofilms may manifest rarefied-gas effects and the r-GCM incorporates kinetic boundary conditions for the gas component in the slip Knudsen regime. These enable an apparent hydrodynamic slip length to be calculated given the gas thickness, the Knudsen number, and the bulk fluid viscosities. We assess the r-GCM through nonequilibrium molecular dynamics (NEMD) simulations of shear-driven liquid flow over an infinite gas nanofilm covering a solid surface, from the gas slip regime to the early transition regime, beyond which NEMD is computationally impractical. We find that, over the flow regimes examined, the r-GCM provides better predictions of the apparent liquid slip and retrieves both the GCM and the free-molecular behavior in the appropriate limits.

A long-term simulation of forest carbon fluxes over the Qilian Mountains

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei; Fan, Wenwu

2016-10-01

In this work, we integrated a remote-sensing-based (the MODIS MOD_17 Gross Primary Productivity (GPP) model (MOD_17)) and a process-based (the Biome-BioGeochemical Cycles (Biome-BGC) model) ecological model in order to estimate long-term (from 2000 to 2012) forest carbon fluxes over the Qilian Mountains in northwest China, a cold and arid forest ecosystem. Our goal was to obtain an accurate and quantitative simulation of spatial GPP patterns using the MOD_17 model and a temporal description of forest processes using the Biome-BGC model. The original MOD_17 model was first optimized using a biome-specific parameter, observed meteorological data, and reproduced fPAR at the eddy covariance site. The optimized MOD_17 model performed much better (R2 = 0.91, RMSE = 5.19 gC/m2/8d) than the original model (R2 = 0.47, RMSE = 20.27 gC/m2/8d). The Biome-BGC model was then calibrated using GPP for 30 representative forest plots selected from the optimized MOD_17 model. The calibrated Biome-BGC model was then driven in order to estimate forest GPP, net primary productivity (NPP), and net ecosystem exchange (NEE). GPP and NEE were validated against two-year (2010 and 2011) EC measurements (R2 = 0.79, RMSE = 1.15 gC/m2/d for GPP; and R2 = 0.69, RMSE = 1.087 gC/m2/d for NEE). NPP estimates from 2000 to 2012 were then compared to dendrochronological measurements (R2 = 0.73, RMSE = 24.46 gC/m2/yr). Our results indicated that integration of the two models can be used for estimating carbon fluxes with good accuracy and a high temporal and spatial resolution. Overall, NPP displayed a downward trend, with an average rate of 0.39 gC/m2/yr, from 2000 and 2012 over the Qilian Mountains. Simulated average annual NPP yielded higher values for the southeast as compared to the northwest. The most positive correlative climatic factor to average annual NPP was downward shortwave radiation. The vapor pressure deficit, and mean temperature and precipitation yielded negative correlations to average annual NPP.

An approach for assessing the sensitivity of floods to regional climate change

NASA Astrophysics Data System (ADS)

Hughes, James P.; Lettenmaier, Dennis P.; Wood, Eric F.

1992-06-01

A high visibility afforded climate change issues is recent years has led to conflicts between and among decision makers and scientists. Decision makers inevitably feel pressure to assess the effect of climate change on the public welfare, while most climate modelers are, to a greater or lesser degree, concerned about the extent to which known inaccuracies in their models limit or preclude the use of modeling results for policy making. The water resources sector affords a good example of the limitations of the use of alternative climate scenarios derived from GCMs for decision making. GCM simulations of precipitation agree poorly between GCMs, and GCM predictions of runoff and evapotranspiration are even more uncertain. Further, water resources managers must be concerned about hydrologic extremes (floods and droughts) which are much more difficult to predict than ``average'' conditions. Most studies of the sensitivity of water resource systems and operating policies to climate change to data have been based on simple perturbations of historic hydroclimatological time series to reflect the difference between large area GCM simulations for an altered climate (e.g., CO2 doubling) and a GCM simulation of present climate. Such approaches are especially limited for assessment of the sensitivity of water resources systems under extreme conditions, conditions, since the distribution of storm inter-arrival times, for instance, is kept identical to that observed in the historic past. Further, such approaches have generally been based on the difference between the GCM altered and present climates for a single grid cell, primarily because the GCM spatial scale is often much larger than the scale at which climate interpretations are desired. The use of single grid cell GCM results is considered inadvisable by many GCM modelers, who feel the spatial scale for which interpretation of GCM results is most reasonable is on the order of several grid cells. In this paper, we demonstrate an alternative approach to assessing the implications of altered climates as predicted by GCMs for extreme (flooding) conditions. The approach is based on the characterization of regional atmospheric circulation patterns through a weather typing procedure, from which a stochastic model of the weather class occurrences is formulated. Weather types are identified through a CART (Classification and Regression Tree) approach. Precipitation occurence/non-occurence at multiple precipitation station is then predicted through a second stage stochastic model. Precipitation amounts are predicted conditional on the weather class identified from the large area circulation information.

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

Hurricane Forecasts with a Global Mesoscale-resolving Model on the NASA Columbia Supercomputer Preliminary Simulations of Hurricane Katrina (2005)

NASA Technical Reports Server (NTRS)

Shen, B.-W.; Atlas, R.; Reale, O.; Chern, J.-D.; Li, S.-J.; Lee, T.; Chang, J.; Henze, C.; Yeh, K.-S.

2006-01-01

It is known that the General Circulation Models (GCMs) have sufficient resolution to accurately simulate hurricane near-eye structure and intensity. To overcome this limitation, the mesoscale-resolving finite-element GCM (fvGCM) has been experimentally deployed on the NASA Columbia supercomputer, and its performance is evaluated choosing hurricane Katrina as an example in this study. On late August 2005 Katrina underwent two stages of rapid intensification and became the sixth most intense hurricane in the Atlantic. Six 5-day simulations of Katrina at both 0.25 deg and 0.125 deg show comparable track forecasts, but the 0,125 deg runs provide much better intensity forecasts, producing center pressure with errors of only +/- 12 hPa. The 0.125 deg simulates better near-eye wind distributions and a more realistic average intensification rate. A convection parameterization (CP) is one of the major limitations in a GCM, the 0.125 deg run with CP disabled produces very encouraging results.

Comparisons Between TIME-GCM/MERRA Simulations and LEO Satellite Observations

NASA Astrophysics Data System (ADS)

Hagan, M. E.; Haeusler, K.; Forbes, J. M.; Zhang, X.; Doornbos, E.; Bruinsma, S.; Lu, G.

2014-12-01

We report on yearlong National Center for Atmospheric Research (NCAR) thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM) simulations where we utilize the recently developed lower boundary condition based on 3-hourly MERRA (Modern-Era Retrospective Analysis for Research and Application) reanalysis data to account for tropospheric waves and tides propagating upward into the model domain. The solar and geomagnetic forcing is based on prevailing geophysical conditions. The simulations show a strong day-to-day variability in the upper thermospheric neutral temperature tidal fields, which is smoothed out quickly when averaging is applied over several days, e.g. up to 50% DE3 amplitude reduction for a 10-day average. This is an important result with respect to tidal diagnostics from satellite observations where averaging over multiple days is inevitable. In order to assess TIME-GCM performance we compare the simulations with measurements from the Gravity field and steady-state Ocean Circulation Explorer (GOCE), Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) satellites.

Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime

DOE Office of Scientific and Technical Information (OSTI.GOV)

von Storch, H.; Zorita, E.; Cubasch, U.

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique. The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It ismore » shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM). The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous [open quotes]2 CO[sub 2][close quotes] doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of I mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the lberian Peninsula, the change is - 10 mm/month, with a minimum of - 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ([open quotes]business as usual[close quotes]) increase of CO[sub 2], the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different. 17 refs., 10 figs.« less

A new dynamical downscaling approach with GCM bias corrections and spectral nudging

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Yang, Zong-Liang

2015-04-01

To improve confidence in regional projections of future climate, a new dynamical downscaling (NDD) approach with both general circulation model (GCM) bias corrections and spectral nudging is developed and assessed over North America. GCM biases are corrected by adjusting GCM climatological means and variances based on reanalysis data before the GCM output is used to drive a regional climate model (RCM). Spectral nudging is also applied to constrain RCM-based biases. Three sets of RCM experiments are integrated over a 31 year period. In the first set of experiments, the model configurations are identical except that the initial and lateral boundary conditions are derived from either the original GCM output, the bias-corrected GCM output, or the reanalysis data. The second set of experiments is the same as the first set except spectral nudging is applied. The third set of experiments includes two sensitivity runs with both GCM bias corrections and nudging where the nudging strength is progressively reduced. All RCM simulations are assessed against North American Regional Reanalysis. The results show that NDD significantly improves the downscaled mean climate and climate variability relative to other GCM-driven RCM downscaling approach in terms of climatological mean air temperature, geopotential height, wind vectors, and surface air temperature variability. In the NDD approach, spectral nudging introduces the effects of GCM bias corrections throughout the RCM domain rather than just limiting them to the initial and lateral boundary conditions, thereby minimizing climate drifts resulting from both the GCM and RCM biases.

Numerical simulation of the circulation of the atmosphere of Titan

NASA Technical Reports Server (NTRS)

Hourdin, F.; Levan, P.; Talagrand, O.; Courtin, Regis; Gautier, Daniel; Mckay, Christopher P.

1992-01-01

A three dimensional General Circulation Model (GCM) of Titan's atmosphere is described. Initial results obtained with an economical two dimensional (2D) axisymmetric version of the model presented a strong superrotation in the upper stratosphere. Because of this result, a more general numerical study of superrotation was started with a somewhat different version of the GCM. It appears that for a slowly rotating planet which strongly absorbs solar radiation, circulation is dominated by global equator to pole Hadley circulation and strong superrotation. The theoretical study of this superrotation is discussed. It is also shown that 2D simulations systemically lead to instabilities which make 2D models poorly adapted to numerical simulation of Titan's (or Venus) atmosphere.

GEOS-5 Chemistry Transport Model User's Guide

NASA Technical Reports Server (NTRS)

Kouatchou, J.; Molod, A.; Nielsen, J. E.; Auer, B.; Putman, W.; Clune, T.

2015-01-01

The Goddard Earth Observing System version 5 (GEOS-5) General Circulation Model (GCM) makes use of the Earth System Modeling Framework (ESMF) to enable model configurations with many functions. One of the options of the GEOS-5 GCM is the GEOS-5 Chemistry Transport Model (GEOS-5 CTM), which is an offline simulation of chemistry and constituent transport driven by a specified meteorology and other model output fields. This document describes the basic components of the GEOS-5 CTM, and is a user's guide on to how to obtain and run simulations on the NCCS Discover platform. In addition, we provide information on how to change the model configuration input files to meet users' needs.

A GCM simulation of the earth-atmosphere radiation balance for winter and summer

NASA Technical Reports Server (NTRS)

Wu, M. L. C.

1979-01-01

The radiation balance of the earth-atmosphere system simulated by using the general circulation model (GCM) of the Laboratory for Atmospheric Sciences (GLAS) is examined in regards to its graphical distribution, zonally-averaged distribution, and global mean. Most of the main features of the radiation balance at the top of the atmosphere are reasonably simulated, with some differences in the detailed structure of the patterns and intensities for both summer and winter in comparison with values as derived from Nimbus and NOAA (National Oceanic and Atmospheric Administration) satellite observations. Both the capability and defects of the model are discussed.

Snow hydrology in a general circulation model

NASA Technical Reports Server (NTRS)

Marshall, Susan; Roads, John O.; Glatzmaier, Gary

1994-01-01

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

Evaluation of the NASA GISS AR5 SCM/GCM at the ARM SGP Site using Self Organizing Maps

NASA Astrophysics Data System (ADS)

Kennedy, A. D.; Dong, X.; Xi, B.; Del Genio, A. D.; Wolf, A.

2011-12-01

Understanding and improving clouds in climate models requires moving beyond comparing annual and seasonal means. Errors can offset resulting in models getting the right long-term solution for the wrong reasons. For example, cloud parameterization errors may be balanced by the model incorrectly simulating the frequency distribution of atmospheric states. To faithfully evaluate climate models it is necessary to partition results into specific regimes. This has been completed in the past by evaluating models by their ability to produce cloud regimes as determined by observational products from satellites. An alternative approach is to first classify meteorological regimes (i.e., synoptic pattern and forcing) and then determine what types of clouds occur for each class. In this study, a competitive neural network known as the Self Organizing Map (SOM) is first used to classify synoptic patterns from a reanalysis over the Southern Great Plains (SGP) region during the period 1999-2008. These results are then used to evaluate simulated clouds from the AR5 version of the NASA GISS Model E Single Column Model (SCM). Unlike past studies that narrowed classes into several categories, this study assumes that the atmosphere is capable of producing an infinite amount of states. As a result, SOMs were generated with a large number of classes for specific months when model errors were found. With nearly ten years of forcing data, an adequate number of samples have been used to determine how cloud fraction varies across the SOM and to distinguish cloud errors. Barring major forcing errors, SCM studies can be thought of as what the GCM would simulate if the dynamics were perfect. As a result, simulated and observed CFs frequently occur for the same atmospheric states. For example, physically deep clouds during the winter months occur for a small number of classes in the SOM. Although the model produces clouds during the correct states, CFs are consistently too low. Instead, the model has a positive bias of thinner clouds during these classes that were associated with low-pressure systems and fronts. To determine if this and other SCM errors are present in the GCM, the Atmospheric Model Intercomparison Project (AMIP) run for the NASA GISS GCM will also be investigated. The SOM will be used to classify atmospheric states within the GCM to determine how well the GCM captures the PDF of observed atmospheric states. Together, these comparisons will allow for a thorough evaluation of the model at the ARM SGP site.

Does Dynamical Downscaling Introduce Novel Information in Climate Model Simulations of Recipitation Change over a Complex Topography Region?

NASA Technical Reports Server (NTRS)

Tselioudis, George; Douvis, Costas; Zerefos, Christos

2012-01-01

Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography.

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Suarez, Max; Sawyer, William; Govindaraju, Ravi C.

1999-01-01

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Projected strengthening of Amazonian dry season by constrained climate model simulations

NASA Astrophysics Data System (ADS)

Boisier, Juan P.; Ciais, Philippe; Ducharne, Agnès; Guimberteau, Matthieu

2015-07-01

The vulnerability of Amazonian rainforest, and the ecological services it provides, depends on an adequate supply of dry-season water, either as precipitation or stored soil moisture. How the rain-bearing South American monsoon will evolve across the twenty-first century is thus a question of major interest. Extensive savanization, with its loss of forest carbon stock and uptake capacity, is an extreme although very uncertain scenario. We show that the contrasting rainfall projections simulated for Amazonia by 36 global climate models (GCMs) can be reproduced with empirical precipitation models, calibrated with historical GCM data as functions of the large-scale circulation. A set of these simple models was therefore calibrated with observations and used to constrain the GCM simulations. In agreement with the current hydrologic trends, the resulting projection towards the end of the twenty-first century is for a strengthening of the monsoon seasonal cycle, and a dry-season lengthening in southern Amazonia. With this approach, the increase in the area subjected to lengthy--savannah-prone--dry seasons is substantially larger than the GCM-simulated one. Our results confirm the dominant picture shown by the state-of-the-art GCMs, but suggest that the `model democracy' view of these impacts can be significantly underestimated.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

An improved standardization procedure to remove systematic low frequency variability biases in GCM simulations

NASA Astrophysics Data System (ADS)

Mehrotra, Rajeshwar; Sharma, Ashish

2012-12-01

The quality of the absolute estimates of general circulation models (GCMs) calls into question the direct use of GCM outputs for climate change impact assessment studies, particularly at regional scales. Statistical correction of GCM output is often necessary when significant systematic biasesoccur between the modeled output and observations. A common procedure is to correct the GCM output by removing the systematic biases in low-order moments relative to observations or to reanalysis data at daily, monthly, or seasonal timescales. In this paper, we present an extension of a recently published nested bias correction (NBC) technique to correct for the low- as well as higher-order moments biases in the GCM-derived variables across selected multiple time-scales. The proposed recursive nested bias correction (RNBC) approach offers an improved basis for applying bias correction at multiple timescales over the original NBC procedure. The method ensures that the bias-corrected series exhibits improvements that are consistently spread over all of the timescales considered. Different variations of the approach starting from the standard NBC to the more complex recursive alternatives are tested to assess their impacts on a range of GCM-simulated atmospheric variables of interest in downscaling applications related to hydrology and water resources. Results of the study suggest that three to five iteration RNBCs are the most effective in removing distributional and persistence related biases across the timescales considered.

Estimates of runoff using water-balance and atmospheric general circulation models

USGS Publications Warehouse

Wolock, D.M.; McCabe, G.J.

1999-01-01

The effects of potential climate change on mean annual runoff in the conterminous United States (U.S.) are examined using a simple water-balance model and output from two atmospheric general circulation models (GCMs). The two GCMs are from the Canadian Centre for Climate Prediction and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HAD). In general, the CCC GCM climate results in decreases in runoff for the conterminous U.S., and the HAD GCM climate produces increases in runoff. These estimated changes in runoff primarily are the result of estimated changes in precipitation. The changes in mean annual runoff, however, mostly are smaller than the decade-to-decade variability in GCM-based mean annual runoff and errors in GCM-based runoff. The differences in simulated runoff between the two GCMs, together with decade-to-decade variability and errors in GCM-based runoff, cause the estimates of changes in runoff to be uncertain and unreliable.

Seasonal simulations of the planetary boundary layer and boundary-layer stratocumulus clouds with a general circulation model

NASA Technical Reports Server (NTRS)

Randall, D. A.; Abeles, J. A.; Corsetti, T. G.

1985-01-01

The formulation of the planetary boundary layer (PBL) and stratocumulus parametrizations in the UCLA general circulation model (GCM) are briefly summarized, and extensive new results are presented illustrating some aspects of the simulated seasonal changes of the global distributions of PBL depth, stratocumulus cloudiness, cloud-top entrainment instability, the cumulus mass flux, and related fields. Results from three experiments designed to reveal the sensitivity of the GCM results to aspects of the PBL and stratocumulus parametrizations are presented. The GCM results show that the layer cloud instability appears to limit the extent of the marine subtropical stratocumulus regimes, and that instability frequently occurs in association with cumulus convection over land. Cumulus convection acts as a very significant sink of PBL mass throughout the tropics and over the midlatitude continents in winter.

Sensitivity of polar ozone recovery predictions of the GMI 3D CTM to GCM and DAS dynamics

NASA Astrophysics Data System (ADS)

Considine, D.; Connell, P.; Strahan, S.; Douglass, A.; Rotman, D.

2003-04-01

The Global Modeling Initiative (GMI) 3-D chemistry and transport model has been used to generate 2 simulations of the 1995-2030 time period. The 36-year simulations both used the source gas and aerosol boundary conditions of the 2002 World Meteorological Organization assessment exercise MA2. The first simulation was based on a single year of meteorological data (winds, temperatures) generated by the new Goddard Space Flight Center "Finite Volume" General Circulation Model (FVGCM), repeated for each year of the simulation. The second simulation used a year of meteorological data generated by a new data assimilation system based on the FVGCM (FVDAS), using observations for July 1, 1999 - June 30, 2000. All other aspects of the two simulations were identical. The increase in vortex-averaged south polar springtime ozone concentrations in the lower stratosphere over the course of the simulations is more robust in the simulation driven by the GCM meteorological data than in the simulation driven by DAS winds. At the same time, the decrease in estimated chemical springtime ozone loss is similar. We thus attribute the differences between the two simulations to differences in the representations of polar dynamics which reduce the sensitivity of the simulation driven by DAS winds to changes in vortex chemistry. We also evaluate the representations in the two simulations of trace constituent distributions in the current polar lower stratosphere using various observations. In these comparisons the GCM-based simulation often is in better agreement with the observations than the DAS-based simulation.

Investigating TIME-GCM Atmospheric Tides for Different Lower Boundary Conditions

NASA Astrophysics Data System (ADS)

Haeusler, K.; Hagan, M. E.; Lu, G.; Forbes, J. M.; Zhang, X.; Doornbos, E.

2013-12-01

It has been recently established that atmospheric tides generated in the lower atmosphere significantly influence the geospace environment. In order to extend our knowledge of the various coupling mechanisms between the different atmospheric layers, we rely on model simulations. Currently there exist two versions of the Global Scale Wave Model (GSWM), i.e. GSWM02 and GSWM09, which are used as a lower boundary (ca. 30 km) condition for the Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM) and account for the upward propagating atmospheric tides that are generated in the troposphere and lower stratosphere. In this paper we explore the various TIME-GCM upper atmospheric tidal responses for different lower boundary conditions and compare the model diagnostics with tidal results from satellite missions such as TIMED, CHAMP, and GOCE. We also quantify the differences between results associated with GSWM02 and GSWM09 forcing and results of TIMEGCM simulations using Modern-Era Retrospective Analysis for Research and Application (MERRA) data as a lower boundary condition.

A new framework for quantifying uncertainties in modelling studies for future climates - how more certain are CMIP5 precipitation and temperature simulations compared to CMIP3?

NASA Astrophysics Data System (ADS)

Sharma, A.; Woldemeskel, F. M.; Sivakumar, B.; Mehrotra, R.

2014-12-01

We outline a new framework for assessing uncertainties in model simulations, be they hydro-ecological simulations for known scenarios, or climate simulations for assumed scenarios representing the future. This framework is illustrated here using GCM projections for future climates for hydrologically relevant variables (precipitation and temperature), with the uncertainty segregated into three dominant components - model uncertainty, scenario uncertainty (representing greenhouse gas emission scenarios), and ensemble uncertainty (representing uncertain initial conditions and states). A novel uncertainty metric, the Square Root Error Variance (SREV), is used to quantify the uncertainties involved. The SREV requires: (1) Interpolating raw and corrected GCM outputs to a common grid; (2) Converting these to percentiles; (3) Estimating SREV for model, scenario, initial condition and total uncertainty at each percentile; and (4) Transforming SREV to a time series. The outcome is a spatially varying series of SREVs associated with each model that can be used to assess how uncertain the system is at each simulated point or time. This framework, while illustrated in a climate change context, is completely applicable for assessment of uncertainties any modelling framework may be subject to. The proposed method is applied to monthly precipitation and temperature from 6 CMIP3 and 13 CMIP5 GCMs across the world. For CMIP3, B1, A1B and A2 scenarios whereas for CMIP5, RCP2.6, RCP4.5 and RCP8.5 representing low, medium and high emissions are considered. For both CMIP3 and CMIP5, model structure is the largest source of uncertainty, which reduces significantly after correcting for biases. Scenario uncertainly increases, especially for temperature, in future due to divergence of the three emission scenarios analysed. While CMIP5 precipitation simulations exhibit a small reduction in total uncertainty over CMIP3, there is almost no reduction observed for temperature projections. Estimation of uncertainty in both space and time sheds lights on the spatial and temporal patterns of uncertainties in GCM outputs, providing an effective platform for risk-based assessments of any alternate plans or decisions that may be formulated using GCM simulations.

Changes in Seasonal and Extreme Hydrologic Conditions of the Georgia Basin/Puget Sound in an Ensemble Regional Climate Simulation for the Mid-Century

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Lai R.; Qian, Yun

This study examines an ensemble of climate change projections simulated by a global climate model (GCM) and downscaled with a region climate model (RCM) to 40 km spatial resolution for the western North America. One control and three ensemble future climate simulations were produced by the GCM following a business as usual scenario for greenhouse gases and aerosols emissions from 1995 to 2100. The RCM was used to downscale the GCM control simulation (1995-2015) and each ensemble future GCM climate (2040-2060) simulation. Analyses of the regional climate simulations for the Georgia Basin/Puget Sound showed a warming of 1.5-2oC and statisticallymore » insignificant changes in precipitation by the mid-century. Climate change has large impacts on snowpack (about 50% reduction) but relatively smaller impacts on the total runoff for the basin as a whole. However, climate change can strongly affect small watersheds such as those located in the transient snow zone, causing a higher likelihood of winter flooding as a higher percentage of precipitation falls in the form of rain rather than snow, and reduced streamflow in early summer. In addition, there are large changes in the monthly total runoff above the upper 1% threshold (or flood volume) from October through May, and the December flood volume of the future climate is 60% above the maximum monthly flood volume of the control climate. Uncertainty of the climate change projections, as characterized by the spread among the ensemble future climate simulations, is relatively small for the basin mean snowpack and runoff, but increases in smaller watersheds, especially in the transient snow zone, and associated with extreme events. This emphasizes the importance of characterizing uncertainty through ensemble simulations.« less

Ground-water/surface-water responses to global climate simulations, Santa Clara-Calleguas basin, Ventura County, California, 1950-93

USGS Publications Warehouse

Hanson, Randall T.; Dettinger, Michael D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara-Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.

Ground water/surface water responses to global climate simulations, Santa Clara-Calleguas Basin, Ventura, California

USGS Publications Warehouse

Hanson, R.T.; Dettinger, M.D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa ClaraCalleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Nin??o Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/??C, compared to 0.9 m/??C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and - when the GCM forecast skills are adequate - for near term predictions.

GCM simulations of intraseasonal variability in the Pacific/North American region

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Suarez, Max; Park, Chung-Kyu; Moorthi, Shrinivas

1993-01-01

General circulation model (GCM) simulations of low-frequency variability with time scales of 20 to 70 days are analyzed for the Pacific sector during boreal winter. The GCM's leading mode in the upper-tropospheric zonal wind is associated with fluctuations of the East Asian jet; this mode resembles, in both structure and amplitude, the Pacific/North American (PNA) pattern found in the observations on these time scales. In both the model and observations, the PNA anomaly is characterized by: (1) a linear balance in the upper-tropospheric vorticity budget with no significant Rossby wave source in the tropics, (2) a barotropic conversion of kinetic energy from the time mean Pacific jet, and (3) a north/south displacement of the Pacific storm track. In the GCM, the latter is associated with synoptic eddy heat flux and latent heat anomalies that appear to contribute to a strong lower-tropospheric source of wave activity over the North Pacific. This is in contrast to the observations, which show only a weak source of wave activity in this region.

Dynamically downscaling predictions for deciduous tree leaf emergence in California under current and future climate.

PubMed

Medvigy, David; Kim, Seung Hee; Kim, Jinwon; Kafatos, Menas C

2016-07-01

Models that predict the timing of deciduous tree leaf emergence are typically very sensitive to temperature. However, many temperature data products, including those from climate models, have been developed at a very coarse spatial resolution. Such coarse-resolution temperature products can lead to highly biased predictions of leaf emergence. This study investigates how dynamical downscaling of climate models impacts simulations of deciduous tree leaf emergence in California. Models for leaf emergence are forced with temperatures simulated by a general circulation model (GCM) at ~200-km resolution for 1981-2000 and 2031-2050 conditions. GCM simulations are then dynamically downscaled to 32- and 8-km resolution, and leaf emergence is again simulated. For 1981-2000, the regional average leaf emergence date is 30.8 days earlier in 32-km simulations than in ~200-km simulations. Differences between the 32 and 8 km simulations are small and mostly local. The impact of downscaling from 200 to 8 km is ~15 % smaller in 2031-2050 than in 1981-2000, indicating that the impacts of downscaling are unlikely to be stationary.

The Simulation of Daily Temperature Time Series from GCM Output. Part II: Sensitivity Analysis of an Empirical Transfer Function Methodology.

NASA Astrophysics Data System (ADS)

Winkler, Julie A.; Palutikof, Jean P.; Andresen, Jeffrey A.; Goodess, Clare M.

1997-10-01

Empirical transfer functions have been proposed as a means for `downscaling' simulations from general circulation models (GCMs) to the local scale. However, subjective decisions made during the development of these functions may influence the ensuing climate scenarios. This research evaluated the sensitivity of a selected empirical transfer function methodology to 1) the definition of the seasons for which separate specification equations are derived, 2) adjustments for known departures of the GCM simulations of the predictor variables from observations, 3) the length of the calibration period, 4) the choice of function form, and 5) the choice of predictor variables. A modified version of the Climatological Projection by Model Statistics method was employed to generate control (1 × CO2) and perturbed (2 × CO2) scenarios of daily maximum and minimum temperature for two locations with diverse climates (Alcantarilla, Spain, and Eau Claire, Michigan). The GCM simulations used in the scenario development were from the Canadian Climate Centre second-generation model (CCC GCMII).Variations in the downscaling methodology were found to have a statistically significant impact on the 2 × CO2 climate scenarios, even though the 1 × CO2 scenarios for the different transfer function approaches were often similar. The daily temperature scenarios for Alcantarilla and Eau Claire were most sensitive to the decision to adjust for deficiencies in the GCM simulations, the choice of predictor variables, and the seasonal definitions used to derive the functions (i.e., fixed seasons, floating seasons, or no seasons). The scenarios were less sensitive to the choice of function form (i.e., linear versus nonlinear) and to an increase in the length of the calibration period.The results of Part I, which identified significant departures of the CCC GCMII simulations of two candidate predictor variables from observations, together with those presented here in Part II, 1) illustrate the importance of detailed comparisons of observed and GCM 1 × CO2 series of candidate predictor variables as an initial step in impact analysis, 2) demonstrate that decisions made when developing the transfer functions can have a substantial influence on the 2 × CO2 scenarios and their interpretation, 3) highlight the uncertainty in the appropriate criteria for evaluating transfer function approaches, and 4) suggest that automation of empirical transfer function methodologies is inappropriate because of differences in the performance of transfer functions between sites and because of spatial differences in the GCM's ability to adequately simulate the predictor variables used in the functions.

Atmospheric, Climatic, and Environmental Research

NASA Technical Reports Server (NTRS)

Broecker, Wallace S.; Gornitz, Vivien M.

1994-01-01

The climate and atmospheric modeling project involves analysis of basic climate processes, with special emphasis on studies of the atmospheric CO2 and H2O source/sink budgets and studies of the climatic role Of CO2, trace gases and aerosols. These studies are carried out, based in part on use of simplified climate models and climate process models developed at GISS. The principal models currently employed are a variable resolution 3-D general circulation model (GCM), and an associated "tracer" model which simulates the advection of trace constituents using the winds generated by the GCM.

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

NASA Technical Reports Server (NTRS)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Montmessin, F.; Brecht, A. S.; Urata, R.; Klassen, D. R.; Wolff, M. J.

2017-01-01

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Quantifying the effect of varying GHG's concentration in Regional Climate Models

NASA Astrophysics Data System (ADS)

López-Romero, Jose Maria; Jerez, Sonia; Palacios-Peña, Laura; José Gómez-Navarro, Juan; Jiménez-Guerrero, Pedro; Montavez, Juan Pedro

2017-04-01

Regional Climate Models (RCMs) are driven at the boundaries by Global Circulation Models (GCM), and in the particular case of Climate Change projections, such simulations are forced by varying greenhouse gases (GHGs) concentrations. In hindcast simulations driven by reanalysis products, the climate change signal is usually introduced in the assimilation process as well. An interesting question arising in this context is whether GHGs concentrations have to be varied within the RCMs model itself, or rather they should be kept constant. Some groups keep the GHGs concentrations constant under the assumption that information about climate change signal is given throughout the boundaries; sometimes certain radiation parameterization schemes do not permit such changes. Other approaches vary these concentrations arguing that this preserves the physical coherence respect to the driving conditions for the RCM. This work aims to shed light on this topic. For this task, various regional climate simulations with the WRF model for the 1954-2004 period have been carried out for using a Euro-CORDEX compliant domain. A series of simulations with constant and variable GHGs have been performed using both, a GCM (ECHAM6-OM) and a reanalysis product (ERA-20C) data. Results indicate that there exist noticeable differences when introducing varying GHGs concentrations within the RCM domain. The differences in 2-m temperature series between the experiments with varying or constant GHGs concentration strongly depend on the atmospheric conditions, appearing a strong interannual variability. This suggests that short-term experiments are not recommended if the aim is to assess the role of varying GHGs. In addition, and consistently in both GCM and reanalysis-driven experiments, the magnitude of temperature trends, as well as the spatial pattern represented by varying GHGs experiment, are closer to the driving dataset than in experiments keeping constant the GHGs concentration. These results point towards the need for the inclusion of varying GHGs concentration within the RCM itself when dynamically downscaling global datasets, both in GCM and hindcast simulations.

Using Web 2.0 Techniques To Bring Global Climate Modeling To More Users

NASA Astrophysics Data System (ADS)

Chandler, M. A.; Sohl, L. E.; Tortorici, S.

2012-12-01

The Educational Global Climate Model has been used for many years in undergraduate courses and professional development settings to teach the fundamentals of global climate modeling and climate change simulation to students and teachers. While course participants have reported a high level of satisfaction in these courses and overwhelmingly claim that EdGCM projects are worth the effort, there is often a high level of frustration during the initial learning stages. Many of the problems stem from issues related to installation of the software suite and to the length of time it can take to run initial experiments. Two or more days of continuous run time may be required before enough data has been gathered to begin analyses. Asking users to download existing simulation data has not been a solution because the GCM data sets are several gigabytes in size, requiring substantial bandwidth and stable dedicated internet connections. As a means of getting around these problems we have been developing a Web 2.0 utility called EzGCM (Easy G-G-M) which emphasizes that participants learn the steps involved in climate modeling research: constructing a hypothesis, designing an experiment, running a computer model and assessing when an experiment has finished (reached equilibrium), using scientific visualization to support analysis, and finally communicating the results through social networking methods. We use classic climate experiments that can be "rediscovered" through exercises with EzGCM and are attempting to make this Web 2.0 tool an entry point into climate modeling for teachers with little time to cover the subject, users with limited computer skills, and for those who want an introduction to the process before tackling more complex projects with EdGCM.

Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Tracer water transport and subgrid precipitation variation within atmospheric general circulation models

NASA Astrophysics Data System (ADS)

Koster, Randal D.; Eagleson, Peter S.; Broecker, Wallace S.

1988-03-01

A capability is developed for monitoring tracer water movement in the three-dimensional Goddard Institute for Space Science Atmospheric General Circulation Model (GCM). A typical experiment with the tracer water model follows water evaporating from selected grid squares and determines where this water first returns to the Earth's surface as precipitation or condensate, thereby providing information on the lateral scales of hydrological transport in the GCM. Through a comparison of model results with observations in nature, inferences can be drawn concerning real world water transport. Tests of the tracer water model include a comparison of simulated and observed vertically-integrated vapor flux fields and simulations of atomic tritium transport from the stratosphere to the oceans. The inter-annual variability of the tracer water model results is also examined.

Tracer water transport and subgrid precipitation variation within atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Eagleson, Peter S.; Broecker, Wallace S.

1988-01-01

A capability is developed for monitoring tracer water movement in the three-dimensional Goddard Institute for Space Science Atmospheric General Circulation Model (GCM). A typical experiment with the tracer water model follows water evaporating from selected grid squares and determines where this water first returns to the Earth's surface as precipitation or condensate, thereby providing information on the lateral scales of hydrological transport in the GCM. Through a comparison of model results with observations in nature, inferences can be drawn concerning real world water transport. Tests of the tracer water model include a comparison of simulated and observed vertically-integrated vapor flux fields and simulations of atomic tritium transport from the stratosphere to the oceans. The inter-annual variability of the tracer water model results is also examined.

Climate simulation of the twenty-first century with interactive land-use changes

NASA Astrophysics Data System (ADS)

Voldoire, Aurore; Eickhout, Bas; Schaeffer, Michiel; Royer, Jean-François; Chauvin, Fabrice

2007-08-01

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.

Comparison of Global Cloud Fraction and TOA Radiation Budgets between the NASA GISS AR5 GCM Simulations and CERES-MODIS Observations

NASA Astrophysics Data System (ADS)

Stanfield, R. E.; Dong, X.; Xi, B.; Del Genio, A. D.; Minnis, P.; Doelling, D.; Loeb, N. G.

2011-12-01

To better advise policymakers, it is necessary for climate models to provide credible predictions of future climates. Meeting this goal requires climate models to successfully simulate the present and past climates. The past, current and future Earth climate has been simulated by the NASA GISS ModelE climate model and has been summarized by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, AR4, 2007). New simulations from the updated AR5 version of the NASA GISS ModelE GCM have been released to the public community and will be included in the IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, however, they have yet to be extensively validated against observations. To evaluate the GISS AR5 simulated global clouds and TOA radiation budgets, we have collected and processed the NASA CERES and MODIS observations during the period 2000-2005. In detail, the 1ox1o resolution monthly averaged SYN1 product has been used with combined observations from both Terra and Aqua satellites, and degraded to a 2ox2.5o grid box to match the GCM spatial resolution. These observations are temporally interpolated and fit to data from geostationary satellites to provide time continuity. The GISS AR5 products were downloaded from the CMIP5 (Coupled Model Intercomparison Project Phase 5) for the IPCC-AR5. Preliminary comparisons between GISS AR5 simulations and CERES-MODIS observations have shown that although their annual and seasonal mean CFs agree within a few percent, there are significant differences in several climatic regions. For example, the modeled CFs have positive biases in the Arctic, Antarctic, Tropics, and Sahara Desert, but negative biases over the southern middle latitudes (30-65 oS). The OLR, albedo and NET radiation comparisons are similar to the CF comparison.

Regional climates in the GISS global circulation model - Synoptic-scale circulation

NASA Technical Reports Server (NTRS)

Hewitson, B.; Crane, R. G.

1992-01-01

A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.

Evaluation of NASA GISS post-CMIP5 single column model simulated clouds and precipitation using ARM Southern Great Plains observations

NASA Astrophysics Data System (ADS)

Zhang, Lei; Dong, Xiquan; Kennedy, Aaron; Xi, Baike; Li, Zhanqing

2017-03-01

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%-20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

Simulating Climate Change in Ireland

NASA Astrophysics Data System (ADS)

Nolan, P.; Lynch, P.

2012-04-01

At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.

Impact of the dynamical core on the direct simulation of tropical cyclones in a high-resolution global model

DOE PAGES

Reed, K. A.; Bacmeister, J. T.; Rosenbloom, N. A.; ...

2015-05-13

Our paper examines the impact of the dynamical core on the simulation of tropical cyclone (TC) frequency, distribution, and intensity. The dynamical core, the central fluid flow component of any general circulation model (GCM), is often overlooked in the analysis of a model's ability to simulate TCs compared to the impact of more commonly documented components (e.g., physical parameterizations). The Community Atmosphere Model version 5 is configured with multiple dynamics packages. This analysis demonstrates that the dynamical core has a significant impact on storm intensity and frequency, even in the presence of similar large-scale environments. In particular, the spectral elementmore » core produces stronger TCs and more hurricanes than the finite-volume core using very similar parameterization packages despite the latter having a slightly more favorable TC environment. Furthermore, these results suggest that more detailed investigations into the impact of the GCM dynamical core on TC climatology are needed to fully understand these uncertainties. Key Points The impact of the GCM dynamical core is often overlooked in TC assessments The CAM5 dynamical core has a significant impact on TC frequency and intensity A larger effort is needed to better understand this uncertainty« less

Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

NASA Astrophysics Data System (ADS)

Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

2015-04-01

At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

Evidence for Limited Indirect Aerosol Forcing in Stratocumulus

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, O. B.; Stevens, D. E.

2003-01-01

Increases in cloud cover and condensed water contribute more than half of the indirect aerosol effect in an ensemble of general circulation model (GCM) simulations estimating the global radiative forcing of anthropogenic aerosols. We use detailed simulations of marine stratocumulus clouds and airborne observations of ship tracks to show that increases in cloud cover and condensed water in reality are far less than represented by the GCM ensemble. Our results offer an explanation for recent simplified inverse climate calculations indicating that indirect aerosol effects are greatly exaggerated in GCMs.

GCM Simulation of the Large-scale North American Monsoon Including Water Vapor Tracer Diagnostics

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried D.; Sud, Yogesh; Walker, Gregory K.

2002-01-01

In this study, we have applied GCM water vapor tracers (WVT) to simulate the North American water cycle. WVTs allow quantitative computation of the geographical source of water for precipitation that occurs anywhere in the model simulation. This can be used to isolate the impact that local surface evaporation has on precipitation, compared to advection and convection. A 15 year 1 deg, 1.25 deg. simulation has been performed with 11 global and 11 North American regional WVTs. Figure 1 shows the source regions of the North American WVTs. When water evaporates from one of these predefined regions, its mass is used as the source for a distinct prognostic variable in the model. This prognostic variable allows the water to be transported and removed (precipitated) from the system in an identical way that occurs to the prognostic specific humidity. Details of the model are outlined by Bosilovich and Schubert (2002) and Bosilovich (2002). Here, we present results pertaining to the onset of the simulated North American monsoon.

Do downscaled general circulation models reliably simulate historical climatic conditions?

USGS Publications Warehouse

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2018-01-01

The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

USGS Publications Warehouse

Hay, Lauren E.; LaFontaine, Jacob H.; Markstrom, Steven

2014-01-01

The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, Bruce

1990-01-01

Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

NASA Technical Reports Server (NTRS)

Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine

2016-01-01

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

Ionosphere variability at mid latitudes during sudden stratosphere warmings

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Maute, A. I.; Maruyama, N.

2015-12-01

Variability of the mid latitude ionosphere and thermosphere during the 2009 and 2013 sudden stratosphere warmings (SSWs) is investigated in the present study using a combination of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations and model simulations. The simulations are performed using the Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM) and Ionosphere Plasmasphere Electrodynamics (IPE) model. Both the COSMIC observations and TIME-GCM simulations reveal perturbations in the F-region peak height (hmF2) at Southern Hemisphere mid latitudes during SSW time periods. The perturbations are ~20-30 km, which corresponds to 10-20% variability in hmF2. The TIME-GCM simulations and COSMIC observations of the hmF2 variability are in overall good agreement, and the simulations can thus be used to understand the physical processes responsible for the hmF2 variability. The simulation results demonstrate that the mid lattiude hmF2 variability is primarily driven by the propagation of the migrating semidiurnal lunar tide (M2) into the thermosphere where it modulates the field aligned neutrals winds, which in-turn raise and lower the F-region peak height. The importance of the thermosphere neutral winds on generating the ionosphere variability at mid latitudes during SSWs is supported by IPE simulations performed both with and without the neutral wind variability. Though there are subtle differences, the consistency of the behavior between the 2009 and 2013 SSWs suggests that variability in the Southern Hemisphere mid latitude ionosphere and thermosphere is a consistent feature of the SSW impact on the upper atmosphere.

Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low generation limits.

PubMed

Miller, Lee M; Kleidon, Axel

2016-11-29

Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power limits that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 W e m -2 ) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 W e m -2 ) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power use can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 W e m -2 of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power.

Wind speed reductions by large-scale wind turbine deployments lower turbine efficiencies and set low generation limits

PubMed Central

Miller, Lee M.; Kleidon, Axel

2016-01-01

Wind turbines generate electricity by removing kinetic energy from the atmosphere. Large numbers of wind turbines are likely to reduce wind speeds, which lowers estimates of electricity generation from what would be presumed from unaffected conditions. Here, we test how well wind power limits that account for this effect can be estimated without explicitly simulating atmospheric dynamics. We first use simulations with an atmospheric general circulation model (GCM) that explicitly simulates the effects of wind turbines to derive wind power limits (GCM estimate), and compare them to a simple approach derived from the climatological conditions without turbines [vertical kinetic energy (VKE) estimate]. On land, we find strong agreement between the VKE and GCM estimates with respect to electricity generation rates (0.32 and 0.37 We m−2) and wind speed reductions by 42 and 44%. Over ocean, the GCM estimate is about twice the VKE estimate (0.59 and 0.29 We m−2) and yet with comparable wind speed reductions (50 and 42%). We then show that this bias can be corrected by modifying the downward momentum flux to the surface. Thus, large-scale limits to wind power use can be derived from climatological conditions without explicitly simulating atmospheric dynamics. Consistent with the GCM simulations, the approach estimates that only comparatively few land areas are suitable to generate more than 1 We m−2 of electricity and that larger deployment scales are likely to reduce the expected electricity generation rate of each turbine. We conclude that these atmospheric effects are relevant for planning the future expansion of wind power. PMID:27849587

Coupled fvGCM-GCE Modeling System, TRMM Latent Heating and Cloud Library

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2004-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to imiprove the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. I this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the Goddard research plan of using Weather Research Forecast (WRF) model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Projecting the spatiotemporal carbon dynamics of the Greater Yellowstone Ecosystem from 2006 to 2050

USGS Publications Warehouse

Huang, Shengli; Liu, Shuguang; Liu, Jinxun; Dahal, Devendra; Young, Claudia; Davis, Brian; Sohl, Terry L.; Hawbaker, Todd J.; Sleeter, Benjamin M.; Zhu, Zhiliang

2015-01-01

BackgroundClimate change and the concurrent change in wildfire events and land use comprehensively affect carbon dynamics in both spatial and temporal dimensions. The purpose of this study was to project the spatial and temporal aspects of carbon storage in the Greater Yellowstone Ecosystem (GYE) under these changes from 2006 to 2050. We selected three emission scenarios and produced simulations with the CENTURY model using three General Circulation Models (GCMs) for each scenario. We also incorporated projected land use change and fire occurrence into the carbon accounting.ResultsThe three GCMs showed increases in maximum and minimum temperature, but precipitation projections varied among GCMs. Total ecosystem carbon increased steadily from 7,942 gC/m2 in 2006 to 10,234 gC/m2 in 2050 with an annual rate increase of 53 gC/m2/year. About 56.6% and 27% of the increasing rate was attributed to total live carbon and total soil carbon, respectively. Net Primary Production (NPP) increased slightly from 260 gC/m2/year in 2006 to 310 gC/m2/year in 2050 with an annual rate increase of 1.22 gC/m2/year. Forest clear-cutting and fires resulted in direct carbon removal; however, the rate was low at 2.44 gC/m2/year during 2006–2050. The area of clear-cutting and wildfires in the GYE would account for 10.87% of total forested area during 2006–2050, but the predictive simulations demonstrated different spatial distributions in national forests and national parks.ConclusionsThe GYE is a carbon sink during 2006–2050. The capability of vegetation is almost double that of soil in terms of sequestering extra carbon. Clear-cutting and wildfires in GYE will affect 10.87% of total forested area, but direct carbon removal from clear-cutting and fires is 109.6 gC/m2, which accounts for only 1.2% of the mean ecosystem carbon level of 9,056 gC/m2, and thus is not significant.

Projecting the spatiotemporal carbon dynamics of the Greater Yellowstone Ecosystem from 2006 to 2050.

PubMed

Huang, Shengli; Liu, Shuguang; Liu, Jinxun; Dahal, Devendra; Young, Claudia; Davis, Brian; Sohl, Terry L; Hawbaker, Todd J; Sleeter, Ben; Zhu, Zhiliang

2015-12-01

Climate change and the concurrent change in wildfire events and land use comprehensively affect carbon dynamics in both spatial and temporal dimensions. The purpose of this study was to project the spatial and temporal aspects of carbon storage in the Greater Yellowstone Ecosystem (GYE) under these changes from 2006 to 2050. We selected three emission scenarios and produced simulations with the CENTURY model using three General Circulation Models (GCMs) for each scenario. We also incorporated projected land use change and fire occurrence into the carbon accounting. The three GCMs showed increases in maximum and minimum temperature, but precipitation projections varied among GCMs. Total ecosystem carbon increased steadily from 7,942 gC/m 2 in 2006 to 10,234 gC/m 2 in 2050 with an annual rate increase of 53 gC/m 2 /year. About 56.6% and 27% of the increasing rate was attributed to total live carbon and total soil carbon, respectively. Net Primary Production (NPP) increased slightly from 260 gC/m 2 /year in 2006 to 310 gC/m 2 /year in 2050 with an annual rate increase of 1.22 gC/m 2 /year. Forest clear-cutting and fires resulted in direct carbon removal; however, the rate was low at 2.44 gC/m 2 /year during 2006-2050. The area of clear-cutting and wildfires in the GYE would account for 10.87% of total forested area during 2006-2050, but the predictive simulations demonstrated different spatial distributions in national forests and national parks. The GYE is a carbon sink during 2006-2050. The capability of vegetation is almost double that of soil in terms of sequestering extra carbon. Clear-cutting and wildfires in GYE will affect 10.87% of total forested area, but direct carbon removal from clear-cutting and fires is 109.6 gC/m 2 , which accounts for only 1.2% of the mean ecosystem carbon level of 9,056 gC/m 2 , and thus is not significant.

Hurricane Forecasting with the High-resolution NASA Finite-volume General Circulation Model

NASA Technical Reports Server (NTRS)

Atlas, R.; Reale, O.; Shen, B.-W.; Lin, S.-J.; Chern, J.-D.; Putman, W.; Lee, T.; Yeh, K.-S.; Bosilovich, M.; Radakovich, J.

2004-01-01

A high-resolution finite-volume General Circulation Model (fvGCM), resulting from a development effort of more than ten years, is now being run operationally at the NASA Goddard Space Flight Center and Ames Research Center. The model is based on a finite-volume dynamical core with terrain-following Lagrangian control-volume discretization and performs efficiently on massive parallel architectures. The computational efficiency allows simulations at a resolution of a quarter of a degree, which is double the resolution currently adopted by most global models in operational weather centers. Such fine global resolution brings us closer to overcoming a fundamental barrier in global atmospheric modeling for both weather and climate, because tropical cyclones and even tropical convective clusters can be more realistically represented. In this work, preliminary results of the fvGCM are shown. Fifteen simulations of four Atlantic tropical cyclones in 2002 and 2004 are chosen because of strong and varied difficulties presented to numerical weather forecasting. It is shown that the fvGCM, run at the resolution of a quarter of a degree, can produce very good forecasts of these tropical systems, adequately resolving problems like erratic track, abrupt recurvature, intense extratropical transition, multiple landfall and reintensification, and interaction among vortices.

Sensitivity of Middle Atmospheric Temperature and Circulation in the UIUC Mesosphere-Stratosphere-Troposphere GCM to the Treatment of Subgrid-Scale Gravity-Wave Breaking

NASA Technical Reports Server (NTRS)

Yang, Fanglin; Schlesinger, Michael E.; Andranova, Natasha; Zubov, Vladimir A.; Rozanov, Eugene V.; Callis, Lin B.

2003-01-01

The sensitivity of the middle atmospheric temperature and circulation to the treatment of mean- flow forcing due to breaking gravity waves was investigated using the University of Illinois at Urbana-Champaign 40-layer Mesosphere-Stratosphere-Troposphere General Circulation Model (MST-GCM). Three GCM experiments were performed. The gravity-wave forcing was represented first by Rayleigh friction, and then by the Alexander and Dunkerton (AD) parameterization with weak and strong breaking effects of gravity waves. In all experiments, the Palmer et al. parameterization was included to treat the breaking of topographic gravity waves in the troposphere and lower stratosphere. Overall, the experiment with the strong breaking effect simulates best the middle atmospheric temperature and circulation. With Rayleigh friction and the weak breaking effect, a large warm bias of up to 60 C was found in the summer upper mesosphere and lower thermosphere. This warm bias was linked to the inability of the GCM to simulate the reversal of the zonal winds from easterly to westerly crossing the mesopause in the summer hemisphere. With the strong breaking effect, the GCM was able to simulate this reversal, and essentially eliminated the warm bias. This improvement was the result of a much stronger meridional transport circulation that possesses a strong vertical ascending branch in the summer upper mesosphere, and hence large adiabatic cooling. Budget analysis indicates that 'in the middle atmosphere the forces that act to maintain a steady zonal-mean zonal wind are primarily those associated with the meridional transport circulation and breaking gravity waves. Contributions from the interaction of the model-resolved eddies with the mean flow are small. To obtain a transport circulation in the mesosphere of the UIUC MST-GCM that is strong enough to produce the observed cold summer mesopause, gravity-wave forcing larger than 100 m/s/day in magnitude is required near the summer mesopause. In the tropics, only with the AD parameterization can the model produce realistic semiannual oscillations.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

The role of global cloud climatologies in validating numerical models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1991-01-01

The net upward longwave surface radiation is exceedingly difficult to measure from space. A hybrid method using General Circulation Model (GCM) simulations and satellite data from the Earth Radiation Budget Experiment (ERBE) and the International Satellite Cloud Climatology Project (ISCCP) was used to produce global maps of this quantity over oceanic areas. An advantage of this technique is that no independent knowledge or assumptions regarding cloud cover for a particular month are required. The only information required is a relationship between the cloud radiation forcing (CRF) at the top of the atmosphere and that at the surface, which is obtained from the GCM simulation. A flow diagram of the technique and results are given.

Coupled fvGCM-GCE Modeling System: TRMM Latent Heating and Cloud Library

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. In this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the GCE model on developing a global cloud simulator.

Dependence of stratocumulus-topped boundary-layer entrainment on cloud-water sedimentation: Impact on global aerosol indirect effect in GISS ModelE3 single column model and global simulations

NASA Astrophysics Data System (ADS)

Ackerman, A. S.; Kelley, M.; Cheng, Y.; Fridlind, A. M.; Del Genio, A. D.; Bauer, S.

2017-12-01

Reduction in cloud-water sedimentation induced by increasing droplet concentrations has been shown in large-eddy simulations (LES) and direct numerical simulation (DNS) to enhance boundary-layer entrainment, thereby reducing cloud liquid water path and offsetting the Twomey effect when the overlying air is sufficiently dry, which is typical. Among recent upgrades to ModelE3, the latest version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), are a two-moment stratiform cloud microphysics treatment with prognostic precipitation and a moist turbulence scheme that includes an option in its entrainment closure of a simple parameterization for the effect of cloud-water sedimentation. Single column model (SCM) simulations are compared to LES results for a stratocumulus case study and show that invoking the sedimentation-entrainment parameterization option indeed reduces the dependence of cloud liquid water path on increasing aerosol concentrations. Impacts of variations of the SCM configuration and the sedimentation-entrainment parameterization will be explored. Its impact on global aerosol indirect forcing in the framework of idealized atmospheric GCM simulations will also be assessed.

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

Hydroclimate variability in Scandinavia over the last millennium - insights from a climate model-proxy data comparison

NASA Astrophysics Data System (ADS)

Seftigen, Kristina; Goosse, Hugues; Klein, Francois; Chen, Deliang

2017-12-01

The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts-pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5-PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data-model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

The Ability of a General Circulation Model to represent the Atmospheric Boundary Layer over the Antarctic Plateau

NASA Astrophysics Data System (ADS)

Vignon, Etienne; Hourdin, Frédéric; Genthon, Christophe; Madeleine, Jean-Baptiste; Cheruy, Frédérique; Gallée, Hubert; Bazile, Eric; Lefebvre, Marie-Pierre; Van de Wiel, Bas J. H.

2017-04-01

In a General Circulation Model (GCM), the turbulent mixing parametrization of the atmospheric boundary layer (ABL) over the Antarctic Plateau is critical since it affects the continental scale temperature inversion, the katabatic winds and finally the Southern Hemisphere circulation. The aim of this study is to evaluate the representation of the Antarctic Plateau ABL in the Laboratoire de Météorologie Dynamique-Zoom (LMDZ) GCM, the atmospheric component of the IPSL Earth System Model in preparation for the sixth Coupled Models Intercomparison Project. We carry out 1D simulations on the fourth Gewex Atmospheric Boundary Layers Study (GABLS4) case, and 3D simulations with the 'zooming capability' of the horizontal grid and with nudging. Simulations are evaluated and validated using in-situ measurements obtained at Dome C, East Antarctic Plateau, and satellite data. Sensitivity tests to surface parameters, vertical grid and turbulent mixing parametrizations led to significant improvements of the model and to a new configuration better adapted for Antarctic conditions. In particular, we point out the need to remove minimum turbulence thresholds to correctly reproduce very steep temperature and wind speed gradients in the stable ABL. We then assess the ability of the GCM to represent the two distinct stable ABL regimes and very strong near-surface temperature inversions, which are fascinating and critical features of the Dome C climate. This leads us to investigate the competition between radiative and turbulent coupling between the ABL and the snow surface in the model. Our results show that the new configuration of LMDZ reproduces reasonnably well the Dome C climatology and it is able to model strong temperature inversions and radiatively-dominated ABL. However, they also reveal a strong sensitivity of the modeling of the different regimes to the radiative scheme and vertical resolution. The present work finally hints at future developments to better and more physically represent the polar ABL in a GCM.

Constraints on Cumulus Parameterization from Simulations of Observed MJO Events

NASA Technical Reports Server (NTRS)

Del Genio, Anthony; Wu, Jingbo; Wolf, Audrey B.; Chen, Yonghua; Yao, Mao-Sung; Kim, Daehyun

2015-01-01

Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden-Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

Extending systems thinking in planning and evaluation using group concept mapping and system dynamics to tackle complex problems.

PubMed

Hassmiller Lich, Kristen; Urban, Jennifer Brown; Frerichs, Leah; Dave, Gaurav

2017-02-01

Group concept mapping (GCM) has been successfully employed in program planning and evaluation for over 25 years. The broader set of systems thinking methodologies (of which GCM is one), have only recently found their way into the field. We present an overview of systems thinking emerging from a system dynamics (SD) perspective, and illustrate the potential synergy between GCM and SD. As with GCM, participatory processes are frequently employed when building SD models; however, it can be challenging to engage a large and diverse group of stakeholders in the iterative cycles of divergent thinking and consensus building required, while maintaining a broad perspective on the issue being studied. GCM provides a compelling resource for overcoming this challenge, by richly engaging a diverse set of stakeholders in broad exploration, structuring, and prioritization. SD provides an opportunity to extend GCM findings by embedding constructs in a testable hypothesis (SD model) describing how system structure and changes in constructs affect outcomes over time. SD can be used to simulate the hypothesized dynamics inherent in GCM concept maps. We illustrate the potential of the marriage of these methodologies in a case study of BECOMING, a federally-funded program aimed at strengthening the cross-sector system of care for youth with severe emotional disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

NASA Astrophysics Data System (ADS)

Yu, Karen; Keller, Christoph A.; Jacob, Daniel J.; Molod, Andrea M.; Eastham, Sebastian D.; Long, Michael S.

2018-01-01

Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.25° × 0.3125° (≈ 25 km) and 2° × 2.5° (≈ 200 km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (≈ 25 km) and c48 (≈ 200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 h and remapped to 0.25° × 0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° × 0.3125° resolution is affected by vertical transport errors of up to 20 % relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3 h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25° × 0.3125° to 2° × 2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40 % in surface air relative to the online c360 simulations and underestimated by up to 40 % in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10 %. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

2002-01-01

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

The Sensitivity of Arctic Ozone Loss to Polar Stratospheric Cloud Volume and Chlorine and Bromine Loading in a Chemistry and Transport Model

NASA Technical Reports Server (NTRS)

Douglass, A. R.; Stolarski, R. S.; Strahan, S. E.; Polansky, B. C.

2006-01-01

The sensitivity of Arctic ozone loss to polar stratospheric cloud volume (V(sub PSC)) and chlorine and bromine loading is explored using chemistry and transport models (CTMs). A simulation using multi-decadal output from a general circulation model (GCM) in the Goddard Space Flight Center (GSFC) CTM complements one recycling a single year s GCM output in the Global Modeling Initiative (GMI) CTM. Winter polar ozone loss in the GSFC CTM depends on equivalent effective stratospheric chlorine (EESC) and polar vortex characteristics (temperatures, descent, isolation, polar stratospheric cloud amount). Polar ozone loss in the GMI CTM depends only on changes in EESC as the dynamics repeat annually. The GSFC CTM simulation reproduces a linear relationship between ozone loss and Vpsc derived from observations for 1992 - 2003 which holds for EESC within approx.85% of its maximum (approx.1990 - 2020). The GMI simulation shows that ozone loss varies linearly with EESC for constant, high V(sub PSC).

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

GCM Simulation of the Large-Scale North American Monsoon Including Water Vapor Tracer Diagnostics

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Walker, Gregory; Schubert, Siegfried D.; Sud, Yogesh; Atlas, Robert M. (Technical Monitor)

2002-01-01

The geographic sources of water for the large scale North American monsoon in a GCM (General Circulation Model) are diagnosed using passive constituent tracers of regional water sources (Water Vapor Tracers, WVT). The NASA Data Assimilation Office Finite Volume (FV) GCM was used to produce a 10-year simulation (1984 through 1993) including observed sea surface temperature. Regional and global WVT sources were defined to delineate the surface origin of water for precipitation in and around the North American Monsoon. The evolution of the mean annual cycle and the interannual variations of the monsoonal circulation will be discussed. Of special concern are the relative contributions of the local source (precipitation recycling) and remote sources of water vapor to the annual cycle and the interannual variation of monsoonal precipitation. The relationships between soil water, surface evaporation, precipitation and precipitation recycling will be evaluated.

A nonadditive methanol force field: Bulk liquid and liquid-vapor interfacial properties via molecular dynamics simulations using a fluctuating charge model

NASA Astrophysics Data System (ADS)

Patel, Sandeep; Brooks, Charles L.

2005-01-01

We study the bulk and interfacial properties of methanol via molecular dynamics simulations using a CHARMM (Chemistry at HARvard Molecular Mechanics) fluctuating charge force field. We discuss the parametrization of the electrostatic model as part of the ongoing CHARMM development for polarizable protein force fields. The bulk liquid properties are in agreement with available experimental data and competitive with existing fixed-charge and polarizable force fields. The liquid density and vaporization enthalpy are determined to be 0.809 g/cm3 and 8.9 kcal/mol compared to the experimental values of 0.787 g/cm3 and 8.94 kcal/mol, respectively. The liquid structure as indicated by radial distribution functions is in keeping with the most recent neutron diffraction results; the force field shows a slightly more ordered liquid, necessarily arising from the enhanced condensed phase electrostatics (as evidenced by an induced liquid phase dipole moment of 0.7 D), although the average coordination with two neighboring molecules is consistent with the experimental diffraction study as well as with recent density functional molecular dynamics calculations. The predicted surface tension of 19.66±1.03 dyn/cm is slightly lower than the experimental value of 22.6 dyn/cm, but still competitive with classical force fields. The interface demonstrates the preferential molecular orientation of molecules as observed via nonlinear optical spectroscopic methods. Finally, via canonical molecular dynamics simulations, we assess the model's ability to reproduce the vapor-liquid equilibrium from 298 to 423 K, the simulation data then used to obtain estimates of the model's critical temperature and density. The model predicts a critical temperature of 470.1 K and critical density of 0.312 g/cm3 compared to the experimental values of 512.65 K and 0.279 g/cm3, respectively. The model underestimates the critical temperature by 8% and overestimates the critical density by 10%, and in this sense is roughly equivalent to the underlying fixed-charge CHARMM22 force field.

Global Climate Model Simulated Hydrologic Droughts and Floods in the Nelson-Churchill Watershed

NASA Astrophysics Data System (ADS)

Vieira, M. J. F.; Stadnyk, T. A.; Koenig, K. A.

2014-12-01

There is uncertainty surrounding the duration, magnitude and frequency of historical hydroclimatic extremes such as hydrologic droughts and floods prior to the observed record. In regions where paleoclimatic studies are less reliable, Global Climate Models (GCMs) can provide useful information about past hydroclimatic conditions. This study evaluates the use of Coupled Model Intercomparison Project 5 (CMIP5) GCMs to enhance the understanding of historical droughts and floods across the Canadian Prairie region in the Nelson-Churchill Watershed (NCW). The NCW is approximately 1.4 million km2 in size and drains into Hudson Bay in Northern Manitoba, Canada. One hundred years of observed hydrologic records show extended dry and wet periods in this region; however paleoclimatic studies suggest that longer, more severe droughts have occurred in the past. In Manitoba, where hydropower is the primary source of electricity, droughts are of particular interest as they are important for future resource planning. Twenty-three GCMs with daily runoff are evaluated using 16 metrics for skill in reproducing historic annual runoff patterns. A common 56-year historic period of 1950-2005 is used for this evaluation to capture wet and dry periods. GCM runoff is then routed at a grid resolution of 0.25° using the WATFLOOD hydrological model storage-routing algorithm to develop streamflow scenarios. Reservoir operation is naturalized and a consistent temperature scenario is used to determine ice-on and ice-off conditions. These streamflow simulations are compared with the historic record to remove bias using quantile mapping of empirical distribution functions. GCM runoff data from pre-industrial and future projection experiments are also bias corrected to obtain extended streamflow simulations. GCM streamflow simulations of more than 650 years include a stationary (pre-industrial) period and future periods forced by radiative forcing scenarios. Quantile mapping adjusts for magnitude only while maintaining the GCM's sequencing of events, allowing for the examination of differences in historic and future hydroclimatic extremes. These bias corrected streamflow scenarios provide an alternative to stochastic simulations for hydrologic data analysis and can aid future resource planning and environmental studies.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

Evaluating the Credibility of Transport Processes in the Global Modeling Initiative 3D Model Simulations of Ozone Recovery

NASA Technical Reports Server (NTRS)

Strahan, Susan E.; Douglass, Anne R.

2003-01-01

The Global Modeling Initiative has integrated two 35-year simulations of an ozone recovery scenario with an offline chemistry and transport model using two different meteorological inputs. Physically based diagnostics, derived from satellite and aircraft data sets, are described and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barrier formation in the subtropics and polar regions, and extratropical wave-driven transport. Some diagnostics are especially relevant to simulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of meteorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a general circulation model (GMI(sub GCM)) showed a very good residual circulation in the tropics and northern hemisphere. The simulation with input from a data assimilation system (GMI(sub DAS)) performed better in the midlatitudes than at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GMI(sub GCM) has greater fidelity throughout the stratosphere than the GMI(sub DAS).

Effects of Meteorological Variability on the Thermosphere-Ionosphere System during the Moderate Geomagnetic Disturbed January 2013 Period As Simulated By Time-GCM

NASA Astrophysics Data System (ADS)

Maute, A. I.; Hagan, M. E.; Richmond, A. D.; Liu, H.; Yudin, V. A.

2014-12-01

The ionosphere-thermosphere system is affected by solar and magnetospheric processes and by meteorological variability. Ionospheric observations of total electron content during the current solar cycle have shown that variability associated with meteorological forcing is important during solar minimum, and can have significant ionospheric effects during solar medium to maximum conditions. Numerical models can be used to study the comparative importance of geomagnetic and meterological forcing.This study focuses on the January 2013 Stratospheric Sudden Warming (SSW) period, which is associated with a very disturbed middle atmosphere as well as with moderately disturbed solar geomagntic conditions. We employ the NCAR Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM) with a nudging scheme using Whole-Atmosphere-Community-Climate-Model-Extended (WACCM-X)/Goddard Earth Observing System Model, Version 5 (GEOS5) results to simulate the effects of the meteorological and solar wind forcing on the upper atmosphere. The model results are evaluated by comparing with observations e.g., TEC, NmF2, ion drifts. We study the effect of the SSW on the wave spectrum, and the associated changes in the low latitude vertical drifts. These changes are compared to the impact of the moderate geomagnetic forcing on the TI-system during the January 2013 time period by conducting numerical experiments. We will present select highlights from our study and elude to the comparative importance of the forcing from above and below as simulated by the TIME-GCM.

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

NASA Technical Reports Server (NTRS)

Stanfield, Ryan E.; Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Del Genio, Anthony D.; Minnia, Patrick; Jiang, Jonathan H.

2014-01-01

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM(post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat- Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 gm22 lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

Evaluation of Transport in the Lower Tropical Stratosphere in a Global Chemistry and Transport Model

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Schoeberl, Mark R.; Rood, Richard B.; Pawson, Steven

2002-01-01

A general circulation model (GCM) relies on various physical parameterizations and provides a solution to the atmospheric equations of motion. A data assimilation system (DAS) combines information from observations with a GCM forecast and produces analyzed meteorological fields that represent the observed atmospheric state. An off-line chemistry and transport model (CTM) can use winds and temperatures from a either a GCM or a DAS. The latter application is in common usage for interpretation of observations from various platforms under the assumption that the DAS transport represents the actual atmospheric transport. Here we compare the transport produced by a DAS with that produced by the particular GCM that is combined with observations to produce the analyzed fields. We focus on transport in the tropics and middle latitudes by comparing the age-of-air inferred from observations of SF6 and CO2 with the age-of-air calculated using GCM fields and DAS fields. We also compare observations of ozone, total reactive nitrogen, and methane with results from the two simulations. These comparisons show that DAS fields produce rapid upward tropical transport and excessive mixing between the tropics and middle latitudes. The unrealistic transport produced by the DAS fields may be due to implicit forcing that is required by the assimilation process when there is bias between the GCM forecast and observations that are combined to produce the analyzed fields. For example, the GCM does not produce a quasi-biennial oscillation (QBO). The QBO is present in the analyzed fields because it is present in the observations, and systematic implicit forcing is required by the DAS. Any systematic bias between observations and the GCM forecast used to produce the DAS analysis is likely to corrupt the transport produced by the analyzed fields. Evaluation of transport in the lower tropical stratosphere in a global chemistry and transport model.

On the climate model simulation of Indian monsoon low pressure systems and the effect of remote disturbances and systematic biases

NASA Astrophysics Data System (ADS)

Levine, Richard C.; Martin, Gill M.

2018-06-01

Monsoon low pressure systems (LPS) are synoptic-scale systems forming over the Indian monsoon trough region, contributing substantially to seasonal mean summer monsoon rainfall there. Many current global climate models (GCMs), including the Met Office Unified Model (MetUM), show deficient rainfall in this region, much of which has previously been attributed to remote systematic biases such as excessive equatorial Indian Ocean (EIO) convection, while also substantially under-representing LPS and associated rainfall as they travel westwards across India. Here the sources and sensitivities of LPS to local, remote and short-timescale forcing are examined, in order to understand the poor representation in GCMs. An LPS tracking method is presented using TRACK feature tracking software for comparison between re-analysis data-sets, MetUM GCM and regional climate model (RCM) simulations. RCM simulations, at similar horizontal resolution to the GCM and forced with re-analysis data at the lateral boundaries, are carried out with different domains to examine the effects of remote biases. The results suggest that remote biases contribute significantly to the poor simulation of LPS in the GCM. As these remote systematic biases are common amongst many current GCMs, it is likely that GCMs are intrinsically capable of representing LPS, even at relatively low resolution. The main problem areas are time-mean excessive EIO convection and poor representation of precursor disturbances transmitted from the Western Pacific. The important contribution of the latter is established using RCM simulations forced by climatological 6-hourly lateral boundary conditions, which also highlight the role of LPS in moving rainfall from steep orography towards Central India.

Parameterization of turbulence and the planetary boundary layer in the GLA Fourth Order GCM

NASA Technical Reports Server (NTRS)

Helfand, H. M.

1985-01-01

A new scheme has been developed to model the planetary boundary layer in the GLAS Fourth Order GCM through explicit resolution of its vertical structure into two or more vertical layers. This involves packing the lowest layers of the GCM close to the ground and developing new parameterization schemes that can express the turbulent vertical fluxes of heat, momentum and moisture at the earth's surface and between the layers that are contained with the PBL region. Offline experiments indicate that the combination of the modified level 2.5 second-order turbulent closure scheme and the 'extended surface layer' similarity scheme should work well to simulate the behavior of the turbulent PBL even at the coarsest vertical resolution with which such schemes will conceivably be used in the GLA Fourth Order GCM.

Improving the Amazonian Hydrologic Cycle in a Coupled Land-Atmosphere, Single Column Model

NASA Astrophysics Data System (ADS)

Harper, A. B.; Denning, S.; Baker, I.; Prihodko, L.; Branson, M.

2006-12-01

We have coupled a land-surface model, the Simple Biosphere Model (SiB3), to a single column of the Colorado State University General Circulation Model (CSU-GCM) in the Amazon River Basin. This is a preliminary step in the broader goal of improved simulation of Basin-wide hydrology. A previous version of the coupled model (SiB2) showed drought and catastrophic dieback of the Amazon rain forest. SiB3 includes updated soil hydrology and root physiology. Our test area for the coupled single column model is near Santarem, Brazil, where measurements from the km 83 flux tower in the Tapajos National Forest can be used to evaluate model output. The model was run for 2001 using NCEP2 Reanalysis as driver data. Preliminary results show that the updated biosphere model coupled to the GCM produces improved simulations of the seasonal cycle of surface water balance and precipitation. Comparisons of the diurnal and seasonal cycles of surface fluxes are also being made.

Signal detection in global mean temperatures after "Paris": an uncertainty and sensitivity analysis

NASA Astrophysics Data System (ADS)

Visser, Hans; Dangendorf, Sönke; van Vuuren, Detlef P.; Bregman, Bram; Petersen, Arthur C.

2018-02-01

In December 2015, 195 countries agreed in Paris to hold the increase in global mean surface temperature (GMST) well below 2.0 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C. Since large financial flows will be needed to keep GMSTs below these targets, it is important to know how GMST has progressed since pre-industrial times. However, the Paris Agreement is not conclusive as regards methods to calculate it. Should trend progression be deduced from GCM simulations or from instrumental records by (statistical) trend methods? Which simulations or GMST datasets should be chosen, and which trend models? What is pre-industrial and, finally, are the Paris targets formulated for total warming, originating from both natural and anthropogenic forcing, or do they refer to anthropogenic warming only? To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets and model choices have been varied. For all cases we evaluated trend progression along with uncertainty information. To do so, we analysed four trend approaches and applied these to the five leading observational GMST products. We find GMST progression to be largely independent of various trend model approaches. However, GMST progression is significantly influenced by the choice of GMST datasets. Uncertainties due to natural variability are largest in size. As a parallel path, we calculated GMST progression from an ensemble of 42 GCM simulations. Mean progression derived from GCM-based GMSTs appears to lie in the range of trend-dataset combinations. A difference between both approaches appears to be the width of uncertainty bands: GCM simulations show a much wider spread. Finally, we discuss various choices for pre-industrial baselines and the role of warming definitions. Based on these findings we propose an estimate for signal progression in GMSTs since pre-industrial.

On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

2016-04-01

Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.

1998-01-01

A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.

Modelling the climate and ice sheets of the mid-Pliocene warm period: a test of model dependency

NASA Astrophysics Data System (ADS)

Dolan, Aisling; Haywood, Alan; Lunt, Daniel; Hill, Daniel

2010-05-01

The mid-Pliocene warm period (MPWP; c. 3.0 - 3.3 million years ago) has been the subject of a large number of published studies during the last decade. It is an interval in Earth history, where conditions were similar to those predicted by climate models for the end of the 21st Century. Not only is it important to increase our understanding of the climate dynamics in a warmer world, it is also important to determine exactly how well numerical models can retrodict a climate significantly different from the present day, in order to have confidence in them for predicting the future climate. Previous General Circulation Model (GCM) simulations have indicated that MPWP mean annual surface temperatures were on average 2 to 3˚C warmer than the pre-industrial era. Coastal stratigraphy and benthic oxygen isotope records suggest that terrestrial ice volumes were reduced when compared to modern. Ice sheet modelling studies have supported this decrease in cryospheric extent. Generally speaking, both climate and ice sheet modelling studies have only used results from one numerical model when simulating the climate of the MPWP. However, recent projects such as PMIP (the Palaeoclimate Modelling Intercomparison Project) have emphasised the need to explore the dependency of past climate predictions on the specific climate model which is used. Here we present a comparison of MPWP climatologies produced by three atmosphere only GCMs from the Goddard Institute of Space Studies (GISS), the National Centre for Atmospheric Research (NCAR) and the Hadley Centre for Climate Prediction and Research (GCMAM3, CAM3-CLM and HadAM3 respectively). We focus on the ability of the GCMs to simulate climate fields needed to drive an offline ice sheet model to assess whether there are any significant differences between the climatologies. By taking the different temperature and precipitation predictions simulated by the three models as a forcing, and adopting GCM-specific topography, we have used the British Antarctic Survey thermomechanically coupled ice sheet model (BASISM) to test the extent to which equilibrium state ice sheets in the Northern Hemisphere are GCM dependent. Initial results which do not use GCM-specific topography suggest that employing different GCM climatologies with only small differences in surface air temperature and precipitation has a dramatic effect on the resultant Greenland ice sheet, where the end-member ice sheets vary from near modern to almost zero ice volume. As an extension of this analysis, we will also present results using a second ice sheet model (Glimmer), with a view to testing the degree to which end-member ice sheets are ice sheet model dependent, something which has not previously been addressed. Initially, BASISM and Glimmer will be internally optimised for performance, but we will also present a comparison where BASISM will be configured to the Glimmer model setup in a further test of ice sheet model dependency.

Evaluating the utility of dynamical downscaling in agricultural impacts projections

PubMed Central

Glotter, Michael; Elliott, Joshua; McInerney, David; Best, Neil; Foster, Ian; Moyer, Elisabeth J.

2014-01-01

Interest in estimating the potential socioeconomic costs of climate change has led to the increasing use of dynamical downscaling—nested modeling in which regional climate models (RCMs) are driven with general circulation model (GCM) output—to produce fine-spatial-scale climate projections for impacts assessments. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield, one of the greatest concerns under climate change. Our results suggest that it does not. We simulate US maize yields under current and future CO2 concentrations with the widely used Decision Support System for Agrotechnology Transfer crop model, driven by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs. We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indistinguishable in all scenarios (<10% discrepancy, equivalent to error from observations). Although RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the benefits for impacts assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computational demands. Progress on fidelity of yield projections may benefit more from continuing efforts to understand and minimize systematic error in underlying climate projections. PMID:24872455

Circulation and rainfall climatology of a 10-year (1979 - 1988) integration with the Goddard Laboratory for atmospheres general circulation model

NASA Technical Reports Server (NTRS)

Kim, J.-H.; Sud, Y. C.

1993-01-01

A 10-year (1979-1988) integration of Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) under Atmospheric Model Intercomparison Project (AMIP) is analyzed and compared with observation. The first momentum fields of circulation variables and also hydrological variables including precipitation, evaporation, and soil moisture are presented. Our goals are (1) to produce a benchmark documentation of the GLA GCM for future model improvements; (2) to examine systematic errors between the simulated and the observed circulation, precipitation, and hydrologic cycle; (3) to examine the interannual variability of the simulated atmosphere and compare it with observation; and (4) to examine the ability of the model to capture the major climate anomalies in response to events such as El Nino and La Nina. The 10-year mean seasonal and annual simulated circulation is quite reasonable compared to the analyzed circulation, except the polar regions and area of high orography. Precipitation over tropics are quite well simulated, and the signal of El Nino/La Nina episodes can be easily identified. The time series of evaporation and soil moisture in the 12 biomes of the biosphere also show reasonable patterns compared to the estimated evaporation and soil moisture.

Can We Use Single-Column Models for Understanding the Boundary Layer Cloud-Climate Feedback?

NASA Astrophysics Data System (ADS)

Dal Gesso, S.; Neggers, R. A. J.

2018-02-01

This study explores how to drive Single-Column Models (SCMs) with existing data sets of General Circulation Model (GCM) outputs, with the aim of studying the boundary layer cloud response to climate change in the marine subtropical trade wind regime. The EC-EARTH SCM is driven with the large-scale tendencies and boundary conditions as derived from two different data sets, consisting of high-frequency outputs of GCM simulations. SCM simulations are performed near Barbados Cloud Observatory in the dry season (January-April), when fair-weather cumulus is the dominant low-cloud regime. This climate regime is characterized by a near equilibrium in the free troposphere between the long-wave radiative cooling and the large-scale advection of warm air. In the SCM, this equilibrium is ensured by scaling the monthly mean dynamical tendency of temperature and humidity such that it balances that of the model physics in the free troposphere. In this setup, the high-frequency variability in the forcing is maintained, and the boundary layer physics acts freely. This technique yields representative cloud amount and structure in the SCM for the current climate. Furthermore, the cloud response to a sea surface warming of 4 K as produced by the SCM is consistent with that of the forcing GCM.

Equatorial waves in a stratospheric GCM: Effects of vertical resolution. [GCM (general circulation model)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boville, B.A.; Randel, W.J.

1992-05-01

Equatorially trapped wave modes, such as Kelvin and mixed Rossby-gravity waves, are believed to play a crucial role in forcing the quasi-biennial oscillation (QBO) of the lower tropical stratosphere. This study examines the ability of a general circulation model (GCM) to simulate these waves and investigates the changes in the wave properties as a function of the vertical resolution of the model. The simulations produce a stratopause-level semiannual oscillation but not a QBO. An unfortunate property of the equatorially trapped waves is that they tend to have small vertical wavelengths ([le] 15 km). Some of the waves, believed to bemore » important in forcing the QBO, have wavelengths as short as 4 km. The short vertical wavelengths pose a stringent computational requirement for numerical models whose vertical grid spacing is typically chosen based on the requirements for simulating extratropical Rossby waves (which have much longer vertical wavelengths). This study examines the dependence of the equatorial wave simulation of vertical resolution using three experiments with vertical grid spacings of approximately 2.8, 1.4, and 0.7 km. Several Kelvin, mixed Rossby-gravity, and 0.7 km. Several Kelvin, mixed Rossby-gravity, and inertio-gravity waves are identified in the simulations. At high vertical resolution, the simulated waves are shown to correspond fairly well to the available observations. The properties of the relatively slow (and vertically short) waves believed to play a role in the QBO vary significantly with vertical resolution. Vertical grid spacings of about 1 km or less appear to be required to represent these waves adequately. The simulated wave amplitudes are at least as large as observed, and the waves are absorbed in the lower stratosphere, as required in order to force the QBO. However, the EP flux divergence associated with the waves is not sufficient to explain the zonal flow accelerations found in the QBO. 39 refs., 17 figs., 1 tab.« less

Stationary Waves of the Ice Age Climate.

NASA Astrophysics Data System (ADS)

Cook, Kerry H.; Held, Isaac M.

1988-08-01

A linearized, steady state, primitive equation model is used to simulate the climatological zonal asymmetries (stationary eddies) in the wind and temperature fields of the 18 000 YBP climate during winter. We compare these results with the eddies simulated in the ice age experiments of Broccoli and Manabe, who used CLIMAP boundary conditions and reduced atmospheric CO2 in an atmospheric general circulation model (GCM) coupled with a static mixed layer ocean model. The agreement between the models is good, indicating that the linear model can be used to evaluate the relative influences of orography, diabatic heating, and transient eddy heat and momentum transports in generating stationary waves. We find that orographic forcing dominates in the ice age climate. The mechanical influence of the continental ice sheets on the atmosphere is responsible for most of the changes between the present day and ice age stationary eddies. This concept of the ice age climate is complicated by the sensitivity of the stationary eddies to the large increase in the magnitude of the zonal mean meridional temperature gradient simulated in the ice age GCM.

Sensitivity simulations of superparameterised convection in a general circulation model

NASA Astrophysics Data System (ADS)

Rybka, Harald; Tost, Holger

2015-04-01

Cloud Resolving Models (CRMs) covering a horizontal grid spacing from a few hundred meters up to a few kilometers have been used to explicitly resolve small-scale and mesoscale processes. Special attention has been paid to realistically represent cloud dynamics and cloud microphysics involving cloud droplets, ice crystals, graupel and aerosols. The entire variety of physical processes on the small-scale interacts with the larger-scale circulation and has to be parameterised on the coarse grid of a general circulation model (GCM). Since more than a decade an approach to connect these two types of models which act on different scales has been developed to resolve cloud processes and their interactions with the large-scale flow. The concept is to use an ensemble of CRM grid cells in a 2D or 3D configuration in each grid cell of the GCM to explicitly represent small-scale processes avoiding the use of convection and large-scale cloud parameterisations which are a major source for uncertainties regarding clouds. The idea is commonly known as superparameterisation or cloud-resolving convection parameterisation. This study presents different simulations of an adapted Earth System Model (ESM) connected to a CRM which acts as a superparameterisation. Simulations have been performed with the ECHAM/MESSy atmospheric chemistry (EMAC) model comparing conventional GCM runs (including convection and large-scale cloud parameterisations) with the improved superparameterised EMAC (SP-EMAC) modeling one year with prescribed sea surface temperatures and sea ice content. The sensitivity of atmospheric temperature, precipiation patterns, cloud amount and types is observed changing the embedded CRM represenation (orientation, width, no. of CRM cells, 2D vs. 3D). Additionally, we also evaluate the radiation balance with the new model configuration, and systematically analyse the impact of tunable parameters on the radiation budget and hydrological cycle. Furthermore, the subgrid variability (individual CRM cell output) is analysed in order to illustrate the importance of a highly varying atmospheric structure inside a single GCM grid box. Finally, the convective transport of Radon is observed comparing different transport procedures and their influence on the vertical tracer distribution.

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe

NASA Astrophysics Data System (ADS)

Donatelli, Marcello; Srivastava, Amit Kumar; Duveiller, Gregory; Niemeyer, Stefan; Fumagalli, Davide

2015-07-01

This study presents an estimate of the effects of climate variables and CO2 on three major crops, namely wheat, rapeseed and sunflower, in EU27 Member States. We also investigated some technical adaptation options which could offset climate change impacts. The time-slices 2000, 2020 and 2030 were chosen to represent the baseline and future climate, respectively. Furthermore, two realizations within the A1B emission scenario proposed by the Special Report on Emissions Scenarios (SRES), from the ECHAM5 and HadCM3 GCM, were selected. A time series of 30 years for each GCM and time slice were used as input weather data for simulation. The time series were generated with a stochastic weather generator trained over GCM-RCM time series (downscaled simulations from the ENSEMBLES project which were statistically bias-corrected prior to the use of the weather generator). GCM-RCM simulations differed primarily for rainfall patterns across Europe, whereas the temperature increase was similar in the time horizons considered. Simulations based on the model CropSyst v. 3 were used to estimate crop responses; CropSyst was re-implemented in the modelling framework BioMA. The results presented in this paper refer to abstraction of crop growth with respect to its production system, and consider growth as limited by weather and soil water. How crop growth responds to CO2 concentrations; pests, diseases, and nutrients limitations were not accounted for in simulations. The results show primarily that different realization of the emission scenario lead to noticeably different crop performance projections in the same time slice. Simple adaptation techniques such as changing sowing dates and the use of different varieties, the latter in terms of duration of the crop cycle, may be effective in alleviating the adverse effects of climate change in most areas, although response to best adaptation (within the techniques tested) differed across crops. Although a negative impact of climate scenarios is evident in most areas, the combination of rainfall patterns and increased photosynthesis efficiency due to CO2 concentrations showed possible improvements of production patterns in some areas, including Southern Europe. The uncertainty deriving from GCM realizations with respect to rainfall suggests that articulated and detailed testing of adaptation techniques would be redundant. Using ensemble simulations would allow for the identification of areas where adaptation, like those simulated, may be run autonomously by farmers, hence not requiring specific intervention in terms of support policies.

Explicit simulation of a midlatitude Mesoscale Convective System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexander, G.D.; Cotton, W.R.

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation andmore » testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.« less

On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Storelvmo, T.

2015-12-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

AIRS-Observed Interrelationships of Anomaly Time-Series of Moist Process-Related Parameters and Inferred Feedback Values on Various Spatial Scales

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel; Iredell, Lena

2011-01-01

In the beginning, a good measure of a GMCs performance was their ability to simulate the observed mean seasonal cycle. That is, a reasonable simulation of the means (i.e., small biases) and standard deviations of TODAY?S climate would suffice. Here, we argue that coupled GCM (CG CM for short) simulations of FUTURE climates should be evaluated in much more detail, both spatially and temporally. Arguably, it is not the bias, but rather the reliability of the model-generated anomaly time-series, even down to the [C]GCM grid-scale, which really matter. This statement is underlined by the social need to address potential REGIONAL climate variability, and climate drifts/changes in a manner suitable for policy decisions.

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

NASA Technical Reports Server (NTRS)

Elsaesser, Greg; Del Genio, Anthony

2015-01-01

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high latitude ice IWP that decreased by 50 relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by 15 in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of 2. This was largely driven by IWC in deep-convecting regions of the tropics.Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter.GCM simulations with the improved convective parameterization yield a 50 decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

NASA Astrophysics Data System (ADS)

Elsaesser, G.; Del Genio, A. D.

2015-12-01

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high-latitude ice IWP that decreased by ~50% relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by ~15% in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (~200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of ~2. This was largely driven by IWC in deep-convecting regions of the tropics. Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter. GCM simulations with the improved convective parameterization yield a ~50% decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

Observational and Modeling Studies of Radiative, Chemical, and Dynamical Interactions in the Earth''s Atmosphere

NASA Technical Reports Server (NTRS)

Salby, Murry

1998-01-01

A 3-dimensional model was developed to support mechanistic studies. The model solves the global primitive equations in isentropic coordinates, which directly characterize diabatic processes forcing the Brewer-Dobson circulation of the middle atmosphere. It's numerical formulation is based on Hough harmonics, which partition horizontal motion into its rotational and divergent components. These computational features, along with others, enable 3D integrations to be performed practically on RISC computer architecture, on which they can be iterated to support mechanistic studies. The model conserves potential vorticity quite accurately under adiabatic conditions. Forced by observed tropospheric structure, in which integrations are anchored, the model generates a diabatic circulation that is consistent with satellite observations of tracer behavior and diabatic cooling rates. The model includes a basic but fairly complete treatment of gas-phase photochemistry that represents some 20 chemical species and 50 governing reactions with diurnally-varying shortwave absorption. The model thus provides a reliable framework to study transport and underlying diabatic processes, which can then be compared against chemical and dynamical structure observed and in GCM integrations. Integrations with the Langley GCM were performed to diagnose feedback between simulated convection and the tropical circulation. These were studied in relation to tropospheric properties controlling moisture convergence and environmental conditions supporting deep convection, for comparison against mechanistic integrations of wave CISK that successfully reproduce the Madden-Julian Oscillation (MJO) of the tropical circulation. These comparisons were aimed at identifying and ultimately improving aspects of the convective simulation, with the objective of recovering a successful simulation of the MJO in the Langley GCM, behavior that should be important to budgets of upper-tropospheric water vapor and chemical species.

Middle atmosphere dynamical sources of the semiannual oscillation in the thermosphere and ionosphere

NASA Astrophysics Data System (ADS)

Jones, M.; Emmert, J. T.; Drob, D. P.; Siskind, D. E.

2017-01-01

The strong global semiannual oscillation (SAO) in thermospheric density has been observed for five decades, but definitive knowledge of its source has been elusive. We use the National Center of Atmospheric Research thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) to study how middle atmospheric dynamics generate the SAO in the thermosphere-ionosphere (T-I). The "standard" TIME-GCM simulates, from first principles, SAOs in thermospheric mass density and ionospheric total electron content that agree well with observed climatological variations. Diagnosis of the globally averaged continuity equation for atomic oxygen ([O]) shows that the T-I SAO originates in the upper mesosphere, where an SAO in [O] is forced by nonlinear, resolved-scale variations in the advective, net tidal, and diffusive transport of O. Contrary to earlier hypotheses, TIME-GCM simulations demonstrate that intra-annually varying eddy diffusion by breaking gravity waves may not be the primary driver of the T-I SAO: A pronounced SAO is produced without parameterized gravity waves.

Sensitivity study of heavy precipitation in Limited Area Model climate simulations: influence of the size of the domain and the use of the spectral nudging technique

NASA Astrophysics Data System (ADS)

Colin, Jeanne; Déqué, Michel; Radu, Raluca; Somot, Samuel

2010-10-01

We assess the impact of two sources of uncertainties in a limited area model (LAM) on the representation of intense precipitation: the size of the domain of integration and the use of the spectral nudging technique (driving of the large-scale within the domain of integration). We work in a perfect-model approach where the LAM is driven by a general circulation model (GCM) run at the same resolution and sharing the same physics and dynamics as the LAM. A set of three 50 km resolution simulations run over Western Europe with the LAM ALADIN-Climate and the GCM ARPEGE-Climate are performed to address this issue. Results are consistent with previous studies regarding the seasonal-mean fields. Furthermore, they show that neither the use of the spectral nudging nor the choice of a small domain are detrimental to the modelling of heavy precipitation in the present experiment.

Evaluating the Credibility of Transport Processes in Simulations of Ozone Recovery using the Global Modeling Initiative Three-dimensional Model

NASA Technical Reports Server (NTRS)

Strahan, Susan E.; Douglass, Anne R.

2004-01-01

The Global Modeling Initiative (GMI) has integrated two 36-year simulations of an ozone recovery scenario with an offline chemistry and tra nsport model using two different meteorological inputs. Physically ba sed diagnostics, derived from satellite and aircraft data sets, are d escribed and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barri er formation in the subtropics and polar regions, and extratropical w ave-driven transport. Some diagnostics are especially relevant to sim ulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The global temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of me teorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a g eneral circulation model (GMI(GCM)) showed a very good residual circulation in the tropics and Northern Hemisphere. The simulation with inp ut from a data assimilation system (GMI(DAS)) performed better in the midlatitudes than it did at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GML(GCM) has greater fidelity throughout the stratosphere tha n it does in the GMI(DAS)

A bias-corrected CMIP5 dataset for Africa using the CDF-t method - a contribution to agricultural impact studies

NASA Astrophysics Data System (ADS)

Moise Famien, Adjoua; Janicot, Serge; Delfin Ochou, Abe; Vrac, Mathieu; Defrance, Dimitri; Sultan, Benjamin; Noël, Thomas

2018-03-01

The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950-2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

The role of shallow convection in promoting the northward propagation of boreal summer intraseasonal oscillation

NASA Astrophysics Data System (ADS)

Liu, Fei; Zhao, Jiuwei; Fu, Xiouhua; Huang, Gang

2018-02-01

By conducting idealized experiments in a general circulation model (GCM) and in a toy theoretical model, we test the hypothesis that shallow convection (SC) is responsible for explaining why the boreal summer intraseasonal oscillation (BSISO) prefers propagating northward. Two simulations are performed using ECHAM4, with the control run using a standard detrainment rate of SC and the sensitivity run turning off the detrainment rate of SC. These two simulations display dramatically different BSISO characteristics. The control run simulates the realistic northward propagation (NP) of the BSISO, while the sensitivity run with little SC only simulates stationary signals. In the sensitivity run, the meridional asymmetries of vorticity and humidity fields are simulated under the monsoon vertical wind shear (VWS); thus, the frictional convergence can be excited to the north of the BSISO. However, the lack of SC makes the lower and middle troposphere very dry, which prohibits further development of deeper convection. A theoretical BSISO model is also constructed, and the result shows that SC is a key to convey the asymmetric vorticity effect to induce the BSISO to move northward. Thus, both the GCM and theoretical model results demonstrate the importance of SC in promoting the NP of the BSISO.

Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing.

PubMed

Feng, X; Liu, G; Chen, J M; Chen, M; Liu, J; Ju, W M; Sun, R; Zhou, W

2007-11-01

The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal-spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gCm(-2)yr(-1), respectively; the total GPP and mean GPP were 4.418 GtC and 465 gCm(-2)yr(-1); and the total RA and mean RA were 2.227 GtC and 234 gCm(-2)yr(-1), respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.

Convergence of methods for coupling of microscopic and mesoscopic reaction-diffusion simulations

NASA Astrophysics Data System (ADS)

Flegg, Mark B.; Hellander, Stefan; Erban, Radek

2015-05-01

In this paper, three multiscale methods for coupling of mesoscopic (compartment-based) and microscopic (molecular-based) stochastic reaction-diffusion simulations are investigated. Two of the three methods that will be discussed in detail have been previously reported in the literature; the two-regime method (TRM) and the compartment-placement method (CPM). The third method that is introduced and analysed in this paper is called the ghost cell method (GCM), since it works by constructing a "ghost cell" in which molecules can disappear and jump into the compartment-based simulation. Presented is a comparison of sources of error. The convergent properties of this error are studied as the time step Δt (for updating the molecular-based part of the model) approaches zero. It is found that the error behaviour depends on another fundamental computational parameter h, the compartment size in the mesoscopic part of the model. Two important limiting cases, which appear in applications, are considered: Δt → 0 and h is fixed; Δt → 0 and h → 0 such that √{ Δt } / h is fixed. The error for previously developed approaches (the TRM and CPM) converges to zero only in the limiting case (ii), but not in case (i). It is shown that the error of the GCM converges in the limiting case (i). Thus the GCM is superior to previous coupling techniques if the mesoscopic description is much coarser than the microscopic part of the model.

Evaluating the feasibility of global climate models to simulate cloud cover effect controlled by Marine Stratocumulus regime transitions

NASA Astrophysics Data System (ADS)

Goren, Tom; Muelmenstaedt, Johannes; Rosenfeld, Daniel; Quaas, Johannes

2017-04-01

Marine stratocumulus clouds (MSC) occur in two main cloud regimes of open and closed cells that differ significantly by their cloud cover. Closed cells gradually get cleansed of high CCN concentrations in a process that involves initiation of drizzle that breaks the full cloud cover into open cells. The drizzle creates downdrafts that organize the convection along converging gust fronts, which in turn produce stronger updrafts that can sustain more cloud water that compensates the depletion of the cloud water by the rain. In addition, having stronger updrafts allow the clouds to grow relatively deep before rain starts to deplete its cloud water. Therefore, lower droplet concentrations and stronger rain would lead to lower cloud fraction, but not necessary also to lower liquid water path (LWP). The fundamental relationships between these key variables derived from global climate model (GCM) simulations are analyzed with respect to observations in order to determine whether the GCM parameterizations can represent well the governing physical mechanisms upon MSC regime transitions. The results are used to evaluate the feasibility of GCM's for estimating aerosol cloud-mediated radiative forcing upon MSC regime transitions, which are responsible for the largest aerosol cloud-mediated radiative forcing.

A post-new horizons global climate model of Pluto including the N2, CH4 and CO cycles

NASA Astrophysics Data System (ADS)

Forget, F.; Bertrand, T.; Vangvichith, M.; Leconte, J.; Millour, E.; Lellouch, E.

2017-05-01

We have built a new 3D Global Climate Model (GCM) to simulate Pluto as observed by New Horizons in 2015. All key processes are parametrized on the basis of theoretical equations, including atmospheric dynamics and transport, turbulence, radiative transfer, molecular conduction, as well as phases changes for N2, CH2 and CO. Pluto's climate and ice cycles are found to be very sensitive to model parameters and initial states. Nevertheless, a reference simulation is designed by running a fast, reduced version of the GCM with simplified atmospheric transport for 40,000 Earth years to initialize the surface ice distribution and sub-surface temperatures, from which a 28-Earth-year full GCM simulation is performed. Assuming a topographic depression in a Sputnik-planum (SP)-like crater on the anti-Charon hemisphere, a realistic Pluto is obtained, with most N2 and CO ices accumulated in the crater, methane frost covering both hemispheres except for the equatorial regions, and a surface pressure near 1.1 Pa in 2015 with an increase between 1988 and 2015, as reported from stellar occultations. Temperature profiles are in qualitative agreement with the observations. In particular, a cold atmospheric layer is obtained in the lowest kilometers above Sputnik Planum, as observed by New Horizons's REX experiment. It is shown to result from the combined effect of the topographic depression and N2 daytime sublimation. In the reference simulation with surface N2 ice exclusively present in Sputnik Planum, the global circulation is only forced by radiative heating gradients and remains relatively weak. Surface winds are locally induced by topography slopes and by N2 condensation and sublimation around Sputnik Planum. However, the circulation can be more intense depending on the exact distribution of surface N2 frost. This is illustrated in an alternative simulation with N2 condensing in the South Polar regions and N2 frost covering latitudes between 35°N and 48°N. A global condensation flow is then created, inducing strong surface winds everywhere, a prograde jet in the southern high latitudes, and an equatorial superrotation likely forced by barotropic instabilities in the southern jet. Using realistic parameters, the GCM predict atmospheric concentrations of CO and CH4 in good agreement with the observations. N2 and CO do not condense in the atmosphere, but CH4 ice clouds can form during daytime at low altitude near the regions covered by N2 ice (assuming that nucleation is efficient enough). This global climate model can be used to study many aspects of the Pluto environment. For instance, organic hazes are included in the GCM and analysed in a companion paper (Bertrand and Forget, Icarus, this issue).

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

Regional and seasonal estimates of fractional storm coverage based on station precipitation observations

NASA Technical Reports Server (NTRS)

Gong, Gavin; Entekhabi, Dara; Salvucci, Guido D.

1994-01-01

Simulated climates using numerical atmospheric general circulation models (GCMs) have been shown to be highly sensitive to the fraction of GCM grid area assumed to be wetted during rain events. The model hydrologic cycle and land-surface water and energy balance are influenced by the parameter bar-kappa, which is the dimensionless fractional wetted area for GCM grids. Hourly precipitation records for over 1700 precipitation stations within the contiguous United States are used to obtain observation-based estimates of fractional wetting that exhibit regional and seasonal variations. The spatial parameter bar-kappa is estimated from the temporal raingauge data using conditional probability relations. Monthly bar-kappa values are estimated for rectangular grid areas over the contiguous United States as defined by the Goddard Institute for Space Studies 4 deg x 5 deg GCM. A bias in the estimates is evident due to the unavoidably sparse raingauge network density, which causes some storms to go undetected by the network. This bias is corrected by deriving the probability of a storm escaping detection by the network. A Monte Carlo simulation study is also conducted that consists of synthetically generated storm arrivals over an artificial grid area. It is used to confirm the bar-kappa estimation procedure and to test the nature of the bias and its correction. These monthly fractional wetting estimates, based on the analysis of station precipitation data, provide an observational basis for assigning the influential parameter bar-kappa in GCM land-surface hydrology parameterizations.

The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.; Rind, David; Healy, Richard J.; Martinson, Douglas G.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment

NASA Technical Reports Server (NTRS)

Skiles, J. W.

1995-01-01

Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.

A senstitivity study of the ground hydrologic model using data generated by an atmospheric general circulation model. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sun, S. F.

1985-01-01

The Ground Hydrologic Model (GHM) developed for use in an atmospheric general circulation model (GCM) has been refined. A series of sensitivity studies of the new version of the GHM were conducted for the purpose of understanding the role played by various physical parameters in the GHM. The following refinements have been made: (1) the GHM is coupled directly with the planetary boundary layer (PBL); (2) a bulk vegetation layer is added with a more realistic large-scale parameterization; and (3) the infiltration rate is modified. This version GHM has been tested using input data derived from a GCM simulation run for eight North America regions for 45 days. The results are compared with those of the resident GHM in the GCM. The daily average of grid surface temperatures from both models agree reasonably well in phase and magnitude. However, large difference exists in one or two regions on some days. The daily average evapotranspiration is in general 10 to 30% less than the corresponding value given by the resident GHM.

[Numeric simulation of functional remodeling of the anterior alveolar bone].

PubMed

Wang, Wei-feng; Xin, Hai-tao; Zang, Shun-lai; Ding, Jie

2012-04-01

To study the remodeling of the anterior alveolar bone with parodontium under physiology loading using finite element method (FEM) and theory of bone remodeling. A FEM model of the maxillary central incisor with parodontium was established, and the change of bone density during the remodeling of alveolar bone was investigated under physiology loading (60 - 150 N) based on the theory of bone remodeling about strain energy density (SED). The finite element analysis software Abaqus user material subroutine (UMAT) were used. With the increase of physiology loading, the pressure stress on the buccal cervical margin increased gradually while the density was decreased gradually. The cortical bone was lower than its initial density 1.74 g/cm(3), which was 1.74 - 1.63 g/cm(3). The density of cancellous bone was 0.90 - 0.77 g/cm(3), which was lower than its intial density 0.90 g/cm(3). The lingual cervical margin was under tensile stress which also increased with loading, the density had no significant change. When the achieve to 120 N, the density of cortical bone was 1.74 - 1.73 g/cm(3). No significant change was found in the cancellous bone. The simulation of the perodontium remodeling is achieved and proved to be effective by the relevant research based on the method of the study. And the result will be helpful to form the basis of analysis bone remodeling process and predict the results in the clinical work.

GCM simulations of Titan's middle and lower atmosphere and comparison to observations

NASA Astrophysics Data System (ADS)

Lora, Juan M.; Lunine, Jonathan I.; Russell, Joellen L.

2015-04-01

Simulation results are presented from a new general circulation model (GCM) of Titan, the Titan Atmospheric Model (TAM), which couples the Flexible Modeling System (FMS) spectral dynamical core to a suite of external/sub-grid-scale physics. These include a new non-gray radiative transfer module that takes advantage of recent data from Cassini-Huygens, large-scale condensation and quasi-equilibrium moist convection schemes, a surface model with "bucket" hydrology, and boundary layer turbulent diffusion. The model produces a realistic temperature structure from the surface to the lower mesosphere, including a stratopause, as well as satisfactory superrotation. The latter is shown to depend on the dynamical core's ability to build up angular momentum from surface torques. Simulated latitudinal temperature contrasts are adequate, compared to observations, and polar temperature anomalies agree with observations. In the lower atmosphere, the insolation distribution is shown to strongly impact turbulent fluxes, and surface heating is maximum at mid-latitudes. Surface liquids are unstable at mid- and low-latitudes, and quickly migrate poleward. The simulated humidity profile and distribution of surface temperatures, compared to observations, corroborate the prevalence of dry conditions at low latitudes. Polar cloud activity is well represented, though the observed mid-latitude clouds remain somewhat puzzling, and some formation alternatives are suggested.

Increasing the relevance of GCM simulations for Climate Services

NASA Astrophysics Data System (ADS)

Smith, L. A.; Suckling, E.

2012-12-01

The design and interpretation of model simulations for climate services differ significantly from experimental design for the advancement of the fundamental research on predictability that underpins it. Climate services consider the sources of best information available today; this calls for a frank evaluation of model skill in the face of statistical benchmarks defined by empirical models. The fact that Physical simulation models are thought to provide the only reliable method for extrapolating into conditions not previously observed has no bearing on whether or not today's simulation models outperform empirical models. Evidence on the length scales on which today's simulation models fail to outperform empirical benchmarks is presented; it is illustrated that this occurs even on global scales in decadal prediction. At all timescales considered thus far (as of July 2012), predictions based on simulation models are improved by blending with the output of statistical models. Blending is shown to be more interesting in the climate context than it is in the weather context, where blending with a history-based climatology is straightforward. As GCMs improve and as the Earth's climate moves further from that of the last century, the skill from simulation models and their relevance to climate services is expected to increase. Examples from both seasonal and decadal forecasting will be used to discuss a third approach that may increase the role of current GCMs more quickly. Specifically, aspects of the experimental design in previous hind cast experiments are shown to hinder the use of GCM simulations for climate services. Alternative designs are proposed. The value in revisiting Thompson's classic approach to improving weather forecasting in the fifties in the context of climate services is discussed.

Evaluation of Stratospheric Transport in New 3D Models Using the Global Modeling Initiative Grading Criteria

NASA Technical Reports Server (NTRS)

Strahan, Susan E.; Douglass, Anne R.; Einaudi, Franco (Technical Monitor)

2001-01-01

The Global Modeling Initiative (GMI) Team developed objective criteria for model evaluation in order to identify the best representation of the stratosphere. This work created a method to quantitatively and objectively discriminate between different models. In the original GMI study, 3 different meteorological data sets were used to run an offline chemistry and transport model (CTM). Observationally-based grading criteria were derived and applied to these simulations and various aspects of stratospheric transport were evaluated; grades were assigned. Here we report on the application of the GMI evaluation criteria to CTM simulations integrated with a new assimilated wind data set and a new general circulation model (GCM) wind data set. The Finite Volume Community Climate Model (FV-CCM) is a new GCM developed at Goddard which uses the NCAR CCM physics and the Lin and Rood advection scheme. The FV-Data Assimilation System (FV-DAS) is a new data assimilation system which uses the FV-CCM as its core model. One year CTM simulations of 2.5 degrees longitude by 2 degrees latitude resolution were run for each wind data set. We present the evaluation of temperature and annual transport cycles in the lower and middle stratosphere in the two new CTM simulations. We include an evaluation of high latitude transport which was not part of the original GMI criteria. Grades for the new simulations will be compared with those assigned during the original GMT evaluations and areas of improvement will be identified.

A framework for evaluating statistical downscaling performance under changing climatic conditions (Invited)

NASA Astrophysics Data System (ADS)

Dixon, K. W.; Balaji, V.; Lanzante, J.; Radhakrishnan, A.; Hayhoe, K.; Stoner, A. K.; Gaitan, C. F.

2013-12-01

Statistical downscaling (SD) methods may be viewed as generating a value-added product - a refinement of global climate model (GCM) output designed to add finer scale detail and to address GCM shortcomings via a process that gleans information from a combination of observations and GCM-simulated climate change responses. Making use of observational data sets and GCM simulations representing the same historical period, cross-validation techniques allow one to assess how well an SD method meets this goal. However, lacking observations of future, the extent to which a particular SD method's skill might degrade when applied to future climate projections cannot be assessed in the same manner. Here we illustrate and describe extensions to a 'perfect model' experimental design that seeks to quantify aspects of SD method performance both for a historical period (1979-2008) and for late 21st century climate projections. Examples highlighting cases in which downscaling performance deteriorates in future climate projections will be discussed. Also, results will be presented showing how synthetic datasets having known statistical properties may be used to further isolate factors responsible for degradations in SD method skill under changing climatic conditions. We will describe a set of input files used to conduct these analyses that are being made available to researchers who wish to utilize this experimental framework to evaluate SD methods they have developed. The gridded data sets cover a region centered on the contiguous 48 United States with a grid spacing of approximately 25km, have daily time resolution (e.g., maximum and minimum near-surface temperature and precipitation), and represent a total of 120 years of model simulations. This effort is consistent with the 2013 National Climate Predictions and Projections Platform Quantitative Evaluation of Downscaling Workshop goal of supporting a community approach to promote the informed use of downscaled climate projections.

Impact of the semidiurnal lunar tide on the midlatitude thermospheric wind and ionosphere during sudden stratosphere warmings

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Maute, A.

2015-12-01

Variability of the midlatitude ionosphere and thermosphere during the 2009 and 2013 sudden stratosphere warmings (SSWs) is investigated in the present study using a combination of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations and thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) simulations. Both the COSMIC observations and TIME-GCM simulations reveal perturbations in the F region peak height (hmF2) at Southern Hemisphere midlatitudes during SSW time periods. The perturbations are ˜20-30 km, which corresponds to 10-20% variability of the background mean hmF2. The TIME-GCM simulations and COSMIC observations of the hmF2 variability are in overall good agreement, and the simulations can thus be used to understand the physical processes responsible for the hmF2 variability. Through comparison of simulations with and without the migrating semidiurnal lunar tide (M2), we conclude that the midlatitude hmF2 variability is primarily driven by the propagation of the M2 into the thermosphere where it modulates the field-aligned neutral winds, which in turn raise and lower the F region peak height. Though there are subtle differences, the consistency of the behavior between the 2009 and 2013 SSWs suggests that variability in the Southern Hemisphere midlatitude ionosphere and thermosphere is a consistent feature of the SSW impact on the upper atmosphere.

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.

What can we learn from simulating Stratospheric Sudden Warming periods with the Thermosphere-Ionosphere-Mesosphere-Electrodynamics GCM?

NASA Astrophysics Data System (ADS)

Maute, A. I.; Hagan, M. E.; Roble, R. G.; Richmond, A. D.; Yudin, V. A.; Liu, H.; Goncharenko, L. P.; Burns, A. G.; Maruyama, N.

2013-12-01

The ionosphere-thermosphere system is not only influenced from geospace but also by meteorological variability. Ionospheric observations of GPS TEC during the current solar cycle have shown that the meteorological variability is important during solar minimum, but also can have significant ionospheric effects during solar medium to maximum conditions. Numerical models can be used to help understand the mechanisms that couple the lower and upper atmosphere over the solar cycle. Numerical modelers invoke different methods to simulate realistic, specified events of meteorological variability, e.g. specify the lower boundary forcing, nudge the middle atmosphere, data assimilation. To study the vertical coupling, we first need to assess the numerical models and the various methods used to simulate realistic events with respect to the dynamics of the mesosphere-lower thermosphere (MLT) region, the electrodynamics, and the ionosphere. This study focuses on Stratospheric Sudden Warming (SSW) periods since these are associated with a strongly disturbed middle atmosphere which can have effects up to the ionosphere. We will use the NCAR Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation model (TIME-GCM) to examine several recent SSW periods, e.g. 2009, 2012, and 2013. The SSW period in TIME-GCM will be specified in three different ways: 1. using reanalysis data to specify the lower boundary; 2. nudging the neutral atmosphere (temperature and winds) with the Whole Atmosphere Community Climate Model (WACCM)/Goddard Earth Observing System Model, Version 5 (GEOS-5) results; 3. nudging the background atmosphere (temperature and winds) with WACCM/GEOS5 results. The different forcing methods will be evaluated for the SSW periods with respect to the dynamics of the MLT region, the low latitude vertical drift changes, and the ionospheric effects for the different SSW periods. With the help of ionospheric data at different longitudinal sectors it will be possible to assess the simulations of the SSW periods and provide guidance for future studies.

Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers.

PubMed

Sundt-Hansen, L E; Hedger, R D; Ugedal, O; Diserud, O H; Finstad, A G; Sauterleute, J F; Tøfte, L; Alfredsen, K; Forseth, T

2018-08-01

Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon. Copyright © 2018. Published by Elsevier B.V.

Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

NASA Astrophysics Data System (ADS)

Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan

2018-05-01

A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

Parameterized Radiative Convective Equilibrium Across a Range of Domains: A Unifying Tool for General Circulation Models and High Resolution Models

NASA Astrophysics Data System (ADS)

Silvers, L. G.; Stevens, B. B.; Mauritsen, T.; Marco, G. A.

2015-12-01

The characteristics of clouds in General Circulation Models (GCMs) need to be constrained in a consistent manner with theory, observations, and high resolution models (HRMs). One way forward is to base improvements of parameterizations on high resolution studies which resolve more of the important dynamical motions and allow for less parameterizations. This is difficult because of the numerous differences between GCMs and HRMs, both technical and theoretical. Century long simulations at resolutions of 20-250 km on a global domain are typical of GCMs while HRMs often simulate hours at resolutions of 0.1km-5km on domains the size of a single GCM grid cell. The recently developed mode ICON provides a flexible framework which allows many of these difficulties to be overcome. This study uses the ICON model to compute SST perturbation simulations on multiple domains in a state of Radiative Convective Equilibrium (RCE) with parameterized convection. The domains used range from roughly the size of Texas to nearly half of Earth's surface area. All simulations use a doubly periodic domain with an effective distance between cell centers of 13 km and are integrated to a state of statistical stationarity. The primary analysis examines the mean characteristics of the cloud related fields and the feedback parameter of the simulations. It is shown that the simulated atmosphere of a GCM in RCE is sufficiently similar across a range of domain sizes to justify the use of RCE to study both a GCM and a HRM on the same domain with the goal of improved constraints on the parameterized clouds. The simulated atmospheres are comparable to what could be expected at midday in a typical region of Earth's tropics under calm conditions. In particular, the differences between the domains are smaller than differences which result from choosing different physics schemes. Significant convective organization is present on all domain sizes with a relatively high subsidence fraction. Notwithstanding the overall qualitative similarities of the simulations, quantitative differences lead to a surprisingly large sensitivity of the feedback parameter. This range of the feedback parameter is more than a factor of two and is similar to the range of feedbacks which were obtained by the CMIP5 models.

An examination of the effects of explicit cloud water in the UCLA GCM

NASA Technical Reports Server (NTRS)

Ose, Tomoaki

1993-01-01

The effect of explicit cloud water on the climate simulation by the University of California of Los Angeles GCM is investigated by adding the mixing ratios of cloud ice and cloud liquid water to the prognostic variables of the model. The detrained cloud ice and cloud liquid water are obtained by the microphysical calculation in the Arakawa-Schubert (1974) cumulus scheme. The results are compared with the observations concerned with cloudiness, planetary albedo, OLR, and the dependence of cloud water content on temperature.

The implementation and validation of improved land-surface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

1993-01-01

New land-surface hydrologic parameterizations are implemented into the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: 1) runoff and evapotranspiration functions that include the effects of subgrid-scale spatial variability and use physically based equations of hydrologic flux at the soil surface and 2) a realistic soil moisture diffusion scheme for the movement of water and root sink in the soil column. A one-dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three-dimensional GCM. Results of the final simulation with the GISS GCM and the new land-surface hydrology indicate that the runoff rate, especially in the tropics, is significantly improved. As a result, the remaining components of the heat and moisture balance show similar improvements when compared to observations. The validation of model results is carried from the large global (ocean and land-surface) scale to the zonal, continental, and finally the regional river basin scales.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Longitudinal Variations of Low-Latitude Gravity Waves and Their Impacts on the Ionosphere

NASA Astrophysics Data System (ADS)

Cullens, C. Y.; England, S.; Immel, T. J.

2014-12-01

The lower atmospheric forcing has important roles in the ionospheric variability. However, influences of lower atmospheric gravity waves on the ionospheric variability are still not clear due to the simplified gravity wave parameterizations and the limited knowledge of gravity wave distributions. In this study, we aim to study the longitudinal variations of gravity waves and their impacts of longitudinal variations of low-latitude gravity waves on the ionospheric variability. Our SABER results show that longitudinal variations of gravity waves at the lower boundary of TIME-GCM are the largest in June-August and January-February. We have implemented these low-latitude gravity wave variations from SABER instrument into TIME-GCM model. TIME-GCM simulation results of ionospheric responses to longitudinal variations of gravity waves and physical mechanisms will be discussed.

Supporting New Missions by Observing Simulation Experiments in WACCM-X/GEOS-5 and TIME-GCM: Initial Design, Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Yudin, V. A.; England, S.; Liu, H.; Solomon, S. C.; Immel, T. J.; Maute, A. I.; Burns, A. G.; Foster, B.; Wu, Q.; Goncharenko, L. P.

2013-12-01

We examine the capability of novel configurations of community models, WACCM-X and TIME-GCM, to support current and forthcoming space-borne missions to monitor the dynamics and composition of the Mesosphere-Thermosphere-Ionosphere (MTI) system. In these configurations the lower atmosphere of WACCM-X is constrained by operational analyses and/or short-term forecasts provided by the Goddard Earth Observing System (GEOS-5) of Global Modeling and Assimilation Office at NASA/GSFC. With the terrestrial weather of GEOS-5 and updated model physics the simulations in the MTI are capable to reproduce observed signatures of the perturbed wave dynamics and ion-neutral coupling during recent stratospheric warming events, short-term, annual and year-to-year variability of prevailing flows, planetary waves, tides, and composition. These 'terrestrial-weather' driven simulations with day-to-day variable solar and geomagnetic inputs can provide background state (first guess) and error statistics for the inverse algorithms of new NASA missions, ICON and GOLD at locations and time of observations in the MTI region. With two different viewing geometries (sun-synchronous and geostationary) of instruments, ICON and GOLD will provide complimentary global observations of temperature, winds and constituents to constrain the first-principle forecast models. This paper will discuss initial design of Observing Simulation Experiments (OSE) in WACCM-X/GEOS-5 and TIME-GCM. As recognized, OSE represent an excellent learning tool for designing and evaluating observing capabilities of novel sensors. They can guide on how to integrate/combine information from different instruments. The choice of assimilation schemes, forecast and observational errors will be discussed along with challenges and perspectives to constrain fast-varying tidal dynamics and their effects in models by combination of sun-synchronous and geostationary observations of ICON and GOLD. We will also discuss how correlative space-borne and ground-based observations can verify OSE results in the observable and non-observable regions of the MTI.

"The Effect of Alternative Representations of Lake ...

EPA Pesticide Factsheets

Lakes can play a significant role in regional climate, modulating inland extremes in temperature and enhancing precipitation. Representing these effects becomes more important as regional climate modeling (RCM) efforts focus on simulating smaller scales. When using the Weather Research and Forecasting (WRF) model to downscale future global climate model (GCM) projections into RCM simulations, model users typically must rely on the GCM to represent temperatures at all water points. However, GCMs have insufficient resolution to adequately represent even large inland lakes, such as the Great Lakes. Some interpolation methods, such as setting lake surface temperatures (LSTs) equal to the nearest water point, can result in inland lake temperatures being set from sea surface temperatures (SSTs) that are hundreds of km away. In other cases, a single point is tasked with representing multiple large, heterogeneous lakes. Similar consequences can result from interpolating ice from GCMs to inland lake points, resulting in lakes as large as Lake Superior freezing completely in the space of a single timestep. The use of a computationally-efficient inland lake model can improve RCM simulations where the input data is too coarse to adequately represent inland lake temperatures and ice (Gula and Peltier 2012). This study examines three scenarios under which ice and LSTs can be set within the WRF model when applied as an RCM to produce 2-year simulations at 12 km gri

Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global Climate Models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D.

2012-09-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon cycle range. These high end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real world climate sensitivity constraints which, if achieved, would lead to reductions on the uppper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present day observables and future changes while the large spread of future projected changes, highlights the ongoing need for such work.

Chemistry-Climate Interactions in the GISS GCM. Part 1; Tropospheric Chemistry Model Description and Evaluation

NASA Technical Reports Server (NTRS)

Shindell, Drew T.; Grenfell, J. Lee; Rind, David; Price, Colin; Grewe, Volker; Hansen, James E. (Technical Monitor)

2001-01-01

A tropospheric chemistry module has been developed for use within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to study interactions between chemistry and climate change. The model uses a simplified chemistry scheme based on CO-NOx-CH4 chemistry, and also includes a parameterization for emissions of isoprene, the most important non-methane hydrocarbon. The model reproduces present day annual cycles and mean distributions of key trace gases fairly well, based on extensive comparisons with available observations. Examining the simulated change between present day and pre-industrial conditions, we find that the model has a similar response to that seen in other simulations. It shows a 45% increase in the global tropospheric ozone burden, within the 25% - 57% range seen in other studies. Annual average zonal mean ozone increases by more than 125% at Northern Hemisphere middle latitudes near the surface. Comparison of model runs that allow the calculated ozone to interact with the GCM's radiation and meteorology with those that do not shows only minor differences for ozone. The common usage of ozone fields that are not calculated interactively seems to be adequate to simulate both the present day and the pre-industrial ozone distributions. However, use of coupled chemistry does alter the change in tropospheric oxidation capacity, enlarging the overall decrease in OH concentrations from the pre-industrial to the present by about 10% (-5.3% global annual average in uncoupled mode, -5.9% in coupled mode). This indicates that there may be systematic biases in the simulation of the pre-industrial to present day decrease in the oxidation capacity of the troposphere (though a 10% difference is well within the total uncertainty). Global annual average radiative forcing from pre-industrial to present day ozone change is 0.32 W/sq m. The forcing seems to be increased by about 10% when the chemistry is coupled to the GCM. Forcing values greater than 0.8 W/sq m are seen over large areas of the United States, Southern Europe, North Africa, the Middle East, Central Asia, and the Arctic. Radiative forcing is greater than 1.5 W/sq m over parts of these areas during Northern summer Though there are local differences, the radiative forcing is overall in good agreement with the results of other modeling studies in both its magnitude and spatial distribution, demonstrating that the simplified chemistry is adequate for climate studies.

Variations of total electron content during geomagnetic disturbances: A model/observation comparison

NASA Technical Reports Server (NTRS)

Roble, G. Lu X. Pi A. D. Richmond R. G.

1997-01-01

This paper studies the ionospheric response to major geomagnetic storm of October 18-19, 1995, using the thermosphere-ionosphere electrodynamic general circulation model (TIE-GCM) simulations and the global ionospheric maps (GIM) of total electron content (TEC) observations from the Global Positioning System (GPS) worldwide network.

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

1999-01-01

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Study of the thermospheric and ionospheric response to the 2009 sudden stratospheric warming using TIME-GCM and GSM TIP models: First results

NASA Astrophysics Data System (ADS)

Klimenko, M. V.; Klimenko, V. V.; Bessarab, F. S.; Korenkov, Yu N.; Liu, Hanli; Goncharenko, L. P.; Tolstikov, M. V.

2015-09-01

This paper presents a study of mesosphere and low thermosphere influence on ionospheric disturbances during 2009 major sudden stratospheric warming (SSW) event. This period was characterized by extremely low solar and geomagnetic activity. The study was performed using two first principal models: thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) and global self-consistent model of thermosphere, ionosphere, and protonosphere (GSM TIP). The stratospheric anomalies during SSW event were modeled by specifying the temperature and density perturbations at the lower boundary of the TIME-GCM (30 km altitude) according to data from European Centre for Medium-Range Weather Forecasts. Then TIME-GCM output at 80 km was used as lower boundary conditions for driving GSM TIP model runs. We compare models' results with ground-based ionospheric data at low latitudes obtained by GPS receivers in the American longitudinal sector. GSM TIP simulation predicts the occurrence of the quasi-wave vertical structure in neutral temperature disturbances at 80-200 km altitude, and the positive and negative disturbances in total electron content at low latitude during the 2009 SSW event. According to our model results the formation mechanisms of the low-latitude ionospheric response are the disturbances in the n(O)/n(N2) ratio and thermospheric wind. The change in zonal electric field is key mechanism driving the ionospheric response at low latitudes, but our model results do not completely reproduce the variability in zonal electric fields (vertical plasma drift) at low latitudes.

Changes in Extreme Events: from GCM Output to Social, Economic and Ecological Impacts

NASA Astrophysics Data System (ADS)

Tebaldi, C.; Meehl, G. A.

2006-12-01

Extreme events can deeply affect social and natural systems. The current generation of global climate model is producing information that can be directly used to characterize future changes in extreme events, and through a further step their impacts, despite their still relatively coarse resolution. It is important to define extreme indicators consistently with what we expect GCM to be able to represent reliably. We use two examples from our work, heat waves and frost days, that well describe different aspects of the analysis of extremes from GCM output. Frost days are "mild extremes" and their definition and computation is straightforward. GCMs can represent them accurately and display a strong consistent signal of change. The impacts of these changes will be extremely relevant for ecosystems and agriculture. Heat waves do not have a standard definition. On the basis of historical episodes we isolate characteristics that were responsible for the worst effects on human health, for example, and analyze these characteristics in model simulations, validating the model's historical simulations. The changes in these characteristics can then be easily translated in expected differential impacts on public health. Work in progress goes in the direction of better characterization of "heat waves" taking into account jointly a set of variables like maximum and minimum temperatures and humidity, better addressing the biological vulnerabilities of the populations at risk.

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, B. C.

1991-01-01

A new diagnostic tool is developed for examining relationships between the synoptic scale circulation and regional temperature distributions in GCMs. The 4 x 5 deg GISS GCM is shown to produce accurate simulations of the variance in the synoptic scale sea level pressure distribution over the U.S. An analysis of the observational data set from the National Meteorological Center (NMC) also shows a strong relationship between the synoptic circulation and grid point temperatures. This relationship is demonstrated by deriving transfer functions between a time-series of circulation parameters and temperatures at individual grid points. The circulation parameters are derived using rotated principal components analysis, and the temperature transfer functions are based on multivariate polynomial regression models. The application of these transfer functions to the GCM circulation indicates that there is considerable spatial bias present in the GCM temperature distributions. The transfer functions are also used to indicate the possible changes in U.S. regional temperatures that could result from differences in synoptic scale circulation between a 1XCO2 and a 2xCO2 climate, using a doubled CO2 version of the same GISS GCM.

Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario

NASA Astrophysics Data System (ADS)

Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John

2015-10-01

As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.

Bias-correction and Spatial Disaggregation for Climate Change Impact Assessments at a basin scale

NASA Astrophysics Data System (ADS)

Nyunt, Cho; Koike, Toshio; Yamamoto, Akio; Nemoto, Toshihoro; Kitsuregawa, Masaru

2013-04-01

Basin-scale climate change impact studies mainly rely on general circulation models (GCMs) comprising the related emission scenarios. Realistic and reliable data from GCM is crucial for national scale or basin scale impact and vulnerability assessments to build safety society under climate change. However, GCM fail to simulate regional climate features due to the imprecise parameterization schemes in atmospheric physics and coarse resolution scale. This study describes how to exclude some unsatisfactory GCMs with respect to focused basin, how to minimize the biases of GCM precipitation through statistical bias correction and how to cover spatial disaggregation scheme, a kind of downscaling, within in a basin. GCMs rejection is based on the regional climate features of seasonal evolution as a bench mark and mainly depends on spatial correlation and root mean square error of precipitation and atmospheric variables over the target region. Global Precipitation Climatology Project (GPCP) and Japanese 25-uear Reanalysis Project (JRA-25) are specified as references in figuring spatial pattern and error of GCM. Statistical bias-correction scheme comprises improvements of three main flaws of GCM precipitation such as low intensity drizzled rain days with no dry day, underestimation of heavy rainfall and inter-annual variability of local climate. Biases of heavy rainfall are conducted by generalized Pareto distribution (GPD) fitting over a peak over threshold series. Frequency of rain day error is fixed by rank order statistics and seasonal variation problem is solved by using a gamma distribution fitting in each month against insi-tu stations vs. corresponding GCM grids. By implementing the proposed bias-correction technique to all insi-tu stations and their respective GCM grid, an easy and effective downscaling process for impact studies at the basin scale is accomplished. The proposed method have been examined its applicability to some of the basins in various climate regions all over the world. The biases are controlled very well by using this scheme in all applied basins. After that, bias-corrected and downscaled GCM precipitation are ready to use for simulating the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) to analyse the stream flow change or water availability of a target basin under the climate change in near future. Furthermore, it can be investigated any inter-disciplinary studies such as drought, flood, food, health and so on.In summary, an effective and comprehensive statistical bias-correction method was established to fulfil the generative applicability of GCM scale to basin scale without difficulty. This gap filling also promotes the sound decision of river management in the basin with more reliable information to build the resilience society.

Quantifying Precipitation Variability on Titan Using a GCM and Implications for Observed Geomorphology

NASA Astrophysics Data System (ADS)

Faulk, Sean P.; Mitchell, Jonathan L.; Moon, Seulgi; Lora, Juan Manuel

2016-10-01

Titan's zonal-mean precipitation behavior has been widely investigated using general circulation models (GCMs), but the spatial and temporal variability of rainfall in Titan's active hydrologic cycle is less well understood. We conduct statistical analyses of rainfall, diagnosed from GCM simulations of Titan's atmosphere, to determine storm intensity and frequency. Intense storms of methane have been proposed to be critical for enabling mechanical erosion of Titan's surface, as indicated by observations of dendritic valley networks. Using precipitation outputs from the Titan Atmospheric Model (TAM), a GCM shown to realistically simulate many features of Titan's atmosphere, we quantify the precipitation variability within eight separate latitude bins for a variety of initial surface liquid distributions. We find that while the overall wettest regions are indeed the poles, the most intense rainfall generally occurs in the high mid-latitudes, between 45-67.5 degrees, consistent with recent geomorphological observations of alluvial fans concentrated at those latitudes. We also find that precipitation rates necessary for surface erosion, as estimated by Perron et al. (2006) J. Geophys. Res. 111, E11001, frequently occur at all latitudes, with recurrence intervals of less than one Titan year. Such analysis is crucial towards understanding the complex interaction between Titan's atmosphere and surface and defining the influence of precipitation on observed geomorphology.

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J. D.

2017-09-01

Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

GCM Simulations of Neoproterozoic "Snowball Earth" Conditions: Implications for the Environmental Limits on Terrestrial Metazoans and Their Extraterrestrial Analogues

NASA Technical Reports Server (NTRS)

Sohl, L. E.; Chandler, M. A.

2001-01-01

The Neoproterozoic Snowball Earth intervals provide excellent opportunities to examine the environmental limits on terrestrial metazoans. A series of GCM simulations was run in order to quantify climatic conditions during these intervals. Additional information is contained in the original extended abstract.

Impact of Land Model Depth on Long Term Climate Variability and Change.

NASA Astrophysics Data System (ADS)

Gonzalez-Rouco, J. F.; García-Bustamante, E.; Hagemann, S.; Lorentz, S.; Jungclaus, J.; de Vrese, P.; Melo, C.; Navarro, J.; Steinert, N.

2017-12-01

The available evidence indicates that the simulation of subsurface thermodynamics in current General Circulation Models (GCMs) is not accurate enough due to the land-surface model imposing a zero heat flux boundary condition that is too close to the surface. Shallow land model components distort the amplitude and phase of the heat propagation in the subsurface with implications for energy storage and land-air interactions. Off line land surface model experiments forced with GCM climate change simulations and comparison with borehole temperature profiles indicate there is a large reduction of the energy storage of the soil using the typical shallow land models included in most GCMs. However, the impact of increasing the depth of the soil model in `on-line' GCM simulations of climate variability or climate change has not yet been systematically explored. The JSBACH land surface model has been used in stand alone mode, driven by outputs of the MPIESM to assess the impacts of progressively increasing the depth of the soil model. In a first stage, preindustrial control simulations are developed increasing the lower depth of the zero flux bottom boundary condition placed for temperature at the base of the fifth model layer (9.83 m) down to 294.6 m (layer 9), thus allowing for the bottom layers to reach equilibrium. Starting from piControl conditions, historical and scenario simulations have been performed since 1850 yr. The impact of increasing depths on the subsurface layer temperatures is analysed as well as the amounts of energy involved. This is done also considering permafrost processes (freezing and thawing). An evaluation on the influence of deepening the bottom boundary on the simulation of low frequency variability and temperature trends is provided.

Parameterisation of Orographic Cloud Dynamics in a GCM

DTIC Science & Technology

2007-01-01

makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged to- wards ERA-40 assimilated winds...this parameterisation makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged towards ERA-40...by ANSI Std Z39-18 et al. (1999), predicted the temperature perturbations in the lower stratosphere which can influence polar stratospheric clouds

Realistic dust and water cycles in the MarsWRF GCM using coupled two-moment microphysics

NASA Astrophysics Data System (ADS)

Lee, Christopher; Richardson, Mark Ian; Mischna, Michael A.; Newman, Claire E.

2017-10-01

Dust and water ice aerosols significantly complicate the Martian climate system because the evolution of the two aerosol fields is coupled through microphysics and because both aerosols strongly interact with visible and thermal radiation. The combination of strong forcing feedback and coupling has led to various problems in understanding and modeling of the Martian climate: in reconciling cloud abundances at different locations in the atmosphere, in generating a stable dust cycle, and in preventing numerical instability within models.Using a new microphysics model inside the MarsWRF GCM we show that fully coupled simulations produce more realistic simulation of the Martian climate system compared to a dry, dust only simulations. In the coupled simulations, interannual variability and intra-annual variability are increased, strong 'solstitial pause' features are produced in both winter high latitude regions, and dust storm seasons are more varied, with early southern summer (Ls 180) dust storms and/or more than one storm occurring in some seasons.A new microphysics scheme was developed as a part of this work and has been included in the MarsWRF model. The scheme uses split spectral/spatial size distribution numerics with adaptive bin sizes to track particle size evolution. Significantly, this scheme is highly accurate, numerically stable, and is capable of running with time steps commensurate with those of the parent atmospheric model.

Liquid-liquid phase transition and anomalous diffusion in simulated liquid GeO 2

NASA Astrophysics Data System (ADS)

Hoang, Vo Van; Anh, Nguyen Huynh Tuan; Zung, Hoang

2007-03-01

We perform molecular dynamics (MD) simulation of diffusion in liquid GeO 2 at the temperatures ranged from 3000 to 5000 K and densities ranged from 3.65 to 7.90 g/cm 3. Simulations were done in a model containing 3000 particles with the new interatomic potentials for liquid and amorphous GeO 2, which have weak Coulomb interaction and Morse-type short-range interaction. We found a liquid-liquid phase transition in simulated liquid GeO 2 from a tetrahedral to an octahedral network structure upon compression. Moreover, such phase transition accompanied with an anomalous diffusion of particles in liquid GeO 2 that the diffusion constant of both Ge and O particles strongly increases with increasing density (e.g. with increasing pressure) and it shows a maximum at the density around 4.95 g/cm 3. The possible relation between anomalous diffusion of particles and structural phase transition in the system has been discussed.

Examining Extreme Events Using Dynamically Downscaled 12-km WRF Simulations

EPA Science Inventory

Continued improvements in the speed and availability of computational resources have allowed dynamical downscaling of global climate model (GCM) projections to be conducted at increasingly finer grid scales and over extended time periods. The implementation of dynamical downscal...

Hydrological and associated biogeochemical consequences of rapid global warming during the Paleocene-Eocene Thermal Maximum

NASA Astrophysics Data System (ADS)

Carmichael, Matthew J.; Inglis, Gordon N.; Badger, Marcus P. S.; Naafs, B. David A.; Behrooz, Leila; Remmelzwaal, Serginio; Monteiro, Fanny M.; Rohrssen, Megan; Farnsworth, Alexander; Buss, Heather L.; Dickson, Alexander J.; Valdes, Paul J.; Lunt, Daniel J.; Pancost, Richard D.

2017-10-01

The Paleocene-Eocene Thermal Maximum (PETM) hyperthermal, 56 million years ago (Ma), is the most dramatic example of abrupt Cenozoic global warming. During the PETM surface temperatures increased between 5 and 9 °C and the onset likely took < 20 kyr. The PETM provides a case study of the impacts of rapid global warming on the Earth system, including both hydrological and associated biogeochemical feedbacks, and proxy data from the PETM can provide constraints on changes in warm climate hydrology simulated by general circulation models (GCMs). In this paper, we provide a critical review of biological and geochemical signatures interpreted as direct or indirect indicators of hydrological change at the PETM, explore the importance of adopting multi-proxy approaches, and present a preliminary model-data comparison. Hydrological records complement those of temperature and indicate that the climatic response at the PETM was complex, with significant regional and temporal variability. This is further illustrated by the biogeochemical consequences of inferred changes in hydrology and, in fact, changes in precipitation and the biogeochemical consequences are often conflated in geochemical signatures. There is also strong evidence in many regions for changes in the episodic and/or intra-annual distribution of precipitation that has not widely been considered when comparing proxy data to GCM output. Crucially, GCM simulations indicate that the response of the hydrological cycle to the PETM was heterogeneous - some regions are associated with increased precipitation - evaporation (P - E), whilst others are characterised by a decrease. Interestingly, the majority of proxy data come from the regions where GCMs predict an increase in PETM precipitation. We propose that comparison of hydrological proxies to GCM output can be an important test of model skill, but this will be enhanced by further data from regions of model-simulated aridity and simulation of extreme precipitation events.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, R; Bai, W

Purpose: Because of statistical noise in Monte Carlo dose calculations, effective point doses may not be accurate. Volume spheres are useful for evaluating dose in Monte Carlo plans, which have an inherent statistical uncertainty.We use a user-defined sphere volume instead of a point, take sphere sampling around effective point make the dose statistics to decrease the stochastic errors. Methods: Direct dose measurements were made using a 0.125cc Semiflex ion chamber (IC) 31010 isocentrically placed in the center of a homogeneous Cylindric sliced RW3 phantom (PTW, Germany).In the scanned CT phantom series the sensitive volume length of the IC (6.5mm) weremore » delineated and defined the isocenter as the simulation effective points. All beams were simulated in Monaco in accordance to the measured model. In our simulation using 2mm voxels calculation grid spacing and choose calculate dose to medium and request the relative standard deviation ≤0.5%. Taking three different assigned IC over densities (air electron density(ED) as 0.01g/cm3 default CT scanned ED and Esophageal lumen ED 0.21g/cm3) were tested at different sampling sphere radius (2.5, 2, 1.5 and 1 mm) statistics dose were compared with the measured does. Results: The results show that in the Monaco TPS for the IC using Esophageal lumen ED 0.21g/cm3 and sampling sphere radius 1.5mm the statistical value is the best accordance with the measured value, the absolute average percentage deviation is 0.49%. And when the IC using air electron density(ED) as 0.01g/cm3 and default CT scanned EDthe recommented statistical sampling sphere radius is 2.5mm, the percentage deviation are 0.61% and 0.70%, respectivly. Conclusion: In Monaco treatment planning system for the ionization chamber 31010 recommend air cavity using ED 0.21g/cm3 and sampling 1.5mm sphere volume instead of a point dose to decrease the stochastic errors. Funding Support No.C201505006.« less

The use of EuroCordex in marine climate projections

NASA Astrophysics Data System (ADS)

Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

2017-04-01

The Northwest European Shelf seas (NWS, including the North Sea, Irish Sea and Celtic Sea) are of economic, environmental and cultural importance to a number of European countries. However, their representation by global climate models (GCMs) is very crude, due to their inability to represent the complex geometry and the absence of tides. Therefore, there is a need to employ dynamical downscaling methods when considering the potential impacts of climate change on the European (and other) shelf seas. Using a shelf seas model to dynamically downscale of the ocean component of the GCM is a well established method. While taking open ocean lateral boundary conditions from the GCM ocean is acceptable, using surface flux forcings from the GCM atmosphere is often problematic. The CORDEX project provides an important dataset of high spatial and temporal resolution atmospheric forcings, derived from 'parent' CMIP5 GCM simulations. We drive the NEMO shelf seas model with data from CMIP5 models and EURO-CORDEX Regional Climate Model (RCM) data to produce a set of NWS climate projections. We require relatively high temporal resolution output, and run-off (for the river forcings), and so are limited to a subset of the available EURO-CORDEX RCMs. From these we select two CMIP5 GCMs with the same RCM with two emissions scenarios to give a minimum estimate of GCM model structural and emission scenario uncertainty. Other experiments allow an initial estimate of the uncertainty associated with the model structure of both the shelf seas and the RCM. Our analysis is focused on the uncertainty associated with the mean change in a number of physical marine impacts and the drivers of coastal variability and change, including sea level and the propagation of open ocean signals onto the shelf. Our work is part of the UK Climate Projections (UKCP18) and will inform the following UK Climate Change Risk Assessments, required as part of the Climate Change Act.

A one-dimensional interactive soil-atmosphere model for testing formulations of surface hydrology

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Eagleson, Peter S.

1990-01-01

A model representing a soil-atmosphere column in a GCM is developed for off-line testing of GCM soil hydrology parameterizations. Repeating three representative GCM sensitivity experiments with this one-dimensional model demonstrates that, to first order, the model reproduces a GCM's sensitivity to imposed changes in parameterization and therefore captures the essential physics of the GCM. The experiments also show that by allowing feedback between the soil and atmosphere, the model improves on off-line tests that rely on prescribed precipitation, radiation, and other surface forcing.

Predicting category intuitiveness with the rational model, the simplicity model, and the generalized context model.

PubMed

Pothos, Emmanuel M; Bailey, Todd M

2009-07-01

Naïve observers typically perceive some groupings for a set of stimuli as more intuitive than others. The problem of predicting category intuitiveness has been historically considered the remit of models of unsupervised categorization. In contrast, this article develops a measure of category intuitiveness from one of the most widely supported models of supervised categorization, the generalized context model (GCM). Considering different category assignments for a set of instances, the authors asked how well the GCM can predict the classification of each instance on the basis of all the other instances. The category assignment that results in the smallest prediction error is interpreted as the most intuitive for the GCM-the authors refer to this way of applying the GCM as "unsupervised GCM." The authors systematically compared predictions of category intuitiveness from the unsupervised GCM and two models of unsupervised categorization: the simplicity model and the rational model. The unsupervised GCM compared favorably with the simplicity model and the rational model. This success of the unsupervised GCM illustrates that the distinction between supervised and unsupervised categorization may need to be reconsidered. However, no model emerged as clearly superior, indicating that there is more work to be done in understanding and modeling category intuitiveness.

Statistical downscaling of summer precipitation over northwestern South America

NASA Astrophysics Data System (ADS)

Palomino Lemus, Reiner; Córdoba Machado, Samir; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda; Jesús Esteban Parra, María

2015-04-01

In this study a statistical downscaling (SD) model using Principal Component Regression (PCR) for simulating summer precipitation in Colombia during the period 1950-2005, has been developed, and climate projections during the 2071-2100 period by applying the obtained SD model have been obtained. For these ends the Principal Components (PCs) of the SLP reanalysis data from NCEP were used as predictor variables, while the observed gridded summer precipitation was the predictand variable. Period 1950-1993 was utilized for calibration and 1994-2010 for validation. The Bootstrap with replacement was applied to provide estimations of the statistical errors. All models perform reasonably well at regional scales, and the spatial distribution of the correlation coefficients between predicted and observed gridded precipitation values show high values (between 0.5 and 0.93) along Andes range, north and north Pacific of Colombia. Additionally, the ability of the MIROC5 GCM to simulate the summer precipitation in Colombia, for present climate (1971-2005), has been analyzed by calculating the differences between the simulated and observed precipitation values. The simulation obtained by this GCM strongly overestimates the precipitation along a horizontal sector through the center of Colombia, especially important at the east and west of this country. However, the SD model applied to the SLP of the GCM shows its ability to faithfully reproduce the rainfall field. Finally, in order to get summer precipitation projections in Colombia for the period 1971-2100, the downscaled model, recalibrated for the total period 1950-2010, has been applied to the SLP output from MIROC5 model under the RCP2.6, RCP4.5 and RCP8.5 scenarios. The changes estimated by the SD models are not significant under the RCP2.6 scenario, while for the RCP4.5 and RCP8.5 scenarios a significant increase of precipitation appears regard to the present values in all the regions, reaching around the 27% in northern Colombia region under the RCP8.5 scenario. Keywords: Statistical downscaling, precipitation, Principal Component Regression, climate change, Colombia. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

The atmospheric boundary layer in the CSIRO global climate model: simulations versus observations

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Rotstayn, L. D.; Krummel, P. B.

2002-07-01

A 5-year simulation of the atmospheric boundary layer in the CSIRO global climate model (GCM) is compared with detailed boundary-layer observations at six locations, two over the ocean and four over land. Field observations, in the form of surface fluxes and vertical profiles of wind, temperature and humidity, are generally available for each hour over periods of one month or more in a single year. GCM simulations are for specific months corresponding to the field observations, for each of five years. At three of the four land sites (two in Australia, one in south-eastern France), modelled rainfall was close to the observed climatological values, but was significantly in deficit at the fourth (Kansas, USA). Observed rainfall during the field expeditions was close to climatology at all four sites. At the Kansas site, modelled screen temperatures (Tsc), diurnal temperature amplitude and sensible heat flux (H) were significantly higher than observed, with modelled evaporation (E) much lower. At the other three land sites, there is excellent correspondence between the diurnal amplitude and phase and absolute values of each variable (Tsc, H, E). Mean monthly vertical profiles for specific times of the day show strong similarities: over land and ocean in vertical shape and absolute values of variables, and in the mixed-layer and nocturnal-inversion depths (over land) and the height of the elevated inversion or height of the cloud layer (over the sea). Of special interest is the presence climatologically of early morning humidity inversions related to dewfall and of nocturnal low-level jets; such features are found in the GCM simulations. The observed day-to-day variability in vertical structure is captured well in the model for most sites, including, over a whole month, the temperature range at all levels in the boundary layer, and the mix of shallow and deep mixed layers. Weaknesses or unrealistic structure include the following, (a) unrealistic model mixed-layer temperature profiles over land in clear skies, related to use of a simple local first-order turbulence closure, (b) a tendency to overpredict cloud liquid water near the surface.

Intraannual variability of tides in the thermosphere from model simulations and in situ satellite observations

NASA Astrophysics Data System (ADS)

Häusler, K.; Hagan, M. E.; Forbes, J. M.; Zhang, X.; Doornbos, E.; Bruinsma, S.; Lu, G.

2015-01-01

In this paper, we provide insights into limitations imposed by current satellite-based strategies to delineate tidal variability in the thermosphere, as well as the ability of a state-of-the-art model to replicate thermospheric tidal determinations. Toward this end, we conducted a year-long thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM) simulation for 2009, which is characterized by low solar and geomagnetic activity. In order to account for tropospheric waves and tides propagating upward into the ˜30-400 km model domain, we used 3-hourly MERRA (Modern-Era Retrospective Analysis for Research and Application) reanalysis data. We focus on exospheric tidal temperatures, which are also compared with 72 day mean determinations from combined Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) satellite observations to assess the model's capability to capture the observed tidal signatures and to quantify the uncertainties associated with the satellite exospheric temperature determination technique. We found strong day-to-day tidal variability in TIME-GCM that is smoothed out when averaged over as few as ten days. TIME-GCM notably overestimates the 72 day mean eastward propagating tides observed by CHAMP/GRACE, while capturing many of the salient features of other tidal components. However, the CHAMP/GRACE tidal determination technique only provides a gross climatological representation, underestimates the majority of the tidal components in the climatological spectrum, and moreover fails to characterize the extreme variability that drives the dynamics and electrodynamics of the ionosphere-thermosphere system. A multisatellite mission that samples at least six local times simultaneously is needed to provide this quantification.

Seasonal Variability in Global Eddy Diffusion and the Effect on Thermospheric Neutral Density

NASA Astrophysics Data System (ADS)

Pilinski, M.; Crowley, G.

2014-12-01

We describe a method for making single-satellite estimates of the seasonal variability in global-average eddy diffusion coefficients. Eddy diffusion values as a function of time between January 2004 and January 2008 were estimated from residuals of neutral density measurements made by the CHallenging Minisatellite Payload (CHAMP) and simulations made using the Thermosphere Ionosphere Mesosphere Electrodynamics - Global Circulation Model (TIME-GCM). The eddy diffusion coefficient results are quantitatively consistent with previous estimates based on satellite drag observations and are qualitatively consistent with other measurement methods such as sodium lidar observations and eddy-diffusivity models. The eddy diffusion coefficient values estimated between January 2004 and January 2008 were then used to generate new TIME-GCM results. Based on these results, the RMS difference between the TIME-GCM model and density data from a variety of satellites is reduced by an average of 5%. This result, indicates that global thermospheric density modeling can be improved by using data from a single satellite like CHAMP. This approach also demonstrates how eddy diffusion could be estimated in near real-time from satellite observations and used to drive a global circulation model like TIME-GCM. Although the use of global values improves modeled neutral densities, there are some limitations of this method, which are discussed, including that the latitude-dependence of the seasonal neutral-density signal is not completely captured by a global variation of eddy diffusion coefficients. This demonstrates the need for a latitude-dependent specification of eddy diffusion consistent with diffusion observations made by other techniques.

Seasonal variability in global eddy diffusion and the effect on neutral density

NASA Astrophysics Data System (ADS)

Pilinski, M. D.; Crowley, G.

2015-04-01

We describe a method for making single-satellite estimates of the seasonal variability in global-average eddy diffusion coefficients. Eddy diffusion values as a function of time were estimated from residuals of neutral density measurements made by the Challenging Minisatellite Payload (CHAMP) and simulations made using the thermosphere-ionosphere-mesosphere electrodynamics global circulation model (TIME-GCM). The eddy diffusion coefficient results are quantitatively consistent with previous estimates based on satellite drag observations and are qualitatively consistent with other measurement methods such as sodium lidar observations and eddy diffusivity models. Eddy diffusion coefficient values estimated between January 2004 and January 2008 were then used to generate new TIME-GCM results. Based on these results, the root-mean-square sum for the TIME-GCM model is reduced by an average of 5% when compared to density data from a variety of satellites, indicating that the fidelity of global density modeling can be improved by using data from a single satellite like CHAMP. This approach also demonstrates that eddy diffusion could be estimated in near real-time from satellite observations and used to drive a global circulation model like TIME-GCM. Although the use of global values improves modeled neutral densities, there are limitations to this method, which are discussed, including that the latitude dependence of the seasonal neutral-density signal is not completely captured by a global variation of eddy diffusion coefficients. This demonstrates the need for a latitude-dependent specification of eddy diffusion which is also consistent with diffusion observations made by other techniques.

A 3D Global Climate Model of the Pluto atmosphere coupled to a volatile transport model to interpret New Horizons observations, including the N2, CH4 and CO cycles and the formation of organic hazes

NASA Astrophysics Data System (ADS)

Bertrand, Tanguy; Forget, Francois

2016-04-01

To interpret New Horizons observations and simulate the Pluto climate system, we have developed a Global Climate Model (GCM) of Pluto's atmosphere. In addition to a 3D "dynamical core" which solves the equation of meteorology, the model takes into account the N2 condensation and sublimation and its thermal and dynamical effects, the vertical turbulent mixing, the radiative transfer through methane and carbon monoxide, molecular thermal conduction, and a detailed surface thermal model with different thermal inertia for various timescales (diurnal, seasonal). The GCM also includes a detailed model of the CH4 and CO cycles, taking into account their transport by the atmospheric circulation and turbulence, as well as their condensation and sublimation on the surface and in the atmosphere, possibly forming methane ice clouds. The GCM consistently predicts the 3D methane abundance in the atmosphere, which is used as an input for our radiative transfer calculation. In a second phase, we also developed a volatile transport model, derived from the GCM, which can be run over thousands of years in order to reach consistent initial states for the GCM runs and better explore the seasonal processes on Pluto. Results obtained with the volatile transport model show that the distribution of N2, CH4 and CO ices primarily depends on the seasonal thermal inertia used for the different ices, and is affected by the assumed topography as well. As observed, it is possible to form a large and permanent nitrogen glacier with CO and CH4 ice deposits in an equatorial basin corresponding to Sputnik Planum, while having a surface pressure evolution consistent with stellar occultations and New Horizons data. In addition, most of the methane ice is sequestered with N2 ice in the basin but seasonal polar caps of CH4 frosts also form explaining the bright polar caps observed with Hubble in the 1980s and in line with New Horizons observations. Using such balanced combination of surface and subsurface conditions as initial conditions, we run the GCM from 1975 to 2015, so that the model become insensitive to the assumed atmospheric initial states (that are not constrained by the volatile transport model). The simulated thermal structure and waves can be compared to the New Horizons occultations measurements. As observed, the horizontal variability is very limited, for fundamental reasons. In addition, we have developed a 3D model of the formation of organic hazes within the GCM. It includes the different steps of aerosols formation as understood on Titan: photolysis of CH4 in the upper atmosphere by the Lyman-alpha radiation, production of various gaseous precursor species, conversion into solid particles through chemistry and aggregation processes, and gravitational sedimentation. Significant amount of haze particles are found to be present at all latitudes up to 100 km. However, if N2 ice is already condensing in the polar night, the majority of the haze particles tend to accumulate in the polar night because of the transport of the haze precursors and aerosols by the condensation flow.

Quantification of downscaled precipitation uncertainties via Bayesian inference

NASA Astrophysics Data System (ADS)

Nury, A. H.; Sharma, A.; Marshall, L. A.

2017-12-01

Prediction of precipitation from global climate model (GCM) outputs remains critical to decision-making in water-stressed regions. In this regard, downscaling of GCM output has been a useful tool for analysing future hydro-climatological states. Several downscaling approaches have been developed for precipitation downscaling, including those using dynamical or statistical downscaling methods. Frequently, outputs from dynamical downscaling are not readily transferable across regions for significant methodical and computational difficulties. Statistical downscaling approaches provide a flexible and efficient alternative, providing hydro-climatological outputs across multiple temporal and spatial scales in many locations. However these approaches are subject to significant uncertainty, arising due to uncertainty in the downscaled model parameters and in the use of different reanalysis products for inferring appropriate model parameters. Consequently, these will affect the performance of simulation in catchment scale. This study develops a Bayesian framework for modelling downscaled daily precipitation from GCM outputs. This study aims to introduce uncertainties in downscaling evaluating reanalysis datasets against observational rainfall data over Australia. In this research a consistent technique for quantifying downscaling uncertainties by means of Bayesian downscaling frame work has been proposed. The results suggest that there are differences in downscaled precipitation occurrences and extremes.

Parameterization of eddy sensible heat transports in a zonally averaged dynamic model of the atmosphere

NASA Technical Reports Server (NTRS)

Genthon, Christophe; Le Treut, Herve; Sadourny, Robert; Jouzel, Jean

1990-01-01

A Charney-Branscome based parameterization has been tested as a way of representing the eddy sensible heat transports missing in a zonally averaged dynamic model (ZADM) of the atmosphere. The ZADM used is a zonally averaged version of a general circulation model (GCM). The parameterized transports in the ZADM are gaged against the corresponding fluxes explicitly simulated in the GCM, using the same zonally averaged boundary conditions in both models. The Charney-Branscome approach neglects stationary eddies and transient barotropic disturbances and relies on a set of simplifying assumptions, including the linear appoximation, to describe growing transient baroclinic eddies. Nevertheless, fairly satisfactory results are obtained when the parameterization is performed interactively with the model. Compared with noninteractive tests, a very efficient restoring feedback effect between the modeled zonal-mean climate and the parameterized meridional eddy transport is identified.

Simulation of monsoon intraseasonal oscillations in a coarse-resolution aquaplanet GCM

NASA Astrophysics Data System (ADS)

Ajayamohan, R. S.; Khouider, Boualem; Majda, Andrew J.

2014-08-01

The skill of the global climate models (GCMs) to realistically simulate the monsoon intraseasonal oscillations (MISOs) is related to the sensitivity of their convective parameterization schemes. Here we show that by coupling a simple multicloud parameterization to a coarse-resolution aquaplanet GCM, realistic MISOs can be simulated. We conduct three different simulations with a fixed nonhomogeneous sea surface temperature mimicking the Indian Ocean/western Pacific warm pool (WP) centered at the three latitudes 5°N, 10°N, and 15°N, respectively, to replicate the seasonal migration of the Tropical Convergence Zone (TCZ). This results in the generation of mean circulation resembling the monsoonal flow pattern in boreal summer. Succession of eastward propagating Madden-Julian Oscillation (MJO) disturbances with phase speed, amplitude, and structure similar to summer MJOs are simulated when the WP is at 5°N. When the WP is located over 10°N, northward and eastward propagating MISOs are simulated. This case captures the meridional seesaw of convection between continental and oceanic TCZ observed during boreal summer over South Asia. Westward propagating Rossby wave-like disturbances are simulated when the WP is over 15°N congruous with the synoptic disturbances seen over the monsoon trough. The initiation of intraseasonal oscillations in the model can occur internally through organization of convective events above the WP associated with internal dynamics.

On the Origins of Mars' Exospheric Nonthermal Oxygen Component as Observed by MAVEN and Modeled by HELIOSARES

NASA Astrophysics Data System (ADS)

Leblanc, F.; Chaufray, J. Y.; Modolo, R.; Leclercq, L.; Curry, S.; Luhmann, J.; Lillis, R.; Hara, T.; McFadden, J.; Halekas, J.; Schneider, N.; Deighan, J.; Mahaffy, P. R.; Benna, M.; Johnson, R. E.; Gonzalez-Galindo, F.; Forget, F.; Lopez-Valverde, M. A.; Eparvier, F. G.; Jakosky, B.

2017-12-01

The first measurements of the emission brightness of the oxygen atomic exosphere by Mars Atmosphere and Volatile EvolutioN (MAVEN) mission have clearly shown that it is composed of a thermal component produced by the extension of the upper atmosphere and of a nonthermal component. Modeling these measurements allows us to constrain the origins of the exospheric O and, as a consequence, to estimate Mars' present oxygen escape rate. We here propose an analysis of three periods of MAVEN observations based on a set of three coupled models: a hybrid magnetospheric model (LATmos HYbrid Simulation (LatHyS)), an Exospheric General Model (EGM), and the Global Martian Circulation model of the Laboratoire de Météorologie Dynamique (LMD-GCM), which provide a description of Mars' environment from the surface up to the solar wind. The simulated magnetosphere by LatHyS is in good agreement with MAVEN Plasma and Field Package instruments data. The LMD-GCM modeled upper atmospheric profiles for the main neutral and ion species are compared to Neutral Gas and Ion Mass Spectrometer/MAVEN data showing that the LMD-GCM can provide a satisfactory global view of Mars' upper atmosphere. Finally, we were able to reconstruct the expected emission brightness intensity from the oxygen exosphere using EGM. The good agreement with the averaged measured profiles by Imaging Ultraviolet Spectrograph during these three periods suggests that Mars' exospheric nonthermal component can be fully explained by the reactions of dissociative recombination of the O2+ ion in Mars' ionosphere, limiting significantly our ability to extract information from MAVEN observations of the O exosphere on other nonthermal processes, such as sputtering.

Accounting for Global Climate Model Projection Uncertainty in Modern Statistical Downscaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johannesson, G

2010-03-17

Future climate change has emerged as a national and a global security threat. To carry out the needed adaptation and mitigation steps, a quantification of the expected level of climate change is needed, both at the global and the regional scale; in the end, the impact of climate change is felt at the local/regional level. An important part of such climate change assessment is uncertainty quantification. Decision and policy makers are not only interested in 'best guesses' of expected climate change, but rather probabilistic quantification (e.g., Rougier, 2007). For example, consider the following question: What is the probability that themore » average summer temperature will increase by at least 4 C in region R if global CO{sub 2} emission increases by P% from current levels by time T? It is a simple question, but one that remains very difficult to answer. It is answering these kind of questions that is the focus of this effort. The uncertainty associated with future climate change can be attributed to three major factors: (1) Uncertainty about future emission of green house gasses (GHG). (2) Given a future GHG emission scenario, what is its impact on the global climate? (3) Given a particular evolution of the global climate, what does it mean for a particular location/region? In what follows, we assume a particular GHG emission scenario has been selected. Given the GHG emission scenario, the current batch of the state-of-the-art global climate models (GCMs) is used to simulate future climate under this scenario, yielding an ensemble of future climate projections (which reflect, to some degree our uncertainty of being able to simulate future climate give a particular GHG scenario). Due to the coarse-resolution nature of the GCM projections, they need to be spatially downscaled for regional impact assessments. To downscale a given GCM projection, two methods have emerged: dynamical downscaling and statistical (empirical) downscaling (SDS). Dynamic downscaling involves configuring and running a regional climate model (RCM) nested within a given GCM projection (i.e., the GCM provides bounder conditions for the RCM). On the other hand, statistical downscaling aims at establishing a statistical relationship between observed local/regional climate variables of interest and synoptic (GCM-scale) climate predictors. The resulting empirical relationship is then applied to future GCM projections. A comparison of the pros and cons of dynamical versus statistical downscaling is outside the scope of this effort, but has been extensively studied and the reader is referred to Wilby et al. (1998); Murphy (1999); Wood et al. (2004); Benestad et al. (2007); Fowler et al. (2007), and references within those. The scope of this effort is to study methodology, a statistical framework, to propagate and account for GCM uncertainty in regional statistical downscaling assessment. In particular, we will explore how to leverage an ensemble of GCM projections to quantify the impact of the GCM uncertainty in such an assessment. There are three main component to this effort: (1) gather the necessary climate-related data for a regional SDS study, including multiple GCM projections, (2) carry out SDS, and (3) assess the uncertainty. The first step is carried out using tools written in the Python programming language, while analysis tools were developed in the statistical programming language R; see Figure 1.« less

Mesosacle eddies in a high resolution OGCM and coupled ocean-atmosphere GCM

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, H.; Lin, P.

2017-12-01

The present study described high-resolution climate modeling efforts including oceanic, atmospheric and coupled general circulation model (GCM) at the state key laboratory of numerical modeling for atmospheric sciences and geophysical fluid dynamics (LASG), Institute of Atmospheric Physics (IAP). The high-resolution OGCM is established based on the latest version of the LASG/IAP Climate system Ocean Model (LICOM2.1), but its horizontal resolution and vertical resolution are increased to 1/10° and 55 layers, respectively. Forced by the surface fluxes from the reanalysis and observed data, the model has been integrated for approximately more than 80 model years. Compared with the simulation of the coarse-resolution OGCM, the eddy-resolving OGCM not only better simulates the spatial-temporal features of mesoscale eddies and the paths and positions of western boundary currents but also reproduces the large meander of the Kuroshio Current and its interannual variability. Another aspect, namely, the complex structures of equatorial Pacific currents and currents in the coastal ocean of China, are better captured due to the increased horizontal and vertical resolution. Then we coupled the high resolution OGCM to NCAR CAM4 with 25km resolution, in which the mesoscale air-sea interaction processes are better captured.

Group Capability Model

NASA Technical Reports Server (NTRS)

Olejarski, Michael; Appleton, Amy; Deltorchio, Stephen

2009-01-01

The Group Capability Model (GCM) is a software tool that allows an organization, from first line management to senior executive, to monitor and track the health (capability) of various groups in performing their contractual obligations. GCM calculates a Group Capability Index (GCI) by comparing actual head counts, certifications, and/or skills within a group. The model can also be used to simulate the effects of employee usage, training, and attrition on the GCI. A universal tool and common method was required due to the high risk of losing skills necessary to complete the Space Shuttle Program and meet the needs of the Constellation Program. During this transition from one space vehicle to another, the uncertainty among the critical skilled workforce is high and attrition has the potential to be unmanageable. GCM allows managers to establish requirements for their group in the form of head counts, certification requirements, or skills requirements. GCM then calculates a Group Capability Index (GCI), where a score of 1 indicates that the group is at the appropriate level; anything less than 1 indicates a potential for improvement. This shows the health of a group, both currently and over time. GCM accepts as input head count, certification needs, critical needs, competency needs, and competency critical needs. In addition, team members are categorized by years of experience, percentage of contribution, ex-members and their skills, availability, function, and in-work requirements. Outputs are several reports, including actual vs. required head count, actual vs. required certificates, CGI change over time (by month), and more. The program stores historical data for summary and historical reporting, which is done via an Excel spreadsheet that is color-coded to show health statistics at a glance. GCM has provided the Shuttle Ground Processing team with a quantifiable, repeatable approach to assessing and managing the skills in their organization. They now have a common frame of reference across NASA/contractor lines to communicate and mitigate any critical skills concerns.

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

Crimp, Steven; Jin, Huidong; Kokic, Philip; Bakar, Shuvo; Nicholls, Neville

2018-04-01

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation.

Timescales of Land Surface Evapotranspiration Response

NASA Technical Reports Server (NTRS)

Scott, Russell; Entekhabi, Dara; Koster, Randal; Suarez, Max

1997-01-01

Soil and vegetation exert strong control over the evapotranspiration rate, which couples the land surface water and energy balances. A method is presented to quantify the timescale of this surface control using daily general circulation model (GCM) simulation values of evapotranspiration and precipitation. By equating the time history of evaporation efficiency (ratio of actual to potential evapotranspiration) to the convolution of precipitation and a unit kernel (temporal weighting function), response functions are generated that can be used to characterize the timescales of evapotranspiration response for the land surface model (LSM) component of GCMS. The technique is applied to the output of two multiyear simulations of a GCM, one using a Surface-Vegetation-Atmosphere-Transfer (SVAT) scheme and the other a Bucket LSM. The derived response functions show that the Bucket LSM's response is significantly slower than that of the SVAT across the globe. The analysis also shows how the timescales of interception reservoir evaporation, bare soil evaporation, and vegetation transpiration differ within the SVAT LSM.

Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models

NASA Technical Reports Server (NTRS)

Xu, L.

1994-01-01

A simple two-layer variable infiltration capacity (VIC-2L) land surface model suitable for incorporation in general circulation models (GCMs) is described. The model consists of a two-layer characterization of the soil within a GCM grid cell, and uses an aerodynamic representation of latent and sensible heat fluxes at the land surface. The effects of GCM spatial subgrid variability of soil moisture and a hydrologically realistic runoff mechanism are represented in the soil layers. The model was tested using long-term hydrologic and climatalogical data for Kings Creek, Kansas to estimate and validate the hydrological parameters. Surface flux data from three First International Satellite Land Surface Climatology Project Field Experiments (FIFE) intensive field compaigns in the summer and fall of 1987 in central Kansas, and from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in Brazil were used to validate the mode-simulated surface energy fluxes and surface temperature.

Observations and simulations of the ionospheric lunar tide: Seasonal variability

NASA Astrophysics Data System (ADS)

Pedatella, N. M.

2014-07-01

The seasonal variability of the ionospheric lunar tide is investigated using a combination of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations and thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) simulations. The present study focuses on the seasonal variability of the lunar tide in the ionosphere and its potential connection to the occurrence of stratosphere sudden warmings (SSWs). COSMIC maximum F region electron density (NmF2) and total electron content observations reveal a primarily annual variation of the ionospheric lunar tide, with maximum amplitudes occurring at low latitudes during December-February. Simulations of the lunar tide climatology in TIME-GCM display a similar annual variability as the COSMIC observations. This leads to the conclusion that the annual variability of the lunar tide in the ionosphere is not solely due to the occurrence of SSWs. Rather, the annual variability of the lunar tide in the ionosphere is generated by the seasonal variability of the lunar tide at E region altitudes. However, compared to the observations, the ionospheric lunar tide annual variability is weaker in the climatological simulations which is attributed to the occurrence of SSWs during the majority of the years included in the observations. Introducing a SSW into the TIME-GCM simulation leads to an additional enhancement of the lunar tide during Northern Hemisphere winter, increasing the lunar tide annual variability and resulting in an annual variability that is more consistent with the observations. The occurrence of SSWs can therefore potentially bias lunar tide climatologies, and it is important to consider these effects in studies of the lunar tide in the atmosphere and ionosphere.

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Changes in the Structure and Propagation of the MJO with Increasing CO2

NASA Technical Reports Server (NTRS)

Adames, Angel F.; Kim, Daehyun; Sobel, Adam H.; Del Genio, Anthony; Wu, Jingbo

2017-01-01

Changes in the Madden-Julian Oscillation (MJO) with increasing CO2 concentrations are examined using the Goddard Institute for Space Studies Global Climate Model (GCM). Four simulations performed with fixed CO2 concentrations of 0.5, 1, 2 and 4 times pre-industrial levels using the GCM coupled with a mixed layer ocean model are analyzed in terms of the basic state, rainfall and moisture variability, and the structure and propagation of the MJO.The GCM simulates basic state changes associated with increasing CO2 that are consistent with results from earlier studies: column water vapor increases at approximately 7.1% K(exp -1), precipitation also increases but at a lower rate (approximately 3% K(exp -1)), and column relative humidity shows little change. Moisture and rainfall variability intensify with warming. Total moisture and rainfall variability increases at a rate that is similar to that of the mean state change. The intensification is faster in the MJO-related anomalies than in the total anomalies, though the ratio of the MJO band variability to its westward counterpart increases at a much slower rate. On the basis of linear regression analysis and space-time spectral analysis, it is found that the MJO exhibits faster eastward propagation, faster westward energy dispersion, a larger zonal scale and deeper vertical structure in warmer climates.

Quantifying Precipitation Variability and Relative Erosion Rates on Titan Using a GCM and Implications for Observed Geomorphology

NASA Astrophysics Data System (ADS)

Faulk, S.; Moon, S.; Mitchell, J.; Lora, J. M.

2016-12-01

Titan's zonal-mean precipitation behavior has been widely investigated using general circulation models (GCMs), but the spatial and temporal variability of rainfall in Titan's active hydrologic cycle is less well understood. We conduct statistical analyses of rainfall, diagnosed from GCM simulations of Titan's atmosphere, to determine storm intensity and frequency. Intense storms of methane have been proposed to be critical for enabling mechanical erosion of Titan's surface, as indicated by extensive observations of dendritic valley networks. Using precipitation outputs from the Titan Atmospheric Model (TAM), a GCM shown to realistically simulate many features of Titan's atmosphere, we quantify the precipitation variability and resulting relative erosion rates within eight separate latitude bins for a variety of initial surface liquid distributions. We find that while the overall wettest regions are indeed the poles, the most intense rainfall generally occurs in the high mid-latitudes, between 45-67.5 degrees, consistent with recent geomorphological observations of alluvial fans concentrated at those latitudes. We also find that precipitation rates necessary for surface erosion, as estimated by Perron et al. (2006) J. Geophys. Res. 111, E11001, frequently occur at all latitudes, with recurrence intervals of less than one Titan year. Such analysis is crucial towards understanding the complex interaction between Titan's atmosphere and surface and defining the influence of precipitation on observed geomorphology.

The Ozone Budget in the Upper Troposphere from Global Modeling Initiative (GMI)Simulations

NASA Technical Reports Server (NTRS)

Rodriquez, J.; Duncan, Bryan N.; Logan, Jennifer A.

2006-01-01

Ozone concentrations in the upper troposphere are influenced by in-situ production, long-range tropospheric transport, and influx of stratospheric ozone, as well as by photochemical removal. Since ozone is an important greenhouse gas in this region, it is particularly important to understand how it will respond to changes in anthropogenic emissions and changes in stratospheric ozone fluxes.. This response will be determined by the relative balance of the different production, loss and transport processes. Ozone concentrations calculated by models will differ depending on the adopted meteorological fields, their chemical scheme, anthropogenic emissions, and treatment of the stratospheric influx. We performed simulations using the chemical-transport model from the Global Modeling Initiative (GMI) with meteorological fields from (It)h e NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), (2) the atmospheric GCM from NASA's Global Modeling and Assimilation Office(GMAO), and (3) assimilated winds from GMAO . These simulations adopt the same chemical mechanism and emissions, and adopt the Synthetic Ozone (SYNOZ) approach for treating the influx of stratospheric ozone -. In addition, we also performed simulations for a coupled troposphere-stratosphere model with a subset of the same winds. Simulations were done for both 4degx5deg and 2degx2.5deg resolution. Model results are being tested through comparison with a suite of atmospheric observations. In this presentation, we diagnose the ozone budget in the upper troposphere utilizing the suite of GMI simulations, to address the sensitivity of this budget to: a) the different meteorological fields used; b) the adoption of the SYNOZ boundary condition versus inclusion of a full stratosphere; c) model horizontal resolution. Model results are compared to observations to determine biases in particular simulations; by examining these comparisons in conjunction with the derived budgets, we may pinpoint deficiencies in the representation of chemical/dynamical processes.

3D General Circulation Model of the Middle Atmosphere of Jupiter

NASA Astrophysics Data System (ADS)

Zube, Nicholas Gerard; Zhang, Xi; Li, Cheng; Le, Tianhao

2017-10-01

The characteristics of Jupiter’s large-scale stratospheric circulation remain largely unknown. Detailed distributions of temperature and photochemical species have been provided by recent observations [1], but have not yet been accurately reproduced by middle atmosphere general circulation models (GCM). Jupiter’s stratosphere and upper troposphere are influenced by radiative forcing from solar insolation and infrared cooling from hydrogen and hydrocarbons, as well as waves propagating from the underlying troposphere [2]. The relative significance of radiative and mechanical forcing on stratospheric circulation is still being debated [3]. Here we present a 3D GCM of Jupiter’s atmosphere with a correlated-k radiative transfer scheme. The simulation results are compared with observations. We analyze the impact of model parameters on the stratospheric temperature distribution and dynamical features. Finally, we discuss future tracer transport and gravity wave parameterization schemes that may be able to accurately simulate the middle atmosphere dynamics of Jupiter and other giant planets.[1] Kunde et al. 2004, Science 305, 1582.[2] Zhang et al. 2013a, EGU General Assembly, EGU2013-5797-2.[3] Conrath 1990, Icarus, 83, 255-281.

Exploring diurnal and seasonal characteristics of global carbon cycle with GISS Model E2 GCM

NASA Astrophysics Data System (ADS)

Aleinov, I. D.; Kiang, N. Y.; Romanou, A.

2017-12-01

The ability to properly model surface carbon fluxes on the diurnal and seasonal time scale is a necessary requirement for understanding of the global carbon cycle. It is also one of the most challenging tasks faced by modern General Circulation Models (GCMs) due to complexity of the algorithms and variety of relevant spatial and temporal scales. The observational data, though abundant, is difficult to interpret at the global scale, because flux tower observations are very sparse for large impact areas (such as Amazon and African rainforest and most of Siberia) and satellite missions often struggle to produce sufficiently high confidence data over the land and may be missing CO2 amounts near the surface due to the nature of the method. In this work we use the GISS Model E2 GCM to perform a subset of experiments proposed by the Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) and relate the results to available observations.The GISS Model E2 GCM is currently equipped with a complete global carbon cycle algorithm. Its surface carbon fluxes are computed by the Ent Terrestrial Biosphere Model (Ent TBM) over the land with observed leaf area index of the Moderate Resolution Imaging Spectrometer (MODIS) and by the NASA Ocean Biogeochemistry Model (NOBM) over the ocean. The propagation of atmospheric CO2 is performed by a generic Model E2 tracer algorithm, which is based on a quadratic upstream method (Prather 1986). We perform a series spin-up experiments for preindustrial climate conditions and fixed preindustrial atmospheric CO2 concentration. First, we perform separate spin-up simulations each for terrestrial and ocean carbon. We then combine the spun-up states and perform a coupled spin-up simulation until the model reaches a sufficient equilibrium. We then release restrictions on CO2 concentration and allow it evolve freely, driven only by simulated surface fluxes. We then study the results of the unforced run, comparing the amplitude and the phase of diurnal and seasonal variation of atmospheric CO2 concentration to selected flux tower observations and OCO-2 satellite datasets.

Improving NASA's Multiscale Modeling Framework for Tropical Cyclone Climate Study

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Nelson, Bron; Cheung, Samson; Tao, Wei-Kuo

2013-01-01

One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.

Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

NASA Astrophysics Data System (ADS)

Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

2015-04-01

Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), mean annual temperature (MAT), mean annual runoff (MAR), the standard deviation of annual precipitation (SDP), standard deviation of runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 worldwide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainties from the 17 catchments and 5 GCMs for 2015-2044 (A1B) were MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould-Dincer Gamma (G-DG) procedure was applied to each annual runoff time series for hypothetical reservoir capacities of 1 × MAR and 3 × MAR and the average uncertainties in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were 25.1% (1 × MAR) and 11.9% (3 × MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1 × MAR or 3 × MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable - these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

Reentrant and Isostructural Transitions in the Cluster-Crystal Forming GEM-4

NASA Astrophysics Data System (ADS)

Zhang, Kai; Charbonneau, Patrick; Mladek, Bianca

2011-03-01

Systems governed by soft, bounded, purely repulsive interactions show two possible equilibrium behaviors under compression: reentrant melting, as in the Gaussian core model (GCM), or clustering, as in the penetrable sphere model (PSM). The generalized exponential model of power 4 (GEM-4), which is the intermedia of the GCM and PSM with a simple isotropic pair interaction u (r) ~e-r4 , is thought to belong to the second family and was indeed found to form clusters at sufficiently high densities at high temperatures. Here, we present the low-temperature behavior of GEM-4 through Monte Carlo simulations using a specially developed free energy integration scheme. We find the phase behavior to be hybrid between the GCM and the PSM limits, showing a surprisingly rich phase behavior in spite of the simplicity of the interaction form. For instance, S- shaped doubly reentrant phase sequences and evidence of a cascade of critical isostructural transitions between crystals of different average lattice site occupancy are observed. The possible annihilation of lattice sites and accompanying clustering moreover leads to an unusual softening upon compression, which suggest that these materials may have interesting mechanical properties. We discuss possible experimental realizations and challenges of this class of materials.

Mars Water Ice and Carbon Dioxide Seasonal Polar Caps: GCM Modeling and Comparison with Mars Express Omega Observations

NASA Technical Reports Server (NTRS)

Forget, F.; Levrard, B.; Montmessin, F.; Schmitt, B.; Doute, S.; Langevin, Y.; Bibring, J. P.

2005-01-01

To better understand the behavior of the Mars CO2 ice seasonal polar caps, and in particular interpret the the Mars Express Omega observations of the recession of the northern seasonal cap, we present some simulations of the Martian Climate/CO2 cycle/ water cycle as modeled by the Laboratoire de Meteorologie Dynamique (LMD) global climate model.

Impact of dynamical regionalization on precipitation biases and teleconnections over West Africa

NASA Astrophysics Data System (ADS)

Gómara, Iñigo; Mohino, Elsa; Losada, Teresa; Domínguez, Marta; Suárez-Moreno, Roberto; Rodríguez-Fonseca, Belén

2018-06-01

West African societies are highly dependent on the West African Monsoon (WAM). Thus, a correct representation of the WAM in climate models is of paramount importance. In this article, the ability of 8 CMIP5 historical General Circulation Models (GCMs) and 4 CORDEX-Africa Regional Climate Models (RCMs) to characterize the WAM dynamics and variability is assessed for the period July-August-September 1979-2004. Simulations are compared with observations. Uncertainties in RCM performance and lateral boundary conditions are assessed individually. Results show that both GCMs and RCMs have trouble to simulate the northward migration of the Intertropical Convergence Zone in boreal summer. The greatest bias improvements are obtained after regionalization of the most inaccurate GCM simulations. To assess WAM variability, a Maximum Covariance Analysis is performed between Sea Surface Temperature and precipitation anomalies in observations, GCM and RCM simulations. The assessed variability patterns are: El Niño-Southern Oscillation (ENSO); the eastern Mediterranean (MED); and the Atlantic Equatorial Mode (EM). Evidence is given that regionalization of the ENSO-WAM teleconnection does not provide any added value. Unlike GCMs, RCMs are unable to precisely represent the ENSO impact on air subsidence over West Africa. Contrastingly, the simulation of the MED-WAM teleconnection is improved after regionalization. Humidity advection and convergence over the Sahel area are better simulated by RCMs. Finally, no robust conclusions can be determined for the EM-WAM teleconnection, which cannot be isolated for the 1979-2004 period. The novel results in this article will help to select the most appropriate RCM simulations to study WAM teleconnections.

Technical report series on global modeling and data assimilation. Volume 1: Documentation of the Goddard Earth Observing System (GEOS) General Circulation Model, version 1

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Takacs, Lawrence L.; Molod, Andrea; Wang, Tina

1994-01-01

This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

NASA Astrophysics Data System (ADS)

Grelle, Gerardo; Bonito, Laura; Lampasi, Alessandro; Revellino, Paola; Guerriero, Luigi; Sappa, Giuseppe; Guadagno, Francesco Maria

2016-04-01

The SiSeRHMap (simulator for mapped seismic response using a hybrid model) is a computerized methodology capable of elaborating prediction maps of seismic response in terms of acceleration spectra. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches and models are organized in a code architecture composed of five interdependent modules. A GIS (geographic information system) cubic model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A meta-modelling process confers a hybrid nature to the methodology. In this process, the one-dimensional (1-D) linear equivalent analysis produces acceleration response spectra for a specified number of site profiles using one or more input motions. The shear wave velocity-thickness profiles, defined as trainers, are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Emul-spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated evolutionary algorithm (EA) and the Levenberg-Marquardt algorithm (LMA) as the final optimizer. In the final step, the GCM maps executor module produces a serial map set of a stratigraphic seismic response at different periods, grid solving the calibrated Emul-spectra model. In addition, the spectra topographic amplification is also computed by means of a 3-D validated numerical prediction model. This model is built to match the results of the numerical simulations related to isolate reliefs using GIS morphometric data. In this way, different sets of seismic response maps are developed on which maps of design acceleration response spectra are also defined by means of an enveloping technique.

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

The Impact of Desert Dust Aerosol Radiative Forcing on Global and West African Precipitation

NASA Astrophysics Data System (ADS)

Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.; Dezfuli, A. K.

2015-12-01

Desert dust aerosols exert a radiative forcing on the atmosphere, influencing atmospheric temperature structure and modifying radiative fluxes at the top of the atmosphere (TOA) and surface. As dust aerosols perturb radiative fluxes, the atmosphere responds by altering both energy and moisture dynamics, with potentially significant impacts on regional and global precipitation. Global Climate Model (GCM) experiments designed to characterize these processes have yielded a wide range of results, owing to both the complex nature of the system and diverse differences across models. Most model results show a general decrease in global precipitation, but regional results vary. Here, we compare simulations from GFDL's CM2Mc GCM with multiple other model experiments from the literature in order to investigate mechanisms of radiative impact and reasons for GCM differences on a global and regional scale. We focus on West Africa, a region of high interannual rainfall variability that is a source of dust and that neighbors major Sahara Desert dust sources. As such, changes in West African climate due to radiative forcing of desert dust aerosol have serious implications for desertification feedbacks. Our CM2Mc results show net cooling of the planet at TOA and surface, net warming of the atmosphere, and significant increases in precipitation over West Africa during the summer rainy season. These results differ from some previous GCM studies, prompting comparative analysis of desert dust parameters across models. This presentation will offer quantitative analysis of differences in dust aerosol parameters, aerosol optical properties, and overall particle burden across GCMs, and will characterize the contribution of model differences to the uncertainty of forcing and climate response affecting West Africa.

GCM simulations of volcanic aerosol forcing. I - Climate changes induced by steady-state perturbations

NASA Technical Reports Server (NTRS)

Pollack, James B.; Rind, David; Lacis, Andrew; Hansen, James E.; Sato, Makiko; Ruedy, Reto

1993-01-01

The response of the climate system to a temporally and spatially constant amount of volcanic particles is simulated using a general circulation model (GCM). The optical depth of the aerosols is chosen so as to produce approximately the same amount of forcing as results from doubling the present CO2 content of the atmosphere and from the boundary conditions associated with the peak of the last ice age. The climate changes produced by long-term volcanic aerosol forcing are obtained by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. The simulations indicate that a significant cooling of the troposphere and surface can occur at times of closely spaced multiple sulfur-rich volcanic explosions that span time scales of decades to centuries. The steady-state climate response to volcanic forcing includes a large expansion of sea ice, especially in the Southern Hemisphere; a resultant large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature.

High-resolution dynamical downscaling of the future Alpine climate

NASA Astrophysics Data System (ADS)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph

2017-04-01

The Alpine region and Switzerland is a challenging area for simulating and analysing Global Climate Model (GCM) results. This is mostly due to the combination of a very complex topography and the still rather coarse horizontal resolution of current GCMs, in which not all of the many-scale processes that drive the local weather and climate can be resolved. In our study, the Weather Research and Forecasting (WRF) model is used to dynamically downscale a GCM simulation to a resolution as high as 2 km x 2 km. WRF is driven by initial and boundary conditions produced with the Community Earth System Model (CESM) for the recent past (control run) and until 2100 using the RCP8.5 climate scenario (future run). The control run downscaled with WRF covers the period 1976-2005, while the future run investigates a 20-year-slice simulated for the 2080-2099. We compare the control WRF-CESM simulations to an observational product provided by MeteoSwiss and an additional WRF simulation driven by the ERA-Interim reanalysis, to estimate the bias that is introduced by the extra modelling step of our framework. Several bias-correction methods are evaluated, including a quantile mapping technique, to ameliorate the bias in the control WRF-CESM simulation. In the next step of our study these corrections are applied to our future WRF-CESM run. The resulting downscaled and bias-corrected data is analysed for the properties of precipitation and wind speed in the future climate. Our special interest focuses on the absolute quantities simulated for these meteorological variables as these are used to identify extreme events, such as wind storms and situations that can lead to floods.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

NASA Astrophysics Data System (ADS)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data sets (or cloud library) stored at Goddard.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2007-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Impacts of Groundwater on the Atmospheric Convection in Amazon using Multi-GCM Simulations from I-GEM project

NASA Astrophysics Data System (ADS)

Lo, M. H.; Chien, R. Y.; Ducharne, A.; Decharme, B.; Lan, C. W.; Wang, F.; Cheruy, F.; Colin, J.

2017-12-01

Previous research indicated that groundwater plays an important role in hydrological cycle and is a major source of water vapor in climate models, which may result in modifications of atmospheric convection. For instance, our previous study showed that when considering the groundwater dynamics in a GCM, the wet soil induced surface cooling effect can further reduce the Amazon dry season convection and precipitation. However, the main mechanisms of the interaction among groundwater, soil moisture, and precipitation are still unclear, and they need to be examined in several climate models. In this study, we further examine the influence of the surface cooling effects due to the groundwater on the convection over the Amazon. To this end, we use idealized simulations of the IGEM (Impact of Groundwater in Earth system Models) project, with 3 GCMs (CESM, CNRM, and IPSL): in each of them, we prescribed a water table at a constant depth throughout all land areas, to create globally wet conditions. Preliminary analysis shows a contradict result of the tendency of precipitation in the three models with wet condition which indicates a great uncertainty of the groundwater's impacts in coupled GCMs.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

2013-04-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

Sensitivity of Boreal-Summer Circulation and Precipitation to Atmospheric Aerosols in Selected Regions: Part I Africa and India

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sud, Yogesh C.; Wilcox, Eric; Lau, William K.

2009-10-23

Version-4 of the Goddard Earth Observing System (GEOS-4) General Circulation Model (GCM) was employed to assess the influence of potential changes in aerosols on the regional circulation, ambient temperatures, and precipitation in four selected regions: India and Africa (current paper), as well as North and South America (companion paper). Ensemble-simulations were carried out with the GCM to assess the aerosol direct and indirect effects, hereafter ADE and AIE. Each simulation was started from the NCEP-analyzed initial conditions for May 1 and was integrated through May-June-July-August of each year: 1982-1987 to provide an ensemble set of six simulations. In the firstmore » set, called the baseline experiment (#1), climatological aerosols were prescribed. The next two experiments (#2 and #3) had two sets of simulations each: one with 2X and another with 1/2X the climatological aerosols over each of the four selected regions. In experiment#2, the anomaly regions were advectively restricted (AR), i.e., the large-scale prognostic fields outside the aerosol anomaly regions were prescribed while in experiment#3, the anomaly regions were advectively Interactive (AI) as is the case in a normal GCM integrations, but with the same aerosols anomalies as in experiment #2. Intercomparisons of circulation, diabatic heating, and precipitation difference fields showed large disparities among the AR and AI simulations, which raised serious questions about the AR assumption, commonly invoked in regional climate simulation studies. Consequently AI simulation mode was chosen for the subsequent studies. Two more experiments (#4 and #5) were performed in the AI mode in which ADE and AIE were activated one at a time. The results showed that ADE and AIE work in concert to make the joint influences larger than sum of each acting alone. Moreover, the ADE and AIE influences were vastly different for the Indian and Africa regions, which suggest an imperative need to include them rationally in climate models. We also found that the aerosol induced increase of tropical cirrus clouds would potentially offset any cirrus thinning that may occur due to global warming in response to CO2 increase.« less

Examining the Performance of Statistical Downscaling Methods: Toward Matching Applications to Data Products

NASA Astrophysics Data System (ADS)

Dixon, K. W.; Lanzante, J. R.; Adams-Smith, D.

2017-12-01

Several challenges exist when seeking to use future climate model projections in a climate impacts study. A not uncommon approach is to utilize climate projection data sets derived from more than one future emissions scenario and from multiple global climate models (GCMs). The range of future climate responses represented in the set is sometimes taken to be indicative of levels of uncertainty in the projections. Yet, GCM outputs are deemed to be unsuitable for direct use in many climate impacts applications. GCM grids typically are viewed as being too coarse. Additionally, regional or local-scale biases in a GCM's simulation of the contemporary climate that may not be problematic from a global climate modeling perspective may be unacceptably large for a climate impacts application. Statistical downscaling (SD) of climate projections - a type of post-processing that uses observations to inform the refinement of GCM projections - is often used in an attempt to account for GCM biases and to provide additional spatial detail. "What downscaled climate projection is the best one to use" is a frequently asked question, but one that is not always easy to answer, as it can be dependent on stakeholder needs and expectations. Here we present results from a perfect model experimental design illustrating how SD method performance can vary not only by SD method, but how performance can also vary by location, season, climate variable of interest, amount of projected climate change, SD configuration choices, and whether one is interested in central tendencies or the tails of the distribution. Awareness of these factors can be helpful when seeking to determine the suitability of downscaled climate projections for specific climate impacts applications. It also points to the potential value of considering more than one SD data product in a study, so as to acknowledge uncertainties associated with the strengths and weaknesses of different downscaling methods.

Toward Realistic Simulation of low-Level Clouds Using a Multiscale Modeling Framework With a Third-Order Turbulence Closure in its Cloud-Resolving Model Component

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Cheng, Anning

2010-01-01

This study presents preliminary results from a multiscale modeling framework (MMF) with an advanced third-order turbulence closure in its cloud-resolving model (CRM) component. In the original MMF, the Community Atmosphere Model (CAM3.5) is used as the host general circulation model (GCM), and the System for Atmospheric Modeling with a first-order turbulence closure is used as the CRM for representing cloud processes in each grid box of the GCM. The results of annual and seasonal means and diurnal variability are compared between the modified and original MMFs and the CAM3.5. The global distributions of low-level cloud amounts and precipitation and the amounts of low-level clouds in the subtropics and middle-level clouds in mid-latitude storm track regions in the modified MMF show substantial improvement relative to the original MMF when both are compared to observations. Some improvements can also be seen in the diurnal variability of precipitation.

A Simple Climate Model Program for High School Education

NASA Astrophysics Data System (ADS)

Dommenget, D.

2012-04-01

The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!

El Nino-southern oscillation simulated in an MRI atmosphere-ocean coupled general circulation model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagai, T.; Tokioka, T.; Endoh, M.

A coupled atmosphere-ocean general circulation model (GCM) was time integrated for 30 years to study interannual variability in the tropics. The atmospheric component is a global GCM with 5 levels in the vertical and 4[degrees]latitude X 5[degrees] longitude grids in the horizontal including standard physical processes (e.g., interactive clouds). The oceanic component is a GCM for the Pacific with 19 levels in the vertical and 1[degrees]x 2.5[degrees] grids in the horizontal including seasonal varying solar radiation as forcing. The model succeeded in reproducing interannual variations that resemble the El Nino-Southern Oscillation (ENSO) with realistic seasonal variations in the atmospheric andmore » oceanic fields. The model ENSO cycle has a time scale of approximately 5 years and the model El Nino (warm) events are locked roughly in phase to the seasonal cycle. The cold events, however, are less evident in comparison with the El Nino events. The time scale of the model ENSO cycle is determined by propagation time of signals from the central-eastern Pacific to the western Pacific and back to the eastern Pacific. Seasonal timing is also important in the ENSO time scale: wind anomalies in the central-eastern Pacific occur in summer and the atmosphere ocean coupling in the western Pacific operates efficiently in the first half of the year.« less

Surface-Atmosphere Connections on Titan: A New Window into Terrestrial Hydroclimate

NASA Astrophysics Data System (ADS)

Faulk, Sean

This dissertation investigates the coupling between the large-scale atmospheric circulation and surface processes on Titan, with a particular focus on methane precipitation and its influence on surface geomorphology and hydrology. As the only body in the Solar System with an active hydrologic cycle other than Earth, Titan presents a valuable laboratory for studying principles of hydroclimate on terrestrial planets. Idealized general circulation models (GCMs) are used here to test hypotheses regarding Titan's surface-atmosphere connections. First, an Earth-like GCM simulated over a range of rotation rates is used to evaluate the effect of rotation rate on seasonal monsoon behavior. Slower rotation rates result in poleward migration of summer rain, indicating a large-scale atmospheric control on Titan's observed dichotomy of dry low latitudes and moist high latitudes. Second, a Titan GCM benchmarked against observations is used to analyze the magnitudes and frequencies of extreme methane rainstorms as simulated by the model. Regional patterns in these extreme events correlate well with observed geomorphic features, with the most extreme rainstorms occurring in mid-latitude regions associated with high alluvial fan concentrations. Finally, a planetary surface hydrology scheme is developed and incorporated into a Titan GCM to evaluate the roles of surface flow, subsurface flow, infiltration, and groundmethane evaporation in Titan's climate. The model reproduces Titan's observed surface liquid and cloud distributions, and reaches an equilibrium state with limited interhemispheric transport where atmospheric transport is approximately balanced by subsurface transport. The equilibrium state suggests that Titan's current hemispheric surface liquid asymmetry, favoring methane accumulation in the north, is stable in the modern climate.

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

2002-01-01

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

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

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

1998-01-01

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

The MJO Transition from Shallow to Deep Convection in CloudSat/CALIPSO Data and GISS GCM Simulations

NASA Technical Reports Server (NTRS)

DelGenio, Anthony G.; Chen, Yonghua; Kim, Daehyun; Yao, Mao-Sung

2013-01-01

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden-Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10MJO events show the following anticipatedMJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for EarthObserving System (EOS) (AMSR-E) columnwater vapor (CWV) increases by;5 mmduring the shallow- deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between;46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow-deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV. 1.

Longwave Band-by-band Cloud Radiative Effect and its Application in GCM Evaluation

NASA Technical Reports Server (NTRS)

Huang, Xianglei; Cole, Jason N. S.; He, Fei; Potter, Gerald L.; Oreopoulos, Lazaros; Lee, Dongmin; Suarez, Max; Loeb, Norman G.

2012-01-01

The cloud radiative effect (CRE) of each longwave (LW) absorption band of a GCM fs radiation code is uniquely valuable for GCM evaluation because (1) comparing band-by-band CRE avoids the compensating biases in the broadband CRE comparison and (2) the fractional contribution of each band to the LW broadband CRE (f(sub CRE)) is sensitive to cloud top height but largely insensitive to cloud fraction, presenting thus a diagnostic metric to separate the two macroscopic properties of clouds. Recent studies led by the first author have established methods to derive such band ]by ]band quantities from collocated AIRS and CERES observations. We present here a study that compares the observed band-by-band CRE over the tropical oceans with those simulated by three different atmospheric GCMs (GFDL AM2, NASA GEOS-5, and CCCma CanAM4) forced by observed SST. The models agree with observation on the annual ]mean LW broadband CRE over the tropical oceans within +/-1W/sq m. However, the differences among these three GCMs in some bands can be as large as or even larger than +/-1W/sq m. Observed seasonal cycles of f(sub CRE) in major bands are shown to be consistent with the seasonal cycle of cloud top pressure for both the amplitude and the phase. However, while the three simulated seasonal cycles of f(sub CRE) agree with observations on the phase, the amplitudes are underestimated. Simulated interannual anomalies from GFDL AM2 and CCCma CanAM4 are in phase with observed anomalies. The spatial distribution of f(sub CRE) highlights the discrepancies between models and observation over the low-cloud regions and the compensating biases from different bands.

The contribution of natural variability to GCM bias: Can we effectively bias-correct climate projections?

NASA Astrophysics Data System (ADS)

McAfee, S. A.; DeLaFrance, A.

2017-12-01

Investigating the impacts of climate change often entails using projections from inherently imperfect general circulation models (GCMs) to drive models that simulate biophysical or societal systems in great detail. Error or bias in the GCM output is often assessed in relation to observations, and the projections are adjusted so that the output from impacts models can be compared to historical or observed conditions. Uncertainty in the projections is typically accommodated by running more than one future climate trajectory to account for differing emissions scenarios, model simulations, and natural variability. The current methods for dealing with error and uncertainty treat them as separate problems. In places where observed and/or simulated natural variability is large, however, it may not be possible to identify a consistent degree of bias in mean climate, blurring the lines between model error and projection uncertainty. Here we demonstrate substantial instability in mean monthly temperature bias across a suite of GCMs used in CMIP5. This instability is greatest in the highest latitudes during the cool season, where shifts from average temperatures below to above freezing could have profound impacts. In models with the greatest degree of bias instability, the timing of regional shifts from below to above average normal temperatures in a single climate projection can vary by about three decades, depending solely on the degree of bias assessed. This suggests that current bias correction methods based on comparison to 20- or 30-year normals may be inappropriate, particularly in the polar regions.

Introducing the Met Office 2.2-km Europe-wide convection-permitting regional climate simulations

NASA Astrophysics Data System (ADS)

Kendon, Elizabeth J.; Chan, Steven C.; Berthou, Segolene; Fosser, Giorgia; Roberts, Malcolm J.; Fowler, Hayley J.

2017-04-01

The Met Office is currently conducting Europe-wide 2.2-km convection-permitting model (CPM) simulations driven by ERA-Interim reanalysis and present/future-climate GCM simulations. Here, we present the preliminary results of these new European simulations examining daily and sub-daily precipitation outputs in comparison with observations across Europe, 12-km European and 1.5-km UK climate model simulations. As the simulations are not yet complete, we focus on diagnostics that are relatively robust with a limited amount of data; for instance, the diurnal cycle and the probability distribution of daily and sub-daily precipitation intensities. We will also present specific case studies that showcase the benefits of using continental-scale CPM simulations over previously-available small-domain CPM simulations.

Radon-222 as a test of convective transport in a general circulation model

NASA Technical Reports Server (NTRS)

Jacob, Daniel J.; Prather, Michael J.

1990-01-01

A three-dimensional tracer model based on the Goddard Institude of Space Studies GCM is used to simulate the distribution of Rn-222 over North America to test the ability of the model to describe the transport of pollutants in the boundary layer and the exchange of mass between the boundary layer and the free troposphere. The model results are compared with surface observations from five sites in the U.S., showing that Rn-222 concentrations are primarily regulated by dry convection. The simulations show satisfactory agreement with observations although the model underpredicts observations at night and the simulated Rn-222 concentrations over the northeastern U.S. are too high in the spring and too low in the fall.

Estimating Past Temperature Change in Antarctica Based on Ice Core Stable Water Isotope Diffusion

NASA Astrophysics Data System (ADS)

Kahle, E. C.; Markle, B. R.; Holme, C.; Jones, T. R.; Steig, E. J.

2017-12-01

The magnitude of the last glacial-interglacial transition is a key target for constraining climate sensitivity on long timescales. Ice core proxy records and general circulation models (GCMs) both provide insight on the magnitude of climate change through the last glacial-interglacial transition, but appear to provide different answers. In particular, the magnitude of the glacial-interglacial temperature change reconstructed from East Antarctic ice-core water-isotope records is greater ( 9 degrees C) than that from most GCM simulations ( 6 degrees C). A possible source of this difference is error in the linear-scaling of water isotopes to temperature. We employ a novel, nonlinear temperature-reconstruction technique using the physics of water-isotope diffusion to infer past temperature. Based on new, ice-core data from the South Pole, this diffusion technique suggests East Antarctic temperature change was smaller than previously thought. We are able to confirm this result using a simple, water-isotope fractionation model to nonlinearly reconstruct temperature change at ice core locations across Antarctica based on combined oxygen and hydrogen isotope ratios. Both methods produce a temperature change of 6 degrees C for South Pole, agreeing with GCM results for East Antarctica. Furthermore, both produce much larger changes in West Antarctica, also in agreement with GCM results and independent borehole thermometry. These results support the fidelity of GCMs in simulating last glacial maximum climate, and contradict the idea, based on previous work, that the climate sensitivity of current GCMs is too low.

Sorption Phase of Supercritical CO2 in Silica Aerogel: Experiments and Mesoscale Computer Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rother, Gernot; Vlcek, Lukas; Gruszkiewicz, Miroslaw

2014-01-01

Adsorption of supercritical CO2 in nanoporous silica aerogel was investigated by a combination of experiments and molecular-level computer modeling. High-pressure gravimetric and vibrating tube densimetry techniques were used to measure the mean pore fluid density and excess sorption at 35 C and 50 C and pressures of 0-200 bar. Densification of the pore fluid was observed at bulk fluid densities below 0.7 g/cm3. Far above the bulk fluid density, near-zero sorption or weak depletion effects were measured, while broad excess sorption maxima form in the vicinity of the bulk critical density region. The CO2 sorption properties are very similar formore » two aerogels with different bulk densities of 0.1 g/cm3 and 0.2 g/cm3, respectively. The spatial distribution of the confined supercritical fluid was analyzed in terms of sorption- and bulk-phase densities by means of the Adsorbed Phase Model (APM), which used data from gravimetric sorption and small-angle neutron scattering experiments. To gain more detailed insight into supercritical fluid sorption, large-scale lattice gas GCMC simulations were utilized and tuned to resemble the experimental excess sorption data. The computed three-dimensional pore fluid density distributions show that the observed maximum of the excess sorption near the critical density originates from large density fluctuations pinned to the pore walls. At this maximum, the size of these fluctuations is comparable to the prevailing pore sizes.« less

Using a Global Climate Model in an On-line Climate Change Course

NASA Astrophysics Data System (ADS)

Randle, D. E.; Chandler, M. A.; Sohl, L. E.

2012-12-01

Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that arise are due to a lack of computer literacy amongst participants and we have found, through iterative improvements in the materials, that breaking assignments into discrete, well-supported tasks has been key to the success.

a New Framework for Characterising Simulated Droughts for Future Climates

NASA Astrophysics Data System (ADS)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross-Dependence across Multiple Time Scales: Implications for Downscaling, Journal of Climate, 29(10), 3519-3539. Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 50, 650-660, doi:10.1002/2013WR013845.

Accounting for interannual variability: A comparison of options for water resources climate change impact assessments

NASA Astrophysics Data System (ADS)

Johnson, Fiona; Sharma, Ashish

2011-04-01

Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment.

On the limitations of General Circulation Climate Models

NASA Technical Reports Server (NTRS)

Stone, Peter H.; Risbey, James S.

1990-01-01

General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

Climate Change Projection for the Department of Energy's Savannah River Site

NASA Astrophysics Data System (ADS)

Werth, D. W.

2014-12-01

As per recent Department of Energy (DOE) sustainability requirements, the Savannah River National Laboratory (SRNL) is developing a climate projection for the DOE's Savannah River Site (SRS) near Aiken, SC. This will comprise data from both a statistical and a dynamic downscaling process, each interpolated to the SRS. We require variables most relevant to operational activities at the site (such as the US Forest Service's forest management program), and select temperature, precipitation, wind, and humidity as being most relevant to energy and water resource requirements, fire and forest ecology, and facility and worker safety. We then develop projections of the means and extremes of these variables, estimate the effect on site operations, and develop long-term mitigation strategies. For example, given that outdoor work while wearing protective gear is a daily facet of site operations, heat stress is of primary importance to work planning, and we use the downscaled data to estimate changes in the occurrence of high temperatures. For the statistical downscaling, we use global climate model (GCM) data from the Climate Model Intercomparison Project, version 5 (CMIP-5), which was used in the IPCC Fifth Assessment Report (AR5). GCM data from five research groups was selected, and two climate change scenarios - RCP 4.5 and RCP 8.5 - are used with observed data from site instruments and other databases to produce the downscaled projections. We apply a quantile regression downscaling method, which involves the use of the observed cumulative distribution function to correct that of the GCM. This produces a downscaled projection with an interannual variability closer to that of the observed data and allows for more extreme values in the projections, which are often absent in GCM data. The statistically downscaled data is complemented with dynamically downscaled data from the NARCCAP database, which comprises output from regional climate models forced with GCM output from the CMIP-3 database of GCM simulations. Applications of the downscaled climate projections to some of the unique operational needs of a large DOE weapons complex site are described.

THE APPLICATION OF A STATISTICAL DOWNSCALING PROCESS TO DERIVE 21{sup ST} CENTURY RIVER FLOW PREDICTIONS USING A GLOBAL CLIMATE SIMULATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werth, D.; Chen, K. F.

2013-08-22

The ability of water managers to maintain adequate supplies in coming decades depends, in part, on future weather conditions, as climate change has the potential to alter river flows from their current values, possibly rendering them unable to meet demand. Reliable climate projections are therefore critical to predicting the future water supply for the United States. These projections cannot be provided solely by global climate models (GCMs), however, as their resolution is too coarse to resolve the small-scale climate changes that can affect hydrology, and hence water supply, at regional to local scales. A process is needed to ‘downscale’ themore » GCM results to the smaller scales and feed this into a surface hydrology model to help determine the ability of rivers to provide adequate flow to meet future needs. We apply a statistical downscaling to GCM projections of precipitation and temperature through the use of a scaling method. This technique involves the correction of the cumulative distribution functions (CDFs) of the GCM-derived temperature and precipitation results for the 20{sup th} century, and the application of the same correction to 21{sup st} century GCM projections. This is done for three meteorological stations located within the Coosa River basin in northern Georgia, and is used to calculate future river flow statistics for the upper Coosa River. Results are compared to the historical Coosa River flow upstream from Georgia Power Company’s Hammond coal-fired power plant and to flows calculated with the original, unscaled GCM results to determine the impact of potential changes in meteorology on future flows.« less

Parameterization of Rocket Dust Storms on Mars in the LMD Martian GCM: Modeling Details and Validation

NASA Astrophysics Data System (ADS)

Wang, Chao; Forget, François; Bertrand, Tanguy; Spiga, Aymeric; Millour, Ehouarn; Navarro, Thomas

2018-04-01

The origin of the detached dust layers observed by the Mars Climate Sounder aboard the Mars Reconnaissance Orbiter is still debated. Spiga et al. (2013, https://doi.org/10.1002/jgre.20046) revealed that deep mesoscale convective "rocket dust storms" are likely to play an important role in forming these dust layers. To investigate how the detached dust layers are generated by this mesoscale phenomenon and subsequently evolve at larger scales, a parameterization of rocket dust storms to represent the mesoscale dust convection is designed and included into the Laboratoire de Météorologie Dynamique (LMD) Martian Global Climate Model (GCM). The new parameterization allows dust particles in the GCM to be transported to higher altitudes than in traditional GCMs. Combined with the horizontal transport by large-scale winds, the dust particles spread out and form detached dust layers. During the Martian dusty seasons, the LMD GCM with the new parameterization is able to form detached dust layers. The formation, evolution, and decay of the simulated dust layers are largely in agreement with the Mars Climate Sounder observations. This suggests that mesoscale rocket dust storms are among the key factors to explain the observed detached dust layers on Mars. However, the detached dust layers remain absent in the GCM during the clear seasons, even with the new parameterization. This implies that other relevant atmospheric processes, operating when no dust storms are occurring, are needed to explain the Martian detached dust layers. More observations of local dust storms could improve the ad hoc aspects of this parameterization, such as the trigger and timing of dust injection.

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

NASA Astrophysics Data System (ADS)

Grelle, G.; Bonito, L.; Lampasi, A.; Revellino, P.; Guerriero, L.; Sappa, G.; Guadagno, F. M.

2015-06-01

SiSeRHMap is a computerized methodology capable of drawing up prediction maps of seismic response. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches and models are organized in a code-architecture composed of five interdependent modules. A GIS (Geographic Information System) Cubic Model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A metamodeling process confers a hybrid nature to the methodology. In this process, the one-dimensional linear equivalent analysis produces acceleration response spectra of shear wave velocity-thickness profiles, defined as trainers, which are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated Evolutionary Algorithm (EA) and the Levenberg-Marquardt Algorithm (LMA) as the final optimizer. In the final step, the GCM Maps Executor module produces a serial map-set of a stratigraphic seismic response at different periods, grid-solving the calibrated Spectra model. In addition, the spectra topographic amplification is also computed by means of a numerical prediction model. This latter is built to match the results of the numerical simulations related to isolate reliefs using GIS topographic attributes. In this way, different sets of seismic response maps are developed, on which, also maps of seismic design response spectra are defined by means of an enveloping technique.

Classical and ab-initio simulations of hydrogen in the dissociating regime

NASA Astrophysics Data System (ADS)

Clerouin, Jean; Blottiau, Patrick; Bernard, Stephane; Dufreche, Jean-Francois

1999-11-01

Recent experiments on shock compressed hydrogen ( L. B. Da Silva, P. Cellires, G. W. Collins., et al., Physical Review Letters 78, 483-486 (1997).) have motivated a large number of theoretical studies to try to reproduce the experimental Hugoniot data. In spite of the simplicity of the hydrogen molecule, a precise description of its dissociation under pressure and temperature is still missing. Here, we compare three different approaches: the empirical Ross model (M. Ross, Physical Review B 58, 669-677 (1998).) which reproduces the experimental data, a classical molecular dynamics model, which allows for the computation of transport coefficients such as the viscosity footnote J. F. Dufreche and J. Clerouin, Physical Review E , submitted (1999). and ab initio simulations for a detailed description of the dissociation process. This comparison reveals that in the region [0.1 g/cm^3< ρ< 1g/cm^3, 2000K

Atmospheric Teleconnections From Cumulants

NASA Astrophysics Data System (ADS)

Sabou, F.; Kaspi, Y.; Marston, B.; Schneider, T.

2011-12-01

Multi-point cumulants of fields such as vorticity provide a way to visualize atmospheric teleconnections, complementing other approaches such as the method of empirical orthogonal functions (EOFs). We calculate equal-time two-point cumulants of the vorticity from NCEP reanalysis data during the period 1980 -- 2010 and from direct numerical simulation (DNS) using an idealized dry general circulation model (GCM) (Schneider and Walker, 2006). Extratropical correlations seen in the NCEP data are qualitatively reproduced by the model. Three- and four-point cumulants accumulated from DNS quantify departures of the probability distribution function from a normal distribution, shedding light on the efficacy of direct statistical simulation (DSS) of atmosphere dynamics by cumulant expansions (Marston, Conover, and Schneider, 2008; Marston 2011). Lagged-time two-point cumulants between temperature gradients and eddy kinetic energy (EKE), accumulated by DNS of an idealized moist aquaplanet GCM (O'Gorman and Schneider, 2008), reveal dynamics of storm tracks. Regions of enhanced baroclinicity (as found along the eastern boundary of continents) lead to a local enhancement of EKE and a suppression of EKE further downstream as the storm track self-destructs (Kaspi and Schneider, 2011).

Effects of topography on simulated net primary productivity at landscape scale.

PubMed

Chen, X F; Chen, J M; An, S Q; Ju, W M

2007-11-01

Local topography significantly affects spatial variations of climatic variables and soil water movement in complex terrain. Therefore, the distribution and productivity of ecosystems are closely linked to topography. Using a coupled terrestrial carbon and hydrological model (BEPS-TerrainLab model), the topographic effects on the net primary productivity (NPP) are analyzed through four modelling experiments for a 5700 km(2) area in Baohe River basin, Shaanxi Province, northwest of China. The model was able to capture 81% of the variability in NPP estimated from tree rings, with a mean relative error of 3.1%. The average NPP in 2003 for the study area was 741 gCm(-2)yr(-1) from a model run including topographic effects on the distributions of climate variables and lateral flow of ground water. Topography has considerable effect on NPP, which peaks near 1350 m above the sea level. An elevation increase of 100 m above this level reduces the average annual NPP by about 25 gCm(-2). The terrain aspect gives rise to a NPP change of 5% for forests located below 1900 m as a result of its influence on incident solar radiation. For the whole study area, a simulation totally excluding topographic effects on the distributions of climatic variables and ground water movement overestimated the average NPP by 5%.

Assessing the contribution of different factors in RegCM4.3 regional climate model projections using the Factor Separation method over the Med-CORDEX domain

NASA Astrophysics Data System (ADS)

Zsolt Torma, Csaba; Giorgi, Filippo

2014-05-01

A set of regional climate model (RCM) simulations applying dynamical downscaling of global climate model (GCM) simulations over the Mediterranean domain specified by the international initiative Coordinated Regional Downscaling Experiment (CORDEX) were completed with the Regional Climate Model RegCM, version RegCM4.3. Two GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the RegCM: HadGEM2-ES (HadGEM) and MPI-ESM-MR (MPI). The simulations consist of an ensemble including multiple physics configurations and different "Reference Concentration Pathways" (RCP4.5 and RCP8.5). In total 15 simulations were carried out with 7 model physics configurations with varying convection and land surface schemes. The horizontal grid spacing of the RCM simulations is 50 km and the simulated period in all cases is 1970-2100 (1970-2099 in case of HadGEM driven simulations). This ensemble includes a combination of experiments in which different model components are changed individually and in combination, and thus lends itself optimally to the application of the Factor Separation (FS) method. This study applies the FS method to investigate the contributions of different factors, along with their synergy, on a set of regional climate model (RCM) projections for the Mediterranean region. The FS method is applied to 6 projections for the period 1970-2100 performed with the regional model RegCM4.3 over the Med-CORDEX domain. Two different sets of factors are intercompared, namely the driving global climate model (HadGEM and MPI) boundary conditions against two model physics settings (convection scheme and irrigation). We find that both the GCM driving conditions and the model physics provide important contributions, depending on the variable analyzed (surface air temperature and precipitation), season (winter vs. summer) and time horizon into the future, while the synergy term mostly tends to counterbalance the contributions of the individual factors. We demonstrate the usefulness of the FS method to assess different sources of uncertainty in RCM-based regional climate projections.

Understanding tropical upper tropospheric warming: The role of SSTs, convective parameterizations, and observational uncertainties

NASA Astrophysics Data System (ADS)

Po-Chedley, S.; Thorsen, T. J.; Fu, Q.

2015-12-01

Recent research has compared CMIP5 general circulation model (GCM) simulations with satellite observations of warming in the tropical upper troposphere relative to the lower-middle troposphere. Although the pattern of SST warming is important, this research demonstrated that models overestimate increases in static stability between the mid- to upper- tropical troposphere, even when they are forced with historical sea surface temperatures. This discrepancy between satellite-borne microwave sounding unit measurements (MSU) and GCMs is important because it has implications for the strength of the lapse rate and water vapor feedback. The apparent model-observational difference for changes in static stability in the tropical upper troposphere represents an important problem, but it is not clear whether the difference is a result of common biases in GCMs, biases in observational datasets, or both. In this work, we will use GCM simulations to examine the importance of the spatial pattern of SST warming and different convective parameterizations in determining the lapse rate changes in tropical troposphere. We will also consider uncertainties in MSU satellite observations, including changes in the diurnal sampling of temperature and instrument calibration biases when comparing GCMs with the observed record.

Analysis of the Diurnal Cycle of Precipitation and its Relation to Cloud Radiative Forcing Using TRMM Products

NASA Technical Reports Server (NTRS)

Randall, David A.; Fowler, Laura D.; Lin, Xin

1998-01-01

In order to improve our understanding of the interactions between clouds, radiation, and the hydrological cycle simulated in the Colorado State University General Circulation Model (CSU GCM), we focused our research on the analysis of the diurnal cycle of precipitation, top-of-the-atmosphere and surface radiation budgets, and cloudiness using 10-year long Atmospheric Model Intercomparison Project (AMIP) simulations. Comparisons the simulated diurnal cycle were made against the diurnal cycle of Earth Radiation Budget Experiment (ERBE) radiation budget and International Satellite Cloud Climatology Project (ISCCP) cloud products. This report summarizes our major findings over the Amazon Basin.

A thermosphere-ionosphere-mesosphere-electrodynamic general circulation model (time-GCM): Equinox solar cycle minimum simulations (30-500 km)

NASA Technical Reports Server (NTRS)

Roble, R. G.; Ridley, E. C.

1994-01-01

A new simulation model of the mesosphere, thermosphere, and ionosphere with coupled electrodynamics has been developed and used to calculate the global circulation, temperature and compositional structure between 30-500 km for equinox, solar cycle minimum, geomagnetic quiet conditions. The model incorporates all of the features of the National Center for Atmospheric Research (NCAR) thermosphere-ionosphere- electrodynamics general circulation model (TIE-GCM) but the lower boundary has been extended downward from 97 to 30 km (10 mb) and it includes the physical and chemical processes appropriate for the mesosphere and upper stratosphere. The first simulation used Rayleigh friction to represent gravity wave drag in the middle atmosphere and although it was able to close the mesospheric jets it severely damped the diurnal tide. Reduced Rayleigh friction allowed the tide to penetrate to thermospheric heights but did not close the jets. A gravity wave parameterization developed by Fritts and Lu (1993) allows both features to exist simultaneously with the structure of tides and mean flow dependent upon the strength of the gravity wave source. The model calculates a changing dynamic structure with the mean flow and diurnal tide dominant in the mesosphere, the in-situ generated semi-diurnal tide dominating the lower thermosphere and an in-situ generated diurnal tide in the upper thermosphere. The results also show considerable interaction between dynamics and composition, especially atomic oxygen between 85 and 120 km.

Atmospheric Modeling of Mars Methane Plumes

NASA Astrophysics Data System (ADS)

Mischna, Michael A.; Allen, M.; Lee, S.

2010-10-01

We present two complementary methods for isolating and modeling surface source releases of methane in the martian atmosphere. From recent observations, there is strong evidence that periodic releases of methane occur from discrete surface locations, although the exact location and mechanism of release is still unknown. Numerical model simulations with the Mars Weather Research and Forecasting (MarsWRF) general circulation model (GCM) have been applied to the ground-based observations of atmospheric methane by Mumma et al., (2009). MarsWRF simulations reproduce the natural behavior of trace gas plumes in the martian atmosphere, and reveal the development of the plume over time. These results provide constraints on the timing and location of release of the methane plume. Additional detections of methane have been accumulated by the Planetary Fourier Spectrometer (PFS) on board Mars Express. For orbital observations, which generally have higher frequency and resolution, an alternate approach to source isolation has been developed. Drawing from the concept of natural selection within biology, we apply an evolutionary computational model to this problem of isolating source locations. Using genetic algorithms that `reward’ best-fit matches between observations and GCM plume simulations (also from MarsWRF) over many generations, we find that we can potentially isolate source locations to within tens of km, which is within the roving capabilities of future Mars rovers. Together, these methods present viable numerical approaches to restricting the timing, duration and size of methane release events, and can be used for other trace gas plumes on Mars as well as elsewhere in the solar system.

Global Radiative Forcing of Coupled Tropospheric Ozone and Aerosols in a Unified General Circulation Model

NASA Technical Reports Server (NTRS)

Liao, Hong; Seinfeld, John H.; Adams, Peter J.; Mickley, Loretta J.

2008-01-01

Global simulations of sea salt and mineral dust aerosols are integrated into a previously developed unified general circulation model (GCM), the Goddard Institute for Space Studies (GISS) GCM II', that simulates coupled tropospheric ozone-NOx-hydrocarbon chemistry and sulfate, nitrate, ammonium, black carbon, primary organic carbon, and secondary organic carbon aerosols. The fully coupled gas-aerosol unified GCM allows one to evaluate the extent to which global burdens, radiative forcing, and eventually climate feedbacks of ozone and aerosols are influenced by gas-aerosol chemical interactions. Estimated present-day global burdens of sea salt and mineral dust are 6.93 and 18.1 Tg with lifetimes of 0.4 and 3.9 days, respectively. The GCM is applied to estimate current top of atmosphere (TOA) and surface radiative forcing by tropospheric ozone and all natural and anthropogenic aerosol components. The global annual mean value of the radiative forcing by tropospheric ozone is estimated to be +0.53 W m(sup -2) at TOA and +0.07 W m(sup -2) at the Earth's surface. Global, annual average TOA and surface radiative forcing by all aerosols are estimated as -0.72 and -4.04 W m(sup -2), respectively. While the predicted highest aerosol cooling and heating at TOA are -10 and +12 W m(sup -2) respectively, surface forcing can reach values as high as -30 W m(sup -2), mainly caused by the absorption by black carbon, mineral dust, and OC. We also estimate the effects of chemistry-aerosol coupling on forcing estimates based on currently available understanding of heterogeneous reactions on aerosols. Through altering the burdens of sulfate, nitrate, and ozone, heterogeneous reactions are predicted to change the global mean TOA forcing of aerosols by 17% and influence global mean TOA forcing of tropospheric ozone by 15%.

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a collaboration between the Center for Ocean-Land-Atmosphere studies (COLA); the Geophysical Fluid Dynamics Laboratory (GFDL); the George Mason University (GMU); the National Center for Atmospheric Research (NCAR); the NCDC; NCEP; the Pacific Marine Environmental Laboratory (PMEL); and the University of Washington. The objective of the NOMADS is to preserve and provide retrospective access to GCM's and reference quality long-term observational and high volume three dimensional data as well as NCEP NWP models and re-start and re-analysis information. The creation of the NOMADS features a data distribution, format independent, methodology enabling scientific collaboration between researchers. The NOMADS configuration will allow a researcher to transparently browse, extract and intercompare retrospective observational and model data products from any of the participating centers. NOMADS will provide the ability to easily initialize and compare the results of ongoing climate model assessments and NWP output. Beyond the ingest and access capability soon to be implemented with NOMADS is the challenge of algorithm development for the inter-comparison of large-array data (e.g., satellite and radar) with surface, upper-air, and sub-surface ocean observational data. The implementation of NOMADS should foster the development of new quality control processes by taking advantage of distributed data access.

Evaluation of a Cloud Resolving Model Using TRMM Observations for Multiscale Modeling Applications

NASA Technical Reports Server (NTRS)

Posselt, Derek J.; L'Ecuyer, Tristan; Tao, Wei-Kuo; Hou, Arthur Y.; Stephens, Graeme L.

2007-01-01

The climate change simulation community is moving toward use of global cloud resolving models (CRMs), however, current computational resources are not sufficient to run global CRMs over the hundreds of years necessary to produce climate change estimates. As an intermediate step between conventional general circulation models (GCMs) and global CRMs, many climate analysis centers are embedding a CRM in each grid cell of a conventional GCM. These Multiscale Modeling Frameworks (MMFs) represent a theoretical advance over the use of conventional GCM cloud and convection parameterizations, but have been shown to exhibit an overproduction of precipitation in the tropics during the northern hemisphere summer. In this study, simulations of clouds, precipitation, and radiation over the South China Sea using the CRM component of the NASA Goddard MMF are evaluated using retrievals derived from the instruments aboard the Tropical Rainfall Measuring Mission (TRMM) satellite platform for a 46-day time period that spans 5 May - 20 June 1998. The NASA Goddard Cumulus Ensemble (GCE) model is forced with observed largescale forcing derived from soundings taken during the intensive observing period of the South China Sea Monsoon Experiment. It is found that the GCE configuration used in the NASA Goddard MMF responds too vigorously to the imposed large-scale forcing, accumulating too much moisture and producing too much cloud cover during convective phases, and overdrying the atmosphere and suppressing clouds during monsoon break periods. Sensitivity experiments reveal that changes to ice cloud microphysical parameters have a relatively large effect on simulated clouds, precipitation, and radiation, while changes to grid spacing and domain length have little effect on simulation results. The results motivate a more detailed and quantitative exploration of the sources and magnitude of the uncertainty associated with specified cloud microphysical parameters in the CRM components of MMFs.

Modeling the imprint of Milankovitch cycles on early Pleistocene ice volume

NASA Astrophysics Data System (ADS)

Roychowdhury, R.; DeConto, R.; Pollard, D.

2017-12-01

Global climate during Quaternary and Late Pliocene (present-3.1 Ma) is characterized by alternating glacial and interglacial conditions. Several proposed theories associate these cycles with variations in the Earth's orbital configuration. In this study, we attempt to address the anomalously strong obliquity forcing in the Late Pliocene/Early Pleistocene ice volume records (41 kyr world), which stands in sharp contrast to the primary cyclicity of insolation, which is at precessional periods (23 kyr). Model results from GCM simulations show that at low eccentricities (e<0.015), the effect of precession is minimal, and the integrated insolation metrics (such as summer metric, PDD, etc.) vary in-phase between the two hemispheres. At higher eccentricities (e>0.015), precessional response is important, and the insolation metrics vary out-of-phase between the two hemispheres. Using simulations from a GCM-driven ice sheet model, we simulate time continuous ice volume changes from Northern and Southern Hemispheres. Under eccentricities lower than 0.015, ice sheets in both hemispheres respond only to obliquity cycle, and grow and melt together (in-phase). If the ice sheet is simulated with eccentricity higher than 0.015, both hemispheres become more sensitive to precessional variation, and vary out-of-phase with each other, which is consistent with proxy observations from the late Pleistocene glaciations. We use the simulated ice volumes from 2.0 to 1.0 ma to empirically calculate global benthic δ18O variations based on the assumption that relationships between collapse and growth of ice-sheets and sea level is linear and symmetric and that the isotopic signature of the individual ice-sheets has not changed with time. Our modeled global benthic δ18O values are broadly consistent with the paleoclimate proxy records such as the LR04 stack.

Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

NASA Astrophysics Data System (ADS)

Hakala, Kirsti; Addor, Nans; Seibert, Jan

2017-04-01

Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.

Regional climate model downscaling may improve the prediction of alien plant species distributions

NASA Astrophysics Data System (ADS)

Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

2014-12-01

Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

Thermosphere-Ionosphere-Mesosphere Modeling Using the TIME-GCM

DTIC Science & Technology

2014-09-30

respectively. The CCM3 is the NCAR Community Climate Model, Version 3.6, a GCM of the troposphere and stratosphere. All models include self-consistent...middle atmosphere version of the NCAR Community Climate Model, (2) the NCAR TIME-GCM, and (3) the Model for Ozone and Related Chemical Tracers (MOZART... troposphere , but the impacts of such events extend well into the mesosphere. The coupled NCAR thermosphere-ionosphere-mesosphere- electrodynamics general

Examination of Daily Weather in the NCAR CCM

NASA Astrophysics Data System (ADS)

Cocke, S. D.

2006-05-01

The NCAR CCM is one of the most extensively studied climate models in the scientific community. However, most studies focus primarily on the long term mean behavior, typically monthly or longer time scales. In this study we examine the daily weather in the GCM by performing a series of daily or weekly 10 day forecasts for one year at moderate (T63) and high (T126) resolution. The model is initialized with operational "AVN" and ECMWF analyses, and model performance is compared to that of major operational centers, using conventional skill scores used by the major centers. Such a detailed look at the CCM at shorter time scales may lead to improvements in physical parameterizations, which may in turn lead to improved climate simulations. One finding from this study is that the CCM has a significant drying tendency in the lower troposphere compared to the operational analyses. Another is that the large scale predictability of the GCM is competitive with most of the operational models, particularly in the southern hemisphere.

Simulating the Current Water Cycle with the NASA Ames Mars Global Climate Model

NASA Astrophysics Data System (ADS)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Brecht, A. S.; Urata, R. A.; Montmessin, F.

2017-12-01

The water cycle is a critical component of the current Mars climate system, and it is now widely recognized that water ice clouds significantly affect the nature of the simulated water cycle. Two processes are key to implementing clouds in a Mars global climate model (GCM): the microphysical processes of formation and dissipation, and their radiative effects on atmospheric heating/cooling rates. Together, these processes alter the thermal structure, change the atmospheric dynamics, and regulate inter-hemispheric transport. We have made considerable progress using the NASA Ames Mars GCM to simulate the current-day water cycle with radiatively active clouds. Cloud fields from our baseline simulation are in generally good agreement with observations. The predicted seasonal extent and peak IR optical depths are consistent MGS/TES observations. Additionally, the thermal response to the clouds in the aphelion cloud belt (ACB) is generally consistent with observations and other climate model predictions. Notably, there is a distinct gap in the predicted clouds over the North Residual Cap (NRC) during local summer, but the clouds reappear in this simulation over the NRC earlier than the observations indicate. Polar clouds are predicted near the seasonal CO2 ice caps, but the column thicknesses of these clouds are generally too thick compared to observations. Our baseline simulation is dry compared to MGS/TES-observed water vapor abundances, particularly in the tropics and subtropics. These areas of disagreement appear to be a consistent with other current water cycle GCMs. Future avenues of investigation will target improving our understanding of what controls the vertical extent of clouds and the apparent seasonal evolution of cloud particle sizes within the ACB.

High resolution interpolation of climate scenarios for the conterminous USA and Alaska derived from general circulation model simulations

Treesearch

Linda A. Joyce; David T. Price; Daniel W. McKenney; R. Martin Siltanen; Pia Papadopol; Kevin Lawrence; David P. Coulson

2011-01-01

Projections of future climate were selected for four well-established general circulation models (GCM) forced by each of three greenhouse gas (GHG) emissions scenarios, namely A2, A1B, and B1 from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). Monthly data for the period 1961-2100 were downloaded mainly from the web...

A serosa-searing apparatus for producing gastric ulcer in rats.

PubMed

Kagoshima, M; Suzuki, T; Katagiri, S; Shimada, H

1994-12-01

Chronic ulcer models produced by serosa-searing method are very similar histologically to the ulcer healing process occurring in humans. In an effort to produce a serosa-searing chronic ulcer model in rats, we devised a new balance-type apparatus. This searing apparatus is capable of changing adequately both temperature and duration of time. Furthermore, the pressure which serves to bring the searing iron tip into contact with the stomach serosa surface can also be precisely changed. Optimal conditions for reproducing the serosa-searing ulcer model were at 65 degrees C and in 5 sec. Moreover, in order to evaluate the effects of pressure, various pressure levels (A: 5 g, 17.68 g/cm2; B: 10 g, 35.37 g/cm2; C: 15 g, 53.05 g/cm2; D: 20 g, 70.74 g/cm2; E: 25 g, 88.42 g/cm2; F: 30 g, 106.10 g/cm2; G: 35 g, 123.79 g/cm2 (+/- 1 g, 0.149 g/cm2)) of 5-sec duration at 65 +/- 0.1 degrees C were used. Macroscopically, gastric mucosal lesions were most clearly observed in a pressure-related manner 7 days after the procedure. Histologically, definite deep ulcerations (UI-III or UI-IV) were observed at pressure level C (15 g, 53.05 g/cm2) or more. The highest incidence (87%) of histological gastric ulcers (UI-IV) was observed in pressure level E (25 g, 88.42 g/cm2). The healing process was observed at 40 to 60 days postoperatively. At 100 days after the procedure, recurrences were observed both macroscopically and histologically. In conclusion, this new apparatus is very useful for reproducing a chronic ulcer model for observing the healing and recurrence process.

Impacts of weighting climate models for hydro-meteorological climate change studies

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

2017-06-01

Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

Measuring the potential utility of seasonal climate predictions

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Kleeman, Richard; Tang, Youmin

2004-11-01

Variation of sea surface temperature (SST) on seasonal-to-interannual time-scales leads to changes in seasonal weather statistics and seasonal climate anomalies. Relative entropy, an information theory measure of utility, is used to quantify the impact of SST variations on seasonal precipitation compared to natural variability. An ensemble of general circulation model (GCM) simulations is used to estimate this quantity in three regions where tropical SST has a large impact on precipitation: South Florida, the Nordeste of Brazil and Kenya. We find the yearly variation of relative entropy is strongly correlated with shifts in ensemble mean precipitation and weakly correlated with ensemble variance. Relative entropy is also found to be related to measures of the ability of the GCM to reproduce observations.

Linear simulation of the stationary eddies in a GCM. II - The 'Mountain' model

NASA Technical Reports Server (NTRS)

Nigam, Sumant; Held, Isaac M.; Lyons, Steven W.

1988-01-01

Linear stationary wave theory is used to account for zonal asymmetries of the winter-averaged tropospheric circulation obtained in a GCM. The eddy zonal velocity field in the upper troposphere indicates that the orographic and thermal plus transient contributions are nearly equal in amplitude, while the eddy meridional velocity field (which is dominated by shorter zonal scales) shows the orographic contribution to be dominant. The two contributions are found to be roughly in phase over the east Asian coast, and they contribute roughly equal amounts to the low level Siberian high. Results indicate that the 300 mb extratropical response to tropical forcing reaches 50 gpm over Alaska, and that the responses to sensible heating and lower tropospheric transients are strongly anticorrelated.

Assessing the Added Value of Dynamical Downscaling in the Context of Hydrologic Implication

NASA Astrophysics Data System (ADS)

Lu, M.; IM, E. S.; Lee, M. H.

2017-12-01

There is a scientific consensus that high-resolution climate simulations downscaled by Regional Climate Models (RCMs) can provide valuable refined information over the target region. However, a significant body of hydrologic impact assessment has been performing using the climate information provided by Global Climate Models (GCMs) in spite of a fundamental spatial scale gap. It is probably based on the assumption that the substantial biases and spatial scale gap from GCMs raw data can be simply removed by applying the statistical bias correction and spatial disaggregation. Indeed, many previous studies argue that the benefit of dynamical downscaling using RCMs is minimal when linking climate data with the hydrological model, from the comparison of the impact between bias-corrected GCMs and bias-corrected RCMs on hydrologic simulations. It may be true for long-term averaged climatological pattern, but it is not necessarily the case when looking into variability across various temporal spectrum. In this study, we investigate the added value of dynamical downscaling focusing on the performance in capturing climate variability. For doing this, we evaluate the performance of the distributed hydrological model over the Korean river basin using the raw output from GCM and RCM, and bias-corrected output from GCM and RCM. The impacts of climate input data on streamflow simulation are comprehensively analyzed. [Acknowledgements]This research is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 17AWMP-B083066-04).

A Cloud Microphysics Model for the Gas Giant Planets

NASA Astrophysics Data System (ADS)

Palotai, Csaba J.; Le Beau, Raymond P.; Shankar, Ramanakumar; Flom, Abigail; Lashley, Jacob; McCabe, Tyler

2016-10-01

Recent studies have significantly increased the quality and the number of observed meteorological features on the jovian planets, revealing banded cloud structures and discrete features. Our current understanding of the formation and decay of those clouds also defines the conceptual modes about the underlying atmospheric dynamics. The full interpretation of the new observational data set and the related theories requires modeling these features in a general circulation model (GCM). Here, we present details of our bulk cloud microphysics model that was designed to simulate clouds in the Explicit Planetary Hybrid-Isentropic Coordinate (EPIC) GCM for the jovian planets. The cloud module includes hydrological cycles for each condensable species that consist of interactive vapor, cloud and precipitation phases and it also accounts for latent heating and cooling throughout the transfer processes (Palotai and Dowling, 2008. Icarus, 194, 303-326). Previously, the self-organizing clouds in our simulations successfully reproduced the vertical and horizontal ammonia cloud structure in the vicinity of Jupiter's Great Red Spot and Oval BA (Palotai et al. 2014, Icarus, 232, 141-156). In our recent work, we extended this model to include water clouds on Jupiter and Saturn, ammonia clouds on Saturn, and methane clouds on Uranus and Neptune. Details of our cloud parameterization scheme, our initial results and their comparison with observations will be shown. The latest version of EPIC model is available as open source software from NASA's PDS Atmospheres Node.

Simulation of future groundwater recharge using a climate model ensemble and SAR-image based soil parameter distributions - A case study in an intensively-used Mediterranean catchment.

PubMed

Herrmann, Frank; Baghdadi, Nicolas; Blaschek, Michael; Deidda, Roberto; Duttmann, Rainer; La Jeunesse, Isabelle; Sellami, Haykel; Vereecken, Harry; Wendland, Frank

2016-02-01

We used observed climate data, an ensemble of four GCM-RCM combinations (global and regional climate models) and the water balance model mGROWA to estimate present and future groundwater recharge for the intensively-used Thau lagoon catchment in southern France. In addition to a highly resolved soil map, soil moisture distributions obtained from SAR-images (Synthetic Aperture Radar) were used to derive the spatial distribution of soil parameters covering the full simulation domain. Doing so helped us to assess the impact of different soil parameter sources on the modelled groundwater recharge levels. Groundwater recharge was simulated in monthly time steps using the ensemble approach and analysed in its spatial and temporal variability. The soil parameters originating from both sources led to very similar groundwater recharge rates, proving that soil parameters derived from SAR images may replace traditionally used soil maps in regions where soil maps are sparse or missing. Additionally, we showed that the variance in different GCM-RCMs influences the projected magnitude of future groundwater recharge change significantly more than the variance in the soil parameter distributions derived from the two different sources. For the period between 1950 and 2100, climate change impacts based on the climate model ensemble indicated that overall groundwater recharge will possibly show a low to moderate decrease in the Thau catchment. However, as no clear trend resulted from the ensemble simulations, reliable recommendations for adapting the regional groundwater management to changed available groundwater volumes could not be derived. Copyright © 2015 Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kremer, R.G.

Three papers are presented that focus on remote sensing and ecosystem simulation modeling of the Intermountain Northwest sagebrush-steppe ecosystem. The first utilizes Advanced Very High Resolution Radiometer data to derive seasonal greenness indices of three pre-dominant vegetation communities in south-central WashingtoN. Temporal signatures were statistically separated, and used to create a classification for the three communities by integrating Normalized Difference Vegetation Indices over the growing season. The classification accuracy was 75% when compared to 53 ground-truthed sites, but was less accurate (62%) in a more topographically variable region. The second paper develops a logic for treating the intermountain sagebrush-steepe asmore » a mosaic of distinct, hydrologically partitioned vegetation communities, and identifies critical ecophysiological considerations for process modeling of arid ecosystems. Soil water and nutrient dynamics of an ecosystem process model were modified to simulate productivity and seasonal water use patterns in Artemisia, Agropyron, and Bromus communities for the same study site. 60 year simulations maintained steady state vegetation productivity while predicting soil moisture content for 65 dates in 1992 with R[sup 2] values ranging from 0.93 to 0.98. In the third paper, the model was used to derive projections of the response of the ecosystem to natural and general circulation model (GCM)-predicted climate variability. Simulations predicted the adaptability of a less productive, invasive grass community (Bromus) to climate change, while a native sagebrush (Artemisia) community does not survive the increased temperatures of the GCM climates. High humidity deficits and greater maintenance respiration costs associated with increased temperatures limit the ability of the sagebrush community to support a relatively high biomass, and substantial increases in soil water storage and subsurface outflow occur was the vegetation senesces.« less

Mapping the Martian Meteorology

NASA Technical Reports Server (NTRS)

Allison, Michael; Ross, J. D.; Soloman, N.

1999-01-01

The Mars-adapted version of the NASA/GISS general circulation model (GCM) has been applied to the hourly/daily simulation of the planet's meteorology over several seasonal orbits. The current running version of the model includes a diurnal solar cycle, CO2 sublimation, and a mature parameterization of upper level wave drag with a vertical domain extending from the surface up to the 6 micro b level. The benchmark simulations provide a four-dimensional archive for the comparative evaluation of various schemes for the retrieval of winds from anticipated polar orbiter measurements of temperatures by the Pressure Modulator Infrared Radiometer.

Poster 17: Methane storms as a driver of Titan's dune orientation.

NASA Astrophysics Data System (ADS)

Charnay, Benjamin; Barth, Erika; Rafkin, Scot; Narteau, Clement; Lebonnois, Sebastien; Rodriguez, Sebastien; Courech Du Pont, Sylvain; Lucas, Antoine

2016-06-01

Titan's equatorial regions are covered by eastward oriented linear dunes [1,2]. This direction is opposite to mean surface winds simulated by Global Climate Models (GCMs) at these latitudes, oriented westward as trade winds on Earth. We propose that Titan's dune orientation is actually determined by equinoctial tropical methane storms producing a coupling with superrotation and dune formation [3]. Using meso-scale simulations of convective methane clouds [4] with a GCM wind profile featuring the superrotation [5,6], we show that Titan's storms should produce fast eastward gust fronts above the surface. Such gusts dominate the aeolian transport. Using GCM wind calculations and analogies with terrestrial dune fields [7], we show that Titan's dune propagation occurs eastward under these conditions. Finally, this scenario combining global circulation winds and methane storms can explain other major features of Titan's dunes as the divergence from the equator or the dune size and spacing. It also implies an equatorial origin of Titan's dune sand and a possible occurence of dust storms.

Modelling of Titan's middle atmosphere with the IPSL climate model

NASA Astrophysics Data System (ADS)

Vatant d'Ollone, Jan; Lebonnois, Sébastien; Guerlet, Sandrine

2017-04-01

Titan's 3-dimensional Global Climate Model developed at the Institute Pierre-Simon Laplace has already demonstrated its efficiency to reproduce and interpret many features of the Saturnian moon's climate (e.g. Lebonnois et al., 2012). However, it suffered from limits at the top of the model, with temperatures far warmer than the observations and no stratopause simulated. To interpret Cassini's overall observations of seasonal effects in the middle atmosphere (e.g. Vinatier et al., 2015), a satisfying modelling of the temperature profile in this region was first required. Latest developments in the GCM now enable a correct modelling of the temperature profile in the middle atmosphere. In particular, a new, more flexible, radiative transfer scheme based on correlated-k method has been set up, using up-to-date spectroscopic data. Special emphasis is put on the too warm upper stratospheric temperatures in the former model that were due to the absence of the infrared ν4 methane line (7.7 μm) in the radiative transfer. While it was usually neglected in the tropospheric radiative models, this line has a strong cooling effect in Titan's stratospheric conditions and cannot be neglected. In this new version of the GCM, the microphysical model is temporarily switched off and we use a mean profile for haze opacity (Lavvas et al., 2010). The circulation in the middle atmosphere is significantly improved by this new radiative transfer. The new 3-D simulations also show an interesting feature in the modeled vertical profile of the zonal wind as the minimum in low stratosphere is now closer to the observations. Works in progress such as the vertical extension and the computation of the radiative effect of the seasonal variations of trace components will also be presented. - Lavvas P. et al., 2010. Titan's vertical aerosol structure at the Huygens landing site: Constraints on particle size, density, charge, and refractive index. Icarus 210, 832-842. - Lebonnois S. et al., 2012. Titan Global Climate Model: new 3-dimensional version of the IPSL Titan GCM. Icarus 218, 707-722. - Vinatier S. et al., 2015. Seasonal variations in Titan's middle atmosphere during the northern spring derived from Cassini/CIRS observations. Icarus 250, 95-115.

Space-based Doppler lidar sampling strategies: Algorithm development and simulated observation experiments

NASA Technical Reports Server (NTRS)

Emmitt, G. D.; Wood, S. A.; Morris, M.

1990-01-01

Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.

Studies of regional-scale climate variability and change. Hidden Markov models and coupled ocean-atmosphere modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghil, M.; Kravtsov, S.; Robertson, A. W.

2008-10-14

This project was a continuation of previous work under DOE CCPP funding, in which we had developed a twin approach of probabilistic network (PN) models (sometimes called dynamic Bayesian networks) and intermediate-complexity coupled ocean-atmosphere models (ICMs) to identify the predictable modes of climate variability and to investigate their impacts on the regional scale. We had developed a family of PNs (similar to Hidden Markov Models) to simulate historical records of daily rainfall, and used them to downscale GCM seasonal predictions. Using an idealized atmospheric model, we had established a novel mechanism through which ocean-induced sea-surface temperature (SST) anomalies might influencemore » large-scale atmospheric circulation patterns on interannual and longer time scales; we had found similar patterns in a hybrid coupled ocean-atmosphere-sea-ice model. The goal of the this continuation project was to build on these ICM results and PN model development to address prediction of rainfall and temperature statistics at the local scale, associated with global climate variability and change, and to investigate the impact of the latter on coupled ocean-atmosphere modes. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling together with the development of associated software; new intermediate coupled models; a new methodology of inverse modeling for linking ICMs with observations and GCM results; and, observational studies of decadal and multi-decadal natural climate results, informed by ICM results.« less

Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

NASA Astrophysics Data System (ADS)

Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

2017-10-01

The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.

Impacts of the cloud structure's latitudinal variation on the general circulation of the Venus atmosphere as modeled by the LMD-GCM

NASA Astrophysics Data System (ADS)

Garate-Lopez, Itziar; Lebonnois, Sébastien

2017-04-01

A new simulation of Venus atmospheric circulation obtained with the LMD Venus GCM is described and the impact of cloud's latitudinal structure on the general circulation is analyzed. The model used here is based on that presented in Lebonnois et al. (2016). However, in the present simulation we consider the latitudinal variation of the cloud structure (Haus et al., 2014) both for the solar heating and to compute the infrared net-exchange rate matrix used in the radiative transfer module. The new cloud treatment affects mainly the balance in the angular momentum and the zonal wind distribution. Consequently, the agreement between the vertical profile of the modeled mean zonal wind and the profiles measured by different probes, is clearly improved from previous simulations in which zonal winds below the clouds were weak (roughly half the observed values). Moreover, the equatorial jet obtained at the base of the cloud deck is now more consistent with the observations. In Lebonnois et al. (2016) it was too strong compared to mid-latitudes, but in the present simulation the equatorial jet is less intense than the mid-latitude jets, in concordance with cloud-tracking measurements (Hueso et al., 2015). Since the atmospheric waves play a crucial role in the angular momentum budget of the Venus's atmospheric circulation, we analyze the wave activity by means of the Fast Fourier Transform technique studying the frequency spectrum of temperature, zonal and meridional wind fields. Modifications in the activity of the different types of waves present in the Venusian atmosphere compared to Lebonnois et al. (2016) are discussed, in terms of horizontal and vertical transport of the angular momentum by diurnal and semi-diurnal tides, barotropic and baroclinic waves, and Rossby and Kelvin type waves. Haus R., Kappel D. and Arnold G., 2014. Atmospheric thermal structure and cloud features in the southern hemisphere of Venus as retrieved from VIRTIS/VEX radiation measurements. Icarus 232, 232-248. Hueso R., Peralta J., Garate-Lopez I., et al., 2015. Six years of Venus winds at the upper cloud level from UV, visible and near infrared observations from VIRTIS on Venus express. Planet. Space Sci. 113-114, 78-99. Lebonnois S., Sugimoto N., and Gilli G., 2016. Wave analysis in the atmosphere of Venus below 100km altitude, simulated by the LMD Venus GCM. Icarus 278, 38-51.

Monte-Carlo Geant4 numerical simulation of experiments at 247-MeV proton microscope

NASA Astrophysics Data System (ADS)

Kantsyrev, A. V.; Skoblyakov, A. V.; Bogdanov, A. V.; Golubev, A. A.; Shilkin, N. S.; Yuriev, D. S.; Mintsev, V. B.

2018-01-01

A radiographic facility for an investigation of fast dynamic processes with areal density of targets up to 5 g/cm2 is under development on the basis of high-current proton linear accelerator at the Institute for Nuclear Research (Troitsk, Russia). A virtual model of the proton microscope developed in a software toolkit Geant4 is presented in the article. Fullscale Monte-Carlo numerical simulation of static radiographic experiments at energy of a proton beam 247 MeV was performed. The results of simulation of proton radiography experiments with static model of shock-compressed xenon are presented. The results of visualization of copper and polymethyl methacrylate step wedges static targets also described.

Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events

NASA Astrophysics Data System (ADS)

Singh, Ankita; Ghosh, Kripan; Mohanty, U. C.

2018-03-01

The sub-seasonal variation of Indian summer monsoon rainfall highly impacts Kharif crop production in comparison with seasonal total rainfall. The rainfall frequency and intensity corresponding to various rainfall events are found to be highly related to crop production and therefore, the predictability of such events are considered to be diagnosed. Daily rainfall predictions are made available by one of the coupled dynamical model National Centers for Environmental Prediction Climate Forecast System (NCEPCFS). A large error in the simulation of daily rainfall sequence influences to take up a bias correction and for that reason, two approaches are used. The bias-corrected GCM is able to capture the inter-annual variability in rainfall events. Maximum prediction skill of frequency of less rainfall (LR) event is observed during the month of September and a similar result is also noticed for moderate rainfall event with maximum skill over the central parts of the country. On the other hand, the impact of rainfall weekly rainfall intensity is evaluated against the Kharif rice production. It is found that weekly rainfall intensity during July is having a significant impact on Kharif rice production, but the corresponding skill was found very low in GCM. The GCM are able to simulate the less and moderate rainfall frequency with significant skill.

AI-based (ANN and SVM) statistical downscaling methods for precipitation estimation under climate change scenarios

NASA Astrophysics Data System (ADS)

Mehrvand, Masoud; Baghanam, Aida Hosseini; Razzaghzadeh, Zahra; Nourani, Vahid

2017-04-01

Since statistical downscaling methods are the most largely used models to study hydrologic impact studies under climate change scenarios, nonlinear regression models known as Artificial Intelligence (AI)-based models such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used to spatially downscale the precipitation outputs of Global Climate Models (GCMs). The study has been carried out using GCM and station data over GCM grid points located around the Peace-Tampa Bay watershed weather stations. Before downscaling with AI-based model, correlation coefficient values have been computed between a few selected large-scale predictor variables and local scale predictands to select the most effective predictors. The selected predictors are then assessed considering grid location for the site in question. In order to increase AI-based downscaling model accuracy pre-processing has been developed on precipitation time series. In this way, the precipitation data derived from various GCM data analyzed thoroughly to find the highest value of correlation coefficient between GCM-based historical data and station precipitation data. Both GCM and station precipitation time series have been assessed by comparing mean and variances over specific intervals. Results indicated that there is similar trend between GCM and station precipitation data; however station data has non-stationary time series while GCM data does not. Finally AI-based downscaling model have been applied to several GCMs with selected predictors by targeting local precipitation time series as predictand. The consequences of recent step have been used to produce multiple ensembles of downscaled AI-based models.

Using an Integrated Surface Water - Groundwater Flow Model for Evaluating the Hydrologic Impacts of Historic and Potential Future Dry Periods on Simulated Water Budgets in the Santa Rosa Plain Watershed, Northern California, USA

NASA Astrophysics Data System (ADS)

Hevesi, J. A.; Woolfenden, L. R.; Nishikawa, T.

2014-12-01

Communities in the Santa Rosa Plain watershed (SRPW), Sonoma County, CA, USA are experiencing increasing demand for limited water resources. Streamflow in the SRPW is runoff dominated; however, groundwater also is an important resource in the basin. The watershed has an area of 262 mi2 that includes natural, agricultural, and urban land uses. To evaluate the hydrologic system, an integrated hydrologic model was developed using the U.S. Geological Survey coupled groundwater and surface-water flow model, GSFLOW. The model uses a daily time step and a grid-based discretization of the SRPW consisting of 16,741 10-acre cells for 8 model layers to simulate all water budget components of the surface and subsurface hydrologic system. Simulation results indicate significant impacts on streamflow and recharge in response to the below average precipitation during the dry periods. The recharge and streamflow distributions simulated for historic dry periods were compared to future dry periods projected from 4 GCM realizations (two different GCMs and two different CO2 forcing scenarios) for the 21st century, with the dry periods defined as 3 consecutive years of below average precipitation. For many of the projected dry periods, the decreases in recharge and streamflow were greater than for the historic dry periods due to a combination of lower precipitation and increases in simulated evapotranspiration for the warmer 21st century projected by the GCM realizations. The greatest impact on streamflow for both historic and projected future dry periods is the diminished baseflow from late spring to early fall, with an increase in the percentage of intermittent and dry stream reaches. The results indicate that the coupled model is a useful tool for water managers to better understand the potential effects of future dry periods on spatially and temporally distributed streamflow and recharge, as well as other components of the water budget.

Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

NASA Astrophysics Data System (ADS)

Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

2017-12-01

Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of vegetation change from the past 1200 years. Accounting for driver uncertainty in model evaluation can help determine the relative influence of structural versus parameterization errors in ecosystem modelings.

Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1990-01-01

Broad-band parameterizations for atmospheric radiative transfer were developed for clear and cloudy skies. These were in the shortwave and longwave regions of the spectrum. These models were compared with other models in an international effort called ICRCCM (Intercomparison of Radiation Codes for Climate Models). The radiation package developed was used for simulations of a General Circulation Model (GCM). A synopsis is provided of the research accomplishments in the two areas separately. Details are available in the published literature.

A conditional Granger causality model approach for group analysis in functional MRI

PubMed Central

Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J.; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M.; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

2011-01-01

Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed for identifying effective connectivity in the human brain with functional MR imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pairwise GCM has commonly been applied based on single voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of an fMRI data with GCM. To compare the effectiveness of our approach with traditional pairwise GCM models, we applied a well-established conditional GCM to pre-selected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis (ICA) of an fMRI dataset in the temporal domain. Datasets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM detected brain activation regions in the emotion related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state dataset, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network (DMN) that can be characterized as both afferent and efferent influences on the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive (MVAR) model can achieve greater accuracy in detecting network connectivity than the widely used pairwise GCM, and this group analysis methodology can be quite useful to extend the information obtainable in fMRI. PMID:21232892

Simulation of South-Asian Summer Monsoon in a GCM

NASA Astrophysics Data System (ADS)

Ajayamohan, R. S.

2007-10-01

Major characteristics of Indian summer monsoon climate are analyzed using simulations from the upgraded version of Florida State University Global Spectral Model (FSUGSM). The Indian monsoon has been studied in terms of mean precipitation and low-level and upper-level circulation patterns and compared with observations. In addition, the model's fidelity in simulating observed monsoon intraseasonal variability, interannual variability and teleconnection patterns is examined. The model is successful in simulating the major rainbelts over the Indian monsoon region. However, the model exhibits bias in simulating the precipitation bands over the South China Sea and the West Pacific region. Seasonal mean circulation patterns of low-level and upper-level winds are consistent with the model's precipitation pattern. Basic features like onset and peak phase of monsoon are realistically simulated. However, model simulation indicates an early withdrawal of monsoon. Northward propagation of rainbelts over the Indian continent is simulated fairly well, but the propagation is weak over the ocean. The model simulates the meridional dipole structure associated with the monsoon intraseasonal variability realistically. The model is unable to capture the observed interannual variability of monsoon and its teleconnection patterns. Estimate of potential predictability of the model reveals the dominating influence of internal variability over the Indian monsoon region.

Comparing Apples to Apples: Paleoclimate Model-Data comparison via Proxy System Modeling

NASA Astrophysics Data System (ADS)

Dee, Sylvia; Emile-Geay, Julien; Evans, Michael; Noone, David

2014-05-01

The wealth of paleodata spanning the last millennium (hereinafter LM) provides an invaluable testbed for CMIP5-class GCMs. However, comparing GCM output to paleodata is non-trivial. High-resolution paleoclimate proxies generally contain a multivariate and non-linear response to regional climate forcing. Disentangling the multivariate environmental influences on proxies like corals, speleothems, and trees can be complex due to spatiotemporal climate variability, non-stationarity, and threshold dependence. Given these and other complications, many paleodata-GCM comparisons take a leap of faith, relating climate fields (e.g. precipitation, temperature) to geochemical signals in proxy data (e.g. δ18O in coral aragonite or ice cores) (e.g. Braconnot et al., 2012). Isotope-enabled GCMs are a step in the right direction, with water isotopes providing a connector point between GCMs and paleodata. However, such studies are still rare, and isotope fields are not archived as part of LM PMIP3 simulations. More importantly, much of the complexity in how proxy systems record and transduce environmental signals remains unaccounted for. In this study we use proxy system models (PSMs, Evans et al., 2013) to bridge this conceptual gap. A PSM mathematically encodes the mechanistic understanding of the physical, geochemical and, sometimes biological influences on each proxy. To translate GCM output to proxy space, we have synthesized a comprehensive, consistently formatted package of published PSMs, including δ18O in corals, tree ring cellulose, speleothems, and ice cores. Each PSM is comprised of three sub-models: sensor, archive, and observation. For the first time, these different components are coupled together for four major proxy types, allowing uncertainties due to both dating and signal interpretation to be treated within a self-consistent framework. The output of this process is an ensemble of many (say N = 1,000) realizations of the proxy network, all equally plausible under assumed dating uncertainties. We demonstrate the utility of the PSM framework with an integrative multi-PSM simulation. An intermediate-complexity AGCM with isotope physics (SPEEDY-IER, (Molteni, 2003, Dee et al., in prep)) is used to simulate the isotope hydrology and atmospheric response to SSTs derived from the LM PMIP3 integration of the CCSM4 model (Landrum et al., 2012). Relevant dynamical and isotope variables are then used to drive PSMs, emulating a realistic multiproxy network (Emile-Geay et al., 2013). We then ask the following question: given our best knowledge of proxy systems, what aspects of GCM behavior may be validated, and with what uncertainties? We approach this question via a three-tiered 'perfect model' study. A random realization of the simulated proxy data (hereafter 'PaleoObs') is used as a benchmark in the following comparisons: (1) AGCM output (without isotopes) vs. PaleoObs; (2) AGCM output (with isotopes) vs. PaleoObs; (3) coupled AGCM-PSM-simulated proxy ensemble vs. PaleoObs. Enhancing model-data comparison using PSMs highlights uncertainties that may arise from ignoring non-linearities in proxy-climate relationships, or the presence of age uncertainties (as is most typically done is paleoclimate model-data intercomparison). Companion experiments leveraging the 3 sub-model compartmentalization of PSMs allows us to quantify the contribution of each sub-system to the observed model-data discrepancies. We discuss potential repercussions for model-data comparison and implications for validating predictive climate models using paleodata. References Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte, V., Abe-Ouchi, A., Otto-Bliesner, B., Zhao, Y., 06 2012. Evaluation of climate models using palaeoclimatic data. Nature Clim. Change 2 (6), 417-424. URL http://dx.doi.org/10.1038/nclimate1456 Emile-Geay, J., Cobb, K. M., Mann, M. E., Wittenberg, A. T., Apr 01 2013. Estimating central equatorial pacific sst variability over the past millennium. part i: Methodology and validation. Journal of Climate 26 (7), 2302-2328. URL http://search.proquest.com/docview/1350277733?accountid=14749 Evans, M., Tolwinski-Ward, S. E., Thompson, D. M., Anchukaitis, K. J., 2013. Applications of proxy system modeling in high resolution paleoclimatology. Quaternary Science Reviews. URL http://adsabs.harvard.edu/abs/2012QuInt.279U.134E Landrum, L., Otto-Bliesner, B. L., Wahl, E. R., Capotondi, A., Lawrence, P. J., Teng, H., 2012. Last Millennium Climate and Its Variability in CCSM4. Journal of Climate (submitted) Molteni, F., 2003. Atmospheric simulations using a GCM with simplified physical parametrizations. I model climatology and variability in multi-decadal experiments. Climate Dynamics, 175-191

Development of a system emulating the global carbon cycle in Earth system models

NASA Astrophysics Data System (ADS)

Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.

2010-08-01

Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).

Recent Upgrades to the NASA Ames Mars General Circulation Model: Applications to Mars' Water Cycle

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Kahre, M. A.; Haberle, R. M.; Montmessin, F.; Wilson, R. J.; Schaeffer, J.

2008-09-01

We report on recent improvements to the NASA Ames Mars general circulation model (GCM), a robust 3D climate-modeling tool that is state-of-the-art in terms of its physics parameterizations and subgrid-scale processes, and which can be applied to investigate physical and dynamical processes of the present (and past) Mars climate system. The most recent version (gcm2.1, v.24) of the Ames Mars GCM utilizes a more generalized radiation code (based on a two-stream approximation with correlated k's); an updated transport scheme (van Leer formulation); a cloud microphysics scheme that assumes a log-normal particle size distribution whose first two moments are treated as atmospheric tracers, and which includes the nucleation, growth and sedimentation of ice crystals. Atmospheric aerosols (e.g., dust and water-ice) can either be radiatively active or inactive. We apply this version of the Ames GCM to investigate key aspects of the present water cycle on Mars. Atmospheric dust is partially interactive in our simulations; namely, the radiation code "sees" a prescribed distribution that follows the MGS thermal emission spectrometer (TES) year-one measurements with a self-consistent vertical depth scale that varies with season. The cloud microphysics code interacts with a transported dust tracer column whose surface source is adjusted to maintain the TES distribution. The model is run from an initially dry state with a better representation of the north residual cap (NRC) which accounts for both surface-ice and bare-soil components. A seasonally repeatable water cycle is obtained within five Mars years. Our sub-grid scale representation of the NRC provides for a more realistic flux of moisture to the atmosphere and a much drier water cycle consistent with recent spacecraft observations (e.g., Mars Express PFS, corrected MGS/TES) compared to models that assume a spatially uniform and homogeneous north residual polar cap.

Projecting impacts of climate change on water availability using artificial neural network techniques

USGS Publications Warehouse

Swain, Eric D.; Gomez-Fragoso, Julieta; Torres-Gonzalez, Sigfredo

2017-01-01

Lago Loíza reservoir in east-central Puerto Rico is one of the primary sources of public water supply for the San Juan metropolitan area. To evaluate and predict the Lago Loíza water budget, an artificial neural network (ANN) technique is trained to predict river inflows. A method is developed to combine ANN-predicted daily flows with ANN-predicted 30-day cumulative flows to improve flow estimates. The ANN application trains well for representing 2007–2012 and the drier 1994–1997 periods. Rainfall data downscaled from global circulation model (GCM) simulations are used to predict 2050–2055 conditions. Evapotranspiration is estimated with the Hargreaves equation using minimum and maximum air temperatures from the downscaled GCM data. These simulated 2050–2055 river flows are input to a water budget formulation for the Lago Loíza reservoir for comparison with 2007–2012. The ANN scenarios require far less computational effort than a numerical model application, yet produce results with sufficient accuracy to evaluate and compare hydrologic scenarios. This hydrologic tool will be useful for future evaluations of the Lago Loíza reservoir and water supply to the San Juan metropolitan area.

Cloud Condensation Nuclei Prediction Error from Application of Kohler Theory: Importance for the Aerosol Indirect Effect

NASA Technical Reports Server (NTRS)

Sotiropoulou, Rafaella-Eleni P.; Nenes, Athanasios; Adams, Peter J.; Seinfeld, John H.

2007-01-01

In situ observations of aerosol and cloud condensation nuclei (CCN) and the GISS GCM Model II' with an online aerosol simulation and explicit aerosol-cloud interactions are used to quantify the uncertainty in radiative forcing and autoconversion rate from application of Kohler theory. Simulations suggest that application of Koehler theory introduces a 10-20% uncertainty in global average indirect forcing and 2-11% uncertainty in autoconversion. Regionally, the uncertainty in indirect forcing ranges between 10-20%, and 5-50% for autoconversion. These results are insensitive to the range of updraft velocity and water vapor uptake coefficient considered. This study suggests that Koehler theory (as implemented in climate models) is not a significant source of uncertainty for aerosol indirect forcing but can be substantial for assessments of aerosol effects on the hydrological cycle in climatically sensitive regions of the globe. This implies that improvements in the representation of GCM subgrid processes and aerosol size distribution will mostly benefit indirect forcing assessments. Predictions of autoconversion, by nature, will be subject to considerable uncertainty; its reduction may require explicit representation of size-resolved aerosol composition and mixing state.

The zonally averaged transport characteristics of the atmosphere as determined by a general circulation model

NASA Technical Reports Server (NTRS)

Plumb, R. A.

1985-01-01

Two dimensional modeling has become an established technique for the simulation of the global structure of trace constituents. Such models are simpler to formulate and cheaper to operate than three dimensional general circulation models, while avoiding some of the gross simplifications of one dimensional models. Nevertheless, the parameterization of eddy fluxes required in a 2-D model is not a trivial problem. This fact has apparently led some to interpret the shortcomings of existing 2-D models as indicating that the parameterization procedure is wrong in principle. There are grounds to believe that these shortcomings result primarily from incorrect implementations of the predictions of eddy transport theory and that a properly based parameterization may provide a good basis for atmospheric modeling. The existence of these GCM-derived coefficients affords an unprecedented opportunity to test the validity of the flux-gradient parameterization. To this end, a zonally averaged (2-D) model was developed, using these coefficients in the transport parameterization. Results from this model for a number of contrived tracer experiments were compared with the parent GCM. The generally good agreement substantially validates the flus-gradient parameterization, and thus the basic principle of 2-D modeling.

Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

DOE PAGES

Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; ...

2014-11-06

In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Syafrina, A. H.; Zalina, M. D.; Juneng, L.

2014-09-01

A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10-40 years.

Holocene constraints on simulated tropical Pacific climate

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Cobb, K. M.; Carre, M.; Braconnot, P.; Leloup, J.; Zhou, Y.; Harrison, S. P.; Correge, T.; Mcgregor, H. V.; Collins, M.; Driscoll, R.; Elliot, M.; Schneider, B.; Tudhope, A. W.

2015-12-01

The El Niño-Southern Oscillation (ENSO) influences climate and weather worldwide, so uncertainties in its response to external forcings contribute to the spread in global climate projections. Theoretical and modeling studies have argued that such forcings may affect ENSO either via the seasonal cycle, the mean state, or extratropical influences, but these mechanisms are poorly constrained by the short instrumental record. Here we synthesize a pan-Pacific network of high-resolution marine biocarbonates spanning discrete snapshots of the Holocene (past 10, 000 years of Earth's history), which we use to constrain a set of global climate model (GCM) simulations via a forward model and a consistent treatment of uncertainty. Observations suggest important reductions in ENSO variability throughout the interval, most consistently during 3-5 kyBP, when approximately 2/3 reductions are inferred. The magnitude and timing of these ENSO variance reductions bear little resemblance to those sim- ulated by GCMs, or to equatorial insolation. The central Pacific witnessed a mid-Holocene increase in seasonality, at odds with the reductions simulated by GCMs. Finally, while GCM aggregate behavior shows a clear inverse relationship between seasonal amplitude and ENSO-band variance in sea-surface temperature, in agreement with many previous studies, such a relationship is not borne out by these observations. Our synthesis suggests that tropical Pacific climate is highly variable, but exhibited millennia-long periods of reduced ENSO variability whose origins, whether forced or unforced, contradict existing explanations. It also points to deficiencies in the ability of current GCMs to simulate forced changes in the tropical Pacific seasonal cycle and its interaction with ENSO, highlighting a key area of growth for future modeling efforts.

Interannual Variability of Martian Global Dust Storms: Simulations with a Low-Order Model of the General Circulation

NASA Technical Reports Server (NTRS)

Pankine, A. A.; Ingersoll, Andrew P.

2002-01-01

We present simulations of the interannual variability of martian global dust storms (GDSs) with a simplified low-order model (LOM) of the general circulation. The simplified model allows one to conduct computationally fast long-term simulations of the martian climate system. The LOM is constructed by Galerkin projection of a 2D (zonally averaged) general circulation model (GCM) onto a truncated set of basis functions. The resulting LOM consists of 12 coupled nonlinear ordinary differential equations describing atmospheric dynamics and dust transport within the Hadley cell. The forcing of the model is described by simplified physics based on Newtonian cooling and Rayleigh friction. The atmosphere and surface are coupled: atmospheric heating depends on the dustiness of the atmosphere, and the surface dust source depends on the strength of the atmospheric winds. Parameters of the model are tuned to fit the output of the NASA AMES GCM and the fit is generally very good. Interannual variability of GDSs is possible in the IBM, but only when stochastic forcing is added to the model. The stochastic forcing could be provided by transient weather systems or some surface process such as redistribution of the sand particles in storm generating zones on the surface. The results are sensitive to the value of the saltation threshold, which hints at a possible feedback between saltation threshold and dust storm activity. According to this hypothesis, erodable material builds up its a result of a local process, whose effect is to lower the saltation threshold until a GDS occurs. The saltation threshold adjusts its value so that dust storms are barely able to occur.

Photochemical numerics for global-scale modeling: Fidelity and GCM testing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elliott, S.; Jim Kao, Chih-Yue; Zhao, X.

1995-03-01

Atmospheric photochemistry lies at the heart of global-scale pollution problems, but it is a nonlinear system embedded in nonlinear transport and so must be modeled in three dimensions. Total earth grids are massive and kinetics require dozens of interacting tracers, taxing supercomputers to their limits in global calculations. A matrix-free and noniterative family scheme is described that permits chemical step sizes an order of magnitude or more larger than time constants for molecular groupings, in the 1-h range used for transport. Families are partitioned through linearized implicit integrations that produce stabilizing species concentrations for a mass-conserving forward solver. The kineticsmore » are also parallelized by moving geographic loops innermost and changes in the continuity equations are automated through list reading. The combination of speed, parallelization and automation renders the programs naturally modular. Accuracy lies within 1% for all species in week-long fidelity tests. A 50-species, 150-reaction stratospheric module tested in a spectral GCM benchmarks at 10 min CPU time per day and agrees with lower-dimensionality simulations. Tropospheric nonmethane hydrocarbon chemistry will soon be added, and inherently three-dimensional phenomena will be investigated both decoupled from dynamics and in a complete chemical GCM. 225 refs., 11 figs., 2 tabs.« less

Importance of ensembles in projecting regional climate trends

NASA Astrophysics Data System (ADS)

Arritt, Raymond; Daniel, Ariele; Groisman, Pavel

2016-04-01

We have performed an ensemble of simulations using RegCM4 to examine the ability to reproduce observed trends in precipitation intensity and to project future changes through the 21st century for the central United States. We created a matrix of simulations over the CORDEX North America domain for 1950-2099 by driving the regional model with two different global models (HadGEM2-ES and GFDL-ESM2M, both for RCP8.5), by performing simulations at both 50 km and 25 km grid spacing, and by using three different convective parameterizations. The result is a set of 12 simulations (two GCMs by two resolutions by three convective parameterizations) that can be used to systematically evaluate the influence of simulation design on predicted precipitation. The two global models were selected to bracket the range of climate sensitivity in the CMIP5 models: HadGEM2-ES has the highest ECS of the CMIP5 models, while GFDL-ESM2M has one of the lowestt. Our evaluation metrics differ from many other RCM studies in that we focus on the skill of the models in reproducing past trends rather than the mean climate state. Trends in frequency of extreme precipitation (defined as amounts exceeding 76.2 mm/day) for most simulations are similar to the observed trend but with notable variations depending on RegCM4 configuration and on the driving GCM. There are complex interactions among resolution, choice of convective parameterization, and the driving GCM that carry over into the future climate projections. We also note that biases in the current climate do not correspond to biases in trends. As an example of these points the Emanuel scheme is consistently "wet" (positive bias in precipitation) yet it produced the smallest precipitation increase of the three convective parameterizations when used in simulations driven by HadGEM2-ES. However, it produced the largest increase when driven by GFDL-ESM2M. These findings reiterate that ensembles using multiple RCM configurations and driving GCMs are essential for projecting regional climate change, even when a single RCM is used. This research was sponsored by the U.S. Department of Agriculture National Institute of Food and Agriculture.

The annual cycle of stratospheric water vapor in a general circulation model

NASA Technical Reports Server (NTRS)

Mote, Philip W.

1995-01-01

The application of general circulation models (GCM's) to stratospheric chemistry and transport both permits and requires a thorough investigation of stratospheric water vapor. The National Center for Atmospheric Research has redesigned its GCM, the Community Climate Model (CCM2), to enable studies of the chemistry and transport of tracers including water vapor; the importance of water vapor to the climate and chemistry of the stratosphere requires that it be better understood in the atmosphere and well represented in the model. In this study, methane is carried as a tracer and converted to water; this simple chemistry provides an adequate representation of the upper stratospheric water vapor source. The cold temperature bias in the winter polar stratosphere, which the CCM2 shares with other GCM's, produces excessive dehydration in the southern hemisphere, but this dry bias can be ameliorated by setting a minimum vapor pressure. The CCM2's water vapor distribution and seasonality compare favorably with observations in many respects, though seasonal variations including the upper stratospheric semiannual oscillation are generally too small. Southern polar dehydration affects midlatitude water vapor mixing ratios by a few tenths of a part per million, mostly after the demise of the vortex. The annual cycle of water vapor in the tropical and northern midlatitude lower stratosphere is dominated by drying at the tropical tropopause. Water vapor has a longer adjustment time than methane and had not reached equilibrium at the end of the 9 years simulated here.

A GCM simulation study of the influence of Saharan evapotranspiration and surface-albedo anomalies on July circulation and rainfall

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Molod, A.

1988-01-01

The influence of surface albedo and evapotranspiration anomalies that could result from the hypothetical semiarid vegetation over North Africa on its July circulation and rainfall is examined using the Goddard Laboratory for Atmospheres GCM. It is shown that increased soil moisture and its dependent evapotranspiration produces a cooler and moister PBL over North Africa that is able to support enhanced moist convection and rainfall in Sahel and southern Sahara. It is found that lower surface albedo yields even higher moist static energy in the PBL and enhances the local moist convection and rainfall. Modifying the rain-evaporation parameterization in the model produces changes in the hydrological cycle and rainfall anomalies in distant regions. The effects of different falling rain parameterizations are discussed.

Data-Conditioned Distributions of Groundwater Recharge Under Climate Change Scenarios

NASA Astrophysics Data System (ADS)

McLaughlin, D.; Ng, G. C.; Entekhabi, D.; Scanlon, B.

2008-12-01

Groundwater recharge is likely to be impacted by climate change, with changes in precipitation amounts altering moisture availability and changes in temperature affecting evaporative demand. This could have major implications for sustainable aquifer pumping rates and contaminant transport into groundwater reservoirs in the future, thus making predictions of recharge under climate change very important. Unfortunately, in dry environments where groundwater resources are often most critical, low recharge rates are difficult to resolve due to high sensitivity to modeling and input errors. Some recent studies on climate change and groundwater have considered recharge using a suite of general circulation model (GCM) weather predictions, an obvious and key source of uncertainty. This work extends beyond those efforts by also accounting for uncertainty in other land-surface model inputs in a probabilistic manner. Recharge predictions are made using a range of GCM projections for a rain-fed cotton site in the semi-arid Southern High Plains region of Texas. Results showed that model simulations using a range of unconstrained literature-based parameter values produce highly uncertain and often misleading recharge rates. Thus, distributional recharge predictions are found using soil and vegetation parameters conditioned on current unsaturated zone soil moisture and chloride concentration observations; assimilation of observations is carried out with an ensemble importance sampling method. Our findings show that the predicted distribution shapes can differ for the various GCM conditions considered, underscoring the importance of probabilistic analysis over deterministic simulations. The recharge predictions indicate that the temporal distribution (over seasons and rain events) of climate change will be particularly critical for groundwater impacts. Overall, changes in recharge amounts and intensity were often more pronounced than changes in annual precipitation and temperature, thus suggesting high susceptibility of groundwater systems to future climate change. Our approach provides a probabilistic sensitivity analysis of recharge under potential climate changes, which will be critical for future management of water resources.

The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)

NASA Astrophysics Data System (ADS)

Chepfer, H.; Bony, S.; Winker, D.; Cesana, G.; Dufresne, J. L.; Minnis, P.; Stubenrauch, C. J.; Zeng, S.

2010-01-01

This article presents the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate the cloudiness simulated by general circulation models (GCMs). For this purpose, Cloud-Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model cloud cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then cloud diagnostics are inferred from these profiles: vertical distribution of cloud fraction, horizontal distribution of low, middle, high, and total cloud fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January-March 2007-2008 and June-August 2006-2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for cloud detection can modify the cloud fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low-level cloud fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the cloud types encountered in different regions. The GOCCP high-level cloud amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low-level and middle-level cloud fractions are larger than those derived from passive remote sensing (International Satellite Cloud Climatology Project, Moderate-Resolution Imaging Spectroradiometer-Cloud and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS-Laboratoire de Météorologie Dynamique) because the latter only provide information on the uppermost cloud layer.

Meeting the Next Generation Science Standards Through "Rediscovered" Climate Model Experiments

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2013-12-01

Since the Educational Global Climate Model (EdGCM) Project made its debut in January 2005, over 150 institutions have employed EdGCM software for a variety of uses ranging from short lab exercises to semester-long and year-long thesis projects. The vast majority of these EdGCM adoptees have been at the undergraduate and graduate levels, with few users at the K-12 level. The K-12 instructors who have worked with EdGCM in professional development settings have commented that, although EdGCM can be used to illustrate a number of the Disciplinary Core Ideas and connects to many of the Common Core State Standards across subjects and grade levels, significant hurdles preclude easy integration of EdGCM into their curricula. Time constraints, a scarcity of curriculum materials, and classroom technology are often mentioned as obstacles in providing experiences to younger grade levels in realistic climate modeling research. Given that the NGSS incorporates student performance expectations relating to Earth System Science, and to climate science and the human dimension in particular, we feel that a streamlined version of EdGCM -- one that eliminates the need to run the climate model on limited computing resources, and provides a more guided climate modeling experience -- would be highly beneficial for the K-12 community. This new tool currently under development, called EzGCM, functions through a browser interface, and presents "rediscovery experiments" that allow students to do their own exploration of model output from published climate experiments, or from sensitivity experiments designed to illustrate how climate models as well as the climate system work. The experiments include background information and sample questions, with more extensive notes for instructors so that the instructors can design their own reflection questions or follow-on activities relating to physical or human impacts, as they choose. An added benefit of the EzGCM tool is that, like EdGCM, it helps illustrate the process of doing research on a complex topic, in a way that builds upon earlier experiences in inquiry-based learning. By having students work through a multi-stage process that requires them to plan several steps ahead, through data processing, analysis and interpretation, they learn how to do research in addition to improving their understanding of climate change.

GCM Simulation of the Large-scale North American Monsoon Including Water Vapor Tracer Diagnostics

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Walker, Gregory; Schubert, Siegfried D.; Sud, Yogesh; Atlas, Robert M. (Technical Monitor)

2001-01-01

The geographic sources of water for the large-scale North American monsoon in a GCM are diagnosed using passive constituent tracers of regional water'sources (Water Vapor Tracers, WVT). The NASA Data Assimilation Office Finite Volume (FV) GCM was used to produce a 10-year simulation (1984 through 1993) including observed sea surface temperature. Regional and global WVT sources were defined to delineate the surface origin of water for precipitation in and around the North American i'vionsoon. The evolution of the mean annual cycle and the interannual variations of the monsoonal circulation will be discussed. Of special concern are the relative contributions of the local source (precipitation recycling) and remote sources of water vapor to the annual cycle and the interannual variation of warm season precipitation. The relationships between soil water, surface evaporation, precipitation and precipitation recycling will be evaluated.

Transport properties and equation of state for HCNO mixtures in and beyond the warm dense matter regime

DOE PAGES

Ticknor, Christopher; Collins, Lee A.; Kress, Joel D.

2015-08-04

We present simulations of a four component mixture of HCNO with orbital free molecular dynamics (OFMD). These simulations were conducted for 5–200 eV with densities ranging between 0.184 and 36.8 g/cm 3. We extract the equation of state from the simulations and compare to average atom models. We found that we only need to add a cold curve model to find excellent agreement. In addition, we studied mass transport properties. We present fits to the self-diffusion and shear viscosity that are able to reproduce the transport properties over the parameter range studied. We compare these OFMD results to models basedmore » on the Coulomb coupling parameter and one-component plasmas.« less

Thermosphere-Ionosphere-Mesosphere Modeling Using the TIE-GCM, TIME-GCM, and WACCM That Will Lead to the Development of a Seamless Model of the Whole Atmosphere

DTIC Science & Technology

2006-09-30

disturbances from the lower atmosphere and ocean affect the upper atmosphere and how this variability interacts with the variability generated by solar and...represents “ general circulation model.” Both models include self-consistent ionospheric electrodynamics, that is, a calculation of the electric fields...and currents generated by the ionospheric dynamo, and consideration of their effects on the neutral dynamics. The TIE-GCM is used for studies that

A Lagrangian analysis of a sudden stratospheric warming - Comparison of a model simulation and LIMS observations

NASA Technical Reports Server (NTRS)

Pierce, R. B.; Remsberg, Ellis E.; Fairlie, T. D.; Blackshear, W. T.; Grose, William L.; Turner, Richard E.

1992-01-01

Lagrangian area diagnostics and trajectory techniques are used to investigate the radiative and dynamical characteristics of a spontaneous sudden warming which occurred during a 2-yr Langley Research Center model simulation. The ability of the Langley Research Center GCM to simulate the major features of the stratospheric circulation during such highly disturbed periods is illustrated by comparison of the simulated warming to the observed circulation during the LIMS observation period. The apparent sink of vortex area associated with Rossby wave-breaking accounts for the majority of the reduction of the size of the vortex and also acts to offset the radiatively driven increase in the area occupied by the 'surf zone'. Trajectory analysis of selected material lines substantiates the conclusions from the area diagnostics.

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

NASA Technical Reports Server (NTRS)

Yao, Mao-Sung; Cheng, Ye

2013-01-01

The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

Modeling CO 2 ice clouds with a Mars Global Climate Model

NASA Astrophysics Data System (ADS)

Audouard, Joachim; Määttänen, Anni; Listowski, Constantino; Millour, Ehouarn; Forget, Francois; Spiga, Aymeric

2016-10-01

Since the first claimed detection of CO2 ice clouds by the Mariner campaign (Herr and Pimentel, 1970), more recent observations and modelling works have put new constraints concerning their altitude, region, time and mechanisms of formation (Clancy and Sandor, 1998; Montmessin et al., 2007; Colaprete et al., 2008; Määttänen et al., 2010; Vincendon et al., 2011; Spiga et al. 2012; Listowski et al. 2014). CO2 clouds are observed at the poles at low altitudes (< 20 km) during the winter and at high altitudes (60-110 km) in the equatorial regions during the first half of the year. However, Martian CO2 clouds's variability and dynamics remain somehow elusive.Towards an understanding of Martian CO2 clouds and especially of their precise radiative impact on the climate throughout the history of the planet, including their formation and evolution in a Global Climate Model (GCM) is necessary.Adapting the CO2 clouds microphysics modeling work of Listowski et al. (2013; 2014), we aim at implementing a complete CO2 clouds scheme in the GCM of the Laboratoire de Météorologie Dynamique (LMD, Forget et al., 1999). It covers CO2 microphysics, growth, evolution and dynamics with a methodology inspired from the water ice clouds scheme recently included in the LMD GCM (Navarro et al., 2014).Two main factors control the formation and evolution of CO2 clouds in the Martian atmosphere: sufficient supersaturation of CO2 is needed and condensation nuclei must be available. Topography-induced gravity-waves (GW) are expected to propagate to the upper atmosphere where they produce cold pockets of supersaturated CO2 (Spiga et al., 2012), thus allowing the formation of clouds provided enough condensation nuclei are present. Such supersaturations have been observed by various instruments, in situ (Schofield et al., 1997) and from orbit (Montmessin et al., 2006, 2011; Forget et al., 2009).Using a GW-induced temperature profile and the 1-D version of the GCM, we simulate the formation of CO2 clouds in the mesosphere and investigate the sensitivity of our microphysics scheme. First results and steps towards the integration in the 3-D GCM will be presented and discussed at the conference.This work is funded by the Laboratory of Excellence ESEP.

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

NASA Astrophysics Data System (ADS)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

Evaluation of WRF Model Against Satellite and Field Measurements During ARM March 2000 IOP

NASA Astrophysics Data System (ADS)

Wu, J.; Zhang, M.

2003-12-01

Meso-scale WRF model is employed to simulate the organization of clouds related with the cyclogenesis occurred during March 1-4, 2000 over ARM SGP CART site. Qualitative comparisons of simulated clouds with GOES8 satellite images show that the WRF model can capture the main features of clouds related with the cyclogenesis. The simulated precipitation patterns also match the Radar reflectivity images well. Further evaluation of the simulated features on GCM grid-scale is conducted against ARM field measurements. The evaluation shows that the evolutions of the simulated state fields such as temperature and moisture, the simulated wind fields and the derived large-scale temperature and moisture tendencies closely follow the observed patterns. These results encourages us to use meso-scale WRF model as a tool to verify the performance of GCMs in simulating cloud feedback processes related with the frontal clouds such that we can test and validate the current cloud parameterizations in climate models, and make possible improvements to different components of current cloud parameterizations in GCMs.

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model.

PubMed

Turner, Sean W D; Ng, Jia Yi; Galelli, Stefano

2017-07-15

An important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction of change in globally aggregated hydropower production (~-5 to +5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~5-20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~5-15%) without investing in new power generation facilities. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model

DOE PAGES

Turner, Sean W. D.; Ng, Jia Yi; Galelli, Stefano

2017-03-07

Here, an important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction ofmore » change in globally aggregated hydropower production (~–5 to + 5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~ 5–20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~ 5–15%) without investing in new power generation facilities.« less

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, Sean W. D.; Ng, Jia Yi; Galelli, Stefano

Here, an important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction ofmore » change in globally aggregated hydropower production (~–5 to + 5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~ 5–20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~ 5–15%) without investing in new power generation facilities.« less

Predictions and Studies with a One-Dimensional Ice/Ocean Model.

DTIC Science & Technology

1987-04-01

Description of the model c. Initial conditions and forcing Two different test cases are used for model valiCa- tion and scientific studies. One is the...the density of ice (0.92 g/cm 3), AS/J(O0 is and y-components of the current velocity, w the z-com- the salinity difference per mill, assumed to be 30... different treatments of the mixed layer on the Semtner, quickly develops in the CML simulation. In growth and decay of ice. Henceforth, Semtner’s model

Changes in the Occurrence and Distribution of Extreme Precipitation Events at the Paleocene-Eocene Thermal Maximum (PETM)

NASA Astrophysics Data System (ADS)

Carmichael, M.; Pancost, R. D.; Lunt, D. J.

2015-12-01

The study of the sensitivity of the hydrological cycle to episodes of global warmth in the geologic past is receiving increased attention, but knowledge of the occurrence of hydrological extremes remains limited. A range of geomorphological, microfossil and biomarker proxies indicate significant hydrological change accompanied the PETM hyperthermal at ~55.8 Ma, many of which have been interpreted to reflect changes to Mean Annual Precipitation (MAP) or runoff. Recently, changes in the occurrence of intense, episodic precipitation has been suggested at some sites, but it is currently unknown whether such regions were particularly susceptible to extremes, or whether proxies from other regions require further interpretation. In this work, we seek to understand whether a numerical climate model is capable of simulating changes in the frequency and global distribution of intense precipitation events by analysing GCM-simulated hourly precipitation rates. Our Eocene simulations are performed at x2 and x4 preindustrial CO2 using a coupled atmosphere-ocean GCM, HadCM3L. Climatological differences between high- and low-CO2 may be considered analogous to the PETM. We find that changes in storm characteristics and extremes are highly regionalised. In particular, our simulations support that extreme events occurred with a reduced return period at the PETM in tropical regions of Africa and South America, whilst in the mid-latitudes the importance of extremes varies significantly between sites in close proximity. We also identify regions where changes in extreme behaviour are decoupled from those of MAP, which may represent important proxy acquisition targets. Given that tropical precipitation distributions are highly sensitive to GCM parameterisation scheme and given biases in the representation of sub-daily precipitation within HadCM3L, there is a clear need for further modelling work to fully characterise the Eocene hydrological cycle. However, our results indicate that the interpretation of existing proxies must consider the influences of both changes in mean annual precipitation rate, but also the occurrence of intense, high impact events.

Mapping the Martian Meteorology

NASA Technical Reports Server (NTRS)

Allison, M.; Ross, J. D.; Solomon, N.

1999-01-01

The Mars-adapted version of the NASA/GISS general circulation model (GCM) has been applied to the hourly/daily simulation of the planet's meteorology over several seasonal orbits. The current running version of the model includes a diurnal solar cycle, CO2 sublimation, and a mature parameterization of upper level wave drag with a vertical domain extending from the surface up to the 6microb level. The benchmark simulations provide a four-dimensional archive for the comparative evaluation of various schemes for the retrieval of winds from anticipated polar orbiter measurements of temperatures by the Pressure Modulator Infrared Radiometer. Additional information is contained in the original extended abstract.

Climate of Earth-Like Planets With and Without Ocean Heat Transport Orbiting a Range of M and K Stars

NASA Technical Reports Server (NTRS)

Kiang, N. Y.; Jablonski, Emma R.; Way, Michael J.; Del Genio, Anthony; Roberge, Aki

2015-01-01

The mean surface temperature of a planet is now acknowledged as insufficient to surmise its full potential habitability. Advancing our understanding requires exploration with 3D general circulation models (GCMs), which can take into account how gradients and fluxes across a planet's surface influence the distribution of heat, clouds, and the potential for heterogeneous distribution of liquid water. Here we present 3D GCM simulations of the effects of alternative stellar spectra, instellation, model resolution, and ocean heat transport, on the simulated distribution of heat and moisture of an Earth-like planet (ELP).

The Stochastic Multicloud Model as part of an operational convection parameterisation in a comprehensive GCM

NASA Astrophysics Data System (ADS)

Peters, Karsten; Jakob, Christian; Möbis, Benjamin

2015-04-01

An adequate representation of convective processes in numerical models of the atmospheric circulation (general circulation models, GCMs) remains one of the grand challenges in atmospheric science. In particular, the models struggle with correctly representing the spatial distribution and high variability of tropical convection. It is thought that this model deficiency partly results from formulating current convection parameterisation schemes in a purely deterministic manner. Here, we use observations of tropical convection to inform the design of a novel convection parameterisation with stochastic elements. The novel scheme is built around the Stochastic MultiCloud Model (SMCM, Khouider et al 2010). We present the progress made in utilising SMCM-based estimates of updraft area fractions at cloud base as part of the deep convection scheme of a GCM. The updraft area fractions are used to yield one part of the cloud base mass-flux used in the closure assumption of convective mass-flux schemes. The closure thus receives a stochastic component, potentially improving modeled convective variability and coherence. For initial investigations, we apply the above methodology to the operational convective parameterisation of the ECHAM6 GCM. We perform 5-year AMIP simulations, i.e. with prescribed observed SSTs. We find that with the SMCM, convection is weaker and more coherent and continuous from timestep to timestep compared to the standard model. Total global precipitation is reduced in the SMCM run, but this reduces i) the overall error compared to observed global precipitation (GPCP) and ii) middle tropical tropospheric temperature biases compared to ERA-Interim. Hovmoeller diagrams indicate a slightly higher degree of convective organisation compared to the base case and Wheeler-Kiladis frequency wavenumber diagrams indicate slightly more spectral power in the MJO range.

Aeolian dunes as ground truth for atmospheric modeling on Mars

USGS Publications Warehouse

Hayward, R.K.; Titus, T.N.; Michaels, T.I.; Fenton, L.K.; Colaprete, A.; Christensen, P.R.

2009-01-01

Martian aeolian dunes preserve a record of atmosphere/surface interaction on a variety of scales, serving as ground truth for both Global Climate Models (GCMs) and mesoscale climate models, such as the Mars Regional Atmospheric Modeling System (MRAMS). We hypothesize that the location of dune fields, expressed globally by geographic distribution and locally by dune centroid azimuth (DCA), may record the long-term integration of atmospheric activity across a broad area, preserving GCM-scale atmospheric trends. In contrast, individual dune morphology, as expressed in slipface orientation (SF), may be more sensitive to localized variations in circulation, preserving topographically controlled mesoscale trends. We test this hypothesis by comparing the geographic distribution, DCA, and SF of dunes with output from the Ames Mars GCM and, at a local study site, with output from MRAMS. When compared to the GCM: 1) dunes generally lie adjacent to areas with strongest winds, 2) DCA agrees fairly well with GCM modeled wind directions in smooth-floored craters, and 3) SF does not agree well with GCM modeled wind directions. When compared to MRAMS modeled winds at our study site: 1) DCA generally coincides with the part of the crater where modeled mean winds are weak, and 2) SFs are consistent with some weak, topographically influenced modeled winds. We conclude that: 1) geographic distribution may be valuable as ground truth for GCMs, 2) DCA may be useful as ground truth for both GCM and mesoscale models, and 3) SF may be useful as ground truth for mesoscale models. Copyright 2009 by the American Geophysical Union.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

NASA Astrophysics Data System (ADS)

Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

2017-02-01

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Cloudy Windows: What GCM Ensembles, Reanalyses and Observations Tell Us About Uncertainty in Greenland's Future Climate and Surface Melting

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2016-12-01

Any analysis that wants to use a GCM-based scenario of future climate benefits from knowing how much uncertainty the GCM's inherent variability adds to the development of climate change predictions. This is extra relevant in the polar regions due to the potential of global impacts (e.g., sea level rise) from local (ice sheet) climate changes such as more frequent/intense surface melting. High-resolution, regional-scale models using GCMs for boundary/initial conditions in future scenarios inherit a measure of GCM-derived externally-driven uncertainty. We investigate these uncertainties for the Greenland ice sheet using the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Recent simulations are skill-tested against the ERA-Interim reanalysis and AWS observations with results informing future scenarios. We focus on key variables influencing surface melting through decadal climatologies, nonlinear analysis of variability with self-organizing maps (SOMs), regional-scale modeling (Polar WRF), and simple melt models. Relative to the ensemble average, spatially averaged climatological July temperature anomalies over a Greenland ice-sheet/ocean domain are mostly between +/- 0.2 °C. The spatial average hides larger local anomalies of up to +/- 2 °C. The ensemble average itself is 2 °C cooler than ERA-Interim. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. For CESMLE, the SOM patterns summarize the variability of multiple realizations of climate. Changes in pattern frequency by ensemble member show the influence of initial conditions. For example, basic statistical analysis of pattern frequency yields interquartile ranges of 2-4% for individual patterns across the ensemble. In climate terms, this tells us about climate state variability through the range of the ensemble, a potentially significant source of melt-prediction uncertainty. SOMs can also capture the different trajectories of climate due to intramodel variability over time. Polar WRF provides higher resolution regional modeling with improved, polar-centric model physics. Simple melt models allow us to characterize impacts of the upstream uncertainties on estimates of surface melting.

Impacts of climate change on river discharge in the northern Tien Shan: Results from the long-term observations and modelling

NASA Astrophysics Data System (ADS)

Shahgedanova, Maria; Afzal, Muhammad; Usmanova, Zamira; Kapitsa, Vasilii; Mayr, Elisabeth; Hagg, Wilfried; Severskiy, Igor; Zhumabayev, Dauren

2017-04-01

The study presents results of investigation of the observed and projected changes in discharge of seven snow- and glacier-nourished rivers of the northern Tien Shan (south-eastern Kazakhstan). The observed trends were assessed using the long-term (40-60 years) homogeneous daily records of discharge from the gauging stations located in the mountains and unaffected by human activities including water abstraction. Positive trends in discharge were registered at most sites between the 1950s and 2010s with the strongest increase in summer and autumn particularly in 2000-2010s in line with the positive temperature trends. The observed increase was most prominent in the catchments with a higher proportion of glacierized area. At the Ulken Almatinka and Kishi Almatinka rivers, where 16% and 12% of the catchment areas are glacierized, positive trends in summer and autumn discharge exceeded 1% per year. The strongest increase was observed in September indicating that melting period extends in the early autumn. In September-November, the number of days with extreme discharge values, defined as daily values exceeding 95th percentile (calculated for each meteorological season), increased at all rivers. Future changes in discharge were modelled using HBV-ETH hydrological model and four climate change scenarios derived using regional climate model PRECIS with 25 km spatial resolution driven by HadGEM GCM for RCP 2.6 and RCP 8.5 scenarios and HadCM3Q0 and ECHAM5 GCM for A1B scenario. A range of glacier change scenarios was considered. All climate experiments project increase in temperature with the strongest warming projected by the HadGEM-driven simulation for RCP 8.5 scenario and HadCM3Q0-driven simulation for A1B scenario. The projected changes in precipitation varied between models and seasons, however, most experiments did not show significant trends in precipitation within the studied catchments. The exception is a simulation driven by HadGEM GCM for 8.5 RCP scenario which projects summer drying. All simulations project that in the 2020s, discharge will remain close to its baseline (1990-2005) values suggesting that peak flow has been reached in the northern Tien Shan. Significant decrease in discharge is projected for the post 2030s period for June-September. The strongest changes are expected in July and August when discharge values are projected to decrease by 25-38% in 2030-2060 and decline further to up 50% of the baseline values in 2060-2099.

Precipitation intensity-duration-frequency curves for central Belgium with an ensemble of EURO-CORDEX simulations, and associated uncertainties

NASA Astrophysics Data System (ADS)

Hosseinzadehtalaei, Parisa; Tabari, Hossein; Willems, Patrick

2018-02-01

An ensemble of 88 regional climate model (RCM) simulations at 0.11° and 0.44° spatial resolutions from the EURO-CORDEX project is analyzed for central Belgium to investigate the projected impact of climate change on precipitation intensity-duration-frequency (IDF) relationships and extreme precipitation quantiles typically used in water engineering designs. The rate of uncertainty arising from the choice of RCM, driving GCM, and radiative concentration pathway (RCP4.5 & RCP8.5) is quantified using a variance decomposition technique after reconstruction of missing data in GCM × RCM combinations. A comparative analysis between the historical simulations of the EURO-CORDEX 0.11° and 0.44° RCMs shows higher precipitation intensities by the finer resolution runs, leading to a larger overestimation of the observations-based IDFs by the 0.11° runs. The results reveal that making a temporal stationarity assumption for the climate system may lead to underestimation of precipitation quantiles up to 70% by the end of this century. This projected increase is generally larger for the 0.11° RCMs compared with the 0.44° RCMs. The relative changes in extreme precipitation do depend on return period and duration, indicating an amplification for larger return periods and for smaller durations. The variance decomposition approach generally identifies RCM as the most dominant component of uncertainty in changes of more extreme precipitation (return period of 10 years) for both 0.11° and 0.44° resolutions, followed by GCM and RCP scenario. The uncertainties associated with cross-contributions of RCMs, GCMs, and RCPs play a non-negligible role in the associated uncertainties of the changes.

Interannual Atmospheric Variability Simulated by a Mars GCM: Impacts on the Polar Regions

NASA Technical Reports Server (NTRS)

Bridger, Alison F. C.; Haberle, R. M.; Hollingsworth, J. L.

2003-01-01

It is often assumed that in the absence of year-to-year dust variations, Mars weather and climate are very repeatable, at least on decadal scales. Recent multi-annual simulations of a Mars GCM reveal however that significant interannual variations may occur with constant dust conditions. In particular, interannual variability (IAV) appears to be associated with the spectrum of atmospheric disturbances that arise due to baroclinic instability. One quantity that shows significant IAV is the poleward heat flux associated with these waves. These variations and their impacts on the polar heat balance will be examined here.

A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.

2016-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

Applications and Improvement of a Coupled, Global and Cloud-Resolving Modeling System

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Chern, J.; Atlas, R.

2005-01-01

Recently Grabowski (2001) and Khairoutdinov and Randall (2001) have proposed the use of 2D CFWs as a "super parameterization" [or multi-scale modeling framework (MMF)] to represent cloud processes within atmospheric general circulation models (GCMs). In the MMF, a fine-resolution 2D CRM takes the place of the single-column parameterization used in conventional GCMs. A prototype Goddard MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM) is now being developed. The prototype includes the fvGCM run at 2.50 x 20 horizontal resolution with 32 vertical layers from the surface to 1 mb and the 2D (x-z) GCE using 64 horizontal and 32 vertical grid points with 4 km horizontal resolution and a cyclic lateral boundary. The time step for the 2D GCE would be 15 seconds, and the fvGCM-GCE coupling frequency would be 30 minutes (i.e. the fvGCM physical time step). We have successfully developed an fvGCM-GCE coupler for this prototype. Because the vertical coordinate of the fvGCM (a terrain-following floating Lagrangian coordinate) is different from that of the GCE (a z coordinate), vertical interpolations between the two coordinates are needed in the coupler. In interpolating fields from the GCE to fvGCM, we use an existing fvGCM finite- volume piecewise parabolic mapping (PPM) algorithm, which conserves the mass, momentum, and total energy. A new finite-volume PPM algorithm, which conserves the mass, momentum and moist static energy in the z coordinate, is being developed for interpolating fields from the fvGCM to the GCE. In the meeting, we will discuss the major differences between the two MMFs (i.e., the CSU MMF and the Goddard MMF). We will also present performance and critical issues related to the MMFs. In addition, we will present multi-dimensional cloud datasets (i.e., a cloud data library) generated by the Goddard MMF that will be provided to the global modeling community to help improve the representation and performance of moist processes in climate models and to improve our understanding of cloud processes globally (the software tools needed to produce cloud statistics and to identify various types of clouds and cloud systems from both high-resolution satellite and model data will be also presented).

Evaluation of a Mineral Dust Simulation in the Atmospheric-Chemistry General Circulation Model-EMAC

NASA Astrophysics Data System (ADS)

Abdel Kader, M.; Astitha, M.; Lelieveld, J.

2012-04-01

This study presents an evaluation of the atmospheric mineral dust cycle in the Atmospheric Chemistry General Circulation Model (AC-GCM) using new developed dust emissions scheme. The dust cycle, as an integral part of the Earth System, plays an important role in the Earth's energy balance by both direct and indirect ways. As an aerosol, it significantly impacts the absorption and scattering of radiation in the atmosphere and can modify the optical properties of clouds and snow/ice surfaces. In addition, dust contributes to a range of physical, chemical and bio-geological processes that interact with the cycles of carbon and water. While our knowledge of the dust cycle, its impacts and interactions with the other global-scale bio-geochemical cycles has greatly advanced in the last decades, large uncertainties and knowledge gaps still exist. Improving the dust simulation in global models is essential to minimize the uncertainties in the model results related to dust. In this study, the results are based on the ECHAM5 Modular Earth Submodel System (MESSy) AC-GCM simulations using T106L31 spectral resolution (about 120km ) with 31 vertical levels. The GMXe aerosol submodel is used to simulate the phase changes of the dust particles between soluble and insoluble modes. Dust emission, transport and deposition (wet and dry) are calculated on-line along with the meteorological parameters in every model time step. The preliminary evaluation of the dust concentration and deposition are presented based on ground observations from various campaigns as well as the evaluation of the optical properties of dust using AERONET and satellite (MODIS and MISR) observations. Preliminarily results show good agreement with observations for dust deposition and optical properties. In addition, the global dust emissions, load, deposition and lifetime is in good agreement with the published results. Also, the uncertainties in the dust cycle that contribute to the overall model performance will be briefly discussed as it is a subject of future work.

GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden

NASA Technical Reports Server (NTRS)

Menon, Surabi; DelGenio, Anthony D.; Koch, Dorothy; Tselioudis, George; Hansen, James E. (Technical Monitor)

2001-01-01

We describe the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea-salt that is used to estimate the aerosol indirect effect. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows us to predict aerosol effects on cloud optical thickness and microphysical process rates. We calculate the aerosol indirect effect by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day vs. pre-industrial emissions. Both the first (radiative) and second (microphysical) indirect effects are explored. We test the sensitivity of our results to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden. The global mean aerosol indirect effect for all three aerosol types ranges from -1.55 to -4.36 W m(exp -2) in our simulations. The results are quite sensitive to the pre-industrial background aerosol burden, with low pre-industrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden

NASA Technical Reports Server (NTRS)

Menon, Surabi; DelGenio, Anthony D.; Koch, Dorothy; Tselioudis, George; Hansen, James E. (Technical Monitor)

2001-01-01

We describe the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea-salt that is used to estimate the aerosol indirect effect. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows us to predict aerosol effects on cloud optical thickness and microphysical process rates. We calculate the aerosol indirect effect by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day vs. pre-industrial emissions. Both the first (radiative) and second (microphysical) indirect effects are explored. We test the sensitivity of our results to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden. The global mean aerosol indirect effect for all three aerosol types ranges from -1.55 to -4.36 W/sq m in our simulations. The results are quite sensitive to the pre-industrial background aerosol burden, with low pre-industrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

Investigating Added Value of Regional Climate Modeling in North American Winter Storm Track Simulations

NASA Astrophysics Data System (ADS)

Poan, E.; Gachon, P., Sr.; Laprise, R.; Aider, R.; Dueymes, G.

2017-12-01

This study describes a framework using possibilities given by regional climate models (RCMs) to gain insight into extratropical cyclone (EC) activity during winter over North America (NA). Recent past climate period (1981 - 2005) is firstly considered using the NCEP regional reanalysis (NARR) as a reference, along with the European global reanalysis ERA-Interim (ERAI) and two CMIP5 Global Climate Models (GCMs) used to drive the Canadian RCM - version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological EC track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while their intensity is well captured. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over the eastern coast. In addition, storm occurrence from GCMs over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with main relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value from the CRCM5 is less prominent and systematic, except over western areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Finally, time period near the end of the 21st century (2071-2100) is considered to analyze EC characteristic trends and changes relative to the current climate conditions, showing important modifications in storm activity for certain winter months, especially in term of intensity over the eastern coast.

Role of the Tropical Pacific in recent Antarctic Sea-Ice Trends

NASA Astrophysics Data System (ADS)

Codron, F.; Bardet, D.; Allouache, C.; Gastineau, G.; Friedman, A. R.; Douville, H.; Voldoire, A.

2017-12-01

The recent (up to 2016) trends in Antarctic sea-ice cover - a global increase masking a dipole between the Ross and Bellingshausen-Weddel seas - are still not well understood, and not reproduced by CMIP5 coupled climate models. We here explore the potential role of atmospheric circulation changes around the Amundsen Sea, themselves possibly forced by tropical SSTs, an explanation that has been recently advanced. As a first check on this hypothesis, we compare the atmospheric circulation trends simulated by atmospheric GCMs coupled with an ocean or with imposed SSTs (AMIP experiment from CMIP5); the latter being in theory able to reproduce changes caused by natural SST variability. While coupled models simulate in aggregate trends that project on the SAM structure, strongest in summer, the AMIP simulations add in the winter season a pronounced Amundsen Sea Low signature (and a PNA signature in the northern hemisphere) both consistent with a Niña-like trend in the tropical Pacific. We then use a specific coupled GCM setup, in which surface wind anomalies over the tropical Pacific are strongly nudged towards the observed ones, including their interannual variability, but the model is free to evolve elsewhere. The two GCMs used then simulate a deepening trend in the Amundsen-Sea Low in winter, and are able to reproduce a dipole in sea-ice cover. Further analysis shows that the sea-ice dipole is partially forced by surface heat flux anomalies in early winter - the extent varying with the region and GCM used. The turbulent heat fluxes then act to damp the anomalies in late winter, which may however be maintained by ice-albedo feedbacks.

Contributions of Lower Atmospheric Drivers to the Semiannual Oscillation in Thermospheric Global Mass Density

NASA Astrophysics Data System (ADS)

Jones, M., Jr.; Emmert, J. T.; Drob, D. P.; Siskind, D. E.

2016-12-01

The thermosphere exhibits intra-annual variations (IAV) in globally averaged mass density that noticeably impact the drag environment of satellites in low Earth orbit. Particularly, the annual and semiannual oscillations (AO and SAO) are collectively the second largest component, after solar variability, of thermospheric global mass density variations. Several mechanisms have been proposed to explain the oscillations, but they have yet to be reproduced by first-principles modeling simulations. Recent studies have focused on estimating the SAO in eddy diffusion required to explain the thermospheric SAO in mass density. Less attention has been paid to the effect of lower and middle atmospheric drivers on the lower boundary of the thermosphere. In this study, we utilize the National Center for Atmospheric Research Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM), to elucidate how the different lower atmospheric drivers influence IAV, and in particular the SAO of globally-averaged thermospheric mass density. We performed numerical simulations of a continuous calendar year assuming constant solar forcing, manipulating the lower atmospheric tidal forcing and gravity wave parameterization in order to quantify the SAO in thermospheric mass density attributable to different lower atmospheric drivers. The prominent initial results are as follows: (1) The "standard" TIME-GCM is capable of simulating the SAO in globally-averaged mass density at 400 km from first-principles, and its amplitude and phase compare well with empirical models; (2) The simulations suggest that seasonally varying Kzz driven by breaking GWs is not the primary driver of the SAO in upper thermospheric globally averaged mass density; (3) Preliminary analysis suggests that the SAO in the upper thermospheric mass density could be a by-product of dynamical wave transport in the mesopause region.

Performance of Goddard Earth Observing System GCM Column Radiation Models under Heterogeneous Cloud Conditions

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Chou, M.-D.; Khairoutdinov, M.; Barker, H. W.; Cahalan, R. F.

2003-01-01

We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koll, Daniel D. B.; Abbot, Dorian S., E-mail: dkoll@uchicago.edu

Next-generation space telescopes will observe the atmospheres of rocky planets orbiting nearby M-dwarfs. Understanding these observations will require well-developed theory in addition to numerical simulations. Here we present theoretical models for the temperature structure and atmospheric circulation of dry, tidally locked rocky exoplanets with gray radiative transfer and test them using a general circulation model (GCM). First, we develop a radiative-convective (RC) model that captures surface temperatures of slowly rotating and cool atmospheres. Second, we show that the atmospheric circulation acts as a global heat engine, which places strong constraints on large-scale wind speeds. Third, we develop an RC-subsiding modelmore » which extends our RC model to hot and thin atmospheres. We find that rocky planets develop large day–night temperature gradients at a ratio of wave-to-radiative timescales up to two orders of magnitude smaller than the value suggested by work on hot Jupiters. The small ratio is due to the heat engine inefficiency and asymmetry between updrafts and subsidence in convecting atmospheres. Fourth, we show, using GCM simulations, that rotation only has a strong effect on temperature structure if the atmosphere is hot or thin. Our models let us map out atmospheric scenarios for planets such as GJ 1132b, and show how thermal phase curves could constrain them. Measuring phase curves of short-period planets will require similar amounts of time on the James Webb Space Telescope as detecting molecules via transit spectroscopy, so future observations should pursue both techniques.« less

Sensitivity of ground - water recharge estimates to climate variability and change, Columbia Plateau, Washington

USGS Publications Warehouse

Vaccaro, John J.

1992-01-01

The sensitivity of groundwater recharge estimates was investigated for the semiarid Ellensburg basin, located on the Columbia Plateau, Washington, to historic and projected climatic regimes. Recharge was estimated for predevelopment and current (1980s) land use conditions using a daily energy-soil-water balance model. A synthetic daily weather generator was used to simulate lengthy sequences with parameters estimated from subsets of the historical record that were unusually wet and unusually dry. Comparison of recharge estimates corresponding to relatively wet and dry periods showed that recharge for predevelopment land use varies considerably within the range of climatic conditions observed in the 87-year historical observation period. Recharge variations for present land use conditions were less sensitive to the same range of historical climatic conditions because of irrigation. The estimated recharge based on the 87-year historical climatology was compared with adjustments to the historical precipitation and temperature records for the same record to reflect CO2-doubling climates as projected by general circulation models (GCMs). Two GCM scenarios were considered: an average of conditions for three different GCMs with CO2 doubling, and a most severe “maximum” case. For the average GCM scenario, predevelopment recharge increased, and current recharge decreased. Also considered was the sensitivity of recharge to the variability of climate within the historical and adjusted historical records. Predevelopment and current recharge were less and more sensitive, respectively, to the climate variability for the average GCM scenario as compared to the variability within the historical record. For the maximum GCM scenario, recharge for both predevelopment and current land use decreased, and the sensitivity to the CO2-related climate change was larger than sensitivity to the variability in the historical and adjusted historical climate records.

GCM Simulations of Titan's Paleoclimate

NASA Astrophysics Data System (ADS)

Lora, Juan M.; Lunine, Jonathan; Russell, Joellen; Hayes, Alexander

2014-11-01

The hemispheric asymmetry observed in the distribution of Titan's lakes and seas has been suggested to be the result of asymmetric seasonal forcing, where a relative moistening of the north occurs in the current epoch due to its longer and less intense summers. General circulation models (GCMs) of present-day Titan have also shown that the atmosphere transports methane away from the equator. In this work, we use a Titan GCM to investigate the effects that changes in Titan's effective orbital parameters have had on its climate in recent geologic history. The simulations show that the climate is relatively insensitive to changes in orbital parameters, with persistently dry low latitudes and wet polar regions. The amount of surface methane that builds up over either pole depends on the insolation distribution, confirming the influence of orbital forcing on the distribution of surface liquids. The evolution of the orbital forcing implies that the surface reservoir must be transported on timescales of ~30 kyr, in which case the asymmetry reverses with a period of ~125 kyr. Otherwise, the orbital forcing is insufficient for generating the observed dichotomy.

Effects of Doubled CO2 on Tropical Sea-Surface Temperature (SSTs) for Onset of Deep Convection and Maximum SST-GCM Simulations Based Inferences

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Zhou, Y. P.; Schmidt, Gavin A.; Lau, K. M.; Cahalan, R. F.

2008-01-01

A primary concern of CO2-induced warming is the associated rise of tropical (10S-10N) seasurface temperatures (SSTs). GISS Model-E was used to produce two sets of simulations-one with the present-day and one with doubled CO2 in the atmosphere. The intrinsic usefulness of model guidance in the tropics was confirmed when the model simulated realistic convective coupling between SSTs and atmospheric soundings and that the simulated-data correlations between SSTs and 300 hPa moiststatic energies were found to be similar to the observed. Model predicted SST limits: (i) one for the onset of deep convection and (ii) one for maximum SST, increased in the doubled C02 case. Changes in cloud heights, cloud frequencies, and cloud mass-fractions showed that convective-cloud changes increased the SSTs, while warmer mixed-layer of the doubled CO2 contained approximately 10% more water vapor; clearly that would be conducive to more intense storms and hurricanes.

Theoretical and Empirical Descriptions of Thermospheric Density

NASA Astrophysics Data System (ADS)

Solomon, S. C.; Qian, L.

2004-12-01

The longest-term and most accurate overall description the density of the upper thermosphere is provided by analysis of change in the ephemeris of Earth-orbiting satellites. Empirical models of the thermosphere developed in part from these measurements can do a reasonable job of describing thermospheric properties on a climatological basis, but the promise of first-principles global general circulation models of the coupled thermosphere/ionosphere system is that a true high-resolution, predictive capability may ultimately be developed for thermospheric density. However, several issues are encountered when attempting to tune such models so that they accurately represent absolute densities as a function of altitude, and their changes on solar-rotational and solar-cycle time scales. Among these are the crucial ones of getting the heating rates (from both solar and auroral sources) right, getting the cooling rates right, and establishing the appropriate boundary conditions. However, there are several ancillary issues as well, such as the problem of registering a pressure-coordinate model onto an altitude scale, and dealing with possible departures from hydrostatic equilibrium in empirical models. Thus, tuning a theoretical model to match empirical climatology may be difficult, even in the absence of high temporal or spatial variation of the energy sources. We will discuss some of the challenges involved, and show comparisons of simulations using the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) to empirical model estimates of neutral thermosphere density and temperature. We will also show some recent simulations using measured solar irradiance from the TIMED/SEE instrument as input to the TIE-GCM.

Assessment of the global energy budget of Mars and comparison to the Earth

NASA Astrophysics Data System (ADS)

Madeleine, J.; Head, J. W.; Forget, F.; Wolff, M. J.

2012-12-01

The energy balance of a planet depends on its radiative environment and internal energy production. In the case of present-day Mars, the whole climate system is by far controlled by solar radiation rather than internal heat. Over the last hundreds of millions of years, changes in the orbital parameters and insolation pattern have induced various climatic excursions, during which the energy transfers within the atmosphere were different from today. On the longer term, i.e. over the last billions of years, the energy budget was even more different, as a result of the larger geothermal flux and heat provided by volcanic eruptions and impacts. Seeing the climate of Mars from an energy budget perspective provides a framework for understanding the key processes, as well as constraining climate models. The goal of this research is thus to characterize and analyze the energy budget of Mars. The first step, which is described in this communication, consists of quantifying the different components of the Mars radiation budget using the LMD (Laboratoire de Météorologie Dynamique) GCM (Global Climate Model). The LMD/GCM has been developed for more than 20 years and has now reached a level of detail that allows us to quantify the different contributions of CO2 gas, dust and clouds to the radiation budget. The general picture of the radiation budget as simulated by the GCM can be summarized as follows. First of all, the global-mean shortwave (SW) flux incident on the top of the Martian atmosphere is 148.5 W m-2. Whereas most of the incoming solar radiation is absorbed by atmospheric gases on Earth, on Mars most of the sunlight is absorbed by dust particles. Our simulations show that around 15% of the incoming solar radiation is absorbed by dust particles whereas 2.5% is reflected by them. Water-ice clouds also reflect around 1.5% of the solar radiation, which is much smaller than the amount of radiation reflected by clouds on Earth (around 20%). The Martian atmosphere is even more transparent in the long-wave (LW) domain. Only 7% of the infrared radiation emitted by the surface is absorbed by the atmosphere. Most of this absorption (around 4% of the total outgoing infrared radiation) is due to dust particles. Water-ice clouds also play a significant role, and absorb approximately half as much LW radiation as the dust particles. The distribution of energy among the different atmospheric processes (release of latent heat by condensing CO2, atmospheric motions, etc.) can also be analyzed with the GCM and is being further documented. The next steps include analyzing the available observations of the radiation budget, using them to better constrain the GCM, simulating the energy budget during past climatic excursions, and further comparing the fluxes to those of terrestrial glacial regions. The analysis of the integrated SW and LW fluxes has been done using instruments such as TES onboard Mars Global Surveyor, but only in the polar regions. Indeed, measuring the energy budget requires a good spatial and temporal sampling that is better achieved in the polar regions (most Martian satellites have a sun-synchronous polar orbit). Now that GCMs can simulate the SW and LW radiation fields accurately, simulations can be used to fill the temporal gaps in non-polar regions and explore the measurements on a global scale.

EdGCM: Research Tools for Training the Climate Change Generation

NASA Astrophysics Data System (ADS)

Chandler, M. A.; Sohl, L. E.; Zhou, J.; Sieber, R.

2011-12-01

Climate scientists employ complex computer simulations of the Earth's physical systems to prepare climate change forecasts, study the physical mechanisms of climate, and to test scientific hypotheses and computer parameterizations. The Intergovernmental Panel on Climate Change 4th Assessment Report (2007) demonstrates unequivocally that policy makers rely heavily on such Global Climate Models (GCMs) to assess the impacts of potential economic and emissions scenarios. However, true climate modeling capabilities are not disseminated to the majority of world governments or U.S. researchers - let alone to the educators who will be training the students who are about to be presented with a world full of climate change stakeholders. The goal is not entirely quixotic; in fact, by the mid-1990's prominent climate scientists were predicting with certainty that schools and politicians would "soon" be running GCMs on laptops [Randall, 1996]. For a variety of reasons this goal was never achieved (nor even really attempted). However, around the same time NASA and the National Science Foundation supported a small pilot project at Columbia University to show the potential of putting sophisticated computer climate models - not just "demos" or "toy models" - into the hands of non-specialists. The Educational Global Climate Modeling Project (EdGCM) gave users access to a real global climate model and provided them with the opportunity to experience the details of climate model setup, model operation, post-processing and scientific visualization. EdGCM was designed for use in both research and education - it is a full-blown research GCM, but the ultimate goal is to develop a capability to embed these crucial technologies across disciplines, networks, platforms, and even across academia and industry. With this capability in place we can begin training the skilled workforce that is necessary to deal with the multitude of climate impacts that will occur over the coming decades. To further increase the educational potential of climate models, the EdGCM project has also created "EZgcm". Through a joint venture of NASA, Columbia University and McGill University EZgcm moves the focus toward a greater use of Web 1.0 and Web 2.0-based technologies. It shifts the educational objectives towards a greater emphasis on teaching students how science is conducted and what role science plays in assessing climate change. That is, students learn about the steps of the scientific process as conveyed by climate modeling research: constructing a hypothesis, designing an experiment, running a computer model, using scientific visualization to support analysis, communicating the results of that analysis, and role playing the scientific peer review process. This is in stark contrast to what they learn from the political debate over climate change, which they often confuse with a scientific debate.

A GCM Recent History of Northern Martian Polar Layered Deposits: Contribution from Past Equatorial Ice Reservoirs

NASA Technical Reports Server (NTRS)

Levrard, B.; Laskar, J.; Montmessin, F.; Forget, F.

2005-01-01

Polar layered deposits are exposed in the walls of the troughs cutting the north polar cap of Mars. They consist of alternating ice and dust layers or layers of an ice-dust mixture with varying proportions and are found throughout the cap. Layers thickness ranges from meters to several tens of meters with an approximately 30 meter dominant wavelength. Although their formation processes is not known, they are presumed to reflect changes in ice and dust stability over orbital and axial variations. Intensive 3-D LMD GCM simulations of the martian water cycle have been thus performed to determine the annual rates of exchange of surface ice between the northern cap and tropical areas for a wide range of obliquity and orbital parameters values.These rates have been employed to reconstruct an history of the northern cap and test simple models of dust-ice layers formation over the last 10 Ma orbital variations. We use the 3-D water cycle model simulated by the 3-D LMD GCM with an intermediate grid resolution (7.5 longitude x 5.625 latitude) and 25 vertical levels. The dust opacity is constant and set to 0,15. No exchange of ice with regolith is allowed. The evolution of the northern cap over obliquity and orbital changes (eccentricity, Longitude of perihelion) has been recently described with this model. High summer insolation favors transfer of ice from the northern pole to the Tharsis and Olympus Montes, while at low obliquity, unstable equatorial ice is redeposited in high-latitude and polar areas of both hemisphere. The disappearance of the equatorial ice reservoir leads to a poleward recession of icy high latitude reservoirs, providing an additional source for the cap accumulation during each obliquity or orbital cycle. Furthering the efforts, a quantitative evolution of ice reservoirs is here investigated for various astronomical conditions.

Two-way against one-way nesting for climate downscaling in Europe and the Mediterranean region using LMDZ4

NASA Astrophysics Data System (ADS)

Li, Shan; Li, Laurent; Le Treut, Hervé

2016-04-01

In the 21st century, the estimated surface temperature warming projected by General Circulation Models (GCMs) is between 0.3 and 4.8 °C, depending on the scenario considered. GCMs exhibit a good representation of climate on a global scale, but they are not able to reproduce regional climate processes with the same level of accuracy. Society and policymakers need model projections to define climate change adaptation and mitigation policies on a global, regional and local scale. Climate downscaling is mostly conducted with a regional model nested into the outputs of a global model. This one-way nesting approach is generally used in the climate community without feedbacks from Regional Climate Models (RCMs) to GCMs. This lack of interaction between the two models may affect regional modes of variability, in particular those with a boundary conflict. The objective of this study is to evaluate a two-way nesting configuration that makes an interactive coupling between the RCM and the GCM, an approach against the traditional configuration of one-way nesting system. An additional aim of this work is to examine if the two-way nesting system can improve the RCM performance. The atmospheric component of the IPSL integrated climate model (LMDZ) is configured at both regional (LMDZ-regional) and global (LMDZ-global) scales. The two models have the same configuration for the dynamical framework and the physical forcings. The climatology values of sea surface temperature (SST) are prescribed for the two models. The stretched-grid of LMDZ-global is applied to a region defined by Europe, the Mediterranean, North Africa and Western North Atlantic. To ensure a good statistical significance of results, all simulations last at least 80 years. The nesting process of models is performed by a relaxation procedure of a time scale of 90 minutes. In the case of two-way nesting, the exchange between the two models is every two hours. The relaxation procedure induces a boundary conflict, particularly in the eastern boundary for temperature and geopotential height. A correlation analysis on the synoptic scale evaluates the relationship between the GCM and the RCM. The beginning of the simulations shows a great consistency of the two models. When dominant dynamics apply, RCM inherits most of the GCM signal with a consistent spatial structure. On the contrary, when the atmospheric circulation is weak, there are not that many effects transferred from the GCM to the RCM. When the RCM has its own dynamics, the boundary conflict is more pronounced. Winter season is chosen for the two-way nesting test due to the predominant role of the atmospheric dynamics in winter. The new approach of a two-way nesting system reduces boundary bias, having a influence in some cases in climate model projections. The effect of two-way nesting is enhanced when using a finer grid.

Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

Trace Gas/Aerosol Interactions and GMI Modeling Support

NASA Technical Reports Server (NTRS)

Penner, Joyce E.; Liu, Xiaohong; Das, Bigyani; Bergmann, Dan; Rodriquez, Jose M.; Strahan, Susan; Wang, Minghuai; Feng, Yan

2005-01-01

Current global aerosol models use different physical and chemical schemes and parameters, different meteorological fields, and often different emission sources. Since the physical and chemical parameterization schemes are often tuned to obtain results that are consistent with observations, it is difficult to assess the true uncertainty due to meteorology alone. Under the framework of the NASA global modeling initiative (GMI), the differences and uncertainties in aerosol simulations (for sulfate, organic carbon, black carbon, dust and sea salt) solely due to different meteorological fields are analyzed and quantified. Three meteorological datasets available from the NASA DAO GCM, the GISS-II' GCM, and the NASA finite volume GCM (FVGCM) are used to drive the same aerosol model. The global sulfate and mineral dust burdens with FVGCM fields are 40% and 20% less than those with DAO and GISS fields, respectively due to its heavier rainfall. Meanwhile, the sea salt burden predicted with FVGCM fields is 56% and 43% higher than those with DAO and GISS, respectively, due to its stronger convection especially over the Southern Hemispheric Ocean. Sulfate concentrations at the surface in the Northern Hemisphere extratropics and in the middle to upper troposphere differ by more than a factor of 3 between the three meteorological datasets. The agreement between model calculated and observed aerosol concentrations in the industrial regions (e.g., North America and Europe) is quite similar for all three meteorological datasets. Away from the source regions, however, the comparisons with observations differ greatly for DAO, FVGCM and GISS, and the performance of the model using different datasets varies largely depending on sites and species. Global annual average aerosol optical depth at 550 nm is 0.120-0.131 for the three meteorological datasets.

The global distribution of gravity wave energy in the lower stratosphere derived from GPS data and gravity wave modelling: Attempt and challenges

NASA Astrophysics Data System (ADS)

Fröhlich, K.; Schmidt, T.; Ern, M.; Preusse, P.; de La Torre, A.; Wickert, J.; Jacobi, Ch.

2007-12-01

Five years of global temperatures retrieved from radio occultations measured by Champ (Challenging Minisatellite Payload) and SAC-C (Satelite de Aplicaciones Cientificas-C) are analyzed for gravity waves (GWs). In order to separate GWs from other atmospheric variations, a high-pass filter was applied on the vertical profile. Resulting temperature fluctuations correspond to vertical wavelengths between 400 m (instrumental resolution) and 10 km (limit of the high-pass filter). The temperature fluctuations can be converted into GW potential energy, but for comparison with parameterization schemes GW momentum flux is required. We therefore used representative values for the vertical and horizontal wavelength to infer GW momentum flux from the GPS measurements. The vertical wavelength value is determined by high-pass filtering, the horizontal wavelength is adopted from a latitude-dependent climatology. The obtained momentum flux distributions agree well, both in global distribution and in absolute values, with simulations using the Warner and McIntyre parameterization (WM) scheme. However, discrepancies are found in the annual cycle. Online simulations, implementing the WM scheme in the mechanistic COMMA-LIM (Cologne Model of the Middle Atmosphere—Leipzig Institute for Meteorology) general circulation model (GCM), do not converge, demonstrating that a good representation of GWs in a GCM requires both a realistic launch distribution and an adequate representation of GW breaking and momentum transfer.

A class of the van Leer-type transport schemes and its application to the moisture transport in a general circulation model

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Chao, Winston C.; Sud, Y. C.; Walker, G. K.

1994-01-01

A generalized form of the second-order van Leer transport scheme is derived. Several constraints to the implied subgrid linear distribution are discussed. A very simple positive-definite scheme can be derived directly from the generalized form. A monotonic version of the scheme is applied to the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) for the moisture transport calculations, replacing the original fourth-order center-differencing scheme. Comparisons with the original scheme are made in idealized tests as well as in a summer climate simulation using the full GLA GCM. A distinct advantage of the monotonic transport scheme is its ability to transport sharp gradients without producing spurious oscillations and unphysical negative mixing ratio. Within the context of low-resolution climate simulations, the aforementioned characteristics are demonstrated to be very beneficial in regions where cumulus convection is active. The model-produced precipitation pattern using the new transport scheme is more coherently organized both in time and in space, and correlates better with observations. The side effect of the filling algorithm used in conjunction with the original scheme is also discussed, in the context of idealized tests. The major weakness of the proposed transport scheme with a local monotonic constraint is its substantial implicit diffusion at low resolution. Alternative constraints are discussed to counter this problem.

High resolution 3D global climate modeling of Pluto's atmosphere to interpret New Horizons observations

NASA Astrophysics Data System (ADS)

Bertrand, Tanguy; Forget, Francois; New Horizons Science Team

2017-10-01

We use the LMD Global Climate Model (GCM) of Pluto's atmosphere to interpret New Horizons observations and simulate the Pluto climate system. The model takes into account the cycles of N2, CH4, CO and organic haze. It is described in details in Forget et al., 2017. In order to ensure our simulations, sensitive to our initial conditions, correctly describe reality, we initialize the 3D model with a set of subsurface temperatures and ice distribution, which converged toward steady state after thousands of years simulated with a 2D version of the model (Bertrand and Forget, 2016).We identify three “realistic” simulations which differ by their spatial distribution of N2 ice in 2015 but remain consistent with the evolution of the surface pressure (Sicardy et al., 2016) and the amount of atmospheric methane observed on Pluto (Lellouch et al., 2015). We perform a comprehensive characterization of Pluto’s atmosphere in 2015 using these simulations. Near surface winds can be compared to wind streaks on Pluto, while the simulated waves and thermal structure can be compared to the New Horizons occultations measurements (Hinson et al., 2017).In particular, we demonstrate the sensitivity of the general circulation to the distribution of N2 ice on the surface. Our latest results suggest that Pluto’s atmosphere undergoes retrograde rotation, a unique circulation regime in the Solar System, induced by the condensation-sublimation of N2 in the Sputnik Planitia basin. In Sputnik Planitia, the near-surface winds favor a deposition of haze particles in the northern and western part of the ice cap, which helps to interpret the different colors observed. The GCM also shows that several atmospheric phenomena are at the origin of the cold boundary layer observed deep in the Sputnik Planitia basin, in particular the sublimation of N2, effects of topography and the supply of cold air by winds. This allows us to understand the near-surface differences observed between the entry and exit temperature profiles, measured by REX on-board New Horizons. However it does not reproduce the differences observed between 6 and 30 km above the mean surface.

The Mars Climate Database (MCD version 5.2)

NASA Astrophysics Data System (ADS)

Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team

2015-10-01

The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2

Ionosphere variability during the 2009 SSW: Influence of the lunar semidiurnal tide and mechanisms producing electron density variability

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Liu, H.-L.; Sassi, F.; Lei, J.; Chau, J. L.; Zhang, X.

2014-05-01

To investigate ionosphere variability during the 2009 sudden stratosphere warming (SSW), we present simulation results that combine the Whole Atmosphere Community Climate Model Extended version and the thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM). The simulations reveal notable enhancements in both the migrating semidiurnal solar (SW2) and lunar (M2) tides during the SSW. The SW2 and M2 amplitudes reach ˜50 m s-1 and ˜40 m s-1, respectively, in zonal wind at E region altitudes. The dramatic increase in the M2 at these altitudes influences the dynamo generation of electric fields, and the importance of the M2 on the ionosphere variability during the 2009 SSW is demonstrated by comparing simulations with and without the M2. TIME-GCM simulations that incorporate the M2 are found to be in good agreement with Jicamarca Incoherent Scatter Radar vertical plasma drifts and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations of the maximum F region electron density. The agreement with observations is worse if the M2 is not included in the simulation, demonstrating that the lunar tide is an important contributor to the ionosphere variability during the 2009 SSW. We additionally investigate sources of the F region electron density variability during the SSW. The primary driver of the electron density variability is changes in electric fields. Changes in meridional neutral winds and thermosphere composition are found to also contribute to the electron density variability during the 2009 SSW. The electron density variability for the 2009 SSW is therefore not solely due to variability in electric fields as previously thought.

Regolith-atmosphere exchange of water in Mars' recent past

NASA Astrophysics Data System (ADS)

Steele, Liam J.; Balme, Matthew R.; Lewis, Stephen R.

2017-03-01

We investigate the exchange of water vapour between the regolith and atmosphere of Mars, and how it varies with different orbital parameters, atmospheric dust contents and surface water ice reservoirs. This is achieved through the coupling of a global circulation model (GCM) and a regolith diffusion model. GCM simulations are performed for hundreds of Mars years, with additional one-dimensional simulations performed for 50 kyr. At obliquities ɛ =15∘ and 30°, the thermal inertia and albedo of the regolith have more control on the subsurface water distribution than changes to the eccentricity or solar longitude of perihelion. At ɛ =45∘ , atmospheric water vapour abundances become much larger, allowing stable subsurface ice to form in the tropics and mid-latitudes. The circulation of the atmosphere is important in producing the subsurface water distribution, with increased water content in various locations due to vapour transport by topographically-steered flows and stationary waves. As these circulation patterns are due to topographic features, it is likely the same regions will also experience locally large amounts of subsurface water at different epochs. The dustiness of the atmosphere plays an important role in the distribution of subsurface water, with a dusty atmosphere resulting in a wetter water cycle and increased stability of subsurface ice deposits.

Investigating the 90-day oscillations using ground-based, satellite and TIME-GCM model simulation data

NASA Astrophysics Data System (ADS)

Zhao, Y.; Taylor, M.; Hagan, M. E.; Pautet, P. D.; Pugmire, J. R.; Pendleton, W. R., Jr.; Russell, J. M., III

2016-12-01

The Andes Lidar Observatory (ALO) is an upper atmospheric observatory located high in the Andes mountain range at Cerro Pachón, Chile (30.3°S, 70.7°W, 2530 m). The Utah State University (USU) Mesospheric Temperature Mapper (MTM) was deployed in August, 2009 collocated with a Na wind/temperature lidar and a meteor wind radar from University of Illinois at Urbana-Champaign (UIUC) as well as other optical instrumentation. In this presentation, we focus on the characteristics of a unique 90-day oscillation identified in the first 18 months in both the mesospheric wind and temperature data from ALO. This event appeared to be long-lived but transient, with similar amplitude to the AO and SAO at this location. Additional mesospheric temperature data from nearby El Leoncito Observatory (31.8°S, 69.3°W), Argentina also showed the same oscillation. The existence and extent of this oscillation are being further examined using SABER/TIMED temperature. The National Center for Atmosphere Research (NCAR) Thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM) simulation of 2009/10 results are utilized to investigate the possible source of this event and the spatial structures are compared with the results from the SABER temperature data.

Snow Cover and Precipitation Impacts on Dry Season Streamflow in the Lower Mekong Basin

NASA Technical Reports Server (NTRS)

Cook, Benjamin I.; Bell, A. R.; Anchukaitis, K. J.; Buckley, B. M.

2012-01-01

Climate change impacts on dry season streamflow in the Mekong River are relatively understudied, despite the fact that water availability during this time is critically important for agricultural and ecological systems. Analyses of two gauging stations (Vientiane and Kratie) in the Lower Mekong Basin (LMB) show significant positive correlations between dry season (March through May, MAM) discharge and upper basin snow cover and local precipitation. Using snow cover, precipitation, and upstream discharge as predictors, we develop skillful regression models for MAM streamflow at Vientiane and Kratie, and force these models with output from a suite of general circulation model (GCM) experiments for the twentieth and twenty-first centuries. The GCM simulations predict divergent trends in snow cover (decreasing) and precipitation (increasing) over the twenty-first century, driving overall negligible long-term trends in dry season streamflow. Our study demonstrates how future changes in dry season streamflow in the LMB will depend on changes in snow cover and precipitation, factors that will need to be considered when assessing the full basin response to other climatic and non-climatic drivers.

Lunar tidal effects during the 2013 stratospheric sudden warming as simulated by the TIME-GCM

NASA Astrophysics Data System (ADS)

Maute, A. I.; Forbes, J. M.; Zhang, X.; Fejer, B. G.; Yudin, V. A.; Pedatella, N. M.

2015-12-01

Stratospheric Sudden Warmings (SSW) are associated with strong planetary wave activity in the winterpolar stratosphere which result in a very disturbed middle atmosphere. The changes in the middle atmospherealter the propagation conditions and the nonlinear interactions of waves and tides, and result in SSW signals in the upper atmosphere in e.g., neutral winds, electric fields, ionospheric currents and plasma distribution. The upper atmosphere changes can be significant at low-latitudes even during medium solar flux conditions. Observationsalso reveal a strong lunar signal during SSW periods in the low latitude vertical drifts and in ionospheric quantities. Forbes and Zhang [2012] demonstrated that during the 2009 SSW period the Pekeris resonance peak of the atmosphere was altered such that the M2 and N2 lunar tidal componentsgot amplified. This study focuses on the effect of the lunar tidal forcing on the thermosphere-ionosphere system during theJanuary 2013 SSW period. We employthe NCAR Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM)with a nudging scheme using the Whole-Atmosphere-Community-Climate-Model-Extended (WACCM-X)/Goddard Earth Observing System Model, Version 5 (GEOS5) results to simulate the effects of meteorological forcing on the upper atmosphere. Additionally lunar tidal forcingis included at the lower boundary of the model. To delineate the lunar tidal effects a base simulation without lunar forcingis employed. Interestingly, Jicamarca observations of that period reveal a suppression of the daytime vertical drift before and after the drift enhancement due the SSW. The simulation suggests that the modulation of the vertical driftmay be caused by the interplay of the migrating solar and lunar semidiurnal tide, and therefore can only be reproduced by the inclusion of both lunar and solar tidal forcings in the model. In this presentation the changes due to the lunar tidal forcing will be quantified, and compared to observations.

Modeling changes in summer temperature of the Fraser River during the next century

NASA Astrophysics Data System (ADS)

Ferrari, Michael R.; Miller, James R.; Russell, Gary L.

2007-09-01

SummaryThe Fraser River basin in British Columbia has significant environmental, economic and cultural importance. Healthy river conditions through sufficient flows and optimal temperatures are of paramount importance for the survival of Pacific salmon, which migrate upriver toward the headwaters to spawn near the end of their lives. Trends have been detected which indicate that the annual flow and summer temperature have been increasing since the middle of the last century. In this study we examine the observed trend in summer temperature of the Fraser River and compare it with temperatures calculated as part of a global climate model (GCM) simulation in which atmospheric greenhouse gases are increasing. We then use the GCM to consider how these trends might continue through the present century. Both the observations and model indicate that during the last half of the 20th century, the summer temperature near the river mouth has been increasing at a rate of approximately 0.12 °C per decade in August. In this study we use an online method in which river temperatures are calculated directly as part of a GCM simulation and project how summer temperature near the mouth of the Fraser River might change by the end of the present century. The results indicate that between 2000 and 2100 river temperatures will increase in all summer months with a maximum increase of 0.14 °C per decade in August. This result is consistent with an offline modeling study by [Morrison, J., Quick, M.C., Goreman, M.G.G. 2002. Climate change in the Fraser River watershed: flow and temperature projections. Journal of Hydrology, 263, 230-244] in which they used output from two GCMS to drive a hydrologic model and predict future changes in river temperature and supports their contention that the timing and magnitude of the increase could be crucial for salmon migration. Future work can extend this analysis to other river systems in an effort to project the potential effects of climate change on the behavior of the world's large river basins, as well as identify the potential biological effects that may accompany these changes.

DREAM Mediated Regulation of GCM1 in the Human Placental Trophoblast

PubMed Central

Baczyk, Dora; Kibschull, Mark; Mellstrom, Britt; Levytska, Khrystyna; Rivas, Marcos; Drewlo, Sascha; Lye, Stephen J.; Naranjo, Jose R.; Kingdom, John C. P.

2013-01-01

The trophoblast transcription factor glial cell missing-1 (GCM1) regulates differentiation of placental cytotrophoblasts into the syncytiotrophoblast layer in contact with maternal blood. Reduced placental expression of GCM1 and abnormal syncytiotrophoblast structure are features of hypertensive disorder of pregnancy – preeclampsia. In-silico techniques identified the calcium-regulated transcriptional repressor – DREAM (Downstream Regulatory Element Antagonist Modulator) - as a candidate for GCM1 gene expression. Our objective was to determine if DREAM represses GCM1 regulated syncytiotrophoblast formation. EMSA and ChIP assays revealed a direct interaction between DREAM and the GCM1 promoter. siRNA-mediated DREAM silencing in cell culture and placental explant models significantly up-regulated GCM1 expression and reduced cytotrophoblast proliferation. DREAM calcium dependency was verified using ionomycin. Furthermore, the increased DREAM protein expression in preeclamptic placental villi was predominantly nuclear, coinciding with an overall increase in sumolylated DREAM and correlating inversely with GCM1 levels. In conclusion, our data reveal a calcium-regulated pathway whereby GCM1-directed villous trophoblast differentiation is repressed by DREAM. This pathway may be relevant to disease prevention via calcium-supplementation. PMID:23300953

Experimental demonstration of laser to x-ray conversion enhancements with low density gold targets

DOE PAGES

Shang, Wanli; Yang, Jiamin; Zhang, Wenhai; ...

2016-02-12

The enhancement of laser to x-ray conversion efficiencies using low density gold targets [W. L. Shang, J. M. Yang, and Y. S. Dong, Appl. Phys. Lett. 102, 094105 (2013)] is demonstrated. Laser to x-ray conversion efficiencies with 6.3% and 12% increases are achieved with target densities of 1 and 0.25 g/cm 3, when compared with that of a solid gold target (19.3 g/cm 3). Experimental data and numerical simulations are in good agreement. Lastly, the enhancement is caused by larger x-ray emission zone lengths formed in low density targets, which is in agreement with the simulation results.

Experimental demonstration of laser to x-ray conversion enhancements with low density gold targets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shang, Wanli; Yang, Jiamin; Zhang, Wenhai

The enhancement of laser to x-ray conversion efficiencies using low density gold targets [W. L. Shang, J. M. Yang, and Y. S. Dong, Appl. Phys. Lett. 102, 094105 (2013)] is demonstrated. Laser to x-ray conversion efficiencies with 6.3% and 12% increases are achieved with target densities of 1 and 0.25 g/cm 3, when compared with that of a solid gold target (19.3 g/cm 3). Experimental data and numerical simulations are in good agreement. Lastly, the enhancement is caused by larger x-ray emission zone lengths formed in low density targets, which is in agreement with the simulation results.

Simulating the 2012 High Plains Drought Using Three Single Column Models (SCM)

NASA Astrophysics Data System (ADS)

Medina, I. D.; Baker, I. T.; Denning, S.; Dazlich, D. A.

2015-12-01

The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited, and have used conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we focus on the 2012 High Plains drought and perform numerical simulations using three single column model (SCM) versions of BUGS5 (Colorado State University (CSU) GCM coupled to the Simple Biosphere Model (SiB3)). In the first version of BUGS5, the model is used in its standard bulk setting (single atmospheric column coupled to a single instance of SiB3), secondly, the Super-Parameterized Community Atmospheric Model (SP-CAM), a cloud resolving model (CRM) (CRM consists of 32 atmospheric columns), replaces the single CSU GCM atmospheric parameterization and is coupled to a single instance of SiB3, and for the third version of BUGS5, an instance of SiB3 is coupled to each CRM column of the SP-CAM (32 CRM columns coupled to 32 instances of SiB3). To assess the physical realism of the land-atmosphere feedbacks simulated by all three versions of BUGS5, differences in simulated energy and moisture fluxes are computed between the 2011 and 2012 period and are compared to those calculated using observational data from the AmeriFlux Tower Network for the same period at the ARM Site in Lamont, OK. This research will provide a better understanding of model deficiencies in reproducing and predicting droughts in the future, which is essential to the economic, ecologic and social well being of the High Plains.

Scaling and stochastic cascade properties of NEMO oceanic simulations and their potential value for GCM evaluation and downscaling

NASA Astrophysics Data System (ADS)

Verrier, Sébastien; Crépon, Michel; Thiria, Sylvie

2014-09-01

Spectral scaling properties have already been evidenced on oceanic numerical simulations and have been subject to several interpretations. They can be used to evaluate classical turbulence theories that predict scaling with specific exponents and to evaluate the quality of GCM outputs from a statistical and multiscale point of view. However, a more complete framework based on multifractal cascades is able to generalize the classical but restrictive second-order spectral framework to other moment orders, providing an accurate description of probability distributions of the fields at multiple scales. The predictions of this formalism still needed systematic verification in oceanic GCM while they have been confirmed recently for their atmospheric counterparts by several papers. The present paper is devoted to a systematic analysis of several oceanic fields produced by the NEMO oceanic GCM. Attention is focused to regional, idealized configurations that permit to evaluate the NEMO engine core from a scaling point of view regardless of limitations involved by land masks. Based on classical multifractal analysis tools, multifractal properties were evidenced for several oceanic state variables (sea surface temperature and salinity, velocity components, etc.). While first-order structure functions estimated a different nonconservativity parameter H in two scaling ranges, the multiorder statistics of turbulent fluxes were scaling over almost the whole available scaling range. This multifractal scaling was then parameterized with the help of the universal multifractal framework, providing parameters that are coherent with existing empirical literature. Finally, we argue that the knowledge of these properties may be useful for oceanographers. The framework seems very well suited for the statistical evaluation of OGCM outputs. Moreover, it also provides practical solutions to simulate subpixel variability stochastically for GCM downscaling purposes. As an independent perspective, the existence of multifractal properties in oceanic flows seems also interesting for investigating scale dependencies in remote sensing inversion algorithms.

Downscaled climate change projections with uncertainty assessment over India using a high resolution multi-model approach.

PubMed

Kumar, Pankaj; Wiltshire, Andrew; Mathison, Camilla; Asharaf, Shakeel; Ahrens, Bodo; Lucas-Picher, Philippe; Christensen, Jens H; Gobiet, Andreas; Saeed, Fahad; Hagemann, Stefan; Jacob, Daniela

2013-12-01

This study presents the possible regional climate change over South Asia with a focus over India as simulated by three very high resolution regional climate models (RCMs). One of the most striking results is a robust increase in monsoon precipitation by the end of the 21st century but regional differences in strength. First the ability of RCMs to simulate the monsoon climate is analyzed. For this purpose all three RCMs are forced with ECMWF reanalysis data for the period 1989-2008 at a horizontal resolution of ~25 km. The results are compared against independent observations. In order to simulate future climate the models are driven by lateral boundary conditions from two global climate models (GCMs: ECHAM5-MPIOM and HadCM3) using the SRES A1B scenario, except for one RCM, which only used data from one GCM. The results are presented for the full transient simulation period 1970-2099 and also for several time slices. The analysis concentrates on precipitation and temperature over land. All models show a clear signal of gradually wide-spread warming throughout the 21st century. The ensemble-mean warming over India is 1.5°C at the end of 2050, whereas it is 3.9°C at the end of century with respect to 1970-1999. The pattern of projected precipitation changes shows considerable spatial variability, with an increase in precipitation over the peninsular of India and coastal areas and, either no change or decrease further inland. From the analysis of a larger ensemble of global climate models using the A1B scenario a wide spread warming (~3.2°C) and an overall increase (~8.5%) in mean monsoon precipitation by the end of the 21st century is very likely. The influence of the driving GCM on the projected precipitation change simulated with each RCM is as strong as the variability among the RCMs driven with one. Copyright © 2013 Elsevier B.V. All rights reserved.

Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, M. J.; Heiser, M.

1998-01-01

In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

The Tropical Upper Troposphere and Lower Stratosphere in the GEOS-2 GCM

NASA Technical Reports Server (NTRS)

Pawson, S.; Takacs, L.; Molod, A.; Nebuda, S.; Chen, M.; Rood, R.; Read, W. L.; Fiorino, M.

1999-01-01

The structure of the tropical upper troposphere and lower stratosphere in the GEOS-2 General Circulation Model (GCM) is discussed. The emphasis of this study is on the reality of monthly-mean temperature and water vapor distributions in the model, compared to reasonable observational estimates. It is shown that although the zonal-mean temperature is in good agreement with observations, the GCM supports an excessive zonal asymmetry near the tropopause compared to the ECMWF Reanalyses. In reality there is a QBO-related variability in the zonally averaged lower stratospheric temperature which is not captured by the model. The observed upper tropospheric temperature and humidity fields show variations related to those in the sea surface temperature, which are not incorporated in the GCM; nevertheless, there is some interannual variability in the GCM, indicating a component arising from internal processes. The model is too moist in the middle troposphere (500 hPa) but too dry in the upper troposphere, suggesting that there is too little vertical transport or too much drying in the GCM. Transport into the stratosphere shows a pronounced annual cycle, with drier air entering the tropical stratosphere when the tropopause is coldest in northern winter; while the alternating dry and moist air masses can be traced ascending through the tropical lower stratosphere, the progression of the anomalies is too rapid.

A new scheme for the parameterization of the turbulent planetary boundary layer in the GLAS fourth order GCM

NASA Technical Reports Server (NTRS)

Helfand, H. M.

1985-01-01

Methods being used to increase the horizontal and vertical resolution and to implement more sophisticated parameterization schemes for general circulation models (GCM) run on newer, more powerful computers are described. Attention is focused on the NASA-Goddard Laboratory for Atmospherics fourth order GCM. A new planetary boundary layer (PBL) model has been developed which features explicit resolution of two or more layers. Numerical models are presented for parameterizing the turbulent vertical heat, momentum and moisture fluxes at the earth's surface and between the layers in the PBL model. An extended Monin-Obhukov similarity scheme is applied to express the relationships between the lowest levels of the GCM and the surface fluxes. On-line weather prediction experiments are to be run to test the effects of the higher resolution thereby obtained for dynamic atmospheric processes.

Projected changes in extreme precipitation over Scotland and Northern England using a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kahana, Ron; Kendon, Elizabeth J.; Fowler, Hayley J.

2018-03-01

The UK Met Office has previously conducted convection-permitting climate simulations over the southern UK (Kendon et al. in Nat Clim Change 4:570-576, 2014). The southern UK simulations have been followed up by a new set of northern UK simulations using the same model configuration. Here we present the mean and extreme precipitation projections from these new simulations. Relative to the southern UK, the northern UK projections show a greater summertime increase of return levels and extreme precipitation intensity in both 1.5 km convection-permitting and 12 km convection-parameterised simulations, but this increase is against a backdrop of large decreases in summertime mean precipitation and precipitation frequency. Similar to the southern UK, projected change is model resolution dependent and the convection-permitting simulation projects a larger intensification. For winter, return level increases are somewhat lower than for the southern UK. Analysis of model biases highlight challenges in simulating the diurnal cycle over high terrain, sensitivity to domain size and driving-GCM biases, and quality issues of radar precipitation observations, which are relevant to the wider regional climate modelling community.

Improvement of Mars surface snow albedo modeling in LMD Mars GCM with SNICAR

NASA Astrophysics Data System (ADS)

Singh, D.; Flanner, M.; Millour, E.

2017-12-01

The current version of Laboratoire de Météorologie Dynamique (LMD) Mars GCM (original-MGCM) uses annually repeating (prescribed) albedo values from the Thermal Emission Spectrometer observations. We integrate the Snow, Ice, and Aerosol Radiation (SNICAR) model with MGCM (SNICAR-MGCM) to prognostically determine H2O and CO2 ice cap albedos interactively in the model. Over snow-covered regions mean SNICAR-MGCM albedo is higher by about 0.034 than original-MGCM. Changes in albedo and surface dust content also impact the shortwave energy flux at the surface. SNICAR-MGCM model simulates a change of -1.26 W/m2 shortwave flux on a global scale. Globally, net CO2 ice deposition increases by about 4% over one Martian annual cycle as compared to original-MGCM simulations. SNICAR integration reduces the net mean global surface temperature, and the global surface pressure of Mars by about 0.87% and 2.5% respectively. Changes in albedo also show a similar distribution as dust deposition over the globe. The SNICAR-MGCM model generates albedos with higher sensitivity to surface dust content as compared to original-MGCM. For snow-covered regions, we improve the correlation between albedo and optical depth of dust from -0.91 to -0.97 with SNICAR-MGCM as compared to original-MGCM. Using new diagnostic capabilities with this model, we find that cryospheric surfaces (with dust) increase the global surface albedo of Mars by 0.022. The cryospheric effect is severely muted by dust in snow, however, which acts to decrease the planet-mean surface albedo by 0.06.

Climatic impact of Amazon deforestation - a mechanistic model study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ning Zeng; Dickinson, R.E.; Xubin Zeng

1996-04-01

Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of thismore » model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.« less

Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent

2016-11-25

The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. Themore » chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.« less

Assessing regional climate simulations of the last 30 years (1982-2012) over Ganges-Brahmaputra-Meghna River Basin

NASA Astrophysics Data System (ADS)

Khandu; Awange, Joseph L.; Anyah, Richard; Kuhn, Michael; Fukuda, Yoichi

2017-10-01

The Ganges-Brahmaputra-Meghna (GBM) River Basin presents a spatially diverse hydrological regime due to it's complex topography and escalating demand for freshwater resources. This presents a big challenge in applying the current state-of-the-art regional climate models (RCMs) for climate change impact studies in the GBM River Basin. In this study, several RCM simulations generated by RegCM4.4 and PRECIS are assessed for their seasonal and interannual variations, onset/withdrawal of the Indian monsoon, and long-term trends in precipitation and temperature from 1982 to 2012. The results indicate that in general, RegCM4.4 and PRECIS simulations appear to reasonably reproduce the mean seasonal distribution of precipitation and temperature across the GBM River Basin, although the two RCMs are integrated over a different domain size. On average, the RegCM4.4 simulations overestimate monsoon precipitation by {˜ }26 and {˜ }5% in the Ganges and Brahmaputra-Meghna River Basin, respectively, while PRECIS simulations underestimate (overestimate) the same by {˜ }7% ({˜ }16%). Both RegCM4.4 and PRECIS simulations indicate an intense cold bias (up to 10° C) in the Himalayas, and are generally stronger in the RegCM4.4 simulations. Additionally, they tend to produce high precipitation between April and May in the Ganges (RegCM4.4 simulations) and Brahmaputra-Meghna (PRECIS simulations) River Basins, resulting in early onset of the Indian monsoon in the Ganges River Basin. PRECIS simulations exhibit a delayed monsoon withdrawal in the Brahmaputra-Meghna River Basin. Despite large spatial variations in onset and withdrawal periods across the GBM River Basin, the basin-averaged results agree reasonably well with the observed periods. Although global climate model (GCM) driven simulations are generally poor in representing the interannual variability of precipitation and winter temperature variations, they tend to agree well with observed precipitation anomalies when driven by perfect boundary conditions. It is also seen that all GCM driven simulations feature significant positive surface temperature trends consistent with the observed datasets.

Disentangling the uncertainty of hydrologic drought characteristics in a multi-model century-long experiment in continental river basins

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Pechlivanidis, Illias; Breuer, Lutz; Wortmann, Michel; Vetter, Tobias; Flörke, Martina; Chamorro, Alejandro; Schäfer, David; Shah, Harsh; Zeng, Xiaofan

2016-04-01

The quantification of the predictive uncertainty in hydrologic models and their attribution to its main sources is of particular interest in climate change studies. In recent years, a number of studies have been aimed at assessing the ability of hydrologic models (HMs) to reproduce extreme hydrologic events. Disentangling the overall uncertainty of streamflow -including its derived low-flow characteristics- into individual contributions, stemming from forcings and model structure, has also been studied. Based on recent literature, it can be stated that there is a controversy with respect to which source is the largest (e.g., Teng, et al. 2012, Bosshard et al. 2013, Prudhomme et al. 2014). Very little has also been done to estimate the relative impact of the parametric uncertainty of the HMs with respect to overall uncertainty of low-flow characteristics. The ISI-MIP2 project provides a unique opportunity to understand the propagation of forcing and model structure uncertainties into century-long time series of drought characteristics. This project defines a consistent framework to deal with compatible initial conditions for the HMs and a set of standardized historical and future forcings. Moreover, the ensemble of hydrologic model predictions varies across a broad range of climate scenarios and regions. To achieve this goal, we use six preconditioned hydrologic models (HYPE or HBV, mHM, SWIM, VIC, and WaterGAP3) set up in seven large continental river basins: Amazon, Blue Nile, Ganges, Niger, Mississippi, Rhine, Yellow. These models are forced with bias-corrected outputs of five CMIP5 general circulation models (GCM) under four extreme representative concentration pathway (RCP) scenarios (i.e. 2.6, 4.5, 6.0, and 8.5 Wm-2) for the period 1971-2099. Simulated streamflow is transformed into a monthly runoff index (RI) to analyze the attribution of the GCM and HM uncertainty into drought magnitude and duration over time. Uncertainty contributions are investigated during periods: 1) 2006-2035, 2) 2036-2065 and 3) 2070-2099. Results presented in Samaniego et al. 2015 (submitted) indicate that GCM uncertainty mostly dominates over HM uncertainty for predictions of runoff drought characteristics, irrespective of the selected RCP and region. For the mHM model, in particular, GCM uncertainty always dominates over parametric uncertainty. In general, the overall uncertainty increases with time. The larger the radiative forcing of the RCP, the larger the uncertainty in drought characteristics, however, the propagation of the GCM uncertainty onto a drought characteristic depends largely upon the hydro-climatic regime. While our study emphasizes the need for multi-model ensembles for the assessment of future drought projections, the agreement between GCM forcings is still weak to draw conclusive recommendations. References: L. Samaniego, R. Kumar, I. G. Pechlivanidis, L. Breuer, M. Wortmann, T. Vetter, M. Flörke, A. Chamorro, D. Schäfer, H. Shah, X. Zeng: Propagation of forcing and model uncertainty into hydrological drought characteristics in a multi-model century-long experiment in continental river basins. Submitted to Climatic Change on Dec 2015. Bosshard, et al. 2013. doi:10.1029/2011WR011533. Prudhomme et al. 2014, doi:10.1073/pnas.1222473110. Teng, et al. 2012, doi:10.1175/JHM-D-11-058.1.

Designing ecological climate change impact assessments to reflect key climatic drivers

USGS Publications Warehouse

Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.

2017-01-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Designing ecological climate change impact assessments to reflect key climatic drivers.

PubMed

Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T

2017-07-01

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.

Importance of including ammonium sulfate ((NH4)2SO4) aerosols for ice cloud parameterization in GCMs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattacharjee, P. S.; Sud, Yogesh C.; Liu, Xiaohong

2010-02-22

A common deficiency of many cloud-physics parameterizations including the NASA’s microphysics of clouds with aerosol- cloud interactions (hereafter called McRAS-AC) is that they simulate less (larger) than the observed ice cloud particle number (size). A single column model (SCM) of McRAS-AC and Global Circulation Model (GCM) physics together with an adiabatic parcel model (APM) for ice-cloud nucleation (IN) of aerosols were used to systematically examine the influence of ammonium sulfate ((NH4)2SO4) aerosols, not included in the present formulations of McRAS-AC. Specifically, the influence of (NH4)2SO4 aerosols on the optical properties of both liquid and ice clouds were analyzed. First anmore » (NH4)2SO4 parameterization was included in the APM to assess its effect vis-à-vis that of the other aerosols. Subsequently, several evaluation tests were conducted over the ARM-SGP and thirteen other locations (sorted into pristine and polluted conditions) distributed over marine and continental sites with the SCM. The statistics of the simulated cloud climatology were evaluated against the available ground and satellite data. The results showed that inclusion of (NH4)2SO4 in the SCM made a remarkable improvement in the simulated effective radius of ice clouds. However, the corresponding ice-cloud optical thickness increased more than is observed. This can be caused by lack of cloud advection and evaporation. We argue that this deficiency can be mitigated by adjusting the other tunable parameters of McRAS-AC such as precipitation efficiency. Inclusion of ice cloud particle splintering introduced through well- established empirical equations is found to further improve the results. Preliminary tests show that these changes make a substantial improvement in simulating the cloud optical properties in the GCM, particularly by simulating a far more realistic cloud distribution over the ITCZ.« less

A general circulation model study of the climatic effect of observed stratospheric ozone depletion between 1980 and 1990

NASA Technical Reports Server (NTRS)

Dudek, Michael P.; Wang, Wei-Chyung; Liang, Xin-Zhong; Li, Zhu

1994-01-01

The total ozone mapping spectrometer (TOMS) and stratospheric aerosol and gas experiment (SAGE) measurements show a significant reduction in the stratospheric ozone over the middle and high latitudes of both hemispheres between the years 1979 and 1991 (WMO, 1992). This change in ozone will effect both the solar and longwave radiation with climate implications. However, recent studies (Ramaswamy et al., 1992; WMO, 1992) indicate that the net effect depends not only on latitudes and seasons, but also on the response of the lower stratospheric temperature. In this study we use a general circulation model (GCM) to calculate the climatic effect due to stratospheric ozone depletion and compare the effect with that due to observed increases of trace gases CO2, CH4, N2O, and CFC's for the period 1980-1990. In the simulations, we use the observed changes in ozone derived from the TOMS data. The GCM used is a version of the NCAR community climate model referenced in Wang et al. (1991). For the present study we run the model in perpetual January and perpetual July modes in which the incoming solar radiation and climatological sea surface temperatures are held constant.

High LMD GCM Resolution Modeling of the Seasonal Evolution of the Martian Northern Permanent Cap: Comparison with Mars Express OMEGA Observations

NASA Technical Reports Server (NTRS)

Levrard, B.; Forget, F.; Montmessin, F.; Schmitt, B.; Doute, S.; Langevin, Y.; Poulet, F.; Bibring, J. P.; Gondet, B.

2005-01-01

Analyses of imaging data from Mariner, Viking and MGS have shown that surface properties (albedo, temperature) of the northern cap present significant differences within the summer season and between Mars years. These observations include differential brightening and/or darkening between polar areas from the end of the spring to midsummer. These differences are attributed to changes in grain size or dust content of surface ice. To better understand the summer behavior of the permanent northern polar cap, we perfomed a high resolution modeling (approximately 1 deg x 1 deg.) of northern cap in the Martian Climate/water cycle as simulated by the Laboratoire de Meteorologie Dynamique (LMD) global climate model. We compare the predicted properties of the surface ice (ice thickness, temperature) with the Mars Express Omega summer observations of the northern cap. albedo and thermal inertia svariations model. In particular, albedo variations could be constrained by OMEGA data. Meteorological predictions of the LMD GCM wil be presented at the conference to interpret the unprecedently resolved OMEGA observations. The specific evolution of regions of interest (cap center, Chasma Boreal...) and the possibility of late summer global cap brightening will be discussed.

Climate-suitable planting as a strategy for maintaining forest productivity and functional diversity.

PubMed

Duveneck, Matthew J; Scheller, Robert M

2015-09-01

Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000-2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass).

Water Source and Isotope changes through the Deglaciation and Holocene

NASA Astrophysics Data System (ADS)

LeGrande, A. N.; Carlson, A. E.; Ullman, D. J.; Nusbaumer, J. M.

2017-12-01

The deglacial period saw radical shifts in climate across the globe. Water isotopologues provide some of the most wide-spread proxy archives of these climate changes. Here we present new analyses on a suite of 12 water isotope-enabled coupled atmosphere-ocean GCM simulations from GISS ModelE-R that span 24kya to the pre-industrial period. We show how millennial scale co-variability in water isotopes and climate (temperature, precipitation, humidity, and moist-static energy) is distinct from regional scale spatial slopes, consistent with proxy archives (e.g., Cuffey et al 1995). We supplement this set of simulations with a new ensemble of deglacial simulations that contain a complementary suite of tracers that determine moisture provenance changes through the deglaciation. We diagnose regions that have had significant changes in moisture provenance and compare this information against simulated changes in the water isotope changes.

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

Investigating added value of regional climate modeling in North American winter storm track simulations

NASA Astrophysics Data System (ADS)

Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

2018-03-01

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Mcdermid, Sonali P.

2017-01-01

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Global Carbon Cycle Modeling in GISS ModelE2 GCM

NASA Astrophysics Data System (ADS)

Aleinov, I. D.; Kiang, N. Y.; Romanou, A.; Romanski, J.

2014-12-01

Consistent and accurate modeling of the Global Carbon Cycle remains one of the main challenges for the Earth System Models. NASA Goddard Institute for Space Studies (GISS) ModelE2 General Circulation Model (GCM) was recently equipped with a complete Global Carbon Cycle algorithm, consisting of three integrated components: Ent Terrestrial Biosphere Model (Ent TBM), Ocean Biogeochemistry Module and atmospheric CO2 tracer. Ent TBM provides CO2 fluxes from the land surface to the atmosphere. Its biophysics utilizes the well-known photosynthesis functions of Farqhuar, von Caemmerer, and Berry and Farqhuar and von Caemmerer, and stomatal conductance of Ball and Berry. Its phenology is based on temperature, drought, and radiation fluxes, and growth is controlled via allocation of carbon from labile carbohydrate reserve storage to different plant components. Soil biogeochemistry is based on the Carnegie-Ames-Stanford (CASA) model of Potter et al. Ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. Atmospheric CO2 is advected with a quadratic upstream algorithm implemented in atmospheric part of ModelE2. Here we present the results for pre-industrial equilibrium and modern transient simulations and provide comparison to available observations. We also discuss the process of validation and tuning of particular algorithms used in the model.

Stochasticity and organization of tropical convection: Role of stratiform heating in the simulation of MJO in an aquaplanet coarse resolution GCM using a stochastic multicloud parameterization

NASA Astrophysics Data System (ADS)

Khouider, B.; Majda, A.; Deng, Q.; Ravindran, A. M.

2015-12-01

Global climate models (GCMs) are large computer codes based on the discretization of the equations of atmospheric and oceanic motions coupled to various processes of transfer of heat, moisture and other constituents between land, atmosphere, and oceans. Because of computing power limitations, typical GCM grid resolution is on the order of 100 km and the effects of many physical processes, occurring on smaller scales, on the climate system are represented through various closure recipes known as parameterizations. The parameterization of convective motions and many processes associated with cumulus clouds such as the exchange of latent heat and cloud radiative forcing are believed to be behind much of uncertainty in GCMs. Based on a lattice particle interacting system, the stochastic multicloud model (SMCM) provide a novel and efficient representation of the unresolved variability in GCMs due to organized tropical convection and the cloud cover. It is widely recognized that stratiform heating contributes significantly to tropical rainfall and to the dynamics of tropical convective systems by inducing a front-to-rear tilt in the heating profile. Stratiform anvils forming in the wake of deep convection play a central role in the dynamics of tropical mesoscale convective systems. Here, aquaplanet simulations with a warm pool like surface forcing, based on a coarse-resolution GCM , of ˜170 km grid mesh, coupled with SMCM, are used to demonstrate the importance of stratiform heating for the organization of convection on planetary and intraseasonal scales. When some key model parameters are set to produce higher stratiform heating fractions, the model produces low-frequency and planetary-scale Madden Julian oscillation (MJO)-like wave disturbances while lower to moderate stratiform heating fractions yield mainly synoptic-scale convectively coupled Kelvin-like waves. Rooted from the stratiform instability, it is conjectured here that the strength and extent of stratiform downdrafts are key contributors to the scale selection of convective organizations perhaps with mechanisms that are in essence similar to those of mesoscale convective systems.

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects

NASA Astrophysics Data System (ADS)

Gu, B.; Yang, P.; Kuo, C. P.; Mlawer, E. J.

2017-12-01

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects Boyan Gu1, Ping Yang1, Chia-Pang Kuo1, Eli J. Mlawer2 Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA Atmospheric and Environmental Research (AER), Lexington, MA 02421, USA Ice clouds play an important role in climate system, especially in the Earth's radiation balance and hydrological cycle. However, the representation of ice cloud radiative effects (CRE) remains significant uncertainty, because scattering properties of ice clouds are not well considered in general circulation models (GCM). We analyze the strengths and weakness of the Rapid Radiative Transfer Model for GCM Applications (RRTMG) and Fu-Liou Radiative Transfer Model (RTM) against rigorous LBLRTM-DISORT (a combination of Line-By-Line Radiative Transfer Model and Discrete Ordinate Radiative Transfer Model) calculations and CERES (Clouds and the Earth's Radiant Energy System) flux observations. In total, 6 US standard atmospheric profiles and 42 atmospheric profiles from Atmospheric and Environmental Research (AER) Company are used to evaluate the RRTMG and Fu-Liou RTM by LBLRTM-DISORT calculations from 0 to 3250 cm-1. Ice cloud radiative effect simulations with RRTMG and Fu-Liou RTM are initialized using the ice cloud properties from MODIS collection-6 products. Simulations of single layer ice cloud CRE by RRTMG and LBLRTM-DISORT show that RRTMG, neglecting scattering, overestimates the TOA flux by about 0-15 W/m2 depending on the cloud particle size and optical depth, and the most significant overestimation occurs when the particle effective radius is small (around 10 μm) and the cloud optical depth is intermediate (about 1-10). The overestimation reduces significantly when the similarity rule is applied to RRTMG. We combine ice cloud properties from MODIS Collection-6 and atmospheric profiles from the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) reanalysis to simulate ice cloud CRE, which is compared with CERES observations.

Comparisons of observed seasonal climate features with a winter and summer numerical simulation produced with the GLAS general circulation model

NASA Technical Reports Server (NTRS)

Halem, M.; Shukla, J.; Mintz, Y.; Wu, M. L.; Godbole, R.; Herman, G.; Sud, Y.

1979-01-01

Results are presented from numerical simulations performed with the general circulation model (GCM) for winter and summer. The monthly mean simulated fields for each integration are compared with observed geographical distributions and zonal averages. In general, the simulated sea level pressure and upper level geopotential height field agree well with the observations. Well simulated features are the winter Aleutian and Icelandic lows, the summer southwestern U.S. low, the summer and winter oceanic subtropical highs in both hemispheres, and the summer upper level Tibetan high and Atlantic ridge. The surface and upper air wind fields in the low latitudes are in good agreement with the observations. The geographical distirbutions of the Earth-atmosphere radiation balance and of the precipitation rates over the oceans are well simulated, but not all of the intensities of these features are correct. Other comparisons are shown for precipitation along the ITCZ, rediation balance, zonally averaged temperatures and zonal winds, and poleward transports of momentum and sensible heat.

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

NASA Technical Reports Server (NTRS)

Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Matsui, Toshihisa; Li, J.-L.; Mohr, Karen I.; Skofronick-Jackson, Gail M.; Peters-Lidard, Christa D.

2016-01-01

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

Improvement of Mars Surface Snow Albedo Modeling in LMD Mars GCM With SNICAR

NASA Astrophysics Data System (ADS)

Singh, D.; Flanner, M. G.; Millour, E.

2018-03-01

The current version of Laboratoire de Météorologie Dynamique (LMD) Mars GCM (original-MGCM) uses annually repeating (prescribed) CO2 snow albedo values based on the Thermal Emission Spectrometer observations. We integrate the Snow, Ice, and Aerosol Radiation (SNICAR) model with MGCM (SNICAR-MGCM) to prognostically determine H2O and CO2 snow albedos interactively in the model. Using the new diagnostic capabilities of this model, we find that cryospheric surfaces (with dust) increase the global surface albedo of Mars by 0.022. Over snow-covered regions, SNICAR-MGCM simulates mean albedo that is higher by about 0.034 than prescribed values in the original-MGCM. Globally, shortwave flux into the surface decreases by 1.26 W/m2, and net CO2 snow deposition increases by about 4% with SNICAR-MGCM over one Martian annual cycle as compared to the original-MGCM simulations. SNICAR integration reduces the mean global surface temperature and the surface pressure of Mars by about 0.87% and 2.5%, respectively. Changes in albedo also show a similar distribution to dust deposition over the globe. The SNICAR-MGCM model generates albedos with higher sensitivity to surface dust content as compared to original-MGCM. For snow-covered regions, we improve the correlation between albedo and optical depth of dust from -0.91 to -0.97 with SNICAR-MGCM as compared to the original-MGCM. Dust substantially darkens Mars's cryosphere, thereby reducing its impact on the global shortwave energy budget by more than half, relative to the impact of pure snow.

A New Approach for Coupled GCM Sensitivity Studies

NASA Astrophysics Data System (ADS)

Kirtman, B. P.; Duane, G. S.

2011-12-01

A new multi-model approach for coupled GCM sensitivity studies is presented. The purpose of the sensitivity experiments is to understand why two different coupled models have such large differences in their respective climate simulations. In the application presented here, the differences between the coupled models using the Center for Ocean-Land-Atmosphere Studies (COLA) and the National Center for Atmospheric Research (NCAR) atmospheric general circulation models (AGCMs) are examined. The intent is to isolate which component of the air-sea fluxes is most responsible for the differences between the coupled models and for the errors in their respective coupled simulations. The procedure is to simultaneously couple the two different atmospheric component models to a single ocean general circulation model (OGCM), in this case the Modular Ocean Model (MOM) developed at the Geophysical Fluid Dynamics Laboratory (GFDL). Each atmospheric component model experiences the same SST produced by the OGCM, but the OGCM is simultaneously coupled to both AGCMs using a cross coupling strategy. In the first experiment, the OGCM is coupled to the heat and fresh water flux from the NCAR AGCM (Community Atmospheric Model; CAM) and the momentum flux from the COLA AGCM. Both AGCMs feel the same SST. In the second experiment, the OGCM is coupled to the heat and fresh water flux from the COLA AGCM and the momentum flux from the CAM AGCM. Again, both atmospheric component models experience the same SST. By comparing these two experimental simulations with control simulations where only one AGCM is used, it is possible to argue which of the flux components are most responsible for the differences in the simulations and their respective errors. Based on these sensitivity experiments we conclude that the tropical ocean warm bias in the COLA coupled model is due to errors in the heat flux, and that the erroneous westward shift in the tropical Pacific cold tongue minimum in the NCAR model is due errors in the momentum flux. All the coupled simulations presented here have warm biases along the eastern boundary of the tropical oceans suggesting that the problem is common to both AGCMs. In terms of interannual variability in the tropical Pacific, the CAM momentum flux is responsible for the erroneous westward extension of the sea surface temperature anomalies (SSTA) and errors in the COLA momentum flux cause the erroneous eastward migration of the El Niño-Southern Oscillation (ENSO) events. These conclusions depend on assuming that the error due to the OGCM can be neglected.

Utilizing Multi-Ensemble of Downscaled CMIP5 GCMs to Investigate Trends and Spatial and Temporal Extent of Drought in Willamette Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Beal, B.; Moradkhani, H.

2015-12-01

Changing climate and potential future increases in global temperature are likely to have impacts on drought characteristics and hydrologic cylce. In this study, we analyze changes in temporal and spatial extent of meteorological and hydrological droughts in future, and their trends. Three statistically downscaled datasets from NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), Multivariate Adaptive Constructed Analogs (MACA), and Bias Correction and Spatial Disagregation (BCSD-PSU) each consisting of 10 CMIP5 Global Climate Models (GCM) are utilized for RCP4.5 and RCP8.5 scenarios. Further, Precipitation Runoff Modeling System (PRMS) hydrologic model is used to simulate streamflow from GCM inputs and assess the hydrological drought characteristics. Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI) are the two indexes used to investigate meteorological and hydrological drought, respectively. Study is done for Willamette Basin with a drainage area of 29,700 km2 accommodating more than 3 million inhabitants and 25 dams. We analyze our study for annual time scale as well as three future periods of near future (2010-2039), intermediate future (2040-2069), and far future (2070-2099). Large uncertainty is found from GCM predictions. Results reveal that meteorological drought events are expected to increase in near future. Severe to extreme drought with large areal coverage and several years of occurance is predicted around year 2030 with the likelihood of exceptional drought for both drought types. SPI is usually showing positive trends, while SDI indicates negative trends in most cases.

Compressive properties of commercially available polyurethane foams as mechanical models for osteoporotic human cancellous bone

PubMed Central

Patel, Purvi SD; Shepherd, Duncan ET; Hukins, David WL

2008-01-01

Background Polyurethane (PU) foam is widely used as a model for cancellous bone. The higher density foams are used as standard biomechanical test materials, but none of the low density PU foams are universally accepted as models for osteoporotic (OP) bone. The aim of this study was to determine whether low density PU foam might be suitable for mimicking human OP cancellous bone. Methods Quasi-static compression tests were performed on PU foam cylinders of different lengths (3.9 and 7.7 mm) and of different densities (0.09, 0.16 and 0.32 g.cm-3), to determine the Young's modulus, yield strength and energy absorbed to yield. Results Young's modulus values were 0.08–0.93 MPa for the 0.09 g.cm-3 foam and from 15.1–151.4 MPa for the 0.16 and 0.32 g.cm-3 foam. Yield strength values were 0.01–0.07 MPa for the 0.09 g.cm-3 foam and from 0.9–4.5 MPa for the 0.16 and 0.32 g.cm-3 foam. The energy absorbed to yield was found to be negligible for all foam cylinders. Conclusion Based on these results, it is concluded that 0.16 g.cm-3 PU foam may prove to be suitable as an OP cancellous bone model when fracture stress, but not energy dissipation, is of concern. PMID:18844988

NASA Downscaling Project: Final Report

NASA Technical Reports Server (NTRS)

Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa

2017-01-01

A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA - 2 reanalyses were used to drive the NU - WRF regional climate model and a GEOS - 5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000 - 2010. The results of these experiments were compared to observational datasets to evaluate the output.

NASA Downscaling Project

NASA Technical Reports Server (NTRS)

Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa

2017-01-01

A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA-2 reanalyses were used to drive the NU-WRF regional climate model and a GEOS-5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000-2010. The results of these experiments were compared to observational datasets to evaluate the output.

Prognostic Aspects of Sub-seasonal Rainfall Characteristics using the Outputs of General Circulation Model: An Application of Statistical Downscaling and Temporal Disaggregation

NASA Astrophysics Data System (ADS)

Singh, A.; Mohanty, U. C.; Ghosh, K.

2015-12-01

Most regions of India experience varied rainfall duration during the southwest monsoon, changes in which exhibit major impact not only agriculture, but also other sectors like hydrology, agriculture, food and fodder storage etc. In addition, changes in sub-seasonal rainfall characteristics highly impact the rice production. As part of the endeavor seasonal climate outlook, as well as information for weather within climate may be helpful for advance planning and risk management in agriculture. The General Circulation Model (GCM) provide an alternative to gather information for weather within climate but variability is very low in comparison to observation. On the other hand, the spatial resolution of GCM predicted rainfall is not found at the observed station/grid point. To tackle the problem, initially a statistical downscaling over 19 station of Odisha state is undertaken using the atmospheric parameters predicted by a GCM (NCEP-CFSv2). For the purpose, an extended domain is taken for analyzing the significant zone for the atmospheric parameters like zonal wind at 850hPa, Sea Surface Temperature (SST), geopotential height. A statistical model using the pattern projection method is further developed based on empirical orthogonal function. The downscaled rainfall is found better in association with station observation in comparison to raw GCM prediction in view of deterministic and probabilistic skill measure. Further, the sub-seasonal and seasonal forecast from the GCMs can be used at different time steps for risk management. Therefore, downscaled seasonal/monthly rainfall is further converted to sub-seasonal/daily time scale using a non-homogeneous markov model. The simulated weather sequences are further compared with the observed sequence in view of categorical rainfall events. The outcomes suggest that the rainfall amount are overestimated for excess rainfall and henceforth larger excess rainfall events can be realized. The skill for prediction of rainfall events corresponding to lower thresholds is found higher. A detail discussion regarding skill of spatial downscale rainfall at observed stations and its further representation of sub-seasonal characteristics (spells, less rainfall, heavy rainfall, and moderate rainfall events) of rainfall for disaggregated outputs will be presented.

Glycycoumarin exerts anti-liver cancer activity by directly targeting T-LAK cell-originated protein kinase.

PubMed

Song, Xinhua; Yin, Shutao; Zhang, Enxiang; Fan, Lihong; Ye, Min; Zhang, Yong; Hu, Hongbo

2016-10-04

Glycycoumarin (GCM) is a major bioactive coumarin compound isolated from licorice and the anti-cancer activity of GCM has not been scientifically addressed. In the present study, we have tested the anti-liver cancer activity of GCM using both in vitro and in vivo models and found for the first time that GCM possesses a potent activity against liver cancer evidenced by cell growth inhibition and apoptosis induction in vitro and tumor reduction in vivo. Mechanistically, GCM was able to bind to and inactivate oncogenic kinase T-LAK cell-originated protein kinase (TOPK), which in turn led to activation of p53 pathway. Our findings supported GCM as a novel active compound that contributed to the anti-cancer activity of licorice and TOPK could be an effective target for hepatocellular carcinoma (HCC) treatment.

Unique relation between surface-limited evaporation and relative humidity profiles holds in both field data and climate model simulations

NASA Astrophysics Data System (ADS)

Salvucci, G.; Rigden, A. J.; Gentine, P.; Lintner, B. R.

2013-12-01

A new method was recently proposed for estimating evapotranspiration (ET) from weather station data without requiring measurements of surface limiting factors (e.g. soil moisture, leaf area, canopy conductance) [Salvucci and Gentine, 2013, PNAS, 110(16): 6287-6291]. Required measurements include diurnal air temperature, specific humidity, wind speed, net shortwave radiation, and either measured or estimated incoming longwave radiation and ground heat flux. The approach is built around the idea that the key, rate-limiting, parameter of typical ET models, the land-surface resistance to water vapor transport, can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. This relation was found to hold over a wide range of climate conditions (arid to humid) and limiting factors (soil moisture, leaf area, energy) at a set of Ameriflux field sites. While the field tests in Salvucci and Gentine (2013) supported the minimum variance hypothesis, the analysis did not reveal the mechanisms responsible for the behavior. Instead the paper suggested, heuristically, that the results were due to an equilibration of the relative humidity between the land surface and the surface layer of the boundary layer. Here we apply this method using surface meteorological fields simulated by a global climate model (GCM), and compare the predicted ET to that simulated by the climate model. Similar to the field tests, the GCM simulated ET is in agreement with that predicted by minimizing the profile relative humidity variance. A reasonable interpretation of these results is that the feedbacks responsible for the minimization of the profile relative humidity variance in nature are represented in the climate model. The climate model components, in particular the land surface model and boundary layer representation, can thus be analyzed in controlled numerical experiments to discern the specific processes leading to the observed behavior. Results of this analysis will be presented.

Simulation of the Intraseasonal Variability over the Eastern Pacific ITCZ in Climate Models

NASA Technical Reports Server (NTRS)

Jiang, Xianan; Waliser, Duane E.; Kim, Daehyun; Zhao, Ming; Sperber, Kenneth R.; Stern, W. F.; Schubert, Siegfried D.; Zhang, Guang J.; Wang, Wanqiu; Khairoutdinov, Marat;

Addressing extreme precipitation change under future climates in the Upper Yangtze River Basin

NASA Astrophysics Data System (ADS)

Yang, Z.; Yuan, Z.; Gao, X.

2017-12-01

Investigating the impact of climate change on extreme precipitation accurately is of importance for application purposes such as flooding mitigation and urban drainage system design. In this paper, a systematical analysis framework to assess the impact of climate change on extreme precipitation events is developed and practiced in the Upper Yangtze River Basin (UYRB) in China. Firstly, the UYRB is gridded and five extreme precipitation indices (annual maximum 3- 5- 7- 15- and 30-day precipitation) are selected. Secondly, with observed precipitation from China's Ground Precipitation 0.5°×0.5° Gridded Dataset (V2.0) and simulated daily precipitation from ten general circulation models (GCMs) of CMIP5, A regionally efficient GCM is selected for each grid by the skill score (SS) method which maximizes the overlapped area of probability density functions of extreme precipitation indices between observations and simulations during the historical period. Then, simulations of assembled efficient GCMs are bias corrected by Equidistant Cumulative Distribution Function method. Finally, the impact of climate change on extreme precipitation is analyzed. The results show that: (1) the MRI-CGCM3 and MIROC-ESM perform better in the UYRB. There are 19.8 to 20.9% and 14.2 to 18.7% of all grids regard this two GCMs as regionally efficient GCM for the five indices, respectively. Moreover, the regionally efficient GCMs are spatially distributed. (2) The assembled GCM performs much better than any single GCM, with the SS>0.8 and SS>0.6 in more than 65 and 85 percent grids. (3) Under the RCP4.5 scenario, the extreme precipitation of 50-year and 100-year return period is projected to increase in most areas of the UYRB in the future period, with 55.0 to 61.3% of the UYRB increasing larger than 10 percent for the five indices. The changes are spatially and temporal distributed. The upstream region of the UYRB has a relatively significant increase compared to the downstream basin, while the increase for annual maximum 5- and 7-day precipitation are more significant than other indices. The results demonstrate the impact of climate change on extreme precipitation in the UYRB, which provides a support to manage the water resource in this area.

Stratospheric chemistry and transport

NASA Technical Reports Server (NTRS)

Prather, Michael; Garcia, Maria M.

1990-01-01

A Chemical Tracer Model (CTM) that can use wind field data generated by the General Circulation Model (GCM) is developed to implement chemistry in the three dimensional GCM of the middle atmosphere. Initially, chemical tracers with simple first order losses such as N2O are used. Successive models are to incorporate more complex ozone chemistry.

TIME-GCM study of the ionospheric equatorial vertical drift changes during the 2006 stratospheric sudden warming

NASA Astrophysics Data System (ADS)

Maute, A.; Hagan, M. E.; Richmond, A. D.; Roble, R. G.

2014-02-01

This modeling study quantifies the daytime low-latitude vertical E×B drift changes in the longitudinal wave number 1 (wn1) to wn4 during the major extended January 2006 stratospheric sudden warming (SSW) period as simulated by the National Center for Atmospheric Research thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM), and attributes the drift changes to specific tides and planetary waves (PWs). The largest drift amplitude change (approximately 5 m/s) is seen in wn1 with a strong temporal correlation to the SSW. The wn1 drift is primarily caused by the semidiurnal westward propagating tide with zonal wave number 1 (SW1), and secondarily by a stationary planetary wave with zonal wave number 1 (PW1). SW1 is generated by the nonlinear interaction of PW1 and the migrating semidiurnal tide (SW2) at high latitude around 90-100 km. The simulations suggest that the E region PW1 around 100-130 km at the different latitudes has different origins: at high latitudes, the PW1 is related to the original stratospheric PW1; at midlatitudes, the model indicates PW1 is due to the nonlinear interaction of SW1 and SW2 around 95-105 km; and at low latitudes, the PW1 might be caused by the nonlinear interaction between DE2 and DE3. The time evolution of the simulated wn4 in the vertical E×B drift amplitude shows no temporal correlation with the SSW. The wn4 in the low-latitude vertical drift is attributed to the diurnal eastward propagating tide with zonal wave number 3 (DE3), and the contributions from SE2, TE1, and PW4 are negligible.

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

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

NASA Technical Reports Server (NTRS)

Barahona, Donifan; Sotiropoulou, Rafaella; Nenes, Athanasios

2011-01-01

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.

Application of molecular dynamics simulation to predict the compatability between water-insoluble drugs and self-associating poly(ethylene oxide)-b-poly(epsilon-caprolactone) block copolymers.

PubMed

Patel, Sarthak; Lavasanifar, Afsaneh; Choi, Phillip

2008-11-01

In the present work, molecular dynamics (MD) simulation was applied to study the solubility of two water-insoluble drugs, fenofibrate and nimodipine, in a series of micelle-forming PEO-b-PCL block copolymers with combinations of blocks having different molecular weights. The solubility predictions based on the MD results were then compared with those obtained from solubility experiments and by the commonly used group contribution method (GCM). The results showed that Flory-Huggins interaction parameters computed by the MD simulations are consistent with the solubility data of the drug/PEO-b-PCL systems, whereas those calculated by the GCM significantly deviate from the experimental observation. We have also accounted for the possibility of drug solubilization in the PEO block of PEO-b-PCL.

An Aerobraking Strategy for Determining Mars Upper Atmospheric Structure

NASA Astrophysics Data System (ADS)

Bougher, S. W.; Murphy, J. R.; Haberle, R. M.

1997-07-01

The Mars Global Surveyor (MGS) spacecraft will enter Mars orbit on Sept. 12, 1997, and thereafter undergo aerobraking for roughly 4-months. The final data-taking orbit to be achieved is sun-synchronous (2PM/2AM). An aerobraking strategy has been developed that not only will provide the walk-in capability needed to safely achieve the required Mars orbit, but also will provide a careful monitoring of the atmospheric structure. In particular, the linkage between the lower (0-100 km) and upper (100- 150 km) Mars atmospheres will be investigated. A suite of complementary measurements is planned that will probe the atmosphere over 0-150 km, including : (1) MGS Accelerometer density and inferred temperatures (100-150 km), (2) MGS Thermal Emission Spectrometer (TES) nadir (25-30 km) and limb (up to about 55 km) temperatures, (3) MGS Electron Reflectometer (ER) F1-peak heights (near 130 km), (4) ground-based microwave disk-averaged temperatures (0-70 km), and (5) Mars Pathfinder (MPF) surface meteorological data at 20 N latitude. These datasets acquired during the aerobraking phase will enable the current state of the atmosphere to be examined. Potential dust storm activity and its manifestations throughout the atmosphere can be monitored over Ls = 184 to 250. A corresponding library of coupled 3-D model simulations, based upon the NASA Ames Mars GCM and the NCAR Mars Thermospheric GCM (MTGCM), will be used to : (1) validate the current state of the Mars atmosphere, (2) investigate the various orbital, seasonal, LAT-LT-LON, and potential dust storm trends, and (3) predict the structure of the Mars atmosphere in the aerobraking corridor that is approaching in future MGS orbits. The in-situ accelerometer and ER data will eventually be used to construct a Mars empirical model covering 100-150 km. We will present a few selected GCM simulations to illustrate the expected atmospheric response to a dust storm event. In addition, we will discuss why these upper atmosphere datasets are important to future Mars missions.

Thermosphere-Ionosphere-Mesosphere Modeling Using the Time-GCM

DTIC Science & Technology

1997-09-30

observations during the GEM/SUNDIAL period of 28-29 March 1992,” J . Geophys. Res., 101, 26,681-26,696. T . J . Fuller-Rowell, M. V. Codrescu, R. G. Roble, and...South Pole, Mawson and Halley. The simulation provided a global background context upon which the widely-separated optical observations can be placed. The...of the ionosphere,” J . Geophys. Res., submitted. B. A. Emery, et al., 1996. “AMIE-TIGCM comparisons with global ionospheric and thermospheric

Large-scale drivers of local precipitation extremes in convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen

2016-04-01

The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

A Single-Phase Analytic Equation of State for Solid Polyurea and Polyurea Aerogels

NASA Astrophysics Data System (ADS)

Whitworth, Nicholas; Lambourn, Brian

2017-06-01

Commercially available polymers are commonly used as impactors in high explosive gas-gun experiments. This paper presents a relatively simple, single-phase, analytic equation of state (EoS) for solid polyurea and polyurea aerogels suitable for use in hydrocode simulations. An exponential shock velocity-particle velocity relation is initially fit to available Hugoniot data on the solid material, which has a density of 1.13 g/cm3. This relation is then converted to a finite strain relation along the principal isentrope, which is used as the reference curve for a Mie-Gruneisen form of EoS with an assumed form for the variation of Gruneisen Γ with specific volume. Using the solid EoS in conjunction with the Snowplough model for porosity, experimental data on the shock response of solid polyurea and polyurea aerogels with initial densities of 0.20 and 0.35 g/cm3 can be reproduced to a reasonable degree of accuracy. A companion paper at this conference describes the application of this and other EoS in modelling shock-release-reshock gas-gun experiments on the insensitive high explosive PBX 9502.

Downscaling GCM Output with Genetic Programming Model

NASA Astrophysics Data System (ADS)

Shi, X.; Dibike, Y. B.; Coulibaly, P.

2004-05-01

Climate change impact studies on watershed hydrology require reliable data at appropriate spatial and temporal resolution. However, the outputs of the current global climate models (GCMs) cannot be used directly because GCM do not provide hourly or daily precipitation and temperature reliable enough for hydrological modeling. Nevertheless, we can get more reliable data corresponding to future climate scenarios derived from GCM outputs using the so called 'downscaling techniques'. This study applies Genetic Programming (GP) based technique to downscale daily precipitation and temperature values at the Chute-du-Diable basin of the Saguenay watershed in Canada. In applying GP downscaling technique, the objective is to find a relationship between the large-scale predictor variables (NCEP data which provide daily information concerning the observed large-scale state of the atmosphere) and the predictand (meteorological data which describes conditions at the site scale). The selection of the most relevant predictor variables is achieved using the Pearson's coefficient of determination ( R2) (between the large-scale predictor variables and the daily meteorological data). In this case, the period (1961 - 2000) is identified to represent the current climate condition. For the forty years of data, the first 30 years (1961-1990) are considered for calibrating the models while the remaining ten years of data (1991-2000) are used to validate those models. In general, the R2 between the predictor variables and each predictand is very low in case of precipitation compared to that of maximum and minimum temperature. Moreover, the strength of individual predictors varies for every month and for each GP grammar. Therefore, the most appropriate combination of predictors has to be chosen by looking at the output analysis of all the twelve months and the different GP grammars. During the calibration of the GP model for precipitation downscaling, in addition to the mean daily precipitation and daily precipitation variability for each month, monthly average dry and wet-spell lengths are also considered as performance criteria. For the cases of Tmax and Tmin, means and variances of these variables corresponding to each month were considered as performance criteria. The GP downscaling results show satisfactory agreement between the observed daily temperature (Tmax and Tmin) and the simulated temperature. However, the downscaling results for the daily precipitation still require some improvement - suggesting further investigation of other grammars. KEY WORDS: Climate change; GP downscaling; GCM.

Tropical cloud feedbacks and natural variability of climate

NASA Technical Reports Server (NTRS)

Miller, R. L.; Del Genio, A. D.

1994-01-01

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

Dynamic climate emulators for solar geoengineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacMartin, Douglas G.; Kravitz, Ben

2016-12-22

Climate emulators trained on existing simulations can be used to project project the climate effects that result from different possible future pathways of anthropogenic forcing, without further relying on general circulation model (GCM) simulations. We extend this idea to include different amounts of solar geoengineering in addition to different pathways of greenhouse gas concentrations, by training emulators from a multi-model ensemble of simulations from the Geoengineering Model Intercomparison Project (GeoMIP). The emulator is trained on the abrupt 4 × CO 2 and a compensating solar reduction simulation (G1), and evaluated by comparing predictions against a simulated 1 % per yearmore » CO 2 increase and a similarly smaller solar reduction (G2). We find reasonable agreement in most models for predicting changes in temperature and precipitation (including regional effects), and annual-mean Northern Hemisphere sea ice extent, with the difference between simulation and prediction typically being smaller than natural variability. This verifies that the linearity assumption used in constructing the emulator is sufficient for these variables over the range of forcing considered. Annual-minimum Northern Hemisphere sea ice extent is less well predicted, indicating a limit to the linearity assumption.« less

Technical Challenges and Solutions in Representing Lakes when using WRF in Downscaling Applications

EPA Science Inventory

The Weather Research and Forecasting (WRF) model is commonly used to make high resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional ...

The thin-layer drying characteristics of sewage sludge by the appropriate foaming pretreatment.

PubMed

Wang, Hui-Ling; Yang, Zhao-Hui; Huang, Jing; Wang, Li-Ke; Gou, Cheng-Liu; Yan, Jing-Wu; Yang, Jian

2014-01-01

As dewatered sludge is highly viscous and sticky, the combination of foaming pretreatment and drying process seems to be an alternative method to improve the drying performance of dewatered sludge. In this study, CaO addition followed by mechanical whipping was employed for foaming the dewatered sludge. It was found that the foams were stable and the diameters of bubbles mainly ranged from 0.1 to 0.3 mm. The drying experiments were carried out in a drying oven in the convective mode. The results indicated that foamed sludge at 0.70 g/cm(3) had the best drying performance at each level of temperature, which could save 35-45% drying time to reach 20% moisture content compared with the non-foamed sludge. The drying rate of foamed sludge at 0.70 g/cm(3) was improved with the increasing of drying temperature. The impact of sample thickness on drying rate was not obvious when the sample thickness increased from 2 to 8 mm. Different mathematical models were used for the simulation of foamed sludge drying curves. The Wang and Singh model represented the drying characteristics better than other models with coefficient of determination values over 0.99.

Numerical simulation of the 6 day wave effects on the ionosphere: Dynamo modulation

NASA Astrophysics Data System (ADS)

Gan, Quan; Wang, Wenbing; Yue, Jia; Liu, Hanli; Chang, Loren C.; Zhang, Shaodong; Burns, Alan; Du, Jian

2016-10-01

The Thermosphere-Ionosphere-Mesosphere Electrodynamics General Circulation Model (TIME-GCM) is used to theoretically study the 6 day wave effects on the ionosphere. By introducing a 6 day perturbation with zonal wave number 1 at the model lower boundary, the TIME-GCM reasonably reproduces the 6 day wave in temperature and horizontal winds in the mesosphere and lower thermosphere region during the vernal equinox. The E region wind dynamo exhibits a prominent 6 day oscillation that is directly modulated by the 6 day wave. Meanwhile, significant local time variability (diurnal and semidiurnal) is also seen in wind dynamo as a result of altered tides due to the nonlinear interaction between the 6 day wave and migrating tides. More importantly, the perturbations in the E region neutral winds (both the 6 day oscillation and tidal-induced short-term variability) modulate the polarization electric fields, thus leading to the perturbations in vertical ion drifts and ionospheric F2 region peak electron density (NmF2). Our modeling work shows that the 6 day wave couples with the ionosphere via both the direct neutral wind modulation and the interaction with atmospheric tides.

Seasonal predictability of Arctic Sea Ice: assessing its limits and potential in a GCM and implications for observations.

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.

2012-12-01

Arctic sea ice has exhibited a dramatic decrease both in area and thickness over the recent decades, particularly during the summer months. This decrease has led to growing interest in the potential predictability of summer sea ice, spurred in part by the socioeconomic implications. Here we present results of several parallel experiments designed to assess and understand the limits and potential for seasonal predictability of Arctic sea ice, with an emphasis on the summer minimum. Building on our experience from the SEARCH Outlook, we present results of a coupled general circulation model (GCM) hindcast simulation of Arctic summer sea ice variability for the satellite period (1979-present). These are initialized with spring sea ice volume anomalies obtained from a modelling and assimilation system, considered to be a close representation of reality. We show that there is significant predictability, yet the stochastic forcing imparted mainly by the atmosphere can lead to large errors in the hindcast. The model, however, can simulate anomalous runs that lie beyond a Gaussian distribution. Additionally, we investigate the regional characteristics of predictability and its links to sea ice dynamics and the spatio-temporal behavior of sea ice anomalies. We show a distinct difference between models. Unfortunately, observational data of thickness are not yet detailed enough to assess the models. Our results indicate the potential for detailed ice thickness observations in improving regional predictability. Finally, we discuss the importance of experiment design in predictability experiments, and show that predictions made with models that have a large mean state bias in sea ice require a careful initialization in order to fully capture all initial value predictability.

Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

NASA Astrophysics Data System (ADS)

Bergant, Klemen; Kajfež-Bogataj, Lučka; Črepinšek, Zalika

2002-02-01

Phenological observations are a valuable source of information for investigating the relationship between climate variation and plant development. Potential climate change in the future will shift the occurrence of phenological phases. Information about future climate conditions is needed in order to estimate this shift. General circulation models (GCM) provide the best information about future climate change. They are able to simulate reliably the most important mean features on a large scale, but they fail on a regional scale because of their low spatial resolution. A common approach to bridging the scale gap is statistical downscaling, which was used to relate the beginning of flowering of Taraxacum officinale in Slovenia with the monthly mean near-surface air temperature for January, February and March in Central Europe. Statistical models were developed and tested with NCAR/NCEP Reanalysis predictor data and EARS predictand data for the period 1960-1999. Prior to developing statistical models, empirical orthogonal function (EOF) analysis was employed on the predictor data. Multiple linear regression was used to relate the beginning of flowering with expansion coefficients of the first three EOF for the Janauary, Febrauary and March air temperatures, and a strong correlation was found between them. Developed statistical models were employed on the results of two GCM (HadCM3 and ECHAM4/OPYC3) to estimate the potential shifts in the beginning of flowering for the periods 1990-2019 and 2020-2049 in comparison with the period 1960-1989. The HadCM3 model predicts, on average, 4 days earlier occurrence and ECHAM4/OPYC3 5 days earlier occurrence of flowering in the period 1990-2019. The analogous results for the period 2020-2049 are a 10- and 11-day earlier occurrence.

A generalized conditional heteroscedastic model for temperature downscaling

NASA Astrophysics Data System (ADS)

Modarres, R.; Ouarda, T. B. M. J.

2014-11-01

This study describes a method for deriving the time varying second order moment, or heteroscedasticity, of local daily temperature and its association to large Coupled Canadian General Circulation Models predictors. This is carried out by applying a multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) approach to construct the conditional variance-covariance structure between General Circulation Models (GCMs) predictors and maximum and minimum temperature time series during 1980-2000. Two MGARCH specifications namely diagonal VECH and dynamic conditional correlation (DCC) are applied and 25 GCM predictors were selected for a bivariate temperature heteroscedastic modeling. It is observed that the conditional covariance between predictors and temperature is not very strong and mostly depends on the interaction between the random process governing temporal variation of predictors and predictants. The DCC model reveals a time varying conditional correlation between GCM predictors and temperature time series. No remarkable increasing or decreasing change is observed for correlation coefficients between GCM predictors and observed temperature during 1980-2000 while weak winter-summer seasonality is clear for both conditional covariance and correlation. Furthermore, the stationarity and nonlinearity Kwiatkowski-Phillips-Schmidt-Shin (KPSS) and Brock-Dechert-Scheinkman (BDS) tests showed that GCM predictors, temperature and their conditional correlation time series are nonlinear but stationary during 1980-2000 according to BDS and KPSS test results. However, the degree of nonlinearity of temperature time series is higher than most of the GCM predictors.

Supporting ITM Missions by Observing System Simulation Experiments: Initial Design, Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Yudin, V. A.; England, S.; Matsuo, T.; Wang, H.; Immel, T. J.; Eastes, R.; Akmaev, R. A.; Goncharenko, L. P.; Fuller-Rowell, T. J.; Liu, H.; Solomon, S. C.; Wu, Q.

2014-12-01

We review and discuss the capability of novel configurations of global community (WACCM-X and TIME-GCM) and planned-operational (WAM) models to support current and forthcoming space-borne missions to monitor the dynamics and composition of the Ionosphere-Thermosphere-Mesosphere (ITM) system. In the specified meteorology model configuration of WACCM-X, the lower atmosphere is constrained by operational analyses and/or short-term forecasts provided by the Goddard Earth Observing System (GEOS-5) of GMAO/NASA/GSFC. With the terrestrial weather of GEOS-5 and updated model physics, WACCM-X simulations are capable to reproduce the observed signatures of the perturbed wave dynamics and ion-neutral coupling during recent (2006-2013) stratospheric warming events, short-term, annual and year-to-year variability of prevailing flows, planetary waves, tides, and composition. With assimilation of the NWP data in the troposphere and stratosphere the planned-operational configuration of WAM can also recreate the observed features of the ITM day-to-day variability. These "terrestrial-weather" driven whole atmosphere simulations, with day-to-day variable solar and geomagnetic inputs, can provide specification of the background state (first guess) and errors for the inverse algorithms of forthcoming NASA ITM missions, such as ICON and GOLD. With two different viewing geometries (sun-synchronous, for ICON and geostationary for GOLD) these missions promise to perform complimentary global observations of temperature, winds and constituents to constrain the first-principle space weather forecast models. The paper will discuss initial designs of Observing System Simulation Experiments (OSSE) in the coupled simulations of TIME-GCM/WACCM-X/GEOS5 and WAM/GIP. As recognized, OSSE represent an excellent learning tool for designing and evaluating observing capabilities of novel sensors. The choice of assimilation schemes, forecast and observational errors will be discussed along with challenges and perspectives to constrain fast-varying dynamics of tides and planetary waves by observations made from sun-synchronous and geostationary space-borne platforms. We will also discuss how correlative space-borne and ground-based observations can evaluate OSSE results.

Sq Currents and Neutral Winds

NASA Astrophysics Data System (ADS)

Yamazaki, Y.

2015-12-01

The relationship between ionospheric dynamo currents and neutral winds is examined using the Thermosphere Ionosphere Mesosphere Electrodynamic General Circulation Model (TIME-GCM). The simulation is run for May and June 2009 with variable neutral winds but with constant solar and magnetospheric energy inputs, which ensures that day-to-day changes in the solar quiet (Sq) current system arise only from lower atmospheric forcing. The intensity and focus position of the simulated Sq current system exhibit large day-to-day variability, as is also seen in ground magnetometer data. We show how the day-to-day variation of the Sq current system relate to variable winds at various altitudes, latitudes, and longitudes.

CORDEX Coordinated Output for Regional Evaluation

NASA Astrophysics Data System (ADS)

Gutowski, William; Giorgi, Filippo; Lake, Irene

2017-04-01

The Science Advisory Team for the Coordinated Regional Downscaling Experiment (CORDEX) has developed a baseline framework of specified regions, resolutions and simulation periods intended to provide a foundation for ongoing regional CORDEX activities: the CORDEX Coordinated Output for Regional Evaluation, or CORDEX-CORE. CORDEX-CORE was conceived in part to be responsive to IPCC needs for coordinated simulations that could provide regional climate downscaling (RCD) that yields fine-scale climate information beyond that resolved by GCMs. For each CORDEX region, a matrix of GCM-RCD experiments is designed based on the need to cover as much as possible different dimensions of the uncertainty space (e.g., different emissions and land-use scenarios, GCMs, RCD models and techniques). An appropriate set of driving GCMs can allow a program of simulations that efficiently addresses key scientific issues within CORDEX, while facilitating comparison and transfer of results and lessons learned across different regions. The CORDEX-CORE program seeks to provide, as much as possible, homogeneity across domains, so it is envisioned that a standard set of regional climate models (RCMs) and empirical statistical downscaling (ESD) methods will downscale a standard set of GCMs over all or at least most CORDEX domains for a minimum set of scenarios (high and low end). The focus is on historical climate simulations for the 20th century and projections for 21st century, implying that data would be needed minimally for the period 1950-2100 (but ideally 1900-2100). This foundational ensemble can be regionally enriched with further contributions (additional GCM-RCD pairs) by individual groups over their selected domains of interest. The RCM model resolution for these core experiments will be in the range of 10-20 km, a resolution that has been shown to provide substantial added value for a variety of climate variables and that represents a significant forward step compared in the CORDEX program. This presentation presents the vision and structure of CORDEX-CORE while also soliciting discussion on plans for implementing the program.

Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices

NASA Astrophysics Data System (ADS)

Seo, Seung Beom; Kim, Young-Oh; Kim, Youngil; Eum, Hyung-Il

2018-04-01

When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis-Kuo-Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models.

Formation of the Martian Polar Layered Terrains: Quantifying Polar Water Ice and Dust Surface Deposition during Current and Past Orbital Epochs with the NASA Ames GCM

NASA Astrophysics Data System (ADS)

Emmett, Jeremy; Murphy, Jim

2016-10-01

Structural and compositional variability in the layering sequences comprising Mars' polar layered terrains (PLT's) is likely explained by orbital-forced climatic variations in the sedimentary cycles of water ice and dust from which they formed [1]. The PLT's therefore contain a direct, extensive record of the recent climate history of Mars encoded in their structure and stratigraphy, but deciphering this record requires understanding the depositional history of their dust and water ice constituents. 3D Mars atmosphere modeling enables direct simulation of atmospheric dynamics, aerosol transport and quantification of surface accumulation for a range of past and present orbital configurations. By quantifying the net yearly polar deposition rates of water ice and dust under Mars' current and past orbital configurations characteristic of the last several millions of years, and integrating these into the present with a time-stepping model, the formation history of the north and south PLT's will be investigated, further constraining their age and composition, and, if reproducible, revealing the processes responsible for prominent features and stratigraphy observed within the deposits. Simulating the formation of the deposits by quantifying net deposition rates during past orbital epochs and integrating these into the present, effectively 'rebuilding' the terrains, could aid in understanding deeper stratigraphic trends, correlating between geographically-separated deposits, explaining the presence and shapes of large-scale polar features, and correlating stratigraphy with geological time. Quantification of the magnitude and geographical distribution of surface aerosol accumulation will build on the work of previous GCM-based investigations [3]. Construction and analysis of hypothetical stratigraphic sequences in the PLT's will draw from previous climate-controlled stratigraphy methodologies [2,4], but will utilize GCM-derived net deposition rates to model orbital influences on sedimentation and erosion.[1] Milkovich S.M. and Head J. W. (2005) JGR, 110. [2] Laskar J.B. and Mustard J.F. (2002) Nature, 419, 375-377 [3] Newman C.E. et al. (2005) Icarus, 174, 135-160. [4] Hvidberg C.S. et al. (2012) Icarus, 221, 405-419.

Detection and Attribution of Regional Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

Patterns of LGM precipitation in the U.S. Rocky Mountains: results from regional application of a glacier mass/energy balance and flow model

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J.; Refsnider, K. A.; Plummer, M. A.; Jacobsen, R. E.; Wollenberg, J. A.

2010-12-01

Global climate model (GCM) simulations of the last glacial maximum (LGM) in the western United States predict changes in atmospheric circulation and storm tracks that would have resulted in significantly less-than-modern precipitation in the Northwest and northern Rockies, and significantly more-than-modern precipitation in the Southwest and southern Rockies. Model simulations also suggest that late Pleistocene pluvial lakes in the intermontane West may have modified local moisture regimes in areas immediately downwind. In this study, we present results of the application of a coupled energy/mass balance and glacier-flow model (Plummer and Phillips, 2003) to reconstructed paleoglaciers in Rocky Mountains of Utah, New Mexico, Colorado, and Wyoming to assess the changes from modern climate that would have been necessary to sustain each glacier in mass-balance equilibrium at its LGM extent. Results demonstrate that strong west-to-east and north-to-south gradients in LGM precipitation, relative to present, would be required if a uniform LGM temperature depression with respect to modern is assumed across the region. At an assumed 7oC temperature depression, approximately modern precipitation would have been necessary to support LGM glaciation in the Colorado Front Range, significantly less than modern precipitation to support glaciation in the Teton Range, and almost twice modern precipitation to sustain glaciers in the Wasatch and Uinta ranges of Utah and the New Mexico Sangre de Cristo Range. The observed west-to-east (Utah-to-Colorado) LGM moisture gradient is consistent with precipitation enhancement from pluvial Lake Bonneville, decreasing with distance downwind from the lake. The north-to-south (Wyoming-to-New Mexico) LGM moisture gradient is consistent with a southward LGM displacement of the mean winter storm track associated with the winter position of the Pacific Jet Stream across the western U.S. Our analysis of paleoglacier extents in the Rocky Mountain region supports the results of GCM simulations of western U.S. precipitation distribution during the LGM, and suggests that this approach provides a practical means of testing such hypotheses about large-scale paleoclimate patterns. Finally, we note that most GCM results indicate greater LGM temperature depression in the northern and eastern portions of the study region than in its southern and western portions - which would necessitate LGM precipitation differences even greater than those determined based on an assumed uniform temperature depression.

Assessing climate change impact by integrated hydrological modelling

NASA Astrophysics Data System (ADS)

Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

2013-04-01

Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations showed some unexpected results, where climate models predicting the largest increase in net precipitation did not result in the largest increase in groundwater heads. This was found to be the result of different initial conditions (1990 - 2010) for the various climate models. In some areas a combination of a high initial groundwater head and an increase in precipitation towards 2021 - 2050 resulted in a groundwater head raise that reached the drainage or the surface water system. This will increase the exchange from the groundwater to the surface water system, but reduce the raise in groundwater heads. An alternative climate model, with a lower initial head can thus predict a higher increase in the groundwater head, although the increase in precipitation is lower. This illustrates an extra dimension in the uncertainty assessment, namely the climate models capability of simulating the current climatic conditions in a way that can reproduce the observed hydrological response. Højberg, AL, Troldborg, L, Stisen, S, et al. (2012) Stakeholder driven update and improvement of a national water resources model - http://www.sciencedirect.com/science/article/pii/S1364815212002423 Seaby, LP, Refsgaard, JC, Sonnenborg, TO, et al. (2012) Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections (submitted) Journal of Hydrology Stisen, S, Højberg, AL, Troldborg, L et al., (2012): On the importance of appropriate rain-gauge catch correction for hydrological modelling at mid to high latitudes - http://www.hydrol-earth-syst-sci.net/16/4157/2012/

Analysis of the anomalous mean-field like properties of Gaussian core model in terms of entropy

NASA Astrophysics Data System (ADS)

Nandi, Manoj Kumar; Maitra Bhattacharyya, Sarika

2018-01-01

Studies of the Gaussian core model (GCM) have shown that it behaves like a mean-field model and the properties are quite different from standard glass former. In this work, we investigate the entropies, namely, the excess entropy (Sex) and the configurational entropy (Sc) and their different components to address these anomalies. Our study corroborates most of the earlier observations and also sheds new light on the high and low temperature dynamics. We find that unlike in standard glass former where high temperature dynamics is dominated by two-body correlation and low temperature by many-body correlations, in the GCM both high and low temperature dynamics are dominated by many-body correlations. We also find that the many-body entropy which is usually positive at low temperatures and is associated with activated dynamics is negative in the GCM suggesting suppression of activation. Interestingly despite the suppression of activation, the Adam-Gibbs (AG) relation that describes activated dynamics holds in the GCM, thus suggesting a non-activated contribution in AG relation. We also find an overlap between the AG relation and mode coupling power law regime leading to a power law behavior of Sc. From our analysis of this power law behavior, we predict that in the GCM the high temperature dynamics will disappear at dynamical transition temperature and below that there will be a transition to the activated regime. Our study further reveals that the activated regime in the GCM is quite narrow.

Stable water isotope behavior during the last glacial maximum: A general circulation model analysis

NASA Technical Reports Server (NTRS)

Jouzel, Jean; Koster, Randal D.; Suozzo, Robert J.; Russell, Gary L.

1994-01-01

Global water isotope geochemisty during the last glacial maximum (LGM) is simulated with an 8 deg x 10 deg atmospheric general circulation model (GCM). The simulation results suggest that the spatial delta O-18/temperature relationships observed for the present day and LGM climates are very similar. Furthermore, the temporal delta O-18/temperature relationship is similar to the present-day spatial relationship in regions for which the LGM/present-day temperature change is significant. This helps justify the standard practice of applying the latter to the interpretation of paleodata, despite the possible influence of other factors, such as changes in the evaportive sources of precipitation or in the seasonality of precipitation. The model suggests, for example, that temperature shifts inferred from ice core data may differ from the true shifts by only about 30%.

Regional Climate Change across North America in 2030 Projected from RCP6.0

NASA Astrophysics Data System (ADS)

Otte, T.; Nolte, C. G.; Faluvegi, G.; Shindell, D. T.

2012-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. In this research, downscaling techniques that we developed with historical data are now applied to GCM fields. Results from downscaling NASA/GISS ModelE2 simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model has been used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 over North America and illustrate potential changes in regional climate that are projected by ModelE2 and WRF under RCP6.0. The analysis focuses on regional climate fields that most strongly influence the interactions between climate change and air quality. In particular, an analysis of extreme temperature and precipitation events will be presented.

Northern Hemisphere winter-like stratospheric variability in an idealized GCM using tropospheric heating perturbations

NASA Astrophysics Data System (ADS)

Lindgren, E. A.; Sheshadri, A.; Plumb, R. A.

2017-12-01

Tropospheric heating perturbations are used to create Northern Hemisphere winter-like stratospheric variability in an idealized atmospheric GCM. Model results with wave 1 and 2 heating perturbations are compared to a model with wave 2 topography, which has previously been shown to produce a realistic sudden stratospheric warming frequency. It is found that both wave 1 and wave 2 heating perturbations cause both split and displacement sudden warmings. This is different from the wave 2 topographic forcing, which only produces splits. Furthermore, the tropospheric heating is shown to produce more reasonable annular mode timescales in the troposphere compared to the topographic forcing. It is argued that the model with wave 2 tropospheric heating perturbation is better at simulating Northern Hemisphere stratospheric variability compared to the model with wave 2 topographic forcing. The long-term variability of zonal winds in the wave 2 heating run is also investigated, under both perpetual winter conditions and with a seasonal cycle. It is found that midlatitude winds in the perpetual winter version of the model exhibit variability on timescales of around 1000 days. These variations are thought to be connected to the QBO-like oscillations in tropical winds found in the model. This connection is further explored in the seasonal cycle version of the model as well as full GCMs with QBOs, where the correlations between tropical winds and polar vortex strength are investigated.

Projecting climate change impacts on hydrology: the potential role of daily GCM output

NASA Astrophysics Data System (ADS)

Maurer, E. P.; Hidalgo, H. G.; Das, T.; Dettinger, M. D.; Cayan, D.

2008-12-01

A primary challenge facing resource managers in accommodating climate change is determining the range and uncertainty in regional and local climate projections. This is especially important for assessing changes in extreme events, which will drive many of the more severe impacts of a changed climate. Since global climate models (GCMs) produce output at a spatial scale incompatible with local impact assessment, different techniques have evolved to downscale GCM output so locally important climate features are expressed in the projections. We compared skill and hydrologic projections using two statistical downscaling methods and a distributed hydrology model. The downscaling methods are the constructed analogues (CA) and the bias correction and spatial downscaling (BCSD). CA uses daily GCM output, and can thus capture GCM projections for changing extreme event occurrence, while BCSD uses monthly output and statistically generates historical daily sequences. We evaluate the hydrologic impacts projected using downscaled climate (from the NCEP/NCAR reanalysis as a surrogate GCM) for the late 20th century with both methods, comparing skill in projecting soil moisture, snow pack, and streamflow at key locations in the Western United States. We include an assessment of a new method for correcting for GCM biases in a hybrid method combining the most important characteristics of both methods.

Multi-scale Modeling of Arctic Clouds

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

2017-12-01

The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

2010-12-01

Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.

Role of a cumulus parameterization scheme in simulating atmospheric circulation and rainfall in the nine-layer Goddard Laboratory for Atmospheres General Circulation Model

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Chao, Winston C.; Walker, G. K.

1992-01-01

The influence of a cumulus convection scheme on the simulated atmospheric circulation and hydrologic cycle is investigated by means of a coarse version of the GCM. Two sets of integrations, each containing an ensemble of three summer simulations, were produced. The ensemble sets of control and experiment simulations are compared and differentially analyzed to determine the influence of a cumulus convection scheme on the simulated circulation and hydrologic cycle. The results show that cumulus parameterization has a very significant influence on the simulation circulation and precipitation. The upper-level condensation heating over the ITCZ is much smaller for the experiment simulations as compared to the control simulations; correspondingly, the Hadley and Walker cells for the control simulations are also weaker and are accompanied by a weaker Ferrel cell in the Southern Hemisphere. Overall, the difference fields show that experiment simulations (without cumulus convection) produce a cooler and less energetic atmosphere.

Uhlenbeck-Ford model: Phase diagram and corresponding-states analysis

NASA Astrophysics Data System (ADS)

Paula Leite, Rodolfo; Santos-Flórez, Pedro Antonio; de Koning, Maurice

2017-09-01

Using molecular dynamics simulations and nonequilibrium thermodynamic-integration techniques we compute the Helmholtz free energies of the body-centered-cubic (bcc), face-centered-cubic (fcc), hexagonal close-packed, and fluid phases of the Uhlenbeck-Ford model (UFM) and use the results to construct its phase diagram. The pair interaction associated with the UFM is characterized by an ultrasoft, purely repulsive pair potential that diverges logarithmically at the origin. We find that the bcc and fcc are the only thermodynamically stable crystalline phases in the phase diagram. Furthermore, we report the existence of two reentrant transition sequences as a function of the number density, one featuring a fluid-bcc-fluid succession and another displaying a bcc-fcc-bcc sequence near the triple point. We find strong resemblances to the phase behavior of other soft, purely repulsive systems such as the Gaussian-core model (GCM), inverse-power-law, and Yukawa potentials. In particular, we find that the fcc-bcc-fluid triple point and the phase boundaries in its vicinity are in good agreement with the prediction supplied by a recently proposed corresponding-states principle [J. Chem. Phys. 134, 241101 (2011), 10.1063/1.3605659; Europhys. Lett. 100, 66004 (2012), 10.1209/0295-5075/100/66004]. The particularly strong resemblance between the behavior of the UFM and GCM models are also discussed.

Mean-state acceleration of cloud-resolving models and large eddy simulations

DOE PAGES

Jones, C. R.; Bretherton, C. S.; Pritchard, M. S.

2015-10-29

In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate themore » evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.« less

Simulations and Evaluation of Mesoscale Convective Systems in a Multi-scale Modeling Framework (MMF)

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.

2017-12-01

It is well known that the mesoscale convective systems (MCS) produce more than 50% of rainfall in most tropical regions and play important roles in regional and global water cycles. Simulation of MCSs in global and climate models is a very challenging problem. Typical MCSs have horizontal scale of a few hundred kilometers. Models with a domain of several hundred kilometers and fine enough resolution to properly simulate individual clouds are required to realistically simulate MCSs. The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has shown some capabilities of simulating organized MCS-like storm signals and propagations. However, its embedded CRMs typically have small domain (less than 128 km) and coarse resolution ( 4 km) that cannot realistically simulate MCSs and individual clouds. In this study, a series of simulations were performed using the Goddard MMF. The impacts of the domain size and model grid resolution of the embedded CRMs on simulating MCSs are examined. The changes of cloud structure, occurrence, and properties such as cloud types, updraft and downdraft, latent heating profile, and cold pool strength in the embedded CRMs are examined in details. The simulated MCS characteristics are evaluated against satellite measurements using the Goddard Satellite Data Simulator Unit. The results indicate that embedded CRMs with large domain and fine resolution tend to produce better simulations compared to those simulations with typical MMF configuration (128 km domain size and 4 km model grid spacing).

A Vertically Resolved Planetary Boundary Layer

NASA Technical Reports Server (NTRS)

Helfand, H. M.

1984-01-01

Increase of the vertical resolution of the GLAS Fourth Order General Circulation Model (GCM) near the Earth's surface and installation of a new package of parameterization schemes for subgrid-scale physical processes were sought so that the GLAS Model GCM will predict the resolved vertical structure of the planetary boundary layer (PBL) for all grid points.

Equilibrium Atmospheric Response to North Atlantic SST Anomalies.

NASA Astrophysics Data System (ADS)

Kushnir, Yochanan; Held, Isaac M.

1996-06-01

The equilibrium general circulation model (GCM) response to sea surface temperature (SST) anomalies in the western North Atlantic region is studied. A coarse resolution GCM, with realistic lower boundary conditions including topography and climatological SST distribution, is integrated in perpetual January and perpetual October modes, distinguished from one another by the strength of the midlatitude westerlies. An SST anomaly with a maximum of 4°C is added to the climatological SST distribution of the model with both positive and negative polarity. These anomaly runs are compared to one another, and to a control integration, to determine the atmospheric response. In all cases warming (cooling) of the midlatitude ocean surface yields a warming (cooling) of the atmosphere over and to the east of the SST anomaly center. The atmospheric temperature change is largest near the surface and decreases upward. Consistent with this simple thermal response, the geopotential height field displays a baroclinic response with a shallow anomalous low somewhat downstream from the warm SST anomaly. The equivalent barotropic, downstream response is weak and not robust. To help interpret the results, the realistic GCM integrations are compared with parallel idealized model runs. The idealized model has full physics and a similar horizontal and vertical resolution, but an all-ocean surface with a single, permanent zonal asymmetry. The idealized and realistic versions of the GCM display compatible response patterns that are qualitatively consistent with stationary, linear, quasigeostrophic theory. However, the idealized model response is stronger and more coherent. The differences between the two model response patterns can be reconciled based on the size of the anomaly, the model treatment of cloud-radiation interaction, and the static stability of the model atmosphere in the vicinity of the SST anomaly. Model results are contrasted with other GCM studies and observations.

The Future of Planetary Climate Modeling and Weather Prediction

NASA Technical Reports Server (NTRS)

Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

2017-01-01

Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

The regional climate model RegCM3 performances over several regions and climate regimes

NASA Astrophysics Data System (ADS)

Coppola, E.; Rauscher, S.; Gao, X.; Giorgi, F.; Im, E. S.; Mariotti, L.; Seth, A.; Sylla, M. B.

2009-04-01

Regional Climate models are more and more needed to provide high resolution regional climate information in climate impact studies. Water availability in a future scenario is the main request of policy makers for adaptation and mitigation purposes. However precipitation changes are unlikely to be as spatially coherent as temperature changes and they are closely related to the regional model itself. In addition model skill varies regionally. An example of several ICTP regional climate model (RegCM3) simulations is reported over China, Korea, Africa, Central and Southern America, Europe and Australia. Over China, Australia, and Korea the regional model improves the simulation compared to the driving GCM when compared with CRU observations. In China, for example, the higher resolution of the regional model inhibits the penetration of the monsoon precipitation front from the southern slope of the Himalaya onto the Tibetan Plateau. In Korea the nested domain simulation (20 km) shows an encouraging performance with regard to capturing extreme precipitation episodes and the finer spatial distribution reflects the detailed geography of the Korean Peninsula. Over South America, RegCM captures the annual cycle of precipitation over Northeast Brazil and the South American Monsoon region, although the monsoon onset occurs too early in the model. Precipitation over the Amazon is not well captured, with too little precipitation associated with weak easterlies and reduced moisture transport into the interior of the continent. RegCM simulates the annual cycle of precipitation over Central America and the Caribbean fairly well; in particular, the complex spatial distribution of the Mid-Summer Drought, a decrease in precipitation that occurs during the middle of the rainy season in July and August, is better captured by RegCM than by the GCM. In addition, RegCM simulates the strength and position of the Caribbean low level jet, a mesoscale feature related to precipitation anomalies in the region. Over Africa our analysis shows that RegCM3 is able to reproduce fairly well the spatial variability of seasonal mean temperature, precipitation and the associated low-level circulation. However, monsoon flow is over predicted while African Easterly Jet (AEJ) core underestimated and shifted a bit northward. Finally, over Europe the regional model shows a cold bias for most part of the year and a wet bias in winter and spring. Rain frequency is too high especially over the mountainous regions. The spatial patter of the precipitation extreme is well represented in the model although a slight overestimation of the 95, 98 99 percentile is evident.

Relationships of Upper Tropospheric Water Vapor, Clouds and SST: MLS Observations, ECMWF Analyses and GCM Simulations

NASA Technical Reports Server (NTRS)

Su, Hui; Waliser, Duane E.; Jiang, Jonathan H.; Li, Jui-lin; Read, William G.; Waters, Joe W.; Tompkins, Adrian M.

2006-01-01

The relationships of upper tropospheric water vapor (UTWV), cloud ice and sea surface temperature (SST) are examined in the annual cycles of ECMWF analyses and simulations from 15 atmosphere-ocean coupled models which were contributed to the IPCC AR4. The results are compared with the observed relationships based on UTWV and cloud ice measurements from MLS on Aura. It is shown that the ECMWF analyses produce positive correlations between UTWV, cloud ice and SST, similar to the MLS data. The rate of the increase of cloud ice and UTWV with SST is about 30% larger than that for MLS. For the IPCC simulations, the relationships between UTWV, cloud ice and SST are qualitatively captured. However, the magnitudes of the simulated cloud ice show a considerable disagreement between models, by nearly a factor of 10. The amplitudes of the approximate linear relations between UTWV, cloud ice and SST vary by a factor up to 4.

Development and Validation of Water Vapor Tracers as Diagnostics for the Atmospheric Hydrologic Cycle

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Understanding of the local and remote sources of water vapor can be a valuable diagnostic in understanding the regional atmospheric hydrologic cycle. In the present study, we have implemented passive tracers as prognostic variables to follow water vapor evaporated in predetermined regions until the water tracer precipitates. The formulation of the sources and sinks of tracer water is generally proportional to the prognostic water vapor variable. Because all water has been accounted for in tracers, the water vapor variable provides the validation of the tracer water and the formulation of the sources and sinks. The tracers have been implemented in a GEOS General Circulation Model (GCM) simulation consisting of several summer periods to determine the source regions of precipitation for the United States and India. The recycling of water and interannual variability of the sources of water will be examined. Potential uses in GCM sensitivity studies, predictability studies and data assimilation will be discussed.

Seasonal Predictions with the GEOS GCM

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Chang, Yehui; Suarez, Max

1999-01-01

A number of ensembles of seasonal forecasts have recently been completed as part of NASA's Seasonal to Interannual Prediction Project (NSIPP). The focus is on the extratropical response of the atmosphere to observed Surface Sea Temperature (SST) anomalies during boreal winter. The prediction experiments consist of nine forecasts starting from slightly different initial conditions for each year of the 15 year period 1981-95, employing version 2 of the Goddard Earth Observing System (GEOS) atmospheric Global Circulation Models (GCM). The initial conditions are obtained from the NASA GEOS-1 reanalysis data. Comparisons with a companion set of six long-term simulations with observed SST (starting in 1978, so they have no memory of the initial conditions for the periods of interest) are used to assess the relative contributions of the initial conditions and SST anomalies to forecast skill ranging from daily to seasonal time scales. The ensembles are used to isolate the signal, and to assess the nature of the inherent variability (noise) of the forecasts.

The GEOS Chemistry Climate Model: Implications of Climate Feedbacks on Ozone Depletion and Recovery

NASA Technical Reports Server (NTRS)

Stolarski, Richard S.; Pawson, Steven; Douglass, Anne R.; Newman, Paul A.; Kawa, S. Randy; Nielsen, J. Eric; Rodriquez, Jose; Strahan, Susan; Oman, Luke; Waugh, Darryn

2008-01-01

The Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) has been developed by combining the atmospheric chemistry and transport modules developed over the years at Goddard and the GEOS general circulation model, also developed at Goddard. The first version of the model was used in the CCMVal intercomparison exercises that contributed to the 2006 WMO/UNEP Ozone Assessment. The second version incorporates the updated version of the GCM (GEOS 5) and will be used for the next round of CCMVal evaluations and the 2010 Ozone Assessment. The third version, now under development, incorporates the combined stratosphere and troposphere chemistry package developed under the Global Modeling Initiative (GMI). We will show comparison to past observations that indicate that we represent the ozone trends over the past 30 years. We will also show the basic temperature, composition, and dynamical structure of the simulations. We will further show projections into the future. We will show results from an ensemble of transient and time-slice simulations, including simulations with fixed 1960 chlorine, simulations with a best guess scenario (Al), and simulations with extremely high chlorine loadings. We will discuss planned extensions of the model to include emission-based boundary conditions for both anthropogenic and biogenic compounds.

GCM studies on Jovian polar dynamics

NASA Astrophysics Data System (ADS)

Tabataba-Vakili, F.; Orton, G.; Li, C.; Young, R. M.; Read, P. L.; Ingersoll, A. P.

2017-12-01

The Juno spacecraft has produced unparalleled measurements of the polar regions of Jupiter. Observations from JunoCAM and JIRAM (Jupiter Infrared Auroral Mapper) have revealed a structure of cyclonic vortices near the poles. We report simulations of the observed polar dynamics using a hierarchy of models from shallow-water to general circulation models with increasing detail. An initialized, unforced shallow-water model of the polar region results in merging cyclones, producing a Saturn-like polar vortex. Further investigations with more detailed models aim to recreate the observed polar structures on Jupiter and investigate the difference between vortical structures on Saturn and Jupiter. Identifying this difference may shed light on the formation and maintenance mechanisms of the observed vortices.

Evidence of nonlinear interaction between quasi 2 day wave and quasi-stationary wave

NASA Astrophysics Data System (ADS)

Gu, Sheng-Yang; Liu, Han-Li; Li, Tao; Dou, Xiankang; Wu, Qian; Russell, James M.

2015-02-01

The nonlinear interaction between the westward quasi 2 day wave (QTDW) with zonal wave number s = 3 (W3) and stationary planetary wave with s = 1 (SPW1) is first investigated using both Thermosphere, Ionosphere, and Mesosphere Electric Dynamics (TIMED) satellite observations and the thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) simulations. A QTDW with westward s = 2 (W2) is identified in the mesosphere and lower thermosphere (MLT) region in TIMED/Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature and TIMED/TIMED Doppler Imager (TIDI) wind observations during 2011/2012 austral summer period, which coincides with a strong SPW1 episode at high latitude of the northern winter hemisphere. The temperature perturbation of W2 QTDW reaches a maximum amplitude of ~8 K at ~30°S and ~88 km in the Southern Hemisphere, with a smaller amplitude in the Northern Hemisphere at similar latitude and minimum amplitude at the equator. The maximum meridional wind amplitude of the W2 QTDW is observed to be ~40 m/s at 95 km in the equatorial region. The TIME-GCM is utilized to simulate the nonlinear interactions between W3 QTDW and SPW1 by specifying both W3 QTDW and SPW1 perturbations at the lower model boundary. The model results show a clear W2 QTDW signature in the MLT region, which agrees well with the TIMED/SABER temperature and TIMED/TIDI horizontal wind observations. We conclude that the W2 QTDW during the 2011/2012 austral summer period results from the nonlinear interaction between W3 QTDW and SPW1.

CFD Validation for Hypersonic Flight: Real Gas Flows

DTIC Science & Technology

2006-01-01

Calculations Two research groups contributed results to this test case. The group of Drs. Marco Marini and Salvatore Borelli from the Italian Aerospace...and Borelli ran calculations at four test con- ditions, and we simulated Run 46, which is the high- enthalpy air case. The test section conditions were...N2 at ρ∞ = 3.31 g/cm3, T∞ = 556 K, u∞ = 4450 m/s. Run 46: Air at ρ∞ = 3.28 g/cm3, T∞ = 672 K, u∞ = 4480 m/s. Marini and Borelli used grids of 144× 40

a Coupled GCM Comparison of Marine Isotope Stages 1, 5e, 11c and 31 IN Relation to Lake El'gygytgyn, NE Russia

NASA Astrophysics Data System (ADS)

Coletti, A. J.; DeConto, R.; Melles, M.; Brigham-Grette, J.; Minyuk, P.

2012-12-01

The lack of scientific data concerning interglacials of the Pleistocene in the Arctic has been a major obstacle within the climate community. Study of the interglacials of Marine Isotope Stage(s) (MIS) 1, 5e, 11c and 31 in high latitudes is important to decoding Arctic sensitivity and providing us with a potential analogue for a future Arctic with climate change. Data from a sediment core recovered from Lake El'Gygytgyn in northeastern (NE) Russia gives a continuous, high-resolution record of the Arctic spanning the past 2.8 million years whilst recording these interglacials. The data was used to correlate simulated interglacial Arctic climate with Arctic climate derived from sediment core proxy studies. Here, we use a Global Circulation Model (GCM) with a coupled atmosphere and land-surface scheme complete with an interactive vegetation component to simulate marine isotope stages 1, 5e, 11c and 31 in the Arctic. GCM simulations of MIS 5e and 31 in the Arctic both show a warmer arctic climate that can be explained by high obliquity, high eccentricity, high CO2 (287 ppmv ,325 ppmv , respectively) and precession that aligns perihelion with boreal summer. Consequently, MIS 5e showed the greatest summer warming compared to the other interglacials and pre-industrial control. However, the distinctly higher values of mean temperature of the warmest month (MTWM) and annual precipitation during stage 11c cannot readily be explained by summer orbital forcings and greenhouse gas (GHG) concentrations. Montane forest is seen migrating northward in stages 1, 5e and 31 as the surface insolation increases and sea ice melts, whereas in 11c, the warmest of the interglacials, evergreen forest takes over and migrates pole ward toward the coast. Feedback from low albedo forest biome was studied and conclusions suggest the increase in temperature due to forest cover is insignificant in creating a significantly warm regional climate. The warming associated with a lack of a Greenland Ice Sheet (GIS) in stage 11c and 31 was not enough to warm temperatures to the observed temperatures seen in 11c during proxy analysis of the Lake El'Gygytgyn sediment core. The surprising warmth during MIS 11c might be explained by linkages with Antarctic ice retreat and decreased Antarctic Bottom Water (AABW) formation. The Lake El'Gygytgyn core provides a high-resolution terrestrial record that is unprecedented. The difficulty for the GCM to properly simulate stage 11c sparks questions for the Arctic climate community. Teleconnections such as the formation Antarctic Bottom Water (AABW) and the upwelling of bottom water in the Arctic could play a major role in affecting temperatures on a smaller, regional scale.

Soil Biogeochemistry in the Ent DGVM

NASA Astrophysics Data System (ADS)

Kharecha, P. A.; Kiang, N. Y.; Aleinov, I.; Moorcroft, P.; Koster, R.

2007-12-01

As the global climate continues to warm in the 21st century, it will be vital to assess the degree of carbon cycle feedbacks from the terrestrial biosphere, particularly the soil. Global soil carbon stocks, which amount to approximately double the carbon stored in vegetation, could provide either positive or negative climate feedbacks, depending on a given ecosystem's response to warming. To predict changes in net terrestrial CO2 fluxes and belowground organic carbon storage, we have developed and evaluated a soil biogeochemistry submodel for the Ent dynamic global vegetation model currently being tested within the GISS GCM. It is a modified version of the soil submodel in the CASA biosphere model (Potter et al., Glob. Biogeoch. Cyc. 7, 1993). We have enhanced it to allow for explicit depth structure (2 soil layers, 0-30 cm and 30-100 cm), first-order inter-layer (vertical) soil organic carbon transport, and a variable-Q10 temperature dependence for soil microbial respiration. We have tested the soil model in numerous offline runs. To spin up the simulated carbon pools offline, we conducted multi-century runs using meteorological and ecological data from various FLUXNET field sites that represent 7 of the 8 GISS GCM plant functional types: tundra, grassland, shrubland, savanna, deciduous forest, evergreen needleleaf forest, and tropical rainforest (the eighth, cropland, will be dealt with in a separate study). We then compare the magnitudes of the simulated spun-up soil pools to soil carbon stock data from these field sites as well as the biome-aggregated data from Post et al. (Nature 317, 1985). Net ecosystem CO2 fluxes and soil respiration are also compared to site-specific measurements where available. Preliminary results suggest that simulated fluxes are reasonably close to measured values, but simulated carbon storage tends to be lower than the measurements. In addition to site-specific comparisons, we discuss the broader implications of our results, e.g., the effects of including explicit depth structure and inter-layer soil carbon transport on simulated soil respiration, carbon storage, and estimation of the global carbon budget.

Global Modeling and Data Assimilation. Volume 11; Documentation of the Tangent Linear and Adjoint Models of the Relaxed Arakawa-Schubert Moisture Parameterization of the NASA GEOS-1 GCM; 5.2

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Yang, Wei-Yu; Todling, Ricardo; Navon, I. Michael

1997-01-01

A detailed description of the development of the tangent linear model (TLM) and its adjoint model of the Relaxed Arakawa-Schubert moisture parameterization package used in the NASA GEOS-1 C-Grid GCM (Version 5.2) is presented. The notational conventions used in the TLM and its adjoint codes are described in detail.

Origins of the Thermosphere-Ionosphere Semiannual Oscillation: Reformulating the "Thermospheric Spoon" Mechanism

NASA Astrophysics Data System (ADS)

Jones, M.; Emmert, J. T.; Drob, D. P.; Picone, J. M.; Meier, R. R.

2018-01-01

We demonstrate how Earth's obliquity generates the global thermosphere-ionosphere (T-I) semiannual oscillation (SAO) in mass density and electron density primarily through seasonally varying large-scale advection of neutral thermospheric constituents, sometimes referred to as the "thermospheric spoon" mechanism (TSM). The National Center for Atmospheric Research thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM) is used to isolate the TSM forcing of this prominent intraannual variation (IAV) and to elucidate the contributions of other processes to the T-I SAO. An ˜30% SAO in globally averaged mass density (relative to its global annual average) at 400 km is reproduced in the TIME-GCM in the absence of seasonally varying eddy diffusion, tropospheric tidal forcing, and gravity wave breaking. Artificially, decreasing the tilt of Earth's rotation axis with respect to the ecliptic plane to 11.75° reduces seasonal variations in insolation and weakens interhemispheric pressure differences at the solstices, thereby damping the global-scale, interhemispheric transport of atomic oxygen (O) and molecular nitrogen in the thermosphere and reducing the simulated global mass density SAO amplitude to ˜10%. Simulated T-I IAVs in mass density and electron density have equinoctial maxima at all latitudes near the F2 region peak; this phasing and its latitude dependence agree well with empirically inferred climatologies. When tropospheric tides and gravity waves are included, simulated IAV amplitudes and their latitudinal dependence also agree well with empirically inferred climatologies. Simulated meridional and vertical transport of O due to the TSM couples to the upper mesospheric circulation, which also contributes to the T-I SAO through O chemistry.

The Co-benefits of Domestic and Foreign GHG Mitigation on US Air Quality

NASA Astrophysics Data System (ADS)

Zhang, Y.; Bowden, J.; Adelman, Z.; Naik, V.; Horowitz, L. W.; West, J. J.

2013-12-01

Authors: Yuqiang Zhang1, Jared Bowden2 , Zachariah Adelman1,2, Vaishali Naik3, Larry W. Horowitz4 , J. Jason West1 1 University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 2 Institute for the Environment, Chapel Hill, NC 27599 3 UCAR/NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540 4 NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540 Abstract: Actions to mitigate greenhouse gas (GHG) emissions will reduce co-emitted air pollutants, which can immediately affect air quality; slowing climate change through GHG mitigation also influences air quality in the long term. We previously used a global model (MOZART-4) to show that global GHG mitigation will have significant co-benefits for air quality and human health. In doing so, we contrasted the Representative Concentration Pathway Scenario 4.5 (RCP4.5), treated as a GHG mitigation scenario, with its associated reference case scenario (REF). Using these same scenarios, we investigate here the air quality co-benefits due to domestic GHGs mitigation in the US alone at fine resolution, and compare these co-benefits with those resulting from foreign GHG mitigation. This work focuses on downscaling the meteorology and air pollutant chemistry to the US scale. We use the latest Weather Research and Forecasting (WRF) model as a Regional Climate Model (RCM) to dynamically downscale the GFDL AM3 Global Climate Model (GCM) over the US at 36 km resolution, in 2000 and 2050. The 2000 simulation will be compared with the multi-year surface observation data, satellite data, and all simulations with the GCM simulation. These simulations will be used as inputs for the newest Community Multiscale Air Quality (CMAQ) modeling system. Initial conditions (IC) and dynamic boundary conditions (BC) for CMAQ will be derived from the global MOZART-4 simulations. Anthropogenic emissions for the REF and RCP4.5 scenarios will be processed through SMOKE to prepare temporally- and spatially-resolved emission files. We will evaluate the co-benefits of GHG mitigation by changing the meteorological and air pollutant emissions inputs for RCP4.5 and REF, as well as the fixed methane level, and will separate the co-benefits of domestic vs. foreign GHG mitigation by using RCP4.5 emissions in the US only, but REF boundary conditions and REF emissions elsewhere.

Modeling The Hydrology And Water Allocation Under Climate Change In Rural River Basins: A Case Study From Nam Ngum River Basin, Laos

NASA Astrophysics Data System (ADS)

Jayasekera, D. L.; Kaluarachchi, J.; Kim, U.

2011-12-01

Rural river basins with sufficient water availability to maintain economic livelihoods can be affected with seasonal fluctuations of precipitation and sometimes by droughts. In addition, climate change impacts can also alter future water availability. General Circulation Models (GCMs) provide credible quantitative estimates of future climate conditions but such estimates are often characterized by bias and coarse scale resolution making it necessary to downscale the outputs for use in regional hydrologic models. This study develops a methodology to downscale and project future monthly precipitation in moderate scale basins where data are limited. A stochastic framework for single-site and multi-site generation of weekly rainfall is developed while preserving the historical temporal and spatial correlation structures. The spatial correlations in the simulated occurrences and the amounts are induced using spatially correlated yet serially independent random numbers. This method is applied to generate weekly precipitation data for a 100-year period in the Nam Ngum River Basin (NNRB) that has a land area of 16,780 km2 located in Lao P.D.R. This method is developed and applied using precipitation data from 1961 to 2000 for 10 selected weather stations that represents the basin rainfall characteristics. Bias-correction method, based on fitted theoretical probability distribution transformations, is applied to improve monthly mean frequency, intensity and the amount of raw GCM precipitation predicted at a given weather station using CGCM3.1 and ECHAM5 for SRES A2 emission scenario. Bias-correction procedure adjusts GCM precipitation to approximate the long-term frequency and the intensity distribution observed at a given weather station. Index of agreement and mean absolute error are determined to assess the overall ability and performance of the bias correction method. The generated precipitation series aggregated at monthly time step was perturbed by the change factors estimated using the corrected GCM and baseline scenarios for future time periods of 2011-2050 and 2051-2090. A network based hydrologic and water resources model, WEAP, was used to simulate the current water allocation and management practices to identify the impacts of climate change in the 20th century. The results of this work are used to identify the multiple challenges faced by stakeholders and planners in water allocation for competing demands in the presence of climate change impacts.

Association of MTHFR C667T polymorphism with bone mineral density and fracture risk: an updated meta-analysis.

PubMed

Wang, H; Liu, C

2012-11-01

This meta-analysis investigated the association of C677T polymorphism in MTHFR gene with bone mineral density (BMD) and fracture risk. The results suggested that C677T polymorphism was marginally associated with fracture risk. In addition, this polymorphism was modestly associated with BMD of lumbar spine, femoral neck, total hip, and total body, respectively. The methylenetetrahydrofolate reductase (MTHFR) gene has been implicated in the regulation of BMD and, thus, may serve as a potential risk factor for the development of fracture. However, results have been inconsistent. In this study, a meta-analysis was performed to clarify the association of C677T polymorphism in MTHFR gene with BMD and fracture risk. Published literature from PubMed and EMBASE were searched for eligible publications. Pooled odds ratio (OR) or weighted mean difference (WMD) and 95% confidence interval (CI) were calculated using a fixed- or random-effects model. Twenty studies (3,525 cases and 17,909 controls) were included in this meta-analysis. The TT genotype of C677T polymorphism was marginally associated with an increased risk of fracture under recessive model (TT vs. TC + CC: OR = 1.23, 95% CI 1.04-1.47). Using this model, similar results were found among East Asians (OR = 1.40, 95% CI 1.07-1.83), female subpopulation (1.27, 95% CI 1.04-1.55), cohort studies (OR = 1.24, 95% CI 1.08-1.44), and subjects younger than aged 60 years (OR = 1.51, 95% CI 1.10-2.07). In addition, under homogeneous co-dominant model, there was a modest association of C677T polymorphism with BMD of lumbar spine (WMD = -0.017 g/cm(2); 95%CI, -0.030-(-0.005) g/cm(2)), femoral neck (WMD = -0.010 g/cm(2); 95% CI -0.017-(-0.003) g/cm(2)), total hip (WMD = -0.013 g/cm(2), 95% CI -0.022-(-0.004) g/cm(2)), and total body (WMD = -0.020 g/cm(2); 95% CI -0.027-(-0.013) g/cm(2)), respectively. This meta-analysis suggested that C677T polymorphism was marginally associated with fracture risk. In addition, this polymorphism was modestly associated with BMD of lumbar spine, femoral neck, total hip, and total body, respectively.

The Role of Air-sea Coupling in the Response of Climate Extremes to Aerosols

NASA Astrophysics Data System (ADS)

Mahajan, S.

2017-12-01

Air-sea interactions dominate the climate of surrounding regions and thus also modulate the climate response to local and remote aerosol forcings. To clearly isolate the role of air-sea coupling in the climate response to aerosols, we conduct experiments with a full complexity atmosphere model that is coupled to a series of ocean models progressively increasing in complexity. The ocean models range from a data ocean model with prescribed SSTs, to a slab ocean model that only allows thermodynamic interactions, to a full dynamic ocean model. In a preliminary study, we have conducted single forcing experiments with black carbon aerosols in an atmosphere GCM coupled to a data ocean model and a slab ocean model. We find that while black carbon aerosols can intensify mean and extreme summer monsoonal precipitation over the Indian sub-continent, air-sea coupling can dramatically modulate this response. Black carbon aerosols in the vicinity of the Arabian Sea result in an increase of sea surface temperatures there in the slab ocean model, which intensify the low-level Somali Jet. The associated increase in moisture transport into Western India enhances the mean as well as extreme precipitation. In prescribed SST experiments, where SSTs are not allowed to respond BC aerosols, the response is muted. We will present results from a hierarchy of GCM simulations that investigate the role of air-sea coupling in the climate response to aerosols in more detail.

Impact of the ongoing Amazonian deforestation on local precipitation: A GCM simulation study

NASA Technical Reports Server (NTRS)

Walker, G. K.; Sud, Y. C.; Atlas, R.

1995-01-01

Numerical simulation experiments were conducted to delineate the influence of in situ deforestation data on episodic rainfall by comparing two ensembles of five 5-day integrations performed with a recent version of the Goddard Laboratory for Atmospheres General Circulation Model (GCM) that has a simple biosphere model (SiB). The first set, called control cases, used the standard SiB vegetation cover (comprising 12 biomes) and assumed a fully forested Amazonia, while the second set, called deforestation cases, distinguished the partially deforested regions of Amazonia as savanna. Except for this difference, all other initial and prescribed boundary conditions were kept identical in both sets of integrations. The differential analyses of these five cases show the following local effects of deforestation. (1) A discernible decrease in evapotranspiration of about 0.80 mm/d (roughly 18%) that is quite robust in the averages for 1-, 2-, and 5-day forecasts. (2) A decrease in precipitation of about 1.18 mm/d (roughly 8%) that begins to emerge even in 1-2 day averages and exhibits complex evolution that extends downstream with the winds. (3) A significant decrease in the surface drag force (as a consequence of reduced surface roughness of deforested regions) that, in turn, affects the dynamical structure of moisture convergence and circulation. The surface winds increase significantly during the first day, and thereafter the increase is well maintained even in the 2- and 5-day averages.

The Effect of Orbital Configuration on the Possible Climates and Habitability of Kepler-62f.

PubMed

Shields, Aomawa L; Barnes, Rory; Agol, Eric; Charnay, Benjamin; Bitz, Cecilia; Meadows, Victoria S

2016-06-01

As lower-mass stars often host multiple rocky planets, gravitational interactions among planets can have significant effects on climate and habitability over long timescales. Here we explore a specific case, Kepler-62f (Borucki et al., 2013 ), a potentially habitable planet in a five-planet system with a K2V host star. N-body integrations reveal the stable range of initial eccentricities for Kepler-62f is 0.00 ≤ e ≤ 0.32, absent the effect of additional, undetected planets. We simulate the tidal evolution of Kepler-62f in this range and find that, for certain assumptions, the planet can be locked in a synchronous rotation state. Simulations using the 3-D Laboratoire de Météorologie Dynamique (LMD) Generic global climate model (GCM) indicate that the surface habitability of this planet is sensitive to orbital configuration. With 3 bar of CO2 in its atmosphere, we find that Kepler-62f would only be warm enough for surface liquid water at the upper limit of this eccentricity range, providing it has a high planetary obliquity (between 60° and 90°). A climate similar to that of modern-day Earth is possible for the entire range of stable eccentricities if atmospheric CO2 is increased to 5 bar levels. In a low-CO2 case (Earth-like levels), simulations with version 4 of the Community Climate System Model (CCSM4) GCM and LMD Generic GCM indicate that increases in planetary obliquity and orbital eccentricity coupled with an orbital configuration that places the summer solstice at or near pericenter permit regions of the planet with above-freezing surface temperatures. This may melt ice sheets formed during colder seasons. If Kepler-62f is synchronously rotating and has an ocean, CO2 levels above 3 bar would be required to distribute enough heat to the nightside of the planet to avoid atmospheric freeze-out and permit a large enough region of open water at the planet's substellar point to remain stable. Overall, we find multiple plausible combinations of orbital and atmospheric properties that permit surface liquid water on Kepler-62f. Extrasolar planets-Habitability-Planetary environments. Astrobiology 16, 443-464.

The Effect of Orbital Configuration on the Possible Climates and Habitability of Kepler-62f

PubMed Central

Barnes, Rory; Agol, Eric; Charnay, Benjamin; Bitz, Cecilia; Meadows, Victoria S.

2016-01-01

Abstract As lower-mass stars often host multiple rocky planets, gravitational interactions among planets can have significant effects on climate and habitability over long timescales. Here we explore a specific case, Kepler-62f (Borucki et al., 2013), a potentially habitable planet in a five-planet system with a K2V host star. N-body integrations reveal the stable range of initial eccentricities for Kepler-62f is 0.00 ≤ e ≤ 0.32, absent the effect of additional, undetected planets. We simulate the tidal evolution of Kepler-62f in this range and find that, for certain assumptions, the planet can be locked in a synchronous rotation state. Simulations using the 3-D Laboratoire de Météorologie Dynamique (LMD) Generic global climate model (GCM) indicate that the surface habitability of this planet is sensitive to orbital configuration. With 3 bar of CO2 in its atmosphere, we find that Kepler-62f would only be warm enough for surface liquid water at the upper limit of this eccentricity range, providing it has a high planetary obliquity (between 60° and 90°). A climate similar to that of modern-day Earth is possible for the entire range of stable eccentricities if atmospheric CO2 is increased to 5 bar levels. In a low-CO2 case (Earth-like levels), simulations with version 4 of the Community Climate System Model (CCSM4) GCM and LMD Generic GCM indicate that increases in planetary obliquity and orbital eccentricity coupled with an orbital configuration that places the summer solstice at or near pericenter permit regions of the planet with above-freezing surface temperatures. This may melt ice sheets formed during colder seasons. If Kepler-62f is synchronously rotating and has an ocean, CO2 levels above 3 bar would be required to distribute enough heat to the nightside of the planet to avoid atmospheric freeze-out and permit a large enough region of open water at the planet's substellar point to remain stable. Overall, we find multiple plausible combinations of orbital and atmospheric properties that permit surface liquid water on Kepler-62f. Key Words: Extrasolar planets—Habitability—Planetary environments. Astrobiology 16, 443–464. PMID:27176715

Ranking GCM Estimates of Twentieth Century Precipitation Seasonality in the Western U.S. and its Influence on Floristic Provinces.

NASA Astrophysics Data System (ADS)

Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Ironside, K.; Cobb, N. S.

2008-12-01

Floristic provinces of the western United States (west of 100W) can be segregated into three regions defined by significant seasonal precipitation during the months of: 1) November-March (Mediterranean); 2) July- September (Monsoonal); or, 3) May-June (Rocky Mountain). This third region is best defined by the absence of the late spring-early summer drought that affects regions 1 and 2. Each of these precipitation regimes is characterized by distinct vegetation types and fire seasonality adapted to that particular cycle of seasonal moisture availability and deficit. Further, areas where these regions blend from one to another can support even more complex seasonal patterns and resulting distinctive vegetation types. As a result, modeling the effects of climates on these ecosystems requires confidence that GCMs can at least approximate these sub- continental seasonal precipitation patterns. We evaluated the late Twentieth Century (1950-1999 AD) estimates of annual precipitation seasonality produced by 22 GCMs contained within the IPCC Fourth Assessment (AR4). These modeled estimates were compared to values from the PRISM dataset, extrapolated from station data, over the same historical period for the 3 seasonal periods defined above. The correlations between GCM estimates and PRISM values were ranked using 4 measures: 1) A map pattern relationship based on the correlation coefficient, 2) A map pattern relationship based on the congruence coefficient, 3) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation amounts, and, 4) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation percentages of the annual total. For each of the four metrics, the rank order of models was very similar. The ranked order of the performance of the different models quantified aspects of the model performance visible in the mapped results. While some models represented the seasonal patterns very well, others showed little correspondence with the regional patterns, especially for the summer monsoon period. These sub-continental patterns were especially well simulated over this period by the UKMO-HadGEM1, ECHAM5/MPI-OM, and the MRI-CGCM2 model runs.

The Importance of Topography in Modeling the Climates of Potentially Habitable Worlds

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Way, M.; Jonas, J.

2017-12-01

The surface features of distant potentially habitable worlds are unknown and likely to remain so for the foreseeable future. As a result, 3-D general circulation model (GCM) simulations of the climates of these worlds commonly utilize an aquaplanet configuration (no emergent land). We highlight here the differences in simulated climates that are produced when using realistic, reconstructed, or idealized continental distributions. Paleo-Earth scenarios as analogues of habitable exoplanets with emergent land exist back to 2 Gyr. There is high confidence in continental reconstructions back to 300 Myr, with moderate confidence reconstructions dating to at least 1 Gyr. A range of habitable states exists throughout the last two billion years of Earth history, including periods that are representative of both inner and outer edge environments, i.e., Snowball Earth and the Cretaceous Greenhouse. Using reconstructed land/ocean distributions with the GCM permits us to test hypotheses based on conceptual models (does a supercontinent at tropical latitudes encourage global cooling via albedo feedbacks?) as well as explore far-field climate teleconnections that may explain enhanced habitability (does the closing of an equatorial seaway drive increased heating in polar regions?). Paleo-Venus simulations, using current topography and a slow rotation rate, have shown that large land fraction in the tropics combined with modest amounts of water actually limits the amount of planetary warming to habitable levels, moreso than aquaplanets, given the equivalent solar flux - thus showing the inner edge of the HZ to be more transitional than previously described. For distant exoplanets or paleo-Earth prior to 2 Gyr, idealized continents or modern Earth topography help illustrate the range of possible habitable states for a given case. With idealized continents, varying the land fraction and location produces as much as a 20˚C difference in global MAT for otherwise identical simulations (same solar/GHG forcings). Synchronously rotating exoplanets modeled with modern Earth topography show how land barriers to zonal water/heat transports result in a global MAT considerably colder than the equivalent aquaplanet scenario, and ice and snow cover can increase by roughly a factor of two when land is beneath the substellar point.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

A Method of Relating General Circulation Model Simulated Climate to the Observed Local Climate. Part I: Seasonal Statistics.

NASA Astrophysics Data System (ADS)

Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David

1990-10-01

Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.

Sensitivity of the Antarctic surface mass balance to oceanic perturbations

NASA Astrophysics Data System (ADS)

Kittel, C.; Amory, C.; Agosta, C.; Fettweis, X.

2017-12-01

Regional climate models (RCMs) are suitable numerical tools to study the surface mass balance (SMB) of the wide polar ice sheets due to their high spatial resolution and polar-adapted physics. Nonetheless, RCMs are driven at their boundaries and over the ocean by reanalysis or global climate model (GCM) products and are thus influenced by potential biases in these large-scale fields. These biases can be significant for both the atmosphere and the sea surface conditions (i.e. sea ice concentration and sea surface temperature). With the RCM MAR, a set of sensitivity experiments has been realized to assess the direct response of the SMB of the Antarctic ice sheet to oceanic perturbations. MAR is forced by ERA-Interim and anomalies based on mean GCM biases are introduced in sea surface conditions. Results show significant increases (decreases) of liquid and solid precipitation due to biases related to warm (cold) oceans. As precipitation is mainly caused by low-pressure systems that intrude into the continent and do not penetrate far inland, coastal areas are more sensitive than inland regions. Furthermore, warm ocean representative biases lead to anomalies as large as anomalies simulated by other RCMs or GCMs for the end of the 21st century.

Evaluating the Appropriateness of Downscaled Climate Information for Projecting Risks of Salmonella.

PubMed

Guentchev, Galina S; Rood, Richard B; Ammann, Caspar M; Barsugli, Joseph J; Ebi, Kristie; Berrocal, Veronica; O'Neill, Marie S; Gronlund, Carina J; Vigh, Jonathan L; Koziol, Ben; Cinquini, Luca

2016-02-29

Foodborne diseases have large economic and societal impacts worldwide. To evaluate how the risks of foodborne diseases might change in response to climate change, credible and usable climate information tailored to the specific application question is needed. Global Climate Model (GCM) data generally need to, both, be downscaled to the scales of the application to be usable, and represent, well, the key characteristics that inflict health impacts. This study presents an evaluation of temperature-based heat indices for the Washington D.C. area derived from statistically downscaled GCM simulations for 1971-2000--a necessary step in establishing the credibility of these data. The indices approximate high weekly mean temperatures linked previously to occurrences of Salmonella infections. Due to bias-correction, included in the Asynchronous Regional Regression Model (ARRM) and the Bias Correction Constructed Analogs (BCCA) downscaling methods, the observed 30-year means of the heat indices were reproduced reasonably well. In April and May, however, some of the statistically downscaled data misrepresent the increase in the number of hot days towards the summer months. This study demonstrates the dependence of the outcomes to the selection of downscaled climate data and the potential for misinterpretation of future estimates of Salmonella infections.

Effects of Variable Eccentricity on the Climate of an Earth-like World

NASA Astrophysics Data System (ADS)

Way, M. J.; Georgakarakos, Nikolaos

2017-01-01

The Kepler era of exoplanetary discovery has presented the astronomical community with a cornucopia of planetary systems that are very different from the one that we inhabit. It has long been known that Jupiter plays a major role in the orbital parameters of Mars and its climate, but there is also a long-standing belief that Jupiter would play a similar role for Earth if not for the Moon. Using a three-dimensional general circulation model (3D GCM) with a fully coupled ocean, we simulate what would happen to the climate of an Earth-like world if Mars did not exist, but a Jupiter-like planet was much closer to Earth’s orbit. We investigate two scenarios that involve the evolution of the Earth-like planet’s orbital eccentricity from 0 to 0.283 over 6500 years, and from 0 to 0.066 on a timescale of 4500 years. In both cases we discover that they would maintain relatively temperate climates over the timescales simulated. More Earth-like planets in multi-planet systems will be discovered as we continue to survey the skies and the results herein show that the proximity of large gas giant planets may play an important role in the habitability of these worlds. These are the first such 3D GCM simulations using a fully coupled ocean with a planetary orbit that evolves over time due to the presence of a giant planet.

The Origin of Antarctic Precipitation: A Modeling Approach

NASA Technical Reports Server (NTRS)

Delaygue, Gilles; Masson, Valerie; Jouzel, Jean; Koster, Randal D.; Healy, Richard J.

1998-01-01

Isotope concentrations in polar ice cores have long been used to estimate paleotemperatures. Underlying the use of this "isotope paleothermometer" is the assumption that the relationship between surface temperature and isotope concentration over time at a single geographical point is the same as that observed over space during the present-day climate. The validity of this assumption may in fact be compromised by several factors related to climate change. The specific factor studied in this paper involves the evaporative sources for polar precipitation. Climatic changes in the relative strengths of these sources would imply a need for a recalibration of the paleothermometer. To quantify such changes, we performed two GCM simulations, one of present-day climate and the other of the climate during the Last Glacial Maximum (LGM), roughly 18000 years ago. Evaporative sources of Antarctic precipitation were established using special tracer diagnostics. Results suggest that polar precipitation during the LGM does indeed consist of (relatively) more water from tropical oceans, a direct reflection of the LGM's increased equator-to-pole temperature gradient and its increased sea ice extent, which reduces high latitude evaporation. This result implies that an uncalibrated ice core paleothermometer would produce LGM temperatures that are biased slightly low. Because LGM boundary conditions are still under debate, we performed a third GCM simulation using a modified set of LGM boundary conditions. Using this simulation gives some qualitatively similar results, though the tropical contribution is not quite as high. Uncertainties in the LGM boundary conditions does hamper success in calibrating the paleothermometer.

Evolution of the Antarctic polar vortex in spring: Response of a GCM to a prescribed Antarctic ozone hole

NASA Technical Reports Server (NTRS)

Boville, B. A.; Kiehl, J. T.; Briegleb, B. P.

1988-01-01

The possible effect of the Antartic ozone hole on the evolution of the polar vortex during late winter and spring using a general circulation model (GCM) is examined. The GCM is a version of the NCAR Community Climate Model whose domain extends from the surface to the mesosphere and is similar to that described on Boville and Randel (1986). Ozone is not a predicted variable in the model. A zonally averaged ozone distribution is specified as a function of latitude, pressure and month for the radiation parameterization. Rather that explicitly address reasons for the formation of the ozone hole, researchers postulate its existence and ask what effect it has on the subsequent evolution of the vortex. The evolution of the model when an ozone hole is imposed is then discussed.

Examining the Stationarity Assumption for Statistically Downscaled Climate Projections of Precipitation

NASA Astrophysics Data System (ADS)

Wootten, A.; Dixon, K. W.; Lanzante, J. R.; Mcpherson, R. A.

2017-12-01

Empirical statistical downscaling (ESD) approaches attempt to refine global climate model (GCM) information via statistical relationships between observations and GCM simulations. The aim of such downscaling efforts is to create added-value climate projections by adding finer spatial detail and reducing biases. The results of statistical downscaling exercises are often used in impact assessments under the assumption that past performance provides an indicator of future results. Given prior research describing the danger of this assumption with regards to temperature, this study expands the perfect model experimental design from previous case studies to test the stationarity assumption with respect to precipitation. Assuming stationarity implies the performance of ESD methods are similar between the future projections and historical training. Case study results from four quantile-mapping based ESD methods demonstrate violations of the stationarity assumption for both central tendency and extremes of precipitation. These violations vary geographically and seasonally. For the four ESD methods tested the greatest challenges for downscaling of daily total precipitation projections occur in regions with limited precipitation and for extremes of precipitation along Southeast coastal regions. We conclude with a discussion of future expansion of the perfect model experimental design and the implications for improving ESD methods and providing guidance on the use of ESD techniques for impact assessments and decision-support.

Changes in yields and their variability at different levels of global warming

NASA Astrophysics Data System (ADS)

Childers, Katelin

2015-04-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the political discussion about mitigation targets as well as for the inclusion of climate change impacts in Integrated Assessment Models (IAMs) that generally only provide global mean temperature change as an indicator of climate change. While there is a well-established framework for the scalability of regional temperature and precipitation changes with global mean temperature change we provide an assessment of the extent to which impacts such as crop yield changes can also be described in terms of global mean temperature changes without accounting for the specific underlying emissions scenario. Based on multi-crop-model simulations of the four major cereal crops (maize, rice, soy, and wheat) on a 0.5 x 0.5 degree global grid generated within ISI-MIP, we show the average spatial patterns of projected crop yield changes at one half degree warming steps. We find that emissions scenario dependence is a minor component of the overall variance of projected yield changes at different levels of global warming. Furthermore, scenario dependence can be reduced by accounting for the direct effects of CO2 fertilization in each global climate model (GCM)/impact model combination through an inclusion of the global atmospheric CO2 concentration as a second predictor. The choice of GCM output used to force the crop model simulations accounts for a slightly larger portion of the total yield variance, but the greatest contributor to variance in both global and regional crop yields and at all levels of warming, is the inter-crop-model spread. The unique multi impact model ensemble available with ISI-MIP data also indicates that the overall variability of crop yields is projected to increase in conjunction with increasing global mean temperature. This result is consistent throughout the ensemble of impact models and across many world regions. Such a hike in yield volatility could have significant policy implications by affecting food prices and supplies.

Experiments on tropical stratospheric mean-wind variations in a spectral general circulation model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, K.; Yuan, L.

1992-12-15

A 30-level version of the rhomboidal-15 GFDL spectral climate model was constructed with roughly 2-km vertical resolution. This model fails to produce a realistic quasi-biennial oscillation (QBO) in the tropical stratosphere. Several simulations were conducted in which the zonal-mean winds and temperatures in the equatorial lower and middle stratosphere were instantaneously perturbed and the model was integrated while the mean state relaxed toward its equilibrium. The time scale for the mean wind relaxation varied from over one month at 40 km to a few months in the lower stratosphere. The wind relaxations in the model also displayed the downward phasemore » propagation characteristic of QBO wind reversals, and mean wind anomalies of opposite sign to the imposed perturbation appear at higher levels. In the GCM the downward propagation is clear only above about 20 mb. Detailed investigations were made of the zonal-mean zonal momentum budget in the equatorial stratosphere. The mean flow relaxations above 20 mb were mostly driven by the vertical Eliassen-Palm flux convergence. The anomalies in the horizontal Eliassen-Palm fluxes from extratropical planetary waves were found to be the dominant effect forcing the mean flow to its equilibrium at altitudes below 20 mb. The vertical eddy momentum fluxes near the equator in the model were decomposed using space-time Fourier analysis. While total fluxes associated with easterly and westerly waves are comparable to those used in simple mechanistic models of the QBO, the GCM has its flux spread over a broad range of wavenumbers and phase speeds. The effects of vertical resolution were studied by repeating part of the control integration with a 69-level version of the model with greatly enhance vertical resolution in the lower and middle stratosphere. The results showed that there is almost no sensitivity of the simulation in the tropical stratosphere to the increased vertical resolution. 34 refs., 16 figs., 3 tabs.« less

Hydrological climate change projections for Central America

NASA Astrophysics Data System (ADS)

Hidalgo, Hugo G.; Amador, Jorge A.; Alfaro, Eric J.; Quesada, Beatriz

2013-07-01

Runoff climate change projections for the 21st century were calculated from a suite of 30 General Circulation Model (GCM) simulations for the A1B emission scenario in a 0.5° × 0.5° grid over Central America. The GCM data were downscaled using a version of the Bias Correction and Spatial Downscaling (BCSD) method and then used in the Variable Infiltration Capacity (VIC) macroscale hydrological model. The VIC model showed calibration skill in Honduras, Nicaragua, Costa Rica and Panama, but the results for some of the northern countries (Guatemala, El Salvador and Belize) and for the Caribbean coast of Central America was not satisfactory. Bias correction showed to remove effectively the biases in the GCMs. Results of the projected climate in the 2050-2099 period showed median significant reductions in precipitation (as much as 5-10%) and runoff (as much as 10-30%) in northern Central America. Therefore in this sub-region the prevalence of severe drought may increase significantly in the future under this emissions scenario. Northern Central America could warm as much as 3 °C during 2050-2099 and southern Central America could reach increases as much as 4 °C during the same period. The projected dry pattern over Central America is consistent with a southward displacement of the Intertropical Convergence Zone (ITCZ). In addition, downscaling of the NCEP/NCAR Reanalysis data from 1948 to 2012 and posterior run in VIC, for two locations in the northern and southern sub-regions of Central America, suggested that the annual runoff has been decreasing since ca. 1980, which is consistent with the sign of the runoff changes of the GCM projections. However, the Reanalysis 1980-2012 drying trends are generally much stronger than the corresponding GCM trends. Among the possible reasons for that discrepancy are model deficiencies, amplification of the trends due to constructive interference with natural modes of variability in the Reanalysis data, errors in the Reanalysis (modeled) precipitation data, and that the drying signal is more pronounced than predicted by the emissions scenario used. A few studies show that extrapolations of future climate from paleoclimatic indicators project a wetter climate in northern Central America, which is inconsistent with the modeling results presented here. However, these types of extrapolations should be done with caution, as the future climate responds to an extra forcing mechanism (anthropogenic) that was not present prehistorically and therefore the response could also be different than in the past.

Multimodel comparison of the ionosphere variability during the 2009 sudden stratosphere warming

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Fang, T.-W.; Jin, H.; Sassi, F.; Schmidt, H.; Chau, J. L.; Siddiqui, T. A.; Goncharenko, L.

2016-07-01

A comparison of different model simulations of the ionosphere variability during the 2009 sudden stratosphere warming (SSW) is presented. The focus is on the equatorial and low-latitude ionosphere simulated by the Ground-to-topside model of the Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Model plus Global Ionosphere Plasmasphere (WAM+GIP), and Whole Atmosphere Community Climate Model eXtended version plus Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (WACCMX+TIMEGCM). The simulations are compared with observations of the equatorial vertical plasma drift in the American and Indian longitude sectors, zonal mean F region peak density (NmF2) from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites, and ground-based Global Positioning System (GPS) total electron content (TEC) at 75°W. The model simulations all reproduce the observed morning enhancement and afternoon decrease in the vertical plasma drift, as well as the progression of the anomalies toward later local times over the course of several days. However, notable discrepancies among the simulations are seen in terms of the magnitude of the drift perturbations, and rate of the local time shift. Comparison of the electron densities further reveals that although many of the broad features of the ionosphere variability are captured by the simulations, there are significant differences among the different model simulations, as well as between the simulations and observations. Additional simulations are performed where the neutral atmospheres from four different whole atmosphere models (GAIA, HAMMONIA (Hamburg Model of the Neutral and Ionized Atmosphere), WAM, and WACCMX) provide the lower atmospheric forcing in the TIME-GCM. These simulations demonstrate that different neutral atmospheres, in particular, differences in the solar migrating semidiurnal tide, are partly responsible for the differences in the simulated ionosphere variability in GAIA, WAM+GIP, and WACCMX+TIMEGCM.

Usefulness of AIRS-Derived OLR, Temperature, Water Vapor and Cloudiness Anomaly Trends for GCM Validation

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel; Iredell, Lena F.

2010-01-01

Mainly due to their global nature, satellite observations can provide a very useful basis for GCM validations. In particular, satellite sounders such as AIRS provide 3-D spatial information (most useful for GCMs), so the question arises: can we use AIRS datasets for climate variability assessments? We show that the recent (September 2002 February 2010) CERES-observed negative trend in OLR of approx.-0.1 W/sq m/yr averaged over the globe is found in the AIRS OLR data as well. Most importantly, even minute details (down to 1 x 1 degree GCM-scale resolution) of spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS-retrieved surface and atmospheric geophysical parameters over this time period are essentially the same. The correspondence can be seen even in the very large spatial variations of these trends with local values ranging from -2.6 W/sq m/yr to +3.0 W/sq m/yr in the tropics, for example. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate, and indirectly validates the anomalies and trends of other AIRS derived products as well. These products show that global and regional anomalies and trends of OLR, water vapor and cloud cover over the last 7+ years are strongly influenced by EI-Nino-La Nina cycles . We have created climate parameter anomaly datasets using AIRS retrievals which can be compared directly with coupled GCM climate variability assessments. Moreover, interrelationships of these anomalies and trends should also be similar between the observed and GCM-generated datasets, and, in cases of discrepancies, GCM parameterizations could be improved based on the relationships observed in the data. First, we assess spatial "trends" of variability of climatic parameter anomalies [since anomalies relative to the seasonal cycle are good proxies of climate variability] at the common 1x1 degree GCM grid-scale by creating spatial anomaly "trends" based on the first 7+ years of AIRS Version 5 Leve13 data. We suggest that modelers should compare these with their (coupled) GCM's performance covering the same period. We evaluate temporal variability and interrelations of climatic anomalies on global to regional e.g., deep Tropical Hovmoller diagrams, El-Nino-related variability scales, and show the effects of El-Nino-La Nina activity on tropical anomalies and trends of water vapor cloud cover and OLR. For GCMs to be trusted highly for long-term climate change predictions, they should be able to reproduce findings similar to these. In summary, the AIRS-based climate variability analyses provide high quality, informative and physically plausible interrelationships among OLR, temperature, humidity and cloud cover both on the spatial and temporal scales. GCM validations can use these results even directly, e. g., by creating 1x1 degree trendmaps for the same period in coupled climate simulations.

Dynamical Downscaling of NASA/GISS ModelE: Continuous, Multi-Year WRF Simulations

NASA Astrophysics Data System (ADS)

Otte, T.; Bowden, J. H.; Nolte, C. G.; Otte, M. J.; Herwehe, J. A.; Faluvegi, G.; Shindell, D. T.

2010-12-01

The WRF Model is being used at the U.S. EPA for dynamical downscaling of the NASA/GISS ModelE fields to assess regional impacts of climate change in the United States. The WRF model has been successfully linked to the ModelE fields in their raw hybrid vertical coordinate, and continuous, multi-year WRF downscaling simulations have been performed. WRF will be used to downscale decadal time slices of ModelE for recent past, current, and future climate as the simulations being conducted for the IPCC Fifth Assessment Report become available. This presentation will focus on the sensitivity to interior nudging within the RCM. The use of interior nudging for downscaled regional climate simulations has been somewhat controversial over the past several years but has been recently attracting attention. Several recent studies that have used reanalysis (i.e., verifiable) fields as a proxy for GCM input have shown that interior nudging can be beneficial toward achieving the desired downscaled fields. In this study, the value of nudging will be shown using fields from ModelE that are downscaled using WRF. Several different methods of nudging are explored, and it will be shown that the method of nudging and the choices made with respect to how nudging is used in WRF are critical to balance the constraint of ModelE against the freedom of WRF to develop its own fields.

Hydroclimatic Change in the Congo River Basin: Past, Present and Future169

NASA Astrophysics Data System (ADS)

Aloysius, N. R.

2016-12-01

Tropical regions provide habitat for the world's most diverse fauna and flora, sequester more atmospheric carbon and provide livelihood for millions of people. The hydrological cycle provides vital linkages for maintaining these ecosystem functions, yet, the understanding of its spatiotemporal variability is limited. Research on the hydrological cycle of the Congo River Basin (CRB), which encompasses the second largest rainforests, has been largely ignored. Global Climate Models (GCM) show limited skills in simulating CRB's climate and their future projections vary widely. Yet, GCMs provide the most plausible scenarios of future climate, based upon which changes in hydrologic fluxes can be predicted with the aid hydrological models. In order to address the gaps in knowledge and to highlight the research needs, we i) developed a spatially explicit hydrological model suitable for describing key hydrological processes, ii) evaluated the performance of GCMs in simulating precipitation and temperature in the region, iii) developed a set of climate change scenarios for the CRB and iv) developed a simplified modeling framework to quantify water management options for rain-fed agriculture with the objective of achieving the triple goals of sustainable development: food security, poverty alleviation and ecosystem conservation. The hydrology model, which was validated with observed stream flows at 50 locations, satisfactorily characterizes spatiotemporal variability of key fluxes. Our evaluation of 25 GCM outputs reveal that many GCMs poorly simulate regional precipitation. We implemented a statistical bias-correction method to develop precipitation and temperature projections for two future greenhouse gas emission scenarios. These climate forcings were, then, used to drive the hydrology model. Our results show that the near-term projections are not affected by emission scenarios. However, towards the mid-21st century, projections are emission scenario dependent. Available freshwater resources are projected to increase in the CRB, except in the semiarid southeast. Our findings have wider implications for climate change assessment and water resource management, because the region, with high population growth and limited capacity to adapt, are primary targets of land and water grabs. 155