Biomass Burning Data and Information

Atmospheric Science Data Center

2015-04-21

Biomass Burning Data and Information This data set represents ... geographical and temporal distribution of total amount of biomass burned. These data may be used in general circulation models (GCMs) and ... models of the atmosphere. Project Title:  Biomass Burning Discipline:  Tropospheric Composition ...

A cyclostrophic transformed Eulerian zonal mean model for the middle atmosphere of slowly rotating planets

NASA Astrophysics Data System (ADS)

Li, K. F.; Yao, K.; Taketa, C.; Zhang, X.; Liang, M. C.; Jiang, X.; Newman, C. E.; Tung, K. K.; Yung, Y. L.

2015-12-01

With the advance of modern computers, studies of planetary atmospheres have heavily relied on general circulation models (GCMs). Because these GCMs are usually very complicated, the simulations are sometimes difficult to understand. Here we develop a semi-analytic zonally averaged, cyclostrophic residual Eulerian model to illustrate how some of the large-scale structures of the middle atmospheric circulation can be explained qualitatively in terms of simple thermal (e.g. solar heating) and mechanical (the Eliassen-Palm flux divergence) forcings. This model is a generalization of that for fast rotating planets such as the Earth, where geostrophy dominates (Andrews and McIntyre 1987). The solution to this semi-analytic model consists of a set of modified Hough functions of the generalized Laplace's tidal equation with the cyclostrohpic terms. As examples, we apply this model to Titan and Venus. We show that the seasonal variations of the temperature and the circulation of these slowly-rotating planets can be well reproduced by adjusting only three parameters in the model: the Brunt-Väisälä bouyancy frequency, the Newtonian radiative cooling rate, and the Rayleigh friction damping rate. We will also discuss the application of this model to study the meridional transport of photochemically produced tracers that can be observed by space instruments.

A cyclostrophic transformed Eulerian zonal mean model for the middle atmosphere of slowly rotating planets

NASA Astrophysics Data System (ADS)

Li, King-Fai; Yao, Kaixuan; Taketa, Cameron; Zhang, Xi; Liang, Mao-Chang; Jiang, Xun; Newman, Claire; Tung, Ka-Kit; Yung, Yuk L.

2016-04-01

With the advance of modern computers, studies of planetary atmospheres have heavily relied on general circulation models (GCMs). Because these GCMs are usually very complicated, the simulations are sometimes difficult to understand. Here we develop a semi-analytic zonally averaged, cyclostrophic residual Eulerian model to illustrate how some of the large-scale structures of the middle atmospheric circulation can be explained qualitatively in terms of simple thermal (e.g. solar heating) and mechanical (the Eliassen-Palm flux divergence) forcings. This model is a generalization of that for fast rotating planets such as the Earth, where geostrophy dominates (Andrews and McIntyre 1987). The solution to this semi-analytic model consists of a set of modified Hough functions of the generalized Laplace's tidal equation with the cyclostrohpic terms. As an example, we apply this model to Titan. We show that the seasonal variations of the temperature and the circulation of these slowly-rotating planets can be well reproduced by adjusting only three parameters in the model: the Brunt-Väisälä bouyancy frequency, the Newtonian radiative cooling rate, and the Rayleigh friction damping rate. We will also discuss an application of this model to study the meridional transport of photochemically produced tracers that can be observed by space instruments.

Estimated migration rates under scenarios of global climate change.

Treesearch

Jay R. Malcolm; Adam Markham; Ronald P. Neilson; Michael Oaraci

2002-01-01

Greefihouse-induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO2 doubled climatic forcing.

A New Look at Stratospheric Sudden Warmings. Part II: Evaluation of Numerical Model Simulations

NASA Technical Reports Server (NTRS)

Charlton, Andrew J.; Polvani, Lorenza M.; Perlwitz, Judith; Sassi, Fabrizio; Manzini, Elisa; Shibata, Kiyotaka; Pawson, Steven; Nielsen, J. Eric; Rind, David

2007-01-01

The simulation of major midwinter stratospheric sudden warmings (SSWs) in six stratosphere-resolving general circulation models (GCMs) is examined. The GCMs are compared to a new climatology of SSWs, based on the dynamical characteristics of the events. First, the number, type, and temporal distribution of SSW events are evaluated. Most of the models show a lower frequency of SSW events than the climatology, which has a mean frequency of 6.0 SSWs per decade. Statistical tests show that three of the six models produce significantly fewer SSWs than the climatology, between 1.0 and 2.6 SSWs per decade. Second, four process-based diagnostics are calculated for all of the SSW events in each model. It is found that SSWs in the GCMs compare favorably with dynamical benchmarks for SSW established in the first part of the study. These results indicate that GCMs are capable of quite accurately simulating the dynamics required to produce SSWs, but with lower frequency than the climatology. Further dynamical diagnostics hint that, in at least one case, this is due to a lack of meridional heat flux in the lower stratosphere. Even though the SSWs simulated by most GCMs are dynamically realistic when compared to the NCEP-NCAR reanalysis, the reasons for the relative paucity of SSWs in GCMs remains an important and open question.

Uncertainties in the projection of species distributions related to general circulation models

PubMed Central

Goberville, Eric; Beaugrand, Grégory; Hautekèete, Nina-Coralie; Piquot, Yves; Luczak, Christophe

2015-01-01

Ecological Niche Models (ENMs) are increasingly used by ecologists to project species potential future distribution. However, the application of such models may be challenging, and some caveats have already been identified. While studies have generally shown that projections may be sensitive to the ENM applied or the emission scenario, to name just a few, the sensitivity of ENM-based scenarios to General Circulation Models (GCMs) has been often underappreciated. Here, using a multi-GCM and multi-emission scenario approach, we evaluated the variability in projected distributions under future climate conditions. We modeled the ecological realized niche (sensu Hutchinson) and predicted the baseline distribution of species with contrasting spatial patterns and representative of two major functional groups of European trees: the dwarf birch and the sweet chestnut. Their future distributions were then projected onto future climatic conditions derived from seven GCMs and four emissions scenarios using the new Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC) AR5 report. Uncertainties arising from GCMs and those resulting from emissions scenarios were quantified and compared. Our study reveals that scenarios of future species distribution exhibit broad differences, depending not only on emissions scenarios but also on GCMs. We found that the between-GCM variability was greater than the between-RCP variability for the next decades and both types of variability reached a similar level at the end of this century. Our result highlights that a combined multi-GCM and multi-RCP approach is needed to better consider potential trajectories and uncertainties in future species distributions. In all cases, between-GCM variability increases with the level of warming, and if nothing is done to alleviate global warming, future species spatial distribution may become more and more difficult to anticipate. When future species spatial distributions are examined, we propose to use a large number of GCMs and RCPs to better anticipate potential trajectories and quantify uncertainties. PMID:25798227

Using Terrestrial GCMs to Understand Climate on Venus, Mars and Titan

NASA Astrophysics Data System (ADS)

Lebonnois, S.; Forget, F.; Hourdin, F.

2008-12-01

For many decades now, General Circulation Models have been developed for the Earth to model our climate. Using these tools, which complexity and efficiency increase with years and computers power, many features of the Earth's circulation may be analyzed and interpreted. But the Earth is a unique case, with rapid rotation rate, with seasons, with water oceans. The Earth GCMs have many parameters finely tuned to reproduce the many observations that are available. How robust are these models under evolving conditions ? To what point may we trust them when exploring Earth's future ? Earth, Venus, Mars and also Titan have dense atmospheres that present many differences, but also similarities. How mechanisms that are at work in the Earth's atmosphere do adapt under these different conditions ? Why are Venus and Titan's atmospheres in super-rotation ? Are the Martian storms produced by processes that also happen on the Earth ? Using the GCMs developed for the Earth for these different atmospheres is very appealing to study these questions. Though the amount of available data is much less for extraterrestrial atmospheres, adapting the terrestrial GCMs to these different environments is worth the effort. Even if the dynamical core may be used almost as it is, adapting the physical parameterizations is not straightforward, but based on the increasing amount of observational data, it may be done with more and more accuracy. These extraterrestrial GCMs may now be used to understand the different features of these climates, but also to compare the different behaviors of these atmospheres under different forcings. It explores the robustness of this kind of tools under widly different conditions, putting strength and confidence in our exploration of Earth's atmosphere future evolution. In this talk, we will present the adaptations that have been necessary to develop GCMs for Mars, Titan and Venus from the LMDZ Earth GCM. These models have then followed their own developments, with many successes in understanding these climates. We will also give exemples of mutual benefits, related to the common base for all these models.

Cloud-radiation interactions and their parameterization in climate models

NASA Technical Reports Server (NTRS)

1994-01-01

This report contains papers from the International Workshop on Cloud-Radiation Interactions and Their Parameterization in Climate Models met on 18-20 October 1993 in Camp Springs, Maryland, USA. It was organized by the Joint Working Group on Clouds and Radiation of the International Association of Meteorology and Atmospheric Sciences. Recommendations were grouped into three broad areas: (1) general circulation models (GCMs), (2) satellite studies, and (3) process studies. Each of the panels developed recommendations on the themes of the workshop. Explicitly or implicitly, each panel independently recommended observations of basic cloud microphysical properties (water content, phase, size) on the scales resolved by GCMs. Such observations are necessary to validate cloud parameterizations in GCMs, to use satellite data to infer radiative forcing in the atmosphere and at the earth's surface, and to refine the process models which are used to develop advanced cloud parameterizations.

Walker circulation in a transient climate

NASA Astrophysics Data System (ADS)

Plesca, Elina; Grützun, Verena; Buehler, Stefan A.

2016-04-01

The tropical overturning circulations modulate the heat exchange across the tropics and between the tropics and the poles. The anthropogenic influence on the climate system will affect these circulations, impacting the dynamics of the Earth system. In this work we focus on the Walker circulation. We investigate its temporal and spatial dynamical changes and their link to other climate features, such as surface and sea-surface temperature patterns, El-Niño Southern Oscillation (ENSO), and ocean heat-uptake, both at global and regional scale. In order to determine the impact of anthropogenic climate change on the tropical circulation, we analyze the outputs of 28 general circulation models (GCMs) from the CMIP5 project. We use the experiment with 1% year-1 increase in CO2 concentration from pre-industrial levels to quadrupling of the concentration. Consistent with previous studies (ex. Ma and Xie 2013), we find that for this experiment most GCMs associate a weakening Walker circulation to a warming transient climate. Due to the role of the Walker Pacific cell in the meridional heat and moisture transport across the tropical Pacific and also the connection to ENSO, we find that a weakened Walker circulation correlates with more extreme El-Niño events, although without a change in their frequency. The spatial analysis of the Pacific Walker cell suggests an eastward displacement of the ascending branch, which is consistent with positive SST anomalies over the tropical Pacific and the link of the Pacific Walker cell to ENSO. Recent studies (ex. England et al. 2014) have linked a strengthened Walker circulation to stronger ocean heat uptake, especially in the western Pacific. The inter-model comparison of the correlation between Walker circulation intensity and ocean heat uptake does not convey a robust response for the investigated experiment. However, there is some evidence that a stronger weakening of the Walker circulation is linked to a higher transient climate response (temperature change by the time of CO2 doubling), which in turn might be related to a decreased ocean heat uptake. This uncertainty across the models we attribute to the multitude of factors controlling ocean and atmosphere heat exchange, both at global and regional scales, as well as to the present capabilities of GCMs in simulating this exchange. References: England, M. H., McGregor, S., Spence, P., Meehl, G. A., Timmermann, A., Cai, W., Gupta, A. S., McPhaden, M. J., Purich, A., and Santoso, A., 2014. Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus. Nature Climate Change 4 (3): 222-227. Ma, J., and Xie, S. P., 2013. Regional Patterns of Sea Surface Temperature Change: A Source of Uncertainty in Future Projections of Precipitation and Atmospheric Circulation*. Journal of Climate, 26 (8): 2482-2501

Impact of the basic state and MJO representation on MJO Pacific teleconnections in GCMs

NASA Astrophysics Data System (ADS)

Henderson, S. A.; Maloney, E. D.; Son, S. W.

2017-12-01

Teleconnection patterns induced by the Madden-Julian Oscillation (MJO) are known to significantly alter extratropical weather and climate patterns. However, accurate MJO representation has been difficult for many General Circulation Models (GCMs). Furthermore, many GCMs contain large basic state biases. These issues present challenges to the simulation of MJO teleconnections and, in turn, their associated extratropical impacts. This study examines the impacts of basic state quality and MJO representation on the quality of MJO teleconnection patterns in GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Results suggest that GCMs assessed to have a good MJO but with large basic state biases have similarly low skill in reproducing MJO teleconnections as GCMs with poor MJO representation. In the good MJO models examined, poor teleconnection quality is associated with large errors in the zonal extent of the Pacific subtropical jet. Whereas the horizontal structure of MJO heating in the Indo-Pacific region is found to have modest impacts on the teleconnection patterns, results suggest that MJO heating east of the dateline can alter the teleconnection pattern characteristics over North America. These findings suggest that in order to accurately simulate the MJO teleconnection patterns and associated extratropical impacts, both the MJO and the basic state must be well represented.

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers.

PubMed

Varela, Sara; Lima-Ribeiro, Matheus S; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12-BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/.

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers

PubMed Central

Varela, Sara; Lima-Ribeiro, Matheus S.; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/. PMID:26068930

Assessment of the scale effect on statistical downscaling quality at a station scale using a weather generator-based model

USDA-ARS?s Scientific Manuscript database

The resolution of General Circulation Models (GCMs) is too coarse to assess the fine scale or site-specific impacts of climate change. Downscaling approaches including dynamical and statistical downscaling have been developed to meet this requirement. As the resolution of climate model increases, it...

Technical report series on global modeling and data assimilation. Volume 5: Documentation of the AIRES/GEOS dynamical core, version 2

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Takacs, Lawrence L.

1995-01-01

A detailed description of the numerical formulation of Version 2 of the ARIES/GEOS 'dynamical core' is presented. This code is a nearly 'plug-compatible' dynamics for use in atmospheric general circulation models (GCMs). It is a finite difference model on a staggered latitude-longitude C-grid. It uses second-order differences for all terms except the advection of vorticity by the rotation part of the flow, which is done at fourth-order accuracy. This dynamical core is currently being used in the climate (ARIES) and data assimilation (GEOS) GCMs at Goddard.

A soil-canopy scheme for use in a numerical model of the atmosphere: 1D stand-alone model

NASA Astrophysics Data System (ADS)

Kowalczyk, E. A.; Garratt, J. R.; Krummel, P. B.

We provide a detailed description of a soil-canopy scheme for use in the CSIRO general circulation models (GCMs) (CSIRO-4 and CSIRO-9), in the form of a one-dimensional stand-alone model. In addition, the paper documents the model's ability to simulate realistic surface fluxes by comparison with mesoscale model simulations (involving more sophisticated soil and boundary-layer treatments) and observations, and the diurnal range in surface quantities, including extreme maximum surface temperatures. The sensitivity of the model to values of the surface resistance is also quantified. The model represents phase 1 of a longer-term plan to improve the atmospheric boundary layer (ABL) and surface schemes in the CSIRO GCMs.

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.

A synopsis of climate change effects on groundwater recharge

NASA Astrophysics Data System (ADS)

Smerdon, Brian D.

2017-12-01

Six review articles published between 2011 and 2016 on groundwater and climate change are briefly summarized. This synopsis focuses on aspects related to predicting changes to groundwater recharge conditions, with several common conclusions between the review articles being noted. The uncertainty of distribution and trend in future precipitation from General Circulation Models (GCMs) results in varying predictions of recharge, so much so that modelling studies are often not able to predict the magnitude and direction (increase or decrease) of future recharge conditions. Evolution of modelling approaches has led to the use of multiple GCMs and hydrologic models to create an envelope of future conditions that reflects the probability distribution. The choice of hydrologic model structure and complexity, and the choice of emissions scenario, has been investigated and somewhat resolved; however, recharge results remain sensitive to downscaling methods. To overcome uncertainty and provide practical use in water management, the research community indicates that modelling at a mesoscale, somewhere between watersheds and continents, is likely ideal. Improvements are also suggested for incorporating groundwater processes within GCMs.

A climate model diagnostic metric for the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Gonzalez, A. O.; Jiang, X.

2016-12-01

Despite its significant impacts on global weather and climate, the Madden-Julian oscillation (MJO) remains a grand challenge for state-of-the-art general circulation models (GCMs). The eastward propagation of the MJO is often poorly simulated in GCMs, represented by a stationary or even westward propagating mode. Recent analyses based on moist static energy processes suggest the horizontal advection of the winter mean moist static energy by the MJO circulation plays a critical role in the observed eastward propagation of the MJO. In this study, we explore relationships between model fidelity in representing the eastward propagation of the MJO and the winter mean lower-tropospheric moisture pattern by analyzing a suite of GCMs from a recent multi-model MJO comparison project. Model capability of reproducing the observed spatial pattern of the 650-900 hPa winter mean specific humidity is a robust indicator of how well they reproduce the MJO's eastward propagation. In particular, model skill in simulating the low-level winter mean specific humidity over the Maritime Continent region (20°S-20°N, 90°-135°E) is highly correlated with model skill of MJO propagation across the 23 GCMs analyzed, with a correlation of about 0.8. Winter mean lower-tropospheric moisture patterns over two other regions, including the western Indian Ocean and an off-equatorial region in the central Indian Ocean, also exhibit high correlations with MJO propagation skill in the model simulations. This study supports recent studies in highlighting the importance of the mean low-level moisture for MJO propagation and it points out a direction for model improvement of the MJO. Meanwhile, it is also suggested that the winter mean low-level moisture pattern over the Indo-Pacific region, particularly over the Maritime Continent region, can serve as a diagnostic metric for the eastward propagation of the MJO in climate model assessments.

Assessment and simulation of global terrestrial latent heat flux by synthesis of CMIP5 climate models and surface eddy covariance observations

Treesearch

Yunjun Yao; Shunlin Liang; Xianglan Li; Shaomin Liu; Jiquan Chen; Xiaotong Zhang; Kun Jia; Bo Jiang; Xianhong Xie; Simon Munier; Meng Liu; Jian Yu; Anders Lindroth; Andrej Varlagin; Antonio Raschi; Asko Noormets; Casimiro Pio; Georg Wohlfahrt; Ge Sun; Jean-Christophe Domec; Leonardo Montagnani; Magnus Lund; Moors Eddy; Peter D. Blanken; Thomas Grunwald; Sebastian Wolf; Vincenzo Magliulo

2016-01-01

The latent heat flux (LE) between the terrestrial biosphere and atmosphere is a major driver of the globalhydrological cycle. In this study, we evaluated LE simulations by 45 general circulation models (GCMs)in the Coupled Model Intercomparison Project Phase 5 (CMIP5) by a comparison...

Narrowing the surface temperature range in CMIP5 simulations over the Arctic

NASA Astrophysics Data System (ADS)

Hao, Mingju; Huang, Jianbin; Luo, Yong; Chen, Xin; Lin, Yanluan; Zhao, Zongci; Xu, Ying

2018-05-01

Much uncertainty exists in reproducing Arctic temperature using different general circulation models (GCMs). Therefore, evaluating the performance of GCMs in reproducing Arctic temperature is critically important. In our study, 32 GCMs in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) during the period 1900-2005 are used, and several metrics, i.e., bias, correlation coefficient ( R), and root mean square error (RMSE), are applied. The Cowtan data set is adopted as the reference data. The results suggest that the GCMs used can reasonably reproduce the Arctic warming trend during the period 1900-2005, as observed in the observational data, whereas a large variation of inter-model differences exists in modeling the Arctic warming magnitude. With respect to the reference data, most GCMs have large cold biases, whereas others have weak warm biases. Additionally, based on statistical thresholds, the models MIROC-ESM, CSIRO-Mk3-6-0, HadGEM2-AO, and MIROC-ESM-CHEM (bias ≤ ±0.10 °C, R ≥ 0.50, and RMSE ≤ 0.60 °C) are identified as well-performing GCMs. The ensemble of the four best-performing GCMs (ES4), with bias, R, and RMSE values of -0.03 °C, 0.72, and 0.39 °C, respectively, performs better than the ensemble with all 32 members, with bias, R, and RMSE values of -0.04 °C, 0.64, and 0.43 °C, respectively. Finally, ES4 is used to produce projections for the next century under the scenarios of RCP2.6, RCP4.5, and RCP8.0. The uncertainty in the projected temperature is greater in the higher emissions scenarios. Additionally, the projected temperature in the cold half year has larger variations than that in the warm half year.

Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

Treesearch

Ying Ouyang; Prem B. Parajuli; Gary Feng; Theodor D. Leininger; Yongshan Wan; Padmanava Dash

2018-01-01

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and...

Summertime land-sea thermal contrast and atmospheric circulation over East Asia in a warming climate—Part I: Past changes and future projections

NASA Astrophysics Data System (ADS)

Kamae, Youichi; Watanabe, Masahiro; Kimoto, Masahide; Shiogama, Hideo

2014-11-01

Land-sea surface air temperature (SAT) contrast, an index of tropospheric thermodynamic structure and dynamical circulation, has shown a significant increase in recent decades over East Asia during the boreal summer. In Part I of this two-part paper, observational data and the results of transient warming experiments conducted using coupled atmosphere-ocean general circulation models (GCMs) are analyzed to examine changes in land-sea thermal contrast and the associated atmospheric circulation over East Asia from the past to the future. The interannual variability of the land-sea SAT contrast over the Far East for 1950-2012 was found to be tightly coupled with a characteristic tripolar pattern of tropospheric circulation over East Asia, which manifests as anticyclonic anomalies over the Okhotsk Sea and around the Philippines, and a cyclonic anomaly over Japan during a positive phase, and vice versa. In response to CO2 increase, the cold northeasterly winds off the east coast of northern Japan and the East Asian rainband were strengthened with the circulation pattern well projected on the observed interannual variability. These results are commonly found in GCMs regardless of future forcing scenarios, indicating the robustness of the East Asian climate response to global warming. The physical mechanisms responsible for the increase of the land-sea contrast are examined in Part II.

Trends in winter circulation over the British Isles and central Europe in twenty-first century projections by 25 CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Stryhal, Jan; Huth, Radan

2018-03-01

Winter midlatitude atmospheric circulation has been extensively studied for its tight link to surface weather, and automated circulation classifications have often been used to this end. Here, eight such classifications are applied to daily sea level pressure patterns simulated by an ensemble of CMIP5 GCMs twenty-first century projections for the British Isles and central Europe in order to robustly estimate future changes in frequency, persistence, and strength of synoptic-scale circulation there. All methods are able to identify present-day biases of models reported before, such as an overestimated occurrence of zonal flow and underestimation of anticyclonic conditions and easterly advection, although the strength of these biases varies among the methods. In future, models show that the zonal flow will become more frequent while the strength of the mean flow is not projected to change. Over the British Isles, the models that better simulate the latitude of zonal flow over the historical period indicate a slight equatorward shift of westerlies in their projections, while the poleward expansion of circulation—expected in future at global scale—is apparent in those models that have large errors. Over central Europe, some classifications indicate an increase in persistence and especially in frequency of anticyclonic types, which is, however, shown to be rather an artifact of some methods than a real feature. On the other hand, the easterly flow is robustly projected to become markedly weaker in central Europe, which we hypothesize might be an important factor contributing to the projected decrease of cold extremes there.

Climate change impact on streamflow in large-scale river basins: projections and their uncertainties sourced from GCMs and RCP scenarios

NASA Astrophysics Data System (ADS)

Nasonova, Olga N.; Gusev, Yeugeniy M.; Kovalev, Evgeny E.; Ayzel, Georgy V.

2018-06-01

Climate change impact on river runoff was investigated within the framework of the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP2) using a physically-based land surface model Soil Water - Atmosphere - Plants (SWAP) (developed in the Institute of Water Problems of the Russian Academy of Sciences) and meteorological projections (for 2006-2099) simulated by five General Circulation Models (GCMs) (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Eleven large-scale river basins were used in this study. First of all, SWAP was calibrated and validated against monthly values of measured river runoff with making use of forcing data from the WATCH data set and all GCMs' projections were bias-corrected to the WATCH. Then, for each basin, 20 projections of possible changes in river runoff during the 21st century were simulated by SWAP. Analysis of the obtained hydrological projections allowed us to estimate their uncertainties resulted from application of different GCMs and RCP scenarios. On the average, the contribution of different GCMs to the uncertainty of the projected river runoff is nearly twice larger than the contribution of RCP scenarios. At the same time the contribution of GCMs slightly decreases with time.

IMPACTS OF CLIMATE VARIATION AND CHANGE ON MID-ATLANTIC REGION HYDROLOGY

EPA Science Inventory

This study analyzes periodic variations in the climate of the mid-Atlantic Region over the last 100 years and uses general circulation models (GCMs) to project major climate trends for the next hundred years. Historical data include the Palmer Drought Severity Index (PDSI) for th...

Estimation and Correction of bias of long-term simulated climate data from Global Circulation Models (GCMs)

NASA Astrophysics Data System (ADS)

Mehan, S.; Gitau, M. W.

2017-12-01

Global circulation models are often used in simulating long-term climate data for use in hydrologic studies. However, some bias (difference between simulated values and observed data) has been observed especially while simulating precipitation events. The bias is especially evident with respect to simulating dry and wet days. This is because GCMs tend to underestimate large precipitation events with the associated precipitation amounts being distributed to some dry days, thus, leading to a larger number of wet days each with some amount of rainfall. The accuracy of precipitation simulations impacts the accuracy of other simulated components such as flow and water quality. It is, thus, very important to correct the bias associated with precipitation before it is used for any modeling applications. This study aims to correct the bias specifically associated with precipitation events with a focus on the Western Lake Erie Basin (WLEB). Analytical, statistical, and extreme event analyses for three different stations (Adrian, MI; Norwalk, OH; and Fort Wayne, IN) in the WLEB were carried out to quantify the bias. Findings indicated that GCMs overestimated the wet sequences and underestimated dry day probabilities. The number of wet sequences simulated by nine GCMs each from two different open sources were 310-678 (Fort Wayne, IN); 318-600 (Adrian, MI); and 346-638 (Norwalk, OH) compared with 166, 150, and 180, respectively. Predicted conditional probabilities of a dry day followed by wet day (P (D|W)) ranged between 0.16-0.42 (Fort Wayne, IN); 0.29-0.41(Adrian, MI); and 0.13-0.40 (Norwalk, OH) from the different GCMs compared to 0.52 (Fort Wayne, IN and Norwalk, OH); and 0.54 (Adrian, MI) from the observed climate data. There was a difference of 0-8.5% between the distribution of simulated climate values and observed climate data for precipitation and temperature for all three stations (Cohen's d effective size < 0.2). Further work involves the use of Stochastic Weather Generators to correct the conditional probabilities and better capture the dry and wet events for use in the hydrologic and water resources modeling.

Evaluating wind extremes in CMIP5 climate models

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Mishra, Vimal; Ganguly, Auroop R.

2015-07-01

Wind extremes have consequences for renewable energy sectors, critical infrastructures, coastal ecosystems, and insurance industry. Considerable debates remain regarding the impacts of climate change on wind extremes. While climate models have occasionally shown increases in regional wind extremes, a decline in the magnitude of mean and extreme near-surface wind speeds has been recently reported over most regions of the Northern Hemisphere using observed data. Previous studies of wind extremes under climate change have focused on selected regions and employed outputs from the regional climate models (RCMs). However, RCMs ultimately rely on the outputs of global circulation models (GCMs), and the value-addition from the former over the latter has been questioned. Regional model runs rarely employ the full suite of GCM ensembles, and hence may not be able to encapsulate the most likely projections or their variability. Here we evaluate the performance of the latest generation of GCMs, the Coupled Model Intercomparison Project phase 5 (CMIP5), in simulating extreme winds. We find that the multimodel ensemble (MME) mean captures the spatial variability of annual maximum wind speeds over most regions except over the mountainous terrains. However, the historical temporal trends in annual maximum wind speeds for the reanalysis data, ERA-Interim, are not well represented in the GCMs. The historical trends in extreme winds from GCMs are statistically not significant over most regions. The MME model simulates the spatial patterns of extreme winds for 25-100 year return periods. The projected extreme winds from GCMs exhibit statistically less significant trends compared to the historical reference period.

Convection in Extratropical Cyclones: Analysis of GPM, NexRAD, GCMs and Re-Analysis

NASA Astrophysics Data System (ADS)

Jeyaratnam, J.; Booth, J. F.; Naud, C. M.; Luo, J.

2017-12-01

Extratropical Cyclones (ETCs) are the most common cause of extreme precipitation in mid-latitudes and are important in the general atmospheric circulation as they redistribute moisture and heat. Isentropic lifting, upright convection, and slantwise convection are mechanisms of vertical motion within an ETC, which deliver different rain rates and might respond differently to global warming. In this study we compare different metrics for identifying convection within the ETC's and calculate the relative contribution of convection to total ETC precipitation. We determine if convection occurs preferentially in specific regions of the storm and decide how to best utilize GPM retrievals covering other parts of the mid-latitudes. Additionally, mid-latitude cyclones are tracked and composites of these tracked cyclones are compared amongst multiple versions of Global Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) prototype models and re-analysis data; Model Diagnostic Task Force (MDTF) Geophysical Fluid Dynamics Laboratory (GFDL) using a two-plume convection scheme, MDTF GFDL using the Donner convection scheme, Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and European Reanalysis produced by the European Center for Medium-Range Weather Forecasts (ECMWF).

Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

NASA Technical Reports Server (NTRS)

Frei, Allan; Nolin, Anne W.; Serreze, Mark C.; Armstrong, Richard L.; McGinnis, David L.; Robinson, David A.

2004-01-01

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.

Controls on the Climates of Tidally Locked Terrestrial Planets

NASA Astrophysics Data System (ADS)

Yang, J.; Cowan, N. B.; Abbot, D. S.

2013-12-01

Earth-size planets in the habitable zone of M-dwarf stars may be very common. Due to strong tidal forces, these planets in circulate orbits are expected to be tidally locked, with one hemisphere experiencing perpetual day and the other permanent night. Previous studies on the climates of tidally locked planets were primarily based on complex 3D general circulation models (GCMs). The central question to be answered in this work is: what is the minimum necessary physics needed to understand the climates simulated by GCMs? A two-column model, primarily based on the weak temperature gradient (WTG) approximation (Sobel et al. 2001) and the fixed anvil temperature (FAT) hypothesis (Hartmann and Larson 2002) for the tropical climate of Earth, is developed for understanding the climates of tidally locked planets. This highly idealized model well reproduces fundamental features of the climates obtained in complicated GCMs (Yang et al. 2013), including planetary albedo, longwave cloud forcing, outgoing longwave radiation (OLR), and atmospheric energy transport. This suggests that the WTG approximation and the FAT hypothesis may be good approximations for tidally locked habitable planets, which provides strong constraints on the large-scale circulations, diabatic processes, and cloud behaviour on these planets. Both the simple model and the GCMs predict that (i) convection and planetary albedo on the dayside increase as stellar flux is increased; (ii) longwave cloud radiative forcing increases as stellar flux is increased, due to the cloud top temperature remains nearly constant as the climate changes (FAT hypothesis); (iii) for planets at the inner regions of the habitable zone, the dayside--nightside OLR contrast becomes very weak or even reverses, due to the strong longwave absorption by water vapor and clouds on the dayside; (iv) the dayside--to--nightside atmospheric energy transport (AET) increases as stellar flux is increased, and decreases as oceanic energy transport (OET) is included, although the compensation between AET and OET is incomplete. To summarize, we are able to construct a realistic low-order model for the climate of tidally locked terrestrial planets, including the cloud behavior, using only the two constraints. This bodes well for the interpretation of complex GCMs and future observations of such planets using, for example, the James Webb Space Telescope. Cited papers: [1]. Sobel, A. H., J. Nilsson and L. M. Polvani: The weak temperature gradient approximation and balanced tropical moisture waves, J. Atmos. Sci., 58, 3650-65, 2001. [2]. Hartmann, D. L. and K. Larson, An important constraint on tropical cloud-climate feedback, Geophys. Res. Lett., 29, 1951-54, 2002. [3]. Yang, J., N. B. Cowan and D. S. Abbot: Stabilizing cloud feedback dramatically expands the habitable zone of tidally locked planets, ApJ. Lett., 771, L45, 2013.

Comparison of Cirrus Cloud Models: A Project of the GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems

NASA Technical Reports Server (NTRS)

Starr, David O'C.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric

2000-01-01

The GEWEX Cloud System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved cloud parameterizations for application in the large-scale general circulation models (GCMs) used for climate research and for numerical weather prediction. The GCSS strategy is founded upon the use of cloud-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual cloud elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated cloud systems. GCSS also employs single-column versions of the parametric cloud models (SCMs) used in GCMs. GCSS has working groups on boundary-layer clouds, cirrus clouds, extratropical layer cloud systems, precipitating deep convective cloud systems, and polar clouds.

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.

Effects of climate change on forest insect and disease outbreaks

Treesearch

David W. Williams; Robert P. Long; Philip M. Wargo; Andrew M. Liebhold

2000-01-01

General circulation models (GCMs) predict dramatic future changes in climate for the northeastern and north central United States under doubled carbon dioxide (CO2) levels (Hansen et al., 1984; Manabe and Wetherald, 1987; Wilson and Mitchell, 1987; Cubasch and Cess, 1990; Mitchell et al., 1990). January temperatures are projected to rise as much...

Projected climate change for the coastal plain region of Georgia, USA

USDA-ARS?s Scientific Manuscript database

Climatic patterns for the Coastal Plain region of Georgia, USA, centered on Tifton, Georgia (31 28 30N, 83 31 54W) were examined for long term patterns in precipitation and air temperature. Climate projections based upon output from seven Global Circulation Models (GCMs) and three future Green Hous...

Probabilistic regional climate projection in Japan using a regression model with CMIP5 multi-model ensemble experiments

NASA Astrophysics Data System (ADS)

Ishizaki, N. N.; Dairaku, K.; Ueno, G.

2016-12-01

We have developed a statistical downscaling method for estimating probabilistic climate projection using CMIP5 multi general circulation models (GCMs). A regression model was established so that the combination of weights of GCMs reflects the characteristics of the variation of observations at each grid point. Cross validations were conducted to select GCMs and to evaluate the regression model to avoid multicollinearity. By using spatially high resolution observation system, we conducted statistically downscaled probabilistic climate projections with 20-km horizontal grid spacing. Root mean squared errors for monthly mean air surface temperature and precipitation estimated by the regression method were the smallest compared with the results derived from a simple ensemble mean of GCMs and a cumulative distribution function based bias correction method. Projected changes in the mean temperature and precipitation were basically similar to those of the simple ensemble mean of GCMs. Mean precipitation was generally projected to increase associated with increased temperature and consequent increased moisture content in the air. Weakening of the winter monsoon may affect precipitation decrease in some areas. Temperature increase in excess of 4 K was expected in most areas of Japan in the end of 21st century under RCP8.5 scenario. The estimated probability of monthly precipitation exceeding 300 mm would increase around the Pacific side during the summer and the Japan Sea side during the winter season. This probabilistic climate projection based on the statistical method can be expected to bring useful information to the impact studies and risk assessments.

Palaeoclimatic insights into future climate challenges.

PubMed

Alley, Richard B

2003-09-15

Palaeoclimatic data document a sensitive climate system subject to large and perhaps difficult-to-predict abrupt changes. These data suggest that neither the sensitivity nor the variability of the climate are fully captured in some climate-change projections, such as the Intergovernmental Panel on Climate Change (IPCC) Summary for Policymakers. Because larger, faster and less-expected climate changes can cause more problems for economies and ecosystems, the palaeoclimatic data suggest the hypothesis that the future may be more challenging than anticipated in ongoing policy making. Large changes have occurred repeatedly with little net forcing. Increasing carbon dioxide concentration appears to have globalized deglacial warming, with climate sensitivity near the upper end of values from general circulation models (GCMs) used to project human-enhanced greenhouse warming; data from the warm Cretaceous period suggest a similarly high climate sensitivity to CO(2). Abrupt climate changes of the most recent glacial-interglacial cycle occurred during warm as well as cold times, linked especially to changing North Atlantic freshwater fluxes. GCMs typically project greenhouse-gas-induced North Atlantic freshening and circulation changes with notable but not extreme consequences; however, such models often underestimate the magnitude, speed or extent of past changes. Targeted research to assess model uncertainties would help to test these hypotheses.

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.

Improving Representation of Tropical Cloud Overlap in GCMs Based on Cloud-Resolving Model Data

NASA Astrophysics Data System (ADS)

Jing, Xianwen; Zhang, Hua; Satoh, Masaki; Zhao, Shuyun

2018-04-01

The decorrelation length ( L cf) has been widely used to describe the behavior of vertical overlap of clouds in general circulation models (GCMs); however, it has been a challenge to associate L cf with the large-scale meteorological conditions during cloud evolution. This study explored the relationship between L cf and the strength of atmospheric convection in the tropics based on output from a global cloud-resolving model. L cf tends to increase with vertical velocity in the mid-troposphere ( w 500) at locations of ascent, but shows little or no dependency on w 500 at locations of descent. A representation of L cf as a function of vertical velocity is obtained, with a linear regression in ascending regions and a constant value in descending regions. This simple and dynamic-related representation of L cf leads to a significant improvement in simulation of both cloud cover and radiation fields compared with traditional overlap treatments. This work presents a physically justifiable approach to depicting cloud overlap in the tropics in GCMs.

Comparison of Cirrus Cloud Models: A Project of the GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems

NASA Technical Reports Server (NTRS)

Starr, David OC.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric; Khvorostyanov, Vitaly;

AMOC decadal variability in Earth system models: Mechanisms and climate impacts

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

Fedorov, Alexey

This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability andmore » predictability, directly relevant to the questions of climate predictability, were at the center of the research work.« less

Simulated response of conterminous United States ecosystems to climate change at different levels of fire suppression, CO2 emission rate, and growth response to CO2

Treesearch

James M. Lenihan; Dominique Bachelet; Ronald P. Neilson; Raymond Drapek

2008-01-01

A modeling experiment was designed to investigate the impact of fire management, CO2 emission rate, and the growth response to CO2 on the response of ecosystems in the conterminous United States to climate scenarios produced by three different general circulation models (GCMs) as simulated by the MCl Dynamic General...

General-circulation-model simulations of future snowpack in the western United States

USGS Publications Warehouse

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

1999-01-01

April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western US. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.

Explicit Global Simulation of Gravity Waves up to the Lower Thermosphere

NASA Astrophysics Data System (ADS)

Becker, E.

2016-12-01

At least for short-term simulations, middle atmosphere general circulation models (GCMs) can be run with sufficiently high resolution in order to describe a good part of the gravity wave spectrum explicitly. Nevertheless, the parameterization of unresolved dynamical scales remains an issue, especially when the scales of parameterized gravity waves (GWs) and resolved GWs become comparable. In addition, turbulent diffusion must always be parameterized along with other subgrid-scale dynamics. A practical solution to the combined closure problem for GWs and turbulent diffusion is to dispense with a parameterization of GWs, apply a high spatial resolution, and to represent the unresolved scales by a macro-turbulent diffusion scheme that gives rise to wave damping in a self-consistent fashion. This is the approach of a few GCMs that extend from the surface to the lower thermosphere and simulate a realistic GW drag and summer-to-winter-pole residual circulation in the upper mesosphere. In this study we describe a new version of the Kuehlungsborn Mechanistic general Circulation Model (KMCM), which includes explicit (though idealized) computations of radiative transfer and the tropospheric moisture cycle. Particular emphasis is spent on 1) the turbulent diffusion scheme, 2) the attenuation of resolved GWs at critical levels, 3) the generation of GWs in the middle atmosphere from body forces, and 4) GW-tidal interactions (including the energy deposition of GWs and tides).

A climatology of gravity wave parameters based on satellite limb soundings

NASA Astrophysics Data System (ADS)

Ern, Manfred; Trinh, Quang Thai; Preusse, Peter; Riese, Martin

2017-04-01

Gravity waves are one of the main drivers of atmospheric dynamics. The resolution of most global circulation models (GCMs) and chemistry climate models (CCMs), however, is too coarse to properly resolve the small scales of gravity waves. Horizontal scales of gravity waves are in the range of tens to a few thousand kilometers. Gravity wave source processes involve even smaller scales. Therefore GCMs/CCMs usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified, and comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. In our study, we present a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). We provide various gravity wave parameters (for example, gravity variances, potential energies and absolute momentum fluxes). This comprehensive climatological data set can serve for comparison with other instruments (ground based, airborne, or other satellite instruments), as well as for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The purpose of providing various different parameters is to make our data set useful for a large number of potential users and to overcome limitations of other observation techniques, or of models, that may be able to provide only one of those parameters. We present a climatology of typical average global distributions and of zonal averages, as well as their natural range of variations. In addition, we discuss seasonal variations of the global distribution of gravity waves, as well as limitations of our method of deriving gravity wave parameters from satellite data.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer

2018-02-01

Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.

On the Predictability of Northeast Monsoon Rainfall over South Peninsular India in General Circulation Models

NASA Astrophysics Data System (ADS)

Nair, Archana; Acharya, Nachiketa; Singh, Ankita; Mohanty, U. C.; Panda, T. C.

2013-11-01

In this study the predictability of northeast monsoon (Oct-Nov-Dec) rainfall over peninsular India by eight general circulation model (GCM) outputs was analyzed. These GCM outputs (forecasts for the whole season issued in September) were compared with high-resolution observed gridded rainfall data obtained from the India Meteorological Department for the period 1982-2010. Rainfall, interannual variability (IAV), correlation coefficients, and index of agreement were examined for the outputs of eight GCMs and compared with observation. It was found that the models are able to reproduce rainfall and IAV to different extents. The predictive power of GCMs was also judged by determining the signal-to-noise ratio and the external error variance; it was noted that the predictive power of the models was usually very low. To examine dominant modes of interannual variability, empirical orthogonal function (EOF) analysis was also conducted. EOF analysis of the models revealed they were capable of representing the observed precipitation variability to some extent. The teleconnection between the sea surface temperature (SST) and northeast monsoon rainfall was also investigated and results suggest that during OND the SST over the equatorial Indian Ocean, the Bay of Bengal, the central Pacific Ocean (over Nino3 region), and the north and south Atlantic Ocean enhances northeast monsoon rainfall. This observed phenomenon is only predicted by the CCM3v6 model.

Variations in Titan's dune orientations as a result of orbital forcing

NASA Astrophysics Data System (ADS)

McDonald, George D.; Hayes, Alexander G.; Ewing, Ryan C.; Lora, Juan M.; Newman, Claire E.; Tokano, Tetsuya; Lucas, Antoine; Soto, Alejandro; Chen, Gang

2016-05-01

Wind-blown dunes are a record of the climatic history in Titan's equatorial region. Through modeling of the climatic conditions associated with Titan's historical orbital configurations (arising from apsidal precessions of Saturn's orbit), we present evidence that the orientations of the dunes are influenced by orbital forcing. Analysis of 3 Titan general circulation models (GCMs) in conjunction with a sediment transport model provides the first direct intercomparison of results from different Titan GCMs. We report variability in the dune orientations predicted for different orbital epochs of up to 70°. Although the response of the GCMs to orbital forcing varies, the orbital influence on the dune orientations is found to be significant across all models. Furthermore, there is near agreement among the two models run with surface topography, with 3 out of the 5 dune fields matching observation for the most recent orbital cycle. Through comparison with observations by Cassini, we find situations in which the observed dune orientations are in best agreement with those modeled for previous orbital configurations or combinations thereof, representing a larger portion of the cycle. We conclude that orbital forcing could be an important factor in governing the present-day dune orientations observed on Titan and should be considered when modeling dune evolution.

Trends in global wildfire potential in a changing climate

Treesearch

Y. Liu; J.A. Stanturf; S.L. Goodrick

2009-01-01

The trend in global wildfire potential under the climate change due to the greenhouse effect is investigated. Fire potential is measured by the Keetch-Byram Drought Index (KBDI), which is calculated using the observed maximum temperature and precipitation and projected changes at the end of this century (2070–2100) by general circulation models (GCMs) for present and...

Model Projections and their Uncertainties of Future Intensity Change of Typhoon Haiyan (2013)

NASA Astrophysics Data System (ADS)

Yoshino, J.; Toyoda, M.; Shinohara, K.; Kobayashi, T.

2017-12-01

The IPCC fifth assessment report indicated that the global mean maximum wind speed and precipitation of tropical cyclone (TC) are likely to increase by the end of 21st century. However, the specific characteristics of future changes are not yet well quantified and there are high uncertainties in region-specific projections. Such uncertainties in future projections may be attributed to the uncertainties of general circulation models (GCMs) and global warming scenarios (GWSs). In order to quantify uncertainties of future changes of TC intensity among 15 GCMs and 9 GWSs, a present climate experiment (PCE), future climate experiments (FCEs) and sensitivity experiments on TC intensity are carried out in this study using a high-resolution typhoon model, coupled with sea spray, dissipative heating, ocean mixed layer parameterizations and automatic-TC tracking moving nests. The initial and boundary conditions for FCEs are produced by the method of pseudo-global warming downscaling technique. Typhoon Haiyan (2013) is selected as the worst case of a TC under the present climate. Using the high-resolution typhoon model with a grid spacing of 3km, PCE reproduces a peak intensity (minimum central pressure) of about 897.1hPa, which is in close agreement with the besttrack data (895hPa). Comparing the results between 9 FCEs driven by 9 GCMs fixed by one of GCMs (HadCM3) and 15 FCEs driven by 15 GWSs fixed by one of GWSs (in the 2090s of SRES A1B), the TC intensities are slightly weakened by +7.9hPa for GCMs and +3.7hPa for GWSs. The standard deviations of future changes of the peak intensity are 9.47hPa for GCMs and 5.89hPa for GWSs. Thus, the uncertainty of future changes of TC intensity among GCMs is approximately two times larger than that among GWSs. Sensitivity experiments, in which each of global warming differences derived from GCMs are separately added to the initial and boundary conditions of PCE, suggest that the future changes of sea surface temperature in GCMs are responsible for intensifying Haiyan by -19.6hPa while the future changes of air temperature in GCMs are accountable for weakening Haiyan by +45.5hPa. Furthermore, the future changes of air temperature and wind speed in GCMs especially reduce the reliabilities of future projections with standard deviations of 7.82hPa and 9.04hPa, respectively.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-05-01

Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Analysis of the variability of the North Atlantic eddy-driven jet stream in CMIP5

NASA Astrophysics Data System (ADS)

Iqbal, Waheed; Leung, Wai-Nang; Hannachi, Abdel

2017-09-01

The North Atlantic eddy-driven jet is a dominant feature of extratropical climate and its variability is associated with the large-scale changes in the surface climate of midlatitudes. Variability of this jet is analysed in a set of General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project phase-5 (CMIP5) over the North Atlantic region. The CMIP5 simulations for the 20th century climate (Historical) are compared with the ERA40 reanalysis data. The jet latitude index, wind speed and jet persistence are analysed in order to evaluate 11 CMIP5 GCMs and to compare them with those from CMIP3 integrations. The phase of mean seasonal cycle of jet latitude and wind speed from historical runs of CMIP5 GCMs are comparable to ERA40. The wind speed mean seasonal cycle by CMIP5 GCMs is overestimated in winter months. A positive (negative) jet latitude anomaly in historical simulations relative to ERA40 is observed in summer (winter). The ensemble mean of jet latitude biases in historical simulations of CMIP3 and CMIP5 with respect to ERA40 are -2.43° and -1.79° respectively. Thus indicating improvements in CMIP5 in comparison to the CMIP3 GCMs. The comparison of historical and future simulations of CMIP5 under RCP4.5 and RCP8.5 for the period 2076-2099, shows positive anomalies in the jet latitude implying a poleward shifted jet. The results from the analysed models offer no specific improvements in simulating the trimodality of the eddy-driven jet.

Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

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

Quaas, Johannes; Ming, Yi; Menon, Surabi

2009-04-10

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found thatmore » the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5+-0.5 Wm-2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcings with estimates of anthropogenic Ta and satellite-retrieved Nd - Ta regression slopes, respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of -0.4+-0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7+-0.5 Wm-2, with a total estimate of -1.2+-0.4 Wm-2.« less

Numerical Hindcast Experiments for Study Tropical Convections and MJO Events during Year of Tropical Convection

NASA Astrophysics Data System (ADS)

Chern, J.; Tao, W.; Shen, B.

2011-12-01

The Madden-Julian oscillation (MJO) is the dominant component of intraseasonal variability in the tropic. It interacts and influences a wide range of weather and climate phenomena across different temporal and spatial scales. Despite the important role the MJO plays in the weather and climate system, past multi-model MJO intercomparison studies have shown that current global general circulation models (GCMs) still have considerable shortcomings in representing and forecasting this phenomenon. To improve representation of MJO and tropical convective cloud systems in global model, an Multiscale Modeling Framework (MMF) in which a cloud-resolving model takes the place of the sing-column cumulus parameterization used in convectional GCMs has been successfully developed at NAAS Goddard (Tao et al. 2009). To evaluate and improve the ability of this modeling system in representation and prediction of the MJO, several numerical hindcast experiments of a few selected MJO events during YOTC have been carried out. The ability of the model to simulate the MJO events is examined using diagnostic and skill metrics developed by the CLIVAR MJO Working Group Project as well as comparisons with a high-resolution global mesoscale model simulations, satellite observations, and analysis dataset. Several key variables associated with the MJO are investigated, including precipitation, outgoing longwave radiation, large-scale circulation, surface latent heat flux, low-level moisture convergence, vertical structure of moisture and hydrometers, and vertical diabatic heating profiles to gain insight of cloud processes associated with the MJO events.

State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

NASA Astrophysics Data System (ADS)

Pfister, Patrik L.; Stocker, Thomas F.

2017-10-01

Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

Multi-criterion model ensemble of CMIP5 surface air temperature over China

NASA Astrophysics Data System (ADS)

Yang, Tiantian; Tao, Yumeng; Li, Jingjing; Zhu, Qian; Su, Lu; He, Xiaojia; Zhang, Xiaoming

2018-05-01

The global circulation models (GCMs) are useful tools for simulating climate change, projecting future temperature changes, and therefore, supporting the preparation of national climate adaptation plans. However, different GCMs are not always in agreement with each other over various regions. The reason is that GCMs' configurations, module characteristics, and dynamic forcings vary from one to another. Model ensemble techniques are extensively used to post-process the outputs from GCMs and improve the variability of model outputs. Root-mean-square error (RMSE), correlation coefficient (CC, or R) and uncertainty are commonly used statistics for evaluating the performances of GCMs. However, the simultaneous achievements of all satisfactory statistics cannot be guaranteed in using many model ensemble techniques. In this paper, we propose a multi-model ensemble framework, using a state-of-art evolutionary multi-objective optimization algorithm (termed MOSPD), to evaluate different characteristics of ensemble candidates and to provide comprehensive trade-off information for different model ensemble solutions. A case study of optimizing the surface air temperature (SAT) ensemble solutions over different geographical regions of China is carried out. The data covers from the period of 1900 to 2100, and the projections of SAT are analyzed with regard to three different statistical indices (i.e., RMSE, CC, and uncertainty). Among the derived ensemble solutions, the trade-off information is further analyzed with a robust Pareto front with respect to different statistics. The comparison results over historical period (1900-2005) show that the optimized solutions are superior over that obtained simple model average, as well as any single GCM output. The improvements of statistics are varying for different climatic regions over China. Future projection (2006-2100) with the proposed ensemble method identifies that the largest (smallest) temperature changes will happen in the South Central China (the Inner Mongolia), the North Eastern China (the South Central China), and the North Western China (the South Central China), under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios, respectively.

Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

NASA Astrophysics Data System (ADS)

Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

2018-02-01

Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

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.

Circulation pattern-based assessment of projected climate change for a catchment in Spain

NASA Astrophysics Data System (ADS)

Gupta, Hoshin V.; Sapriza-Azuri, Gonzalo; Jódar, Jorge; Carrera, Jesús

2018-01-01

We present an approach for evaluating catchment-scale hydro-meteorological impacts of projected climate change based on the atmospheric circulation patterns (ACPs) of a region. Our approach is motivated by the conjecture that GCMs are especially good at simulating the atmospheric circulation patterns that control moisture transport, and which can be expected to change in response to global warming. In support of this, we show (for the late 20th century) that GCMs provide much better simulations of ACPs than those of precipitation amount for the Upper Guadiana Basin in central Spain. For the same period, four of the twenty GCMs participating in the most recent (5th) IPCC Assessment provide quite accurate representations of the spatial patterns of mean sea level pressure, the frequency distribution of ACP type, the 'number of rainy days per month', and the daily 'probability of rain' (they also reproduce the trend of 'wet day amount', though not the actual magnitudes). A consequent analysis of projected trends and changes in hydro-climatic ACPology between the late 20th and 21st Centuries indicates that (1) actual changes appear to be occurring faster than predicted by the models, and (2) for two greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5) the expected decline in precipitation volume is associated mainly with a few specific ACPs (primarily directional flows from the Atlantic Ocean and Cantabric Sea), and with decreasing probability of rain (linked to increasing temperatures) rather than wet day amount. Our approach is a potentially more insightful alternative for catchment-scale climate impacts assessments than the common approach of statistical downscaling and bias correction.

Physiological and genotypic responses of central hardwood species to allelochemicals, other stresses, and their interactions

Treesearch

J. W. Van Sambeek; John E. Preece; Nadia E. Navarrete; George Rink

1996-01-01

In response to increasing carbon dioxide levels, most general circulation models (GCMs) predict increasing temperatures and decreasing precipitation for the central hardwood region of the United States. Plants in this region will need to adapt to these changes as well as to other stress agents if they are to germinate, grow, and reproduce. For the last five years, our...

Importance of Including Topography in Numerical Simulations of Venus' Atmospheric Circulation

NASA Astrophysics Data System (ADS)

Parish, H. F.; Schubert, G.; Lebonnois, S.; Covey, C. C.; Walterscheid, R. L.; Grossman, A.

2012-12-01

Venus' atmosphere is characterized by strong superrotation, in which the wind velocities at cloud heights are around 60 times faster than the surface rotation rate. The reasons for this strong superrotation are still not well understood. Since the surface of the planet is both a source and sink of atmospheric angular momentum it is important to understand and properly account for the interactions at the surface-atmosphere boundary. A key aspect of the surface-atmosphere interaction is the topography. Topography has been introduced into different general circulation models (GCMs) of Venus' atmosphere, producing significant, but widely varying effects on the atmospheric circulation. The reasons for the inconsistencies among model results are not well known, but our studies suggest they might be related to the influences of different dynamical cores. In our recent study, we have analyzed the angular momentum budget for two Venus GCMs, the Venus Community Atmosphere model (Venus CAM) and the Laboratoire de Meteorologie Dynamique (LMD) Venus GCM. Because of Venus' low magnitude surface winds, surface friction alone supplies only a relatively weak angular momentum forcing to the atmosphere. We find that if surface friction is introduced without including surface topography, the angular momentum balance of the atmosphere may be dominated by effects such as numerical diffusion, a sponge layer, or other numerical residuals that are generally included in all GCMs, and can themselves be sources of angular momentum. However, we find the mountain torque associated with realistic Venus surface topography supplies a much larger source of angular momentum than the surface friction, and dominates nonphysical numerical terms. (A similar effect occurs for rapidly rotating planets like Earth, but in this case numerical errors in the angular momentum budget are relatively small even in the absence of mountain torque). Even if surface friction dominates numerical terms in the angular momentum budgets of simulations without realistic topography, it must be remembered that there are no observational constraints on model parameterizations of the real surface friction on Venus. It is essential for a planet such as Venus, for which surface friction alone supplies only weak angular momentum forcing, to include surface topography to generate realistic forcing of angular momentum and avoid the influences of numerical artifacts, which can be significant. Venus' topography, as mapped using measurements from the Magellan mission, shows significant hemispheric asymmetry. In this work we examine the impact of this asymmetry using simulations of Venus' circulation with and without topography, within the latest version of the Venus CAM GCM.

An application of hybrid downscaling model to forecast summer precipitation at stations in China

NASA Astrophysics Data System (ADS)

Liu, Ying; Fan, Ke

2014-06-01

A pattern prediction hybrid downscaling method was applied to predict summer (June-July-August) precipitation at China 160 stations. The predicted precipitation from the downscaling scheme is available one month before. Four predictors were chosen to establish the hybrid downscaling scheme. The 500-hPa geopotential height (GH5) and 850-hPa specific humidity (q85) were from the skillful predicted output of three DEMETER (Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction) general circulation models (GCMs). The 700-hPa geopotential height (GH7) and sea level pressure (SLP) were from reanalysis datasets. The hybrid downscaling scheme (HD-4P) has better prediction skill than a conventional statistical downscaling model (SD-2P) which contains two predictors derived from the output of GCMs, although two downscaling schemes were performed to improve the seasonal prediction of summer rainfall in comparison with the original output of the DEMETER GCMs. In particular, HD-4P downscaling predictions showed lower root mean square errors than those based on the SD-2P model. Furthermore, the HD-4P downscaling model reproduced the China summer precipitation anomaly centers more accurately than the scenario of the SD-2P model in 1998. A hybrid downscaling prediction should be effective to improve the prediction skill of summer rainfall at stations in China.

Saturn Dynamo Model (Invited)

NASA Astrophysics Data System (ADS)

Glatzmaier, G. A.

2010-12-01

There has been considerable interest during the past few years about the banded zonal winds and global magnetic field on Saturn (and Jupiter). Questions regarding the depth to which the intense winds extend below the surface and the role they play in maintaining the dynamo continue to be debated. The types of computer models employed to address these questions fall into two main classes: general circulation models (GCMs) based on hydrostatic shallow-water assumptions from the atmospheric and ocean modeling communities and global non-hydrostatic deep convection models from the geodynamo and solar dynamo communities. The latter class can be further divided into Boussinesq models, which do not account for density stratification, and anelastic models, which do. Recent efforts to convert GCMs to deep circulation anelastic models have succeeded in producing fluid flows similar to those obtained from the original deep convection anelastic models. We describe results from one of the original anelastic convective dynamo simulations and compare them to a recent anelastic dynamo benchmark for giant gas planets. This benchmark is based on a polytropic reference state that spans five density scale heights with a radius and rotation rate similar to those of our solar system gas giants. The resulting magnetic Reynolds number is about 3000. Better spatial resolution will be required to produce more realistic predictions that capture the effects of both the density and electrical conductivity stratifications and include enough of the turbulent kinetic energy spectrum. Important additional physics may also be needed in the models. However, the basic models used in all simulation studies of the global dynamics of giant planets will hopefully first be validated by doing these simpler benchmarks.

Aerosol indirect effects - general circulation model intercomparison and evaluation with satellite data

NASA Astrophysics Data System (ADS)

Quaas, J.; Ming, Y.; Menon, S.; Takemura, T.; Wang, M.; Penner, J. E.; Gettelman, A.; Lohmann, U.; Bellouin, N.; Boucher, O.; Sayer, A. M.; Thomas, G. E.; McComiskey, A.; Feingold, G.; Hoose, C.; Kristjánsson, J. E.; Liu, X.; Balkanski, Y.; Donner, L. J.; Ginoux, P. A.; Stier, P.; Grandey, B.; Feichter, J.; Sednev, I.; Bauer, S. E.; Koch, D.; Grainger, R. G.; Kirkevåg, A.; Iversen, T.; Seland, Ø.; Easter, R.; Ghan, S. J.; Rasch, P. J.; Morrison, H.; Lamarque, J.-F.; Iacono, M. J.; Kinne, S.; Schulz, M.

2009-11-01

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τa) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between τa and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and τa as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld-τa relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between τa and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR-τa relationship show a strong positive correlation between τa and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τa, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5±0.5 Wm-2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic τa and satellite-retrieved Nd-τa regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of -0.4±0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7±0.5 Wm-2, with a total estimate of -1.2±0.4 Wm-2.

Aerosol indirect effects ? general circulation model intercomparison and evaluation with satellite data

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

Quaas, Johannes; Ming, Yi; Menon, Surabi

2010-03-12

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth ({tau}{sub a}) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is foundmore » that the model-simulated influence of aerosols on cloud droplet number concentration (N{sub d}) compares relatively well to the satellite data at least over the ocean. The relationship between {tau}{sub a} and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (f{sub cld}) and {tau}{sub a} as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong f{sub cld} - {tau}{sub a} relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between {tau}{sub a} and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - {tau}{sub a} relationship show a strong positive correlation between {tau}{sub a} and f{sub cld} The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of {tau}{sub a}, and parameterization assumptions such as a lower bound on N{sub d}. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5 {+-} 0.5 Wm{sup -2}. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic {tau}{sub a} and satellite-retrieved Nd - {tau}{sub a} regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of -0.4 {+-} 0.2 Wm{sup -2} and a cloudy-sky (aerosol indirect effect) estimate of -0.7 {+-} 0.5 Wm{sup -2}, with a total estimate of -1.2 {+-} 0.4 Wm{sup -2}.« less

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

NASA Astrophysics Data System (ADS)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

Strengthening of Ocean Heat Uptake Efficiency Associated with the Recent Climate Hiatus

NASA Technical Reports Server (NTRS)

Watanabe, Masahiro; Kamae, Youichi; Yoshimori, Masakazu; Oka, Akira; Sato, Makiko; Ishii, Masayoshi; Mochizuki, Takashi; Kimoto, Masahide

2013-01-01

The rate of increase of global-mean surface air temperature (SAT(sub g)) has apparently slowed during the last decade. We investigated the extent to which state-of-the-art general circulation models (GCMs) can capture this hiatus period by using multimodel ensembles of historical climate simulations. While the SAT(sub g) linear trend for the last decade is not captured by their ensemble means regardless of differences in model generation and external forcing, it is barely represented by an 11-member ensemble of a GCM, suggesting an internal origin of the hiatus associated with active heat uptake by the oceans. Besides, we found opposite changes in ocean heat uptake efficiency (k), weakening in models and strengthening in nature, which explain why the models tend to overestimate the SAT(sub g) trend. The weakening of k commonly found in GCMs seems to be an inevitable response of the climate system to global warming, suggesting the recovery from hiatus in coming decades.

Equilibrium Climate Sensitivity Obtained From Multimillennial Runs of Two GFDL Climate Models

NASA Astrophysics Data System (ADS)

Paynter, D.; Frölicher, T. L.; Horowitz, L. W.; Silvers, L. G.

2018-02-01

Equilibrium climate sensitivity (ECS), defined as the long-term change in global mean surface air temperature in response to doubling atmospheric CO2, is usually computed from short atmospheric simulations over a mixed layer ocean, or inferred using a linear regression over a short-time period of adjustment. We report the actual ECS from multimillenial simulations of two Geophysical Fluid Dynamics Laboratory (GFDL) general circulation models (GCMs), ESM2M, and CM3 of 3.3 K and 4.8 K, respectively. Both values are 1 K higher than estimates for the same models reported in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change obtained by regressing the Earth's energy imbalance against temperature. This underestimate is mainly due to changes in the climate feedback parameter (-α) within the first century after atmospheric CO2 has stabilized. For both GCMs it is possible to estimate ECS with linear regression to within 0.3 K by increasing CO2 at 1% per year to doubling and using years 51-350 after CO2 is constant. We show that changes in -α differ between the two GCMs and are strongly tied to the changes in both vertical velocity at 500 hPa (ω500) and estimated inversion strength that the GCMs experience during the progression toward the equilibrium. This suggests that while cloud physics parametrizations are important for determining the strength of -α, the substantially different atmospheric state resulting from a changed sea surface temperature pattern may be of equal importance.

Intercomparison of general circulation models for hot extrasolar planets

NASA Astrophysics Data System (ADS)

Polichtchouk, I.; Cho, J. Y.-K.; Watkins, C.; Thrastarson, H. Th.; Umurhan, O. M.; de la Torre Juárez, M.

2014-02-01

We compare five general circulation models (GCMs) which have been recently used to study hot extrasolar planet atmospheres (BOB, CAM, IGCM, MITgcm, and PEQMOD), under three test cases useful for assessing model convergence and accuracy. Such a broad, detailed intercomparison has not been performed thus far for extrasolar planets study. The models considered all solve the traditional primitive equations, but employ different numerical algorithms or grids (e.g., pseudospectral and finite volume, with the latter separately in longitude-latitude and ‘cubed-sphere’ grids). The test cases are chosen to cleanly address specific aspects of the behaviors typically reported in hot extrasolar planet simulations: (1) steady-state, (2) nonlinearly evolving baroclinic wave, and (3) response to fast timescale thermal relaxation. When initialized with a steady jet, all models maintain the steadiness, as they should-except MITgcm in cubed-sphere grid. A very good agreement is obtained for a baroclinic wave evolving from an initial instability in pseudospectral models (only). However, exact numerical convergence is still not achieved across the pseudospectral models: amplitudes and phases are observably different. When subject to a typical ‘hot-Jupiter’-like forcing, all five models show quantitatively different behavior-although qualitatively similar, time-variable, quadrupole-dominated flows are produced. Hence, as have been advocated in several past studies, specific quantitative predictions (such as the location of large vortices and hot regions) by GCMs should be viewed with caution. Overall, in the tests considered here, pseudospectral models in pressure coordinate (PEBOB and PEQMOD) perform the best and MITgcm in cubed-sphere grid performs the worst.

A scheme for parameterizing ice cloud water content in general circulation models

NASA Technical Reports Server (NTRS)

Heymsfield, Andrew J.; Donner, Leo J.

1989-01-01

A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-11-01

Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

How Might Recharge Change Under Projected Climate Change in Western US?

NASA Astrophysics Data System (ADS)

Niraula, R.; Meixner, T.; Rodell, M.; Ajami, H.; Gochis, D. J.; Castro, C. L.

2015-12-01

Although ground water is a major source of water in the western US, little research has been done on the impacts of climate change on western groundwater storage and recharge. Here we assess the impact of projected changes in precipitation and temperature on groundwater recharge across the western US by dividing the domain into five major regions (viz. Northern Rockies and Plains, South, Southwest, Northwest and West). Hydrologic outputs from the Variable Infiltration Capacity (VIC) model based on Bias-Correction and Spatial Disaggregation (BCSD) Coupled Model Inter-comparison Project Phase 5 (CMIP5) climate projections from 11 Global Circulation Models (GCMs) for Representative Concentration pathway 6.0 (RCP 6.0) scenarios were selected for projecting changes in recharge. Projections are made for near future (2020-2050) and far future (2070-2100) relative to the historical period (1970-2000). Averaged over the domain, half of the GCMs caused VIC to increase recharge across the region while the remaining half resulted in decreased recharge for both the near (-10.1% to 5.8%) and far (-9.7% to 17%) future. A majority (9 out of 11 GCMs) of the VIC simulations projected increased recharge in the Northern Rockies and Plains for both the near and far future. A majority of the simulations agreed on reduced recharge in other regions for the near future. For the far future, a majority of the simulations agreed on decreased recharge in the South (9 out of 11 GCMs) and Southwest (7 out of 11 GCMs) regions. The change is projected to be largest for the South region which could see recharged reduced by as much as 50%. Changes in recharge in the Northwest region are predicted to be small (within 10% of historical recharge). Despite the large variability in projected recharge across the GCMs, recharge projections from this study will help water managers with long term water management planning.

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.

Representation of Arctic mixed-phase clouds and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a cloud-resolving study

NASA Astrophysics Data System (ADS)

Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei

2011-01-01

Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, regimes of cloud particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase clouds are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform cloud but the WBF process occurs in about 50% of cloud volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.

Brief communication: Drought likelihood for East Africa

NASA Astrophysics Data System (ADS)

Yang, Hui; Huntingford, Chris

2018-02-01

The East Africa drought in autumn of year 2016 caused malnutrition, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya needed food, water and medical assistance. Many factors influence drought stress and response. However, inevitably the following question is asked: are elevated greenhouse gas concentrations altering extreme rainfall deficit frequency? We investigate this with general circulation models (GCMs). After GCM bias correction to match the climatological mean of the CHIRPS data-based rainfall product, climate models project small decreases in probability of drought with the same (or worse) severity as 2016 ASO (August to October) East African event. This is by the end of the 21st century compared to the probabilities for present day. However, when further adjusting the climatological variability of GCMs to also match CHIRPS data, by additionally bias-correcting for variance, then the probability of drought occurrence will increase slightly over the same period.

Numerical simulation of surface solar radiation over Southern Africa. Part 1: Evaluation of regional and global climate models

NASA Astrophysics Data System (ADS)

Tang, Chao; Morel, Béatrice; Wild, Martin; Pohl, Benjamin; Abiodun, Babatunde; Bessafi, Miloud

2018-02-01

This study evaluates the performance of climate models in reproducing surface solar radiation (SSR) over Southern Africa (SA) by validating five Regional Climate Models (RCM, including CCLM4, HIRHAM5, RACMO22T, RCA4 and REMO2009) that participated in the Coordinated Regional Downscaling Experiment program over Africa (CORDEX-Africa) along with their ten driving General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 over SA. The model simulated SSR was thereby compared to reference data from ground-based measurements, satellite-derived products and reanalyses over the period 1990-2005. Results show that (1) the references obtained from satellite retrievals and reanalyses overall overestimate SSR by up to 10 W/m2 on average when compared to ground-based measurements from the Global Energy Balance Archive, which are located mainly over the eastern part of the southern African continent. (2) Compared to one of the satellite products (Surface Solar Radiation Data Set—Heliosat Edition 2; SARAH-2): GCMs overestimate SSR over SA in terms of their multi-model mean by about 1 W/m2 (compensation of opposite biases over sub-regions) and 7.5 W/m2 in austral summer and winter respectively; RCMs driven by GCMs show in their multimodel mean underestimations of SSR in both seasons with Mean Bias Errors (MBEs) of about - 30 W/m2 in austral summer and about - 14 W/m2 in winter compared to SARAH-2. This multi-model mean low bias is dominated by the simulations of the CCLM4, with negative biases up to - 76 W/m2 in summer and - 32 W/m2 in winter. (3) The discrepancies in the simulated SSR over SA are larger in the RCMs than in the GCMs. (4) In terms of trend during the "brightening" period 1990-2005, both GCMs and RCMs (driven by European Centre for Medium-Range Weather Forecasts Reanalysis ERA-Interim, short as ERAINT and GCMs) simulate an SSR trend of less than 1 W/m2 per decade. However, variations of SSR trend exist among different references data. (5) For individual RCM models, their SSR bias fields seem rather insensitive with respect to the different lateral forcings provided by ERAINT and various GCMs, in line with previous findings over Europe. (6) Biases in SSR are overall qualitatively consistent with those in total cloud cover. The information obtained in present study is of crucial importance for understanding future climate projections of SSR and for relevant impact studies.

Patterns and variability of projected bioclimatic habitat for Pinus albicaulis in the Greater Yellowstone Area.

PubMed

Chang, Tony; Hansen, Andrew J; Piekielek, Nathan

2014-01-01

Projected climate change at a regional level is expected to shift vegetation habitat distributions over the next century. For the sub-alpine species whitebark pine (Pinus albicaulis), warming temperatures may indirectly result in loss of suitable bioclimatic habitat, reducing its distribution within its historic range. This research focuses on understanding the patterns of spatiotemporal variability for future projected P.albicaulis suitable habitat in the Greater Yellowstone Area (GYA) through a bioclimatic envelope approach. Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. P.albicaulis was modeled using a Random Forests algorithm for the 1980-2010 climate period and showed strong presence/absence separations by summer maximum temperatures and springtime snowpack. Patterns of projected habitat change by the end of the century suggested a constant decrease in suitable climate area from the 2010 baseline for both Representative Concentration Pathways (RCPs) 8.5 and 4.5 climate forcing scenarios. Percent suitable climate area estimates ranged from 2-29% and 0.04-10% by 2099 for RCP 8.5 and 4.5 respectively. Habitat projections between GCMs displayed a decrease of variability over the 2010-2099 time period related to consistent warming above the 1910-2010 temperature normal after 2070 for all GCMs. A decreasing pattern of projected P.albicaulis suitable habitat area change was consistent across GCMs, despite strong differences in magnitude. Future ecological research in species distribution modeling should consider a full suite of GCM projections in the analysis to reduce extreme range contractions/expansions predictions. The results suggest that restoration strageties such as planting of seedlings and controlling competing vegetation may be necessary to maintain P.albicaulis in the GYA under the more extreme future climate scenarios.

Patterns and Variability of Projected Bioclimatic Habitat for Pinus albicaulis in the Greater Yellowstone Area

PubMed Central

Chang, Tony; Hansen, Andrew J.; Piekielek, Nathan

2014-01-01

Projected climate change at a regional level is expected to shift vegetation habitat distributions over the next century. For the sub-alpine species whitebark pine (Pinus albicaulis), warming temperatures may indirectly result in loss of suitable bioclimatic habitat, reducing its distribution within its historic range. This research focuses on understanding the patterns of spatiotemporal variability for future projected P.albicaulis suitable habitat in the Greater Yellowstone Area (GYA) through a bioclimatic envelope approach. Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. P.albicaulis was modeled using a Random Forests algorithm for the 1980–2010 climate period and showed strong presence/absence separations by summer maximum temperatures and springtime snowpack. Patterns of projected habitat change by the end of the century suggested a constant decrease in suitable climate area from the 2010 baseline for both Representative Concentration Pathways (RCPs) 8.5 and 4.5 climate forcing scenarios. Percent suitable climate area estimates ranged from 2–29% and 0.04–10% by 2099 for RCP 8.5 and 4.5 respectively. Habitat projections between GCMs displayed a decrease of variability over the 2010–2099 time period related to consistent warming above the 1910–2010 temperature normal after 2070 for all GCMs. A decreasing pattern of projected P.albicaulis suitable habitat area change was consistent across GCMs, despite strong differences in magnitude. Future ecological research in species distribution modeling should consider a full suite of GCM projections in the analysis to reduce extreme range contractions/expansions predictions. The results suggest that restoration strageties such as planting of seedlings and controlling competing vegetation may be necessary to maintain P.albicaulis in the GYA under the more extreme future climate scenarios. PMID:25372719

Time variation of effective climate sensitivity in GCMs

NASA Astrophysics Data System (ADS)

Williams, K. D.; Ingram, W. J.; Gregory, J. M.

2009-04-01

Effective climate sensitivity is often assumed to be constant (if uncertain), but some previous studies of General Circulation Model (GCM) simulations have found it varying as the simulation progresses. This complicates the fitting of simple models to such simulations, as well as having implications for the estimation of climate sensitivity from observations. This study examines the evolution of the feedbacks determining the climate sensitivity in GCMs submitted to the Coupled Model Intercomparison Project. Apparent centennial-timescale variations of effective climate sensitivity during stabilisation to a forcing can be considered an artefact of using conventional forcings which only allow for instantaneous effects and stratospheric adjustment. If the forcing is adjusted for processes occurring on timescales which are short compared to the climate stabilisation timescale then there is little centennial timescale evolution of effective climate sensitivity in any of the GCMs. We suggest that much of the apparent variation in effective climate sensitivity identified in previous studies is actually due to the comparatively fast forcing adjustment. Persistent differences are found in the strength of the feedbacks between the coupled atmosphere - ocean (AO) versions and their atmosphere - mixed-layer ocean (AML) counterparts, (the latter are often assumed to give the equilibrium climate sensitivity of the AOGCM). The AML model can typically only estimate the equilibrium climate sensitivity of the parallel AO version to within about 0.5K. The adjustment to the forcing to account for comparatively fast processes varies in magnitude and sign between GCMs, as well as differing between AO and AML versions of the same model. There is evidence from one AOGCM that the forcing adjustment may take a couple of decades, with implications for observationally based estimates of equilibrium climate sensitivity. We suggest that at least some of the spread in 21st century global temperature predictions between GCMs is due to differing adjustment processes, hence work to understand these differences should be a priority.

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

NASA Astrophysics Data System (ADS)

Kostov, Yavor; Marshall, John; Hausmann, Ute; Armour, Kyle C.; Ferreira, David; Holland, Marika M.

2017-03-01

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern Annular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the response of the Southern Ocean SST (55°S-70°S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step response function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only 3 years after a step increase in the SAM. This intermodel diversity can be related to differences in the models' climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use observational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

PDF added value of a high resolution climate simulation for precipitation

NASA Astrophysics Data System (ADS)

Soares, Pedro M. M.; Cardoso, Rita M.

2015-04-01

General Circulation Models (GCMs) are models suitable to study the global atmospheric system, its evolution and response to changes in external forcing, namely to increasing emissions of CO2. However, the resolution of GCMs, of the order of 1o, is not sufficient to reproduce finer scale features of the atmospheric flow related to complex topography, coastal processes and boundary layer processes, and higher resolution models are needed to describe observed weather and climate. The latter are known as Regional Climate Models (RCMs) and are widely used to downscale GCMs results for many regions of the globe and are able to capture physically consistent regional and local circulations. Most of the RCMs evaluations rely on the comparison of its results with observations, either from weather stations networks or regular gridded datasets, revealing the ability of RCMs to describe local climatic properties, and assuming most of the times its higher performance in comparison with the forcing GCMs. The additional climatic details given by RCMs when compared with the results of the driving models is usually named as added value, and it's evaluation is still scarce and controversial in the literuature. Recently, some studies have proposed different methodologies to different applications and processes to characterize the added value of specific RCMs. A number of examples reveal that some RCMs do add value to GCMs in some properties or regions, and also the opposite, elighnening that RCMs may add value to GCM resuls, but improvements depend basically on the type of application, model setup, atmospheric property and location. The precipitation can be characterized by histograms of daily precipitation, or also known as probability density functions (PDFs). There are different strategies to evaluate the quality of both GCMs and RCMs in describing the precipitation PDFs when compared to observations. Here, we present a new method to measure the PDF added value obtained from dynamical downscaling, based on simple PDF skill scores. The measure can assess the full quality of the PDFs and at the same time integrates a flexible manner to weight differently the PDF tails. In this study we apply the referred method to characaterize the PDF added value of a high resolution simulation with the WRF model. Results from a WRF climate simulation centred at the Iberian Penisnula with two nested grids, a larger one at 27km and a smaller one at 9km. This simulation is forced by ERA-Interim. The observational data used covers from rain gauges precipitation records to observational regular grids of daily precipitation. Two regular gridded precipitation datasets are used. A Portuguese grid precipitation dataset developed at 0.2°× 0.2°, from observed rain gauges daily precipitation. A second one corresponding to the ENSEMBLES observational gridded dataset for Europe, which includes daily precipitation values at 0.25°. The analisys shows an important PDF added value from the higher resolution simulation, regarding the full PDF and the extremes. This method shows higher potential to be applied to other simulation exercises and to evaluate other variables.

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.

The Influence of the Green River Lake System on the Local Climate During the Early Eocene Period

NASA Astrophysics Data System (ADS)

Elguindi, N.; Thrasher, B.; Sloan, L. C.

2006-12-01

Several modeling efforts have attempted to reproduce the climate of the early Eocene North America. However when compared to proxy data, General Circulation Models (GCMs) tend to produce a large-scale cold-bias. Although higher resolution Regional Climate Models (RCMs) that are able to resolve many of the sub-GCM scale forcings improve this cold bias, RCMs are still unable to reproduce the warm climate of the Eocene. From geologic data, we know that the greater Green River and the Uinta basins were intermontane basins with a large lake system during portions of the Eocene. We speculate that the lack of presence of these lakes in previous modeling studies may explain part of the persistent cold-bias of GCMs and RCMs. In this study, we utilize a regional climate model coupled with a 1D-lake model in an attempt to reduce the uncertainties and biases associated with climate simulations over Eocene western North American. Specifically, we include the Green River Lake system in our RCM simulation and compare climates with and without lakes to proxy data.

Robust impact of coupled stratospheric ozone chemistry on the response of the Austral circulation to increased greenhouse gases

NASA Astrophysics Data System (ADS)

Chiodo, G.; Polvani, L. M.

2016-12-01

Due to computational constraints, interactive stratospheric chemistry is commonly neglected in most GCMs participating in inter-comparison projects. The impact of this simplification on the modeled response to external forcings remains largely unexplored. In this work, we examine the impact of the stratospheric chemistry coupling on the SH circulation response to an abrupt quadrupling of CO2. We accomplish this with a version of the Whole Atmosphere Community Climate (WACCM) model, which allows coupling and de-coupling stratospheric chemistry, without altering any other physical parameterization. We find that the chemistry coupling in WACCM significantly reduces (by about 20%) the response of both eddy-driven mid-latitude jet and the Hadley Cell strength, without altering the surface temperature response. This behavior is linked to the representation of stratospheric ozone, and its effects on the meridional temperature gradient at the extratropical tropopause. Our results imply that neglecting stratospheric ozone chemistry results in a potential overestimation of the circulation response to GHGs. Hence, stratospheric ozone chemistry produces a substantial negative feedback on the response of the atmospheric circulation to increased greenhouse gases.

Increasing risk of Amazonian drought due to decreasing aerosol pollution.

PubMed

Cox, Peter M; Harris, Phil P; Huntingford, Chris; Betts, Richard A; Collins, Matthew; Jones, Chris D; Jupp, Tim E; Marengo, José A; Nobre, Carlos A

2008-05-08

The Amazon rainforest plays a crucial role in the climate system, helping to drive atmospheric circulations in the tropics by absorbing energy and recycling about half of the rainfall that falls on it. This region (Amazonia) is also estimated to contain about one-tenth of the total carbon stored in land ecosystems, and to account for one-tenth of global, net primary productivity. The resilience of the forest to the combined pressures of deforestation and global warming is therefore of great concern, especially as some general circulation models (GCMs) predict a severe drying of Amazonia in the twenty-first century. Here we analyse these climate projections with reference to the 2005 drought in western Amazonia, which was associated with unusually warm North Atlantic sea surface temperatures (SSTs). We show that reduction of dry-season (July-October) rainfall in western Amazonia correlates well with an index of the north-south SST gradient across the equatorial Atlantic (the 'Atlantic N-S gradient'). Our climate model is unusual among current GCMs in that it is able to reproduce this relationship and also the observed twentieth-century multidecadal variability in the Atlantic N-S gradient, provided that the effects of aerosols are included in the model. Simulations for the twenty-first century using the same model show a strong tendency for the SST conditions associated with the 2005 drought to become much more common, owing to continuing reductions in reflective aerosol pollution in the Northern Hemisphere.

Dynamical Downscaling of Global Circulation Models With the Weather Research and Forecast Model in the Northern Great Plains

NASA Astrophysics Data System (ADS)

Burtch, D.; Mullendore, G. L.; Kennedy, A. D.; Simms, M.; Kirilenko, A.; Coburn, J.

2015-12-01

Understanding the impacts of global climate change on regional scales is crucial for accurate decision-making by state and local governments. This is especially true in North Dakota, where climate change can have significant consequences on agriculture, its traditionally strongest economic sector. This region of the country shows a high variability in precipitation, especially in the summer months and so the focus of this study is on warm season processes over decadal time scales. The Weather Research and Forecast (WRF) model is used to dynamically downscale two Global Circulation Models (GCMs) from the CMIP5 ensemble in order to determine the microphysical parameterization and nudging techniques (spectral or analysis) best suited for this region. The downscaled domain includes the entirety of North Dakota at a horizontal resolution of 5 km. In addition, smaller domains of 1 km horizontal resolution are centered over regions of focused hydrological importance. The dynamically downscaled simulations are compared with both gridded observational data and statistically downscaled data to evaluate the performance of the simulations. Preliminary results have shown a marked difference between the two downscaled GCMs in terms of temperature and precipitation bias. Choice of microphysical parameterization has not shown to create any significant differences in the temperature fields. However, the precipitation fields do appear to be most affected by the microphysical parameterization, regardless of the choice of GCM. Implications on the unique water resource challenges faced in this region will also be discussed.

Introduction. Pliocene climate, processes and problems

USGS Publications Warehouse

Haywood, A.M.; Dowsett, H.J.; Valdes, P.J.; Lunt, D.J.; Francis, J.E.; Sellwood, B.W.

2009-01-01

Climate predictions produced by numerical climate models, often referred to as general circulation models (GCMs), suggest that by the end of the twenty-first century global mean annual surface air temperatures will increase by 1.1-6.4??C. Trace gas records from ice cores indicate that atmospheric concentrations of CO2 are already higher than at any time during the last 650000 years. In the next 50 years, atmospheric CO2 concentrations are expected to reach a level not encountered since an epoch of time known as the Pliocene. Uniformitarianism is a key principle of geological science, but can the past also be a guide to the future? To what extent does an examination of the Pliocene geological record enable us to successfully understand and interpret this guide? How reliable are the 'retrodictions' of Pliocene climates produced by GCMs and what does this tell us about the accuracy of model predictions for the future? These questions provide the scientific rationale for this Theme Issue. ?? 2008 The Royal Society.

Socioeconomic impacts of climate change on U.S. water supplies

USGS Publications Warehouse

Frederick, K.D.; Schwarz, G.E.

1999-01-01

A greenhouse warming would have major effects on water supplies and demands. A framework for examining the socioeconomic impacts associated with changes in the long-term availability of water is developed and applied to the hydrologic implications of the Canadian and British Hadley2 general circulation models (GCMs) for the 18 water resource regions in the conterminous United States. The climate projections of these two GCMs have very different implications for future water supplies and costs. The Canadian model suggests most of the nation would be much drier in the year 2030. Under the least-cost management scenario the drier climate could add nearly $105 billion to the estimated costs of balancing supplies and demands relative to the costs without climate change. Measures to protect instream flows and irrigation could result in significantly higher costs. In contrast, projections based on the Hadley model suggest water supplies would increase throughout much of the nation, reducing the costs of balancing water supplies with demands relative to the no-climate-change case.

Remote Sensing and halocene Vegetation: History of Global Change

NASA Technical Reports Server (NTRS)

D'Antoni, Hector L.; Schaebitz, Frank

1995-01-01

Predictions of the future evolution of the earth's atmospheric chemistry and its impact on global circulation patterns are based on Global Climate Models (GCMs) that integrate the complex interactions of the biosphere, atmosphere and the oceans. Most of the available records of climate and environment are short-term records (from decades to a few hundred years) with convolved information of real trends and short-term fluctuations. GCMs must be tested beyond the short-term record of climate and environment to insure that predictions are based on trends and therefore are appropriate to support long term policy making. Unfortunately different parts of the world, weather stations are scattered, records extend over a period of only few years, and there are no systematic climate records for large portions of the globe.

Historical droughts in Mediterranean regions during the last 500 years: a data/model approach

NASA Astrophysics Data System (ADS)

Brewer, S.; Alleaume, S.; Guiot, J.; Nicault, A.

2007-06-01

We present here a new method for comparing the output of General Circulation Models (GCMs) with proxy-based reconstructions, using time series of reconstructed and simulated climate parameters. The method uses k-means clustering to allow comparison between different periods that have similar spatial patterns, and a fuzzy logic-based distance measure in order to take reconstruction errors into account. The method has been used to test two coupled ocean-atmosphere GCMs over the Mediterranean region for the last 500 years, using an index of drought stress, the Palmer Drought Severity Index. The results showed that, whilst no model exactly simulated the reconstructed changes, all simulations were an improvement over using the mean climate, and a good match was found after 1650 with a model run that took into account changes in volcanic forcing, solar irradiance, and greenhouse gases. A more detailed investigation of the output of this model showed the existence of a set of atmospheric circulation patterns linked to the patterns of drought stress: 1) a blocking pattern over northern Europe linked to dry conditions in the south prior to the Little Ice Age (LIA) and during the 20th century; 2) a NAO-positive like pattern with increased westerlies during the LIA; 3) a NAO-negative like period shown in the model prior to the LIA, but that occurs most frequently in the data during the LIA. The results of the comparison show the improvement in simulated climate as various forcings are included and help to understand the atmospheric changes that are linked to the observed reconstructed climate changes.

Partitioning the effects of Global Warming on the Hydrological Cycle with Stable Isotopes in Water Vapor

NASA Astrophysics Data System (ADS)

Dee, S. G.; Russell, J. M.; Nusbaumer, J. M.; Konecky, B. L.; Buenning, N. H.; Lee, J. E.; Noone, D.

2016-12-01

General circulation models (GCMs) suggest that much of the global hydrological cycle's response to anthropogenic warming will be caused by increased lower-tropospheric water vapor concentrations and associated feedbacks. However, fingerprinting changes in the global hydrological cycle due to anthropogenic warming remains challenging. Held and Soden (2006) predicted that as lower-tropospheric water vapor increases, atmospheric circulation will weaken as climate warms to maintain the surface energy budget. Unfortunately, the strength of this feedback and the fallout for other branches of the hydrological cycle is difficult to constrain in situ or with GCMs alone. We demonstrate the utility of stable hydrogen isotope ratios in atmospheric water vapor to quantitatively trace changes in atmospheric circulation and convective mass flux in a warming world. We compare water isotope-enabled GCM experiments for control (present-day) CO2 vs. high CO2(2x, 4x) atmospheres in two GCMs, IsoGSM and iCAM5. We evaluate changes in the distribution of water vapor, vertical velocity (omega), and the stream function between these experiments in order to identify spatial patterns of circulation change over the tropical Pacific (where vertical motion is strong) and map the δD of water vapor associated with atmospheric warming. We also probe the simulations to isolate isotopic signatures associated with water vapor residence time, precipitation efficiency, divergence, and cloud physics. We show that there are robust mechanisms that moisten the troposphere and weaken convective mass flux, and that these mechanisms can be tracked using the δD of water vapor. Further, we find that these responses are most pronounced in the upper troposphere. These findings provide a framework to develop new metrics for the detection of global warming impacts to the hydrological cycle. Further, currently available satellite missions measure δD in the atmospheric boundary layer, the free atmosphere, or the total column; our study suggests that more accurate upper troposphere measurements (above 500hPa) may be needed to detect changes in convective mass flux using water vapor isotope ratios.

Composite Study Of Aerosol Long-Range Transport Events From East Asia And North America

NASA Astrophysics Data System (ADS)

Jiang, X.; Waliser, D. E.; Guan, B.; Xavier, P.; Petch, J.; Klingaman, N. P.; Woolnough, S.

2011-12-01

While the Madden-Julian Oscillation (MJO) exerts pronounced influences on global climate and weather systems, current general circulation models (GCMs) exhibit rather limited capability in representing this prominent tropical variability mode. Meanwhile, the fundamental physics of the MJO are still elusive. Given the central role of the diabatic heating for prevailing MJO theories and demands for reducing the model deficiencies in simulating the MJO, a global model inter-comparison project on diabatic processes and vertical heating structure associated with the MJO has been coordinated through a joint effort by the WCRP-WWRP/THORPEX YOTC MJO Task Force and GEWEX GASS Program. In this presentation, progress of this model inter-comparison project will be reported, with main focus on climate simulations from about 27 atmosphere-only and coupled GCMs. Vertical structures of heating and diabatic processes associated with the MJO based on multi-model simulations will be presented along with their reanalysis and satellite estimate counterparts. Key processes possibly responsible for a realistic simulation of the MJO, including moisture-convection interaction, gross moist stability, ocean coupling, and surface heat flux, will be discussed.

Rain, Brains and Climate Change: improving understanding of regional precipitation with medical registration techniques (Invited)

NASA Astrophysics Data System (ADS)

Levy, A.; Ingram, W.; Allen, M. R.; Jenkinson, M.; Lambert, F. H.; Huntingford, C.

2013-12-01

Precipitation is one of the most important climate variables, but is extremely difficult for general circulation models (GCMs) to simulate accurately. Not only do GCMs disagree on projected and past changes, but they also struggle to get the mean present day distribution of precipitation correct. Some of this disagreement in changes, though, is due to errors in location in the GCMs' mean climate. For example, if the GCMs disagree about the location of the South Asian monsoon, they will disagree in their projections when compared locally, even if they all simulate an intensification of this feature. We have therefore implemented techniques to remove biases of location from GCMs' mean climates. Initially, we adapted medical registration software designed for the analysis of brain scans, using it to transform each GCM's mean climate onto observations. These transformations (or ';warps') were then applied to each GCM's projected changes under an extreme climate change scenario (1% CO2 experiment). We found that both the inter-model range and standard deviation were decreased by 15%, with many regions of the globe receiving a more than 50% reduction [Levy et al. 2013, GRL]. We have now developed a technique tailored to the spatial (longitudinal and latitudinal) and seasonal warping of precipitation fields, which is able to correct precipitation fields much more accurately, as well as providing the option to conserve total global rainfall upon warping. As well as allowing more confident projections of future climate change, this technique can be expected to improve the power and accuracy of the detection and attribution of past changes in precipitation. We have now begun investigating this application, and preliminary results will be presented here.

The Double ITCZ Syndrome in GCMs: A Coupled Problem among Convection, Atmospheric and Ocean Circulations

NASA Astrophysics Data System (ADS)

Zhang, G. J.; Song, X.

2017-12-01

The double ITCZ bias has been a long-standing problem in coupled atmosphere-ocean models. A previous study indicates that uncertainty in the projection of global warming due to doubling of CO2 is closely related to the double ITCZ biases in global climate models. Thus, reducing the double ITCZ biases is not only important to getting the current climate features right, but also important to narrowing the uncertainty in future climate projection. In this work, we will first review the possible factors contributing to the ITCZ problem. Then, we will focus on atmospheric convection, presenting recent progress in alleviating the double ITCZ problem and its sensitivity to details of convective parameterization, including trigger conditions for convection onset, convective memory, entrainment rate, updraft model and closure in the NCAR CESM1. These changes together can result in dramatic improvements in the simulation of ITCZ. Results based on both atmospheric only and coupled simulations with incremental changes of convection scheme will be shown to demonstrate the roles of convection parameterization and coupled interaction between convection, atmospheric circulation and ocean circulation in the simulation of ITCZ.

Hurricane Intensity Forecasts with a Global Mesoscale Model on the NASA Columbia Supercomputer

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Atlas, Robert

2006-01-01

It is known that General Circulation Models (GCMs) have insufficient resolution to accurately simulate hurricane near-eye structure and intensity. The increasing capabilities of high-end computers (e.g., the NASA Columbia Supercomputer) have changed this. In 2004, the finite-volume General Circulation Model at a 1/4 degree resolution, doubling the resolution used by most of operational NWP center at that time, was implemented and run to obtain promising landfall predictions for major hurricanes (e.g., Charley, Frances, Ivan, and Jeanne). In 2005, we have successfully implemented the 1/8 degree version, and demonstrated its performance on intensity forecasts with hurricane Katrina (2005). It is found that the 1/8 degree model is capable of simulating the radius of maximum wind and near-eye wind structure, and thereby promising intensity forecasts. In this study, we will further evaluate the model s performance on intensity forecasts of hurricanes Ivan, Jeanne, Karl in 2004. Suggestions for further model development will be made in the end.

Problems with the North American Monsoon in CMIP/IPCC GCM Precipitation

NASA Astrophysics Data System (ADS)

Schiffer, N. J.; Nesbitt, S. W.

2011-12-01

Successful water management in the Desert Southwest and surrounding areas hinges on anticipating the timing and distribution of precipitation. IPCC AR4 models predict a more arid climate, more extreme precipitation events, and an earlier peak in springtime streamflow in the North American Monsoon region as the area warms. This study aims to assess the summertime skill with which general circulation models (GCMs) simulate precipitation and related dynamics over this region, a necessary precursor to reliable hydroclimate projections. Thirty-year climatologies of several GCMs in the third and fifth Climate Model Intercomparison Projects (CMIP) are statistically evaluated against each other and observed climatology for their skill in representing the location, timing, variability, character, and large-scale forcing of precipitation over the southwestern United States and northwestern Mexico. The results of this study will lend greater credence to more detailed, higher resolution studies, based on the CMIP and IPCC models, of the region's future hydrology. Our ultimate goal is to provide guidance such that decision-makers can plan future water management with more confidence.

Climate Projections from the NARCliM Project: Bayesian Model Averaging of Maximum Temperature Projections

NASA Astrophysics Data System (ADS)

Olson, R.; Evans, J. P.; Fan, Y.

2015-12-01

NARCliM (NSW/ACT Regional Climate Modelling Project) is a regional climate project for Australia and the surrounding region. It dynamically downscales 4 General Circulation Models (GCMs) using three Regional Climate Models (RCMs) to provide climate projections for the CORDEX-AustralAsia region at 50 km resolution, and for south-east Australia at 10 km resolution. The project differs from previous work in the level of sophistication of model selection. Specifically, the selection process for GCMs included (i) conducting literature review to evaluate model performance, (ii) analysing model independence, and (iii) selecting models that span future temperature and precipitation change space. RCMs for downscaling the GCMs were chosen based on their performance for several precipitation events over South-East Australia, and on model independence.Bayesian Model Averaging (BMA) provides a statistically consistent framework for weighing the models based on their likelihood given the available observations. These weights are used to provide probability distribution functions (pdfs) for model projections. We develop a BMA framework for constructing probabilistic climate projections for spatially-averaged variables from the NARCliM project. The first step in the procedure is smoothing model output in order to exclude the influence of internal climate variability. Our statistical model for model-observations residuals is a homoskedastic iid process. Comparing RCMs with Australian Water Availability Project (AWAP) observations is used to determine model weights through Monte Carlo integration. Posterior pdfs of statistical parameters of model-data residuals are obtained using Markov Chain Monte Carlo. The uncertainty in the properties of the model-data residuals is fully accounted for when constructing the projections. We present the preliminary results of the BMA analysis for yearly maximum temperature for New South Wales state planning regions for the period 2060-2079.

Applicability of ranked Regional Climate Models (RCM) to assess the impact of climate change on Ganges: A case study.

NASA Astrophysics Data System (ADS)

Anand, Jatin; Devak, Manjula; Gosain, Ashvani Kumar; Khosa, Rakesh; Dhanya, Ct

2017-04-01

The negative impact of climate change is felt over wide range of spatial scales, ranging from small basins to large watershed area, which can possibly outweighs the benefits of natural water system. General Circulation Models (GCMs) has been widely used as an input to a hydrological models (HMs), to simulate different hydrological components of a river basin. However, the coarser scale of GCMs and spatio-temporal biases, restricted its use at finer resolution. If downscaled, adds one more level of uncertainty i.e., downscaling uncertainty together with model and scenario uncertainty. The outputs computed from Regional Climate Models (RCM) may aid the uncertainties arising from GCMs, as the RCMs are the miniatures of GCMs. However, the RCMs do have some inherent systematic biases, hence bias correction is a prerequisite process before it is fed to HMs. RCMs, together with the input from GCMs at later boundaries also takes topography of the area into account. Hence, RCMs need to be ranked a priori. In this study, impact of climate change on the Ganga basin, India, is assessed using the ranked RCMs. Firstly, bias correction of 14 RCM models are done using Quantile-Quantile mapping and Equidistant cumulative distribution method, for historic (1990-2004) and future scenario (2021-2100), respectively. The runoff simulations from Soil Water Assessment Tool (SWAT), for historic scenario is used for ranking of RCMs. Entropy and PROMETHEE-2 method is employed to rank the RCMs based on five performance indicators namely, Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), normalised root mean square error (NRMSE), absolute normalised mean bias error (ANMBE) and average absolute relative error (AARE). The results illustrated that each of the performance indicators behaves differently for different RCMs. RCA 4 (CNRM-CERFACS) is found as the best model with the highest value of  (0.85), followed by RCA4 (MIROC) and RCA4 (ICHEC) with  values of 0.80 and 0.53, respectively, for Ganga basin. Flow-duration curve and long-term average of streamflow for ranked RCMs, confirm that SWAT model is efficient in capturing the hydrology of the basin. For monsoon months (June, July, August and September), future annual mean surface runoff decreases substantially ( -50 % to -10%), while the base flow for October, November and December is projected to increase ( 10- 20 %). Analysis of snow-melt hydrology, indicated that the snow-melt is projected to increase during the months of November to March, with a maximum increase (400%) shown by RCA 4 (CNRM-CERFACS) and least by RCA4 (ICHEC) (15%). Further, all the RCMs projected higher and lower frequency of dry and wet monsoon, respectively. The analysis of simulated base flow and recharge illustrates that the change varies from +100% to - 500% and +97% to -600%, respectively, with central part of the basin undergoing major loss in the recharge. Hence, this research provides important insights of surface runoff to climate change projections and therefore, better administration and management of available resources is necessary. Keyword: Climate change, uncertainty, Soil Water Assessment Tool (SWAT), General Circulation Model (GCM), Regional Climate Models (RCM), Bias correction.

Effects of Projected Transient Changes in Climate on Tennessee Forests

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

Dale, Virginia H; Tharp, M Lynn; Lannom, Karen O.

This study examines transient effects of projected climate change on the structure and species composition of forests in Tennessee. The climate change scenarios for 2030 and 2080 were provided by the National Center for Atmospheric Research (NCAR) from three General Circulation Models (GCMs) that simulate the range of potential climate conditions for the state. The precipitation and temperature projections from the three GCMs for 2030 and 2080 were related to changes in the ecoregions by using the monthly record of temperature and precipitation from 1980 to 1997 for each 1 km cell across the state as aggregated into the fivemore » ecological provinces. Temperatures are projected to increase in all ecological provinces in all months for all three GCMs for both 2030 and 2080. Precipitation patterns are more complex with one model projecting wetter summers and two models projecting drier summers. The forest ecosystem model LINKAGES was used to simulate conditions in forest stands for the five ecological provinces of Tennessee from 1989 to 2300. These model runs suggest there will be a change in tree diversity and species composition in all ecological provinces with the greatest changes occurring in the Southern Mixed Forest province. Most projections show a decline in total tree biomass followed by recovery as species replacement occurs in stands. The changes in forest biomass and composition, as simulated in this study, are likely to have implications on forest economy, tourism, understory conditions, wildlife habitat, mast provisioning, and other services provided by forest systems.« less

Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, FrançOis P.; Poulin, Annie; Leconte, Robert

2011-12-01

General circulation models (GCMs) and greenhouse gas emissions scenarios (GGES) are generally considered to be the two major sources of uncertainty in quantifying the climate change impacts on hydrology. Other sources of uncertainty have been given less attention. This study considers overall uncertainty by combining results from an ensemble of two GGES, six GCMs, five GCM initial conditions, four downscaling techniques, three hydrological model structures, and 10 sets of hydrological model parameters. Each climate projection is equally weighted to predict the hydrology on a Canadian watershed for the 2081-2100 horizon. The results show that the choice of GCM is consistently a major contributor to uncertainty. However, other sources of uncertainty, such as the choice of a downscaling method and the GCM initial conditions, also have a comparable or even larger uncertainty for some hydrological variables. Uncertainties linked to GGES and the hydrological model structure are somewhat less than those related to GCMs and downscaling techniques. Uncertainty due to the hydrological model parameter selection has the least important contribution among all the variables considered. Overall, this research underlines the importance of adequately covering all sources of uncertainty. A failure to do so may result in moderately to severely biased climate change impact studies. Results further indicate that the major contributors to uncertainty vary depending on the hydrological variables selected, and that the methodology presented in this paper is successful at identifying the key sources of uncertainty to consider for a climate change impact study.

The parameterization of the planetary boundary layer in the UCLA general circulation model - Formulation and results

NASA Technical Reports Server (NTRS)

Suarez, M. J.; Arakawa, A.; Randall, D. A.

1983-01-01

A planetary boundary layer (PBL) parameterization for general circulation models (GCMs) is presented. It uses a mixed-layer approach in which the PBL is assumed to be capped by discontinuities in the mean vertical profiles. Both clear and cloud-topped boundary layers are parameterized. Particular emphasis is placed on the formulation of the coupling between the PBL and both the free atmosphere and cumulus convection. For this purpose a modified sigma-coordinate is introduced in which the PBL top and the lower boundary are both coordinate surfaces. The use of a bulk PBL formulation with this coordinate is extensively discussed. Results are presented from a July simulation produced by the UCLA GCM. PBL-related variables are shown, to illustrate the various regimes the parameterization is capable of simulating.

Ice sheets play important role in climate change

NASA Astrophysics Data System (ADS)

Clark, Peter U.; MacAyeal, Douglas R.; Andrews, John T.; Bartlein, Patrick J.

Ice sheets once were viewed as passive elements in the climate system enslaved to orbitally generated variations in solar radiation. Today, modeling results and new geologic records suggest that ice sheets actively participated in late-Pleistocene climate change, amplifying or driving significant variability at millennial as well as orbital timescales. Although large changes in global ice volume were ultimately caused by orbital variations (the Milankovitch hypothesis), once in existence, the former ice sheets behaved dynamically and strongly influenced regional and perhaps even global climate by altering atmospheric and oceanic circulation and temperature.Experiments with General Circulation Models (GCMs) yielded the first inklings of ice sheets' climatic significance. Manabe and Broccoli [1985], for example, found that the topographic and albedo effects of ice sheets alone explain much of the Northern Hemisphere cooling identified in paleoclimatic records of the last glacial maximum (˜21 ka).

The impact of climatological model biases in the North Atlantic jet on predicted future circulation change

NASA Astrophysics Data System (ADS)

Simpson, I.

2015-12-01

A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet.

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.

Evaluation of Extratropical Cyclone Precipitation in the North Atlantic Basin: An analysis of ERA-Interim, WRF, and two CMIP5 models.

PubMed

Booth, James F; Naud, Catherine M; Willison, Jeff

2018-03-01

The representation of extratropical cyclones (ETCs) precipitation in general circulation models (GCMs) and a weather research and forecasting (WRF) model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic Basin. Lagrangian cyclone tracks of ETCs in ERA-Interim reanalysis (ERAI), the GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km resolution WRF model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with GISS generating the most, followed by ERAI and then GFDL. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.

Assessment of Surface Air Temperature over China Using Multi-criterion Model Ensemble Framework

NASA Astrophysics Data System (ADS)

Li, J.; Zhu, Q.; Su, L.; He, X.; Zhang, X.

2017-12-01

The General Circulation Models (GCMs) are designed to simulate the present climate and project future trends. It has been noticed that the performances of GCMs are not always in agreement with each other over different regions. Model ensemble techniques have been developed to post-process the GCMs' outputs and improve their prediction reliabilities. To evaluate the performances of GCMs, root-mean-square error, correlation coefficient, and uncertainty are commonly used statistical measures. However, the simultaneous achievements of these satisfactory statistics cannot be guaranteed when using many model ensemble techniques. Meanwhile, uncertainties and future scenarios are critical for Water-Energy management and operation. In this study, a new multi-model ensemble framework was proposed. It uses a state-of-art evolutionary multi-objective optimization algorithm, termed Multi-Objective Complex Evolution Global Optimization with Principle Component Analysis and Crowding Distance (MOSPD), to derive optimal GCM ensembles and demonstrate the trade-offs among various solutions. Such trade-off information was further analyzed with a robust Pareto front with respect to different statistical measures. A case study was conducted to optimize the surface air temperature (SAT) ensemble solutions over seven geographical regions of China for the historical period (1900-2005) and future projection (2006-2100). The results showed that the ensemble solutions derived with MOSPD algorithm are superior over the simple model average and any single model output during the historical simulation period. For the future prediction, the proposed ensemble framework identified that the largest SAT change would occur in the South Central China under RCP 2.6 scenario, North Eastern China under RCP 4.5 scenario, and North Western China under RCP 8.5 scenario, while the smallest SAT change would occur in the Inner Mongolia under RCP 2.6 scenario, South Central China under RCP 4.5 scenario, and South Central China under RCP 8.5 scenario.

Thoughts on why in CESM a more poleward TOA energy imbalance favors more ocean-centric energy transport and weaker ITCZ shift responses

NASA Astrophysics Data System (ADS)

Yu, S.; Pritchard, M. S.

2017-12-01

The role of different location of top-of-atmosphere (TOA) solar forcing to the annual-mean, zonal-mean ITCZ location is examined in a dynamic ocean coupled Community Earth System Model. We observe a damped ITCZ shift response that is now a familiar response of coupled GCMs, but a new finding is that the damping efficiency is increases monotonically as the latitudinal location of forcing is moved poleward. More Poleward forcing cases exhibit weaker shifts of the annual-mean ITCZ position consistent with a more ocean-centric cross-equatorial energy partitioning response to the forcing, which is in turn linked to changes in ocean circulation, not thermodynamic structure. The ocean's dynamic response is partly due to Ekman-driven shallow overturning circulation responses, as expected from a recent theory, but also contains a significant Atlantic meridional overturning circulation (AMOC) component--which is in some sense surprising given that it is activated even in near-tropical forcing experiments. Further analysis of the interhemispheric energy budget reveals the surface heating feedback response provides a useful framework for interpreting the cross-equatorial energy transport partitioning between atmosphere and ocean. Overall, the results of this study may help explain the mixed results of the degree of ITCZ shift response to interhemispheric asymmetric forcing documented in coupled GCMs in recent years. Furthermore, the sensitive AMOC response motivates expanding current coupled theoretical frameworks on meridional energy transport partitioning to include effects beyond Ekman transport.

Revisiting Gill's Circulation. Dynamic Response to Diabatic Heating of Different Horizontal Extents

NASA Astrophysics Data System (ADS)

Reboredo, B.; Bellon, G.

2017-12-01

The horizontal extent of diabatic heating associated with the MJO is thought to be crucial to its development, and the inability of GCMs to simulate the spatial, horizontal organization of clouds is considered a leading hypothesis to explain their limited capacity to simulate MJO events. This prevents the MJO large-circulation response from developing and feeding back on the development of clouds. We apply mid-tropospheric heating of different size in simple linear and non-linear models of the tropical atmosphere following Gill's seminal work on heat-induced tropical circulations. Results show that there is a scale for which the characteristic circulation {Γ c} for the vertical advection of moisture to produce the latent heat mean {Q} gives a rough estimate of the real world MJO scale. Overturning circulation flow rates above {Γ c} account for a circulation that transports more moisture than necessary to be maintained, and below {Γ c}, circulation would not transport enough moisture to maintain circulation. This dynamic scale might constrain the size of the spatially-organised convection necessary to the development of an MJO event. However, other effects are expected to modulate this scale, such as vertical advection of moisture anomalies, horizontal advection, evaporation, radiative heating, and sensible heat fluxes.

Decadal covariability of Atlantic SSTs and western Amazon dry-season hydroclimate in observations and CMIP5 simulations

NASA Astrophysics Data System (ADS)

Fernandes, Katia; Giannini, Alessandra; Verchot, Louis; Baethgen, Walter; Pinedo-Vasquez, Miguel

2015-08-01

The unusual severity and return time of the 2005 and 2010 dry-season droughts in western Amazon is attributed partly to decadal climate fluctuations and a modest drying trend. Decadal variability of western Amazon hydroclimate is highly correlated to the Atlantic sea surface temperature (SST) north-south gradient (NSG). Shifts of dry and wet events frequencies are also related to the NSG phase, with a 66% chance of 3+ years of dry events per decade when NSG > 0 and 19% when NSG < 0. The western Amazon and NSG decadal covariability is well reproduced in general circulation models (GCMs) historical (HIST) and preindustrial control (PIC) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). The HIST and PIC also reproduce the shifts in dry and wet events probabilities, indicating potential for decadal predictability based on GCMs. Persistence of the current NSG positive phase favors above normal frequency of western Amazon dry events in coming decades.

Climate pattern-scaling set for an ensemble of 22 GCMs - adding uncertainty to the IMOGEN version 2.0 impact system

NASA Astrophysics Data System (ADS)

Zelazowski, Przemyslaw; Huntingford, Chris; Mercado, Lina M.; Schaller, Nathalie

2018-02-01

Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25 ± 5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44 ± 4.37 and 14.98 ± 4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources

USGS Publications Warehouse

Palmquist, Kyle A.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, Willliam K.

2016-01-01

In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.

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.

Towards a phenomena-based model assessment: The Case of Blocking over Europe

NASA Astrophysics Data System (ADS)

Jury, Martin W.; Barriopedro, David

2016-04-01

Atmospheric Blocking (AB) is a main phenomenon influencing the future climate change in Europe. Results of Global Circulation Models (GCMs) state with medium confidence that the frequency of AB over the Northern Hemisphere will not increase, while AB-related regional changes in Europe are uncertain especially in connection to AB intensity and its persistence. Here, we present results of a study connecting GCMs' ability to reproduce AB patterns and its abilities to correctly reproduce Temperature near the surface (tas) and Precipitation (pr). The used method detects AB by localizing high pressure systems between 55°N and 65°N with the use of geopotential height gradients on the 500 hPa level (zg500). Daily fields of tas and pr are connected to the results of the AB detection over continental Europe. The AB detection method accounts for AB frequency, AB duration and AB intensity and henceforth allowing a detailed comparison of AB representations in GCMs. Furthermore, the number of AB episodes, average AB duration, longitudinal extension and longitudinal propagation are taken into account. The AB detection is applied on zg500 fields of 3 Reanalysis (ERA40, JRA55 and NCEP/NCAR) and 10 GCMs of the CMIP5 between 1961 and 1990 over the Atlantic and over Europe. Most of the evaluated models underrepresent the spatial distribution of annual blocking days over Europe. This is also the case on seasonal timescales, with the largest underestimations during winter and only some overestimations during summer. There are indications that biases in the representation of AB are connected to overall GCM biases concerning the representation of surface fields. Especially when taking into account the seasonal as well as localized characteristics of the AB representation and the surface biases.

Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

NASA Astrophysics Data System (ADS)

García-García, A.; Cuesta-Valero, F. J.; Beltrami, H.; Smerdon, J. E.

2017-12-01

The relationships between air and ground surface temperatures across North America are examined in the historical and future projection simulations from 32 General Circulation Models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The covariability between surface air (2 m) and ground surface temperatures (10 cm) is affected by simulated snow cover, vegetation cover and precipitation through changes in soil moisture at the surface. At high latitudes, the differences between air and ground surface temperatures, for all CMIP5 simulations, are related to the insulating effect of snow cover and soil freezing phenomena. At low latitudes, the differences between the two temperatures, for the majority of simulations, are inversely proportional to leaf area index and precipitation, likely due to induced-changes in latent and sensible heat fluxes at the ground surface. Our results show that the transport of energy across the air-ground interface differs from observations and among GCM simulations, by amounts that depend on the components of the land-surface models that they include. The large variability among GCMs and the marked dependency of the results on the choice of the land-surface model, illustrate the need for improving the representation of processes controlling the coupling of the lower atmosphere and the land surface in GCMs as a means of reducing the variability in their representation of weather and climate phenomena, with potentially important implications for positive climate feedbacks such as permafrost and soil carbon stability.

Do Coupled Climate Models Correctly SImulate the Upward Branch of the Deept Ocean Global Conveyor?

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

Sarmiento, Jorge L; Downes, Stephanie; Bianchi, Daniele

The large-scale meridional overturning circulation (MOC) connects the deep ocean, a major reservoir of carbon, to the other components of the climate system and must therefore be accurately represented in Earth System Models. Our project aims to address the specific question of the pathways and mechanisms controlling the upwelling branch of the MOC, a subject of significant disagreement between models and observational syntheses, and among general circulation models. Observations of these pathways are limited, particularly in regions of complex hydrography such as the Southern Ocean. As such, we rely on models to examine theories of the overturning circulation, both physicallymore » and biogeochemically. This grant focused on a particular aspect of the meridional overturning circulation (MOC) where there is currently significant disagreement between models and observationally based analyses of the MOC, and amongst general circulation models. In particular, the research focused on addressing the following questions: 1. Where does the deep water that sinks in the polar regions rise to the surface? 2. What processes are responsible for this rise? 3. Do state-of-the-art coupled GCMs capture these processes? Our research had three key components: observational synthesis, model development and model analysis. In this final report we outline the key results from these areas of research for the 2007 to 2012 grant period. The research described here was carried out primarily by graduate student, Daniele Bianchi (now a Postdoc at McGill University, Canada), and Postdoc Stephanie Downes (now a Research Fellow at The Australian national University, Australia). Additional support was provided for programmers Jennifer Simeon as well as Rick Slater.« less

Statistical downscaling of GCM simulations to streamflow using relevance vector machine

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Mujumdar, P. P.

2008-01-01

General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical downscaling based on sparse Bayesian learning and Relevance Vector Machine (RVM) to model streamflow at river basin scale for monsoon period (June, July, August, September) using GCM simulated climatic variables. NCEP/NCAR reanalysis data have been used for training the model to establish a statistical relationship between streamflow and climatic variables. The relationship thus obtained is used to project the future streamflow from GCM simulations. The statistical methodology involves principal component analysis, fuzzy clustering and RVM. Different kernel functions are used for comparison purpose. The model is applied to Mahanadi river basin in India. The results obtained using RVM are compared with those of state-of-the-art Support Vector Machine (SVM) to present the advantages of RVMs over SVMs. A decreasing trend is observed for monsoon streamflow of Mahanadi due to high surface warming in future, with the CCSR/NIES GCM and B2 scenario.

Cloud ice: A climate model challenge with signs and expectations of progress

NASA Astrophysics Data System (ADS)

Waliser, Duane E.; Li, Jui-Lin F.; Woods, Christopher P.; Austin, Richard T.; Bacmeister, Julio; Chern, Jiundar; Del Genio, Anthony; Jiang, Jonathan H.; Kuang, Zhiming; Meng, Huan; Minnis, Patrick; Platnick, Steve; Rossow, William B.; Stephens, Graeme L.; Sun-Mack, Szedung; Tao, Wei-Kuo; Tompkins, Adrian M.; Vane, Deborah G.; Walker, Christopher; Wu, Dong

2009-04-01

Present-day shortcomings in the representation of upper tropospheric ice clouds in general circulation models (GCMs) lead to errors in weather and climate forecasts as well as account for a source of uncertainty in climate change projections. An ongoing challenge in rectifying these shortcomings has been the availability of adequate, high-quality, global observations targeting ice clouds and related precipitating hydrometeors. In addition, the inadequacy of the modeled physics and the often disjointed nature between model representation and the characteristics of the retrieved/observed values have hampered GCM development and validation efforts from making effective use of the measurements that have been available. Thus, even though parameterizations in GCMs accounting for cloud ice processes have, in some cases, become more sophisticated in recent years, this development has largely occurred independently of the global-scale measurements. With the relatively recent addition of satellite-derived products from Aura/Microwave Limb Sounder (MLS) and CloudSat, there are now considerably more resources with new and unique capabilities to evaluate GCMs. In this article, we illustrate the shortcomings evident in model representations of cloud ice through a comparison of the simulations assessed in the Intergovernmental Panel on Climate Change Fourth Assessment Report, briefly discuss the range of global observational resources that are available, and describe the essential components of the model parameterizations that characterize their "cloud" ice and related fields. Using this information as background, we (1) discuss some of the main considerations and cautions that must be taken into account in making model-data comparisons related to cloud ice, (2) illustrate present progress and uncertainties in applying satellite cloud ice (namely from MLS and CloudSat) to model diagnosis, (3) show some indications of model improvements, and finally (4) discuss a number of remaining questions and suggestions for pathways forward.

Ensembles modeling approach to study Climate Change impacts on Wheat

NASA Astrophysics Data System (ADS)

Ahmed, Mukhtar; Claudio, Stöckle O.; Nelson, Roger; Higgins, Stewart

2017-04-01

Simulations of crop yield under climate variability are subject to uncertainties, and quantification of such uncertainties is essential for effective use of projected results in adaptation and mitigation strategies. In this study we evaluated the uncertainties related to crop-climate models using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and 14 general circulation models (GCMs) for 2 representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 W m-2) in the Pacific Northwest (PNW), USA. The aim was to assess how different process-based crop models could be used accurately for estimation of winter wheat growth, development and yield. Firstly, all models were calibrated for high rainfall, medium rainfall, low rainfall and irrigated sites in the PNW using 1979-2010 as the baseline period. Response variables were related to farm management and soil properties, and included crop phenology, leaf area index (LAI), biomass and grain yield of winter wheat. All five models were run from 2000 to 2100 using the 14 GCMs and 2 RCPs to evaluate the effect of future climate (rainfall, temperature and CO2) on winter wheat phenology, LAI, biomass, grain yield and harvest index. Simulated time to flowering and maturity was reduced in all models except EPIC with some level of uncertainty. All models generally predicted an increase in biomass and grain yield under elevated CO2 but this effect was more prominent under rainfed conditions than irrigation. However, there was uncertainty in the simulation of crop phenology, biomass and grain yield under 14 GCMs during three prediction periods (2030, 2050 and 2070). We concluded that to improve accuracy and consistency in simulating wheat growth dynamics and yield under a changing climate, a multimodel ensemble approach should be used.

FIRE Science Results 1989

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor)

1990-01-01

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.

RACORO Extended-Term Aircraft Observations of Boundary-Layer Clouds

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; McFarquhar, Greg M.; Ogren, John A.; Turner, David D.; Comstock, Jennifer M.; Feingold, Graham; Long, Charles N.; Jonsson, Haflidi H.; Bucholtz, Anthony; Collins, Don R.;

Potential evapotranspiration and the likelihood of future drought

NASA Technical Reports Server (NTRS)

Rind, D.; Hansen, J.; Goldberg, R.; Rosenzweig, C.; Ruedy, R.

1990-01-01

The possibility that the greenhouse warming predicted by the GISS general-circulation model and other GCMs could lead to severe droughts is investigated by means of numerical simulations, with a focus on the role of potential evapotranspiration E(P). The relationships between precipitation (P), E(P), soil moisture, and vegetation changes in GCMs are discussed; the empirically derived Palmer drought-intensity index and a new supply-demand index (SDDI) based on changes in P - E(P) are described; and simulation results for the period 1960-2060 are presented in extensive tables, graphs, and computer-generated color maps. Simulations with both drought indices predict increasing drought frequency for the U.S., with effects already apparent in the 1990s and a 50-percent frequency of severe droughts by the 2050s. Analyses of arid periods during the Mesozoic and Cenozoic are shown to support the use of the SDDI in GCM drought prediction.

Overlap Properties of Clouds Generated by a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Khairoutdinov, M.

2002-01-01

In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will estimate the radiation effects of multi-layer cloud fields more accurately.

Projection of spatial and temporal changes of rainfall in Sarawak of Borneo Island using statistical downscaling of CMIP5 models

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Chung, Eun-Sung; Ismail, Tarmizi bin

2017-11-01

This study assesses the possible changes in rainfall patterns of Sarawak in Borneo Island due to climate change through statistical downscaling of General Circulation Models (GCM) projections. Available in-situ observed rainfall data were used to downscale the future rainfall from ensembles of 20 GCMs of Coupled Model Intercomparison Project phase 5 (CMIP5) for four Representative Concentration Pathways (RCP) scenarios, namely, RCP2.6, RCP4.5, RCP6.0 and RCP8.5. Model Output Statistics (MOS) based downscaling models were developed using two data mining approaches known as Random Forest (RF) and Support Vector Machine (SVM). The SVM was found to downscale all GCMs with normalized mean square error (NMSE) of 48.2-75.2 and skill score (SS) of 0.94-0.98 during validation. The results show that the future projection of the annual rainfalls is increasing and decreasing on the region-based and catchment-based basis due to the influence of the monsoon season affecting the coast of Sarawak. The ensemble mean of GCMs projections reveals the increased and decreased mean of annual precipitations at 33 stations with the rate of 0.1% to 19.6% and one station with the rate of - 7.9% to - 3.1%, respectively under all RCP scenarios. The remaining 15 stations showed inconsistency neither increasing nor decreasing at the rate of - 5.6% to 5.2%, but mainly showing a trend of decreasing rainfall during the first period (2010-2039) followed by increasing rainfall for the period of 2070-2099.

Exacerbation of South Asian monsoon biases in GCMs using when using coupled ocean models

NASA Astrophysics Data System (ADS)

Turner, Andrew

2015-04-01

Cold biases during spring in the northern Arabian Sea of coupled ocean-atmosphere GCMs have previously been shown to limit monsoon rainfall over South Asia during the subsequent summer, by limiting the availability of moisture being advected. The cold biases develop following advection of cold dry air on anomalous northerly low level flow, suggestive of a too-strong winter monsoon in the coupled GCMs. As the same time, these cold biases and the anomalous advection have been related to larger scales by interaction with progression of the midlatitude westerly upper level flow. In this study we compare monsoon characteristics in 20th century historical and AMIP integrations of the CMIP5 multi-model database. We use a period of 1979-2005, common to both the AMIP and historical integrations. While all available observed boundary conditions, including sea-surface temperature (SST), are prescribed in the AMIP integrations, the historical integrations feature ocean-atmosphere models that generate SSTs via air-sea coupled processes. In AMIP experiments, the seasonal mean monsoon rainfall is shown to be systematically larger than in the coupled versions, with an earlier onset date also shown using a variety of circulation and precipitation metrics. In addition, examination of the springtime jet structure suggests that it sits too far south in the coupled models, leading to a delayed formation of the South Asia High over the Tibetan Plateau in summer. Further, we show that anomalous low entropy air is being advected near the surface from the north over the Arabian Sea in spring in the coupled models.

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.

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.

Biosphere-Atmosphere Transfer Scheme (BATS) version le as coupled to the NCAR community climate model. Technical note. [NCAR (National Center for Atmospheric Research)

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

Dickinson, R.E.; Henderson-Sellers, A.; Kennedy, P.J.

A comprehensive model of land-surface processes has been under development suitable for use with various National Center for Atmospheric Research (NCAR) General Circulation Models (GCMs). Special emphasis has been given to describing properly the role of vegetation in modifying the surface moisture and energy budgets. The result of these efforts has been incorporated into a boundary package, referred to as the Biosphere-Atmosphere Transfer Scheme (BATS). The current frozen version, BATS1e is a piece of software about four thousand lines of code that runs as an offline version or coupled to the Community Climate Model (CCM).

Performance of the CORDEX regional climate models in simulating offshore wind and wind potential

NASA Astrophysics Data System (ADS)

Kulkarni, Sumeet; Deo, M. C.; Ghosh, Subimal

2018-03-01

This study is oriented towards quantification of the skill addition by regional climate models (RCMs) in the parent general circulation models (GCMs) while simulating wind speed and wind potential with particular reference to the Indian offshore region. To arrive at a suitable reference dataset, the performance of wind outputs from three different reanalysis datasets is evaluated. The comparison across the RCMs and their corresponding parent GCMs is done on the basis of annual/seasonal wind statistics, intermodel bias, wind climatology, and classes of wind potential. It was observed that while the RCMs could simulate spatial variability of winds, well for certain subregions, they generally failed to replicate the overall spatial pattern, especially in monsoon and winter. Various causes of biases in RCMs were determined by assessing corresponding maps of wind vectors, surface temperature, and sea-level pressure. The results highlight the necessity to carefully assess the RCM-yielded winds before using them for sensitive applications such as coastal vulnerability and hazard assessment. A supplementary outcome of this study is in form of wind potential atlas, based on spatial distribution of wind classes. This could be beneficial in suitably identifying viable subregions for developing offshore wind farms by intercomparing both the RCM and GCM outcomes. It is encouraging that most of the RCMs and GCMs indicate that around 70% of the Indian offshore locations in monsoon would experience mean wind potential greater than 200 W/m2.

GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

NASA Astrophysics Data System (ADS)

Ern, Manfred; Trinh, Quang Thai; Preusse, Peter; Gille, John C.; Mlynczak, Martin G.; Russell, James M., III; Riese, Martin

2018-04-01

Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs) and chemistry climate models (CCMs) usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE). GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Typical distributions (zonal averages and global maps) of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments) and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658.

Intercomparison of General Circulation Models for Hot Extrasolar Planet Atmospheres

NASA Astrophysics Data System (ADS)

Cho, James

2013-11-01

In this collaborative work with I. Polichtchouk, C. Watkins, H. Th. Thrastarson, O. M. Umurhan, and M. de la Torre-Juárez, we compare five general circulation models (GCMs) which have been recently used to study hot extrasolar planet atmospheres (BOB, CAM, IGCM, MITgcm, and PEQMOD), under three test cases useful for assessing model convergence and accuracy. Such a broad, detailed intercomparison has not been performed thus far for extrasolar planets study. The models considered all solve the traditional primitive equations, but employ different numerical algorithms or grids (e.g., pseudospectral and finite volume, with the latter separately in longitude-latitude and ``cubed-sphere'' grids). The test cases are chosen to cleanly address specific aspects of the behaviors typically reported in hot extrasolar planet simulations: 1) steady-state, 2) nonlinearly evolving baroclinic wave, and 3) response to fast timescale thermal relaxation. When initialized with a steady jet, all models maintain the steadiness, as they should--except MITgcm in cubed-sphere grid. A very good agreement is obtained for a baroclinic wave evolving from an initial instability in spectral models (only). However, exact numerical convergence is still not achieved across the spectral models: amplitudes and phases are observably different. When subject to a typical ``hot-Jupiter''-like forcing, all five models show quantitatively different behavior--although qualitatively similar, time-variable, quadrupole-dominated flows are produced. Hence, as have been advocated in several past studies, specific quantitative predictions (such as the location of large vortices and hot regions) by GCMs should be viewed with caution. Overall, in the tests considered here, spectral models in pressure coordinate (PEBOB and PEQMOD) perform the best and MITgcm in cubed-sphere grid performs the worst. This work has been supported by the Science and Technology Facilities Council, Westfield Small Grant, NASA Postdoctoral Program, and Institute for Theory and Computation, Harvard College Observatory.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Impact of climate change on precipitation distribution and water availability in the Nile using CMIP5 GCM ensemble.

NASA Astrophysics Data System (ADS)

Mekonnen, Z. T.; Gebremichael, M.

2017-12-01

ABSTRACT In a basin like the Nile where millions of people depend on rainfed agriculture and surface water resources for their livelihoods, changes in precipitation will have tremendous social and economic consequences. General circulation models (GCMs) have been associated with high uncertainty in their projection of future precipitation for the Nile basin. Some studies tried to compare performance of different GCMs by doing a Multi-Model comparison for the region. Many indicated that there is no single model that gives the "best estimate" of precipitation for a very complex and large basin like the Nile. In this study, we used a combination of satellite and long term rain gauge precipitation measurements (TRMM and CenTrends) to evaluate the performance of 10 GCMs from the 5th Coupled Model Intercomparison Project (CMIP5) at different spatial and seasonal scales and produce a weighted ensemble projection. Our results confirm that there is no single model that gives best estimate over the region, hence the approach of creating an ensemble depending on how the model performed in specific areas and seasons resulted in an improved estimate of precipitation compared with observed values. Following the same approach, we created an ensemble of future precipitation projections for four different time periods (2000-2024, 2025-2049 and 2050-2100). The analysis showed that all the major sub-basins of the Nile will get will get more precipitation with time, even though the distribution with in the sub basin might be different. Overall the analysis showed a 15 % increase (125 mm/year) by the end of the century averaged over the area up to the Aswan dam. KEY WORDS: Climate Change, CMIP5, Nile, East Africa, CenTrends, Precipitation, Weighted Ensembles

Estimation of climate change impact on dead fuel moisture at local scale by using weather generators

NASA Astrophysics Data System (ADS)

Pellizzaro, Grazia; Bortolu, Sara; Dubrovsky, Martin; Arca, Bachisio; Ventura, Andrea; Duce, Pierpaolo

2015-04-01

The moisture content of dead fuel is an important variable in fire ignition and fire propagation. Moisture exchange in dead materials is controlled by physical processes, and is clearly dependent on atmospheric changes. According to projections of future climate in Southern Europe, changes in temperature, precipitation and extreme events are expected. More prolonged drought seasons could influence fuel moisture content and, consequently, the number of days characterized by high ignition danger in Mediterranean ecosystems. The low resolution of the climate data provided by the general circulation models (GCMs) represents a limitation for evaluating climate change impacts at local scale. For this reason, the climate research community has called to develop appropriate downscaling techniques. One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking a stochastic weather generator with the climate model outputs. Weather generators linked to climate change scenarios can therefore be used to create synthetic weather series (air temperature and relative humidity, wind speed and precipitation) representing present and future climates at local scale. The main aims of this work are to identify useful tools to determine potential impacts of expected climate change on dead fuel status in Mediterranean shrubland and, in particular, to estimate the effect of climate changes on the number of days characterized by critical values of dead fuel moisture. Measurements of dead fuel moisture content (FMC) in Mediterranean shrubland were performed by using humidity sensors in North Western Sardinia (Italy) for six years. Meteorological variables were also recorded. Data were used to determine the accuracy of the Canadian Fine Fuels Moisture Code (FFM code) in modelling moisture dynamics of dead fuel in Mediterranean vegetation. Critical threshold values of FFM code for Mediterranean climate were identified by percentile analysis, and new fuel moisture code classes were also defined. A stochastic weather generator (M&Rfi), linked to climate change scenarios derived from 17 available General Circulation Models (GCMs), was used to produce synthetic weather series, representing present and future climates, for four selected sites located in North Western Sardinia, Italy. The number of days with critical FFM code values for present and future climate were calculated and the potential impact of future climate change was analysed.

Identifying misbehaving models using baseline climate variance

NASA Astrophysics Data System (ADS)

Schultz, Colin

2011-06-01

The majority of projections made using general circulation models (GCMs) are conducted to help tease out the effects on a region, or on the climate system as a whole, of changing climate dynamics. Sun et al., however, used model runs from 20 different coupled atmosphere-ocean GCMs to try to understand a different aspect of climate projections: how bias correction, model selection, and other statistical techniques might affect the estimated outcomes. As a case study, the authors focused on predicting the potential change in precipitation for the Murray-Darling Basin (MDB), a 1-million- square- kilometer area in southeastern Australia that suffered a recent decade of drought that left many wondering about the potential impacts of climate change on this important agricultural region. The authors first compared the precipitation predictions made by the models with 107 years of observations, and they then made bias corrections to adjust the model projections to have the same statistical properties as the observations. They found that while the spread of the projected values was reduced, the average precipitation projection for the end of the 21st century barely changed. Further, the authors determined that interannual variations in precipitation for the MDB could be explained by random chance, where the precipitation in a given year was independent of that in previous years.

Skills of General Circulation and Earth System Models in reproducing streamflow to the ocean: the case of Congo river

NASA Astrophysics Data System (ADS)

Santini, M.; Caporaso, L.

2017-12-01

Although the importance of water resources in the context of climate change, it is still difficult to correctly simulate the freshwater cycle over the land via General Circulation and Earth System Models (GCMs and ESMs). Existing efforts from the Climate Model Intercomparison Project 5 (CMIP5) were mainly devoted to the validation of atmospheric variables like temperature and precipitation, with low attention to discharge.Here we investigate the present-day performances of GCMs and ESMs participating to CMIP5 in simulating the discharge of the river Congo to the sea thanks to: i) the long-term availability of discharge data for the Kinshasa hydrological station representative of more than 95% of the water flowing in the whole catchment; and ii) the River's still low influence by human intervention, which enables comparison with the (mostly) natural streamflow simulated within CMIP5.Our findings suggest how most of models appear overestimating the streamflow in terms of seasonal cycle, especially in the late winter and spring, while overestimation and variability across models are lower in late summer. Weighted ensemble means are also calculated, based on simulations' performances given by several metrics, showing some improvements of results.Although simulated inter-monthly and inter-annual percent anomalies do not appear significantly different from those in observed data, when translated into well consolidated indicators of drought attributes (frequency, magnitude, timing, duration), usually adopted for more immediate communication to stakeholders and decision makers, such anomalies can be misleading.These inconsistencies produce incorrect assessments towards water management planning and infrastructures (e.g. dams or irrigated areas), especially if models are used instead of measurements, as in case of ungauged basins or for basins with insufficient data, as well as when relying on models for future estimates without a preliminary quantification of model biases.

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.

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

USGS Publications Warehouse

Hostetler, S.W.; Alder, J.R.; Allan, A.M.

2011-01-01

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

Tropical Cumulus Convection and Upward Propagating Waves in Middle Atmospheric GCMs

NASA Technical Reports Server (NTRS)

Horinouchi, T.; Pawson, S.; Shibata, K.; Langematz, U.; Manzini, E.; Giorgetta, M. A.; Sassi, F.; Wilson, R. J.; Hamilton, K. P.; deGranpre, J.;

Combined top-down and bottom-up climate change impact assessment for the hydrological system in the Vu Gia- Thu Bon River Basin.

PubMed

Tra, Tran Van; Thinh, Nguyen Xuan; Greiving, Stefan

2018-07-15

Vu Gia- Thu Bon (VGTB) River Basin, located in the Central Coastal zone of Viet Nam currently faces water shortage. Climate change is expected to exacerbate the challenge. Therefore, there is a need to study the impacts of climate change on water shortage in the river basin. The study adopts a combined top-down and bottom-up climate change impact assessment to address the impacts of climate change on water shortage in the VGTB River Basin. A MIKE BASIN water balance model for the river basin was established to simulate the response of the hydrological system. Simulations were performed through parametrically varying temperature and precipitation to determine the vulnerability space of water shortage. General Circulation Models (GCMs) were then utilized to provide climate projections for the river basin. The output from GCMs was then mapped onto the vulnerability space determined earlier. In total, 9 out of 55 water demand nodes in the simulation are expected to face problematic conditions as future climate changes. Copyright © 2018 Elsevier B.V. All rights reserved.

Impact of cloud timing on surface temperature and related hydroclimatic dynamics

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Yin, J.

2015-12-01

Cloud feedbacks have long been identified as one of the largest source of uncertainty in climate change predictions. Differences in the spatial distribution of clouds and the related impact on surface temperature and climate dynamics have been recently emphasized in quasi-equilibrium General Circulation Models (GCM). However, much less attention has been paid to the temporal variation of cloud presence and thickness. Clouds in fact shade the solar radiation during the daytime, but also acts as greenhouse gas to reduce the emission of longwave radiation to the outer space anytime of the day. Thus it is logical to expect that even small differences in timing and thickness of clouds could result in very different predictions in GCMs. In this study, these two effects of cloud dynamics are analyzed by tracking the cloud impacts on longwave and shortwave radiation in a minimalist transient thermal balance model of the land surface. The marked changes in surface temperature due to alterations in the timing of onset of clouds demonstrate that capturing temporal variation of cloud at sub-daily scale should be a priority in cloud parameterization schemes in GCMs.

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 Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

NASA Technical Reports Server (NTRS)

Barsugli, Joseph J.; Guentchev, Galina; Horton, Radley M.; Wood, Andrew; Mearns, Lindo O.; Liang, Xin-Zhong; Winkler, Julia A.; Dixon, Keith; Hayhoe, Katharine; Rood, Richard B.;

Improvement of the GEOS-5 AGCM upon Updating the Air-Sea Roughness Parameterization

NASA Technical Reports Server (NTRS)

Garfinkel, C. I.; Molod, A.; Oman, L. D.; Song, I.-S.

2011-01-01

The impact of an air-sea roughness parameterization over the ocean that more closely matches recent observations of air-sea exchange is examined in the NASA Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model. Surface wind biases in the GEOS-5 AGCM are decreased by up to 1.2m/s. The new parameterization also has implications aloft as improvements extend into the stratosphere. Many other GCMs (both for operational weather forecasting and climate) use a similar class of parameterization for their air-sea roughness scheme. We therefore expect that results from GEOS-5 are relevant to other models as well.

Mid-latitude shrub steppe plant communities: climate change consequences for soil water resources.

PubMed

Palmquist, Kyle A; Schlaepfer, Daniel R; Bradford, John B; Lauenroth, William K

2016-09-01

In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: (1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems, and (2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT, to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, whereas changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer, drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen. © 2016 by the Ecological Society of America.

Quantifying the effect of mixing on the mean age of air in CCMVal-2 and CCMI-1 models

NASA Astrophysics Data System (ADS)

Dietmüller, Simone; Eichinger, Roland; Garny, Hella; Birner, Thomas; Boenisch, Harald; Pitari, Giovanni; Mancini, Eva; Visioni, Daniele; Stenke, Andrea; Revell, Laura; Rozanov, Eugene; Plummer, David A.; Scinocca, John; Jöckel, Patrick; Oman, Luke; Deushi, Makoto; Kiyotaka, Shibata; Kinnison, Douglas E.; Garcia, Rolando; Morgenstern, Olaf; Zeng, Guang; Stone, Kane Adam; Schofield, Robyn

2018-05-01

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry-climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry-Climate Model Validation Activity 2) and CCMI-1 (Chemistry-Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Simulated impacts of climate change on phosphorus loading to Lake Michigan

USGS Publications Warehouse

Robertson, Dale M.; Saad, David A.; Christiansen, Daniel E.; Lorenz, David J

2016-01-01

Phosphorus (P) loading to the Great Lakes has caused various types of eutrophication problems. Future climatic changes may modify this loading because climatic models project changes in future meteorological conditions, especially for the key hydrologic driver — precipitation. Therefore, the goal of this study is to project how P loading may change from the range of projected climatic changes. To project the future response in P loading, the HydroSPARROW approach was developed that links results from two spatially explicit models, the SPAtially Referenced Regression on Watershed attributes (SPARROW) transport and fate watershed model and the water-quantity Precipitation Runoff Modeling System (PRMS). PRMS was used to project changes in streamflow throughout the Lake Michigan Basin using downscaled meteorological data from eight General Circulation Models (GCMs) subjected to three greenhouse gas emission scenarios. Downscaled GCMs project a + 2.1 to + 4.0 °C change in average-annual air temperature (+ 2.6 °C average) and a − 5.1% to + 16.7% change in total annual precipitation (+ 5.1% average) for this geographic area by the middle of this century (2045–2065) and larger changes by the end of the century. The climatic changes by mid-century are projected to result in a − 21.2% to + 8.9% change in total annual streamflow (− 1.8% average) and a − 29.6% to + 17.2% change in total annual P loading (− 3.1% average). Although the average projected changes in streamflow and P loading are relatively small for the entire basin, considerable variability exists spatially and among GCMs because of their variability in projected future precipitation.

Implications of climate change for wetland-dependent birds in the Prairie Pothole Region

USGS Publications Warehouse

Steen, Valerie; Skagen, Susan K.; Melcher, Cynthia P.

2016-01-01

The habitats and food resources required to support breeding and migrant birds dependent on North American prairie wetlands are threatened by impending climate change. The North American Prairie Pothole Region (PPR) hosts nearly 120 species of wetland-dependent birds representing 21 families. Strategic management requires knowledge of avian habitat requirements and assessment of species most vulnerable to future threats. We applied bioclimatic species distribution models (SDMs) to project range changes of 29 wetland-dependent bird species using ensemble modeling techniques, a large number of General Circulation Models (GCMs), and hydrological climate covariates. For the U.S. PPR, mean projected range change, expressed as a proportion of currently occupied range, was −0.31 (± 0.22 SD; range − 0.75 to 0.16), and all but two species were projected to lose habitat. Species associated with deeper water were expected to experience smaller negative impacts of climate change. The magnitude of climate change impacts was somewhat lower in this study than earlier efforts most likely due to use of different focal species, varying methodologies, different modeling decisions, or alternative GCMs. Quantification of the projected species-specific impacts of climate change using species distribution modeling offers valuable information for vulnerability assessments within the conservation planning process.

Insights into low-latitude cloud feedbacks from high-resolution models.

PubMed

Bretherton, Christopher S

2015-11-13

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes. © 2015 The Author(s).

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.

Bias correction of temperature produced by the Community Climate System Model using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Moghim, S.; Hsu, K.; Bras, R. L.

2013-12-01

General Circulation Models (GCMs) are used to predict circulation and energy transfers between the atmosphere and the land. It is known that these models produce biased results that will have impact on their uses. This work proposes a new method for bias correction: the equidistant cumulative distribution function-artificial neural network (EDCDFANN) procedure. The method uses artificial neural networks (ANNs) as a surrogate model to estimate bias-corrected temperature, given an identification of the system derived from GCM models output variables. A two-layer feed forward neural network is trained with observations during a historical period and then the adjusted network can be used to predict bias-corrected temperature for future periods. To capture the extreme values this method is combined with the equidistant CDF matching method (EDCDF, Li et al. 2010). The proposed method is tested with the Community Climate System Model (CCSM3) outputs using air and skin temperature, specific humidity, shortwave and longwave radiation as inputs to the ANN. This method decreases the mean square error and increases the spatial correlation between the modeled temperature and the observed one. The results indicate the EDCDFANN has potential to remove the biases of the model outputs.

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.

The Surface Energy Balance at Local and Regional Scales-A Comparison of General Circulation Model Results with Observations.

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Krummel, P. B.; Kowalczyk, E. A.

1993-06-01

Aspects of the mean monthly energy balance at continental surfaces are examined by appeal to the results of general circulation model (GCM) simulations, climatological maps of surface fluxes, and direct observations. Emphasis is placed on net radiation and evaporation for (i) five continental regions (each approximately 20°×150°) within Africa, Australia, Eurasia, South America, and the United States; (ii) a number of continental sites in both hemispheres. Both the mean monthly values of the local and regional fluxes and the mean monthly diurnal cycles of the local fluxes are described. Mostly, GCMs tend to overestimate the mean monthly levels of net radiation by about 15% -20% on an annual basis, for observed annual values in the range 50 to 100 Wm2. This is probably the result of several deficiencies, including (i) continental surface albedos being undervalued in a number of the models, resulting in overestimates of the net shortwave flux at the surface (though this deficiency is steadily being addressed by modelers); (ii) incoming shortwave fluxes being overestimated due to uncertainties in cloud schemes and clear-sky absorption; (iii) land-surface temperatures being under-estimated resulting in an underestimate of the outgoing longwave flux. In contrast, and even allowing for the poor observational base for evaporation, there is no obvious overall bias in mean monthly levels of evaporation determined in GCMS, with one or two exceptions. Rather, and far more so than with net radiation, there is a wide range in values of evaporation for all regions investigated. For continental regions and at times of the year of low to moderate rainfall, there is a tendency for the simulated evaporation to be closely related to the precipitation-this is not surprising. In contrast, for regions where there is sufficient or excessive rainfall, the evaporation tends to follow the behavior of the net radiation. Again, this is not surprising given the close relation between potential evaporation and net radiation, as discussed by Priestley and Taylor. Finally, the introduction into GCMs of an `improved' surface scheme (incorporating more realistic representations of soil and canopy processes and revised albedos) does tend to improve the calculations of both regional net radiation and evaporation.

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.

Microwave Investigation of the Mars Atmosphere and Surface

NASA Technical Reports Server (NTRS)

Gulkis, S.; Forget, F.; Janssen, M.; Riley, A. L.; Hartogh, P.; Clancy, T.; Allen, M.; Frerking, M.

2000-01-01

The Microwave Investigation of the Mars Atmosphere and Surface Experiment (MIMAS) is designed to address two major scientific goals: 1) To understand the three dimensional general circulation of the Martian atmosphere, and 2) To understand the hydrologic cycle of water on Mars, including the time-variable sources, sinks, and atmospheric transport of water vapor. The proposed instrument is a submillimeter wave, heterodyne receiver, with both continuum and very high spectral resolution capability. A small reflector antenna will be used to feed the receiver. Instrument heritage comes from the MIRO receiver, currently under design for the ESA Rosetta Mission, and from SWAS, a NASA astrophysics mission. The instrument will be able to measure atmospheric spectral lines from both water and carbon monoxide and use these lines as tracers of atmospheric winds. Measurement objectives of MIMAS are to measure surface temperature, atmospheric temperature from the surface up to an altitude of 60 km or more, the distribution of CO and H2O in the atmosphere, and certain wind fields (zonal and meridional). The global distribution of CO, as well as temperature distributions, will be used as input data for GCMs (general circulation models). Water vapor profiles will be used to understand the sources and sinks of water on Mars and to understand how it is transported globally by the general circulation. Zonal and meridional wind fields will provide further tests of the GCMs. An important aspect of this experiment is that the temperature and humidity measurements are insensitive to dust and ice condensates thereby making the measurement capability independent of the presence of dust clouds and ice particles. Temperature measurements derived from the data can be used in conjunction with infrared measurements to determine dust profiles.

Evaluation of performance of seasonal precipitation prediction at regional scale over India

NASA Astrophysics Data System (ADS)

Mohanty, U. C.; Nageswararao, M. M.; Sinha, P.; Nair, A.; Singh, A.; Rai, R. K.; Kar, S. C.; Ramesh, K. J.; Singh, K. K.; Ghosh, K.; Rathore, L. S.; Sharma, R.; Kumar, A.; Dhekale, B. S.; Maurya, R. K. S.; Sahoo, R. K.; Dash, G. P.

2018-03-01

The seasonal scale precipitation amount is an important ingredient in planning most of the agricultural practices (such as a type of crops, and showing and harvesting schedules). India being an agroeconomic country, the seasonal scale prediction of precipitation is directly linked to the socioeconomic growth of the nation. At present, seasonal precipitation prediction at regional scale is a challenging task for the scientific community. In the present study, an attempt is made to develop multi-model dynamical-statistical approach for seasonal precipitation prediction at the regional scale (meteorological subdivisions) over India for four prominent seasons which are winter (from December to February; DJF), pre-monsoon (from March to May; MAM), summer monsoon (from June to September; JJAS), and post-monsoon (from October to December; OND). The present prediction approach is referred as extended range forecast system (ERFS). For this purpose, precipitation predictions from ten general circulation models (GCMs) are used along with the India Meteorological Department (IMD) rainfall analysis data from 1982 to 2008 for evaluation of the performance of the GCMs, bias correction of the model results, and development of the ERFS. An extensive evaluation of the performance of the ERFS is carried out with dependent data (1982-2008) as well as independent predictions for the period 2009-2014. In general, the skill of the ERFS is reasonably better and consistent for all the seasons and different regions over India as compared to the GCMs and their simple mean. The GCM products failed to explain the extreme precipitation years, whereas the bias-corrected GCM mean and the ERFS improved the prediction and well represented the extremes in the hindcast period. The peak intensity, as well as regions of maximum precipitation, is better represented by the ERFS than the individual GCMs. The study highlights the improvement of forecast skill of the ERFS over 34 meteorological subdivisions as well as India as a whole during all the four seasons.

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.

Future changes in the Mediterranean water budget projected by an ensemble of regional climate models

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, E.; Somot, S.; Mariotti, A.

2009-11-01

The Mediterranean basin is a region characterized by its vulnerability to changes in the water cycle. Hence, the impact of global warming on the water resources in the Mediterranean zone is one of the major concerns for the scientific community. The future climate projections used to elaborate the IPCC report of 2007 show great alterations in the evaporation and precipitation over the Mediterranean Sea at the end of 21st century. In this work we investigate the changes in the Mediterranean Sea water budget by using SRES-A1B scenario experiments performed with high resolution (25 km) regional climate models (RCMs). The RCMs provide good estimates of the water budget components, in particular with a significant improvement of the runoff and Black Sea discharge terms compared to the coarser resolution general circulation models (GCMs) used in the last Intergovernmental Panel of Climate Change (IPCC) report. As for the case of GCMs, the RCMs show that the Mediterranean water budget is likely to be significantly altered at the end of 21st century. The response of the hydrological variables to global warming starts to be statistically significant from 2050, though some alterations are already observed before 2050. The RCMs predict an increase of evaporation, and a decrease of precipitation, and river and Black Sea discharge, yielding to a large increase of the Mediterranean fresh water deficit. The freshwater deficit for the period 2070-2099 related to 1950-1999 presents a mean increase of +40% for both RCMs and GCMs.

North American Megadroughts in the Common Era: Reconstructions and Simulations

NASA Technical Reports Server (NTRS)

Cook, Benjamin I.; Cook, Edward R.; Smerdon, Jason E.; Seager, Richard; Williams, A. Park; Coats, Sloan; Stahle, David W.; Villanueva Diaz, Jose

2016-01-01

During the Medieval Climate Anomaly (MCA), Western North America experienced episodes of intense aridity that persisted for multiple decades or longer. These megadroughts are well documented in many proxy records, but the causal mechanisms are poorly understood. General circulation models (GCMs) simulate megadroughts, but do not reproduce the temporal clustering of events during the MCA, suggesting they are not caused by the time history of volcanic or solar forcing. Instead, GCMs generate megadroughts through (1) internal atmospheric variability, (2) sea-surface temperatures, and (3) land surface and dust aerosol feedbacks. While no hypothesis has been definitively rejected, and no GCM has accurately reproduced all features (e.g., timing, duration, and extent) of any specific megadrought, their persistence suggests a role for processes that impart memory to the climate system (land surface and ocean dynamics). Over the 21st century, GCMs project an increase in the risk of megadrought occurrence through greenhouse gas forced reductions in precipitation and increases in evaporative demand. This drying is robust across models and multiple drought indicators, but major uncertainties still need to be resolved. These include the potential moderation of vegetation evaporative losses at higher atmospheric [CO2], variations in land surface model complexity, and decadal to multidecadal modes of natural climate variability that could delay or advance onset of aridification over the the next several decades. Because future droughts will arise from both natural variability and greenhouse gas forced trends in hydroclimate, improving our understanding of the natural drivers of persistent multidecadal megadroughts should be a major research priority.

Wind-driven variations in an overturning circulation

NASA Astrophysics Data System (ADS)

Bringedal, Carina; Eldevik, Tor; Spall, Michael

2017-04-01

The Atlantic overturning circulation and poleward heat transport is balanced by northern heat loss to the atmosphere and corresponding water mass transformation. The structure of this circulation and transformation is particularly manifested - and observed - at the Greenland-Scotland ridge. There is however a rich variability in the exchanges across the ridge on seasonal and yearly time scales. This variability has been almost perfectly captured in atmospherically forced ocean GCMs (e.g. Olsen et al 2008, Sandø et al 2012), suggesting that on shorter time scales the variability of the exchanges are connected to sea level pressure and corresponding wind stress forcing. Focusing on seasonal and yearly time scales, we accordingly propose that the connection between the exchanges of overturning waters across the Greenland-Scotland ridge and the sea level pressure must be direct and simple, and we use idealized simulations to support this hypothesis. The mechanisms underlying the connection are formulated through conceptual models. Although the models and simulations are simplified with respect to bathymetry and hydrography, they can reproduce the main features of the overturning circulation in the Nordic seas. In the observations, the variable exchanges can largely be related to sea level pressure variations and large scale wind patterns, and the idealized simulations and accompanying conceptual models show how these impacts can manifest via coastal downwelling and gyre circulation. S. M. Olsen, B. Hansen, D. Quadfasel and S. Østerhus, Observed and modelled stability of overflow across the Greenland-Scotland ridge, Nature 455, (2008) A. B. Sandø, J. E. Ø. Nilsen, T. Eldevik and M. Bentsen, Mechanisms for variable North Atlantic-Nordic seas exchanges, Journal of Geophysical Research 117, (2012)

On the Relative Influences of Different Ocean Basin Sea Surface Temperature Anomalies on Southern African Rainfall in 20th and 21st Century GCM Simulations

NASA Astrophysics Data System (ADS)

Lickley, M.; Solomon, S.

2017-12-01

Southern Africa rainfall (SAR) is generally projected to decrease during the 21st century as a result of climate change, though there is some disagreement regarding the location and magnitude of this reduction in General Circulation Models (GCMs). Here we examine the robustness of the rainfall response to sea surface temperature (SST) anomalies. Previous work argues that warmer SSTs in the Indian Ocean suppress SAR. Other studies argue that El Niños lead to suppressed SAR. We examine the SAR response to SST anomalies in the Indian Ocean, Atlantic Ocean and ENSO 3.4 region both in observations and in two large ensembles of GCMs run over the 20th and 21st century. We find that ENSO SSTs are most correlated with SAR, while correlations between SAR and the Indian Ocean are dominated by their respective responses to ENSO. This relationship appears to persist under a warming background state.

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.

The Plane-parallel Albedo Bias of Liquid Clouds from MODIS Observations

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Cahalan, Robert F.; Platnick, Steven

2007-01-01

In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument MODIS on the Terra and Aqua satellites, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the MODIS product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for reflected or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.

Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

NASA Astrophysics Data System (ADS)

Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

2010-12-01

Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

The influence of tropical heating displacements on the extratropical climate

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

1993-01-01

The hypothesis is advanced that a latitudinal shift in the tropical convective heating pattern can significantly alter temperatures in the extratropics. Results of a simplified general circulation model (GCM) show that the shift of a prescribed tropical heating toward the summer pole, on time scales longer than a few weeks, leads to a more intense cross-equatorial 'winter' Hadley circulation, enhanced upper-level tropical easterlies, and a slightly stronger subtropical winter jet, accompanied by warming at the winter middle and high latitudes as a result of increased dynamical heating. The indications are that there is a robust connection between the net dynamic heating in the extratropics and the implied changes in the subtropical wind shear resulting from adjustments in the Hadley circulation associated with convective heating displacements in the tropics. The implications are that (1) the low-frequency temporal variability in the Hadley circulation may play an important role in modulating wave transport in the winter extratropics, (2) the global climate may be sensitive to those processes that control deep cumulus convection in the tropics, and (3) systematic temperature biases in GCMs may be reduced by improving the tropical rainfall simulation.

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.

Stochastic climate dynamics: Stochastic parametrizations and their global effects

NASA Astrophysics Data System (ADS)

Ghil, Michael

2010-05-01

A well-known difficulty in modeling the atmosphere and oceans' general circulation is the limited, albeit increasing resolution possible in the numerical solution of the governing partial differential equations. While the mass, energy and momentum of an individual cloud, in the atmosphere, or convection chimney, in the oceans, is negligible, their combined effects over long times are not. Until recently, small, subgrid-scale processes were represented in general circulation models (GCMs) by deterministic "parametrizations." While A. Arakawa and associates had realized over three decades ago the conceptual need for ensembles of clouds in such parametrizations, it is only very recently that truly stochastic parametrizations have been introduced into GCMs and weather prediction models. These parametrizations essentially transform a deterministic autonomous system into a non-autonomous one, subject to random forcing. To study systematically the long-term effects of such a forcing has to rely on theory of random dynamical systems (RDS). This theory allows one to consider the detailed geometric structure of the random attractors associated with nonlinear, stochastically perturbed systems. These attractors extend the concept of strange attractors from autonomous dynamical systems to non-autonomous systems with random forcing. To illustrate the essence of the theory, its concepts and methods, we carry out a high-resolution numerical study of two "toy" models in their respective phase spaces. This study allows one to obtain a good approximation of their global random attractors, as well as of the time-dependent invariant measures supported by these attractors. The first of the two models studied herein is the Arnol'd family of circle maps in the presence of noise. The maps' fine-grained, resonant landscape --- associated with Arnol'd tongues --- is smoothed by the noise, thus permitting a comparison with the observable aspects of the "Devil's staircase" that arises in modeling the El Nino-Southern Oscillation (ENSO). These results are confirmed by studying a "French garden" that is obtained by smoothing a "Devil's quarry." Such a quarry results from coupling two circle maps, and random forcing leads to a smoothed version thereof. We thus suspect that stochastic parametrizations will stabilize the sensitive dependence on parameters that has been noticed in the development of GCMs. This talk represents joint work with Mickael D. Chekroun, D. Kondrashov, Eric Simonnet and I. Zaliapin. Several other talks and posters complement the results presented here and provide further insights into RDS theory and its application to the geosciences.

The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

DOE PAGES

Tsushima, Yoko; Brient, Florent; Klein, Stephen A.; ...

2017-11-27

The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. Here, this paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments willmore » also be facilitated by the sharing of diagnostic codes via this catalogue. Any code which implements diagnostics relevant to analysing clouds – including cloud–circulation interactions and the contribution of clouds to estimates of climate sensitivity in models – and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.« less

The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

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

Tsushima, Yoko; Brient, Florent; Klein, Stephen A.

The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. Here, this paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments willmore » also be facilitated by the sharing of diagnostic codes via this catalogue. Any code which implements diagnostics relevant to analysing clouds – including cloud–circulation interactions and the contribution of clouds to estimates of climate sensitivity in models – and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.« less

Nonlinear Advection of Tropospheric Humidity and Cloud and Evaporation Feedbacks in the Madden-Julian Oscillation

NASA Astrophysics Data System (ADS)

Sugiyama, M.; Emanuel, K.; Stone, P.

2006-05-01

Despite active research on the Madden-Julian Oscillation (MJO), general circulation models (GCMs) continue to suffer from poor simulations of this tropical intraseasonal variability, and the theory on the MJO remains elusive. To assist model development and deepen our understanding, we develop a simple new model of the MJO, using the Quasiequilibrium Tropical Circulation Model of Neelin and Zeng. The MJO-like disturbance develops as a single-column instability because of cloud-radiative and surface flux feedbacks, a mechanism identified by Sobel and Gildor in their study on a tropical hot spot. Two processes contribute to the eastward movement: Nonlinear advection of the tropospheric humidity to the west, and convergence-induced moistening to the east. The key to the model disturbance is the interplay between tropospheric humidity and precipitation, moisture-convection feedback. As the humidity field propagates eastward by advection and convergence-induced moistening, the precipitation field follows. This study points to possible research areas on GCM parameterizations: 1) the effect of tropospheric humidity on moist convection; 2) the impact of downdraft-enhanced gustiness on surface heat flux; and 3) relationship between precipitation and cloud-radiative forcing.

High resolution decadal precipitation predictions over the continental United States for impacts assessment

NASA Astrophysics Data System (ADS)

Salvi, Kaustubh; Villarini, Gabriele; Vecchi, Gabriel A.

2017-10-01

Unprecedented alterations in precipitation characteristics over the last century and especially in the last two decades have posed serious socio-economic problems to society in terms of hydro-meteorological extremes, in particular flooding and droughts. The origin of these alterations has its roots in changing climatic conditions; however, its threatening implications can only be dealt with through meticulous planning that is based on realistic and skillful decadal precipitation predictions (DPPs). Skillful DPPs represent a very challenging prospect because of the complexities associated with precipitation predictions. Because of the limited skill and coarse spatial resolution, the DPPs provided by General Circulation Models (GCMs) fail to be directly applicable for impact assessment. Here, we focus on nine GCMs and quantify the seasonally and regionally averaged skill in DPPs over the continental United States. We address the problems pertaining to the limited skill and resolution by applying linear and kernel regression-based statistical downscaling approaches. For both the approaches, statistical relationships established over the calibration period (1961-1990) are applied to the retrospective and near future decadal predictions by GCMs to obtain DPPs at ∼4 km resolution. The skill is quantified across different metrics that evaluate potential skill, biases, long-term statistical properties, and uncertainty. Both the statistical approaches show improvements with respect to the raw GCM data, particularly in terms of the long-term statistical properties and uncertainty, irrespective of lead time. The outcome of the study is monthly DPPs from nine GCMs with 4-km spatial resolution, which can be used as a key input for impacts assessments.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.

CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific

NASA Astrophysics Data System (ADS)

Chen, Bingzhang; Smith, Sherwood Lan

2018-02-01

Diversity plays critical roles in ecosystem functioning, but it remains challenging to model phytoplankton diversity in order to better understand those roles and reproduce consistently observed diversity patterns in the ocean. In contrast to the typical approach of resolving distinct species or functional groups, we present a ContInuous TRAiT-basEd phytoplankton model (CITRATE) that focuses on macroscopic system properties such as total biomass, mean trait values, and trait variance. This phytoplankton component is embedded within a nitrogen-phytoplankton-zooplankton-detritus-iron model that itself is coupled with a simplified one-dimensional ocean model. Size is used as the master trait for phytoplankton. CITRATE also incorporates trait diffusion for sustaining diversity and simple representations of physiological acclimation, i.e., flexible chlorophyll-to-carbon and nitrogen-to-carbon ratios. We have implemented CITRATE at two contrasting stations in the North Pacific where several years of observational data are available. The model is driven by physical forcing including vertical eddy diffusivity imported from three-dimensional general ocean circulation models (GCMs). One common set of model parameters for the two stations is optimized using the Delayed-Rejection Adaptive Metropolis-Hasting Monte Carlo (DRAM) algorithm. The model faithfully reproduces most of the observed patterns and gives robust predictions on phytoplankton mean size and size diversity. CITRATE is suitable for applications in GCMs and constitutes a prototype upon which more sophisticated continuous trait-based models can be developed.

A Test of the Fundamental Physics Underlying Exoplanet Climate Models

NASA Astrophysics Data System (ADS)

Beatty, Thomas; Keating, Dylan; Cowan, Nick; Gaudi, Scott; Kataria, Tiffany; Fortney, Jonathan; Stassun, Keivan; Collins, Karen; Deming, Drake; Bell, Taylor; Dang, Lisa; Rogers, Tamara; Colon, Knicole

2018-05-01

A fundamental issue in how we understand exoplanet atmospheres is the assumed physical behavior underlying 3D global circulation models (GCMs). Modeling an entire 3D atmosphere is a Herculean task, and so in exoplanet GCMs we generally assume that there are no clouds, no magnetic effects, and chemical equilibrium (e.g., Kataria et al 2016). These simplifying assumptions are computationally necessary, but at the same time their exclusion allows for a large theoretical lee-way when comparing to data. Thus, though significant discrepancies exist between almost all a priori GCM predictions and their corresponding observations, these are assumed to be due to the lack of clouds, or atmospheric drag, or chemical disequilibrium, in the models (e.g., Wong et al. 2016, Stevenson et al. 2017, Lewis et al. 2017, Zhang et al. 2018). Since these effects compete with one another and have large uncertainties, this makes tests of the fundamental physics in GCMs extremely difficult. To rectify this, we propose to use 88.4 hours of Spitzer time to observe 3.6um and 4.5um phase curves of the transiting giant planet KELT-9b. KELT-9b has an observed dayside temperature of 4600K (Gaudi et al. 2017), which means that there will very likely be no clouds on the day- or nightside, and is hot enough that the atmosphere should be close to local chemical equilibrium. Additionally, we plan to leverage KELT-9b's high temperature to make the first measurement of global wind speed on an exoplanet (Bell & Cowan 2018), giving a constraint on atmospheric drag and magnetic effects. Combined, this means KELT-9b is close to a real-world GCM, without most of the effects present on lower temperature planets. Additionally, since KELT-9b orbits an extremely bright host star these will be the highest signal-to-noise ratio phase curves taken with Spitzer by more than a factor of two. This gives us a unique opportunity to make the first precise and direct investigation into the fundamental physics that are the foundation of all exoplanet GCMs.

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.

Dry-bean production under climate change conditions in the north of Argentina: Risk assessment and economic implications

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

Feijoo, M.; Mestre, F.; Castagnaro, A.

This study evaluates the potential effect of climate change on Dry-bean production in Argentina, combining climate models, a crop productivity model and a yield response model estimation of climate variables on crop yields. The study was carried out in the North agricultural regions of Jujuy, Salta, Santiago del Estero and Tucuman which include the largest areas of Argentina where dry beans are grown as a high input crop. The paper combines the output from a crop model with different techniques of analysis. The scenarios used in this study were generated from the output of two General Circulation Models (GCMs): themore » Goddard Institute for Space Studies model (GISS) and the Canadian Climate Change Model (CCCM). The study also includes a preliminary evaluation of the potential changes in monetary returns taking into account the possible variability of yields and prices, using mean-Gini stochastic dominance (MGSD). The results suggest that large climate change may have a negative impact on the Argentine agriculture sector, due to the high relevance of this product in the export sector. The difference negative effect depends on the varieties of dry bean and also the General Circulation Model scenarios considered for double levels of atmospheric carbon dioxide.« less

A Comprehensive Evaluation of Steroid Metabolism in Women with Intrahepatic Cholestasis of Pregnancy

PubMed Central

Pařízek, Antonín; Hill, Martin; Dušková, Michaela; Vítek, Libor; Velíková, Marta; Kancheva, Radmila; Šimják, Patrik; Koucký, Michal; Kokrdová, Zuzana; Adamcová, Karolína; Černý, Andrej; Hájek, Zdeněk; Stárka, Luboslav

2016-01-01

Intrahepatic cholestasis of pregnancy (ICP) is a common liver disorder, mostly occurring in the third trimester. ICP is defined as an elevation of serum bile acids, typically accompanied by pruritus and elevated activities of liver aminotransferases. ICP is caused by impaired biliary lipid secretion, in which endogenous steroids may play a key role. Although ICP is benign for the pregnant woman, it may be harmful for the fetus. We evaluated the differences between maternal circulating steroids measured by RIA (17-hydroxypregnenolone and its sulfate, 17-hydroxyprogesterone, and cortisol) and GC-MS (additional steroids), hepatic aminotransferases and bilirubin in women with ICP (n = 15, total bile acids (TBA) >8 μM) and corresponding controls (n = 17). An age-adjusted linear model, receiver-operating characteristics (ROC), and multivariate regression (a method of orthogonal projections to latent structure, OPLS) were used for data evaluation. While aminotransferases, conjugates of pregnanediols, 17-hydroxypregnenolone and 5β-androstane-3α,17β-diol were higher in ICP patients, 20α-dihydropregnenolone, 16α-hydroxy-steroids, sulfated 17-oxo-C19-steroids, and 5β-reduced steroids were lower. The OPLS model including steroids measured by GC-MS and RIA showed 93.3% sensitivity and 100% specificity, while the model including steroids measured by GC-MS in a single sample aliquot showed 93.3% sensitivity and 94.1% specificity. A composite index including ratios of sulfated 3α/β-hydroxy-5α/β-androstane-17-ones to conjugated 5α/β-pregnane-3α/β, 20α-diols discriminated with 93.3% specificity and 81.3% sensitivity (ROC analysis). These new data demonstrating altered steroidogenesis in ICP patients offer more detailed pathophysiological insights into the role of steroids in the development of ICP. PMID:27494119

Uncertainty quantification of US Southwest climate from IPCC projections.

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

Boslough, Mark Bruce Elrick

2011-01-01

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statisticalmore » analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.« less

Vistas in applied mathematics: Numerical analysis, atmospheric sciences, immunology

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

Balakrishnan, A.V.; Dorodnitsyn, A.A.; Lions, J.L.

1986-01-01

Advances in the theory and application of numerical modeling techniques are discussed in papers contributed, primarily by Soviet scientists, on the occasion of the 60th birthday of Gurii I. Marchuk. Topics examined include splitting techniques for computations of industrial flows, the mathematical foundations of the k-epsilon turbulence model, splitting methods for the solution of the incompressible Navier-Stokes equations, the approximation of inhomogeneous hyperbolic boundary-value problems, multigrid methods, and the finite-element approximation of minimal surfaces. Consideration is given to dynamic modeling of moist atmospheres, satellite observations of the earth radiation budget and the problem of energy-active ocean regions, a numerical modelmore » of the biosphere for use with GCMs, and large-scale modeling of ocean circulation. Also included are several papers on modeling problems in immunology.« less

Do we know what difference a delay makes?

NASA Astrophysics Data System (ADS)

Risbey, James S.; Handel, Mark David; Stone, Peter H.

In our original comment [Risbey et al.., 1991] we argued that the work of Schlesinger and Jiang [1991a] is too limited to determine whether or not (as they put it) “the penalty is small for a 10-year delay in initiating the transition to a regime in which greenhouse-gas emissions are reduced.” In their reply, Schlesinger and Jiang [1991b] (hereafter S&J) presented their reasons for concluding definitively that the penalty is small. However S&J's discussion of the evidence and literature on climate change and greenhouse warming contains significant omissions and mis-statements.In dismissing our concern that their model was too simple to evaluate the possibility of abrupt climate change, S&J rely on results from coupled ocean-atmosphere general circulation models (GCMs), in particular the work of Cubasch et al.. [1991]. Here S&J make two claims, one of which is incorrect and the other questionable. First, they claim that “the coupled atmosphere-ocean model of Cubasch et al. [1991] does allow the nonlinearities that Risbey et al.. [1991] criticize our simple model for not including.” In fact we explicitly mentioned changes in polar ice caps [Oerlemans and van der Veen, 1984] and release of methane from clathrates [MacDonald, 1990; Bell, 1982], neither of which are included in the model of Cubasch et al.. [1991]. Indeed, none of the published simulations of global warming using coupled ocean-atmosphere GCMs include these effects. Nor do these models yet include in their enhanced greenhouse simulations many of the possible feedbacks involving the carbon cycle and biosphere [Lashof, 1989; Bacastow and Maier-Reimer, 1990; Sellers, 1987] that could significantly alter greenhouse gas concentrations and surface properties. The published simulations with these models do allow for some changes in deep ocean circulation and cloud behavior, but there is controversy over whether they correctly represent these processes [Marotzke, 1991; Mitchell, 1989; Cess, 1990]. In addition the coupled models must be arbitrarily tuned (requiring substantial artificial fluxes of heat and moisture) to get the current climate right [Manabe et al.., 1991; Cubasch et al.., 1991]. Their greenhouse change simulations are at least partly constrained by these flux adjustments.

Thermohaline circulation: a missing equation and its climate-change implications

NASA Astrophysics Data System (ADS)

Ou, Hsien-Wang

2018-01-01

We formulate a box model of coupled ocean-atmosphere to examine the differential fields interactive with the thermohaline circulation (THC) and their response to global warming. We discern a robust convective bound on the atmospheric heat transport, which would divide the climate regime into warm and cold branches; but unlike the saline mode of previous box models, the cold state, if allowed, has the same-signed—though weaker—density contrast and THC as the present climate, which may explain its emergence from coupled general circulation models. We underscore the nondeterminacy of the THC due to random eddy shedding and apply the fluctuation theorem to constrain the shedding rate, thus closing the problem. The derivation reveals an ocean propelled toward the maximum entropy production (MEP) on millennial timescale (termed "MEP-adjustment"), the long timescale arising from the compounding effect of microscopic fluctuations in the shedding rate and their slight probability bias. Global warming may induce hysteresis between the two branches, like that seen in GCMs, but the cold transition is far more sensitive to the moistening than the heating effects as the latter would be countered by the hydrological feedback. The uni- or bi-modality of the current state—hence whether the THC may recover after the cold transition—depends on the global-mean convective flux and may not be easily assessed due to its observed uncertainty.

An improved rainfall disaggregation technique for GCMs

NASA Astrophysics Data System (ADS)

Onof, C.; Mackay, N. G.; Oh, L.; Wheater, H. S.

1998-08-01

Meteorological models represent rainfall as a mean value for a grid square so that when the latter is large, a disaggregation scheme is required to represent the spatial variability of rainfall. In general circulation models (GCMs) this is based on an assumption of exponentiality of rainfall intensities and a fixed value of areal rainfall coverage, dependent on rainfall type. This paper examines these two assumptions on the basis of U.K. and U.S. radar data. Firstly, the coverage of an area is strongly dependent on its size, and this dependence exhibits a scaling law over a range of sizes. Secondly, the coverage is, of course, dependent on the resolution at which it is measured, although this dependence is weak at high resolutions. Thirdly, the time series of rainfall coverages has a long-tailed autocorrelation function which is comparable to that of the mean areal rainfalls. It is therefore possible to reproduce much of the temporal dependence of coverages by using a regression of the log of the mean rainfall on the log of the coverage. The exponential assumption is satisfactory in many cases but not able to reproduce some of the long-tailed dependence of some intensity distributions. Gamma and lognormal distributions provide a better fit in these cases, but they have their shortcomings and require a second parameter. An improved disaggregation scheme for GCMs is proposed which incorporates the previous findings to allow the coverage to be obtained for any area and any mean rainfall intensity. The parameters required are given and some of their seasonal behavior is analyzed.

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

NASA Astrophysics Data System (ADS)

Van Hooidonk, R. J.

2011-12-01

Future widespread coral bleaching and subsequent mortality has been projected with sea surface temperature (SST) data from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. These model weaknesses likely reduce the skill of coral bleaching predictions, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends and their propagation in predictions. To analyze the relative importance of various types of model errors and biases on coral reef bleaching predictive skill, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from GCMs 20th century simulations to be included in the Intergovernmental Panel on Climate Change (IPCC) 5th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate skill using an objective measure of forecast quality, the Peirce Skill Score (PSS). This methodology will identify frequency bands that are important to predicting coral bleaching and it will highlight deficiencies in these bands in models. The methodology we describe can be used to improve future climate model derived predictions of coral reef bleaching and it can be used to better characterize the errors and uncertainty in predictions.

A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation

NASA Astrophysics Data System (ADS)

Xiao, C.; Lofgren, B. M.

2014-12-01

As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.

Evaluation of Drought Occurrence and Climate Change in the Pearl River Basin in South China

NASA Astrophysics Data System (ADS)

DU, Y.; Chen, J.; Wang, K.; Shi, H.

2015-12-01

This study uses the Variable Infiltration Capacity (VIC) Model to simulate the hydrological processes over the Pearl River basin in South China. The observed streamflow data in the Pearl River Basin for the period 1951-2000 are used to evaluate the model simulation results. Further, in this study, the 55 datasets of climate projection from 18 General Circulation Models (GCMs) for the IPCC AR4 (SRES A2/A1B/B1) and AR5 (RCP 2.6/4.5/6.0/8.5) are used to drive the VIC model at 0.5°× 0.5°spatial resolution and daily temporal resolution. Then, the monthly Standard Precipitation Index (SPI) and standardized runoff index (SRI) are generated to detect the drought occurrence. This study validates the GCMs projection through comparing the observed precipitation for the period of 2000-2013. Then, spatial variation of the frequency change of moderate drought, severe drought and extreme drought are analyzed for the 21st century. The study reveals that the frequencies of severe drought and extreme drought occurrences over the Pearl River Basin increase along with time. Specifically, for the scenario of AR5 RCP 8.5, the east and west parts of the Pearl River Basin most likely suffer from severe drought and extreme drought with an increased frequency throughout the 21st century.

New Approaches to Parameterizing Convection

NASA Technical Reports Server (NTRS)

Randall, David A.; Lappen, Cara-Lyn

1999-01-01

Many general circulation models (GCMs) currently use separate schemes for planetary boundary layer (PBL) processes, shallow and deep cumulus (Cu) convection, and stratiform clouds. The conventional distinctions. among these processes are somewhat arbitrary. For example, in the stratocumulus-to-cumulus transition region, stratocumulus clouds break up into a combination of shallow cumulus and broken stratocumulus. Shallow cumulus clouds may be considered to reside completely within the PBL, or they may be regarded as starting in the PBL but terminating above it. Deeper cumulus clouds often originate within the PBL with also can originate aloft. To the extent that our models separately parameterize physical processes which interact strongly on small space and time scales, the currently fashionable practice of modularization may be doing more harm than good.

"What Controls the Structure and Stability of the Ocean Meridional Overturning Circulation: Implications for Abrupt Climate Change?"

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

Fedorov, Alexey

2013-11-23

The central goal of this research project is to understand the properties of the ocean meridional overturning circulation (MOC) – a topic critical for understanding climate variability and stability on a variety of timescales (from decadal to centennial and longer). Specifically, we have explored various factors that control the MOC stability and decadal variability in the Atlantic and the ocean thermal structure in general, including the possibility abrupt climate change. We have also continued efforts on improving the performance of coupled ocean-atmosphere GCMs.

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.

On the sensitivity of the global ocean circulation to reconstructions of paleo-bathymetry

NASA Astrophysics Data System (ADS)

Weber, Tobias; Thomas, Maik

2013-04-01

The ability to model the long-term evolution of the climate does considerably depend on the accuracy of ocean models and their interaction with the atmosphere. Thereby, the ocean model's behavior with respect to uncertain and changing boundary conditions is of crucial importance. One of the remaining questions is, how different reconstructions of the ocean floor influence the model. Although of general interest, this effect has mostly been neglected, so far. We modeled Pliocene and pre-industrial ocean currents with the Max-Planck-Institute Ocean Model (MPIOM), forced by climatologies derived from an atmospheric and vegetational Global Circulation Model (GCM). We equipped it with different reconstructions of the bathymetry, what allowed us to study the model's sensitivity regarding changes in bathymetry. On the one hand we examined the influence of reconstructions with different locations of major ridges, but the same treatment of the shelf. On the other hand, reconstruction techniques that treated the shelf areas differently were taken into consideration. This leads to different oceanic circulation realizations, which induce changes in deep ocean temperature and salinity. Some of the simulations result in unrealistic behavior, such as an increase in surface temperature by several degrees. Most important, small bathymetric changes in the areas of deep water formation near Greenland and the Antarctic alter the thermohaline circulation strongly. This leads to its complete cessation in some of the simulations and therefore to stationary deep laying ocean masses. This shows that not all bathymetric reconstruction sequences are applicable for the generation of boundary conditions for GCMs. In order to obtain reliable and physically realistic data from the models, the reconstruction method to be used for the paleo-bathymetry also needs to be applied to the present day bathymetry. This reconstruction can then be used in a control simulation which can be validated against measurements. Hereby systematic errors introduced by the reconstruction technique are identified.

Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios

USGS Publications Warehouse

Erikson, Li H.; Hegermiller, Christie; Barnard, Patrick; Ruggiero, Peter; van Ormondt, Martin

2015-01-01

Hindcast and 21st century winds, simulated by General Circulation Models (GCMs), were used to drive global- and regional-scale spectral wind-wave generation models in the Pacific Ocean Basin to assess future wave conditions along the margins of the North American west coast and Hawaiian Islands. Three-hourly winds simulated by four separate GCMs were used to generate an ensemble of wave conditions for a recent historical time-period (1976–2005) and projections for the mid and latter parts of the 21st century under two radiative forcing scenarios (RCP 4.5 and RCP 8.5), as defined by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) experiments. Comparisons of results from historical simulations with wave buoy and ERA-Interim wave reanalysis data indicate acceptable model performance of wave heights, periods, and directions, giving credence to generating projections. Mean and extreme wave heights are projected to decrease along much of the North American west coast. Extreme wave heights are projected to decrease south of ∼50°N and increase to the north, whereas extreme wave periods are projected to mostly increase. Incident wave directions associated with extreme wave heights are projected to rotate clockwise at the eastern end of the Aleutian Islands and counterclockwise offshore of Southern California. Local spatial patterns of the changing wave climate are similar under the RCP 4.5 and RCP 8.5 scenarios, but stronger magnitudes of change are projected under RCP 8.5. Findings of this study are similar to previous work using CMIP3 GCMs that indicates decreasing mean and extreme wave conditions in the Eastern North Pacific, but differ from other studies with respect to magnitude and local patterns of change. This study contributes toward a larger ensemble of global and regional climate projections needed to better assess uncertainty of potential future wave climate change, and provides model boundary conditions for assessing the impacts of climate change on coastal systems.

Statistical downscaling of sub-daily (6-hour) temperature in Romania, by means of artificial neural networks

NASA Astrophysics Data System (ADS)

Birsan, Marius-Victor; Dumitrescu, Alexandru; Cǎrbunaru, Felicia

2016-04-01

The role of statistical downscaling is to model the relationship between large-scale atmospheric circulation and climatic variables on a regional and sub-regional scale, making use of the predictions of future circulation generated by General Circulation Models (GCMs) in order to capture the effects of climate change on smaller areas. The study presents a statistical downscaling model based on a neural network-based approach, by means of multi-layer perceptron networks. Sub-daily temperature data series from 81 meteorological stations over Romania, with full data records are used as predictands. As large-scale predictor, the NCEP/NCAD air temperature data at 850 hPa over the domain 20-30E / 40-50N was used, at a spatial resolution of 2.5×2.5 degrees. The period 1961-1990 was used for calibration, while the validation was realized over the 1991-2010 interval. Further, in order to estimate future changes in air temperature for 2021-2050 and 2071-2100, air temperature data at 850 hPa corresponding to the IPCC A1B scenario was extracted from the CNCM33 model (Meteo-France) and used as predictor. This work has been realized within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian Executive Agency for Higher Education Research, Development and Innovation Funding (UEFISCDI).

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.­

Simulations of Hurricane Katrina (2005) with the 0.125 degree finite-volume General Circulation Model on the NASA Columbia Supercomputer

NASA Technical Reports Server (NTRS)

Shen, B.-W.; Atlas, R.; Reale, O.; Lin, S.-J.; Chern, J.-D.; Chang, J.; Henze, C.

2006-01-01

Hurricane Katrina was the sixth most intense hurricane in the Atlantic. Katrina's forecast poses major challenges, the most important of which is its rapid intensification. Hurricane intensity forecast with General Circulation Models (GCMs) is difficult because of their coarse resolution. In this article, six 5-day simulations with the ultra-high resolution finite-volume GCM are conducted on the NASA Columbia supercomputer to show the effects of increased resolution on the intensity predictions of Katrina. It is found that the 0.125 degree runs give comparable tracks to the 0.25 degree, but provide better intensity forecasts, bringing the center pressure much closer to observations with differences of only plus or minus 12 hPa. In the runs initialized at 1200 UTC 25 AUG, the 0.125 degree simulates a more realistic intensification rate and better near-eye wind distributions. Moreover, the first global 0.125 degree simulation without convection parameterization (CP) produces even better intensity evolution and near-eye winds than the control run with CP.

Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

NASA Astrophysics Data System (ADS)

Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

2001-12-01

A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations Environmental Programme's Intergovernmental Panel on Climate Change, IPCC, reports (1990, 1995 and 2001). Our review highlights only the enormous scientific difficulties facing the calculation of climatic effects of added atmospheric CO2 in a GCM. The purpose of such a limited review of the deficiencies of climate model physics and the use of GCMs is to illuminate areas for improvement. Our review does not disprove a significant anthropogenic influence on global climate.

Climate change and forest fires.

PubMed

Flannigan, M D; Stocks, B J; Wotton, B M

2000-11-15

This paper addresses the impacts of climate change on forest fires and describes how this, in turn, will impact on the forests of the United States. In addition to reviewing existing studies on climate change and forest fires we have used two transient general circulation models (GCMs), namely the Hadley Centre and the Canadian GCMs, to estimate fire season severity in the middle of the next century. Ratios of 2 x CO2 seasonal severity rating (SSR) over present day SSR were calculated for the means and maximums for North America. The results suggest that the SSR will increase by 10-50% over most of North America; although, there are regions of little change or where the SSR may decrease by the middle of the next century. Increased SSRs should translate into increased forest fire activity. Thus, forest fires could be viewed as an agent of change for US forests as the fire regime will respond rapidly to climate warming. This change in the fire regime has the potential to overshadow the direct effects of climate change on species distribution and migration.

How Dry is the Tropical Free Troposphere? Implications for Global Warming Theory

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Braswell, William D.

1997-01-01

The humidity of the free troposphere is being increasingly scrutinized in climate research due to its central role in global warming theory through positive water vapor feedback. This feedback is the primary source of global warming in general circulation models (GCMs). Because the loss of infrared energy to space increases nonlinearly with decreases in relative humidity, the vast dry zones in the Tropics are of particular interest. These dry zones are nearly devoid of radiosonde stations, and most of those stations have, until recently, ignored the low humidity information from the sondes. This results in substantial uncertainty in GCM tuning and validation based on sonde data. While satellite infrared radiometers are now beginning to reveal some information about the aridity of the tropical free troposphere, the authors show that the latest microwave humidity sounder data suggests even drier conditions than have been previously reported. This underscores the importance of understanding how these low humidity levels are controlled in order to tune and validate GCMs, and to predict the magnitude of water vapor feedback and thus the magnitude of global warming.

Freshwater fluxes into the subpolar North Atlantic from secular trends in Arctic land ice mass balance

NASA Astrophysics Data System (ADS)

Bamber, J. L.; Enderlin, E. M.; Howat, I. M.; Wouters, B.; van den Broeke, M.

2015-12-01

Freshwater fluxes (FWF) from river runoff and precipitation minus evaporation for the pan Arctic seas are relatively well documented and prescribed in ocean GCMs. Fluxes from Greenland and Arctic glaciers and ice caps on the other hand are generally ignored, despite their potential impacts on ocean circulation and marine biology and growing evidence for changes to the hydrography of parts of the subpolar North Atlantic. In a previous study we determined the FWF from Greenland for the period 1958-2010 using a combination of observations and regional climate modeling. Here, we update the analysis with data from new satellite observations to extend the record both in space and time. The new FWF estimates cover the period 1958-2014 and include the Canadian, Russian and Norwegian Arctic (Svalbard) in addition to the contributions from Greenland. We combine satellite altimetry (including CryoSat 2) with grounding line flux data, regional climate modeling of surface mass balance and gravimetry to produce consistent estimates of solid ice and liquid FWF into the Arctic and North Atlantic Oceans. The total cumulative FWF anomaly from land ice mass loss started to increase significantly in the mid 1990s and now exceeds 5000 km^3, a value that is about half of the Great Salinity Anomaly of the 1970s. The majority of the anomaly is entering two key areas of deep water overturning in the Labrador and Irminger Seas, at a rate that has been increasing steadily over the last ~20 years. Since the mid 2000s, however, the Canadian Arctic archipelago has been making a significant contribution to the FW anomaly entering Baffin Bay. Tracer experiments with eddy-permitting ocean GCMs suggest that the FW input from southern Greenland and the Canadian Arctic should accumulate in Baffin Bay with the potential to affect geostrophic circulation, stratification in the region and possibly the strength of the Atlantic Meridional Overturning Circulation. We also examine the trajectory of freshwater input in the form of icebergs, which does not have the same fate as liquid input.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

NASA Astrophysics Data System (ADS)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

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.

Model unification and scale-adaptivity in the Eddy-Diffusivity Mass-Flux (EDMF) approach

NASA Astrophysics Data System (ADS)

Neggers, R.; Siebesma, P.

2011-12-01

It has long been understood that the turbulent-convective transport of heat, moisture and momentum plays an important role in the dynamics and climate of the earth's atmosphere. Accordingly, the representation of these processes in General Circulation Models (GCMs) has always been an active research field. Turbulence and convection act on temporal and spatial scales that are unresolved by most present-day GCMs, and have to be represented through parametric relations. Over the years a variety of schemes has been successfully developed. Although differing widely in their details, only two basic transport models stand at the basis of most of these schemes. The first is the diffusive transport model, which can only act down-gradient. An example is the turbulent mixing at small scales. The second is the advective transport model, which can act both down-gradient and counter-gradient. A good example is the transport of heat and moisture by convective updrafts that overshoot into stable layers of air. In practice, diffusive models often make use of a K-profile method or a prognostic TKE budget, while advective models make use of a rising (and entraining) plume budget. While most transport schemes classicaly apply either the diffusive model or advective model, the relatively recently introduced Eddy-Diffusivity Mass-Flux (EDMF) approach aims to combine both techniques. By applying advection and diffusion simultaneously, one can make use of the benefits of both approaches. Since its emergence about a decade ago, the EDMF approach has been successfully applied in both research and operational circulation models. This presentation is dedicated to the EDMF framework. Apart from a short introduction to the EDMF concept and a short overview of its current implementations, our main goal is to elaborate on the opportunities EDMF brings in addressing some long-standing problems in the parameterization of turbulent-convective transport. The first problem is the need for a unified approach in the parameterization of distinct transport regimes. The main objections to a separate representation of regimes are i) artificially discrete regime-transitions, and ii) superfluous and intransparent coding. For a unified approach we need to establish what complexity is sufficient to achieve general applicability. We argue that adding only little complexity already enables the standard EDMF framework to represent multiple boundary-layer transport regimes and smooth transitions between those. The second long-standing problem is that the ever increasing computational capacity and speed has lead to increasingly fine discretizations in GCMs, which requires scale-adaptivity in a sub-grid transport model. It is argued that a flexible partitioning between advection and diffusion within EDMF, as well as the potential to introduce stochastic elements in the advective part of EDMF, creates opportunities to introduce such adaptivity. In the final part of the presentation we will attempt to give an overview of currently ongoing developments of the EDMF framework, both concerning model formulation as well as evaluation efforts of key assumptions against observational datasets and large-eddy simulation results.

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.

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.

Projecting Wind Energy Potential Under Climate Change with Ensemble of Climate Model Simulations

NASA Astrophysics Data System (ADS)

Jain, A.; Shashikanth, K.; Ghosh, S.; Mukherjee, P. P.

2013-12-01

Recent years have witnessed an increasing global concern over energy sustainability and security, triggered by a number of issues, such as (though not limited to): fossil fuel depletion, energy resource geopolitics, economic efficiency versus population growth debate, environmental concerns and climate change. Wind energy is a renewable and sustainable form of energy in which wind turbines convert the kinetic energy of wind into electrical energy. Global warming and differential surface heating may significantly impact the wind velocity and hence the wind energy potential. Sustainable design of wind mills requires understanding the impacts of climate change on wind energy potential, which we evaluate here with multiple General Circulation Models (GCMs). GCMs simulate the climate variables globally considering the greenhouse emission scenarios provided as Representation Concentration path ways (RCPs). Here we use new generation climate model outputs obtained from Coupled model Intercomparison Project 5(CMIP5). We first compute the wind energy potential with reanalysis data (NCEP/ NCAR), at a spatial resolution of 2.50, where the gridded data is fitted to Weibull distribution and with the Weibull parameters, the wind energy densities are computed at different grids. The same methodology is then used, to CMIP5 outputs (resultant of U-wind and V-wind) of MRI, CMCC, BCC, CanESM, and INMCM4 for historical runs. This is performed separately for four seasons globally, MAM, JJA, SON and DJF. We observe the muti-model average of wind energy density for historic period has significant bias with respect to that of reanalysis product. Here we develop a quantile based superensemble approach where GCM quantiles corresponding to selected CDF values are regressed to reanalysis data. It is observed that this regression approach takes care of both, bias in GCMs and combination of GCMs. With superensemble, we observe that the historical wind energy density resembles quite well with reanalysis/ observed output. We apply the same for future under RCP scenarios. We observe spatially and temporally varying global change of wind energy density. The underlying assumption is that the regression relationship will also hold good for future. The results highlight the needs to change the design standards of wind mills at different locations, considering climate change and at the same time the requirement of height modifications for existing mills to produce same energy in future.

Steroids in house sparrows (Passer domesticus): Effects of POPs and male quality signalling.

PubMed

Nossen, Ida; Ciesielski, Tomasz M; Dimmen, Malene V; Jensen, Henrik; Ringsby, Thor Harald; Polder, Anuschka; Rønning, Bernt; Jenssen, Bjørn M; Styrishave, Bjarne

2016-03-15

At high trophic levels, environmental contaminants have been found to affect endocrinological processes. Less attention has been paid to species at lower trophic levels. The house sparrow (Passer domesticus) may be a useful model for investigating effects of POPs in mid-range trophic level species. In male house sparrows, ornamental traits involved in male quality signalling are important for female selection. These traits are governed by endocrinological systems, and POPs may therefore interfere with male quality signalling. The aim of the present study was to use the house sparrow as a mid-range trophic level model species to study the effects of environmental contaminants on endocrinology and male quality signalling. We analysed the levels of selected PCBs, PBDEs and OCPs and investigated the possible effects of these contaminants on circulating levels of steroid hormones (4 progestagens, 4 androgens and 3 estrogens) in male and female adult house sparrows from a population on the island Leka, Norway. Plasma samples were analysed for steroid hormones by GC-MS and liver samples were analysed for environmental contaminants by GC-ECD and GC-MS. In males, we also quantified ornament traits. It was hypothesised that POPs may have endocrine disrupting effects on the local house sparrow population and can thus interfere with the steroid hormone homeostasis. Among female house sparrows, bivariate correlations revealed negative relationships between POPs and estrogens. Among male sparrows, positive relationships between dihydrotestosterone levels and PCBs were observed. In males, positive relationships were also found between steroids and beak length, and between steroids and ornamental traits such as total badge size. This was confirmed by a significant OPLS model between beak length and steroids. Although sparrows are in the mid-range trophic levels, the present study indicates that POPs may affect steroid homeostasis in house sparrows, in particular for females. For males, circulating steroid levels appears to be more associated with biometric parameters related to ornamental traits. Copyright © 2015 Elsevier B.V. All rights reserved.

Martian atmospheric gravity waves simulated by a high-resolution general circulation model

NASA Astrophysics Data System (ADS)

Kuroda, Takeshi; Yiǧit, Erdal; Medvedev, Alexander S.; Hartogh, Paul

2016-07-01

Gravity waves (GWs) significantly affect temperature and wind fields in the Martian middle and upper atmosphere. They are also one of the observational targets of the MAVEN mission. We report on the first simulations with a high-resolution general circulation model (GCM) and present a global distributions of small-scale GWs in the Martian atmosphere. The simulated GW-induced temperature variances are in a good agreement with available radio occultation data in the lower atmosphere between 10 and 30 km. For the northern winter solstice, the model reveals a latitudinal asymmetry with stronger wave generation in the winter hemisphere and two distinctive sources of GWs: mountainous regions and the meandering winter polar jet. Orographic GWs are filtered upon propagating upward, and the mesosphere is primarily dominated by harmonics with faster horizontal phase velocities. Wave fluxes are directed mainly against the local wind. GW dissipation in the upper mesosphere generates a body force per unit mass of tens of m s^{-1} per Martian solar day (sol^{-1}), which tends to close the simulated jets. The results represent a realistic surrogate for missing observations, which can be used for constraining GW parameterizations and validating GCMs.

Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

USGS Publications Warehouse

Bucklin, David N.; Watling, James I.; Speroterra, Carolina; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

2013-01-01

High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

Daily Reservoir Inflow Forecasting using Deep Learning with Downscaled Multi-General Circulation Models (GCMs) Platform

NASA Astrophysics Data System (ADS)

Li, D.; Fang, N. Z.

2017-12-01

Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

NASA Astrophysics Data System (ADS)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2017-10-01

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

On testing two major cumulus parameterization schemes using the CSU Regional Atmospheric Modeling System

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

Kao, C.Y.J.; Bossert, J.E.; Winterkamp, J.

1993-10-01

One of the objectives of the DOE ARM Program is to improve the parameterization of clouds in general circulation models (GCMs). The approach taken in this research is two fold. We first examine the behavior of cumulus parameterization schemes by comparing their performance against the results from explicit cloud simulations with state-of-the-art microphysics. This is conducted in a two-dimensional (2-D) configuration of an idealized convective system. We then apply the cumulus parameterization schemes to realistic three-dimensional (3-D) simulations over the western US for a case with an enormous amount of convection in an extended period of five days. In themore » 2-D idealized tests, cloud effects are parameterized in the ``parameterization cases`` with a coarse resolution, whereas each cloud is explicitly resolved by the ``microphysics cases`` with a much finer resolution. Thus, the capability of the parameterization schemes in reproducing the growth and life cycle of a convective system can then be evaluated. These 2-D tests will form the basis for further 3-D realistic simulations which have the model resolution equivalent to that of the next generation of GCMs. Two cumulus parameterizations are used in this research: the Arakawa-Schubert (A-S) scheme (Arakawa and Schubert, 1974) used in Kao and Ogura (1987) and the Kuo scheme (Kuo, 1974) used in Tremback (1990). The numerical model used in this research is the Regional Atmospheric Modeling System (RAMS) developed at Colorado State University (CSU).« less

Simulating Eastern- and Central-Pacific Type ENSO Using a Simple Coupled Model

NASA Astrophysics Data System (ADS)

Fang, Xianghui; Zheng, Fei

2018-06-01

Severe biases exist in state-of-the-art general circulation models (GCMs) in capturing realistic central-Pacific (CP) El Niño structures. At the same time, many observational analyses have emphasized that thermocline (TH) feedback and zonal advective (ZA) feedback play dominant roles in the development of eastern-Pacific (EP) and CP El Niño-Southern Oscillation (ENSO), respectively. In this work, a simple linear air-sea coupled model, which can accurately depict the strength distribution of the TH and ZA feedbacks in the equatorial Pacific, is used to investigate these two types of El Niño. The results indicate that the model can reproduce the main characteristics of CP ENSO if the TH feedback is switched off and the ZA feedback is retained as the only positive feedback, confirming the dominant role played by ZA feedback in the development of CP ENSO. Further experiments indicate that, through a simple nonlinear control approach, many ENSO characteristics, including the existence of both CP and EP El Niño and the asymmetries between El Niño and La Niña, can be successfully captured using the simple linear air-sea coupled model. These analyses indicate that an accurate depiction of the climatological sea surface temperature distribution and the related ZA feedback, which are the subject of severe biases in GCMs, is very important in simulating a realistic CP El Niño.

Testing the sensitivity of snowpack to climatic change in a large physiographically diverse watershed

NASA Astrophysics Data System (ADS)

MacDonald, R. J.; Byrne, J. M.; Kienzle, S. W.; Sauchyn, D.

2009-12-01

Snowpack in mountain watersheds provide a large portion of fresh water for many human and ecosystem function. Given the sensitivity of snow processes to temperature, it is likely that available water from snowpack will be reduced under future climate warming. It is important to understand how mountain environments will respond to changes in climate in order to properly manage water future resources. In order to assess potential changes in mountain snowpack and subsequent effects on water supply, we use a combination of hydrometeorological and general circulation models (GCMs). This work describes the application of the GENESYS (GENerate Earth SYstems Science input) spatial hydrometeorological model in simulating potential future changes in snowpack for the North Saskatchewan River watershed, Alberta. Snowpack in the North Saskatchewan River watershed supplies fresh water for over one million people and supports a wide range of ecosystem processes. To assess how snowpack may change in the watershed, scenarios from five GCMs are applied by perturbing the 1961-90 time series with mean changes in temperature and precipitation for the 2010-39, 2040-69 and 2070-99 periods. This study demonstrates that snowpack in the North Saskatchewan River watershed is highly susceptible to climate change and adaptive management strategies should be implemented to ensure sustainable water resources in the region.

Marli: Mars Lidar for Global Wind Profiles and Aerosol Profiles from Orbit

NASA Technical Reports Server (NTRS)

Abshire, J. B.; Guzewich, S. D.; Smith, M. D.; Riris, H.; Sun, X.; Gentry, B. M.; Yu, A.; Allan, G. R.

2016-01-01

The Mars Exploration Analysis Group's Next Orbiter Science Analysis Group (NEXSAG) has recently identified atmospheric wind measurements as one of 5 top compelling science objectives for a future Mars orbiter. To date, only isolated lander observations of martian winds exist. Winds are the key variable to understand atmospheric transport and answer fundamental questions about the three primary cycles of the martian climate: CO2, H2O, and dust. However, the direct lack of observations and imprecise and indirect inferences from temperature observations leave many basic questions about the atmospheric circulation unanswered. In addition to addressing high priority science questions, direct wind observations from orbit would help validate 3D general circulation models (GCMs) while also providing key input to atmospheric reanalyses. The dust and CO2 cycles on Mars are partially coupled and their influences on the atmospheric circulation modify the global wind field. Dust absorbs solar infrared radiation and its variable spatial distribution forces changes in the atmospheric temperature and wind fields. Thus it is important to simultaneously measure the height-resolved wind and dust profiles. MARLI provides a unique capability to observe these variables continuously, day and night, from orbit.

[Study on material basis of essential oil from Yin Teng Gu Bi Kang prescription on activating blood circulation].

PubMed

Wang, Yuan-Qing; Yan, Jian-Ye; Gong, Li-Min; Luo, Kun; Li, Shun-Xiang; Yang, Yan-Tao; Xie, Yu

2014-08-01

To explore the component difference of the serum containing essential oil from Yin Teng Gu Bi Kang prescription in pathologic and physiologic rat models, and to reveal the material basis of its efficacy of activating blood circulation. The essential oils were obtained by CO2 supercritical fluid extraction and the ingredients of the essential oils in vitro and in vivo (under physiological and pathological status) were analyzed by GC-MS to compare differences of the essential oil under physiological and pathological status in rats. 32 components were identified with the main components of Z-ligustilide (39.23%) and d-limonene (21.7%) in the essential oil. In vivo analysis on the essential oil indicated that 16 components were identified, 7 existed originally in essential oil and 9 were metabolites under physiological status; while 22 components were identified, 10 existed originally in essential oil and 12 were metabolites under pathological status (acute blood stasis). There were 7 common prototypes and 8 common metabolites under different physiological status. The absorption and metabolism of essential oils were affected by blood stasis and the compounds migrating to blood may be the effective substance in activating blood circulation.

Sensitivity of Climate Simulations to Land-Surface and Atmospheric Boundary-Layer Treatments-A Review.

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1993-03-01

Aspects of the land-surface and boundary-layer treatments in some 20 or so atmospheric general circulation models (GCMS) are summarized. In only a small fraction of these have significant sensitivity studies been carried out and published. Predominantly, the sensitivity studies focus upon the parameterization of land-surface processes and specification of land-surface properties-the most important of these include albedo, roughness length, soil moisture status, and vegetation density. The impacts of surface albedo and soil moisture upon the climate simulated in GCMs with bare-soil land surfaces are well known. Continental evaporation and precipitation tend to decrease with increased albedo and decreased soil moisture availability. For example, results from numerous studies give an average decrease in continental precipitation of 1 mm day1 in response to an average albedo increase of 0.13. Few conclusive studies have been carried out on the impact of a gross roughness-length change-the primary study included an important statistical assessment of the impact upon the mean July climate around the globe of a decreased continental roughness (by three orders of magnitude). For example, such a decrease reduced the precipitation over Amazonia by 1 to 2 mm day1.The inclusion of a canopy scheme in a GCM ensures the combined impacts of roughness (canopies tend to be rougher than bare soil), albedo (canopies tend to be less reflective than bare soil), and soil-moisture availability (canopies prevent the near-surface soil region from drying out and can access the deep soil moisture) upon the simulated climate. The most revealing studies to date involve the regional impact of Amazonian deforestation. The results of four such studies show that replacing tropical forest with a degraded pasture results in decreased evaporation ( 1 mm day1) and precipitation (1-2 mm day1), and increased near-surface air temperatures (2 K).Sensitivity studies as a whole suggest the need for a realistic surface representation in general circulation models of the atmosphere. It is not yet clear how detailed this representation needs to be, but even allowing for the importance of surface processes, the parameterization of boundary-layer and convective clouds probably represents a greater challenge to improved climate simulations. This is illustrated in the case of surface net radiation for Aniazonia, which is not well simulated and tends to be overestimated, leading to evaporation rates that are too large. Underestimates in cloudiness, cloud albedo, and clear-sky shortwave absorption, rather than in surface albedo, appear to be the main culprits.There are three major tasks that confront the researcher so far as the development and validation of atmospheric boundary-layer (ABL) and surface schemes in GCMs are concerned:(i) There is a need to as' critically the impact of `improved' parameterization schemes on WM simulations, taking into account the problem of natural variability and hence the statistical significance of the induced changes.(ii) There is a need to compare GCM simulations of surface and ABL behavior (particularly regarding the diurnal cycle of surface fluxes, air temperature, and ABL depth) with observations over a range of surface types (vegetation, desert, ocean). In this context, area-average values of surface fluxes will be required to calibrate directly the ABL/land-surface scheme in the GCM.(iii) There is a need for intercomparisons of ABL and land-surface schemes used in GCMS, both for one- dimensional stand-alone models and for GCMs that incorporate the respective schemes.

Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature

NASA Astrophysics Data System (ADS)

Hassan, Zulkarnain; Shamsudin, Supiah; Harun, Sobri

2014-04-01

Climate change is believed to have significant impacts on the water basin and region, such as in a runoff and hydrological system. However, impact studies on the water basin and region are difficult, since general circulation models (GCMs), which are widely used to simulate future climate scenarios, do not provide reliable hours of daily series rainfall and temperature for hydrological modeling. There is a technique named as "downscaling techniques", which can derive reliable hour of daily series rainfall and temperature due to climate scenarios from the GCMs output. In this study, statistical downscaling models are used to generate the possible future values of local meteorological variables such as rainfall and temperature in the selected stations in Peninsular of Malaysia. The models are: (1) statistical downscaling model (SDSM) that utilized the regression models and stochastic weather generators and (2) Long Ashton research station weather generator (LARS-WG) that only utilized the stochastic weather generators. The LARS-WG and SDSM models obviously are feasible methods to be used as tools in quantifying effects of climate change condition in a local scale. SDSM yields a better performance compared to LARS-WG, except SDSM is slightly underestimated for the wet and dry spell lengths. Although both models do not provide identical results, the time series generated by both methods indicate a general increasing trend in the mean daily temperature values. Meanwhile, the trend of the daily rainfall is not similar to each other, with SDSM giving a relatively higher change of annual rainfall compared to LARS-WG.

Modeling impacts of climate change on freshwater availability in Africa

NASA Astrophysics Data System (ADS)

Faramarzi, Monireh; Abbaspour, Karim C.; Ashraf Vaghefi, Saeid; Farzaneh, Mohammad Reza; Zehnder, Alexander J. B.; Srinivasan, Raghavan; Yang, Hong

2013-02-01

SummaryThis study analyzes the impact of climate change on freshwater availability in Africa at the subbasin level for the period of 2020-2040. Future climate projections from five global circulation models (GCMs) under the four IPCC emission scenarios were fed into an existing SWAT hydrological model to project the impact on different components of water resources across the African continent. The GCMs have been downscaled based on observed data of Climate Research Unit to represent local climate conditions at 0.5° grid spatial resolution. The results show that for Africa as a whole, the mean total quantity of water resources is likely to increase. For individual subbasins and countries, variations are substantial. Although uncertainties are high in the simulated results, we found that in many regions/countries, most of the climate scenarios projected the same direction of changes in water resources, suggesting a relatively high confidence in the projections. The assessment of the number of dry days and the frequency of their occurrences suggests an increase in the drought events and their duration in the future. Overall, the dry regions have higher uncertainties than the wet regions in the projected impacts on water resources. This poses additional challenge to the agriculture in dry regions where water shortage is already severe while irrigation is expected to become more important to stabilize and increase food production.

Shortwave and longwave radiative contributions to global warming under increasing CO2.

PubMed

Donohoe, Aaron; Armour, Kyle C; Pendergrass, Angeline G; Battisti, David S

2014-11-25

In response to increasing concentrations of atmospheric CO2, high-end general circulation models (GCMs) simulate an accumulation of energy at the top of the atmosphere not through a reduction in outgoing longwave radiation (OLR)—as one might expect from greenhouse gas forcing—but through an enhancement of net absorbed solar radiation (ASR). A simple linear radiative feedback framework is used to explain this counterintuitive behavior. It is found that the timescale over which OLR returns to its initial value after a CO2 perturbation depends sensitively on the magnitude of shortwave (SW) feedbacks. If SW feedbacks are sufficiently positive, OLR recovers within merely several decades, and any subsequent global energy accumulation is because of enhanced ASR only. In the GCM mean, this OLR recovery timescale is only 20 y because of robust SW water vapor and surface albedo feedbacks. However, a large spread in the net SW feedback across models (because of clouds) produces a range of OLR responses; in those few models with a weak SW feedback, OLR takes centuries to recover, and energy accumulation is dominated by reduced OLR. Observational constraints of radiative feedbacks—from satellite radiation and surface temperature data—suggest an OLR recovery timescale of decades or less, consistent with the majority of GCMs. Altogether, these results suggest that, although greenhouse gas forcing predominantly acts to reduce OLR, the resulting global warming is likely caused by enhanced ASR.

On the Climate Impacts of Upper Tropospheric and Lower Stratospheric Ozone

NASA Astrophysics Data System (ADS)

Xia, Yan; Huang, Yi; Hu, Yongyun

2018-01-01

The global warming simulations of the general circulation models (GCMs) are generally performed with different ozone prescriptions. We find that the differences in ozone distribution, especially in the upper tropospheric and lower stratospheric (UTLS) region, account for important model discrepancies shown in the ozone-only historical experiment of the Coupled Model Intercomparison Project Phase 5 (CMIP5). These discrepancies include global high cloud fraction, stratospheric temperature, and stratospheric water vapor. Through a set of experiments conducted by an atmospheric GCM with contrasting UTLS ozone prescriptions, we verify that UTLS ozone not only directly radiatively heats the UTLS region and cools the upper parts of the stratosphere but also strongly influences the high clouds due to its impact on relative humidity and static stability in the UTLS region and the stratospheric water vapor due to its impact on the tropical tropopause temperature. These consequences strongly affect the global mean effective radiative forcing of ozone, as noted in previous studies. Our findings suggest that special attention should be paid to the UTLS ozone when evaluating the climate effects of ozone depletion in the 20th century and recovery in the 21st century. UTLS ozone difference may also be important for understanding the intermodel discrepancy in the climate projections of the CMIP6 GCMs in which either prescribed or interactive ozone is used.

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

DOE PAGES

Baker, I. T.; Sellers, P. J.; Denning, A. S.; ...

2017-03-01

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

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

Baker, I. T.; Sellers, P. J.; Denning, A. S.

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

Simulation of seasonal cloud forcing anomalies

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

Randall, D.A.

1990-08-01

One useful way to classify clouds is according to the processes that generate them. There are three main cloud-formation agencies: deep convection; surface evaporation; large-scale lifting in the absence of conditional instability. Although traditionally clouds have been viewed as influencing the atmospheric general circulation primarily through the release of latent heat, the atmospheric science literature contains abundant evidence that, in reality, clouds influence the general circulation through four more or less equally important effects: interactions with the solar and terrestrial radiation fields; condensation and evaporation; precipitation; small-scale circulations within the atmosphere. The most advanced of the current generation of GCMsmore » include parameterizations of all four effects. Until recently there has been lingering skepticism, in the general circulation modeling community, that the radiative effects of clouds significantly influence the atmospheric general circulation. GCMs have provided the proof that the radiative effects of clouds are important for the general circulation of the atmosphere. An important concept in analysis of the effects of clouds on climate is the cloud radiative forcing (CRF), which is defined as the difference between the radiative flux which actually occurs in the presence of clouds, and that which would occur if the clouds were removed but the atmospheric state were otherwise unchanged. We also use the term CRF to denote warming or cooling tendencies due to cloud-radiation interactions. Cloud feedback is the change in CRF that accompanies a climate change. The present study concentrates on the planetary CRF and its response to external forcing, i.e. seasonal change.« less

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

NASA Astrophysics Data System (ADS)

Raje, Deepashree; Mujumdar, P. P.

2010-09-01

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change.

COSP: Satellite simulation software for model assessment

DOE PAGES

Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...

2011-08-01

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less

European climate change at global mean temperature increases of 1.5 and 2 °C above pre-industrial conditions as simulated by the EURO-CORDEX regional climate models

NASA Astrophysics Data System (ADS)

Kjellström, Erik; Nikulin, Grigory; Strandberg, Gustav; Bøssing Christensen, Ole; Jacob, Daniela; Keuler, Klaus; Lenderink, Geert; van Meijgaard, Erik; Schär, Christoph; Somot, Samuel; Sørland, Silje Lund; Teichmann, Claas; Vautard, Robert

2018-05-01

We investigate European regional climate change for time periods when the global mean temperature has increased by 1.5 and 2 °C compared to pre-industrial conditions. Results are based on regional downscaling of transient climate change simulations for the 21st century with global climate models (GCMs) from the fifth-phase Coupled Model Intercomparison Project (CMIP5). We use an ensemble of EURO-CORDEX high-resolution regional climate model (RCM) simulations undertaken at a computational grid of 12.5 km horizontal resolution covering Europe. The ensemble consists of a range of RCMs that have been used for downscaling different GCMs under the RCP8.5 forcing scenario. The results indicate considerable near-surface warming already at the lower 1.5 °C of warming. Regional warming exceeds that of the global mean in most parts of Europe, being the strongest in the northernmost parts of Europe in winter and in the southernmost parts of Europe together with parts of Scandinavia in summer. Changes in precipitation, which are less robust than the ones in temperature, include increases in the north and decreases in the south with a borderline that migrates from a northerly position in summer to a southerly one in winter. Some of these changes are already seen at 1.5 °C of warming but are larger and more robust at 2 °C. Changes in near-surface wind speed are associated with a large spread among individual ensemble members at both warming levels. Relatively large areas over the North Atlantic and some parts of the continent show decreasing wind speed while some ocean areas in the far north show increasing wind speed. The changes in temperature, precipitation and wind speed are shown to be modified by changes in mean sea level pressure, indicating a strong relationship with the large-scale circulation and its internal variability on decade-long timescales. By comparing to a larger ensemble of CMIP5 GCMs we find that the RCMs can alter the results, leading either to attenuation or amplification of the climate change signal in the underlying GCMs. We find that the RCMs tend to produce less warming and more precipitation (or less drying) in many areas in both winter and summer.

Vertical structure and physical processes of the Madden-Julian oscillation: Exploring key model physics in climate simulations

DOE PAGES

Jiang, Xianan; Waliser, Duane E.; Xavier, Prince K.; ...

2015-05-27

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. Here, it is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but notmore » in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high- and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Finally, results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO.« less

A multi-scale methodology for comparing GCM and RCM results over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Samuels, Rana; Krichak, Simon; Breitgand, Joseph; Alpert, Pinhas

2010-05-01

The importance of skillful climate modeling is increasingly being realized as results are being incorporated into environmental, economic, and even business planning. Global circulation models (GCMs) employed by the IPCC provide results at spatial scales of hundreds of kilometers, which is useful for understanding global trends but not appropriate for use as input into regional and local impacts models used to inform policy and development. To address this shortcoming, regional climate models (RCMs) which dynamically downscale the results of the GCMs are used. In this study we present first results of a dynamically downscaled RCM focusing on the Eastern Mediterranean region. For the historical 1960-2000 time period, results at a spatial scale of both 25 km and 50 km are compared with historical station data from 5 locations across Israel as well as with the results of 3 GCM models (ECHAM5, NOAA GFDL, and CCCMA) at annual, monthly and daily time scales. Results from a recently completed Japanese GCM at a spatial scale of 20 km are also included. For the historical validation period, we show that as spatial scale increases the skill in capturing annual and inter-annual temperature and rainfall also increases. However, for intra-seasonal rainfall characteristics important for hydrological and agricultural planning (eg. dry and wet spells, number of rain days) the GCM results (including the 20 km Japanese model) capture the historical trends better than the dynamically downscaled RegCM. For future scenarios of temperature and precipitation changes, we compare results across the models for the available time periods, generating a range of future trends.

Is Polar Amplification Deeper and Stronger than Dynamicists Assume?

NASA Astrophysics Data System (ADS)

Scheff, J.; Maroon, E.

2017-12-01

In the CMIP multi-model mean under strong future warming, Arctic amplification is confined to the lower troposphere, so that the meridional gradient of warming reverses around 500 mb and the upper troposphere is characterized by strong "tropical amplification" in which warming weakens with increasing latitude. This model-derived pattern of warming maxima in the upper-level tropics and lower-level Arctic has become a canonical assumption driving theories of the large-scale circulation response to climate change. Yet, several lines of evidence and reasoning suggest that Arctic amplification may in fact extend through the entire depth of the troposphere, and/or may be stronger than commonly modeled. These include satellite Microwave Sounding Unit (MSU) temperature trends as a function of latitude and vertical level, the recent discovery that the extratropical negative cloud phase feedback in models is largely spurious, and the very strong polar amplification observed in past warm and lukewarm climates. Such a warming pattern, with deep, dominant Arctic amplification, would have very different implications for the circulation than a canonical CMIP-like warming: instead of slightly shifting poleward and strengthening, eddies, jets and cells might shift equatorward and considerably weaken. Indeed, surface winds have been mysteriously weakening ("stilling") at almost all stations over the last half-century or so, there has been no poleward shift in northern hemisphere circulation metrics, and past warm climates' subtropics were apparently quite wet (and their global ocean circulations were weak.) To explore these possibilities more deeply, we examine the y-z structure of warming and circulation changes across a much broader range of models, scenarios and time periods than the CMIP future mean, and use an MSU simulator to compare them to the satellite warming record. Specifically, we examine whether the use of historical (rather than future) forcing, AMIP (rather than CMIP) configuration, individual GCMs, and/or individual ensemble members can better reproduce the structure of the MSU and surface-wind observations. Figure 1 already shows that tropical amplification is absent in the CESM1 historical ensemble (1979-2012). The results of these analyses will guide our future modeling work on these topics.

Geothermal heating enhances atmospheric asymmetries on synchronously rotating planets

NASA Astrophysics Data System (ADS)

Haqq-Misra, Jacob; Kopparapu, Ravi Kumar

2015-01-01

Earth-like planets within the liquid water habitable zone of M-type stars may evolve into synchronous rotators. On these planets, the substellar hemisphere experiences perpetual daylight while the opposing antistellar hemisphere experiences perpetual darkness. Because the night-side hemisphere has no direct source of energy, the air over this side of the planet is prone to freeze out and deposit on the surface, which could result in atmospheric collapse. However, general circulation models (GCMs) have shown that atmospheric dynamics can counteract this problem and provide sufficient energy transport to the antistellar side. Here, we use an idealized GCM to consider the impact of geothermal heating on the habitability of synchronously rotating planets. Geothermal heating may be expected due to tidal interactions with the host star, and the effects of geothermal heating provide additional habitable surface area and may help to induce melting of ice on the antistellar hemisphere. We also explore the persistence of atmospheric asymmetries between the Northern and Southern hemispheres, and we find that the direction of the meridional circulation (for rapidly rotating planets) or the direction of zonal wind (for slowly rotating planets) reverses on either side of the substellar point. We show that the zonal circulation approaches a theoretical state similar to a Walker circulation only for slowly rotating planets, while rapidly rotating planets show a zonal circulation with the opposite direction. We find that a cross-polar circulation is present in all cases and provides an additional mechanism of mass and energy transport from the substellar to antistellar point. Characterization of the atmospheres of synchronously rotating planets should include consideration of hemispheric differences in meridional circulation and examination of transport due to cross-polar flow.

Three dimensional adaptive mesh refinement on a spherical shell for atmospheric models with lagrangian coordinates

NASA Astrophysics Data System (ADS)

Penner, Joyce E.; Andronova, Natalia; Oehmke, Robert C.; Brown, Jonathan; Stout, Quentin F.; Jablonowski, Christiane; van Leer, Bram; Powell, Kenneth G.; Herzog, Michael

2007-07-01

One of the most important advances needed in global climate models is the development of atmospheric General Circulation Models (GCMs) that can reliably treat convection. Such GCMs require high resolution in local convectively active regions, both in the horizontal and vertical directions. During previous research we have developed an Adaptive Mesh Refinement (AMR) dynamical core that can adapt its grid resolution horizontally. Our approach utilizes a finite volume numerical representation of the partial differential equations with floating Lagrangian vertical coordinates and requires resolving dynamical processes on small spatial scales. For the latter it uses a newly developed general-purpose library, which facilitates 3D block-structured AMR on spherical grids. The library manages neighbor information as the blocks adapt, and handles the parallel communication and load balancing, freeing the user to concentrate on the scientific modeling aspects of their code. In particular, this library defines and manages adaptive blocks on the sphere, provides user interfaces for interpolation routines and supports the communication and load-balancing aspects for parallel applications. We have successfully tested the library in a 2-D (longitude-latitude) implementation. During the past year, we have extended the library to treat adaptive mesh refinement in the vertical direction. Preliminary results are discussed. This research project is characterized by an interdisciplinary approach involving atmospheric science, computer science and mathematical/numerical aspects. The work is done in close collaboration between the Atmospheric Science, Computer Science and Aerospace Engineering Departments at the University of Michigan and NOAA GFDL.

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

NASA Technical Reports Server (NTRS)

Wang, Hui; Long, Lindsey; Kumar, Arun; Wang, Wanqiu; Schemm, Jae-Kyung E.; Zhao, Ming; Vecchi, Gabriel A.; LaRow, Timorhy E.; Lim, Young-Kwon; Schubert, Siegfried D.;

A new paradigm for predicting zonal-mean climate and climate change

NASA Astrophysics Data System (ADS)

Armour, K.; Roe, G.; Donohoe, A.; Siler, N.; Markle, B. R.; Liu, X.; Feldl, N.; Battisti, D. S.; Frierson, D. M.

2016-12-01

How will the pole-to-equator temperature gradient, or large-scale patterns of precipitation, change under global warming? Answering such questions typically involves numerical simulations with comprehensive general circulation models (GCMs) that represent the complexities of climate forcing, radiative feedbacks, and atmosphere and ocean dynamics. Yet, our understanding of these predictions hinges on our ability to explain them through the lens of simple models and physical theories. Here we present evidence that zonal-mean climate, and its changes, can be understood in terms of a moist energy balance model that represents atmospheric heat transport as a simple diffusion of latent and sensible heat (as a down-gradient transport of moist static energy, with a diffusivity coefficient that is nearly constant with latitude). We show that the theoretical underpinnings of this model derive from the principle of maximum entropy production; that its predictions are empirically supported by atmospheric reanalyses; and that it successfully predicts the behavior of a hierarchy of climate models - from a gray radiation aquaplanet moist GCM, to comprehensive GCMs participating in CMIP5. As an example of the power of this paradigm, we show that, given only patterns of local radiative feedbacks and climate forcing, the moist energy balance model accurately predicts the evolution of zonal-mean temperature and atmospheric heat transport as simulated by the CMIP5 ensemble. These results suggest that, despite all of its dynamical complexity, the atmosphere essentially responds to energy imbalances by simply diffusing latent and sensible heat down-gradient; this principle appears to explain zonal-mean climate and its changes under global warming.

Evaluating Vertical Moisture Structure of the Madden-Julian Oscillation in Contemporary GCMs

NASA Astrophysics Data System (ADS)

Guan, B.; Jiang, X.; Waliser, D. E.

2013-12-01

The Madden-Julian Oscillation (MJO) remains a major challenge in our understanding and modeling of the tropical convection and circulation. Many models have troubles in realistically simulating key characteristics of the MJO, such as the strength, period, and eastward propagation. For models that do simulate aspects of the MJO, it remains to be understood what parameters and processes are the most critical in determining the quality of the simulations. This study focuses on the vertical structure of moisture in MJO simulations, with the aim to identify and understand the relationship between MJO simulation qualities and key parameters related to moisture. A series of 20-year simulations conducted by 26 GCMs are analyzed, including four that are coupled to ocean models and two that have a two-dimensional cloud resolving model embedded (i.e., superparameterized). TRMM precipitation and ERA-Interim reanalysis are used to evaluate the model simulations. MJO simulation qualities are evaluated based on pattern correlations of lead/lag regressions of precipitation - a measure of the model representation of the eastward propagating MJO convection. Models with strongest and weakest MJOs (top and bottom quartiles) are compared in terms of differences in moisture content, moisture convergence, moistening rate, and moist static energy. It is found that models with strongest MJOs have better representations of the observed vertical tilt of moisture. Relative importance of convection, advection, boundary layer, and large scale convection/precipitation are discussed in terms of their contribution to the moistening process. The results highlight the overall importance of vertical moisture structure in MJO simulations. The work contributes to the climatological component of the joint WCRP-WWRP/THORPEX YOTC MJO Task Force and the GEWEX Atmosphere System Study (GASS) global model evaluation project focused on the vertical structure and diabatic processes of the MJO.

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.

CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

NASA Astrophysics Data System (ADS)

Li, Laifang; Li, Wenhong; Ballard, Tristan; Sun, Ge; Jeuland, Marc

2016-05-01

Kiremt-season (June-September) precipitation provides a significant water supply for Ethiopia, particularly in the central and northern regions. The response of Kiremt-season precipitation to climate change is thus of great concern to water resource managers. However, the complex processes that control Kiremt-season precipitation challenge the capability of general circulation models (GCMs) to accurately simulate precipitation amount and variability. This in turn raises questions about their utility for predicting future changes. This study assesses the impact of climate change on Kiremt-season precipitation using state-of-the-art GCMs participating in the Coupled Model Intercomparison Project Phase 5. Compared to models with a coarse resolution, high-resolution models (horizontal resolution <2°) can more accurately simulate precipitation, most likely due to their ability to capture precipitation induced by topography. Under the Representative Concentration Pathway (RCP) 4.5 scenario, these high-resolution models project an increase in precipitation over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 105 m2 s-2) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The influence of the NASH on Kiremt-season precipitation becomes more evident in the future due to the offsetting effects of two other major circulation systems: the East African Low-level Jet (EALLJ) and the Tropical Easterly Jet (TEJ). The high-resolution models project a strengthening of the EALLJ, but a weakening of the TEJ. Future changes in the EALLJ and TEJ will drive this precipitation system in opposite directions, leading to small or no net changes in precipitation in Ethiopia.

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).

Can Aerosol Direct Radiative Effects Account for Analysis Increments of Temperature in the Tropical Atlantic?

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Alpert, Pinhas

2016-01-01

In the late 1990's, prior to the launch of the Terra satellite, atmospheric general circulation models (GCMs) did not include aerosol processes because aerosols were not properly monitored on a global scale and their spatial distributions were not known well enough for their incorporation in operational GCMs. At the time of the first GEOS Reanalysis (Schubert et al. 1993), long time series of analysis increments (the corrections to the atmospheric state by all available meteorological observations) became readily available, enabling detailed analysis of the GEOS-1 errors on a global scale. Such analysis revealed that temperature biases were particularly pronounced in the Tropical Atlantic region, with patterns depicting a remarkable similarity to dust plumes emanating from the African continent as evidenced by TOMS aerosol index maps. Yoram Kaufman was instrumental encouraging us to pursue this issue further, resulting in the study reported in Alpert et al. (1998) where we attempted to assess aerosol forcing by studying the errors of a the GEOS-1 GCM without aerosol physics within a data assimilation system. Based on this analysis, Alpert et al. (1998) put forward that dust aerosols are an important source of inaccuracies in numerical weather-prediction models in the Tropical Atlantic region, although a direct verification of this hypothesis was not possible back then. Nearly 20 years later, numerical prediction models have increased in resolution and complexity of physical parameterizations, including the representation of aerosols and their interactions with the circulation. Moreover, with the advent of NASA's EOS program and subsequent satellites, atmospheric aerosols are now monitored globally on a routine basis, and their assimilation in global models are becoming well established. In this talk we will reexamine the Alpert et al. (1998) hypothesis using the most recent version of the GEOS-5 Data Assimilation System with assimilation of aerosols. We will explicitly calculate the impact of aerosols on the temperature analysis increments in the tropical Atlantic and assess the extent to which inclusion of atmospheric aerosols have reduced these increments.

Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.

2016-12-01

Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of representations of large-scale moisture transport, cloud microphysics, ice nucleation, and cumulus detrainment in order to improve the mixed-phase transition in GCMs.

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

Diagnostic Evaluation of Nmme Precipitation and Temperature Forecasts for the Continental United States

NASA Astrophysics Data System (ADS)

Karlovits, G. S.; Villarini, G.; Bradley, A.; Vecchi, G. A.

2014-12-01

Forecasts of seasonal precipitation and temperature can provide information in advance of potentially costly disruptions caused by flood and drought conditions. The consequences of these adverse hydrometeorological conditions may be mitigated through informed planning and response, given useful and skillful forecasts of these conditions. However, the potential value and applicability of these forecasts is unavoidably linked to their forecast quality. In this work we evaluate the skill of four global circulation models (GCMs) part of the North American Multi-Model Ensemble (NMME) project in forecasting seasonal precipitation and temperature over the continental United States. The GCMs we consider are the Geophysical Fluid Dynamics Laboratory (GFDL)-CM2.1, NASA Global Modeling and Assimilation Office (NASA-GMAO)-GEOS-5, The Center for Ocean-Land-Atmosphere Studies - Rosenstiel School of Marine & Atmospheric Science (COLA-RSMAS)-CCSM3, Canadian Centre for Climate Modeling and Analysis (CCCma) - CanCM4. These models are available at a resolution of 1-degree and monthly, with a minimum forecast lead time of nine months, up to one year. These model ensembles are compared against gridded monthly temperature and precipitation data created by the PRISM Climate Group, which represent the reference observation dataset in this work. Aspects of forecast quality are quantified using a diagnostic skill score decomposition that allows the evaluation of the potential skill and conditional and unconditional biases associated with these forecasts. The evaluation of the decomposed GCM forecast skill over the continental United States, by season and by lead time allows for a better understanding of the utility of these models for flood and drought predictions. Moreover, it also represents a diagnostic tool that could provide model developers feedback about strengths and weaknesses of their models.

The tropopause inversion layer in models and analyses

NASA Astrophysics Data System (ADS)

Birner, T.; Sankey, D.; Shepherd, T. G.

2006-07-01

Recent high-resolution radiosonde climatologies have revealed a tropopause inversion layer (TIL) in the extratropics: temperature strongly increases just above a sharp local cold point tropopause. Here, it is asked to what extent a TIL exists in current general circulation models (GCMs) and meteorological analyses. Only a weak hint of a TIL exists in NCEP/NCAR reanalysis data. In contrast, the Canadian Middle Atmosphere Model (CMAM), a comprehensive GCM, exhibits a TIL of realistic strength. However, in data assimilation mode CMAM exhibits a much weaker TIL, especially in the Southern Hemisphere where only coarse satellite data are available. The discrepancy between the analyses and the GCM is thus hypothesized to be mainly due to data assimilation acting to smooth the observed strong curvature in temperature around the tropopause. This is confirmed in the reanalysis where the stratification around the tropopause exhibits a strong discontinuity at the start of the satellite era.

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

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

Xu, Kuan-Man; Cheng, Anning

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation andmore » stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.« less

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

DOE PAGES

Xu, Kuan-Man; Cheng, Anning

2016-11-15

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation andmore » stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.« less

Quasi-biennial oscillations of ozone and diabatic circulation in the equatorial stratosphere

NASA Technical Reports Server (NTRS)

Hasebe, Fumio

1994-01-01

The quasi-biennial oscillation (QBO) in ozone in the equatorial stratosphere is obtained by analyzing the Stratospheric Aerosol and Gas Experiment (SAGE) data from 1984 to 1989. The phase of the ozone QBO in the lower stratosphere is found to precede the zonal wind QBO by several months as opposed to the theoretically expected in-phase relationship between the two. A mechanistic model is developed to explore possible reasons for this disagreement. The model is capable of simulating the actual time evolution of the ozone QBO by introducing the observed zonal wind profile as input. The modeled results confirm the conventional view that the ozone QBO is generated by the vertical ozone advection that is driven to maintain the temperature structure against radiative damping. However, a series of experiments emphasizes the importance of the feedback of the ozone QBO to the diabatic heating through the absorption of solar radiation. Due to this effect, the phase of the ozone QBO shifts up to a quarter cycle ahead and approaches that of the temperature QBO. Because of this inphase relationship, the feedback of the ozone QBO to the diabatic heating acts to compensate for the radiative damping of the temperature structure, thus reducing the magnitude of the induced diabatic circulation. Because the reduction of the magnitude of the vertical motion facilitates downward transport of easterly momentum by the mean flow, this feedback process can help to resolve the insufficiency of the easterly momentum in driving the dynamical QBO in general circulation models (GCMs). It should be emphasized that more sophisticated models that allow for full interaction between the chemical species and radiative and dynamical processes should be developed to improve our understanding of both dynamical and ozone QBOs.

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.

The effect of metallicity on the atmospheres of exoplanets with fully coupled 3D hydrodynamics, equilibrium chemistry, and radiative transfer

NASA Astrophysics Data System (ADS)

Drummond, B.; Mayne, N. J.; Baraffe, I.; Tremblin, P.; Manners, J.; Amundsen, D. S.; Goyal, J.; Acreman, D.

2018-05-01

In this work, we have performed a series of simulations of the atmosphere of GJ 1214b assuming different metallicities using the Met Office Unified Model (UM). The UM is a general circulation model (GCM) that solves the deep, non-hydrostatic equations of motion and uses a flexible and accurate radiative transfer scheme, based on the two-stream and correlated-k approximations, to calculate the heating rates. In this work we consistently couple a well-tested Gibbs energy minimisation scheme to solve for the chemical equilibrium abundances locally in each grid cell for a general set of elemental abundances, further improving the flexibility and accuracy of the model. As the metallicity of the atmosphere is increased we find significant changes in the dynamical and thermal structure, with subsequent implications for the simulated phase curve. The trends that we find are qualitatively consistent with previous works, though with quantitative differences. We investigate in detail the effect of increasing the metallicity by splitting the mechanism into constituents, involving the mean molecular weight, the heat capacity and the opacities. We find the opacity effect to be the dominant mechanism in altering the circulation and thermal structure. This result highlights the importance of accurately computing the opacities and radiative transfer in 3D GCMs.

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

NASA Astrophysics Data System (ADS)

van Hooidonk, R.; Huber, M.

2012-03-01

Future widespread coral bleaching and subsequent mortality has been projected using sea surface temperature (SST) data derived from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. Such weaknesses most likely reduce the accuracy of predicting coral bleaching, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends, and their propagation in predictions. To analyze the relative importance of various types of model errors and biases in predicting coral bleaching, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from 24 GCMs 20th century simulations included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate accuracy using an objective measure of forecast quality, the Peirce skill score (PSS). Major findings are that: (1) predictions are most sensitive to the seasonal cycle and inter-annual variability in the ENSO 24-60 months frequency band and (2) because models tend to understate the seasonal cycle at reef locations, they systematically underestimate future bleaching. The methodology we describe can be used to improve the accuracy of bleaching predictions by characterizing the errors and uncertainties involved in the predictions.

Multi-model ensemble projections of future extreme heat stress on rice across southern China

NASA Astrophysics Data System (ADS)

He, Liang; Cleverly, James; Wang, Bin; Jin, Ning; Mi, Chunrong; Liu, De Li; Yu, Qiang

2017-08-01

Extreme heat events have become more frequent and intense with climate warming, and these heatwaves are a threat to rice production in southern China. Projected changes in heat stress in rice provide an assessment of the potential impact on crop production and can direct measures for adaptation to climate change. In this study, we calculated heat stress indices using statistical scaling techniques, which can efficiently downscale output from general circulation models (GCMs). Data across the rice belt in southern China were obtained from 28 GCMs in the Coupled Model Intercomparison Project phase 5 (CMIP5) with two emissions scenarios (RCP4.5 for current emissions and RCP8.5 for increasing emissions). Multi-model ensemble projections over the historical period (1960-2010) reproduced the trend of observations in heat stress indices (root-mean-square error RMSE = 6.5 days) better than multi-model arithmetic mean (RMSE 8.9 days) and any individual GCM (RMSE 11.4 days). The frequency of heat stress events was projected to increase by 2061-2100 in both scenarios (up to 185 and 319% for RCP4.5 and RCP8.5, respectively), especially in the middle and lower reaches of the Yangtze River. This increasing risk of exposure to heat stress above 30 °C during flowering and grain filling is predicted to impact rice production. The results of our study suggest the importance of specific adaption or mitigation strategies, such as selection of heat-tolerant cultivars and adjustment of planting date in a warmer future world.

Predicting climate change: Uncertainties and prospects for surmounting them

NASA Astrophysics Data System (ADS)

Ghil, Michael

2008-03-01

General circulation models (GCMs) are among the most detailed and sophisticated models of natural phenomena in existence. Still, the lack of robust and efficient subgrid-scale parametrizations for GCMs, along with the inherent sensitivity to initial data and the complex nonlinearities involved, present a major and persistent obstacle to narrowing the range of estimates for end-of-century warming. Estimating future changes in the distribution of climatic extrema is even more difficult. Brute-force tuning the large number of GCM parameters does not appear to help reduce the uncertainties. Andronov and Pontryagin (1937) proposed structural stability as a way to evaluate model robustness. Unfortunately, many real-world systems proved to be structurally unstable. We illustrate these concepts with a very simple model for the El Niño--Southern Oscillation (ENSO). Our model is governed by a differential delay equation with a single delay and periodic (seasonal) forcing. Like many of its more or less detailed and realistic precursors, this model exhibits a Devil's staircase. We study the model's structural stability, describe the mechanisms of the observed instabilities, and connect our findings to ENSO phenomenology. In the model's phase-parameter space, regions of smooth dependence on parameters alternate with rough, fractal ones. We then apply the tools of random dynamical systems and stochastic structural stability to the circle map and a torus map. The effect of noise with compact support on these maps is fairly intuitive: it is the most robust structures in phase-parameter space that survive the smoothing introduced by the noise. The nature of the stochastic forcing matters, thus suggesting that certain types of stochastic parametrizations might be better than others in achieving GCM robustness. This talk represents joint work with M. Chekroun, E. Simonnet and I. Zaliapin.

Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques

NASA Astrophysics Data System (ADS)

Fenta Mekonnen, Dagnenet; Disse, Markus

2018-04-01

Climate change is becoming one of the most threatening issues for the world today in terms of its global context and its response to environmental and socioeconomic drivers. However, large uncertainties between different general circulation models (GCMs) and coarse spatial resolutions make it difficult to use the outputs of GCMs directly, especially for sustainable water management at regional scale, which introduces the need for downscaling techniques using a multimodel approach. This study aims (i) to evaluate the comparative performance of two widely used statistical downscaling techniques, namely the Long Ashton Research Station Weather Generator (LARS-WG) and the Statistical Downscaling Model (SDSM), and (ii) to downscale future climate scenarios of precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) of the Upper Blue Nile River basin at finer spatial and temporal scales to suit further hydrological impact studies. The calibration and validation result illustrates that both downscaling techniques (LARS-WG and SDSM) have shown comparable and good ability to simulate the current local climate variables. Further quantitative and qualitative comparative performance evaluation was done by equally weighted and varying weights of statistical indexes for precipitation only. The evaluation result showed that SDSM using the canESM2 CMIP5 GCM was able to reproduce more accurate long-term mean monthly precipitation but LARS-WG performed best in capturing the extreme events and distribution of daily precipitation in the whole data range. Six selected multimodel CMIP3 GCMs, namely HadCM3, GFDL-CM2.1, ECHAM5-OM, CCSM3, MRI-CGCM2.3.2 and CSIRO-MK3 GCMs, were used for downscaling climate scenarios by the LARS-WG model. The result from the ensemble mean of the six GCM showed an increasing trend for precipitation, Tmax and Tmin. The relative change in precipitation ranged from 1.0 to 14.4 % while the change for mean annual Tmax may increase from 0.4 to 4.3 °C and the change for mean annual Tmin may increase from 0.3 to 4.1 °C. The individual result of the HadCM3 GCM has a good agreement with the ensemble mean result. HadCM3 from CMIP3 using A2a and B2a scenarios and canESM2 from CMIP5 GCMs under RCP2.6, RCP4.5 and RCP8.5 scenarios were downscaled by SDSM. The result from the two GCMs under five different scenarios agrees with the increasing direction of three climate variables (precipitation, Tmax and Tmin). The relative change of the downscaled mean annual precipitation ranges from 2.1 to 43.8 % while the change for mean annual Tmax and Tmin may increase in the range from 0.4 to 2.9 °C and from 0.3 to 1.6 °C respectively.

Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa

NASA Astrophysics Data System (ADS)

Endris, Hussen Seid; Lennard, Christopher; Hewitson, Bruce; Dosio, Alessandro; Nikulin, Grigory; Artan, Guleid A.

2018-05-01

This study examines the projected changes in the characteristics of the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) in terms of mean state, intensity and frequency, and associated rainfall anomalies over eastern Africa. Two regional climate models driven by the same four global climate models (GCMs) and the corresponding GCM simulations are used to investigate projected changes in teleconnection patterns and East African rainfall. The period 1976-2005 is taken as the reference for present climate and the far-future climate (2070-2099) under Representative Concentration Pathway 8.5 (RCP8.5) is analyzed for projected change. Analyses of projections based on GCMs indicate an El Niño-like (positive IOD-like) warming pattern over the tropical Pacific (Indian) Ocean. However, large uncertainties remain in the projected future changes in ENSO/IOD frequency and intensity with some GCMs show increase of ENSO/IOD frequency and intensity, and others a decrease or no/small change. Projected changes in mean rainfall over eastern Africa based on the GCM and RCM data indicate a decrease in rainfall over most parts of the region during JJAS and MAM seasons, and an increase in rainfall over equatorial and southern part of the region during OND, with the greatest changes in equatorial region. During ENSO and IOD years, important changes in the strength of the teleconnections are found. During JJAS, when ENSO is an important driver of rainfall variability over the region, both GCM and RCM projections show an enhanced La Niña-related rainfall anomaly compared to the present period. Although the long rains (MAM) have little association with ENSO in the reference period, both GCMs and RCMs project stronger ENSO teleconnections in the future. On the other hand, during the short rains (OND), a dipole future change in rainfall teleconnection associated with ENSO and IOD is found, with a stronger ENSO/IOD related rainfall anomaly over the eastern part of the domain, but a weaker ENSO/IOD signal over the southern part of the region. This signal is consistent and robust in all global and regional model simulations. The projected increase in OND rainfall over the eastern horn of Africa might be linked with the mean changes in SST over Indian and Pacific Ocean basins and the associated Walker circulations.

The Software Architecture of Global Climate Models

NASA Astrophysics Data System (ADS)

Alexander, K. A.; Easterbrook, S. M.

2011-12-01

It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

Spatial-temporal changes in runoff and terrestrial ecosystem water retention under 1.5 and 2 °C warming scenarios across China

NASA Astrophysics Data System (ADS)

Zhai, Ran; Tao, Fulu; Xu, Zhihui

2018-06-01

The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 °C above pre-industrial levels, pursuing efforts to limit this to 1.5 °C; it is therefore important to understand the impacts of climate change under 1.5 and 2.0 °C warming scenarios for climate adaptation and mitigation. Here, climate scenarios from four global circulation models (GCMs) for the baseline (2006-2015), 1.5, and 2.0 °C warming scenarios (2106-2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on runoff and terrestrial ecosystem water retention (TEWR) across China at a spatial resolution of 0.5°. This study applied ensemble projections from multiple GCMs to provide more comprehensive and robust results. The trends in annual mean temperature, precipitation, runoff, and TEWR were analyzed at the grid and basin scale. Results showed that median change in runoff ranged from 3.61 to 13.86 %, 4.20 to 17.89 %, and median change in TEWR ranged from -0.45 to 6.71 and -3.48 to 4.40 % in the 10 main basins in China under 1.5 and 2.0 °C warming scenarios, respectively, across all four GCMs. The interannual variability of runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from the 1.5 to the 2.0 °C warming scenario. In contrast, TEWR would remain relatively stable, the median change in standard deviation (SD) of TEWR ranged from -10 to 10 % in about 90 % grids under 1.5 and 2.0 °C warming scenarios, across all four GCMs. Both low and high runoff would increase under the two warming scenarios in most areas across China, with high runoff increasing more. The risks of low and high runoff events would be higher under the 2.0 than under the 1.5 °C warming scenario in terms of both extent and intensity. Runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our results were supported by previous studies. However, there existed large uncertainties in climate scenarios from different GCMs, which led to large uncertainties in impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. Our findings on the spatiotemporal patterns of climate impacts and their shifts from the 1.5 to the 2.0 °C warming scenario are useful for water resource management under different warming scenarios.

Effect of climate data on simulated carbon and nitrogen balances for Europe

NASA Astrophysics Data System (ADS)

Blanke, Jan Hendrik; Lindeskog, Mats; Lindström, Johan; Lehsten, Veiko

2016-05-01

In this study, we systematically assess the spatial variability in carbon and nitrogen balance simulations related to the choice of global circulation models (GCMs), representative concentration pathways (RCPs), spatial resolutions, and the downscaling methods used as calculated with LPJ-GUESS. We employed a complete factorial design and performed 24 simulations for Europe with different climate input data sets and different combinations of these four factors. Our results reveal that the variability in simulated output in Europe is moderate with 35.6%-93.5% of the total variability being common among all combinations of factors. The spatial resolution is the most important factor among the examined factors, explaining 1.5%-10.7% of the total variability followed by GCMs (0.3%-7.6%), RCPs (0%-6.3%), and downscaling methods (0.1%-4.6%). The higher-order interactions effect that captures nonlinear relations between the factors and random effects is pronounced and accounts for 1.6%-45.8% to the total variability. The most distinct hot spots of variability include the mountain ranges in North Scandinavia and the Alps, and the Iberian Peninsula. Based on our findings, we advise to conduct the application of models such as LPJ-GUESS at a reasonably high spatial resolution which is supported by the model structure. There is no notable gain in simulations of ecosystem carbon and nitrogen stocks and fluxes from using regionally downscaled climate in preference to bias-corrected, bilinearly interpolated CMIP5 projections.

The Effect of an Increased Convective Entrainment Rate on Indian Monsoon Biases in the Met Office Unified Model

NASA Astrophysics Data System (ADS)

Bush, Stephanie; Turner, Andrew; Woolnough, Steve; Martin, Gill

2013-04-01

Global circulation models (GCMs) are a key tool for understanding and predicting monsoon rainfall, now and under future climate change. However, many GCMs show significant, systematic biases in their simulation of monsoon rainfall and dynamics that spin up over very short time scales and persist in the climate mean state. We describe several of these biases as simulated in the Met Office Unified Model and show they are sensitive to changes in the convective parameterization's entrainment rate. To improve our understanding of the biases and inform efforts to improve convective parameterizations, we explore the reasons for this sensitivity. We show the results of experiments where we increase the entrainment rate in regions of especially large bias: the western equatorial Indian Ocean, western north Pacific and India itself. We use the results to determine whether improvements in biases are due to the local increase in entrainment or are the remote response of the entrainment increase elsewhere in the GCM. We find that feedbacks usually strengthen the local response, but the local response leads to a different mean state change in different regions. We also show results from experiments which demonstrate the spin-up of the local response, which we use to further understand the response in complex regions such as the Western North Pacific. Our work demonstrates that local application of parameterization changes is a powerful tool for understanding their global impact.

Shortwave and longwave radiative contributions to global warming under increasing CO2

PubMed Central

Donohoe, Aaron; Armour, Kyle C.; Pendergrass, Angeline G.; Battisti, David S.

2014-01-01

In response to increasing concentrations of atmospheric CO2, high-end general circulation models (GCMs) simulate an accumulation of energy at the top of the atmosphere not through a reduction in outgoing longwave radiation (OLR)—as one might expect from greenhouse gas forcing—but through an enhancement of net absorbed solar radiation (ASR). A simple linear radiative feedback framework is used to explain this counterintuitive behavior. It is found that the timescale over which OLR returns to its initial value after a CO2 perturbation depends sensitively on the magnitude of shortwave (SW) feedbacks. If SW feedbacks are sufficiently positive, OLR recovers within merely several decades, and any subsequent global energy accumulation is because of enhanced ASR only. In the GCM mean, this OLR recovery timescale is only 20 y because of robust SW water vapor and surface albedo feedbacks. However, a large spread in the net SW feedback across models (because of clouds) produces a range of OLR responses; in those few models with a weak SW feedback, OLR takes centuries to recover, and energy accumulation is dominated by reduced OLR. Observational constraints of radiative feedbacks—from satellite radiation and surface temperature data—suggest an OLR recovery timescale of decades or less, consistent with the majority of GCMs. Altogether, these results suggest that, although greenhouse gas forcing predominantly acts to reduce OLR, the resulting global warming is likely caused by enhanced ASR. PMID:25385628

Phenological Versus Meteorological Controls on Land-atmosphere Water and Carbon Fluxes

NASA Technical Reports Server (NTRS)

Puma, Michael J.; Koster, Randal D.; Cook, Benjamin I.

2013-01-01

Phenological dynamics and their related processes strongly constrain land-atmosphere interactions, but their relative importance vis-à-vis meteorological forcing within general circulation models (GCMs) is still uncertain. Using an off-line land surface model, we evaluate leaf area and meteorological controls on gross primary productivity, evapotranspiration, transpiration, and runoff at four North American sites, representing different vegetation types and background climates. Our results demonstrate that compared to meteorological controls, variation in leaf area has a dominant control on gross primary productivity, a comparable but smaller influence on transpiration, a weak influence on total evapotranspiration, and a negligible impact on runoff. Climate regime and characteristic variations in leaf area have important modulating effects on these relative controls, which vary depending on the fluxes and timescales of interest. We find that leaf area in energylimited evaporative regimes tends to exhibit greater control on annual gross primary productivity than in moisture-limited regimes, except when vegetation exhibits little interannual variation in leaf area. For transpiration, leaf area control is somewhat less in energylimited regimes and greater in moisture-limited regimes for maximum pentad and annual fluxes. These modulating effects of climate and leaf area were less clear for other fluxes and at other timescales. Our findings are relevant to land-atmosphere coupling in GCMs, especially considering that leaf area variations are a fundamental element of land use and land cover change simulations.

Combined ice core and climate-model evidence for the collapse of the West Antarctic Ice Sheet during Marine Isotope Stage 5e.

NASA Astrophysics Data System (ADS)

Steig, Eric J.; Huybers, Kathleen; Singh, Hansi A.; Steiger, Nathan J.; Frierson, Dargan M. W.; Popp, Trevor; White, James W. C.

2015-04-01

It has been speculated that collapse of the West Antarctic Ice Sheet explains the very high eustatic sea level rise during the last interglacial period, marine isotope stage (MIS) 5e, but the evidence remains equivocal. Changes in atmospheric circulation resulting from a collapse of the West Antarctic Ice Sheet (WAIS) would have significant regional impacts that should be detectable in ice core records. We conducted simulations using general circulation models (GCMs) at varying levels of complexity: a gray-radiation aquaplanet moist GCM (GRaM), the slab ocean version of GFDL-AM2 (also as an aquaplanet), and the fully-coupled version of NCAR's CESM with realistic topography. In all the experiments, decreased elevation from the removal of the WAIS leads to greater cyclonic circulation over the West Antarctic region. This creates increased advection of relatively warm marine air from the Amundsen-Bellingshausen Seas towards the South Pole, and increased cold-air advection from the East Antarctic plateau towards the Ross Sea and coastal Marie Byrd Land. The result is anomalous warming in some areas of the East Antarctic interior, and significant cooling in Marie Byrd Land. Comparison of ice core records shows good agreement with the model predictions. In particular, isotope-paleotemperature records from ice cores in East Antarctica warmed more between the previous glacial period (MIS 6) and MIS 5e than coastal Marie Byrd Land. These results add substantial support to other evidence for WAIS collapse during the last interglacial period.

Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes

NASA Astrophysics Data System (ADS)

Iizumi, Toshichika; Takikawa, Hiroki; Hirabayashi, Yukiko; Hanasaki, Naota; Nishimori, Motoki

2017-08-01

The use of different bias-correction methods and global retrospective meteorological forcing data sets as the reference climatology in the bias correction of general circulation model (GCM) daily data is a known source of uncertainty in projected climate extremes and their impacts. Despite their importance, limited attention has been given to these uncertainty sources. We compare 27 projected temperature and precipitation indices over 22 regions of the world (including the global land area) in the near (2021-2060) and distant future (2061-2100), calculated using four Representative Concentration Pathways (RCPs), five GCMs, two bias-correction methods, and three reference forcing data sets. To widen the variety of forcing data sets, we developed a new forcing data set, S14FD, and incorporated it into this study. The results show that S14FD is more accurate than other forcing data sets in representing the observed temperature and precipitation extremes in recent decades (1961-2000 and 1979-2008). The use of different bias-correction methods and forcing data sets contributes more to the total uncertainty in the projected precipitation index values in both the near and distant future than the use of different GCMs and RCPs. However, GCM appears to be the most dominant uncertainty source for projected temperature index values in the near future, and RCP is the most dominant source in the distant future. Our findings encourage climate risk assessments, especially those related to precipitation extremes, to employ multiple bias-correction methods and forcing data sets in addition to using different GCMs and RCPs.

Clustering of Global Climate Models outputs as a tool for scenario-based risk assessment

NASA Astrophysics Data System (ADS)

R Pereira, V.; Zullo, J., Jr.; Avila, A. M. H. D.

2016-12-01

The choice of the Global Climate Models (GCMs) future projections outputs for the scenario based risk assessment studies is a challenge for the non-climate models scientists. This study presents a method to select a range of the GCMs scenarios for regional/continental agriculture studies. The technique proposed here is based on grouping the surface air temperature (tas) anomalies in a continental /regional scale - in Brazil-South America - projected by the AR5-CMIP5-GCMs. We run the k-means cluster algorithm and the silhouette method to identify the optimal number and to group the GCMs tas outputs under the rcp 8.5. We applied the delta method to calculate the near future climate change. This method is based on the difference between the future and the baseline in a 30 year running mean periods basis. The future considered here is the 2021-2050 [2030s] and the baseline is the period of 1976-2005 (1980s). As expected, all the models projections showed increases in tas in the near future, ranging from ≅ 3.6 to 0.2 oC. The k-means clustering clearly indicates 5 groups of GCMs tas deltas. The majority of GCMs indicated an intermediate future temperature changes. There is a group of 12 GCMs that is indicating an average change of ≅ 2 oC and another group of 16 indicating ≅ 1 oC. The other two groups with 3 GCMs each indicated a most extreme tas scenario - 0.2 and 3.6 oC respectively. The results were in agreement with previous studies with the AR4 GCMs in which the Miroc5 and HADGEM ES predecessors were classified in different groups of models. The results also allowed us to gradually access the optimist - pessimist groups of 34 GCMs that is a good reference to guide the public policy demands for agriculture under climate change conditions.

The Tropical Subseasonal Variability Simulated in the NASA GISS General Circulation Model

NASA Technical Reports Server (NTRS)

Kim, Daehyun; Sobel, Adam H.; DelGenio, Anthony D.; Chen, Yonghua; Camargo, Suzana J.; Yao, Mao-Sung; Kelley, Maxwell; Nazarenko, Larissa

2012-01-01

The tropical subseasonal variability simulated by the Goddard Institute for Space Studies general circulation model, Model E2, is examined. Several versions of Model E2 were developed with changes to the convective parameterization in order to improve the simulation of the Madden-Julian oscillation (MJO). When the convective scheme is modified to have a greater fractional entrainment rate, Model E2 is able to simulate MJO-like disturbances with proper spatial and temporal scales. Increasing the rate of rain reevaporation has additional positive impacts on the simulated MJO. The improvement in MJO simulation comes at the cost of increased biases in the mean state, consistent in structure and amplitude with those found in other GCMs when tuned to have a stronger MJO. By reinitializing a relatively poor-MJO version with restart files from a relatively better-MJO version, a series of 30-day integrations is constructed to examine the impacts of the parameterization changes on the organization of tropical convection. The poor-MJO version with smaller entrainment rate has a tendency to allow convection to be activated over a broader area and to reduce the contrast between dry and wet regimes so that tropical convection becomes less organized. Besides the MJO, the number of tropical-cyclone-like vortices simulated by the model is also affected by changes in the convection scheme. The model simulates a smaller number of such storms globally with a larger entrainment rate, while the number increases significantly with a greater rain reevaporation rate.

Impact of 3-D orographic gravity wave parameterisation on stratosphere dynamics

NASA Astrophysics Data System (ADS)

Eichinger, Roland; Garny, Hella; Cai, Duy; Jöckel, Patrick

2017-04-01

Stratosphere dynamics are strongly influenced by gravity waves (GWs) propagating upwards from the troposphere. Some of these GWs are generated through flow over small-scale orography and can not be resolved by common general circulation models (GCMs). Due to computational model designs, their parameterisation usually follows a one dimensional columnar approach that, among other simplifications, neglects the horizontal propagation of GWs on their way up into the Middle Atmosphere. This causes contradictions between models and observations in location and strength of GW drag force through their dissipation and as a consequence, also in stratospheric mean flow. In the EMAC (ECHAM MESSy Atmospheric Chemistry) model, we have found this deficiency to cause a too weak Antarctic polar vortex, which directly impacts stratospheric temperatures and thereby the chemical reactions that determine ozone depletion. For this reason, we adapt a three dimensional parameterisation for orographic GWs, that had been implemented and tested in the MIROC GCM, to the MESSy coding standard. This computationally light scheme can then be used in a modular and flexible way in a cascade of model setups from an idealised version for conceptional process analyses to full climate chemistry simulations for quantitative investigations. This model enhancement can help to reconcile models and observations in wave drag forcing itself, but in consequence, also in Brewer-Dobson Circulation trends across the recent decades. Furthermore, uncertainties in weather and climate predictions as well as in future ozone projections can be reduced.

Seasonal prediction skill of winter temperature over North India

NASA Astrophysics Data System (ADS)

Tiwari, P. R.; Kar, S. C.; Mohanty, U. C.; Dey, S.; Kumari, S.; Sinha, P.

2016-04-01

The climatology, amplitude error, phase error, and mean square skill score (MSSS) of temperature predictions from five different state-of-the-art general circulation models (GCMs) have been examined for the winter (December-January-February) seasons over North India. In this region, temperature variability affects the phenological development processes of wheat crops and the grain yield. The GCM forecasts of temperature for a whole season issued in November from various organizations are compared with observed gridded temperature data obtained from the India Meteorological Department (IMD) for the period 1982-2009. The MSSS indicates that the models have skills of varying degrees. Predictions of maximum and minimum temperature obtained from the National Centers for Environmental Prediction (NCEP) climate forecast system model (NCEP_CFSv2) are compared with station level observations from the Snow and Avalanche Study Establishment (SASE). It has been found that when the model temperatures are corrected to account the bias in the model and actual orography, the predictions are able to delineate the observed trend compared to the trend without orography correction.

Climate Change Impacts for Conterminous USA: An Integrated Assessment Part 2. Models and Validation

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

Thomson, Allison M.; Rosenberg, Norman J.; Izaurralde, R Cesar C.

As CO{sub 2} and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using a suite of climate change predictions from General Circulation Models (GCMs) as described in Part 1. Here we describe the agriculture model EPIC and the HUMUS water model and validate them with historical crop yields and streamflow data. We compare EPIC simulated grainmore » and forage crop yields with historical crop yields from the US Department of Agriculture and find an acceptable level of agreement for this study. The validation of HUMUS simulated streamflow with estimates of natural streamflow from the US Geological Survey shows that the model is able to reproduce significant relationships and capture major trends.« less

Correction of Excessive Precipitation over Steep Mountains in a General Circulation Model (GCM)

NASA Technical Reports Server (NTRS)

Chao, Winston C.

2012-01-01

Excessive precipitation over steep and high mountains (EPSM) is a well-known problem in GCMs and regional climate models even at a resolution as high as 19km. The affected regions include the Andes, the Himalayas, Sierra Madre, New Guinea and others. This problem also shows up in some data assimilation products. Among the possible causes investigated in this study, we found that the most important one, by far, is a missing upward transport of heat out of the boundary layer due to the vertical circulations forced by the daytime subgrid-scale upslope winds, which in turn is forced by heated boundary layer on the slopes. These upslope winds are associated with large subgrid-scale topographic variance, which is found over steep mountains. Without such subgrid-scale heat ventilation, the resolvable-scale upslope flow in the boundary layer generated by surface sensible heat flux along the mountain slopes is excessive. Such an excessive resolvable-scale upslope flow in the boundary layer combined with the high moisture content in the boundary layer results in excessive moisture transport toward mountaintops, which in turn gives rise to excessive precipitation over the affected regions. We have parameterized the effects of subgrid-scale heated-slope-induced vertical circulation (SHVC) by removing heat from the boundary layer and depositing it in the layers higher up when topographic variance exceeds a critical value. Test results using NASA/Goddard's GEOS-5 GCM have shown that the EPSM problem is largely solved.

Some remarks on using circulation classifications to evaluate circulation model and atmospheric reanalysis data

NASA Astrophysics Data System (ADS)

Stryhal, Jan; Huth, Radan

2017-04-01

Automated classifications of atmospheric circulation patterns represent a tool widely used for studying the circulation in both the real atmosphere, represented by atmospheric reanalyses, and in circulation model outputs. It is well known that the results of studies utilizing one of these methods are influenced by several subjective choices, of which one of the most crucial is the selection of the method itself. Authors of the present study used eight methods from the COST733 classification software (Grosswettertypes, two variants of Jenkinson-Collison, Lund, T-mode PCA with oblique rotation of principal components, k-medoids, k-means with differing starting partitions, and SANDRA) to assess the winter 1961-2000 daily sea level pressure patterns in five reanalysis datasets (ERA-40, NCEP-1, JRA-55, 20CRv2, and ERA-20C), as well as in the historical runs and 21st century projections of an ensemble of CMIP5 GCMs. The classification methods were quite consistent in displaying the strongest biases in GCM simulations. However, the results also showed that multiple classifications are required to quantify the biases in certain types of circulation (e.g., zonal circulation or blocking-like patterns). There was no sign that any method should have a tendency to over- or underestimate the biases in circulation type frequency. The bias found by a particular method for a particular domain clearly reflects the ability of the algorithm to detect groups of similar patterns within the data space, and whether these groups do or do not differ one dataset to another is to a large extend coincidental. There were, nevertheless, systematic differences between groups of methods that use some form of correlation to classify the patterns to circulation types (CTs) and those which use the Euclidean distance. The comparison of reanalyses, which was conducted over eight European domains, showed that there is even a weak negative correlation between the average differences of CT frequency found by cluster analysis methods on one hand, and the remaining methods on the other. This suggests that groups of different methods capture different kinds of errors and that averaging the results obtained by an ensemble of methods very likely leads to an underestimation of the errors actually present in the data.

Climate change impacts under CMIP5 RCP scenarios on water resources of the Kelantan River Basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Ibrahim, Ab Latif; Yusop, Zulkifli; Chua, Vivien P.; Chan, Ngai Weng

2017-06-01

This study aims to evaluate the potential impacts of climate change on water resources of the Kelantan River Basin in north-eastern Peninsular Malaysia using the Soil and Water Assessment Tool (SWAT) model. Thirty-six downscaled climate projections from five General Circulation Models (GCMs) under the three Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 scenarios for the periods of 2015-2044 and 2045-2074 were incorporated into the calibrated SWAT model. Differences of these scenarios were calculated by comparing to the 1975-2004 baseline period. Overall, the SWAT model performed well in monthly streamflow simulation, with the Nash-Sutcliffe efficiency values of 0.75 and 0.63 for calibration and validation, respectively. Based on the ensemble of five GCMs, the annual rainfall and maximum temperature are projected to increase by 1.2-8.7% and 0.6-2.1 °C, respectively. This corresponds to the increases in the annual streamflow (14.6-27.2%), evapotranspiration (0.3-2.7%), surface runoff (46.8-90.2%) and water yield (14.2-26.5%) components. The study shows an increase of monthly rainfall during the wet season, and decrease during the dry season. Therefore, the monthly streamflow and surface runoff are likely to increase significantly in November, December and January. In addition, slight decreases in the monthly water yield are found between June and October (1.9-8.9%) during the 2015-2044 period. These findings could act as a scientific reference to develop better climate adaptation strategies.

The geographic distribution and economic value of climate change-related ozone health impacts in the United States in 2030.

PubMed

Fann, Neal; Nolte, Christopher G; Dolwick, Patrick; Spero, Tanya L; Brown, Amanda Curry; Phillips, Sharon; Anenberg, Susan

2015-05-01

In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1-4°C and 1-5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$). Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1-5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$).

A flexible climate model for use in integrated assessments

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Stone, P. H.

Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model's sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100-150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties.

Weather and extremes in the last Millennium - a challenge for climate modelling

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Blumer, Sandro R.; Gomez-Navarro, Juan J.; Lehner, Flavio

2015-04-01

Changes in the climate mean state are expected to influence society, but the socio-economic sensitivity to extreme events might be even more severe. Whether or not the current frequency and severity of extreme events is a unique characteristic of anthropogenic-driven climate change can be assessed by putting the observed changes in a long-term perspective. In doing so, early instrumental series and proxy archives are a rich source to investigate also extreme events, in particular during the last millennium, yet they suffer from spatial and temporal scarcity. Therefore, simulations with coupled general circulation models (GCMs) could fill such gaps and help in deepening our process understanding. In this study, an overview of past and current efforts as well as challenges in modelling paleo weather and extreme events is presented. Using simulations of the last millennium we investigate extreme midlatitude cyclone characteristics, precipitation, and their connection to large-scale atmospheric patterns in the North Atlantic European region. In cold climate states such as the Maunder Minimum, the North Atlantic Oscillation (NAO) is found to be predominantly in its negative phase. In this sense, simulations of different models agree with proxy findings for this period. However, some proxy data available for this period suggests an increase in storminess during this period, which could be interpreted as a positive phase of the NAO - a superficial contradiction. The simulated cyclones are partly reduced over Europe, which is consistent with the aforementioned negative phase of the NAO. However, as the meridional temperature gradient is increased during this period - which constitutes a source of low-level baroclincity - they also intensify. This example illustrates how model simulations could be used to improve our proxy interpretation and to gain additional process understanding. Nevertheless, there are also limitations associated with climate modeling efforts to simulate the last millennium. In particular, these models still struggle to properly simulate atmospheric blocking events, an important dynamical feature for dry conditions during summer times. Finally, new and promising ways in improving past climate modelling are briefly introduced. In particular, the use of dynamical downscaling is a powerful tool to bridge the gap between the coarsely resolved GCMs and characteristics of the regional climate, which is potentially recorded in proxy archives. In particular, the representation of extreme events could be improved by dynamical downscaling as processes are better resolved than GCMs.

Comparison of simulated and reconstructed variations in East African hydroclimate over the last millennium

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

Klein, Francois; Goosse, Hugues; Graham, Nicholas E.

The multi-decadal to centennial hydroclimate changes in East Africa over the last millennium are studied by comparing the results of forced transient simulations by six general circulation models (GCMs) with published hydroclimate reconstructions from four lakes: Challa and Naivasha in equatorial East Africa, and Masoko and Malawi in southeastern inter-tropical Africa. All GCMs simulate fairly well the unimodal seasonal cycle of precipitation in the Masoko–Malawi region, while the bimodal seasonal cycle characterizing the Challa–Naivasha region is generally less well captured by most models. Model results and lake-based hydroclimate reconstructions display very different temporal patterns over the last millennium. Additionally, theremore » is no common signal among the model time series, at least until 1850. This suggests that simulated hydroclimate fluctuations are mostly driven by internal variability rather than by common external forcing. After 1850, half of the models simulate a relatively clear response to forcing, but this response is different between the models. Overall, the link between precipitation and tropical sea surface temperatures (SSTs) over the pre-industrial portion of the last millennium is stronger and more robust for the Challa–Naivasha region than for the Masoko–Malawi region. At the inter-annual timescale, last-millennium Challa–Naivasha precipitation is positively (negatively) correlated with western (eastern) Indian Ocean SST, while the influence of the Pacific Ocean appears weak and unclear. Although most often not significant, the same pattern of correlations between East African rainfall and the Indian Ocean SST is still visible when using the last-millennium time series smoothed to highlight centennial variability, but only in fixed-forcing simulations. Furthermore, this means that, at the centennial timescale, the effect of (natural) climate forcing can mask the imprint of internal climate variability in large-scale teleconnections.« less

Comparison of simulated and reconstructed variations in East African hydroclimate over the last millennium

DOE PAGES

Klein, Francois; Goosse, Hugues; Graham, Nicholas E.; ...

2016-07-13

The multi-decadal to centennial hydroclimate changes in East Africa over the last millennium are studied by comparing the results of forced transient simulations by six general circulation models (GCMs) with published hydroclimate reconstructions from four lakes: Challa and Naivasha in equatorial East Africa, and Masoko and Malawi in southeastern inter-tropical Africa. All GCMs simulate fairly well the unimodal seasonal cycle of precipitation in the Masoko–Malawi region, while the bimodal seasonal cycle characterizing the Challa–Naivasha region is generally less well captured by most models. Model results and lake-based hydroclimate reconstructions display very different temporal patterns over the last millennium. Additionally, theremore » is no common signal among the model time series, at least until 1850. This suggests that simulated hydroclimate fluctuations are mostly driven by internal variability rather than by common external forcing. After 1850, half of the models simulate a relatively clear response to forcing, but this response is different between the models. Overall, the link between precipitation and tropical sea surface temperatures (SSTs) over the pre-industrial portion of the last millennium is stronger and more robust for the Challa–Naivasha region than for the Masoko–Malawi region. At the inter-annual timescale, last-millennium Challa–Naivasha precipitation is positively (negatively) correlated with western (eastern) Indian Ocean SST, while the influence of the Pacific Ocean appears weak and unclear. Although most often not significant, the same pattern of correlations between East African rainfall and the Indian Ocean SST is still visible when using the last-millennium time series smoothed to highlight centennial variability, but only in fixed-forcing simulations. Furthermore, this means that, at the centennial timescale, the effect of (natural) climate forcing can mask the imprint of internal climate variability in large-scale teleconnections.« less

Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degree global warming

NASA Astrophysics Data System (ADS)

Thober, S.; Kumar, R.; Wanders, N.; Marx, A.; Pan, M.; Rakovec, O.; Samaniego, L. E.; Sheffield, J.; Wood, E. F.; Zink, M.

2017-12-01

Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 General Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over entire Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow water equivalent decreases flood events in this region. The contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share of the overall uncertainty and exceed GCM uncertainty in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but has to account for significantly higher changes under 3 K global warming.

Evaluation of rainfall simulations over West Africa in dynamically downscaled CMIP5 global circulation models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Ajayi, V. O.; Adejare, A. T.; Adeyeri, O. E.; Gbode, I. E.; Ogunjobi, K. O.; Nikulin, G.; Abolude, A. T.

2018-04-01

This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully reproduce the key features of rainfall climatology over West Africa for the period of 1980-2005. The seasonal climatology and annual cycle of the RCA4 simulations were assessed over three homogenous subregions of West Africa (Guinea coast, Savannah, and Sahel) and evaluated using observed precipitation data from the Global Precipitation Climatology Project (GPCP). Furthermore, the model output was evaluated using a wide range of statistical measures. The interseasonal and interannual variability of the RCA4 were further assessed over the subregions and the whole of the West Africa domain. Results indicate that the RCA4 captures the spatial and interseasonal rainfall pattern adequately but exhibits a weak performance over the Guinea coast. Findings from the interannual rainfall variability indicate that the model performance is better over the larger West Africa domain than the subregions. The largest difference across the RCA4 simulated annual rainfall was found in the Sahel. Result from the Mann-Kendall test showed no significant trend for the 1980-2005 period in annual rainfall either in GPCP observation data or in the model simulations over West Africa. In many aspects, the RCA4 simulation driven by the HadGEM2-ES perform best over the region. The use of the multimodel ensemble mean has resulted to the improved representation of rainfall characteristics over the study domain.

Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

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).

Hydrologic Impacts of Climate Change: Quantification of Uncertainties (Alexander von Humboldt Medal Lecture)

NASA Astrophysics Data System (ADS)

Mujumdar, Pradeep P.

2014-05-01

Climate change results in regional hydrologic change. The three prominent signals of global climate change, viz., increase in global average temperatures, rise in sea levels and change in precipitation patterns convert into signals of regional hydrologic change in terms of modifications in water availability, evaporative water demand, hydrologic extremes of floods and droughts, water quality, salinity intrusion in coastal aquifers, groundwater recharge and other related phenomena. A major research focus in hydrologic sciences in recent years has been assessment of impacts of climate change at regional scales. An important research issue addressed in this context deals with responses of water fluxes on a catchment scale to the global climatic change. A commonly adopted methodology for assessing the regional hydrologic impacts of climate change is to use the climate projections provided by the General Circulation Models (GCMs) for specified emission scenarios in conjunction with the process-based hydrologic models to generate the corresponding hydrologic projections. The scaling problem arising because of the large spatial scales at which the GCMs operate compared to those required in distributed hydrologic models, and their inability to satisfactorily simulate the variables of interest to hydrology are addressed by downscaling the GCM simulations to hydrologic scales. Projections obtained with this procedure are burdened with a large uncertainty introduced by the choice of GCMs and emission scenarios, small samples of historical data against which the models are calibrated, downscaling methods used and other sources. Development of methodologies to quantify and reduce such uncertainties is a current area of research in hydrology. In this presentation, an overview of recent research carried out by the author's group on assessment of hydrologic impacts of climate change addressing scale issues and quantification of uncertainties is provided. Methodologies developed with conditional random fields, Dempster-Shafer theory, possibility theory, imprecise probabilities and non-stationary extreme value theory are discussed. Specific applications on uncertainty quantification in impacts on streamflows, evaporative water demands, river water quality and urban flooding are presented. A brief discussion on detection and attribution of hydrologic change at river basin scales, contribution of landuse change and likely alterations in return levels of hydrologic extremes is also provided.

Impact of Climate Change on Potential, Attainable, and Actual Wheat Yield in Oklahoma

NASA Astrophysics Data System (ADS)

Dhakal, K.; Linde, E.; Kakani, V. G.; Alderman, P. D.; Brunson, D.; Ochsner, T. E.; Carver, B.

2017-12-01

Gradually developing climatic and weather anomalies due to increasing atmospheric greenhouse gases concentration can pose threat to farmers and resource managers. This study was aimed at investigating the effects of climate change on winter wheat (Triticum aestivum L.) under the Representative Concentration Pathways 6.0 and 8.5 using downscaled climate projections from different models and their ensembles. Daily data of maximum and minimum air temperature, rainfall, and solar radiation for, four General Circulation Models (MRIOC5, MRI-CGCM3, HadGEM2-ES, CSRIO-Mk3.6.0), ensemble of four models and ensemble of 17 GCMs, at 800 m resolution, were developed for two RCPs using Marksim. We describe a methodology for rapid synthesis of GCM-based, spatially explicit, high resolution future weather data inputs for the DSSAT crop model, for cropland area across wheat growing regions of Oklahoma for the future period 2040-2060. The potential impacts of climate change and variability on potential, attainable, and actual winter wheat yield in Oklahoma is discussed.

AgMIP Climate Data and Scenarios for Integrated Assessment. Chapter 3

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; Winter, Jonathan M.; McDermid, Sonali P.; Hudson, Nicholas I.

2015-01-01

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

Diurnal cycle of precipitation at Dakar in the model LMDZ

NASA Astrophysics Data System (ADS)

Sane, Y.; Bonazzola, M.; Hourdin, F.; Diongue-Niang, A.

2009-04-01

Most diurnal cycles of precipitation are not well represented in general circulation models (GCMs). It is a concern for climate modeling because of the key role of clouds in the radiative and water budgets. The diurnal phasing of deep convection is a challenge, the pact of deep convection being generally simulated too early in the day (Guichard et al., 2004). Thus a "thermal plume model" - a mass flux scheme combined with a classical diffusive approach - originally developed to represent turbulent transport in the dry convective boundary layer, is extented to the representation of cloud processes. The modified parametrization was validated in a 1D configuration against results of large eddy simulations (Rio, 2008). It is here validated in a 3D configuration against in situ precipitation measurements of the AMMA campaign. A data analysis of the diurnal cycle of precipitation as measured by the pluviometers net in the Dakar area is performed. The improvement of the diurnal cyle of convection in the GCM is demonstrated, and the involved processes are analysed.

Role of Equatorial Pacific SST Anomalies in Precipitation over Western Americas

NASA Astrophysics Data System (ADS)

Jong, B. T.; Ting, M.; Seager, R.; Henderson, N.; Lee, D.

2017-12-01

El Niño, as the prime source of seasonal to interannual climate predictability, could impose impacts on the Americas from tropical to mid-latitude regions. The teleconnection patterns are sensitive to the longitudinal location of the maximum tropical sea surface temperature anomalies (SSTA). Meanwhile, slight differences in the location and configuration of the anomalous atmospheric circulations could differentiate between a wet and dry season regionally. For example, the 2015/16 strong El Niño event did not bring excessive precipitation to California despite expectations based on observational and model-based analyses. Whether the westward shift in the tropical SSTA pattern played a key role during this event is examined. We conduct two SSTA-forced experimental runs in three NCAR GCMs (CCM3, CAM4, and CAM5): one forced by the observed February-March-April 2016 SSTA and the other forced by the model-ensemble mean forecast FMA 2016 SSTA from the North America Multi-Model Ensemble. The observed SSTAs, compared to the forecast SSTAs, are colder in the central-eastern tropical Pacific and slightly warmer in the westernmost tropical Pacific. In response, all three models have a weaker and westward shifted low-pressure anomaly over the North Pacific and west coast of North America when the observed SSTA is prescribed. As the result, northern California is either about the same or drier in the observed SSTA runs than in the forecast SSTA runs. However, the precipitation over southern California responds differently across models. One of the possible explanations is that in CCM3 the teleconnections respond mainly to the SSTA differences in the eastern tropical Pacific; while in CAM4 and CAM5, the teleconnections are also sensitive to the small SSTA differences in the western tropical Pacific. The results suggest that the tropical SSTA differences matter for atmospheric circulations and precipitation over western Americas even though models disagree on the details of the circulation responses and subsequently the sign of regional precipitation responses. Further work on the sensitivity of circulations and precipitation to the tropical Pacific SSTA forcing will be conducted to improve the prediction of precipitation over western Americas.

Partitioning uncertainty in streamflow projections under nonstationary model conditions

NASA Astrophysics Data System (ADS)

Chawla, Ila; Mujumdar, P. P.

2018-02-01

Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them for future streamflow projections and segregate the contribution of various sources to the uncertainty.

Global and regional modeling of clouds and aerosols in the marine boundary layer during VOCALS: the VOCA intercomparison

DOE PAGES

Wyant, M. C.; Bretherton, Christopher S.; Wood, Robert; ...

2015-01-09

A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar tomore » observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO 2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.« less

Performance of CMIP3 and CMIP5 GCMs to simulate observed rainfall characteristics over the Western Himalayan region

NASA Astrophysics Data System (ADS)

Meher, J. K.; Das, L.

2017-12-01

The Western Himalayan Region (WHR) was subject to a significant negative trend in the annual and monsoon rainfall during 1902-2005. Annual and seasonal rainfall change over WHR of India was estimated using 22 rain gauge station rainfall data from the India Meteorological Department. The performance of 13 global climate models (GCMs) from the coupled model intercomparison project phase 3 (CMIP3) and 42 GCMs from CMIP5 was evaluated through multiple analysis: the evaluation of the mean annual cycle, annual cycles of interannual variability, spatial patterns, trends and signal-to-noise ratio. In general, CMIP5 GCMs were more skillful in terms of simulating the annual cycle of interannual variability compared to CMIP3 GCMs. The CMIP3 GCMs failed to reproduce the observed trend whereas 50% of the CMIP5 GCMs reproduced the statistical distribution of short-term (30-years) trend-estimates than for the longer term (99-years). GCMs from both CMIP3 and CMIP5 were able to simulate the spatial distribution of observed rainfall in pre-monsoon and winter months. Based on performance, each model of CMIP3 and CMIP5 was given an overall rank, which puts the high resolution version of the MIROC3.2 model (MIROC3.2 hires) and MIROC5 at the top in CMIP3 and CMIP5 respectively. Robustness of the ranking was judged through a sensitivity analysis, which indicated that ranks were independent during the process of adding or removing any individual method. It also revealed that trend analysis was not a robust method of judging performances of the model as compared to other methods.

Overview of the United States Department of Energy's ARM (Atmospheric Radiation Measurement) Program

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

Stokes, G.M.; Tichler, J.L.

The Department of Energy (DOE) is initiating a major atmospheric research effort, the Atmospheric Radiation Measurement Program (ARM). The program is a key component of DOE's research strategy to address global climate change and is a direct continuation of DOE's decade-long effort to improve the ability of General Circulation Models (GCMs) to provide reliable simulations of regional, and long-term climate change in response to increasing greenhouse gases. The effort is multi-disciplinary and multi-agency, involving universities, private research organizations and more than a dozen government laboratories. The objective of the ARM Research is to provide an experimental testbed for the studymore » of important atmospheric effects, particularly cloud and radiative processes, and to test parameterizations of these processes for use in atmospheric models. This effort will support the continued and rapid improvement of GCM predictive capability. 2 refs.« less

How consistent are precipitation patterns predicted by GCMs in the absence of cloud radiative effects?

NASA Astrophysics Data System (ADS)

Popke, Dagmar; Bony, Sandrine; Mauritsen, Thorsten; Stevens, Bjorn

2015-04-01

Model simulations with state-of-the-art general circulation models reveal a strong disagreement concerning the simulated regional precipitation patterns and their changes with warming. The deviating precipitation response even persists when reducing the model experiment complexity to aquaplanet simulation with forced sea surface temperatures (Stevens and Bony, 2013). To assess feedbacks between clouds and radiation on precipitation responses we analyze data from 5 models performing the aquaplanet simulations of the Clouds On Off Klima Intercomparison Experiment (COOKIE), where the interaction of clouds and radiation is inhibited. Although cloud radiative effects are then disabled, the precipitation patterns among models are as diverse as with cloud radiative effects switched on. Disentangling differing model responses in such simplified experiments thus appears to be key to better understanding the simulated regional precipitation in more standard configurations. By analyzing the local moisture and moist static energy budgets in the COOKIE experiments we investigate likely causes for the disagreement among models. References Stevens, B. & S. Bony: What Are Climate Models Missing?, Science, 2013, 340, 1053-1054

An A-Train Climatology of Extratropical Cyclone Clouds

NASA Technical Reports Server (NTRS)

Posselt, Derek J.; van den Heever, Susan C.; Booth, James F.; Del Genio, Anthony D.; Kahn, Brian; Bauer, Mike

2016-01-01

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

CMIP5 based downscaled temperature over Western Himalayan region

NASA Astrophysics Data System (ADS)

Dutta, M.; Das, L.; Meher, J. K.

2016-12-01

Limited numbers of reliable temperature data is available for assessing warming over the Western Himalayan Region (WHR) of India. India meteorological Department provided many stations having more than 30% missing values. Stations having <30% missing values, were replaced using the Multiple Imputation Chained Equation (MICE) technique. Finally 16 stations having continuous records during 1969-2009 were considered as the "reference stations" for assessing the trends in addition to evaluate the Coupled Model Intercomparison, phase 5 (CMIP5) Global Circulation Model(GCMs). Station data indicates higher and rapid (1.41oC) winter warming than the other seasons and least warming was observed in the post monsoon (0.31oC) season. Mean annual warming is 0.84 oC during 1969-2009 indicating the warming over the WHR is more than double the global warming (0.85oC during 1880-2012). The performance of 34 CMIP5 models was evaluated through three different approaches namely comparison of: i) mean seasonal cycle ii) temporal trends and iii) spatial correlation and a rank was assigned to each GCM. How the better performing GCMs able to reproduce the observed spatial details were verified the ERA-interim reanalysis data. Finally station level future downscaled winter temperature has constructed using Empirical Statistical Downscaling (ESD) technique where 2 meter air temperature (T2m) is considered as predictor and station temperature as predictant. Future range of downscaled temperature change for the stations Dheradun, Manali and Gulmarg are 1.3-6.1OC, 1.1-5.8OC and 0.5-5.8OC respectively at the end of 21st century.

Are there trends towards drier hydrological conditions in Central America?

NASA Astrophysics Data System (ADS)

Hidalgo, H. G.

2013-12-01

A summary of hydrological projections at the end of the century from 30 General Circulation Models (GCMs) is presented; and several hydrometeorological parameters are analyzed to validate if there are hydroclimatological trends during the observational period (1982-2005) consistent with the GCMs results. At the end of the century the median of 30 GCM simulations projects a drier future for Tegucigalpa and San Jose, with a marked increment in evapotranspiration in the first half of the rainy season along with reductions of soil moisture. With respect to the observations (1982-2005): 1) the Normalized Difference Vegetation Index showed negative trends in the North Pacific coast of Costa Rica, the border of Honduras and Nicaragua, and especially in southern Mexico (except the Yucatan Peninsula). Positive trends were found in the several parts of Central America, 2) the Palmer Drought Severity Index showed strong and consistent trends from Nicaragua to the North of Central America and southern Mexico (not including Yucatan), consistent with the direction of GCM projections; 3) negative precipitation trends in satellite data were found in Nicaragua, with strong trends in its Caribbean coast; 4) NCEP/NCAR Reanalysis precipitation showed strong negative trends in northern Central America, the Central Valley, the Dry Pacific of Costa Rica and the South-Pacific coast of Nicaragua, all consistent with the direction of GCM projections; and 5) station data showed no significant trends however, and 6) Reanalysis' temperature showed positive trends in southern Mexico (not including Yucatan) and negative trends in El Salvador. It can be concluded that several trends in drought indexes and precipitation are consistent with the future projected by the GCMs; that is, with some exceptions some of the trends were validated towards a drier future for the region, especially in the northern part.

Hydrological Responses of Chaobai River Basin under 1.5° and 2.0° Global Warming Using Multi-GCMs and Multi-RCPs

NASA Astrophysics Data System (ADS)

Hao, Y.; Ma, J.

2017-12-01

The global warming of 1.5° and 2.0° proposed in Paris Agreement has became the iconic threshold of climate change impact research and discussion. In order to provide useful reference to the effective water resource management and planning for the capital city of China, this study aims to assessing the potential impact of 1.5° and 2.0° global warming on river discharge in Chaobai River Basin(CRB) which is main water supply source of Beijing. A semi-distributed hydrological model SWAT was driven by climate projections from five General Circulation Models(GCMs) under three Representative Concentration Pathways (RCP4.5, RCP6.0 and RCP8.5) to simulate the future discharge in CRB under 1.5° and 2.0° global warming respectively. On this basis, climate change impact on annual and monthly discharge, seasonal discharge distribution, extreme monthly discharge in CRB were assessed and the uncertainty associated with GCMs and RCPs were analyzed quantitatively. The results indicate that the average annual discharge will increase slightly and more concentrate in midsummer and early autumn under 1.5° global warming. When the global average temperature rise 2°, the annual discharge in CRB show an evident positive tendency with the magnitude increasing by approximate 30% and the extreme monthly runoff will significantly increase. However, the proportion of discharge in summer which is the peak water usage period will decline. It is obvious that the increment of 0.5° will lead to more flood events and bring great challenge to water resource management. There is a certain uncertainty in the projection of temperature, precipitation and discharge, by contrast, uncertainty of discharge projection is far greater than that of other two meteorological elements. Compared with RCPs, GCMs are proved to be the main factor which are responsible for the impact uncertainty in CRB under two global warming horizons. The uncertainty will be larger as the warming magnitude increase. In a word, the additional 0.5 will be crucial to flood control and water security, therefore, it is better to pursue efforts to limit the temperature increase to 1.5C above pre-industrial levels.

Mountain Glaciers and Ice Caps

USGS Publications Warehouse

Ananichheva, Maria; Arendt, Anthony; Hagen, Jon-Ove; Hock, Regine; Josberger, Edward G.; Moore, R. Dan; Pfeffer, William Tad; Wolken, Gabriel J.

2011-01-01

Projections of future rates of mass loss from mountain glaciers and ice caps in the Arctic focus primarily on projections of changes in the surface mass balance. Current models are not yet capable of making realistic forecasts of changes in losses by calving. Surface mass balance models are forced with downscaled output from climate models driven by forcing scenarios that make assumptions about the future rate of growth of atmospheric greenhouse gas concentrations. Thus, mass loss projections vary considerably, depending on the forcing scenario used and the climate model from which climate projections are derived. A new study in which a surface mass balance model is driven by output from ten general circulation models (GCMs) forced by the IPCC (Intergovernmental Panel on Climate Change) A1B emissions scenario yields estimates of total mass loss of between 51 and 136 mm sea-level equivalent (SLE) (or 13% to 36% of current glacier volume) by 2100. This implies that there will still be substantial glacier mass in the Arctic in 2100 and that Arctic mountain glaciers and ice caps will continue to influence global sea-level change well into the 22nd century.

The impact of resolution on the dynamics of the martian global atmosphere: Varying resolution studies with the MarsWRF GCM

NASA Astrophysics Data System (ADS)

Toigo, Anthony D.; Lee, Christopher; Newman, Claire E.; Richardson, Mark I.

2012-09-01

We investigate the sensitivity of the circulation and thermal structure of the martian atmosphere to numerical model resolution in a general circulation model (GCM) using the martian implementation (MarsWRF) of the planetWRF atmospheric model. We provide a description of the MarsWRF GCM and use it to study the global atmosphere at horizontal resolutions from 7.5° × 9° to 0.5° × 0.5°, encompassing the range from standard Mars GCMs to global mesoscale modeling. We find that while most of the gross-scale features of the circulation (the rough location of jets, the qualitative thermal structure, and the major large-scale features of the surface level winds) are insensitive to horizontal resolution over this range, several major features of the circulation are sensitive in detail. The northern winter polar circulation shows the greatest sensitivity, showing a continuous transition from a smooth polar winter jet at low resolution, to a distinct vertically “split” jet as resolution increases. The separation of the lower and middle atmosphere polar jet occurs at roughly 10 Pa, with the split jet structure developing in concert with the intensification of meridional jets at roughly 10 Pa and above 0.1 Pa. These meridional jets appear to represent the separation of lower and middle atmosphere mean overturning circulations (with the former being consistent with the usual concept of the “Hadley cell”). Further, the transition in polar jet structure is more sensitive to changes in zonal than meridional horizontal resolution, suggesting that representation of small-scale wave-mean flow interactions is more important than fine-scale representation of the meridional thermal gradient across the polar front. Increasing the horizontal resolution improves the match between the modeled thermal structure and the Mars Climate Sounder retrievals for northern winter high latitudes. While increased horizontal resolution also improves the simulation of the northern high latitudes at equinox, even the lowest model resolution considered here appears to do a good job for the southern winter and southern equinoctial pole (although in detail some discrepancies remain). These results suggest that studies of the northern winter jet (e.g., transient waves and cyclogenesis) will be more sensitive to global model resolution that those of the south (e.g., the confining dynamics of the southern polar vortex relevant to studies of argon transport). For surface winds, the major effect of increased horizontal resolution is in the superposition of circulations forced by local-scale topography upon the large-scale surface wind patterns. While passive predictions of dust lifting are generally insensitive to model horizontal resolution when no lifting threshold is considered, increasing the stress threshold produces significantly more lifting in higher resolution simulations with the generation of finer-scale, higher-stress winds due primarily to better-resolved topography. Considering the positive feedbacks expected for radiatively active dust lifting, we expect this bias to increase when such feedbacks are permitted.

Dynamic Rainfall Patterns and the Simulation of Changing Scenarios: A behavioral watershed response

NASA Astrophysics Data System (ADS)

Chu, M.; Guzman, J.; Steiner, J. L.; Hou, C.; Moriasi, D.

2015-12-01

Rainfall is one of the fundamental drivers that control hydrologic responses including runoff production and transport phenomena that consequently drive changes in aquatic ecosystems. Quantifying the hydrologic responses to changing scenarios (e.g., climate, land use, and management) using environmental models requires a realistic representation of probable rainfall in its most sensible spatio-temporal dimensions matching that of the phenomenon under investigation. Downscaling projected rainfall from global circulation models (GCMs) is the most common practice in deriving rainfall datasets to be used as main inputs to hydrologic models which in turn are used to assess the impacts of climate changes on ecosystems. Downscaling assumes that local climate is a combination of large-scale climatic/atmospheric conditions and local conditions. However, the representation of the latter is generally beyond the capacity of current GCMs. The main objective of this study was to develop and implement a synthetic rainfall generator to downscale expected rainfall trends to 1 x 1 km rainfall daily patterns that mimic the dynamic propagation of probability distribution functions (pdf) derived from historic rainfall data (rain-gauge or radar estimated). Future projections were determined based on actual and expected changes in the pdf and stochastic processes to account for variability. Watershed responses in terms of streamflow and nutrients loads were evaluated using synthetically generated rainfall patterns and actual data. The framework developed in this study will allow practitioners to generate rainfall datasets that mimic the temporal and spatial patterns exclusive to their study area under full disclosure of the uncertainties involved. This is expected to provide significantly more accurate environmental models than is currently available and would provide practitioners with ways to evaluate the spectrum of systemic responses to changing scenarios.

Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability

NASA Astrophysics Data System (ADS)

Fu, Guobin; Charles, Stephen P.; Chiew, Francis H. S.; Ekström, Marie; Potter, Nick J.

2018-05-01

The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate statistical downscaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and specific humidity at 700 hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and dewpoint temperature depression at 850 hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature.

Towards a meaningful assessment of marine ecological impacts in life cycle assessment (LCA).

PubMed

Woods, John S; Veltman, Karin; Huijbregts, Mark A J; Verones, Francesca; Hertwich, Edgar G

2016-01-01

Human demands on marine resources and space are currently unprecedented and concerns are rising over observed declines in marine biodiversity. A quantitative understanding of the impact of industrial activities on the marine environment is thus essential. Life cycle assessment (LCA) is a widely applied method for quantifying the environmental impact of products and processes. LCA was originally developed to assess the impacts of land-based industries on mainly terrestrial and freshwater ecosystems. As such, impact indicators for major drivers of marine biodiversity loss are currently lacking. We review quantitative approaches for cause-effect assessment of seven major drivers of marine biodiversity loss: climate change, ocean acidification, eutrophication-induced hypoxia, seabed damage, overexploitation of biotic resources, invasive species and marine plastic debris. Our review shows that impact indicators can be developed for all identified drivers, albeit at different levels of coverage of cause-effect pathways and variable levels of uncertainty and spatial coverage. Modeling approaches to predict the spatial distribution and intensity of human-driven interventions in the marine environment are relatively well-established and can be employed to develop spatially-explicit LCA fate factors. Modeling approaches to quantify the effects of these interventions on marine biodiversity are less well-developed. We highlight specific research challenges to facilitate a coherent incorporation of marine biodiversity loss in LCA, thereby making LCA a more comprehensive and robust environmental impact assessment tool. Research challenges of particular importance include i) incorporation of the non-linear behavior of global circulation models (GCMs) within an LCA framework and ii) improving spatial differentiation, especially the representation of coastal regions in GCMs and ocean-carbon cycle models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pyrolysis-GCMS Analysis of Solid Organic Products from Catalytic Fischer-Tropsch Synthesis Experiments

NASA Technical Reports Server (NTRS)

Locke, Darren R.; Yazzie, Cyriah A.; Burton, Aaron S.; Niles, Paul B.; Johnson, Natasha M.

2015-01-01

Abiotic synthesis of complex organic compounds in the early solar nebula that formed our solar system is hypothesized to occur via a Fischer-Tropsch type (FTT) synthesis involving the reaction of hydrogen and carbon monoxide gases over metal and metal oxide catalysts. In general, at low temperatures (less than 200 C), FTT synthesis is expected to form abundant alkane compounds while at higher temperatures (greater than 200 C) it is expected to product lesser amounts of n-alkanes and greater amounts of alkene, alcohol, and polycyclic aromatic hydrocarbons (PAHs). Experiments utilizing a closed-gas circulation system to study the effects of FTT reaction temperature, catalysts, and number of experimental cycles on the resulting solid insoluble organic products are being performed in the laboratory at NASA Goddard Space Flight Center. These experiments aim to determine whether or not FTT reactions on grain surfaces in the protosolar nebula could be the source of the insoluble organic matter observed in meteorites. The resulting solid organic products are being analyzed at NASA Johnson Space Center by pyrolysis gas chromatography mass spectrometry (PY-GCMS). PY-GCMS yields the types and distribution of organic compounds released from the insoluble organic matter generated from the FTT reactions. Previously, exploratory work utilizing PY-GCMS to characterize the deposited organic materials from these reactions has been reported. Presented here are new organic analyses using magnetite catalyst to produce solid insoluble organic FTT products with varying reaction temperatures and number of experimental cycles.

Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E; Sheffels, Trevor R.; Carter, Jacoby; Systma, Mark D.; Talbert, Colin

2017-01-01

Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.

Development of probabilistic regional climate scenario in East Asia

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Ishizaki, N. N.

2015-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in East Asia (CORDEX-EA and Japan), the probability distribution of 2m air temperature was estimated by using developed regression model. The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. Probabilistic climate information in present (1969-1998) and future (2069-2098) climate was developed using CMIP3 SRES A1b scenarios 21 models and the observation data (CRU_TS3.22 & University of Delaware in CORDEX-EA, NIAES AMeDAS mesh data in Japan). The prototype of probabilistic information in CORDEX-EA and Japan represent the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Appropriate combination of statistical methods and optimization of climate ensemble experiments using multi-General Circulation Models (GCMs) and multi-regional climate models (RCMs) ensemble downscaling experiments are investigated.

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

NASA Astrophysics Data System (ADS)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations

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

Qian, Yun; Long, Charles N.; Wang, Hailong

2012-02-17

Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulations in the IPCC AR4 GCMs against ARM ground measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity, for both inter-model deviation and model-measurement discrepancy. Our intercomparisons of three CF or sky-cover related dataset reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The results also show that the model-observation and the inter-model deviations have a similar magnitude for themore » total CF (TCF) and the normalized cloud effect, and they are twice as large as the surface downward solar radiation and cloud transmissivity. This implies that the other cloud properties, such as cloud optical depth and height, have a similar magnitude of disparity to TCF among the GCMs, and suggests that a better agreement among the GCMs in solar radiative fluxes could be the result of compensating errors in either cloud vertical structure, cloud optical depth or cloud fraction. Similar deviation pattern between inter-model and model-measurement suggests that the climate models tend to generate larger bias against observations for those variables with larger inter-model deviation. The simulated TCF from IPCC AR4 GCMs are very scattered through all seasons over three ARM sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). The GCMs perform better at SGP than at Manus and NSA in simulating the seasonal variation and probability distribution of TCF; however, the TCF in these models is remarkably underpredicted and cloud transmissivity is less susceptible to the change of TCF than the observed at SGP. Much larger inter-model deviation and model bias are found over NSA than the other sites in estimating the TCF, cloud transmissivity and cloud-radiation interaction, suggesting that the Arctic region continues to challenge cloud simulations in climate models. Most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels in the tropics. The high altitude CF is much larger in the GCMs than the observation and the inter-model variability of CF also reaches maximum at high levels in the tropics. Most of the GCMs tend to underpredict CF by 50-150% relative to the measurement average at low and middle levels over SGP. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near surface over the Arctic. The internal variability of CF simulated in ensemble runs with the same model is very minimal.« less

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

PubMed Central

Shafapour Tehrany, Mahyat; Solhjouy-fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion. PMID:29576954

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

PubMed

Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion.

Precipitation response to solar geoengineering in a high-resolution tropical-cyclone permitting coupled general circulation model

NASA Astrophysics Data System (ADS)

Irvine, P. J.; Keith, D.; Dykema, J. A.; Vecchi, G. A.; Horowitz, L. W.

2016-12-01

Solar geoengineering may limit or even halt the rise in global-average surface temperatures. Evidence from the geoMIP model intercomparison project shows that idealized geoengineering can greatly reduce temperature changes on a region-by-region basis. If solar geoengineering is used to hold radiative forcing or surface temperatures constant in the face of rising CO2, then the global evaporation and precipitation rates will be reduced below pre-industrial. The spartial and frequency distribution of the precipitation response is, however, much less well understood. There is limited evidence that solar geoengineering may reduce extreme precipitation events more that it reduces mean precipitation, but that evidence is based on relatively course resolution models that may to a poor job representing the distribution of extreme precipitation in the current climate. The response of global and regional climate, as well as tropical cyclone (TC) activity, to increasing solar geoengineering is explored through experiments with climate models spanning a broad range of atmospheric resolutions. Solar geoengineering is represented by an idealized adjustment of the solar constant that roughly halves the rate of increase in radiative forcing in a scenario with increasing CO2 concentration. The coarsest resolution model has approximately a 2-degree global resolution, representative of the typical resolution of past GCMs used to explore global response to CO2 increase, and its response is compared to that of two tropical cyclone permitting GCMs of approximately 0.5 and 0.25 degree resolution (FLOR and HiFLOR). The models have exactly the same ocean and sea-ice components, as well as the same parameterizations and parameter settings. These high-resolution models are used for real-time seasonal prediction, providing a unified framework for seasonal-to-multidecadal climate modeling. We assess the extreme precipitation response, comparing the frequency distribution of extreme events with and without solar geoengineering. We compare our results to two prior studies of the response of climate extremes to solar geoengineering.

Model Independence in Downscaled Climate Projections: a Case Study in the Southeast United States

NASA Astrophysics Data System (ADS)

Gray, G. M. E.; Boyles, R.

2016-12-01

Downscaled climate projections are used to deduce how the climate will change in future decades at local and regional scales. It is important to use multiple models to characterize part of the future uncertainty given the impact on adaptation decision making. This is traditionally employed through an equally-weighted ensemble of multiple GCMs downscaled using one technique. Newer practices include several downscaling techniques in an effort to increase the ensemble's representation of future uncertainty. However, this practice may be adding statistically dependent models to the ensemble. Previous research has shown a dependence problem in the GCM ensemble in multiple generations, but has not been shown in the downscaled ensemble. In this case study, seven downscaled climate projections on the daily time scale are considered: CLAREnCE10, SERAP, BCCA (CMIP5 and CMIP3 versions), Hostetler, CCR, and MACA-LIVNEH. These data represent 83 ensemble members, 44 GCMs, and two generations of GCMs. Baseline periods are compared against the University of Idaho's METDATA gridded observation dataset. Hierarchical agglomerative clustering is applied to the correlated errors to determine dependent clusters. Redundant GCMs across different downscaling techniques show the most dependence, while smaller dependence signals are detected within downscaling datasets and across generations of GCMs. These results indicate that using additional downscaled projections to increase the ensemble size must be done with care to avoid redundant GCMs and the process of downscaling may increase the dependence of those downscaled GCMs. Climate model generation does not appear dissimilar enough to be treated as two separate statistical populations for ensemble building at the local and regional scales.

Evaluation of the Surface Representation of the Greenland Ice Sheet in a General Circulation Model

NASA Technical Reports Server (NTRS)

Cullather, Richard I.; Nowicki, Sophie M. J.; Zhao, Bin; Suarez, Max J.

2014-01-01

Simulated surface conditions of the Goddard Earth Observing System model, version 5 (GEOS 5) atmospheric general circulation model (AGCM) are examined for the contemporary Greenland Ice Sheet (GrIS). A surface parameterization that explicitly models surface processes including snow compaction, meltwater percolation and refreezing, and surface albedo is found to remedy an erroneous deficit in the annual net surface energy flux and provide an adequate representation of surface mass balance (SMB) in an evaluation using simulations at two spatial resolutions. The simulated 1980-2008 GrIS SMB average is 24.7+/-4.5 cm yr(- 1) water-equivalent (w.e.) at.5 degree model grid spacing, and 18.2+/-3.3 cm yr(- 1) w.e. for 2 degree grid spacing. The spatial variability and seasonal cycle of the simulation compare favorably to recent studies using regional climate models, while results from 2 degree integrations reproduce the primary features of the SMB field. In comparison to historical glaciological observations, the coarser resolution model overestimates accumulation in the southern areas of the GrIS, while the overall SMB is underestimated. These changes relate to the sensitivity of accumulation and melt to the resolution of topography. The GEOS-5 SMB fields contrast with available corresponding atmospheric models simulations from the Coupled Model Intercomparison Project (CMIP5). It is found that only a few of the CMIP5 AGCMs examined provide significant summertime runoff, a dominant feature of the GrIS seasonal cycle. This is a condition that will need to be remedied if potential contributions to future eustatic change from polar ice sheets are to be examined with GCMs.

Synchronous precipitation reduction in the American Tropics associated with Heinrich 2.

PubMed

Medina-Elizalde, Martín; Burns, Stephen J; Polanco-Martinez, Josué; Lases-Hernández, Fernanda; Bradley, Raymond; Wang, Hao-Cheng; Shen, Chuan-Chou

2017-09-11

During the last ice age temperature in the North Atlantic oscillated in cycles known as Dansgaard-Oeschger (D-O) events. The magnitude of Caribbean hydroclimate change associated with D-O variability and particularly with stadial intervals, remains poorly constrained by paleoclimate records. We present a 3.3 thousand-year long stalagmite δ 18 O record from the Yucatan Peninsula (YP) that spans the interval between 26.5 and 23.2 thousand years before present. We estimate quantitative precipitation variability and the high resolution and dating accuracy of this record allow us to investigate how rainfall in the region responds to D-O events. Quantitative precipitation estimates are based on observed regional amount effect variability, last glacial paleotemperature records, and estimates of the last glacial oxygen isotopic composition of precipitation based on global circulation models (GCMs). The new precipitation record suggests significant low latitude hydrological responses to internal modes of climate variability and supports a role of Caribbean hydroclimate in helping Atlantic Meridional Overturning Circulation recovery during D-O events. Significant in-phase precipitation reduction across the equator in the tropical Americas associated with Heinrich event 2 is suggested by available speleothem oxygen isotope records.

Analysis of the Arctic system for freshwater cycle intensification: Observations and expectations

USGS Publications Warehouse

Rawlins, M.A.; Steele, M.; Holland, M.M.; Adam, J.C.; Cherry, J.E.; Francis, J.A.; Groisman, P.Y.; Hinzman, L.D.; Huntington, T.G.; Kane, D.L.; Kimball, J.S.; Kwok, R.; Lammers, R.B.; Lee, C.M.; Lettenmaier, D.P.; McDonald, K.C.; Podest, E.; Pundsack, J.W.; Rudels, B.; Serreze, Mark C.; Shiklomanov, A.; Skagseth, O.; Troy, T.J.; Vorosmarty, C.J.; Wensnahan, M.; Wood, E.F.; Woodgate, R.; Yang, D.; Zhang, K.; Zhang, T.

2010-01-01

Hydrologic cycle intensification is an expected manifestation of a warming climate. Although positive trends in several global average quantities have been reported, no previous studies have documented broad intensification across elements of the Arctic freshwater cycle (FWC). In this study, the authors examine the character and quantitative significance of changes in annual precipitation, evapotranspiration, and river discharge across the terrestrial pan-Arctic over the past several decades from observations and a suite of coupled general circulation models (GCMs). Trends in freshwater flux and storage derived from observations across the Arctic Ocean and surrounding seas are also described. With few exceptions, precipitation, evapotranspiration, and river discharge fluxes from observations and the GCMs exhibit positive trends. Significant positive trends above the 90% confidence level, however, are not present for all of the observations. Greater confidence in the GCM trends arises through lower interannual variability relative to trend magnitude. Put another way, intrinsic variability in the observations tends to limit confidence in trend robustness. Ocean fluxes are less certain, primarily because of the lack of long-term observations. Where available, salinity and volume flux data suggest some decrease in saltwater inflow to the Barents Sea (i.e., a decrease in freshwater outflow) in recent decades. A decline in freshwater storage across the central Arctic Ocean and suggestions that large-scale circulation plays a dominant role in freshwater trends raise questions as to whether Arctic Ocean freshwater flows are intensifying. Although oceanic fluxes of freshwater are highly variable and consistent trends are difficult to verify, the other components of the Arctic FWC do show consistent positive trends over recent decades. The broad-scale increases provide evidence that the Arctic FWC is experiencing intensification. Efforts that aim to develop an adequate observation system are needed to reduce uncertainties and to detect and document ongoing changes in all system components for further evidence of Arctic FWC intensification.

Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degrees global warming

NASA Astrophysics Data System (ADS)

Thober, Stephan; Kumar, Rohini; Wanders, Niko; Marx, Andreas; Pan, Ming; Rakovec, Oldrich; Samaniego, Luis; Sheffield, Justin; Wood, Eric F.; Zink, Matthias

2018-01-01

Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 general circulation models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over the entirety of Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow melt equivalent decreases flood events in this region. Neglecting uncertainties originating from internal climate variability, downscaling technique, and hydrologic model parameters, the contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but have to account for significantly higher changes under 3 K global warming.

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.

Comparison of convective clouds observed by spaceborne W-band radar and simulated by cloud-resolving atmospheric models

NASA Astrophysics Data System (ADS)

Dodson, Jason B.

Deep convective clouds (DCCs) play an important role in regulating global climate through vertical mass flux, vertical water transport, and radiation. For general circulation models (GCMs) to simulate the global climate realistically, they must simulate DCCs realistically. GCMs have traditionally used cumulus parameterizations (CPs). Much recent research has shown that multiple persistent unrealistic behaviors in GCMs are related to limitations of CPs. Two alternatives to CPs exist: the global cloud-resolving model (GCRM), and the multiscale modeling framework (MMF). Both can directly simulate the coarser features of DCCs because of their multi-kilometer horizontal resolutions, and can simulate large-scale meteorological processes more realistically than GCMs. However, the question of realistic behavior of simulated DCCs remains. How closely do simulated DCCs resemble observed DCCs? In this study I examine the behavior of DCCs in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and Superparameterized Community Atmospheric Model (SP-CAM), the latter with both single-moment and double-moment microphysics. I place particular emphasis on the relationship between cloud vertical structure and convective environment. I also emphasize the transition between shallow clouds and mature DCCs. The spatial domains used are the tropical oceans and the contiguous United States (CONUS), the latter of which produces frequent vigorous convection during the summer. CloudSat is used to observe DCCs, and A-Train and reanalysis data are used to represent the large-scale environment in which the clouds form. The CloudSat cloud mask and radar reflectivity profiles for CONUS cumuliform clouds (defined as clouds with a base within the planetary boundary layer) during boreal summer are first averaged and compared. Both NICAM and SP-CAM greatly underestimate the vertical growth of cumuliform clouds. Then they are sorted by three large-scale environmental variables: total preciptable water (TPW), surface air temperature (SAT), and 500hPa vertical velocity (W500), representing the dynamical and thermodynamical environment in which the clouds form. The sorted CloudSat profiles are then compared with NICAM and SP-CAM profiles simulated with the Quickbeam CloudSat simulator. Both models have considerable difficulty representing the relationship of SAT and clouds over CONUS. For TPW and W500, shallow clouds transition to DCCs at higher values than observed. This may be an indication of the models' inability to represent the formation of DCCs in marginal convective environments. NICAM develops tall DCCs in highly favorable environments, but SP-CAM appears to be incapable of developing tall DCCs in almost any environment. The use of double moment microphysics in SP-CAM improves the frequency of deep clouds and their relationship with TPW, but not SAT. Both models underpredict radar reflectivity in the upper cloud of mature DCCs. SP-CAM with single moment microphysics has a particularly unrealistic DCC reflectivity profile, but with double moment microphysics it improves substantially. SP-CAM with double-moment microphysics unexpectedly appears to weaken DCC updraft strength as TPW increases, but otherwise both NICAM and SP-CAM represent the environment-versus-DCC relationships fairly realistically.

Predicting 21st-century polar bear habitat distribution from global climate models

USGS Publications Warehouse

Durner, George M.; Douglas, David C.; Nielson, R.M.; Amstrup, Steven C.; McDonald, T.L.; Stirling, I.; Mauritzen, Mette; Born, E.W.; Wiig, O.; Deweaver, E.; Serreze, Mark C.; Belikov, Stanislav; Holland, M.M.; Maslanik, J.; Aars, Jon; Bailey, D.A.; Derocher, A.E.

2009-01-01

Projections of polar bear (Ursus maritimus) sea ice habitat distribution in the polar basin during the 21st century were developed to understand the consequences of anticipated sea ice reductions on polar bear populations. We used location data from satellitecollared polar bears and environmental data (e.g., bathymetry, distance to coastlines, and sea ice) collected from 1985 to 1995 to build resource selection functions (RSFs). RSFs described habitats that polar bears preferred in summer, autumn, winter, and spring. When applied to independent data from 1996 to 2006, the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st-century sea ice concentration projected by 10 general circulation models (GCMs) used in the Intergovernmental Panel of Climate Change Fourth Assessment Report, under the A1B greenhouse gas forcing scenario. Despite variation in their projections, all GCMs indicated habitat losses in the polar basin during the 21st century. Losses in the highest-valued RSF habitat (optimal habitat) were greatest in the southern seas of the polar basin, especially the Chukchi and Barents seas, and least along the Arctic Ocean shores of Banks Island to northern Greenland. Mean loss of optimal polar bear habitat was greatest during summer; from an observed 1.0 million km2 in 1985-1995 (baseline) to a projected multi-model mean of 0.32 million km2 in 2090-2099 (-68% change). Projected winter losses of polar bear habitat were less: from 1.7 million km2 in 1985-1995 to 1.4 million km2 in 2090-2099 (-17% change). Habitat losses based on GCM multi-model means may be conservative; simulated rates of habitat loss during 1985-2006 from many GCMs were less than the actual observed rates of loss. Although a reduction in the total amount of optimal habitat will likely reduce polar bear populations, exact relationships between habitat losses and population demographics remain unknown. Density and energetic effects may become important as polar bears make long-distance annual migrations from traditional winter ranges to remnant high-latitude summer sea ice. These impacts will likely affect specific sex and age groups differently and may ultimately preclude bears from seasonally returning to their traditional ranges.

Future changes in precipitation patterns and extremes: a model-based approach

NASA Astrophysics Data System (ADS)

Mitsakis, Evangelos; Stamos, Iraklis; Anastassiadou, Kalliopi; Kammerer, Harald; Kaundinya, Ingo; Kohl, Bernhard; Kapsomenakis, John; Zerefos, Christos; Aifadopoulou, Georfia

2016-04-01

In recent decades, the Earth has experienced abrupt climate changes, including changes of mean precipitation heights as well as precipitation extremes. It is very likely that the abrupt climate changes which are result of the increase of the greenhouse gases (GHG) concentration (IPCC 2007) will continue with an accelerate magnitude in the coming decades. The modern tool used to project the future climate change is General Circulation Models (GCMs). Due to computational resources limitations, the horizontal resolution of present day GCMs is quite low, usually in the order of hundreds of kilometers. In such a crude resolution many local aspects of the climate are unable to be represented. In addition, the topographical input is equally crude, thus excluding important local features of the topographic forcing. For these reasons downscaling methods have been developed, which input the GCM results producing high resolution localized climate information. Dynamical downscaling is achieved using Regional Climate Models (RCMs) that increase the resolution of the GCMs to even less than 10 km. In that direction, future changes in the mean precipitation as well as precipitation extremes due to the anthropogenic climate change over the area of Greece are examined for various emission scenarios in the framework of this paper (e.g. RCP 8.5, SRES A1B, etc.). Regarding Greece, future changes are based on daily precipitation data from 18 Region Climate Models simulations (6 for RCP 8.5 and 12 for SRES A1B). The changes in precipitation extremes are defined by calculating the changes of nine extreme precipitation indices which are divided in three categories: percentile (R75p, R95p, R99p), absolute threshold (Rmax, R10, R20, R50, RX5day) and duration (CDD) indices, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). Taking into account all the results that are discussed explicitly in the following sections we conclude that the mean precipitation as well as the number of moderate rainy days is projected to decrease over Greece especially in the end of 21th century. Nevertheless the frequency as well as the strength of individual extremely high precipitation events will be increased over the largest part of Greece.

Exploiting Synoptic-Scale Climate Processes to Develop Nonstationary, Probabilistic Flood Hazard Projections

NASA Astrophysics Data System (ADS)

Spence, C. M.; Brown, C.; Doss-Gollin, J.

2016-12-01

Climate model projections are commonly used for water resources management and planning under nonstationarity, but they do not reliably reproduce intense short-term precipitation and are instead more skilled at broader spatial scales. To provide a credible estimate of flood trend that reflects climate uncertainty, we present a framework that exploits the connections between synoptic-scale oceanic and atmospheric patterns and local-scale flood-producing meteorological events to develop long-term flood hazard projections. We demonstrate the method for the Iowa River, where high flow episodes have been found to correlate with tropical moisture exports that are associated with a pressure dipole across the eastern continental United States We characterize the relationship between flooding on the Iowa River and this pressure dipole through a nonstationary Pareto-Poisson peaks-over-threshold probability distribution estimated based on the historic record. We then combine the results of a trend analysis of dipole index in the historic record with the results of a trend analysis of the dipole index as simulated by General Circulation Models (GCMs) under climate change conditions through a Bayesian framework. The resulting nonstationary posterior distribution of dipole index, combined with the dipole-conditioned peaks-over-threshold flood frequency model, connects local flood hazard to changes in large-scale atmospheric pressure and circulation patterns that are related to flooding in a process-driven framework. The Iowa River example demonstrates that the resulting nonstationary, probabilistic flood hazard projection may be used to inform risk-based flood adaptation decisions.

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America

PubMed Central

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data. PMID:27275583

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America.

PubMed

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901-2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011-2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.

Influence of spatial resolution on precipitation simulations for the central Andes Mountains

NASA Astrophysics Data System (ADS)

Trachte, Katja; Bendix, Jörg

2013-04-01

The climate of South America is highly influenced by the north-south oriented Andes Mountains. Their complex structure causes modifications of large-scale atmospheric circulations resulting in various mesoscale phenomena as well as a high variability in the local conditions. Due to their height and length the terrain generates distinctly climate conditions between the western and the eastern slopes. While in the tropical regions along the western flanks the conditions are cold and arid, the eastern slopes are dominated by warm-moist and rainy air coming from the Amazon basin. Below 35° S the situation reverses with rather semiarid conditions in the eastern part and temperate rainy climate along southern Chile. Generally, global circulation models (GCMs) describe the state of the global climate and its changes, but are disabled to capture regional or even local features due to their coarse resolution. This is particularly true in heterogeneous regions such as the Andes Mountains, where local driving features, e. g. local circulation systems, highly varies on small scales and thus, lead to a high variability of rainfall distributions. An appropriate technique to overcome this problem and to gain regional and local scale rainfall information is the dynamical downscaling of the global data using a regional climate model (RCM). The poster presents results of the evaluation of the performance of the Weather Research and Forecasting (WRF) model over South America with special focus on the central Andes Mountains of Ecuador. A sensitivity study regarding the cumulus parametrization, microphysics, boundary layer processes and the radiation budget is conducted. With 17 simulations consisting of 16 parametrization scheme combinations and 1 default run a suitable model set-up for climate research in this region is supposed to be evaluated. The simulations were conducted in a two-way nested mode i) to examine the best physics scheme combination for the target and ii) to analyze the impact of spatial resolution and thus, the representation of the terrain on the result.

Design and Performance of McRas in SCMs and GEOS I/II GCMs

NASA Technical Reports Server (NTRS)

Sud, Yogesh C.; Einaudi, Franco (Technical Monitor)

2000-01-01

The design of a prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) for general circulation models (GCMs) will be discussed. McRAS distinguishes three types of clouds: (1) convective, (2) stratiform, and (3) boundary-layer types. The convective clouds transform and merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the auto-conversion equations 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, as well as diffuse both horizontally and vertically with a fully interactive cloud-microphysics throughout the life-cycle of the cloud, 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 and 5-ARN CART datasets has shown that together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without many systematic errors. The time history and time mean incloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvil and towers, and the convective updraft and downdraft velocities and mass fluxes all show a realistic behavior. Performance of McRAS in GEOS 11 GCM shows several satisfactory features but some of the remaining deficiencies suggest need for additional research involving convective triggers and inhibitors, provision for continuously detraining updraft, a realistic scheme for cumulus gravity wave drag, and refinements to physical conditions for ascertaining cloud detrainment level.

Climate-driven effects of fire on winter habitat for caribou in the Alaskan-Yukon Arctic.

PubMed

Gustine, David D; Brinkman, Todd J; Lindgren, Michael A; Schmidt, Jennifer I; Rupp, T Scott; Adams, Layne G

2014-01-01

Climatic warming has direct implications for fire-dominated disturbance patterns in northern ecosystems. A transforming wildfire regime is altering plant composition and successional patterns, thus affecting the distribution and potentially the abundance of large herbivores. Caribou (Rangifer tarandus) are an important subsistence resource for communities throughout the north and a species that depends on terrestrial lichen in late-successional forests and tundra systems. Projected increases in area burned and reductions in stand ages may reduce lichen availability within caribou winter ranges. Sufficient reductions in lichen abundance could alter the capacity of these areas to support caribou populations. To assess the potential role of a changing fire regime on winter habitat for caribou, we used a simulation modeling platform, two global circulation models (GCMs), and a moderate emissions scenario to project annual fire characteristics and the resulting abundance of lichen-producing vegetation types (i.e., spruce forests and tundra >60 years old) across a modeling domain that encompassed the winter ranges of the Central Arctic and Porcupine caribou herds in the Alaskan-Yukon Arctic. Fires were less numerous and smaller in tundra compared to spruce habitats throughout the 90-year projection for both GCMs. Given the more likely climate trajectory, we projected that the Porcupine caribou herd, which winters primarily in the boreal forest, could be expected to experience a greater reduction in lichen-producing winter habitats (-21%) than the Central Arctic herd that wintered primarily in the arctic tundra (-11%). Our results suggest that caribou herds wintering in boreal forest will undergo fire-driven reductions in lichen-producing habitats that will, at a minimum, alter their distribution. Range shifts of caribou resulting from fire-driven changes to winter habitat may diminish access to caribou for rural communities that reside in fire-prone areas.

Hydrological study of climate change impact on the Llobregat basin

NASA Astrophysics Data System (ADS)

Versini, Pierre-Antoine; Ballinas-Gonzáles, Romeo; Sempere-Torres, Daniel; Escaler, Isabel

2010-05-01

Climate change may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological variables may modify the water cycle: run-off, infiltration, aquifer recharge, etc… In Spain, climate change scenarios describe a general trend to increase temperature and reduced precipitation. This would result in a reduction of available water between 5 and 14% that can rise to 20-22% for the scenarios of the XXI century (AEMET, 2008). This work has focused on studying the impacts of climate change in one of the most important basins in Catalonia (Spain), the Llobregat river basin. It is a highly populated and urbanized catchment, where water resources are used for different purposes, such as drinking water production, agriculture irrigation, industry and hydro-electric energy production. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program) which deals with medium and long-term water resources modelling as a tool for planning and global change adaptation. Usually, to study the impact of climate change, future climate scenarios produced by general circulation models (GCMs) are used. To adapt the large-scale information provided by GCMs to a finer spatial scale required for regional and environmental impact studies, downscaling techniques have been developed. Here, an analogues downscaling method has been applied to simulate daily precipitation projections at rain gauge locations. The HBV hydrological model has been chosen to evaluate the discharges for strategic points (dam, channel and water extractions) in different areas within the watershed. The first results have shown that the water available for supply has a tendency to decrease, implying that measures have to be taken to face the future miss.

Climate-driven effects of fire on winter habitat for caribou in the Alaskan-Yukon Arctic

USGS Publications Warehouse

Gustine, David D.; Brinkman, Todd J.; Lindgren, Michael A.; Schmidt, Jennifer I.; Rupp, T. Scott; Adams, Layne G.

2014-01-01

Climatic warming has direct implications for fire-dominated disturbance patterns in northern ecosystems. A transforming wildfire regime is altering plant composition and successional patterns, thus affecting the distribution and potentially the abundance of large herbivores. Caribou (Rangifer tarandus) are an important subsistence resource for communities throughout the north and a species that depends on terrestrial lichen in late-successional forests and tundra systems. Projected increases in area burned and reductions in stand ages may reduce lichen availability within caribou winter ranges. Sufficient reductions in lichen abundance could alter the capacity of these areas to support caribou populations. To assess the potential role of a changing fire regime on winter habitat for caribou, we used a simulation modeling platform, two global circulation models (GCMs), and a moderate emissions scenario to project annual fire characteristics and the resulting abundance of lichen-producing vegetation types (i.e., spruce forests and tundra >60 years old) across a modeling domain that encompassed the winter ranges of the Central Arctic and Porcupine caribou herds in the Alaskan-Yukon Arctic. Fires were less numerous and smaller in tundra compared to spruce habitats throughout the 90-year projection for both GCMs. Given the more likely climate trajectory, we projected that the Porcupine caribou herd, which winters primarily in the boreal forest, could be expected to experience a greater reduction in lichen-producing winter habitats (−21%) than the Central Arctic herd that wintered primarily in the arctic tundra (−11%). Our results suggest that caribou herds wintering in boreal forest will undergo fire-driven reductions in lichen-producing habitats that will, at a minimum, alter their distribution. Range shifts of caribou resulting from fire-driven changes to winter habitat may diminish access to caribou for rural communities that reside in fire-prone areas.

Circulating neuroactive C21- and C19-steroids in young men before and after ejaculation.

PubMed

Stárka, L; Hill, M; Havlíková, H; Kancheva, L; Sobotka, V

2006-01-01

Twelve neuroactive and neuroprotective steroids, androgens and androgen precursors i.e. 3alpha,17beta-dihydroxy-5alpha-androstane, 3alpha-hydroxy-5alpha-androstan-17-one, 3alpha-hydroxy-5beta-androstan-17-one, androst-5-ene-3beta,17beta-diol, 3beta,17alpha-dihydroxy-pregn-5-en-20-one (17alpha-hydroxy-pregnenolone), 3beta-hydroxy-androst-5-en-17-one (dehydroepiandrosterone, DHEA), testosterone, androst-4-ene-3,17-dione (androstenedione), 3alpha-hydroxy-5alpha-pregnan-20-one (allopregnanolone), 3beta-hydroxy-pregn-5-en-20-one (pregnenolone), 7alpha-hydroxy-DHEA, and 7beta-hydroxy-DHEA were measured using the GC-MS system in young men before and after ejaculation provoked by masturbation. The circulating level of 17alpha-hydroxypregnenolone increased significantly, whereas the other circulating steroids were not changed at all. This fact speaks against the hypothesis that a drop in the level of neuroactive steroids, e.g. allopregnanolone may trigger the orgasm-related increase of oxytocin, reported by other authors.

Modelling climate change impact: A case of bambara groundnut (Vigna subterranea)

NASA Astrophysics Data System (ADS)

Mabhaudhi, Tafadzwanashe; Chibarabada, Tendai Polite; Chimonyo, Vimbayi Grace Petrova; Modi, Albert Thembinkosi

2018-06-01

Climate change projections for southern Africa indicate low and erratic rainfall as well as increasing frequency and intensity of rainfall extremes such as drought. The 2015/16 drought devastated large parts of southern Africa and highlighted the need for drought tolerant crops. Bambara groundnut is an African indigenous crop, commonly cultivated in southern Africa, with a higher potential for drought tolerance compared to other staple legumes. AquaCrop model was used to evaluate the impacts of climate change on yield, water use (ET) and water productivity (WP) of bambara groundnut using climate change data representative of the past (1961-1991), present (1995-2025), mid-century (2030-2060) and late century (2065-2095) obtained from five global circulation models (GCMs). The carbon dioxide (CO2) file selected was for the A2 scenario. The model was run at a sub-catchment level. Model simulations showed that yield and WP of bambara groundnut will increase over time. The mean values of yield at the different time scales across the GCMs showed that yield of bambara groundnut increased by ∼9% from the past to the present, will increase by ∼15% from the present to mid-century and will increase by 6% from mid-to late-century. The simulated results of ET showed seasonal ranges of 703-796 mm. Of this, 45% was lost to soil evaporation, suggesting the need for developing bambara groundnut varieties with faster establishment and high canopy cover. Model simulations showed an increase in WP by ∼13% from the past to present and ∼15% from the present to mid-century and ∼11% from mid-century to late century. While the results of these simulations are preliminary, they confirm the view that bambara groundnut is a potential future crop suitable for cultivation in marginal agricultural production areas. Future research should focus on crop improvement to improve current yield of bambara groundnut.

Insights into the paleoclimate of the PETM from an ensemble of EMIC simulations

NASA Astrophysics Data System (ADS)

Keery, John; Holden, Philip; Edwards, Neil; Monteiro, Fanny; Ridgwell, Andy

2016-04-01

The Eocene epoch, and in particular, the Paleocene-Eocene Thermal Maximum (PETM) of 55.8 Ma, exhibit several features of particular interest for probing our understanding of the Earth system and carbon cycle. CO2 levels have not yet been definitively established, but were known to have varied considerably, peaking at up to several times modern values. Temperatures were several degrees higher than in the modern era, and there were periods of relatively rapid warming, with substantial variability in carbon cycle processes. The Eocene is therefore highly relevant for our understanding of the climate of the 21st Century. Earth system models of intermediate complexity (EMICs), with less detailed simulation of the dynamics of the atmosphere and oceans than general circulation models (GCMs), are sufficiently fast to allow climate modelling over long periods of geological time in comparatively short periods of computer run-time. This speed advantage of EMICs over GCMs permits an "ensemble" of model simulations to be run, allowing statistical analysis of results to be carried out, and allowing the uncertainties in model predictions to be estimated. Here we apply the EMICs PLASIM-GENIE, and GENIE-1, with an Eocene paleogeography which incorporates the major continental configurations and ocean connections, including a shallow strait linking the Arctic to the Tethys, but with neither the Tasman Gateway nor the Drake Passage yet open. Our two model strategy benefits from the detailed simulation of ocean biogeochemistry in GENIE-1, and the 3D spectral atmospheric dynamics in PLASIM-GENIE, which also provides boundary conditions for the GENIE-1 simulations. Using a 50-member ensemble of 1000-year quasi-equilibrium simulations with PLASIM-GENIE, we investigate the relative contributions of orbital and CO2 variability on climate and equator-pole temperature gradients. Results from PLASIM-GENIE are used to configure a harmonised ensemble of GENIE-1 simulations, which will be compared with newly obtained geochemical data on ocean oxygenation through the Eocene from the UK NERC RESPIRE project.

The impact of precipitation evaporation on the atmospheric aerosol distribution in EC-Earth v3.2.0

NASA Astrophysics Data System (ADS)

de Bruine, Marco; Krol, Maarten; van Noije, Twan; Le Sager, Philippe; Röckmann, Thomas

2018-04-01

The representation of aerosol-cloud interaction in global climate models (GCMs) remains a large source of uncertainty in climate projections. Due to its complexity, precipitation evaporation is either ignored or taken into account in a simplified manner in GCMs. This research explores various ways to treat aerosol resuspension and determines the possible impact of precipitation evaporation and subsequent aerosol resuspension on global aerosol burdens and distribution. The representation of aerosol wet deposition by large-scale precipitation in the EC-Earth model has been improved by utilising additional precipitation-related 3-D fields from the dynamical core, the Integrated Forecasting System (IFS) general circulation model, in the chemistry and aerosol module Tracer Model, version 5 (TM5). A simple approach of scaling aerosol release with evaporated precipitation fraction leads to an increase in the global aerosol burden (+7.8 to +15 % for different aerosol species). However, when taking into account the different sizes and evaporation rate of raindrops following Gong et al. (2006), the release of aerosols is strongly reduced, and the total aerosol burden decreases by -3.0 to -8.5 %. Moreover, inclusion of cloud processing based on observations by Mitra et al. (1992) transforms scavenged small aerosol to coarse particles, which enhances removal by sedimentation and hence leads to a -10 to -11 % lower aerosol burden. Finally, when these two effects are combined, the global aerosol burden decreases by -11 to -19 %. Compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, aerosol optical depth (AOD) is generally underestimated in most parts of the world in all configurations of the TM5 model and although the representation is now physically more realistic, global AOD shows no large improvements in spatial patterns. Similarly, the agreement of the vertical profile with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite measurements does not improve significantly. We show, however, that aerosol resuspension has a considerable impact on the modelled aerosol distribution and needs to be taken into account.

Correction of Excessive Precipitation Over Steep and High Mountains in a General Circulation Model

NASA Technical Reports Server (NTRS)

Chao, Winston C.

2012-01-01

Excessive precipitation over steep and high mountains (EPSM) is a well-known problem in GCMs and meso-scale models. This problem impairs simulation and data assimilation products. Among the possible causes investigated in this study, we found that the most important one, by far, is a missing upward transport of heat out of the boundary layer due to the vertical circulations forced by the daytime upslope winds, which are forced by the heated boundary layer on subgrid-scale slopes. These upslope winds are associated with large subgrid-scale topographic variation, which is found over steep and high mountains. Without such subgridscale heat ventilation, the resolvable-scale upslope flow in the boundary layer generated by surface sensible heat flux along the mountain slopes is excessive. Such an excessive resolvablescale upslope flow combined with the high moisture content in the boundary layer results in excessive moisture transport toward mountaintops, which in turn gives rise to EPSM. Other possible causes of EPSM that we have investigated include 1) a poorly-designed horizontal moisture flux in the terrain-following coordinates, 2) the condition for cumulus convection being too easily satisfied at mountaintops, 3) the presence of conditional instability of the computational kind, and 4) the absence of blocked flow drag. These are all minor or inconsequential. We have parameterized the ventilation effects of the subgrid-scale heated-slope-induced vertical circulation (SHVC) by removing heat from the boundary layer and depositing it in layers higher up when the topographic variance exceeds a critical value. Test results using NASA/Goddard's GEOS-S GCM have shown that this largely solved the EPSM problem.

The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

NASA Astrophysics Data System (ADS)

Johnson, Stephanie J.; Levine, Richard C.; Turner, Andrew G.; Martin, Gill M.; Woolnough, Steven J.; Schiemann, Reinhard; Mizielinski, Matthew S.; Roberts, Malcolm J.; Vidale, Pier Luigi; Demory, Marie-Estelle; Strachan, Jane

2016-02-01

The South Asian monsoon is one of the most significant manifestations of the seasonal cycle. It directly impacts nearly one third of the world's population and also has substantial global influence. Using 27-year integrations of a high-resolution atmospheric general circulation model (Met Office Unified Model), we study changes in South Asian monsoon precipitation and circulation when horizontal resolution is increased from approximately 200-40 km at the equator (N96-N512, 1.9°-0.35°). The high resolution, integration length and ensemble size of the dataset make this the most extensive dataset used to evaluate the resolution sensitivity of the South Asian monsoon to date. We find a consistent pattern of JJAS precipitation and circulation changes as resolution increases, which include a slight increase in precipitation over peninsular India, changes in Indian and Indochinese orographic rain bands, increasing wind speeds in the Somali Jet, increasing precipitation over the Maritime Continent islands and decreasing precipitation over the northern Maritime Continent seas. To diagnose which resolution-related processes cause these changes, we compare them to published sensitivity experiments that change regional orography and coastlines. Our analysis indicates that improved resolution of the East African Highlands results in the improved representation of the Somali Jet and further suggests that improved resolution of orography over Indochina and the Maritime Continent results in more precipitation over the Maritime Continent islands at the expense of reduced precipitation further north. We also evaluate the resolution sensitivity of monsoon depressions and lows, which contribute more precipitation over northeast India at higher resolution. We conclude that while increasing resolution at these scales does not solve the many monsoon biases that exist in GCMs, it has a number of small, beneficial impacts.

The impact of greenhouse climate change on the energetics and hydrologic processes of mid-latitude transient eddies

NASA Technical Reports Server (NTRS)

Branscome, Lee E.; Gutowski, William J., Jr.

1991-01-01

Atmospheric transient eddies contribute significantly to mid-latitude energy and water vapor transports. Changes in the global climate, as induced by greenhouse enhancement, will likely alter transient eddy behavior. Unraveling all the feedbacks that occur in general circulation models (GCMs) can be difficult. The transient eddies are isolated from the feedbacks and are focused on the response of the eddies to zonal-mean climate changes that result from CO2-doubling. Using a primitive-equation spectral model, the impact of climate change on the life cycles of transient eddies is examined. Transient eddy behavior in experiments is compared with initial conditions that are given by the zonal-mean climates of the GCMs with current and doubled amounts of CO2. The smaller meridional temperature gradient in a doubled CO2 climate leads to a reduction in eddy kinetic energy, especially in the subtropics. The decrease in subtropical eddy energy is related to a substantial reduction in equatorward flux of eddy activity during the latter part of the life cycle. The reduction in equatorward energy flux alters the moisture cycle. Eddy meridional transport of water vapor is shifted slightly poleward and subtropical precipitation is reduced. The water vapor transport exhibits a relatively small change in magnitude, compared to changes in eddy energy, due to the compensating effect of higher specific humidity in the doubled-CO2 climate. An increase in high-latitude precipitation is related to the poleward shift in eddy water vapor flux. Surface evaporation amplifies climatic changes in water vapor transport and precipitation in the experiments.

Characteristics of Mesoscale Organization in WRF Simulations of Convection during TWP-ICE

NASA Technical Reports Server (NTRS)

Del Genio, Anthony D.; Wu, Jingbo; Chen, Yonghua

2013-01-01

Compared to satellite-derived heating profiles, the Goddard Institute for Space Studies general circulation model (GCM) convective heating is too deep and its stratiform upper-level heating is too weak. This deficiency highlights the need for GCMs to parameterize the mesoscale organization of convection. Cloud-resolving model simulations of convection near Darwin, Australia, in weak wind shear environments of different humidities are used to characterize mesoscale organization processes and to provide parameterization guidance. Downdraft cold pools appear to stimulate further deep convection both through their effect on eddy size and vertical velocity. Anomalously humid air surrounds updrafts, reducing the efficacy of entrainment. Recovery of cold pool properties to ambient conditions over 5-6 h proceeds differently over land and ocean. Over ocean increased surface fluxes restore the cold pool to prestorm conditions. Over land surface fluxes are suppressed in the cold pool region; temperature decreases and humidity increases, and both then remain nearly constant, while the undisturbed environment cools diurnally. The upper-troposphere stratiform rain region area lags convection by 5-6 h under humid active monsoon conditions but by only 1-2 h during drier break periods, suggesting that mesoscale organization is more readily sustained in a humid environment. Stratiform region hydrometeor mixing ratio lags convection by 0-2 h, suggesting that it is strongly influenced by detrainment from convective updrafts. Small stratiform region temperature anomalies suggest that a mesoscale updraft parameterization initialized with properties of buoyant detrained air and evolving to a balance between diabatic heating and adiabatic cooling might be a plausible approach for GCMs.

Projected impacts of climate change on environmental suitability for malaria transmission in West Africa.

PubMed

Yamana, Teresa K; Eltahir, Elfatih A B

2013-10-01

Climate change is expected to affect the distribution of environmental suitability for malaria transmission by altering temperature and rainfall patterns; however, the local and global impacts of climate change on malaria transmission are uncertain. We assessed the effect of climate change on malaria transmission in West Africa. We coupled a detailed mechanistic hydrology and entomology model with climate projections from general circulation models (GCMs) to predict changes in vectorial capacity, an indication of the risk of human malaria infections, resulting from changes in the availability of mosquito breeding sites and temperature-dependent development rates. Because there is strong disagreement in climate predictions from different GCMs, we focused on the GCM projections that produced the best and worst conditions for malaria transmission in each zone of the study area. Simulation-based estimates suggest that in the desert fringes of the Sahara, vectorial capacity would increase under the worst-case scenario, but not enough to sustain transmission. In the transitional zone of the Sahel, climate change is predicted to decrease vectorial capacity. In the wetter regions to the south, our estimates suggest an increase in vectorial capacity under all scenarios. However, because malaria is already highly endemic among human populations in these regions, we expect that changes in malaria incidence would be small. Our findings highlight the importance of rainfall in shaping the impact of climate change on malaria transmission in future climates. Even under the GCM predictions most conducive to malaria transmission, we do not expect to see a significant increase in malaria prevalence in this region.

Downscaling of sea level and fluxes in the Malacca and Singapore Straits using A2 scenario projections of AR4 GCMs

NASA Astrophysics Data System (ADS)

Tkalich, Pavel; Koshebutsky, Volodymyr; Maderich, Vladimir; Thompson, Bijoy

2013-04-01

IPCC-coordinated work has been completed within Fourth Assessment Report (AR4) to project climate and ocean variables for the 21st century using coupled atmospheric-ocean General Circulation Models (GCMs). Resolution of the GCMs is not sufficient to resolve local features of narrow Malacca and Singapore Straits, having complex coastal line and bathymetry; therefore, dynamical downscaling of ocean variables from the global grid to the regional scale is advisable using ocean models, such as Regional Ocean Modeling System (ROMS). ROMS is customized for the domain centered on the Singapore and Malacca Straits, extending from 98°E to 109°E and 6°S to 14°N. Following IPCC methodology, the modelling is done for the past reference period 1961-1990, and then for the 21st century projections; subsequently, established past and projected trends and variability of ocean parameters are inter-compared. Boundary conditions for the past reference period are extracted from Simple Ocean Data Assimilation (SODA), while the projections are made using A2 scenario runs of ECHAM5 and CCSM3 GCMs. Atmospheric forcing for ROMS is downscaled with WRF using ERA-40 dataset for the past period, and outputs of atmospheric variables of respective GCMs for the projections. ROMS-downscaled regional sea level change during 1961-1990, corrected for the global thermosteric effect, land-ice melting and Global Isostatic Adjustment (GIA) effect, corresponds to a mean total trend of 1.52 mm/year, which is higher than the global estimate 1.25 mm/year and observed global sea-level rise (1.44 mm/year) for the same period. Local linear trend in the Singapore Strait (0.9 mm/year) corresponds to the observed trend at Victoria Dock tide gauge (1.1 mm/year) for the past period. Mean discharges through the Karimata, Malacca and Singapore Straits are 0.9, 0.21 and 0.12 Sv, respectively, fall in the range of observations and recent model estimates. A2 scenario projections using ROMS-ECHAM5 and ROMS-CCSM3 for 2011-2099 suggest that linear trends of sea level rise in Singapore Strait are 5.4 and 6.1 mm/year, respectively. These values fall in the range of global estimates of 3.0-8.5 mm/year. Mean sea level rise is expected around 0.43 m (ROMS-ECHAM5) and 0.47 m (ROMS-CCSM3) in 2099 relative to mean sea level in 2011. These values are greater than median estimation of global sea rise 0.32 under scenario A2. Mean discharge through Singapore Strait for scenario A2 during 2011 to 2099 is projected to be 0.062 Sv for ROMS-ECHAM5 and 0.11 Sv for ROMS-CCSM3. These projections are comparable to the discharges during 1961-1990 (0.065 and 0.11 Sv, respectively). The linear trend in discharges for the period 2011-2099 is relatively small with statistical confidence level being less than 95%. An important feature computationally discovered is the transient reversal of flow in the Singapore Strait during southwest monsoon. In general, the reversals of flow in ROMS-ECHAM5 and ROMS-CCSM3 are observed respectively to occur 1/3 and 1/5 of the whole period.

Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

NASA Astrophysics Data System (ADS)

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

The Equatorial Pacific Cold Tongue Simulated by IPCC AR4 Coupled GCMs: Upper Ocean Heat Budget and Feedback Analysis

DTIC Science & Technology

2012-05-15

ET AL .: THE PACIFIC COLD TONGUE BIAS ANALYSIS C05024 circulation, which intensifies the surface easterly winds over the Pacific Basin, further...productivity, and in carbon cycling since it is the major oceanic source of C02 for the atmosphere [Field et al , 1998; Calvo et al , 2011]. Large SST anomalies...used for climate predictions and projec- tions [Neelin et al , 1992; Mechoso et al , 1995; Delecluse et al , 1998; Laufet al , 2001; Davey

Regional Climate Change across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations

NASA Astrophysics Data System (ADS)

Otte, T. L.; Nolte, C. G.; Otte, M. J.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

2011-12-01

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. Preliminary results from downscaling NASA/GISS ModelE simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model will be used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0.

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.

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.

Comparing Mid-Century Climate Change Projections at Convective Resolving Scales (2-km) for Life Zones Within Puerto Rico

NASA Astrophysics Data System (ADS)

Bowden, J.; Wootten, A.; Terando, A. J.; Boyles, R.; Misra, V.; Bhardwaj, A.

2016-12-01

Puerto Rico is home to over 3.5 million people and numerous endemic plant and animal species that may be at risk as a result of anthropogenic climate change. This study downscales three CMIP5 Global Circulation Models (GCMs) to a 2-km horizontal resolution using different regional climate models (RCMs) to resolve the island's climate. Here we compare projected climate change from a single GCM, CCSM4, from two RCMs centered on the mid-century, 2041-2060, for a high greenhouse gas emission scenario, RCP8.5. We will discuss similarities and differences in ecologically relevant climate variables, which were selected based on dialogue with experts who have knowledge about potential biological impacts of climate change for current life zones within Puerto Rico. Notable differences appear between the RCMs and include regions with critical ecosystems, such as the El Yunque National Forest in northeast Puerto Rico. This study helps to highlight RCMs structural uncertainty at convective resolving scales.

Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

NASA Technical Reports Server (NTRS)

Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng

2004-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from MODIS instruments aboard NASA's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.

Influences of climate change on water resources availability in Jinjiang Basin, China.

PubMed

Sun, Wenchao; Wang, Jie; Li, Zhanjie; Yao, Xiaolei; Yu, Jingshan

2014-01-01

The influences of climate change on water resources availability in Jinjiang Basin, China, were assessed using the Block-wise use of the TOPmodel with the Muskingum-Cunge routing method (BTOPMC) distributed hydrological model. The ensemble average of downscaled output from sixteen GCMs (General Circulation Models) for A1B emission scenario (medium CO2 emission) in the 2050s was adopted to build regional climate change scenario. The projected precipitation and temperature data were used to drive BTOPMC for predicting hydrological changes in the 2050s. Results show that evapotranspiration will increase in most time of a year. Runoff in summer to early autumn exhibits an increasing trend, while in the rest period of a year it shows a decreasing trend, especially in spring season. From the viewpoint of water resource availability, it is indicated that it has the possibility that water resources may not be sufficient to fulfill irrigation water demand in the spring season and one possible solution is to store more water in the reservoir in previous summer.

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.

Understanding uncertainty in precipitation changes in a balanced perturbed-physics ensemble under multiple climate forcings

NASA Astrophysics Data System (ADS)

Millar, R.; Ingram, W.; Allen, M. R.; Lowe, J.

2013-12-01

Temperature and precipitation patterns are the climate variables with the greatest impacts on both natural and human systems. Due to the small spatial scales and the many interactions involved in the global hydrological cycle, in general circulation models (GCMs) representations of precipitation changes are subject to considerable uncertainty. Quantifying and understanding the causes of uncertainty (and identifying robust features of predictions) in both global and local precipitation change is an essential challenge of climate science. We have used the huge distributed computing capacity of the climateprediction.net citizen science project to examine parametric uncertainty in an ensemble of 20,000 perturbed-physics versions of the HadCM3 general circulation model. The ensemble has been selected to have a control climate in top-of-atmosphere energy balance [Yamazaki et al. 2013, J.G.R.]. We force this ensemble with several idealised climate-forcing scenarios including carbon dioxide step and transient profiles, solar radiation management geoengineering experiments with stratospheric aerosols, and short-lived climate forcing agents. We will present the results from several of these forcing scenarios under GCM parametric uncertainty. We examine the global mean precipitation energy budget to understand the robustness of a simple non-linear global precipitation model [Good et al. 2012, Clim. Dyn.] as a better explanation of precipitation changes in transient climate projections under GCM parametric uncertainty than a simple linear tropospheric energy balance model. We will also present work investigating robust conclusions about precipitation changes in a balanced ensemble of idealised solar radiation management scenarios [Kravitz et al. 2011, Atmos. Sci. Let.].

Inter-sectoral comparison of model uncertainty of climate change impacts in Africa

NASA Astrophysics Data System (ADS)

van Griensven, Ann; Vetter, Tobias; Piontek, Franzisca; Gosling, Simon N.; Kamali, Bahareh; Reinhardt, Julia; Dinkneh, Aklilu; Yang, Hong; Alemayehu, Tadesse

2016-04-01

We present the model results and their uncertainties of an inter-sectoral impact model inter-comparison initiative (ISI-MIP) for climate change impacts in Africa. The study includes results on hydrological, crop and health aspects. The impact models used ensemble inputs consisting of 20 time series of daily rainfall and temperature data obtained from 5 Global Circulation Models (GCMs) and 4 Representative concentration pathway (RCP). In this study, we analysed model uncertainty for the Regional Hydrological Models, Global Hydrological Models, Malaria models and Crop models. For the regional hydrological models, we used 2 African test cases: the Blue Nile in Eastern Africa and the Niger in Western Africa. For both basins, the main sources of uncertainty are originating from the GCM and RCPs, while the uncertainty of the regional hydrological models is relatively low. The hydrological model uncertainty becomes more important when predicting changes on low flows compared to mean or high flows. For the other sectors, the impact models have the largest share of uncertainty compared to GCM and RCP, especially for Malaria and crop modelling. The overall conclusion of the ISI-MIP is that it is strongly advised to use ensemble modeling approach for climate change impact studies throughout the whole modelling chain.

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Possible Impacts of Global Warming on Hydrology of the Ogallala Aquifer Region

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

Rosenberg, Norman J.; Epstein, Daniel J.; Wang, Dahong

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km{sup 3} (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. We anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water formore » irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO2 concentration (hereafter denoted by[CO2]) in order to estimate the impacts of direct CO2 effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO2-fertilization reverses these losses and yields increase slightly. CO2 fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.« less

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.

Impacts of climate change on the trends of extreme rainfall indices and values of maximum precipitation at Olimpiyat Station, Istanbul, Turkey

NASA Astrophysics Data System (ADS)

Nigussie, Tewodros Assefa; Altunkaynak, Abdusselam

2018-03-01

In this study, extreme rainfall indices of Olimpiyat Station were determined from reference period (1971-2000) and future period (2070-2099) daily rainfall data projected using the HadGEM2-ES and GFDL-ESM2M global circulation models (GCMs) and downscaled by the RegCM4.3.4 regional model under the Representative Concentration Pathway RCP4.5 and RCP8.5 scenarios. The Mann-Kendall (MK) trend statistics was used to detect trends in the indices of each group, and the nonparametric Wilcoxon signed ranks test was employed to identify the presence of differences among the values of the rainfall indices of the three groups. Moreover, the peaks-over-threshold (POT) method was used to undertake frequency analysis and estimate the maximum 24-h rainfall values of various return periods. The results of the M-K-based trend analyses showed that there are insignificant increasing trends in most of the extreme rainfall indices. However, based on the Wilcoxon signed ranks test, the values of the extreme rainfall indices determined for the future period, particularly under RCP8.5, were found to be significantly different from the corresponding values determined for the reference period. The maximum 24-h rainfall amounts of the 50-year return period of the future period under RCP4.5 of the HadGEM2-ES and GFDL-ESM2M GCMs were found to be larger (by 5.85%) than the corresponding value of the reference period by 5.85 and 21.43%, respectively. The results also showed that the maximum 24-h rainfall amount under RCP8.5 of both the HadGEM2-ES and GFDL-ESM2M GCMs was found to be greater (34.33 and 12.18%, respectively, for the 50-year return period) than the reference period values. This may increase the risk of flooding in Ayamama Watershed, and thus, studying the effects of the predicted amount of rainfall under the RCP8.5 scenario on the flooding risk of Ayamama Watershed and devising management strategies are recommended to enhance the design and implementation of adaptation measures.

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.

Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

PubMed Central

Hao, Zhenchun; Ju, Qin; Jiang, Weijuan; Zhu, Changjun

2013-01-01

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least. PMID:23970827

Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: a multi-model analysis with a new set of land-cover change scenarios

NASA Astrophysics Data System (ADS)

Guimberteau, Matthieu; Ciais, Philippe; Ducharne, Agnès; Boisier, Juan Pablo; Dutra Aguiar, Ana Paula; Biemans, Hester; De Deurwaerder, Hannes; Galbraith, David; Kruijt, Bart; Langerwisch, Fanny; Poveda, German; Rammig, Anja; Andres Rodriguez, Daniel; Tejada, Graciela; Thonicke, Kirsten; Von Randow, Celso; Von Randow, Rita C. S.; Zhang, Ke; Verbeeck, Hans

2017-03-01

Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3 °C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14 %, respectively. However, in south-east Amazonia, precipitation decreases by 10 % at the end of the dry season and the three LSMs produce a 6 % decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31 % in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34 % over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27 % in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.

Stochasticity of convection in Giga-LES data

NASA Astrophysics Data System (ADS)

De La Chevrotière, Michèle; Khouider, Boualem; Majda, Andrew J.

2016-09-01

The poor representation of tropical convection in general circulation models (GCMs) is believed to be responsible for much of the uncertainty in the predictions of weather and climate in the tropics. The stochastic multicloud model (SMCM) was recently developed by Khouider et al. (Commun Math Sci 8(1):187-216, 2010) to represent the missing variability in GCMs due to unresolved features of organized tropical convection. The SMCM is based on three cloud types (congestus, deep and stratiform), and transitions between these cloud types are formalized in terms of probability rules that are functions of the large-scale environment convective state and a set of seven arbitrary cloud timescale parameters. Here, a statistical inference method based on the Bayesian paradigm is applied to estimate these key cloud timescales from the Giga-LES dataset, a 24-h large-eddy simulation (LES) of deep tropical convection (Khairoutdinov et al. in J Adv Model Earth Syst 1(12), 2009) over a domain comparable to a GCM gridbox. A sequential learning strategy is used where the Giga-LES domain is partitioned into a few subdomains, and atmospheric time series obtained on each subdomain are used to train the Bayesian procedure incrementally. Convergence of the marginal posterior densities for all seven parameters is demonstrated for two different grid partitions, and sensitivity tests to other model parameters are also presented. A single column model simulation using the SMCM parameterization with the Giga-LES inferred parameters reproduces many important statistical features of the Giga-LES run, without any further tuning. In particular it exhibits intermittent dynamical behavior in both the stochastic cloud fractions and the large scale dynamics, with periods of dry phases followed by a coherent sequence of congestus, deep, and stratiform convection, varying on timescales of a few hours consistent with the Giga-LES time series. The chaotic variations of the cloud area fractions were captured fairly well both qualitatively and quantitatively demonstrating the stochastic nature of convection in the Giga-LES simulation.

An assessment of irrigation needs and crop yield for the United States under potential climate changes

USGS Publications Warehouse

Brumbelow, Kelly; Georgakakos, Aris P.

2000-01-01

Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently, in the response of agricultural systems.

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

Estimating the risk of Amazonian forest dieback.

PubMed

Rammig, Anja; Jupp, Tim; Thonicke, Kirsten; Tietjen, Britta; Heinke, Jens; Ostberg, Sebastian; Lucht, Wolfgang; Cramer, Wolfgang; Cox, Peter

2010-08-01

*Climate change will very likely affect most forests in Amazonia during the course of the 21st century, but the direction and intensity of the change are uncertain, in part because of differences in rainfall projections. In order to constrain this uncertainty, we estimate the probability for biomass change in Amazonia on the basis of rainfall projections that are weighted by climate model performance for current conditions. *We estimate the risk of forest dieback by using weighted rainfall projections from 24 general circulation models (GCMs) to create probability density functions (PDFs) for future forest biomass changes simulated by a dynamic vegetation model (LPJmL). *Our probabilistic assessment of biomass change suggests a likely shift towards increasing biomass compared with nonweighted results. Biomass estimates range between a gain of 6.2 and a loss of 2.7 kg carbon m(-2) for the Amazon region, depending on the strength of CO(2) fertilization. *The uncertainty associated with the long-term effect of CO(2) is much larger than that associated with precipitation change. This underlines the importance of reducing uncertainties in the direct effects of CO(2) on tropical ecosystems.

Adaptation to climate change: changes in farmland use and stocking rate in the U.S.

USGS Publications Warehouse

Mu, Jianhong E.; McCarl, Bruce A.; Wein, Anne M.

2013-01-01

This paper examines possible adaptations to climate change in terms of pasture and crop land use and stocking rate in the United States (U.S.). Using Agricultural Census and climate data in a statistical model, we find that as temperature and precipitation increases agricultural commodity producers respond by reducing crop land and increasing pasture land. In addition, cattle stocking rate decreases as the summer Temperature-humidity Index (THI) increases and summer precipitation decreases. Using the statistical model with climate data from four General Circulation Models (GCMs), we project that land use shifts from cropping to grazing and the stocking rate declines, and these adaptations are more pronounced in the central and the southeast regions of the U.S. Controlling for other farm production variables, crop land decreases by 6 % and pasture land increases by 33 % from the baseline. Correspondingly, the associated economic impact due to adaptation is around -14 and 29 million dollars to crop producers and pasture producers by the end of this century, respectively. The national and regional results have implications for farm programs and subsidy policies.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.

2005-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA's Terra and &la satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which curtails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, &mate models, and global change research projects.

Using MLT Composition Observations to Evaluate Transport in a Comprehensive High Top Model

NASA Astrophysics Data System (ADS)

Smith, A. K.

2016-12-01

Gravity waves play an outsized role in the MLT: driving the mean meridional circulation, exerting a large degree of control over the mean winds and seasonal variations in temperature, and leading to diffusive vertical transport of heat and trace species. These waves are represented using a parameterization in the NCAR Whole Atmosphere Community Climate Model (WACCM), as in many other GCMs. To evaluate their impact, we need to consider not just the mean temperature and wind but the distributions of trace species that are affected by advection due to resolved winds and waves and diffusion associated with gravity wave dissipation. The responses of chemical species to changes in the gravity wave forcing are complex and sometimes unexpected. Transport and diffusion simultaneously affect all species and the heat and momentum budgets; subsequent interactions, and the strong dependence of reaction rates on temperature, affect the net impact of transport on the composition. In evaluating the model, we evaluate the simulations using a range of available observations of composition, including O, O3, CO, CO2, NO, NO2, OH, and H2O.

Trade-Wind Cloudiness and Climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1997-01-01

Closed Mesoscale Cellular Convection (MCC) consists of mesoscale cloud patches separated by narrow clear regions. Strong radiative cooling occurs at the cloud top. A dry two-dimensional Bousinesq model is used to study the effects of cloud-top cooling on convection. Wide updrafts and narrow downdrafts are used to indicate the asymmetric circulations associated with the mesoscale cloud patches. Based on the numerical results, a conceptual model was constructed to suggest a mechanism for the formation of closed MCC over cool ocean surfaces. A new method to estimate the radioative and evaporative cooling in the entrainment layer of a stratocumulus-topped boundary layer has been developed. The method was applied to a set of Large-Eddy Simulation (LES) results and to a set of tethered-balloon data obtained during FIRE. We developed a statocumulus-capped marine mixed layer model which includes a parameterization of drizzle based on the use of a predicted Cloud Condensation Nuclei (CCN) number concentration. We have developed, implemented, and tested a very elaborate new stratiform cloudiness parameterization for use in GCMs. Finally, we have developed a new, mechanistic parameterization of the effects of cloud-top cooling on the entrainment rate.

Response of the Atlantic meridional overturning circulation to a reversal of greenhouse gas increases

NASA Astrophysics Data System (ADS)

Jackson, L. C.; Schaller, N.; Smith, R. S.; Palmer, M. D.; Vellinga, M.

2014-06-01

The reversibility of the Atlantic meridional overturning circulation (AMOC) is investigated in multi-model experiments using global climate models (GCMs) where CO2 concentrations are increased by 1 or 2 % per annum to 2× or 4× preindustrial conditions. After a period of stabilisation the CO2 is decreased back to preindustrial conditions. In most experiments when the CO2 decreases, the AMOC recovers before becoming anomalously strong. This "overshoot" is up to an extra 18.2Sv or 104 % of its preindustrial strength, and the period with an anomalously strong AMOC can last for several hundred years. The magnitude of this overshoot is shown to be related to the build up of salinity in the subtropical Atlantic during the previous period of high CO2 levels. The magnitude of this build up is partly related to anthropogenic changes in the hydrological cycle. The mechanisms linking the subtropical salinity increase to the subsequent overshoot are analysed, supporting the relationship found. This understanding is used to explain differences seen in some models and scenarios. In one experiment there is no overshoot because there is little salinity build up, partly as a result of model differences in the hydrological cycle response to increased CO2 levels and partly because of a less aggressive scenario. Another experiment has a delayed overshoot, possibly as a result of a very weak AMOC in that GCM when CO2 is high. This study identifies aspects of overshoot behaviour that are robust across a multi-model and multi-scenario ensemble, and those that differ between experiments. These results could inform an assessment of the real-world AMOC response to decreasing CO2.

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.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Climate change threatens polar bear populations: a stochastic demographic analysis.

PubMed

Hunter, Christine M; Caswell, Hal; Runge, Michael C; Regehr, Eric V; Amstrup, Steve C; Stirling, Ian

2010-10-01

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in lambda in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log lambdas, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log lambdas approximately - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act.

How Hot was Africa during the Mid-Holocene? Reexamining Africa's Thermal History via integrated Climate and Proxy System Modeling

NASA Astrophysics Data System (ADS)

Dee, S.; Russell, J. M.; Morrill, C.

2017-12-01

Climate models predict Africa will warm by up to 5°C in the coming century. Reconstructions of African temperature since the Last Glacial Maximum (LGM) have made fundamental contributions to our understanding of past, present, and future climate and can help constrain predictions from general circulation models (GCMs). However, many of these reconstructions are based on proxies of lake temperature, so the confounding influences of lacustrine processes may complicate our interpretations of past changes in tropical climate. These proxy-specific uncertainties require robust methodology for data-model comparison. We develop a new proxy system model (PSM) for paleolimnology to facilitate data-model comparison and to fully characterize uncertainties in climate reconstructions. Output from GCMs are used to force the PSM to simulate lake temperature, hydrology, and associated proxy uncertainties. We compare reconstructed East African lake and air temperatures in individual records and in a stack of 9 lake records to those predicted by our PSM forced with Paleoclimate Model Intercomparison Project (PMIP3) simulations, focusing on the mid-Holocene (6 kyr BP). We additionally employ single-forcing transient climate simulations from TraCE (10 kyr to 4 kyr B.P. and historical), as well as 200-yr time slice simulations from CESM1.0 to run the lake PSM. We test the sensitivity of African climate change during the mid-Holocene to orbital, greenhouse gas, and ice-sheet forcing in single-forcing simulations, and investigate dynamical hypotheses for these changes. Reconstructions of tropical African temperature indicate 1-2ºC warming during the mid-Holocene relative to the present, similar to changes predicted in the coming decades. However, most climate models underestimate the warming observed in these paleoclimate data (Fig. 1, 6kyr B.P.). We investigate this discrepancy using the new lake PSM and climate model simulations, with attention to the (potentially non-stationary) relationship between lake surface temperature and air temperature. The data-model comparison helps partition the impacts of lake-specific processes such as energy balance, mixing, sedimentation and bioturbation. We provide new insight into the patterns, amplitudes, sensitivity, and mechanisms of African temperature change.

Climate change threatens polar bear populations: A stochastic demographic analysis

USGS Publications Warehouse

Hunter, C.M.; Caswell, H.; Runge, M.C.; Regehr, E.V.; Amstrup, Steven C.; Stirling, I.

2010-01-01

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in ?? in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log ??s, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log ??s ' - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act. ?? 2010 by the Ecological Society of America.

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).

Application of physical scaling towards downscaling climate model precipitation data

NASA Astrophysics Data System (ADS)

Gaur, Abhishek; Simonovic, Slobodan P.

2018-04-01

Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2-4 day), and long (more than 5-day) precipitation events is projected.

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.

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.

Utilization of an Enhanced Canonical Correlation Analysis (ECCA) to Predict Daily Precipitation and Temperature in a Semi-Arid Environment

NASA Astrophysics Data System (ADS)

Lopez, S. R.; Hogue, T. S.

2011-12-01

Global climate models (GCMs) are primarily used to generate historical and future large-scale circulation patterns at a coarse resolution (typical order of 50,000 km2) and fail to capture climate variability at the ground level due to localized surface influences (i.e topography, marine, layer, land cover, etc). Their inability to accurately resolve these processes has led to the development of numerous 'downscaling' techniques. The goal of this study is to enhance statistical downscaling of daily precipitation and temperature for regions with heterogeneous land cover and topography. Our analysis was divided into two periods, historical (1961-2000) and contemporary (1980-2000), and tested using sixteen predictand combinations from four GCMs (GFDL CM2.0, GFDL CM2.1, CNRM-CM3 and MRI-CGCM2 3.2a. The Southern California area was separated into five county regions: Santa Barbara, Ventura, Los Angeles, Orange and San Diego. Principle component analysis (PCA) was performed on ground-based observations in order to (1) reduce the number of redundant gauges and minimize dimensionality and (2) cluster gauges that behave statistically similarly for post-analysis. Post-PCA analysis included extensive testing of predictor-predictand relationships using an enhanced canonical correlation analysis (ECCA). The ECCA includes obtaining the optimal predictand sets for all models within each spatial domain (county) as governed by daily and monthly overall statistics. Results show all models maintain mean annual and monthly behavior within each county and daily statistics are improved. The level of improvement highly depends on the vegetation extent within each county and the land-to-ocean ratio within the GCM spatial grid. The utilization of the entire historical period also leads to better statistical representation of observed daily precipitation. The validated ECCA technique is being applied to future climate scenarios distributed by the IPCC in order to provide forcing data for regional hydrologic models and assess future water resources in the Southern California region.

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.

Adapting wheat to uncertain future

NASA Astrophysics Data System (ADS)

Semenov, Mikhail; Stratonovitch, Pierre

2015-04-01

This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 RCPs, RCP4.5 and RCP8.5, were integrated with LARS-WG. Climate sensitivity indexes for temperature and precipitation were computed for all GCMs and for 21 regions in the world. For computationally demanding impact assessments, where it is not practical to explore all possible combinations of GCM × RCP, climate sensitivity indexes could be used to select a subset of GCMs from CMIP5 with contrasting climate sensitivity. This would allow to quantify uncertainty in impacts resulting from the CMIP5 ensemble by conducting fewer simulation experiments. As an example, an in silico design of wheat ideotype optimised for future climate scenarios in Europe was described. Two contrasting GCMs were selected for the analysis, "hot" HadGEM2-ES and "cool" GISS-E2-R-CC, along with 2 RCPs. Despite large uncertainty in climate projections, several wheat traits were identified as beneficial for the high-yielding wheat ideotypes that could be used as targets for wheat improvement by breeders.

Sub-seasonal to Seasonal Prediction in the Midst of Uncertainties: Recognizing the Music in What May Seem Like Noises Across this scale

NASA Astrophysics Data System (ADS)

Tiwari, P.; Kar, S. C.; Dey, S.; Mohanty, U. C.

2016-12-01

Sub-seasonal to Seasonal (S2S) prediction has long been considered a predictability desert and forecasting across this scale has received much less attention than medium and seasonal scale. Hoskins (2013) has suggested that there is an urgent need to understand the phenomena and structures that provide the potential sources of predictability across this scale. Therefore, after a problem on this scale and its associated implications in various sectors (for e.g. agriculture and food security, water and health), the question arises whether strategies of S2S prediction that have proved useful elsewhere can they be adapted to the North Indian plains and complex terrain of Himalayas as well? The aim of the present study is in three-folds. Firstly, it attempts to assess the sub seasonal to seasonal predictive skill of six general circulation models (GCMs) for a period of 31 years (1982-2012) and identify forecast windows of opportunity. Secondly, an attempt has been made to reproduce the information of the GCMs at higher resolution using both dynamical and statistical downscaling approaches along with bias correction. Thirdly, an attempt has been also made to use the S2S prediction for water cycle studies as lives of millions of people in North Indian plains depends on water availability from rivers of western Himalayan origin. Finally, the plausible reasons of model failure, potential sources of predictability across this scale and how S2S framework has played a key role in addressing such issues is highlighted. Key words: S2S, predictability, downscaling, water cycle.

Impact of Multiple Scattering on Longwave Radiative Transfer Involving Clouds

DOE PAGES

Kuo, Chia-Pang; Yang, Ping; Huang, Xianglei; ...

2017-12-13

General circulation models (GCMs) are extensively used to estimate the influence of clouds on the global energy budget and other aspects of climate. Because radiative transfer computations involved in GCMs are costly, it is typical to consider only absorption but not scattering by clouds in longwave (LW) spectral bands. In this study, the flux and heating rate biases due to neglecting the scattering of LW radiation by clouds are quantified by using advanced cloud optical property models, and satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth's Radiant Energy System (CERES), and Moderatemore » Resolution Imaging Spectrometer (MODIS) merged products (CCCM). From the products, information about the atmosphere and clouds (microphysical and buck optical properties, and top and base heights) is used to simulate fluxes and heating rates. One-year global simulations for 2010 show that the LW scattering decreases top-of-atmosphere (TOA) upward flux and increases surface downward flux by 2.6 and 1.2 W/m 2, respectively, or approximately 10% and 5% of the TOA and surface LW cloud radiative effect, respectively. Regional TOA upward flux biases are as much as 5% of global averaged outgoing longwave radiation (OLR). LW scattering causes approximately 0.018 K/d cooling at the tropopause and about 0.028 K/d heating at the surface. Furthermore, over 40% of the total OLR bias for ice clouds is observed in 350–500 cm -1. Overall, the radiative effects associated with neglecting LW scattering are comparable to the counterpart due to doubling atmospheric CO 2 under clear-sky conditions.« less

neoPASCAL: A Cubesat-based approach to validate Mars GCMs using a network of landed sensors

NASA Astrophysics Data System (ADS)

Moores, John; Podmore, Hugh; Lee, Regina S. K.; Haberle, Robert

2017-10-01

Beginning in the 1990s, concepts for a network of 15-20 small (12.8 kg) landers to measure surface pressure across Mars were proposed (Merrihew et al., 1996). Such distributed measurements were seen as particularly valuable as they held the promise of validating Mars Global Circulation Models (GCMs), for which the diurnal and seasonal variations in surface pressure may be diagnostically related to atmospheric parameters (Haberle et al., 1996). MicroMET, later renamed PASCAL, was a Discovery contender, however, the total mass required for the 20 landers and a support orbiter presented a challenge compared to the delivered science.In the 20 years since this concept originated, miniaturization of spacecraft systems, sensors and components has made substantial progress. Several small planetary science spacecraft based on the CubeSat design approach will launch in the next few years. Yet, only one meteorological station (REMS) currently operates on the surface of Mars. Meanwhile, the output from atmospheric models have become ever more critical for understanding key Martian geological processes including volatile transport, identifying the extent and persistence of surface brines, understanding the sources and sinks of methane and investigating the past climate of Mars, to name only a few areas.As such, it is time to reconsider the PASCAL concept. We find that modern equipment opens up payload space in the original 12.8 kg entry-vehicles from 23 g to nearly 1 kg, sufficient for adding small imagers, spectrometers and other additional or alternate payloads to examine atmosphere and surface over a wide geographic range of settings. If, instead, we seek the minimum solution for spacecraft mass, we find that a pressure-sensing vehicle would mass < 250 g at entry making these spacecraft appealing secondary payloads for future Mars missions.

The Influence of Runoff and Surface Hydrology on Titan's Weather and Climate

NASA Astrophysics Data System (ADS)

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

2017-12-01

Titan's surface liquid distribution has been shown by general circulation models (GCMs) to greatly influence the hydrological cycle, producing characteristic weather and seasonal climate patterns. Simulations from the Titan Atmospheric Model (TAM) with imposed polar methane "wetlands" reservoirs realistically produce observed cloud features and temperature profiles of Titan's atmosphere, whereas "aquaplanet" simulations with a global methane ocean are not as successful. In addition, wetlands simulations, unlike aquaplanet simulations, demonstrate strong correlations between extreme rainfall behavior and observed geomorphic features, indicating the influential role of precipitation in shaping Titan's surface. The wetlands configuration is, in part, motivated by Titan's large-scale topography featuring low-latitude highlands and high-latitude lowlands, with the implication being that methane may concentrate in the high-latitude lowlands by way of runoff and subsurface flow of a global or regional methane table. However, the extent to which topography controls the surface liquid distribution and thus impacts the global hydrological cycle by driving surface and subsurface flow is unclear. Here we present TAM simulations wherein the imposed wetlands reservoirs are replaced by a surface runoff scheme that allows surface liquid to self-consistently redistribute under the influence of topography. We discuss the impact of surface runoff on the surface liquid distribution over seasonal timescales and compare the resulting hydrological cycle to observed cloud and surface features, as well as to the hydrological cycles of the TAM wetlands and aquaplanet simulations. While still idealized, this more realistic representation of Titan's hydrology provides new insight into the complex interaction between Titan's atmosphere and surface, demonstrates the influence of surface runoff on Titan's global climate, and lays the groundwork for further surface hydrology developments in Titan GCMs, including infiltration and subsurface flow.

The impact of runoff and surface hydrology on Titan's climate

NASA Astrophysics Data System (ADS)

Faulk, Sean; Lora, Juan; Mitchell, Jonathan

2017-10-01

Titan’s surface liquid distribution has been shown by general circulation models (GCMs) to greatly influence the hydrological cycle. Simulations from the Titan Atmospheric Model (TAM) with imposed polar methane “wetlands” reservoirs realistically produce many observed features of Titan’s atmosphere, whereas “aquaplanet” simulations with a global methane ocean are not as successful. In addition, wetlands simulations, unlike aquaplanet simulations, demonstrate strong correlations between extreme rainfall behavior and observed geomorphic features, indicating the influential role of precipitation in shaping Titan’s surface. The wetlands configuration is, in part, motivated by Titan’s large-scale topography featuring low-latitude highlands and high-latitude lowlands, with the implication being that methane may concentrate in the high-latitude lowlands by way of runoff and subsurface flow. However, the extent to which topography controls the surface liquid distribution and thus impacts the global hydrological cycle by driving surface and subsurface flow is unclear. Here we present TAM simulations wherein the imposed wetlands reservoirs are replaced by a surface runoff scheme that allows surface liquid to self-consistently redistribute under the influence of topography. To isolate the singular impact of surface runoff on Titan’s climatology, we run simulations without parameterizations of subsurface flow and topography-atmosphere interactions. We discuss the impact of surface runoff on the surface liquid distribution over seasonal timescales and compare the resulting hydrological cycle to observed cloud and surface features, as well as to the hydrological cycles of the TAM wetlands and aquaplanet simulations. While still idealized, this more realistic representation of Titan’s hydrology provides new insight into the complex interaction between Titan’s atmosphere and surface, demonstrates the influence of surface runoff on Titan’s global climate, and lays the groundwork for further surface hydrology developments in Titan GCMs.

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.

Assessing the Value of Post-processed State-of-the-art Long-term Weather Forecast Ensembles within An Integrated Agronomic Modelling Framework

NASA Astrophysics Data System (ADS)

LI, Y.; Castelletti, A.; Giuliani, M.

2014-12-01

Over recent years, long-term climate forecast from global circulation models (GCMs) has been demonstrated to show increasing skills over the climatology, thanks to the advances in the modelling of coupled ocean-atmosphere dynamics. Improved information from long-term forecast is supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping time) and for more effectively coping with the adverse impacts of climate variability. Yet, evaluating how valuable this information can be is not straightforward and farmers' response must be taken into consideration. Indeed, while long-range forecast are traditionally evaluated in terms of accuracy by comparison of hindcast and observed values, in the context of agricultural systems, potentially useful forecast information should alter the stakeholders' expectation, modify their decisions and ultimately have an impact on their annual benefit. Therefore, it is more desirable to assess the value of those long-term forecasts via decision-making models so as to extract direct indication of probable decision outcomes from farmers, i.e. from an end-to-end perspective. In this work, we evaluate the operational value of thirteen state-of-the-art long-range forecast ensembles against climatology forecast and subjective prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of farmers' behavior. Collected ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and distributed crop simulation model. The agronomic model is first simulated using the forecast information (ex-ante), followed by a second run with actual climate (ex-post). Multi-year simulations are performed to account for climate variability and the value of the different climate forecast is evaluated against the perfect foresight scenario based on the expected crop productivity as well as the land-use decisions. Our results show that not all the products generate beneficial effects to farmers and that the forecast errors might be amplified by the farmers decisions.

Inception of the Laurentide Ice Sheet using asynchronous coupling of a regional atmospheric model and an ice model

NASA Astrophysics Data System (ADS)

Birch, L.; Cronin, T.; Tziperman, E.

2017-12-01

The climate over the past 0.8 million years has been dominated by ice ages. Ice sheets have grown about every 100 kyrs, starting from warm interglacials, until they spanned continents. State-of-the-art global climate models (GCMs) have difficulty simulating glacial inception, or the transition of Earth's climate from an interglacial to a glacial state. It has been suggested that this failure may be related to their poorly resolved local mountain topography, due to their coarse spatial resolution. We examine this idea as well as the possible role of ice flow dynamics missing in GCMs. We investigate the growth of the Laurentide Ice Sheet at 115 kya by focusing on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred. We use the Weather Research and Forecasting model (WRF) in a regional, cloud-resolving configuration with resolved mountain terrain to explore how quickly Baffin Island could become glaciated with the favorable yet realizable conditions of 115 kya insolation, cool summers, and wet winters. Using the model-derived mountain glacier mass balance, we force an ice sheet model based on the shallow-ice approximation, capturing the ice flow that may be critical to the spread of ice sheets away from mountain ice caps. The ice sheet model calculates the surface area newly covered by ice and the change in the ice surface elevation, which we then use to run WRF again. Through this type of iterated asynchronous coupling, we investigate how the regional climate responds to both larger areas of ice cover and changes in ice surface elevation. In addition, we use the NOAH-MP Land model to characterize the importance of land processes, like refreezing. We find that initial ice growth on the Penny Ice Cap causes regional cooling that increases the accumulation on the Barnes Ice Cap. We investigate how ice and topography changes on Baffin Island may impact both the regional climate and the large-scale circulation.

On the Interaction Between Gravity Waves and Atmospheric Thermal Tides

NASA Astrophysics Data System (ADS)

Agner, Ryan Matthew

Gravity waves and thermal tides are two of the most important dynamical features of the atmosphere. They are both generated in the lower atmosphere and propagate upward transporting energy and momentum to the upper atmosphere. This dissertation focuses on the interaction of these waves in the Mesosphere and Lower Thermosphere (MLT) region of the atmosphere using both observational data and Global Circulation Model (GCMs). The first part of this work focuses on observations of gravity wave interactions with the tides using both LIDAR data at the Star Fire Optical Range (SOR, 35?N, 106.5?W) and a meteor radar data at the Andes LIDAR Observatory (ALO, 30.3?S, 70.7?W). At SOR, the gravity waves are shown to enhance or damp the amplitude of the diurnal variations dependent on altitude while the phase is always delayed. The results compare well with previous mechanistic model results and with the Japanese Atmospheric General circulation model for Upper Atmosphere Research (JAGUAR) high resolution global circulation model. The meteor radar observed the GWs to almost always enhance the tidal amplitudes and either delay or advance the phase depending on the altitude. When compared to previous radar results from the same meteor radar when it was located in Maui, Hawaii, the Chile results are very similar while the LIDAR results show significant differences. This is because of several instrument biases when calculating GW momentum fluxes that is not significant when determining the winds. The radar needs to perform large amounts of all-sky averaging across many weeks, while the LIDAR directly detects waves in a small section of sky. The second part of this work focuses on gravity wave parameterization scheme effects on the tides in GCMs. The Specified Dynamics Whole Atmosphere Community Climate Model (SD-WACCM) and the extended Canadian Middle Atmosphere Model (eCMAM) are used for this analysis. The gravity wave parameterization schemes in the eCMAM (Hines scheme) have been shown to enhance the tidal amplitudes compared to observations while the parameterization scheme in SD-WACCM (Lindzen scheme) overdamps the tides. It is shown here that the Hines scheme assumption that only small scale gravity waves force the atmosphere do not create enough drag to properly constrain the tidal amplitudes. The Lindzen scheme produces too much drag because all wave scales are assumed to be saturated thus continuing to provide forcing on the atmosphere above the breaking altitude. The final part of this work investigates GWs, tides and their interactions on a local time scale instead of a global scale in the two GCMs. The local time GWs in eCMAM are found to have a strong seasonal dependence, with the majority of the forcings at the winter pole at latitudes where the diurnal variations are weak limiting their interactions. In SD-WACCM, the largest local GW forcings are located at mid latitudes near where the diurnal variations peak causing them to dampen the diurnal amplitudes. On a local time level the diurnal variations may be a summation of many tidal modes. The analysis reveals that in eCMAM the DW1 tidal mode is by far the dominant mode accounting for the local time variations. The high amount of modulation of GWs by the DW1 tidal winds does not allow it to be properly constrained, causing it to dominate the local time diurnal variations. Similarly, the DW1 projection of GW forcing is dominant over all other other modes and contributes the most to the local time diurnal GW variations. The local time wind variations in SD-WACCM are in uenced by several tidal modes because the DW1 tide is of compatible amplitudes to other modes. This is because of the increased damping on the tide by the GWs. It is also found that the local GW diurnal variations have significant contributions from all tidal modes due to the time and location of the forcing being dependent only on the tropospheric source regions and not the at altitude tidal winds.

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

An international land-biosphere model benchmarking activity for the IPCC Fifth Assessment Report (AR5)

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

Hoffman, Forrest M; Randerson, James T; Thornton, Peter E

2009-12-01

The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less

Ocean circulation drifts in multi-millennial climate simulations: the role of salinity corrections and climate feedbacks

NASA Astrophysics Data System (ADS)

Dentith, Jennifer E.; Ivanovic, Ruza F.; Gregoire, Lauren J.; Tindall, Julia C.; Smith, Robin S.

2018-05-01

Low-resolution, complex general circulation models (GCMs) are valuable tools for studying the Earth system on multi-millennial timescales. However, slowly evolving salinity drifts can cause large shifts in climatic and oceanic regimes over thousands of years. We test two different schemes for neutralising unforced salinity drifts in the FAMOUS GCM: surface flux correction and volumetric flux correction. Although both methods successfully maintain a steady global mean salinity, local drifts and subsequent feedbacks promote cooling (≈ 4 °C over 6000 years) and freshening (≈ 2 psu over 6000 years) in the North Atlantic Ocean, and gradual warming (≈ 0.2 °C per millennium) and salinification (≈ 0.15 psu per millennium) in the North Pacific Ocean. Changes in the surface density in these regions affect the meridional overturning circulation (MOC), such that, after several millennia, the Atlantic MOC (AMOC) is in a collapsed state, and there is a strong, deep Pacific MOC (PMOC). Furthermore, the AMOC exhibits a period of metastability, which is only identifiable with run lengths in excess of 1500 years. We also compare simulations with two different land surface schemes, demonstrating that small biases in the surface climate may cause regional salinity drifts and significant shifts in the MOC (weakening of the AMOC and the initiation then invigoration of PMOC), even when the global hydrological cycle has been forcibly closed. Although there is no specific precursor to the simulated AMOC collapse, the northwest North Pacific and northeast North Atlantic are important areas that should be closely monitored for trends arising from such biases.

Quasi-biennial oscillations of ozone and diabatic circulation in the equatorial stratosphere

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

Hasebe, F.

1994-03-01

The quasi-biennial oscillation (QBO) in ozone in the equatorial stratosphere is obtained by analyzing the Stratospheric Aerosol and Gas Experiment (SAGE) data from 1984 to 1989. The phase of the ozone QBO in the lower stratosphere is found to precede the zonal wind QBO by several months as opposed to the theoretically expected in-phase relationship between the two. A mechanistic model is developed; to explore possible reasons for this disagreement. The model is capable of simulating the actual time evolution of the ozone QBO by introducing the observed zonal wind profile as input. The modeled results confirm the conventional viewmore » that the ozone QBO is generated by the vertical ozone advection that is driven to maintain the temperature structure against radiative damping. However, a series of experiments emphasizes the importance of the feedback of the ozone QBO to the diabatic heating through the absorption of solar radiation. Due to this effect, the phase of the ozone QBO shifts up to a quarter cycle ahead and approaches that of the temperature QBO. Because of this in-phase relationship, the feedback of the ozone QBO to the diabatic heating acts to compensate for the radiative damping of the temperature structure, thus reducing the magnitude of the induced diabatic circulation. Because the reduction of the magnitude of the vertical motion facilitates downward transport of easterly momentum by the mean flow, this feedback process can help to resolve the insufficiency of the easterly momentum in driving the dynamical QBO in GCMs. It should be emphasized that more sophisticated models that allow for full interaction between the chemical species and radiative and dynamical processes should be developed to improve the understanding of both dynamical and ozone QBOs. 48 refs., 13 figs., 2 tabs.« less

Sea Level Rise, Rainfall and Coastal Flooding in Northeastern U.S. Cities Vivien Gornitz, Radley Horton, Philip Orton, Nickitas Georgas, Alan Blumberg, and Cynthia Rosenzweig

NASA Astrophysics Data System (ADS)

Gornitz, V.; Horton, R. M.; Orton, P. M.; Georgas, N.; Blumberg, A. F.; Rosenzweig, C.

2012-12-01

Populations and infrastructure along much of the northeastern coast of the United States will become increasingly vulnerable to the impacts of rising sea level and storm surges over the coming century. This vulnerability is amplified by regional land subsidence and likely also by shifts in ocean circulation. Building upon recent studies for the New York City Panel on Climate Change (NPCC), New York State ClimAid assessment, and the latest U.S. National Climate Assessment, we report new regional sea level rise projections based on the latest CMIP-5 global climate models (GCMs) and RCP emission scenarios, adjusted for revised glacial ice melt contributions, and other factors such as gravitational effects, land water storage, and changes in the Atlantic Meriodional Overturning Circulation (AMOC). Over the coming two years, GCM-derived sea level outputs for future decades will be utilized in risk assessments for coastal flooding in New York City, Boston, and Philadelphia, as part of the Consortium for Climate Risk in the Urban Northeast-RISA project. The Stevens Institute Estuarine and Coastal Ocean Model (sECOM) will be used to produce best estimates (including uncertainty ranges) of sea level rise impacts for a wide range of tropical and extra-tropical cyclones for the 2010s, 2050s, and 2080s. Major improvements over prior studies include (a) the use of a detailed, extensively validated ocean model, and (b) inclusion of rainfall and river flow influences on coastal flooding, which affect flood levels in enclosed tidal waterways (e.g., the Hudson and Delaware Rivers), and which are also likely important in coastal confluence zones of impermeable urbanized watersheds. In addition to the sea level rise results, we present initial model validation results for historical storms.

Modeling the Climatic Effect of Convergent Tectonics During the Middle to Late Miocene: Effective Closure of the Indonesian Seaway, Himalayan Uplift and the East Asian Monsoon

NASA Astrophysics Data System (ADS)

DeConto, R. M.; MacConnell, A.; Leckie, R.

2001-05-01

During the middle to late Miocene, the northward drift of Australia and New Guinea progressively restricted Indonesian throughflow (ITF). Today, ITF plays an important role in modulating inter-basin fresh water flux, heat transport, and the volume of the Western Pacific Warm Pool (WPWP). Today's WPWP is a center for deep convection that contributes considerable diabatic heating to the tropical atmosphere, affecting both the Walker and Hadley circulation. The WPWP fuels the East Asian Monsoon with moisture and latent heat and is an important component of ENSO. As the Indonesian Seaway became restricted, India was impinging on Asia. Asian continentality was increased and Himalayan/Tibetan uplift begun affecting zonal atmospheric flow and land-surface albedo. In order to better understand the climate system's response to changing Miocene paleogeography (horizontal and vertical tectonics), we have begun a series of climate model experiments using atmosphere, ocean, and coupled atmosphere-ocean general circulation models (GCMs). The GCM experiments are designed to isolate the possible response to effective Indonesian gateway closure within the framework of evolving Miocene Paleogeography between 11 and 7 Ma. In the first phase of our modeling study, an AGCM was used to test the sensitivity of tropical Indo-Pacific and Asian climate (including monsoonal intensity) to the presence of a WPWP in a pre and post Himalayan/Tibetan Plateau world. The results of the GCM simulations will be discussed in the context of the hypotheses that 1) a proto-WPWP became established as the Indonesian Seaway became increasingly restricted during the late middle to late Miocene; and 2) the growth of the WPWP had a first order affect on tropical Pacific climate and the East Asian monsoon.

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

NASA Technical Reports Server (NTRS)

Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

2013-01-01

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

Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change.

PubMed

Galbraith, David; Levy, Peter E; Sitch, Stephen; Huntingford, Chris; Cox, Peter; Williams, Mathew; Meir, Patrick

2010-08-01

*The large-scale loss of Amazonian rainforest under some future climate scenarios has generally been considered to be driven by increased drying over Amazonia predicted by some general circulation models (GCMs). However, the importance of rainfall relative to other drivers has never been formally examined. *Here, we conducted factorial simulations to ascertain the contributions of four environmental drivers (precipitation, temperature, humidity and CO(2)) to simulated changes in Amazonian vegetation carbon (C(veg)), in three dynamic global vegetation models (DGVMs) forced with climate data based on HadCM3 for four SRES scenarios. *Increased temperature was found to be more important than precipitation reduction in causing losses of Amazonian C(veg) in two DGVMs (Hyland and TRIFFID), and as important as precipitation reduction in a third DGVM (LPJ). Increases in plant respiration, direct declines in photosynthesis and increases in vapour pressure deficit (VPD) all contributed to reduce C(veg) under high temperature, but the contribution of each mechanism varied greatly across models. Rising CO(2) mitigated much of the climate-driven biomass losses in the models. *Additional work is required to constrain model behaviour with experimental data under conditions of high temperature and drought. Current models may be overly sensitive to long-term elevated temperatures as they do not account for physiological acclimation.

Evaluating Impacts of climate and land use changes on streamflow using SWAT and land use models based CESM1-CAM5 Climate scenarios

NASA Astrophysics Data System (ADS)

Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu

2015-04-01

Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change

Simple physical-empirical model of the precipitation distribution based on a tropical sea surface temperature threshold and the effects of climate change

NASA Astrophysics Data System (ADS)

Jauregui, Yakelyn R.; Takahashi, Ken

2018-03-01

The observed nonlinear relationship between tropical sea surface temperature (T_s) and precipitation ( P) on climate timescales, by which a threshold (T_c) must be exceeded by T_s in order for deep convection to occur, is the basis of a physical-empirical model (PEM) that we fitted to observational data and CMIP5 climate model output and used to show that, with essentially only two constant parameters (T_c and the sensitivity a_1 of P to T_s>T_c), it provides a useful first-order description of the climatological and interannual variability of the large-scale distribution of tropical P given T_s, as well as of the biases of the Global Climate Models (GCMs). A substantial limitation is its underestimation of the peak P in the convergence zones, as the necessary processes associated with the atmospheric circulation are not considered. The pattern of the intermodel correlation between the mean T_s-T_c for each GCM and the average P distribution is in agreement with the double ITCZ bias, featuring roughly zonally-symmetric off-equatorial maxima, rather than being regionally or hemispherically restricted. The inter-comparison of GCMs indicates a relationship between T_c with the near-equatorial low-level (850 hPa) tropospheric temperature, consistent with the interpretation that it is a measure of the convective inhibition (CIN). The underestimation of T_c is linked to the cold free tropospheric bias in the GCMs. However, the discrepancy among the observational datasets is a limitation for assessing the GCM biases from the PEM framework quantitatively. Under the RCP4.5 climate change scenario, T_c increases slightly more than the mean tropical T_s, implying a stabilizing trend consistent with the amplified free tropospheric warming relative to the surface. However, since a_1 increases by 10-50%/°C with the surface warming, its effect dominates and results in generally positive precipitation change (Δ P) in the equatorial regions. In the equatorial eastern-central Pacific cold tongue, Δ (T_s-T_c) is positive, but the absolute T_s-T_c remains small, which explains the double band pattern of Δ P along the equatorial flanks of the spuriously strong double ITCZs. When the GCM biases are corrected in the PEM, the positive Δ P in the southeast Pacific and Atlantic oceans is substantially reduced.

When could global warming reach 4°C?

PubMed

Betts, Richard A; Collins, Matthew; Hemming, Deborah L; Jones, Chris D; Lowe, Jason A; Sanderson, Michael G

2011-01-13

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) assessed a range of scenarios of future greenhouse-gas emissions without policies to specifically reduce emissions, and concluded that these would lead to an increase in global mean temperatures of between 1.6°C and 6.9°C by the end of the twenty-first century, relative to pre-industrial. While much political attention is focused on the potential for global warming of 2°C relative to pre-industrial, the AR4 projections clearly suggest that much greater levels of warming are possible by the end of the twenty-first century in the absence of mitigation. The centre of the range of AR4-projected global warming was approximately 4°C. The higher end of the projected warming was associated with the higher emissions scenarios and models, which included stronger carbon-cycle feedbacks. The highest emissions scenario considered in the AR4 (scenario A1FI) was not examined with complex general circulation models (GCMs) in the AR4, and similarly the uncertainties in climate-carbon-cycle feedbacks were not included in the main set of GCMs. Consequently, the projections of warming for A1FI and/or with different strengths of carbon-cycle feedbacks are often not included in a wider discussion of the AR4 conclusions. While it is still too early to say whether any particular scenario is being tracked by current emissions, A1FI is considered to be as plausible as other non-mitigation scenarios and cannot be ruled out. (A1FI is a part of the A1 family of scenarios, with 'FI' standing for 'fossil intensive'. This is sometimes erroneously written as A1F1, with number 1 instead of letter I.) This paper presents simulations of climate change with an ensemble of GCMs driven by the A1FI scenario, and also assesses the implications of carbon-cycle feedbacks for the climate-change projections. Using these GCM projections along with simple climate-model projections, including uncertainties in carbon-cycle feedbacks, and also comparing against other model projections from the IPCC, our best estimate is that the A1FI emissions scenario would lead to a warming of 4°C relative to pre-industrial during the 2070s. If carbon-cycle feedbacks are stronger, which appears less likely but still credible, then 4°C warming could be reached by the early 2060s in projections that are consistent with the IPCC's 'likely range'.

Rebased Global Mean Temperature comparisons between Global Climate Models and observed Global Mean Temperature: constraints and implications

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2017-12-01

One of the benchmarks of global climate models (GCMs) is that their slow, decadal or longer timescale variations in past changes in Global Mean Temperature (GMT) track each other [1] and the observed GMT reasonably closely. However, the different GCMs tend to generate GMT time-series which have absolute values that are offset with respect to each other by as much as 3 degrees [2]. Subtracting these offsets, or rebasing, is an integral part of comparisons between observed past GMT and the GMT anomalies generated by ensembles of GCMs. We will formalize how rebasing introduces constraints in how the GCMs are related to each other. The GMT of a given GCM is a macroscopic reduced variable that tracks a subset of the full information contained in the time evolving solution of that GCM. If the GMT slow timescale dynamics of different GCMs is to a good approximation the same subject to a linear translation, then the phenomenology captured by this dynamics is essentially linear. Feedbacks in the different models when expressed through GMT are then to leading order linear. It then follows that a linear energy balance evolution equation for GMT is sufficient to reproduce the slow timescale GMT dynamics, given the appropriate effective heat capacity and feedback parameters. As a consequence, the GMT timeseries future projections generated by the GCMs may underestimate the impact of, and uncertainty in, the outcomes of future forcing scenarios. The offset subtraction procedure identifies a slow time-scale dynamics in model generated GMT. Fluctuations on much faster timescales do not typically track each other from one GCM to another, with the exception of major forcing events such as volcanic eruptions. This suggests that the GMT time-series can be decomposed into a slow and fast timescale which naturally leads to stochastic reduced energy balance models for GMT. [1] IPCC Chapter 9 P743 and fig 9.8, IPCC TS.1 [2] see e.g. [Mauritsen et al., Tuning the Climate of a Global Model, Journal of Advances in Modelling Earth Systems, 2012]4, IPCC SPM.6

Intercomparison of Radiation Codes in Climate Models (ICRCCM) Infrared (Clear-Sky) Line-by Line Radiative Fluxes (DB1002)

DOE Data Explorer

Arking, A.; Ridgeway, B.; Clough, T.; Iacono, M.; Fomin, B.; Trotsenko, A.; Freidenreich, S.; Schwarzkopf, D.

1994-01-01

The intercomparison of Radiation Codes in Climate Models (ICRCCM) study was launched under the auspices of the World Meteorological Organization and with the support of the U.S. Department of Energy to document differences in results obtained with various radiation codes and radiation parameterizations in general circulation models (GCMs). ICRCCM produced benchmark, longwave, line-by-line (LBL) fluxes that may be compared against each other and against models of lower spectral resolution. During ICRCCM, infrared fluxes and cooling rates for several standard model atmospheres with varying concentrations of water vapor, carbon dioxide, and ozone were calculated with LBL methods at resolutions of 0.01 cm-1 or higher. For comparison with other models, values were summed for the IR spectrum and given at intervals of 5 or 10 cm-1. This archive contains fluxes for ICRCCM-prescribed clear-sky cases. Radiative flux and cooling-rate profiles are given for specified atmospheric profiles for temperature, water vapor, and ozone-mixing ratios. The archive contains 328 files, including spectral summaries, formatted data files, and a variety of programs (i.e., C-shell scripts, FORTRAN codes, and IDL programs) to read, reformat, and display data. Collectively, these files require approximately 59 MB of disk space.

Coupled impacts of climate and land use change across a river-lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000-2040

NASA Astrophysics Data System (ADS)

Zia, Asim; Bomblies, Arne; Schroth, Andrew W.; Koliba, Christopher; Isles, Peter D. F.; Tsai, Yushiou; Mohammed, Ibrahim N.; Bucini, Gabriela; Clemins, Patrick J.; Turnbull, Scott; Rodgers, Morgan; Hamed, Ahmed; Beckage, Brian; Winter, Jonathan; Adair, Carol; Galford, Gillian L.; Rizzo, Donna; Van Houten, Judith

2016-11-01

Global climate change (GCC) is projected to bring higher-intensity precipitation and higher-variability temperature regimes to the Northeastern United States. The interactive effects of GCC with anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrient fluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated by warmer water temperatures due to GCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCC on the hydrological regime, water temperature, water quality, bloom duration and severity through 2040 in transnational Lake Champlain’s Missisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-based model was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrological model to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulated with a 3D hydrodynamic-biogeochemical model. We find accelerated GCC could drastically limit land management options to maintain water quality, but the nature and severity of this impact varies dramatically by GCM and GCC scenario.

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

Impacts of climate change on peanut yield in China simulated by CMIP5 multi-model ensemble projections

NASA Astrophysics Data System (ADS)

Xu, Hanqing; Tian, Zhan; Zhong, Honglin; Fan, Dongli; Shi, Runhe; Niu, Yilong; He, Xiaogang; Chen, Maosi

2017-09-01

Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years' (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.

Future climate impacts on maize farming and food security in Malawi

NASA Astrophysics Data System (ADS)

Stevens, Tilele; Madani, Kaveh

2016-11-01

Agriculture is the mainstay of Malawi’s economy and maize is the most important crop for food security. As a Least Developed Country (LDC), adverse effects of climate change (CC) on agriculture in Malawi are expected to be significant. We examined the impacts of CC on maize production and food security in Malawi’s dominant cereal producing region, Lilongwe District. We used five Global Circulation Models (GCMs) to make future (2011 to 2100) rainfall and temperature projections and simulated maize yields under these projections. Our future rainfall projections did not reveal a strong increasing or decreasing trend, but temperatures are expected to increase. Our crop modelling results, for the short-term future, suggest that maize farming might benefit from CC. However, faster crop growth could worsen Malawi’s soil fertility problem. Increasing temperature could drive lower maize yields in the medium to long-term future. Consequently, up to 12% of the population in Lilongwe District might be vulnerable to food insecurity by the end of the century. Measures to increase soil fertility and moisture must be developed to build resilience into Malawi’s agriculture sector.

Influences of Climate Change on Water Resources Availability in Jinjiang Basin, China

PubMed Central

Wang, Jie; Li, Zhanjie; Yao, Xiaolei

2014-01-01

The influences of climate change on water resources availability in Jinjiang Basin, China, were assessed using the Block-wise use of the TOPmodel with the Muskingum-Cunge routing method (BTOPMC) distributed hydrological model. The ensemble average of downscaled output from sixteen GCMs (General Circulation Models) for A1B emission scenario (medium CO2 emission) in the 2050s was adopted to build regional climate change scenario. The projected precipitation and temperature data were used to drive BTOPMC for predicting hydrological changes in the 2050s. Results show that evapotranspiration will increase in most time of a year. Runoff in summer to early autumn exhibits an increasing trend, while in the rest period of a year it shows a decreasing trend, especially in spring season. From the viewpoint of water resource availability, it is indicated that it has the possibility that water resources may not be sufficient to fulfill irrigation water demand in the spring season and one possible solution is to store more water in the reservoir in previous summer. PMID:24701192

Nonlinear Eddy-Eddy Interactions in Dry Atmospheres Macroturbulence

NASA Astrophysics Data System (ADS)

Ait Chaalal, F.; Schneider, T.

2012-12-01

The statistical moment equations derived from the atmospheric equation of motions are not closed. However neglecting the large-scale eddy-eddy nonlinear interactions in an idealized dry general circulation model (GCM), which is equivalent to truncating the moment equations at the second order, can reproduce some of the features of the general circulation ([1]), highlighting the significance of eddy-mean flow interactions and the weakness of eddy-eddy interactions in atmospheric macroturbulence ([2]). The goal of the present study is to provide new insight into the rôle of these eddy-eddy interactions and discuss the relevance of a simple stochastic parametrization to represent them. We investigate in detail the general circulation in an idealized dry GCM, comparing full simulations with simulations where the eddy-eddy interactions are removed. The radiative processes are parametrized through Newtonian relaxation toward a radiative-equilibrium state with a prescribed equator to pole temperature contrast. A convection scheme relaxing toward a prescribed convective vertical lapse rate mimics some aspects of moist convection. The study is performed over a wide range of parameters covering the planetary rotation rate, the equator to pole temperature contrast and the vertical lapse rate. Particular attention is given to the wave-mean flow interactions and to the spectral budget. It is found that the no eddy-eddy simulations perform well when the baroclinic activity is weaker, for example for lower equator to pole temperature contrasts or higher rotation rates: the mean meridional circulation is well reproduced, with realistic eddy-driven jets and energy-containing eddy length scales of the order of the Rossby deformation radius. For a stronger baroclinic activity the no eddy-eddy model does not achieve a realistic isotropization of the eddies, the meridional circulation is compressed in the meridional direction and secondary eddy-driven jets emerge. In addition, the baroclinic wave activity does not reach the upper troposphere in association with a very weak or absent Rossby wave absorption in the upper subtropical troposphere. Understanding these deficiencies and the rôle of the eddy-eddy nonlinear interactions in determining the mean meridional circulation paves the way to the development of stochastic third order moments parametrizations, to eventually build GCMs that directly solve for the flow statistics and that could provide a deeper understanding of anthropogenic and natural climate changes. [1] O'Gorman, P. A., & Schneider, T. 2007, Geophysical Research Letters, 34, 22801 [2] Schneider, T., and C. C. Walker, 2006, Journal of the Atmospheric Sciences, 63, 1569-1586.

The mid-cretaceous water bearer: Isotope mass balance quantification of the Albian hydrologic cycle

USGS Publications Warehouse

Ufnar, David F.; Gonzalez, Luis A.; Ludvigson, Greg A.; Brenner, Richard L.; Witzke, B.J.

2002-01-01

A latitudinal gradient in meteoric ??18O compositions compiled from paleosol sphaerosiderites throughout the Cretaceous Western Interior Basin (KWIB) (34-75??N paleolatitude) exhibits a steeper, more depleted trend than modern (predicted) values (3.0??? [34??N latitude] to 9.7??? [75??N] lighter). Furthermore, the sphaerosiderite meteoric ??18O latitudinal gradient is significantly steeper and more depleted (5.8??? [34??N] to 13.8??? [75??N] lighter) than a predicted gradient for the warm mid-Cretaceous using modern empirical temperature-??18O precipitation relationships. We have suggested that the steeper and more depleted (relative to the modern theoretical gradient) meteoric sphaerosiderite ??18O latitudinal gradient resulted from increased air mass rainout effects in coastal areas of the KWIB during the mid-Cretaceous. The sphaerosiderite isotopic data have been used to constrain a mass balance model of the hydrologic cycle in the northern hemisphere and to quantify precipitation rates of the equable 'greenhouse' Albian Stage in the KWIB. The mass balance model tracks the evolving isotopic composition of an air mass and its precipitation, and is driven by latitudinal temperature gradients. Our simulations indicate that significant increases in Albian precipitation (34-52%) and evaporation fluxes (76-96%) are required to reproduce the difference between modern and Albian meteoric siderite ??18O latitudinal gradients. Calculations of precipitation rates from model outputs suggest mid-high latitude precipitation rates greatly exceeded modern rates (156-220% greater in mid latitudes [2600-3300 mm/yr], 99% greater at high latitudes [550 mm/yr]). The calculated precipitation rates are significantly different from the precipitation rates predicted by some recent general circulation models (GCMs) for the warm Cretaceous, particularly in the mid to high latitudes. Our mass balance model by no means replaces GCMs. However, it is a simple and effective means of obtaining quantitative data regarding the mid-Cretaceous hydrologic cycle in the KWIB. Our goal is to encourage the incorporation of isotopic tracers into GCM simulations of the mid-Cretaceous, and to show how our empirical data and mass balance model estimates help constrain the boundary conditions. ?? 2002 Elsevier Science B.V. All rights reserved.

Assessment of impacts of climate change on surface water availability using coupled SWAT and WEAP models: case of upper Pangani River Basin, Tanzania

NASA Astrophysics Data System (ADS)

Kishiwa, Peter; Nobert, Joel; Kongo, Victor; Ndomba, Preksedis

2018-05-01

This study was designed to investigate the dynamics of current and future surface water availability for different water users in the upper Pangani River Basin under changing climate. A multi-tier modeling technique was used in the study, by coupling the Soil and Water Assessment Tool (SWAT) and Water Evaluation And Planning (WEAP) models, to simulate streamflows under climate change and assess scenarios of future water availability to different socio-economic activities by year 2060. Six common Global Circulation Models (GCMs) from WCRP-CMIP3 with emissions Scenario A2 were selected. These are HadCM3, HadGEM1, ECHAM5, MIROC3.2MED, GFDLCM2.1 and CSIROMK3. They were downscaled by using LARS-WG to station scale. The SWAT model was calibrated with observed data and utilized the LARS-WG outputs to generate future streamflows before being used as input to WEAP model to assess future water availability to different socio-economic activities. GCMs results show future rainfall increase in upper Pangani River Basin between 16-18 % in 2050s relative to 1980-1999 periods. Temperature is projected to increase by an average of 2 °C in 2050s, relative to baseline period. Long-term mean streamflows is expected to increase by approximately 10 %. However, future peak flows are estimated to be lower than the prevailing average peak flows. Nevertheless, the overall annual water demand in Pangani basin will increase from 1879.73 Mm3 at present (2011) to 3249.69 Mm3 in the future (2060s), resulting to unmet demand of 1673.8 Mm3 (51.5 %). The impact of future shortage will be more severe in irrigation where 71.12 % of its future demand will be unmet. Future water demands of Hydropower and Livestock will be unmet by 27.47 and 1.41 % respectively. However, future domestic water use will have no shortage. This calls for planning of current and future surface water use in the upper Pangani River Basin.

Toward improving hurricane forecasts using the JPL Tropical Cyclone Information System (TCIS): A framework to address the issues of Big Data

NASA Astrophysics Data System (ADS)

Hristova-Veleva, S. M.; Boothe, M.; Gopalakrishnan, S.; Haddad, Z. S.; Knosp, B.; Lambrigtsen, B.; Li, P.; montgomery, M. T.; Niamsuwan, N.; Tallapragada, V. S.; Tanelli, S.; Turk, J.; Vukicevic, T.

2013-12-01

Accurate forecasting of extreme weather requires the use of both regional models as well as global General Circulation Models (GCMs). The regional models have higher resolution and more accurate physics - two critical components needed for properly representing the key convective processes. GCMs, on the other hand, have better depiction of the large-scale environment and, thus, are necessary for properly capturing the important scale interactions. But how to evaluate the models, understand their shortcomings and improve them? Satellite observations can provide invaluable information. And this is where the issues of Big Data come: satellite observations are very complex and have large variety while model forecast are very voluminous. We are developing a system - TCIS - that addresses the issues of model evaluation and process understanding with the goal of improving the accuracy of hurricane forecasts. This NASA/ESTO/AIST-funded project aims at bringing satellite/airborne observations and model forecasts into a common system and developing on-line tools for joint analysis. To properly evaluate the models we go beyond the comparison of the geophysical fields. We input the model fields into instrument simulators (NEOS3, CRTM, etc.) and compute synthetic observations for a more direct comparison to the observed parameters. In this presentation we will start by describing the scientific questions. We will then outline our current framework to provide fusion of models and observations. Next, we will illustrate how the system can be used to evaluate several models (HWRF, GFS, ECMWF) by applying a couple of our analysis tools to several hurricanes observed during the 2013 season. Finally, we will outline our future plans. Our goal is to go beyond the image comparison and point-by-point statistics, by focusing instead on understanding multi-parameter correlations and providing robust statistics. By developing on-line analysis tools, our framework will allow for consistent model evaluation, providing results that are much more robust than those produced by case studies - the current paradigm imposed by the Big Data issues (voluminous data and incompatible analysis tools). We believe that this collaborative approach, with contributions of models, observations and analysis approaches used by the research and operational communities, will help untangle the complex interactions that lead to hurricane genesis and rapid intensity changes - two processes that still pose many unanswered questions. The developed framework for evaluation of the global models will also have implications for the improvement of the climate models, which output only a limited amount of information making it difficult to evaluate them. Our TCIS will help by investigating the GCMs under current weather scenarios and with much more detailed model output, making it possible to compare the models to multiple observed parameters to help narrow down the uncertainty in their performance. This knowledge could then be transferred to the climate models to lower the uncertainty in their predictions. The work described here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

On the Seasonality of Sudden Stratospheric Warmings

NASA Astrophysics Data System (ADS)

Reichler, T.; Horan, M.

2017-12-01

The downward influence of sudden stratospheric warmings (SSWs) creates significant tropospheric circulation anomalies that last for weeks. It is therefore of theoretical and practical interest to understand the time when SSWs are most likely to occur and the controlling factors for the temporal distribution of SSWs. Conceivably, the distribution between mid-winter and late-winter is controlled by the interplay between decreasing eddy convergence in the region of the polar vortex and the weakening strength of the polar vortex. General circulation models (GCMs) tend to produce SSW maxima later in winter than observations, which has been considered as a model deficiency. However, the observed record is short, suggesting that under-sampling of SSWs may contribute to this discrepancy. Here, we study the climatological frequency distribution of SSWs and related events in a long control simulation with a stratosphere resolving GCM. We also create a simple statistical model to determine the primary factors controlling the SSW distribution. The statistical model is based on the daily climatological mean, standard deviation, and autocorrelation of stratospheric winds, and assumes that the winds follow a normal distribution. We find that the null hypothesis, that model and observations stem from the same distribution, cannot be rejected, suggesting that the mid-winter SSW maximum seen in the observations is due to sampling uncertainty. We also find that the statistical model faithfully reproduces the seasonal distribution of SSWs, and that the decreasing climatological strength of the polar vortex is the primary factor for it. We conclude that the late-winter SSW maximum seen in most models is realistic and that late events will be more prominent in future observations. We further conclude that SSWs simply form the tail of normally distributed stratospheric winds, suggesting that there is a continuum of weak polar vortex states and that statistically there is nothing special about the zero-threshold used to define SSWs.

A new general circulation model of Jupiter's atmosphere based on the UKMO Unified Model: Three-dimensional evolution of isolated vortices and zonal jets in mid-latitudes

NASA Astrophysics Data System (ADS)

Yamazaki, Y. H.; Skeet, D. R.; Read, P. L.

2004-04-01

We have been developing a new three-dimensional general circulation model for the stratosphere and troposphere of Jupiter based on the dynamical core of a portable version of the Unified Model of the UK Meteorological Office. Being one of the leading terrestrial GCMs, employed for operational weather forecasting and climate research, the Unified Model has been thoroughly tested and performance tuned for both vector and parallel computers. It is formulated as a generalized form of the standard primitive equations to handle a thick atmosphere, using a scaled pressure as the vertical coordinate. It is able to accurately simulate the dynamics of a three-dimensional fully compressible atmosphere on the whole or a part of a spherical shell at high spatial resolution in all three directions. Using the current version of the GCM, we examine the characteristics of the Jovian winds in idealized configurations based on the observed vertical structure of temperature. Our initial focus is on the evolution of isolated eddies in the mid-latitudes. Following a brief theoretical investigation of the vertical structure of the atmosphere, limited-area cyclic channel domains are used to numerically investigate the nonlinear evolution of the mid-latitude winds. First, the evolution of deep and shallow cyclones and anticyclones are tested in the atmosphere at rest to identify a preferred horizontal and vertical structure of the vortices. Then, the dependency of the migration characteristics of the vortices are investigated against modelling parameters to find that it is most sensitive to the horizontal diffusion. We also examine the hydrodynamical stability of observed subtropical jets in both northern and southern hemispheres in the three-dimensional nonlinear model as initial value problems. In both cases, it was found that the prominent jets are unstable at various scales and that vorteces of various sizes are generated including those comparable to the White Ovals and the Great Red Spot.

The Delineation of Coral Bleaching Thresholds and Future Reef Health, Little Cayman Cayman Islands

NASA Astrophysics Data System (ADS)

Manfrino, C.; Van Hooidonk, R. J.; Manzello, D.; Hendee, J.

2011-12-01

The global rise in sea temperature through anthropogenic climate change is affecting coral reef ecosystems through a phenomenon known as coral bleaching; a common reaction to thermally induced physiological stress in reef-building corals that often leads to coral mortality. We describe aspects of the most prevalent episode of coral bleaching ever recorded at Little Cayman, Cayman Islands, during the fall of 2009. Scleractinian coral species exhibiting susceptibility to thermal stress and bleaching in Little Cayman were, in order, Siderastrea siderea, Montastraea annularis, and Montastraea faveolata, while Diplora strigosa and Agaricia spp. were less so, yet still showed considerable bleaching prevalence and severity. In contrast, the least susceptible were Porites porites, Porites astreoides, and Montastraea cavernosa. These observations and other reported observations of coral bleaching, together with 29 years (1982 - 2010) of satellite-derived sea surface temperatures, were used in a Degree Heating Weeks (DHW) and Peirce Skill Score (PSS) analysis to calculate a bleaching threshold above which bleaching was expected to occur. A threshold of 4.2 DHW had the highest skill, with a PSS of 0.70. This threshold and susceptibility ranking are used in combination with SST data from global, coupled ocean-atmosphere general circulation models (GCM) from the fourth IPCC assessment to forecast future reef health on Little Cayman. While these GCMs possess skill in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. These model weaknesses likely reduce the skill of coral bleaching predictions. To overcome this, a multi-model ensemble of GCMs are corrected for their mean, annual cycle and ENSO variability prior to calculating future thermal stress. Preliminary results show that from 2045 on Little Cayman is likely to see more than two massive bleaching episodes per decade.

Potential increase in floods in California's Sierra Nevada under future climate projections

USGS Publications Warehouse

Das, T.; Dettinger, M.D.; Cayan, D.R.; Hidalgo, H.G.

2011-01-01

California's mountainous topography, exposure to occasional heavily moisture-laden storm systems, and varied communities and infrastructures in low lying areas make it highly vulnerable to floods. An important question facing the state-in terms of protecting the public and formulating water management responses to climate change-is "how might future climate changes affect flood characteristics in California?" To help address this, we simulate floods on the western slopes of the Sierra Nevada Mountains, the state's primary catchment, based on downscaled daily precipitation and temperature projections from three General Circulation Models (GCMs). These climate projections are fed into the Variable Infiltration Capacity (VIC) hydrologic model, and the VIC-simulated streamflows and hydrologic conditions, from historical and from projected climate change runs, allow us to evaluate possible changes in annual maximum 3-day flood magnitudes and frequencies of floods. By the end of the 21st Century, all projections yield larger-than-historical floods, for both the Northern Sierra Nevada (NSN) and for the Southern Sierra Nevada (SSN). The increases in flood magnitude are statistically significant (at p <= 0. 01) for all the three GCMs in the period 2051-2099. The frequency of flood events above selected historical thresholds also increases under projections from CNRM CM3 and NCAR PCM1 climate models, while under the third scenario, GFDL CM2. 1, frequencies remain constant or decline slightly, owing to an overall drying trend. These increases appear to derive jointly from increases in heavy precipitation amount, storm frequencies, and days with more precipitation falling as rain and less as snow. Increases in antecedent winter soil moisture also play a role in some areas. Thus, a complex, as-yet unpredictable interplay of several different climatic influences threatens to cause increased flood hazards in California's complex western Sierra landscapes. ?? 2011 Springer Science+Business Media B.V.

Impacts of climate change on TN load and its control in a River Basin with complex pollution sources.

PubMed

Yang, Xiaoying; Warren, Rachel; He, Yi; Ye, Jinyin; Li, Qiaoling; Wang, Guoqing

2018-02-15

It is increasingly recognized that climate change could affect the quality of water through complex natural and anthropogenic mechanisms. Previous studies on climate change and water quality have mostly focused on assessing its impact on pollutant loads from agricultural runoff. A sub-daily SWAT model was developed to simulate the discharge, transport, and transformation of nitrogen from all known anthropogenic sources including industries, municipal sewage treatment plants, concentrated and scattered feedlot operations, rural households, and crop production in the Upper Huai River Basin. This is a highly polluted basin with total nitrogen (TN) concentrations frequently exceeding Class V of the Chinese Surface Water Quality Standard (GB3838-2002). Climate change projections produced by 16 Global Circulation Models (GCMs) under the RCP 4.5 and RCP 8.5 scenarios in the mid (2040-2060) and late (2070-2090) century were used to drive the SWAT model to evaluate the impacts of climate change on both the TN loads and the effectiveness of three water pollution control measures (reducing fertilizer use, constructing vegetative filter strips, and improving septic tank performance) in the basin. SWAT simulation results have indicated that climate change is likely to cause an increase in both monthly average and extreme TN loads in February, May, and November. The projected impact of climate change on TN loads in August is more varied between GCMs. In addition, climate change is projected to have a negative impact on the effectiveness of septic tanks in reducing TN loads, while its impacts on the other two measures are more uncertain. Despite the uncertainty, reducing fertilizer use remains the most effective measure for reducing TN loads under different climate change scenarios. Meanwhile, improving septic tank performance is relatively more effective in reducing annual TN loads, while constructing vegetative filter strips is more effective in reducing annual maximum monthly TN loads. Copyright © 2017 Elsevier B.V. All rights reserved.

Stirring up a storm: convective climate variability on tidally locked exoplanets

NASA Astrophysics Data System (ADS)

Koll, D. D. B.; Cronin, T.

2017-12-01

Earth-sized exoplanets are extremely common in the galaxy and many of them are likely tidally locked, such that they have permanent day- and nightsides. Astronomers have started to probe the atmospheres of such planets, which raises the question: can tidally locked planets support habitable climates and life?Several studies have explored this question using global circulation models (GCMs). Not only did these studies find that tidally locked Earth analogs can indeed sustain habitable climates, their large day-night contrast should also create a distinct cloud structure that could help astronomers identify such planets. These studies, however, relied on GCMs which do not explicitly resolve convection, raising the question of how robust their results are.Here we consider the dynamics of clouds and convection on a tidally locked planet using the System for Atmospheric Modeling (SAM) cloud-resolving model. We simulate a 3d `channel', representing an equatorial strip that covers both day- and nightside of a tidally locked planet. We use interactive radiation and an interactive slab ocean surface and investigate the response to changes in the stellar constant. We find mean climates that are broadly comparable to those produced by a GCM. However, when the slab ocean is shallow, we also find internal variability that is far bigger than in a GCM. Convection in a tidally locked domain can self-organize in a dramatic fashion, with large outbursts of convection followed by periods of relative calm. We show that one of the timescales for this behavior is set by the time it takes for a dry gravity wave to travel between day- and nightside. The quasi-periodic self-organization of clouds can vary the planetary albedo by up to 50%. Changes this large are potentially detectable with future space telescopes, which raises the prospect of using convectively driven variability to identify high priority targets in the search for life around other stars.

Climate-Driven Effects of Fire on Winter Habitat for Caribou in the Alaskan-Yukon Arctic

PubMed Central

Gustine, David D.; Brinkman, Todd J.; Lindgren, Michael A.; Schmidt, Jennifer I.; Rupp, T. Scott; Adams, Layne G.

2014-01-01

Climatic warming has direct implications for fire-dominated disturbance patterns in northern ecosystems. A transforming wildfire regime is altering plant composition and successional patterns, thus affecting the distribution and potentially the abundance of large herbivores. Caribou (Rangifer tarandus) are an important subsistence resource for communities throughout the north and a species that depends on terrestrial lichen in late-successional forests and tundra systems. Projected increases in area burned and reductions in stand ages may reduce lichen availability within caribou winter ranges. Sufficient reductions in lichen abundance could alter the capacity of these areas to support caribou populations. To assess the potential role of a changing fire regime on winter habitat for caribou, we used a simulation modeling platform, two global circulation models (GCMs), and a moderate emissions scenario to project annual fire characteristics and the resulting abundance of lichen-producing vegetation types (i.e., spruce forests and tundra >60 years old) across a modeling domain that encompassed the winter ranges of the Central Arctic and Porcupine caribou herds in the Alaskan-Yukon Arctic. Fires were less numerous and smaller in tundra compared to spruce habitats throughout the 90-year projection for both GCMs. Given the more likely climate trajectory, we projected that the Porcupine caribou herd, which winters primarily in the boreal forest, could be expected to experience a greater reduction in lichen-producing winter habitats (−21%) than the Central Arctic herd that wintered primarily in the arctic tundra (−11%). Our results suggest that caribou herds wintering in boreal forest will undergo fire-driven reductions in lichen-producing habitats that will, at a minimum, alter their distribution. Range shifts of caribou resulting from fire-driven changes to winter habitat may diminish access to caribou for rural communities that reside in fire-prone areas. PMID:24991804

How changes of climate extremes affect summer and winter crop yields and water productivity in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, D.; Cammarano, D.

2017-12-01

Modeling changes of crop production at regional scale is important to make adaptation measures for sustainably food supply under global change. In this study, we explore how changing climate extremes in the 20th and 21st century affect maize (summer crop) and wheat (winter crop) yields in an agriculturally important region: the southeast United States. We analyze historical (1950-1999) and projected (2006-2055) precipitation and temperature extremes by calculating the changes of 18 climate extreme indices using the statistically downscaled CMIP5 data from 10 general circulation models (GCMs). To evaluate how these climate extremes affect maize and wheat yields, historical baseline and projected maize and wheat yields under RCP4.5 and RCP8.5 scenarios are simulated using the DSSAT-CERES maize and wheat models driven by the same downscaled GCMs data. All of the changes are examined at 110 locations over the study region. The results show that most of the precipitation extreme indices do not have notable change; mean precipitation, precipitation intensity, and maximum 1-day precipitation are generally increased; the number of rainy days is decreased. The temperature extreme indices mostly showed increased values on mean temperature, number of high temperature days, diurnal temperature range, consecutive high temperature days, maximum daily maximum temperature, and minimum daily minimum temperature; the number of low temperature days and number of consecutive low temperature days are decreased. The conditional probabilistic relationships between changes in crop yields and changes in extreme indices suggested different responses of crop yields to climate extremes during sowing to anthesis and anthesis to maturity periods. Wheat yields and crop water productivity for wheat are increased due to an increased CO2 concentration and minimum temperature; evapotranspiration, maize yields, and crop water productivity for wheat are decreased owing to the increased temperature extremes. We found the effects of precipitation changes on both yields are relatively uncertain.

Projected shifts in fish species dominance in Wisconsin lakes under climate change.

PubMed

Hansen, Gretchen J A; Read, Jordan S; Hansen, Jonathan F; Winslow, Luke A

2017-04-01

Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989-2014) and future (2040-2064 and 2065-2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33-75% of lakes where recruitment is currently supported and a 27-60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations. © 2016 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Projected shifts in fish species dominance in Wisconsin lakes under climate change

USGS Publications Warehouse

Hansen, Gretchen JA; Read, Jordan S.; Hansen, Jonathan F.; Winslow, Luke

2016-01-01

Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.

Bias correction in Global Mean Temperature comparisons between Global Climate Models and implications for the deterministic and stochastic dynamics

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2017-04-01

Global mean temperature (GMT) provides a simple means of benchmarking a broad ensemble of global climate models (GCMs) against past observed GMT which in turn provide headline assessments of the consequences of possible future forcing scenarios. The slow variations of past changes in GMT seen in different GCMs track each other [1] and the observed GMT reasonably closely. However, the different GCMs tend to generate GMT time-series which have absolute values that are offset with respect to each other [2]. Subtracting these offsets is an integral part of comparisons between ensembles of GCMs and observed past GMT. We will discuss how this constrains how the GCMs are related to each other. The GMT of a given GCM is a macroscopic reduced variable that tracks a subset of the full information contained in the time evolving solution of that GCM. If the GMT slow timescale dynamics of different GCMs is to a good approximation the same, subject to a linear translation, then the phenomenology captured by this dynamics is essentially linear; any feedback is to leading order linear in GMT. It then follows that a linear energy balance evolution equation for GMT is sufficient to reproduce the slow timescale GMT dynamics, provided that the appropriate effective heat capacity and feedback parameters are known. As a consequence, the GCM's GMT timeseries may underestimate the impact of, and uncertainty in, the outcomes of future forcing scenarios. The offset subtraction procedure identifies a slow time-scale dynamics in model generated GMT. Fluctuations on much faster timescales do not typically track each other from one GCM to another, with the exception of major forcing events such as volcanic eruptions. This suggests that the GMT time-series can be decomposed into a slow and fast timescale which naturally leads to stochastic reduced energy balance models for GMT. [1] IPCC Chapter 9 P743 and fig 9.8,IPCC TS.1 [2] see e.g. [Mauritsen et al., Tuning the Climate of a Global Model, Journal of Advances in Modelling Earth Systems, 2012] 4, IPCC SPM.6

Linking Wildfire and Climate as Drivers of Plant Species and Community-level Change

NASA Astrophysics Data System (ADS)

Newingham, B. A.; Hudak, A. T.; Bright, B. C.

2015-12-01

Plant species distributions and community shifts after fire are affected by burn severity, elevation, aspect, and climate. However, little empirical data exists on long-term (decadal) recovery after fire across these interacting factors, limiting understanding of fire regime characteristics and climate in post-fire community trajectories. We examined plant species and community responses a decade after fire across five fires in ponderosa pine, dry mixed coniferous, and moist mixed coniferous forests across the western USA. Using field data, we determined changes in plant communities one and ten years post-fire across gradients of burn severity, elevation, and aspect. Existing published work has shown that plant species distributions can be accurately predicted from physiologically relevant climate variables using non-parametric Random Forests models; such models have also been linked to projected climate profiles in 2030, 2060, and 2090 generated from three commonly used general circulation models (GCMs). We explore the possibility that fire and climate are coupled drivers affecting plant species distributions. Climate change may not manifest as a slow shift in plant species distributions, but as sudden, localized events tied to changing fire and other disturbance regimes.

Final Report fir DE-SC0005507 (A1618): The Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations

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

McFarquhar, Greg M.

2012-09-21

We proposed to analyze data collected during the Routine Aerial Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) in order to develop an integrated product of cloud microphysical properties (number concentration of drops in different size bins, total liquid drop concentration integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds, effective radius of water drops, and radar reflectivity factor) that could be used to evaluate large-eddy simulations (LES), general circulation models (GCMs) and ground-based remote sensing retrievals, and to develop cloud parameterizations with the end goal of improving the modeling ofmore » cloud processes and properties and their impact on atmospheric radiation. We have completed the development of this microphysical database. We investigated the differences in the size distributions measured by the Cloud and Aerosol Spectrometer (CAS) and the Forward Scattering Probe (FSSP), between the one dimensional cloud imaging probe (1DC) and the two-dimensional cloud imaging probe (2DC), and between the bulk LWCs measured by the Gerber probe against those derived from the size resolved probes.« less

Forecasting effects of climate change on Great Lakes fisheries: models that link habitat supply to population dynamics can help

USGS Publications Warehouse

Jones, Michael L.; Shuter, Brian J.; Zhao, Yingming; Stockwell, Jason D.

2006-01-01

Future changes to climate in the Great Lakes may have important consequences for fisheries. Evidence suggests that Great Lakes air and water temperatures have risen and the duration of ice cover has lessened during the past century. Global circulation models (GCMs) suggest future warming and increases in precipitation in the region. We present new evidence that water temperatures have risen in Lake Erie, particularly during summer and winter in the period 1965–2000. GCM forecasts coupled with physical models suggest lower annual runoff, less ice cover, and lower lake levels in the future, but the certainty of these forecasts is low. Assessment of the likely effects of climate change on fish stocks will require an integrative approach that considers several components of habitat rather than water temperature alone. We recommend using mechanistic models that couple habitat conditions to population demographics to explore integrated effects of climate-caused habitat change and illustrate this approach with a model for Lake Erie walleye (Sander vitreum). We show that the combined effect on walleye populations of plausible changes in temperature, river hydrology, lake levels, and light penetration can be quite different from that which would be expected based on consideration of only a single factor.

Radar and satellite determined macrophysical properties of wet season convection in Darwin as a function of wet season regime.

NASA Astrophysics Data System (ADS)

Jackson, R. C.; Collis, S. M.; Protat, A.; Louf, V.; Lin, W.; Vogelmann, A. M.; Endo, S.; Majewski, L.

2017-12-01

A known deficiency of general circulation models (GCMs) is that convection is typically parameterized using given assumptions about entrainment rates and mass fluxes. Furthermore, mechanisms coupling large scale forcing and convective organization are poorly represented, leading to a poor representation of the macrophysical properties of convection. The U.S. Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) aims to run at a 12 km resolution. At this scale mesoscale motions are resolved and how they interact with the convective parameterization is unknown. This prompts the need for observational datasets to validate the macrophysical characteristics of convection in simulations and guide model development in ACME in several regions of the globe. This presentation will highlight a study of convective systems focused on data collected at the Tropical Western Pacific (TWP) ARM site in Darwin, Australia and the surrounding maritime continent. In Darwin well defined forcing regimes occur during the wet season of November to April with the onset and break of the Northern Australian Monsoon and the phase of the Madden-Julien Oscillation (MJO) which can alter the characteristics of convection over the region. The echo top heights, and convective and stratiform areas are retrieved from fifteen years of continuous plan position indicator scans from the C-band POLarimetric (CPOL) radar. Echo top heights in convective regions are 2 to 3 km lower than those retrieved by the Multifunctional Transport Satellites over Darwin, suggesting that the radar underestimates the vertical extent of convection. Distributions of echo top heights are trimodal in convective regions and unimodal in stratiform regions. This regime based convective behaviour will be used to assess the skill of ACME in reproducing the macrophysical properties of maritime continent clouds vital to the global circulation.

Precipitation extremes in the Iberian Peninsula: an overview of the CLIPE project

NASA Astrophysics Data System (ADS)

Santos, João A.; Gonçalves, Paulo M.; Rodrigues, Tiago; Carvalho, Maria J.; Rocha, Alfredo

2014-05-01

The main aims of the project "Climate change of precipitation extreme episodes in the Iberian Peninsula and its forcing mechanisms - CLIPE" are 1) to diagnose the climate change signal in the precipitation extremes over the Iberian Peninsula (IP) and 2) to identify the underlying physical mechanisms. For the first purpose, a multi-model ensemble of 25 Regional Climate Model (RCM) simulations, from the ENSEMBLES project, is used. These experiments were generated by 15 RCMs, driven by five General Circulation Models (GCMs) under both historic conditions (1951-2000) and SRES A1B scenario (2001-2100). In this project, daily precipitation and mean sea level pressure, for the periods 1961-1990 (recent past) and 2021-2100 (future), are used. Using the Standardised Precipitation Index (SPI) on a daily basis, a precipitation extreme is defined by the pair of threshold values (Dmin, Imin), where Dmin is the minimum number of consecutive days with daily SPI above the Imin value. For both past and future climates, a precipitation extreme of a specific type is then characterised by two variables: the number of episodes with a specific duration in days and the number of episodes with a specific mean intensity (SPI/duration). Climate change is also assessed by changes in their Probability Density Functions (PDFs), estimated at sectors representative of different precipitation regimes. Lastly, for the second objective of this project, links between precipitation and Circulation Weather Regimes (CWRs) are explored for both past and future climates. Acknowledgments: this work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project CLIPE (PTDC/AAC-CLI/111733/2009).

Spectral Generation from the Ames Mars GCM for the Study of Martian Clouds

NASA Astrophysics Data System (ADS)

Klassen, David R.; Kahre, Melinda A.; Wolff, Michael J.; Haberle, Robert; Hollingsworth, Jeffery L.

2017-10-01

Studies of martian clouds come from two distinct groups of researchers: those modeling the martian system from first principles and those observing Mars from ground-based and orbital platforms. The model-view begins with global circulation models (GCMs) or mesoscale models to track a multitude of state variables over a prescribed set of spatial and temporal resolutions. The state variables can then be processed into distinct maps of derived product variables, such as integrated optical depth of aerosol (e.g., water ice cloud, dust) or column integrated water vapor for comparison to observational results. The observer view begins, typically, with spectral images or imaging spectra, calibrated to some form of absolute units then run through some form of radiative transfer model to also produce distinct maps of derived product variables. Both groups of researchers work to adjust model parameters and assumptions until some level of agreement in derived product variables is achieved. While this system appears to work well, it is in some sense only an implicit confirmation of the model assumptions that attribute to the work from both sides. We have begun a project of testing the NASA Ames Mars GCM and key aerosol model assumptions more directly by taking the model output and creating synthetic TES-spectra from them for comparison to actual raw-reduced TES spectra. We will present some preliminary generated GCM spectra and TES comparisons.

Basic state lower-tropospheric humidity distribution: key to successful simulation and prediction of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Kim, D.; Ahn, M. S.; DeMott, C. A.; Jiang, X.; Klingaman, N. P.; Kim, H. M.; Lee, J. H.; Lim, Y.; Xavier, P. K.

2017-12-01

The Madden-Julian Oscillation (MJO) influences the global weather-climate system, thereby providing the source of predictability on the intraseasonal timescales worldwide. An accurate representation of the MJO, however, is still one of the most challenging tasks for many contemporary global climate models (GCMs). Identifying aspects of the GCMs that are tightly linked to GCMs' MJO simulation capability is a step toward improving the GCM representation of the MJO. This study surveys recent modeling work that collectively evidence that the horizontal distribution of the basic state low-tropospheric humidity is crucial to a successful simulation and prediction of the MJO. Specifically, the simulated horizontal and meridional gradients of the mean low-tropospheric humidity determine the magnitude of the moistening (drying) to the east (west) of the enhance MJO, thereby enabling or disabling the eastward propagation of the MJO. Supporting this argument, many MJO-incompetent GCMs also exhibit biases in the mean humidity that weaken the horizontal moisture gradient. Also, MJO prediction skill of the S2S models is tightly related to the biases in the mean moisture gradient. Implications of the robust relationship between the MJO and the mean state on MJO modeling and prediction will be discussed.

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

NASA Astrophysics Data System (ADS)

Marx, Andreas; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Wanders, Niko; Zink, Matthias; Wood, Eric F.; Pan, Ming; Sheffield, Justin; Samaniego, Luis

2018-02-01

There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000 km2. The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5 km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90 % of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from -12 % under 1.5 K, compared to the baseline period 1971-2000, to -35 % under global warming of 3 K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5 K) to +45 % (3 K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2 K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of period-averaged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multi-model ensemble as well as its single members in the adaptation process.

NIR-Driven Moist Upper Atmospheres of Synchronously Rotating Temperate Terrestrial Exoplanets

NASA Technical Reports Server (NTRS)

Fujii, Yuka; Del Genio, Anthony D.; Amundsen, David S.

2017-01-01

H2O is a key molecule in characterizing atmospheres of temperate terrestrial planets, and observations of transmission spectra are expected to play a primary role in detecting its signatures in the near future. The detectability of H2O absorption features in transmission spectra depends on the abundance of water vapor in the upper part of the atmosphere. We study the three-dimensional distribution of atmospheric H2O for synchronously rotating Earth-sized aquaplanets using the general circulation model (GCM) ROCKE-3D, and examine the effects of total incident flux and stellar spectral type. We observe a more gentle increase of the water vapor mixing ratio in response to increased incident flux than one-dimensional models suggest, in qualitative agreement with the climate-stabilizing effect of clouds around the substellar point previously observed in GCMs applied to synchronously rotating planets. However, the water vapor mixing ratio in the upper atmosphere starts to increase while the surface temperature is still moderate. This is explained by the circulation in the upper atmosphere being driven by the radiative heating due to absorption by water vapor and cloud particles, causing efficient vertical transport of water vapor. Consistently, the water vapor mixing ratio is found to be well-correlated with the near-infrared portion of the incident flux. We also simulate transmission spectra based on the GCM outputs, and show that for the more highly irradiated planets, the H2O signatures may be strengthened by a factor of a few, loosening the observational demands for a H2O detection.

Using regime analysis to identify the contribution of clouds to surface temperature errors in weather and climate models

DOE PAGES

Van Weverberg, Kwinten; Morcrette, Cyril J.; Ma, Hsi -Yen; ...

2015-06-17

Many global circulation models (GCMs) exhibit a persistent bias in the 2 m temperature over the midlatitude continents, present in short-range forecasts as well as long-term climate simulations. A number of hypotheses have been proposed, revolving around deficiencies in the soil–vegetation–atmosphere energy exchange, poorly resolved low-level boundary-layer clouds or misrepresentations of deep-convective storms. A common approach to evaluating model biases focuses on the model-mean state. However, this makes difficult an unambiguous interpretation of the origins of a bias, given that biases are the result of the superposition of impacts of clouds and land-surface deficiencies over multiple time steps. This articlemore » presents a new methodology to objectively detect the role of clouds in the creation of a surface warm bias. A unique feature of this study is its focus on temperature-error growth at the time-step level. It is shown that compositing the temperature-error growth by the coinciding bias in total downwelling radiation provides unambiguous evidence for the role that clouds play in the creation of the surface warm bias during certain portions of the day. Furthermore, the application of an objective cloud-regime classification allows for the detection of the specific cloud regimes that matter most for the creation of the bias. We applied this method to two state-of-the-art GCMs that exhibit a distinct warm bias over the Southern Great Plains of the USA. Our analysis highlights that, in one GCM, biases in deep-convective and low-level clouds contribute most to the temperature-error growth in the afternoon and evening respectively. In the second GCM, deep clouds persist too long in the evening, leading to a growth of the temperature bias. In conclusion, the reduction of the temperature bias in both models in the morning and the growth of the bias in the second GCM in the afternoon could not be assigned to a cloud issue, but are more likely caused by a land-surface deficiency.« less

Influence of parameterized small-scale gravity waves on the migrating diurnal tide in Earth's thermosphere

NASA Astrophysics Data System (ADS)

Yiǧit, Erdal; Medvedev, Alexander S.

2017-04-01

Effects of subgrid-scale gravity waves (GWs) on the diurnal migrating tides are investigated from the mesosphere to the upper thermosphere for September equinox conditions, using a general circulation model coupled with the extended spectral nonlinear GW parameterization of Yiğit et al. (). Simulations with GW effects cut off above the turbopause and included in the entire thermosphere have been conducted. GWs appreciably impact the mean circulation and cool the thermosphere down by up to 12-18%. GWs significantly affect the winds modulated by the diurnal migrating tide, in particular, in the low-latitude mesosphere and lower thermosphere and in the high-latitude thermosphere. These effects depend on the mutual correlation of the diurnal phases of the GW forcing and tides: GWs can either enhance or reduce the tidal amplitude. In the low-latitude MLT, the correlation between the direction of the deposited GW momentum and the tidal phase is positive due to propagation of a broad spectrum of GW harmonics through the alternating winds. In the Northern Hemisphere high-latitude thermosphere, GWs act against the tide due to an anticorrelation of tidal wind and GW momentum, while in the Southern high-latitudes they weakly enhance the tidal amplitude via a combination of a partial correlation of phases and GW-induced changes of the circulation. The variable nature of GW effects on the thermal tide can be captured in GCMs provided that a GW parameterization (1) considers a broad spectrum of harmonics, (2) properly describes their propagation, and (3) correctly accounts for the physics of wave breaking/saturation.

Observational Analysis of Cloud and Precipitation in Midlatitude Cyclones: Northern Versus Southern Hemisphere Warm Fronts

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.

2012-01-01

Extratropical cyclones are responsible for most of the precipitation and wind damage in the midlatitudes during the cold season, but there are still uncertainties on how they will change in a warming climate. An ubiquitous problem amongst General Circulation Models (GCMs) is a lack of cloudiness over the southern oceans that may be in part caused by a lack of clouds in cyclones. We analyze CloudSat, CALIPSO and AMSR-E observations for 3 austral and boreal cold seasons and composite cloud frequency of occurrence and precipitation at the warm fronts for northern and southern hemisphere oceanic cyclones. We find that cloud frequency of occurrence and precipitation rate are similar in the early stage of the cyclone life cycle in both northern and southern hemispheres. As cyclones evolve and reach their mature stage, cloudiness and precipitation at the warm front increase in the northern hemisphere but decrease in the southern hemisphere. This is partly caused by lower amounts of precipitable water being available to southern hemisphere cyclones, and smaller increases in wind speed as the cyclones evolve. Southern hemisphere cloud occurrence at the warm front is found to be more sensitive to the amount of moisture in the warm sector than to wind speeds. This suggests that cloudiness in southern hemisphere storms may be more susceptible to changes in atmospheric water vapor content, and thus to changes in surface temperature than their northern hemisphere counterparts. These differences between northern and southern hemisphere cyclones are statistically robust, indicating A-Train-based analyses as useful tools for evaluation of GCMs in the next IPCC report.

Data systems for science integration within the Atmospheric Radiation Measurement Program

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

Gracio, D.K.; Hatfield, L.D.; Yates, K.R.

The Atmospheric Radiation Measurement (ARM) Program was developed by the US Department of Energy to support the goals and mission of the US Global Change Research Program. The purpose of the ARM program is to improve the predictive capabilities of General Circulation Models (GCMs) in their treatment of clouds and radiative transfer effects. Three experimental testbeds were designed for the deployment of instruments to collect atmospheric data used to drive the GCMs. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation.more » The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in early 1996 in the Tropical Western Pacific (TWP) and in 1997 on the North Slope of Alaska (NSA). Approximately 1.5 GB of data are transferred per day via the Internet from the CART sites, and external data sources to the ARM Experiment Center (EC) at Pacific Northwest Laboratory in Richland, Washington. The Experimental Center is central to the ARM data path and provides for the collection, processing, analysis and delivery of ARM data. Data from the CART sites from a variety of instrumentation, observational systems and from external data sources are transferred to the Experiment Center. The EC processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while maintaining a three-month running archive of data.« less

Midlatitude Storm Potential in a Changing Climate

NASA Astrophysics Data System (ADS)

Seeley, J.; Romps, D. M.

2013-12-01

The effect of climate change on severe weather over the continental U.S. is calculated using CMIP5 output from ten GCMs. The potential for severe weather is evaluated in these models using an operational proxy of CAPE times shear; the calculation of CAPE is made possible by the presence of high-frequency data in the CMIP5 archive that was not available in CMIP3. First, the ability of each GCM to replicate modern-day distributions of CAPE and shear is assessed. It is found that the GCMs replicate the observed seasonal cycle of CAPE with reasonable fidelity, but a majority of the GCMs show an erroneous summertime CAPE maximum on the East Coast. The source of this persistent bias is explored. Second, the predicted changes in future severe-storm potential over the continental U.S. are evaluated using the RCP4.5 emissions scenario. The seasonal cycle of domain-averaged undilute CAPE over CONUS for 10 GCMs and radiosonde measurements. Data is averaged over the recent past ("RP") period of 1999-2008. Summertime (JJA) climatologies of CAPE over CONUS for 10 GCMs and radiosonde observations. Data is averaged over the recent past ("RP") period of 1999-2008. Six of the models show an erroneous CAPE maximum on the East Coast.

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.

Uncertainties in Integrated Climate Change Impact Assessments by Sub-setting GCMs Based on Annual as well as Crop Growing Period under Rice Based Farming System of Indo-Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Pillai, S. N.; Singh, H.; Panwar, A. S.; Meena, M. S.; Singh, S. V.; Singh, B.; Paudel, G. P.; Baigorria, G. A.; Ruane, A. C.; McDermid, S.; Boote, K. J.; Porter, C.; Valdivia, R. O.

2016-12-01

Integrated assessment of climate change impact on agricultural productivity is a challenge to the scientific community due to uncertainties of input data, particularly the climate, soil, crop calibration and socio-economic dataset. However, the uncertainty due to selection of GCMs is the major source due to complex underlying processes involved in initial as well as the boundary conditions dealt in solving the air-sea interactions. Under Agricultural Modeling Intercomparison and Improvement Project (AgMIP), the Indo-Gangetic Plains Regional Research Team investigated the uncertainties caused due to selection of GCMs through sub-setting based on annual as well as crop-growth period of rice-wheat systems in AgMIP Integrated Assessment methodology. The AgMIP Phase II protocols were used to study the linking of climate-crop-economic models for two study sites Meerut and Karnal to analyse the sensitivity of current production systems to climate change. Climate Change Projections were made using 29 CMIP5 GCMs under RCP4.5 and RCP 8.5 during mid-century period (2040-2069). Two crop models (APSIM & DSSAT) were used. TOA-MD economic model was used for integrated assessment. Based on RAPs (Representative Agricultural Pathways), some of the parameters, which are not possible to get through modeling, derived from literature and interactions with stakeholders incorporated into the TOA-MD model for integrated assessment.

Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model.

PubMed

Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki

2018-03-07

Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

Intercomparison of Downscaling Methods on Hydrological Impact for Earth System Model of NE United States

NASA Astrophysics Data System (ADS)

Yang, P.; Fekete, B. M.; Rosenzweig, B.; Lengyel, F.; Vorosmarty, C. J.

2012-12-01

Atmospheric dynamics are essential inputs to Regional-scale Earth System Models (RESMs). Variables including surface air temperature, total precipitation, solar radiation, wind speed and humidity must be downscaled from coarse-resolution, global General Circulation Models (GCMs) to the high temporal and spatial resolution required for regional modeling. However, this downscaling procedure can be challenging due to the need to correct for bias from the GCM and to capture the spatiotemporal heterogeneity of the regional dynamics. In this study, the results obtained using several downscaling techniques and observational datasets were compared for a RESM of the Northeast Corridor of the United States. Previous efforts have enhanced GCM model outputs through bias correction using novel techniques. For example, the Climate Impact Research at Potsdam Institute developed a series of bias-corrected GCMs towards the next generation climate change scenarios (Schiermeier, 2012; Moss et al., 2010). Techniques to better represent the heterogeneity of climate variables have also been improved using statistical approaches (Maurer, 2008; Abatzoglou, 2011). For this study, four downscaling approaches to transform bias-corrected HADGEM2-ES Model output (daily at .5 x .5 degree) to the 3'*3'(longitude*latitude) daily and monthly resolution required for the Northeast RESM were compared: 1) Bilinear Interpolation, 2) Daily bias-corrected spatial downscaling (D-BCSD) with Gridded Meteorological Datasets (developed by Abazoglou 2011), 3) Monthly bias-corrected spatial disaggregation (M-BCSD) with CRU(Climate Research Unit) and 4) Dynamic Downscaling based on Weather Research and Forecast (WRF) model. Spatio-temporal analysis of the variability in precipitation was conducted over the study domain. Validation of the variables of different downscaling methods against observational datasets was carried out for assessment of the downscaled climate model outputs. The effects of using the different approaches to downscale atmospheric variables (specifically air temperature and precipitation) for use as inputs to the Water Balance Model (WBMPlus, Vorosmarty et al., 1998;Wisser et al., 2008) for simulation of daily discharge and monthly stream flow in the Northeast US for a 100-year period in the 21st century were also assessed. Statistical techniques especially monthly bias-corrected spatial disaggregation (M-BCSD) showed potential advantage among other methods for the daily discharge and monthly stream flow simulation. However, Dynamic Downscaling will provide important complements to the statistical approaches tested.

Aircraft Observations of Soil Hydrological Influence on the Atmosphere in Northern India

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Barton, Emma J.; Belusic, Danijel; Böing, Steven J.; Hunt, Kieran M. R.; Mitra, Ashis K.; Parker, Douglas J.; Turner, Andrew G.

2017-04-01

India is considered to be a region of the world where the influence of land surface fluxes of sensible and latent heat play an important role in regional weather and climate. Indian rainfall simulations in GCMs are known to be particularly sensitive to soil moisture. However, in a monsoon region where seasonal convective rainfall dominates, it is a big challenge for GCMs to capture, on the one hand, a realistic depiction of surface fluxes during wetting up and drying down at seasonal and sub-seasonal scales, and on the other, the sensitivity of convective rainfall and regional circulations to space-time fluctuations in land surface fluxes. On top of this, most GCMs and operational atmospheric forecast models don't explicitly consider irrigation. In the Indo-Gangetic plains of the Indian sub-continent, irrigated agriculture has become the dominant land use. Irrigation suppresses temporal flux variability for much of the year, and at the same time enhances spatial heterogeneity. One of the key objectives of the Anglo-Indian Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) collaborative project is to better understand the coupling between the land surface and the Indian summer monsoon, and build this understanding into improved prediction of rainfall on multiple time and space scales. During June and July 2016, a series of research flights was performed across the sub-continent using the NERC/Met Office BAe146 aircraft. Here we will present results for a case study from a flight on 30th June which sampled the Planetary Boundary Layer (PBL) on a 700 km low level transect, from the semi-arid region of Rajasthan eastwards into the extensively irrigated state of Uttar Pradesh. As well as crossing different land uses, the flight also sampled mesoscale regions with contrasting recent rainfall conditions. Here we will show how variations in surface hydrology, driven by both irrigation and rainfall, influence the temperature, humidity and winds in the PBL. These unique observations will provide a powerful tool for understanding the dominant land-atmosphere coupling mechanisms operating on a range of multiple length scales, and which help to shape the Indian monsoon.

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.

A Graphical User Interface for Parameterizing Biochemical Models of Photosynthesis and Chlorophyll Fluorescence

NASA Astrophysics Data System (ADS)

Kornfeld, A.; Van der Tol, C.; Berry, J. A.

2015-12-01

Recent advances in optical remote sensing of photosynthesis offer great promise for estimating gross primary productivity (GPP) at leaf, canopy and even global scale. These methods -including solar-induced chlorophyll fluorescence (SIF) emission, fluorescence spectra, and hyperspectral features such as the red edge and the photochemical reflectance index (PRI) - can be used to greatly enhance the predictive power of global circulation models (GCMs) by providing better constraints on GPP. The way to use measured optical data to parameterize existing models such as SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) is not trivial, however. We have therefore extended a biochemical model to include fluorescence and other parameters in a coupled treatment. To help parameterize the model, we then use nonlinear curve-fitting routines to determine the parameter set that enables model results to best fit leaf-level gas exchange and optical data measurements. To make the tool more accessible to all practitioners, we have further designed a graphical user interface (GUI) based front-end to allow researchers to analyze data with a minimum of effort while, at the same time, allowing them to change parameters interactively to visualize how variation in model parameters affect predicted outcomes such as photosynthetic rates, electron transport, and chlorophyll fluorescence. Here we discuss the tool and its effectiveness, using recently-gathered leaf-level data.

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.

Anthropogenic sulfate aerosol and the southward shift of tropical precipitation in the late 20th century

NASA Astrophysics Data System (ADS)

Hwang, Yen-Ting; Frierson, Dargan M. W.; Kang, Sarah M.

2013-06-01

In this paper, we demonstrate a global scale southward shift of the tropical rain belt during the latter half of the 20th century in observations and global climate models (GCMs). In rain gauge data, the southward shift maximizes in the 1980s and is associated with signals in Africa, Asia, and South America. A southward shift exists at a similar time in nearly all CMIP3 and CMIP5 historical simulations, and occurs on both land and ocean, although in most models the shifts are significantly less than in observations. Utilizing a theoretical framework based on atmospheric energetics, we perform an attribution of the zonal mean southward shift of precipitation across a large suite of CMIP3 and CMIP5 GCMs. Our results suggest that anthropogenic aerosol cooling of the Northern Hemisphere is the primary cause of the consistent southward shift across GCMs, although other processes affecting the atmospheric energy budget also contribute to the model-to-model spread.

Regional climate models reduce biases of global models and project smaller European summer warming

NASA Astrophysics Data System (ADS)

Soerland, S.; Schar, C.; Lüthi, D.; Kjellstrom, E.

2017-12-01

The assessment of regional climate change and the associated planning of adaptation and response strategies are often based on complex model chains. Typically, these model chains employ global and regional climate models (GCMs and RCMs), as well as one or several impact models. It is a common belief that the errors in such model chains behave approximately additive, thus the uncertainty should increase with each modeling step. If this hypothesis were true, the application of RCMs would not lead to any intrinsic improvement (beyond higher-resolution detail) of the GCM results. Here, we investigate the bias patterns (offset during the historical period against observations) and climate change signals of two RCMs that have downscaled a comprehensive set of GCMs following the EURO-CORDEX framework. The two RCMs reduce the biases of the driving GCMs, reduce the spread and modify the amplitude of the GCM projected climate change signal. The GCM projected summer warming at the end of the century is substantially reduced by both RCMs. These results are important, as the projected summer warming and its likely impact on the water cycle are among the most serious concerns regarding European climate change.

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.

Are Plant Species Able to Keep Pace with the Rapidly Changing Climate?

PubMed Central

Cunze, Sarah; Heydel, Felix; Tackenberg, Oliver

2013-01-01

Future climate change is predicted to advance faster than the postglacial warming. Migration may therefore become a key driver for future development of biodiversity and ecosystem functioning. For 140 European plant species we computed past range shifts since the last glacial maximum and future range shifts for a variety of Intergovernmental Panel on Climate Change (IPCC) scenarios and global circulation models (GCMs). Range shift rates were estimated by means of species distribution modelling (SDM). With process-based seed dispersal models we estimated species-specific migration rates for 27 dispersal modes addressing dispersal by wind (anemochory) for different wind conditions, as well as dispersal by mammals (dispersal on animal's coat – epizoochory and dispersal by animals after feeding and digestion – endozoochory) considering different animal species. Our process-based modelled migration rates generally exceeded the postglacial range shift rates indicating that the process-based models we used are capable of predicting migration rates that are in accordance with realized past migration. For most of the considered species, the modelled migration rates were considerably lower than the expected future climate change induced range shift rates. This implies that most plant species will not entirely be able to follow future climate-change-induced range shifts due to dispersal limitation. Animals with large day- and home-ranges are highly important for achieving high migration rates for many plant species, whereas anemochory is relevant for only few species. PMID:23894290

Performance of Versions 1,2 and 3 of the Goddard Earth Observing System (GEOS) Chemistry-Climate Model (CCM)

NASA Technical Reports Server (NTRS)

Pawson, Steven; Stolarski, Richard S.; Nielsen, J. Eric; Duncan, Bryan N.

2008-01-01

Version 1 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) was used in the first CCMVa1 model evaluation and forms the basis for several studies of links between ozone and the circulation. That version of the CCM was based on the GEOS-4 GCM. Versions 2 and 3 of the GEOS CCM are based on the GEOS-5 GCM, which retains the "Lin-Rood" dynamical core but has a totally different set of physical parameterizatiOns to GEOS-4. In Version 2 of the GEOS CCM the Goddard stratospheric chemistry module is retained. Difference between Versions 1 and 2 thus reflect the physics changes of the underlying GCMs. Several comparisons between these two models are made, several of which reveal improvements in Version 2 (including a more realistic representation of the interannual variability of the Antarctic vortex). In Version 3 of the GEOS CCM, the stratospheric chemistry mechanism is replaced by the "GMI COMBO" code that includes tropospheric chemistry and different computational approaches. An advantage of this model version. is the reduction of high ozone biases that prevail at low chlorine loadings in Versions 1 and 2. This poster will compare and contrast various aspects of the three model versions that are relevant for understanding interactions between ozone and climate.

Future Irrigation Requirement of Rice Under Irrigated Area - Uncertainty through GCMs and Crop Models : A Case Study of Indo-Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Pillai, S. N.; Singh, H.; Ruane, A. C.; Boote, K. G.; Porter, C.; Rosenzweig, C.; Panwar, A. S.

2017-12-01

Indo-Gangetic Plains (IGP), the food basket of South Asia, characterised by predominantly cereal-based farming systems where livestock is an integral part of farm economy. Climate change is projected to have significant effects on agriculture production and hence on food and livelihood security because more than 90 per cent farmers fall under small and marginal category. The rising temperatures and uncertainties in rainfall associated with global warming may have serious direct and indirect impacts on crop production. A loss of 10-40% crop production is predicted in different crops in India by the end of this century by different researchers. Cereal crops (mainly rice and wheat) are crucial to ensuring the food security in the region, but sustaining their productivity has become a major challenge due to climate variability and uncertainty. Under AgMIP Project, we have analysed the climate change impact on farm level productivity of rice at Meerut District, Uttar Pradesh using 29 GCMs under RCP4.5 and RCP8.5 during mid-century period 2041-2070. Two crop simulation models DSSAT4.6 and APSIM7.7 were used for impact study. There is lot of uncertainty in yield level by different GCMs and crop models. Under RCP4.5, APSIM showed a declining yield up to 14.5 % while DSSAT showed a declining yield level of 6.5 % only compared to the baseline (1980-2010). However, out of 29 GCMs, 15 GCMs showed negative impact and 14 showed positive impact under APSIM while it showed 21 and 8 GCMs, respectively in the case of DSSAT. DSSAT and APSIM simulated irrigation water requirement in future of the order of 645±75 mm and 730±107 mm, respectively under RCP4.5. However, the same will be of the order of 626 ± 99 mm and 749 ± 147 mm, respectively under RCP8.5. Projected irrigation water productivity showed a range of 4.87-12.15 kg ha-1 mm-1 and 6.77-12.63 kg ha-1 mm-1 through APSIM and DSSAT, respectively under RCP4.5, which stands an average of 7.81 and 8.53 kg ha-1 mm-1 during the baseline period. It reduced to 4.22-10.64 and 6.37-12.56 kg ha-1 mm-1 through APSIM and DSSAT, respectively under RCP8.5. This showed the uncertainty of GCMs as well as the Crop models for future projection. A multi-model approach with optimistic and pessimistic projections should be used for scenario analysis and policy planning in future rather than single model projections.

The local impact of climate change on the alpine mountains Zugspitze and Sonnblick

NASA Astrophysics Data System (ADS)

Kaspar, Severin; Philipp, Andreas; Jacobeit, Jucundus

2017-04-01

In the past decades, the alpine region indicates a high sensitivity to the impact of climate change, as one can see in a higher increase in surface air temperature in the alps compared to the surrounding area. Beside the effect on temperature, a change on the components of the hydrological cycle may be expected, which can be critical for mankind in many areas, where the alpine region provides water security or ensures economical income due to, for example, winter tourism. Changes in certain meteorological variables will also have effects on the alpine ecosystem itself. In this study, some of these quantities and their development under changing climate boundary conditions are examined for the meteorological stations Zugspitze and Sonnblick. Temperature, precipitation, wind and humidity were evaluated at the Zugspitze station, which is located in the northern part of the alps, temperature and precipitation at the Sonnblick Observatory, which is located in the center of the Alps. For the impact analysis, a statistical downscaling (SD) approach was developed to find a link between the large scale atmosphere and the respective local effect. The SD framework is based on the artificial neural network (ANN) method. Models are calibrated for each season on a daily time scale using the 20th century reanalysis dataset as a substitute for atmospheric observational data. The developed ANN setups and configurations show promising results, e.g. up to 90% of explained variance (R2) for temperature and up to 60 % R2 for precipitation and relative humidity, while wind strength reaches with about 30% the lowest performance values. The identified ANN setups are afterwards driven with scenario data from five general circulation models (GCMs) from CMIP5 and additionally with two further realizations of one of the GCMs. As representative concentration pathways, two radiative forcings, 4.5 and 8.5 Watts, are selected. All future projections show a continuing increase in temperature throughout the 21st century for both stations and all seasons. The impact on precipitation is more differentiated: While for all seasons of the Zugspitze station, increased precipitation is simulated (highest in winter), the Sonnblick station shows a decrease in summer. Relative humidity at the Zugspitze is expected to decrease slightly throughout the year and wind strength at the Zugspitze station is projected with a slight increase in winter and spring and a slight decrease in summer and autumn. Further analyses will consider the synoptic interpretation of the interdependency between large scale circulation and the respective local impact, to figure out the cause of the local climatic behavior in the 21st century. Therefore, classification algorithms will be applied as reference class forecast models for a quantitative evaluation.

Dynamics of the Venus upper atmosphere: Outstanding problems and new constraints expected from Venus Express

NASA Astrophysics Data System (ADS)

Bougher, S. W.; Rafkin, S.; Drossart, P.

2006-11-01

A consistent picture of the dynamics of the Venus upper atmosphere from ˜90 to 200 km has begun to emerge [e.g., Bougher, S.W., Alexander, M.J., Mayr, H.G., 1997. Upper Atmosphere Dynamics: Global Circulation and Gravity Waves. Venus II, CH. 2.4. University of Arizona Press, Tucson, pp. 259-292; Lellouch, E., Clancy, T., Crisp, D., Kliore, A., Titov, D., Bougher, S.W., 1997. Monitoring of Mesospheric Structure and Dynamics. Venus II, CH. 3.1. University of Arizona Press, Tucson, pp. 295-324]. The large-scale circulation of the Venus upper atmosphere (upper mesosphere and thermosphere) can be decomposed into two distinct flow patterns: (1) a relatively stable subsolar-to-antisolar (SS-AS) circulation cell driven by solar heating, and (2) a highly variable retrograde superrotating zonal (RSZ) flow. Wave-like perturbations have also been observed. However, the processes responsible for maintaining (and driving variations in) these SS-AS and RSZ winds are not well understood. Variations in winds are thought to result from gravity wave breaking and subsequent momentum and energy deposition in the upper atmosphere [Alexander, M.J., 1992. A mechanism for the Venus thermospheric superrotation. Geophys. Res. Lett. 19, 2207-2210; Zhang, S., Bougher, S.W., Alexander, M.J., 1996. The impact of gravity waves on the Venus thermosphere and O2 IR nightglow. J. Geophys. Res. 101, 23195-23205]. However, existing data sets are limited in their spatial and temporal coverage, thereby restricting our understanding of these changing circulation patterns. One of the major goals of the Venus Express (VEX) mission is focused upon increasing our understanding of the circulation and dynamical processes of the Venus atmosphere up to the exobase [Titov, D.V., Lellouch, E., Taylor, F.W., 2001. Venus Express: Response to ESA's call for ideas for the re-use of the Mars Express platform. Proposal to European Space Agency, 1-74]. Several VEX instruments are slated to obtain remote measurements (2006-2008) that will complement those obtained earlier by the Pioneer Venus Orbiter (PVO) between 1978 and 1992. These VEX measurements will provide a more comprehensive investigation of the Venus upper atmosphere (90-200 km) structure and dynamics over another period in the solar cycle and for variable lower atmosphere conditions. An expanded climatology of Venus upper atmosphere structure and wind components will be developed. In addition, gravity wave parameters above the cloud tops will be measured (or inferred), and used to constrain gravity wave breaking models. In this manner, the gravity wave breaking mechanism (thought to regulate highly variable RSZ winds) can be tested using Venus general circulation models (GCMs).

Constructing optimal ensemble projections for predictive environmental modelling in Northern Eurasia

NASA Astrophysics Data System (ADS)

Anisimov, Oleg; Kokorev, Vasily

2013-04-01

Large uncertainties in climate impact modelling are associated with the forcing climate data. This study is targeted at the evaluation of the quality of GCM-based climatic projections in the specific context of predictive environmental modelling in Northern Eurasia. To accomplish this task, we used the output from 36 CMIP5 GCMs from the IPCC AR-5 data base for the control period 1975-2005 and calculated several climatic characteristics and indexes that are most often used in the impact models, i.e. the summer warmth index, duration of the vegetation growth period, precipitation sums, dryness index, thawing degree-day sums, and the annual temperature amplitude. We used data from 744 weather stations in Russia and neighbouring countries to analyze the spatial patterns of modern climatic change and to delineate 17 large regions with coherent temperature changes in the past few decades. GSM results and observational data were averaged over the coherent regions and compared with each other. Ultimately, we evaluated the skills of individual models, ranked them in the context of regional impact modelling and identified top-end GCMs that "better than average" reproduce modern regional changes of the selected meteorological parameters and climatic indexes. Selected top-end GCMs were used to compose several ensembles, each combining results from the different number of models. Ensembles were ranked using the same algorithm and outliers eliminated. We then used data from top-end ensembles for the 2000-2100 period to construct the climatic projections that are likely to be "better than average" in predicting climatic parameters that govern the state of environment in Northern Eurasia. The ultimate conclusions of our study are the following. • High-end GCMs that demonstrate excellent skills in conventional atmospheric model intercomparison experiments are not necessarily the best in replicating climatic characteristics that govern the state of environment in Northern Eurasia, and independent model evaluation on regional level is necessary to identify "better than average" GCMs. • Each of the ensembles combining results from several "better than average" models replicate selected meteorological parameters and climatic indexes better than any single GCM. The ensemble skills are parameter-specific and depend on models it consists of. The best results are not necessarily those based on the ensemble comprised by all "better than average" models. • Comprehensive evaluation of climatic scenarios using specific criteria narrows the range of uncertainties in environmental projections.

Water Availability in a Warming World

NASA Astrophysics Data System (ADS)

Aminzade, Jennifer

As climate warms during the 21st century, the resultant changes in water availability are a vital issue for society, perhaps even more important than the magnitude of warming itself. Yet our climate models disagree in their forecasts of water availability, limiting our ability to plan accordingly. This thesis investigates future water availability projections from Coupled Ocean-Atmosphere General Circulation Models (GCMs), primarily using two water availability measures: soil moisture and the Supply Demand Drought Index (SDDI). Chapter One introduces methods of measuring water availability and explores some of the fundamental differences between soil moisture, SDDI and the Palmer Drought Severity Index (PDSI). SDDI and PDSI tend to predict more severe future drought conditions than soil moisture; 21st century projections of SDDI show conditions rivaling North American historic mega-droughts. We compare multiple potential evapotranspiration (EP) methods in New York using input from the GISS Model ER GCM and local station data from Rochester, NY, and find that they compare favorably with local pan evaporation measurements. We calculate SDDI and PDSI values using various EP methods, and show that changes in future projections are largest when using EP methods most sensitive to global warming, not necessarily methods producing EP values with the largest magnitudes. Chapter Two explores the characteristics and biases of the five GCMs and their 20th and 21st century climate projections. We compare atmospheric variables that drive water availability changes globally, zonally, and geographically among models. All models show increases in both dry and wet extremes for SDDI and soil moisture, but increases are largest for extreme drying conditions using SDDI. The percentage of gridboxes that agree on the sign of change of soil moisture and SDDI between models is very low, but does increase in the 21st century. Still, differences between models are smaller than differences between SDDI and soil moisture projections. Chapter Three addresses the three major differences between SDDI and soil moisture calculations that shed light on why their future projections diverge: evaporation approximations, dependence on previous months' conditions, and the inclusion of additional variables such as runoff. We implement various changes in SDDI and a GCM vegetation scheme to test the sensitivity of each measure and to evaluate which alterations increase the similarity between SDDI and soil moisture. In addition to deconstructing the differences between SDDI and soil moisture, we analyze their projections regionally in Chapter Four. In seven regions (the southwest U.S., southern Europe, eastern China, eastern Siberia, Australia, Uruguay and Colombia), we (1) assess the forecasts of future water availability changes, (2) compare the atmospheric dynamical processes that produce rainfall and drought in the real world to the way it occurs in individual GCMs, (3) determine how these processes change as global temperatures increase, and (4) identify the most likely scenarios for future regional water availability. Chapter Five summarizes key findings by chapter, enumerating this dissertation's contributions to the field. It then discusses the limitations of existing models and measures, and suggests potential solutions for overcoming their predictive shortfalls. Finally, the chapter concludes with a proposal for future research to expand upon this dissertation work. This thesis highlights the global and zonal differences between two water availability measures, SDDI and soil moisture and identifies regions where they agree and disagree in 21st century modeled scenarios. It provides an explanation for differing projections in soil moisture and SDDI and proves that it is possible to bring convergence to their future projections, which is also applicable to PDSI. Finally, a detailed analysis of climatic changes from five GCMs made it possible to present the most likely scenarios for 21st century water availability in seven regions.

The influence of model resolution on the simulated sensitivity of North Atlantic tropical cyclone maximum intensity to sea surface temperature

DOE PAGES

Strazzo, S. E.; Elsner, J. B.; LaRow, T. E.; ...

2016-07-10

Global climate models (GCMs) are routinely relied upon to study the possible impacts of climate change on a wide range of meteorological phenomena, including tropical cyclones (TCs). Previous studies addressed whether GCMs are capable of reproducing observed TC frequency and intensity distributions. This research builds upon earlier studies by examining how well GCMs capture the physically relevant relationship between TC intensity and SST. Specifically, the influence of model resolution on the ability of a GCM to reproduce the sensitivity of simulated TC intensity to SST is examined for the MRI-AGCM (20 km), the GFDL-HiRAM (50 km), the FSU-COAPS (0.94°) model,more » and two versions of the CAM5 (1° and 0.25°). Results indicate that while a 1°C increase in SST corresponds to a 5.5–7.0 m s -1 increase in observed maximum intensity, the same 1°C increase in SST is not associated with a statistically significant increase in simulated TC maximum intensity for any of the models examined. However, it also is shown that the GCMs all capably reproduce the observed sensitivity of potential intensity to SST. The models generate the thermodynamic environment suitable for the development of strong TCs over the correct portions of the Nort h Atlantic basin, but strong simulated TCs do not develop over these areas, even for models that permit Category 5 TCs. This result supports the notion that direct simulation of TC eyewall convection is necessary to accurately represent TC intensity and intensification processes in climate models, although additional explanations are also explored.« less

Hydrological regime modifications induced by climate change in Mediterranean area

NASA Astrophysics Data System (ADS)

Pumo, Dario; Caracciolo, Domenico; Viola, Francesco; Valerio Noto, Leonardo

2015-04-01

The knowledge of river flow regimes has a capital importance for a variety of practical applications, in water resource management, including optimal and sustainable use. Hydrological regime is highly dependent on climatic factors, among which the most important is surely the precipitation, in terms of frequency, seasonal distribution and intensity of rainfall events. The streamflow frequency regime of river basins are often summarized by flow duration curves (FDCs), that offer a simple and comprehensive graphical view of the overall historical variability associated with streamflow, and characterize the ability of the basin to provide flows of various magnitudes. Climate change is likely to lead shifts in the hydrological regime, and, consequently, in the FDCs. Staring from this premise, the primary objective of the present study is to explore the effects of potential climate changes on the hydrological regime of some small Mediterranean basins. To this aim it is here used a recent hydrological model, the ModABa model (MODel for Annual flow duration curves assessment in ephemeral small BAsins), for the probabilistic characterization of the daily streamflows in small catchments. The model has been calibrated and successively validated in a unique small catchment, where it has shown a satisfactory accuracy in reproducing the empirical FDC starting from easily derivable parameters arising from basic ecohydrological knowledge of the basin and commonly available climatic data such as daily precipitation and temperatures. Thus, this work also represents a first attempt to apply the ModABa to basins different from that used for its preliminary design in order to testing its generality. Different case studies are selected within the Sicily region; the model is first calibrated at the sites and then forced by future climatic scenarios, highlighting the principal differences emerging from the current scenario and future FDCs. The future climate scenarios are generated using a stochastic downscaling technique based on the weather generator, AWE-GEN. This methodology allows for the downscaling of an ensemble of climate model outputs deriving the frequency distribution functions of factors of change for several statistics of temperature and precipitation from outputs of General Circulation Models (GCMs). The stochastic downscaling is carried out using simulations of GCMs adopted in the IPCC 5AR, for the future periods of 2046-2065 and 2081-2100.

An observational and modeling study of the regional impacts of climate variability

NASA Astrophysics Data System (ADS)

Horton, Radley M.

Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners---regional planners, extension agents, commodity groups and cooperatives---that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997--1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this 'proof of concept' test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even during El Nino events. Based on the results from Chapter One, the analysis is expanded in several ways in Chapter Two. To gain a more complete and statistically meaningful understanding of ENSO, a 25 year time period is used instead of a single event. To gain a fuller understanding of climate variability, additional patterns are analyzed. Finally analysis is conducted at the regional scales that are of interest to farmers and agricultural planners. Key findings are that GISS ModelE can reproduce: (1) the spatial pattern associated with two additional related modes, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO); (2) rainfall patterns in Indonesia; and (3) dynamical features such as sea level pressure (SLP) gradients and wind in the study regions. When run in coupled mode, the same model reproduces similar modes spatially but with reduced variance and weak teleconnections. Since Chapter Two identified Western Indonesia as the region where GCMs hold the most promise for agricultural applications, in Chapter Three a finer spatial and temporal scale analysis of ENSO's effects is presented. Agricultural decision-making is also linked to ENSO's climate effects. Early rainy season precipitation and circulation, and same-season planting and harvesting dates, are shown to be sensitive to ENSO. The locus of ENSO convergence and rainfall anomalies is shown to be near the axis of rainy season establishment, defined as the 6--8 mm/day isohyet, an approximate threshold for irrigated rice cultivation. As the axis tracks south and east between October and January, so do ENSO anomalies. Circulation anomalies associated with ENSO are shown to be similar to those associated with rainfall anomalies, suggesting that long lead-time ENSO forecasts may allow more adaptation than 'wait and see' methods, with little loss of forecast skill. Additional findings include: (1) rice and corn yields are lower (higher) during dry (wet) trimesters and El Nino (La Nina) years; and (2) a statistically significant negative relationship exists between malaria cases and ENSO. The final chapter adds climate change to the climate variability story. Under high CO2, the model able to capture ENSO dynamics---an atmospheric model coupled to the Cane-Zebiak ocean model ('C4' here)---generates more El Nino-like mean conditions in the tropical Pacific. These changes produce a 4x larger increase in maximum precipitation with warming in C4 than an atmospheric model with a slab ocean (Q4), dramatically enhancing the Pacific Hadley and Walker circulations, and through positive feedbacks, increasing the global temperature. Near Nordeste warming alone (Q4) produces added rainfall, which in C4 is partially cancelled out by El Nino-like changes in the Walker Cell. Both Q4 and C4 produce small changes in Indonesia, although C4 generates large circulation and precipitation anomalies over the Western Indian Ocean. C4 changes in the midlatitudes produce a very strong Pacific North American pattern (PNA) response that dominates a small positive AO change associated with Q4. These PNA changes produce increased rainfall over the Southeastern United States (SEUS) in C4. AO and NAO-like variability are also found to increase with enhanced CO2. This thesis highlights how climate variability influences regional climate variability, with an emphasis on four regions: Nordeste, Brazil, Western Indonesia, the Southeastern United States (SEUS), and the Mediterranean. It links El Nino-driven delay in the onset of rainy season drivers in Western Indonesia to decision-making about when to plant the year's largest crop. In a coupled configuration, the GISS GCM produces strong El Nino-like changes with global warming. This result suggests that the impacts---climatological and agricultural---of climate change may ultimately exceed the impacts of current variability. Somewhat paradoxically, these results indicate that one of the central manifestations of climate change is likely to be changes in patterns of climate variability and their regional impacts.

Statistical and dynamical forecast of regional precipitation after mature phase of ENSO

NASA Astrophysics Data System (ADS)

Sohn, S.; Min, Y.; Lee, J.; Tam, C.; Ahn, J.

2010-12-01

While the seasonal predictability of general circulation models (GCMs) has been improved, the current model atmosphere in the mid-latitude does not respond correctly to external forcing such as tropical sea surface temperature (SST), particularly over the East Asia and western North Pacific summer monsoon regions. In addition, the time-scale of prediction scope is considerably limited and the model forecast skill still is very poor beyond two weeks. Although recent studies indicate that coupled model based multi-model ensemble (MME) forecasts show the better performance, the long-lead forecasts exceeding 9 months still show a dramatic decrease of the seasonal predictability. This study aims at diagnosing the dynamical MME forecasts comprised of the state of art 1-tier models as well as comparing them with the statistical model forecasts, focusing on the East Asian summer precipitation predictions after mature phase of ENSO. The lagged impact of El Nino as major climate contributor on the summer monsoon in model environments is also evaluated, in the sense of the conditional probabilities. To evaluate the probability forecast skills, the reliability (attributes) diagram and the relative operating characteristics following the recommendations of the World Meteorological Organization (WMO) Standardized Verification System for Long-Range Forecasts are used in this study. The results should shed light on the prediction skill for dynamical model and also for the statistical model, in forecasting the East Asian summer monsoon rainfall with a long-lead time.

Trend and uncertainty analysis of simulated climate change impacts with multiple GCMs and emission scenarios

USDA-ARS?s Scientific Manuscript database

Impacts of climate change on hydrology, soil erosion, and wheat production during 2010-2039 at El Reno in central Oklahoma, USA, were simulated using the Water Erosion Prediction Project (WEPP) model. Projections from four GCMs (CCSR/NIES, CGCM2, CSIRO-Mk2, and HadCM3) under three emissions scenari...

The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

NASA Astrophysics Data System (ADS)

Dessens, Olivier

2016-04-01

Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of analysing GCMs with the step-experiments. Acknowledgments: This work is supported by the FP7 HELIX project (www.helixclimate.eu) References: Anandarajah, G., Pye, S., Usher, W., Kesicki, F., & Mcglade, C. (2011). TIAM-UCL Global model documentation. https://www.ucl.ac.uk/energy-models/models/tiam-ucl/tiam-ucl-manual Good, P., Gregory, J. M., Lowe, J. A., & Andrews, T. (2013). Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections. Climate Dynamics, 40(3-4), 1041-1053.

Variability and Predictability of Land-Atmosphere Interactions: Observational and Modeling Studies

NASA Technical Reports Server (NTRS)

Roads, John; Oglesby, Robert; Marshall, Susan; Robertson, Franklin R.

2002-01-01

The overall goal of this project is to increase our understanding of seasonal to interannual variability and predictability of atmosphere-land interactions. The project objectives are to: 1. Document the low frequency variability in land surface features and associated water and energy cycles from general circulation models (GCMs), observations and reanalysis products. 2. Determine what relatively wet and dry years have in common on a region-by-region basis and then examine the physical mechanisms that may account for a significant portion of the variability. 3. Develop GCM experiments to examine the hypothesis that better knowledge of the land surface enhances long range predictability. This investigation is aimed at evaluating and predicting seasonal to interannual variability for selected regions emphasizing the role of land-atmosphere interactions. Of particular interest are the relationships between large, regional and local scales and how they interact to account for seasonal and interannual variability, including extreme events such as droughts and floods. North and South America, including the Global Energy and Water Cycle Experiment Continental International Project (GEWEX GCIP), MacKenzie, and LBA basins, are currently being emphasized. We plan to ultimately generalize and synthesize to other land regions across the globe, especially those pertinent to other GEWEX projects.

Massive processing of pyro-chromatogram mass spectra (py-GCMS) of soil samples using the PARAFAC2 algorithm

NASA Astrophysics Data System (ADS)

Cécillon, Lauric; Quénéa, Katell; Anquetil, Christelle; Barré, Pierre

2015-04-01

Due to its large heterogeneity at all scales (from soil core to the globe), several measurements are often mandatory to get a meaningful value of a measured soil property. A large number of measurements can therefore be needed to study a soil property whatever the scale of the study. Moreover, several soil investigation techniques produce large and complex datasets, such as pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) which produces complex 3-way data. In this context, straightforward methods designed to speed up data treatments are needed to deal with large datasets. GC-MS pyrolysis (py-GCMS) is a powerful and frequently used tool to characterize soil organic matter (SOM). However, the treatment of the results of a py-GCMS analysis of soil sample is time consuming (number of peaks, co-elution, etc.) and the treatment of large data set of py-GCMS results is rather laborious. Moreover, peak position shifts and baseline drifts between analyses make the automation of GCMS programs data treatment difficult. These problems can be fixed using the Parallel Factor Analysis 2 (PARAFAC 2, Kiers et al., 1999; Bro et al., 1999). This algorithm has been applied frequently on chromatography data but has never been applied to analyses of SOM. We developed a Matlab routine based on existing Matlab packages dedicated to the simultaneous treatment of dozens of pyro-chromatograms mass spectra. We applied this routine on 40 soil samples. The benefits and expected improvements of our method will be discussed in our poster. References Kiers et al. (1999) PARAFAC2 - PartI. A direct fitting algorithm for the PARAFAC2 model. Journal of Chemometrics, 13: 275-294. Bro et al. (1999) PARAFAC2 - PartII. Modeling chromatographic data with retention time shifts. Journal of Chemometrics, 13: 295-309.

Projected wetland densities under climate change: Habitat loss but little geographic shift in conservation strategy

USGS Publications Warehouse

Sofaer, Helen R.; Skagen, Susan K.; Barsugli, Joseph J.; Rashford, Benjamin S.; Reese, Gordon C.; Hoeting, Jennifer A.; Wood, Andrew W.; Noon, Barry R.

2016-01-01

Climate change poses major challenges for conservation and management because it alters the area, quality, and spatial distribution of habitat for natural populations. To assess species’ vulnerability to climate change and target ongoing conservation investments, researchers and managers often consider the effects of projected changes in climate and land use on future habitat availability and quality and the uncertainty associated with these projections. Here, we draw on tools from hydrology and climate science to project the impact of climate change on the density of wetlands in the Prairie Pothole Region of the USA, a critical area for breeding waterfowl and other wetland-dependent species. We evaluate the potential for a trade-off in the value of conservation investments under current and future climatic conditions and consider the joint effects of climate and land use. We use an integrated set of hydrological and climatological projections that provide physically based measures of water balance under historical and projected future climatic conditions. In addition, we use historical projections derived from ten general circulation models (GCMs) as a baseline from which to assess climate change impacts, rather than historical climate data. This method isolates the impact of greenhouse gas emissions and ensures that modeling errors are incorporated into the baseline rather than attributed to climate change. Our work shows that, on average, densities of wetlands (here defined as wetland basins holding water) are projected to decline across the U.S. Prairie Pothole Region, but that GCMs differ in both the magnitude and the direction of projected impacts. However, we found little evidence for a shift in the locations expected to provide the highest wetland densities under current vs. projected climatic conditions. This result was robust to the inclusion of projected changes in land use under climate change. We suggest that targeting conservation towards wetland complexes containing both small and relatively large wetland basins, which is an ongoing conservation strategy, may also act to hedge against uncertainty in the effects of climate change.

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.

Analysing regional climate change in Africa in a 1.5 °C global warming world

NASA Astrophysics Data System (ADS)

Weber, Torsten; Haensler, Andreas; Jacob, Daniela

2017-04-01

At the 21st session of the UNFCCC Conference of the Parties (COP21) in Paris, a reaffirmation to strengthen the effort to limit the global temperature increase to 1.5 °C was decided. However, even if global warming is limited, some regions might still be substantially affected by climate change, especially for continents like Africa where the socio-economic conditions are strongly linked to the climatic conditions. Hence, providing a detailed analysis of the projected climate changes in a 1.5 °C global warming scenario will allow the African society to undertake measures for adaptation in order to mitigate potential negative consequences. In order to provide such climate change information, the existing CORDEX Africa ensemble for RCP2.6 scenario simulations has systematically been increased by conducting additional REMO simulations using data from various global circulation models (GCMs) as lateral boundary conditions. Based on this ensemble, which now consists of eleven CORDEX Africa RCP2.6 regional climate model simulations from three RCMs (forced with different GCMs), various temperature and precipitation indices such as number of cold/hot days and nights, duration of the rainy season, the amount of rainfall in the rainy seasons and the number of dry spells have been calculated for a 1.5 °C global warming scenario. The applied method to define the 1.5 °C global warming period has been already applied in the IMPACT2C project. In our presentation, we will discuss the analysis of the climate indices in a 1.5 °C global warming world for the CORDEX-Africa region. Amongst presenting the magnitude of projected changes, we will also address the question for selected indices if the changes projected in a 1.5 °C global warming scenario are already larger than the climate variability and we will also draw links to the changes projected under a more extreme scenario.

Flow regime alterations under changing climate in two river basins: Implications for freshwater ecosystems

USGS Publications Warehouse

Gibson, C.A.; Meyer, J.L.; Poff, N.L.; Hay, L.E.; Georgakakos, A.

2005-01-01

We examined impacts of future climate scenarios on flow regimes and how predicted changes might affect river ecosystems. We examined two case studies: Cle Elum River, Washington, and Chattahoochee-Apalachicola River Basin, Georgia and Florida. These rivers had available downscaled global circulation model (GCM) data and allowed us to analyse the effects of future climate scenarios on rivers with (1) different hydrographs, (2) high future water demands, and (3) a river-floodplain system. We compared observed flow regimes to those predicted under future climate scenarios to describe the extent and type of changes predicted to occur. Daily stream flow under future climate scenarios was created by either statistically downscaling GCMs (Cle Elum) or creating a regression model between climatological parameters predicted from GCMs and stream flow (Chattahoochee-Apalachicola). Flow regimes were examined for changes from current conditions with respect to ecologically relevant features including the magnitude and timing of minimum and maximum flows. The Cle Elum's hydrograph under future climate scenarios showed a dramatic shift in the timing of peak flows and lower low flow of a longer duration. These changes could mean higher summer water temperatures, lower summer dissolved oxygen, and reduced survival of larval fishes. The Chattahoochee-Apalachicola basin is heavily impacted by dams and water withdrawals for human consumption; therefore, we made comparisons between pre-large dam conditions, current conditions, current conditions with future demand, and future climate scenarios with future demand to separate climate change effects and other anthropogenic impacts. Dam construction, future climate, and future demand decreased the flow variability of the river. In addition, minimum flows were lower under future climate scenarios. These changes could decrease the connectivity of the channel and the floodplain, decrease habitat availability, and potentially lower the ability of the river to assimilate wastewater treatment plant effluent. Our study illustrates the types of changes that river ecosystems might experience under future climates. Copyright ?? 2005 John Wiley & Sons, Ltd.

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model

PubMed Central

Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J.; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H.; Molina, Mario J.

2014-01-01

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol–climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by −2.5 and +1.3 W m−2, respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors’ knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale. PMID:24733923

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model.

PubMed

Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H; Molina, Mario J

2014-05-13

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by -2.5 and +1.3 W m(-2), respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors' knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.

Observed heavy precipitation increase confirms theory and early model

NASA Astrophysics Data System (ADS)

Fischer, E. M.; Knutti, R.

2016-12-01

Environmental phenomena are often first observed, and then explained or simulated quantitatively. The complexity and diversity of processes, the range of scales involved, and the lack of first principles to describe many processes make it challenging to predict conditions beyond the ones observed. Here we use the intensification of heavy precipitation as a counterexample, where seemingly complex and potentially computationally intractable processes to first order manifest themselves in simple ways: the intensification of heavy precipitation is now emerging in the observed record across many regions of the world, confirming both theory and a variety of model predictions made decades ago, before robust evidence arose from observations. We here compare heavy precipitation changes over Europe and the contiguous United States across station series and gridded observations, theoretical considerations and multi-model ensembles of GCMs and RCMs. We demonstrate that the observed heavy precipitation intensification aggregated over large areas agrees remarkably well with Clausius-Clapeyron scaling. The observed changes in heavy precipitation are consistent yet somewhat larger than predicted by very coarse resolution GCMs in the 1980s and simulated by the newest generation of GCMs and RCMs. For instance the number of days with very heavy precipitation over Europe has increased by about 45% in observations (years 1981-2013 compared to 1951-1980) and by about 25% in the model average in both GCMs and RCMs, although with substantial spread across models and locations. As the anthropogenic climate signal strengthens, there will be more opportunities to test climate predictions for other variables against observations and across a hierarchy of different models and theoretical concepts. *Fischer, E.M., and R. Knutti, 2016, Observed heavy precipitation increase confirms theory and early models, Nature Climate Change, in press.

NIR-driven Moist Upper Atmospheres of Synchronously Rotating Temperate Terrestrial Exoplanets

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

Fujii, Yuka; Del Genio, Anthony D.; Amundsen, David S.

H{sub 2}O is a key molecule in characterizing atmospheres of temperate terrestrial planets, and observations of transmission spectra are expected to play a primary role in detecting its signatures in the near future. The detectability of H{sub 2}O absorption features in transmission spectra depends on the abundance of water vapor in the upper part of the atmosphere. We study the three-dimensional distribution of atmospheric H{sub 2}O for synchronously rotating Earth-sized aquaplanets using the general circulation model (GCM) ROCKE-3D, and examine the effects of total incident flux and stellar spectral type. We observe a more gentle increase of the water vapormore » mixing ratio in response to increased incident flux than one-dimensional models suggest, in qualitative agreement with the climate-stabilizing effect of clouds around the substellar point previously observed in GCMs applied to synchronously rotating planets. However, the water vapor mixing ratio in the upper atmosphere starts to increase while the surface temperature is still moderate. This is explained by the circulation in the upper atmosphere being driven by the radiative heating due to absorption by water vapor and cloud particles, causing efficient vertical transport of water vapor. Consistently, the water vapor mixing ratio is found to be well-correlated with the near-infrared portion of the incident flux. We also simulate transmission spectra based on the GCM outputs, and show that for the more highly irradiated planets, the H{sub 2}O signatures may be strengthened by a factor of a few, loosening the observational demands for a H{sub 2}O detection.« less

Influence of atmospheric internal variability on the long-term Siberian water cycle during the past 2 centuries

NASA Astrophysics Data System (ADS)

Oshima, Kazuhiro; Ogata, Koto; Park, Hotaek; Tachibana, Yoshihiro

2018-05-01

River discharges from Siberia are a large source of freshwater into the Arctic Ocean, whereas the cause of the long-term variation in Siberian discharges is still unclear. The observed river discharges of the Lena in the east and the Ob in the west indicated different relationships in each of the epochs during the past 7 decades. The correlations between the two river discharges were negative during the 1980s to mid-1990s, positive during the mid-1950s to 1960s, and became weak after the mid-1990s. More long-term records of tree-ring-reconstructed discharges have also shown differences in the correlations in each of the epochs. It is noteworthy that the correlations obtained from the reconstructions tend to be negative during the past 2 centuries. Such tendency has also been obtained from precipitations in observations, and in simulations with an atmospheric general circulation model (AGCM) and fully coupled atmosphere-ocean GCMs conducted for the Fourth Assessment Report of the IPCC. The AGCM control simulation further demonstrated that an east-west seesaw pattern of summertime large-scale atmospheric circulation frequently emerges over Siberia as an atmospheric internal variability. This results in an opposite anomaly of precipitation over the Lena and Ob and the negative correlation. Consequently, the summertime atmospheric internal variability in the east-west seesaw pattern over Siberia is a key factor influencing the long-term variation in precipitation and river discharge, i.e., the water cycle in this region.

Importance of ocean mesoscale variability for air-sea interactions in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Putrasahan, D. A.; Kamenkovich, I.; Le Hénaff, M.; Kirtman, B. P.

2017-06-01

Mesoscale variability of currents in the Gulf of Mexico (GoM) can affect oceanic heat advection and air-sea heat exchanges, which can influence climate extremes over North America. This study is aimed at understanding the influence of the oceanic mesoscale variability on the lower atmosphere and air-sea heat exchanges. The study contrasts global climate model (GCM) with 0.1° ocean resolution (high resolution; HR) with its low-resolution counterpart (1° ocean resolution with the same 0.5° atmosphere resolution; LR). The LR simulation is relevant to current generation of GCMs that are still unable to resolve the oceanic mesoscale. Similar to observations, HR exhibits positive correlation between sea surface temperature (SST) and surface turbulent heat flux anomalies, while LR has negative correlation. For HR, we decompose lateral advective heat fluxes in the upper ocean into mean (slowly varying) and mesoscale-eddy (fast fluctuations) components. We find that the eddy flux divergence/convergence dominates the lateral advection and correlates well with the SST anomalies and air-sea latent heat exchanges. This result suggests that oceanic mesoscale advection supports warm SST anomalies that in turn feed surface heat flux. We identify anticyclonic warm-core circulation patterns (associated Loop Current and rings) which have an average diameter of 350 km. These warm anomalies are sustained by eddy heat flux convergence at submonthly time scales and have an identifiable imprint on surface turbulent heat flux, atmospheric circulation, and convective precipitation in the northwest portion of an averaged anticyclone.

On-line Analysis of Catalytic Reaction Products Using a High-Pressure Tandem Micro-reactor GC/MS.

PubMed

Watanabe, Atsushi; Kim, Young-Min; Hosaka, Akihiko; Watanabe, Chuichi; Teramae, Norio; Ohtani, Hajime; Kim, Seungdo; Park, Young-Kwon; Wang, Kaige; Freeman, Robert R

2017-01-01

When a GC/MS system is coupled with a pressurized reactor, the separation efficiency and the retention time are directly affected by the reactor pressure. To keep the GC column flow rate constant irrespective of the reaction pressure, a restrictor capillary tube and an open split interface are attached between the GC injection port and the head of a GC separation column. The capability of the attached modules is demonstrated for the on-line GC/MS analysis of catalytic reaction products of a bio-oil model sample (guaiacol), produced under a pressure of 1 to 3 MPa.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE PAGES

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-02

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

NASA Astrophysics Data System (ADS)

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-01

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

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

Donahue, Aaron S.; Caldwell, Peter M.

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

An Evaluation of CMIP5 Precipitation Variability for China Relative to Observations and CMIP3

NASA Astrophysics Data System (ADS)

Frauenfeld, O. W.; Chen, L.

2013-12-01

Precipitation represents an important link between the atmosphere, hydrosphere, and biosphere and is thus a key component of the climate system. As indicated by the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), global surface air temperatures increased by 0.74°C during the 20th century, with further warming of 0.2°C/decade projected by the 2030s. Projected changes in precipitation, however, are much more variable, and exhibit more complex temporal and spatial patterns. This presentation focuses on precipitation variability based on 20 general circulation models (GCMs) participating in the fifth coupled model intercomparison project (CMIP5). Specifically, we focus on China and provide a comprehensive evaluation of the CMIP5 models compared to historical 20th century precipitation variability from two observational precipitation products: the University of East Anglia's Climatic Research Unit (CRU) time series (TS) dataset version 3.10, and the Global Precipitation Climatology Centre (GPCC) version 6. We also reassess the performance of the third CMIP (CMIP3) to quantify potential improvements in CMIP5 over the previous generation of GCMs. Finally, we provide 21st century precipitation projections for China based on three representative concentration pathways (RCP): RCP 8.5, 4.5, and 2.6. These future precipitation projections are presented in light of the observed 20th century biases in the models. We find that CMIP5 models are able to better reproduce the general spatial pattern of observed 20th century precipitation than CMIP3. However, for China as a whole, the annual precipitation magnitude is overestimated in CMIP5, more so than in CMIP3. This smaller overestimation in CMIP3 was primarily driven by a large underestimation of summer precipitation. Spatially, overestimated precipitation magnitudes are evident for most regions of China, especially along the eastern margin of the Tibetan Plateau. Over southeastern China during summer, the precipitation amounts are underestimated. The multidecadal precipitation variability in CMIP5 is muted relative to observations, but improved when compared to CMIP3. We also assess precipitation trends and correlations relative to observations, and again find better agreement for CMIP5 than for CMIP3. Both observations and models indicated precipitation increases over parts of northwestern China, and decreases over the Tibetan Plateau throughout the 20th century. However, for the southeastern and northern regions of China there is poor agreement in precipitation trends. Precipitation is projected to increase across all of China under all the three emission scenarios during the 21st century. The largest significant trend is evident for RCP 8.5, which projects a precipitation increase of 1.5 mm/year, resulting in a 16% increase in precipitation by the end of the century. The smallest increases are projected to occur under the RCP 2.6 scenario, resulting in only a +6% change by 2100. The regions of greatest precipitation increases are the Tibetan Plateau and eastern China during summer, suggesting a potential change in the monsoonal circulation in the future.

Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

PubMed

Reisetter, Anna C; Muehlbauer, Michael J; Bain, James R; Nodzenski, Michael; Stevens, Robert D; Ilkayeva, Olga; Metzger, Boyd E; Newgard, Christopher B; Lowe, William L; Scholtens, Denise M

2017-02-02

Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.

Integrating K-means Clustering with Kernel Density Estimation for the Development of a Conditional Weather Generation Downscaling Model

NASA Astrophysics Data System (ADS)

Chen, Y.; Ho, C.; Chang, L.

2011-12-01

In previous decades, the climate change caused by global warming increases the occurrence frequency of extreme hydrological events. Water supply shortages caused by extreme events create great challenges for water resource management. To evaluate future climate variations, general circulation models (GCMs) are the most wildly known tools which shows possible weather conditions under pre-defined CO2 emission scenarios announced by IPCC. Because the study area of GCMs is the entire earth, the grid sizes of GCMs are much larger than the basin scale. To overcome the gap, a statistic downscaling technique can transform the regional scale weather factors into basin scale precipitations. The statistic downscaling technique can be divided into three categories include transfer function, weather generator and weather type. The first two categories describe the relationships between the weather factors and precipitations respectively based on deterministic algorithms, such as linear or nonlinear regression and ANN, and stochastic approaches, such as Markov chain theory and statistical distributions. In the weather type, the method has ability to cluster weather factors, which are high dimensional and continuous variables, into weather types, which are limited number of discrete states. In this study, the proposed downscaling model integrates the weather type, using the K-means clustering algorithm, and the weather generator, using the kernel density estimation. The study area is Shihmen basin in northern of Taiwan. In this study, the research process contains two steps, a calibration step and a synthesis step. Three sub-steps were used in the calibration step. First, weather factors, such as pressures, humidities and wind speeds, obtained from NCEP and the precipitations observed from rainfall stations were collected for downscaling. Second, the K-means clustering grouped the weather factors into four weather types. Third, the Markov chain transition matrixes and the conditional probability density function (PDF) of precipitations approximated by the kernel density estimation are calculated respectively for each weather types. In the synthesis step, 100 patterns of synthesis data are generated. First, the weather type of the n-th day are determined by the results of K-means clustering. The associated transition matrix and PDF of the weather type were also determined for the usage of the next sub-step in the synthesis process. Second, the precipitation condition, dry or wet, can be synthesized basing on the transition matrix. If the synthesized condition is dry, the quantity of precipitation is zero; otherwise, the quantity should be further determined in the third sub-step. Third, the quantity of the synthesized precipitation is assigned as the random variable of the PDF defined above. The synthesis efficiency compares the gap of the monthly mean curves and monthly standard deviation curves between the historical precipitation data and the 100 patterns of synthesis data.

Projection of invertebrate populations in the headwater streams of a temperate catchment under a changing climate.

PubMed

Nukazawa, Kei; Arai, Ryosuke; Kazama, So; Takemon, Yasuhiro

2018-06-14

Climate change places considerable stress on riverine ecosystems by altering flow regimes and increasing water temperature. This study evaluated how water temperature increases under climate change scenarios will affect stream invertebrates in pristine headwater streams. The studied headwater-stream sites were distributed within a temperate catchment of Japan and had similar hydraulic-geographical conditions, but were subject to varying temperature conditions due to altitudinal differences (100 to 850 m). We adopted eight general circulation models (GCMs) to project air temperature under conservative (RCP2.6), intermediate (RCP4.5), and extreme climate scenarios (RCP8.5) during the near (2031-2050) and far (2081-2100) future. Using the water temperature of headwater streams computed by a distributed hydrological-thermal model as a predictor variable, we projected the population density of stream invertebrates in the future scenarios based on generalized linear models. The mean decrease in the temporally averaged population density of Plecoptera was 61.3% among the GCMs, even under RCP2.6 in the near future, whereas density deteriorated even further (90.7%) under RCP8.5 in the far future. Trichoptera density was also projected to greatly deteriorate under RCP8.5 in the far future. We defined taxa that exhibited temperature-sensitive declines under climate change as cold stenotherms and found that most Plecoptera taxa were cold stenotherms in comparison to other orders. Specifically, the taxonomic families that only distribute in Palearctic realm (e.g., Megarcys ochracea and Scopura longa) were selectively assigned, suggesting that Plecoptera family with its restricted distribution in the Palearctic might be a sensitive indicator of climate change. Plecoptera and Trichoptera populations in the headwaters are expected/anticipated to decrease over the considerable geographical range of the catchment, even under the RCP2.6 in the near future. Given headwater invertebrates play important roles in streams, such as contributing to watershed productivity, our results provide useful information for managing streams at the catchment-level. Copyright © 2018 Elsevier B.V. All rights reserved.

Weather patterns as a downscaling tool - evaluating their skill in stratifying local climate variables

NASA Astrophysics Data System (ADS)

Murawski, Aline; Bürger, Gerd; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

The use of a weather pattern based approach for downscaling of coarse, gridded atmospheric data, as usually obtained from the output of general circulation models (GCM), allows for investigating the impact of anthropogenic greenhouse gas emissions on fluxes and state variables of the hydrological cycle such as e.g. on runoff in large river catchments. Here we aim at attributing changes in high flows in the Rhine catchment to anthropogenic climate change. Therefore we run an objective classification scheme (simulated annealing and diversified randomisation - SANDRA, available from the cost733 classification software) on ERA20C reanalyses data and apply the established classification to GCMs from the CMIP5 project. After deriving weather pattern time series from GCM runs using forcing from all greenhouse gases (All-Hist) and using natural greenhouse gas forcing only (Nat-Hist), a weather generator will be employed to obtain climate data time series for the hydrological model. The parameters of the weather pattern classification (i.e. spatial extent, number of patterns, classification variables) need to be selected in a way that allows for good stratification of the meteorological variables that are of interest for the hydrological modelling. We evaluate the skill of the classification in stratifying meteorological data using a multi-variable approach. This allows for estimating the stratification skill for all meteorological variables together, not separately as usually done in existing similar work. The advantage of the multi-variable approach is to properly account for situations where e.g. two patterns are associated with similar mean daily temperature, but one pattern is dry while the other one is related to considerable amounts of precipitation. Thus, the separation of these two patterns would not be justified when considering temperature only, but is perfectly reasonable when accounting for precipitation as well. Besides that, the weather patterns derived from reanalyses data should be well represented in the All-Hist GCM runs in terms of e.g. frequency, seasonality, and persistence. In this contribution we show how to select the most appropriate weather pattern classification and how the classes derived from it are reflected in the GCMs.

Projected impacts of climate change on hydropower potential in China

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

Liu, Xingcai; Tang, Qiuhong; Voisin, Nathalie

Hydropower is an important renewable energy source in China, but it is sensitive to climate change, because the changing climate may alter hydrological conditions (e.g., river flow and reservoir storage). Future changes and associated uncertainties in China's gross hydropower potential (GHP) and developed hydropower potential (DHP) are projected using simulations from eight global hydrological models (GHMs), including a large-scale reservoir regulation model, forced by five general circulation models (GCMs) with climate data under two representative concentration pathways (RCP2.6 and RCP8.5). Results show that the estimation of the present GHP of China is comparable to other studies; overall, the annual GHP is projectedmore » to change by −1.7 to 2 % in the near future (2020–2050) and increase by 3 to 6 % in the late 21st century (2070–2099). The annual DHP is projected to change by −2.2 to −5.4 % (0.7–1.7 % of the total installed hydropower capacity (IHC)) and −1.3 to −4 % (0.4–1.3 % of total IHC) for 2020–2050 and 2070–2099, respectively. Regional variations emerge: GHP will increase in northern China but decrease in southern China – mostly in south central China and eastern China – where numerous reservoirs and large IHCs currently are located. The area with the highest GHP in southwest China will have more GHP, while DHP will reduce in the regions with high IHC (e.g., Sichuan and Hubei) in the future. The largest decrease in DHP (in %) will occur in autumn or winter, when streamflow is relatively low and water use is competitive. Large ranges in hydropower estimates across GHMs and GCMs highlight the necessity of using multimodel assessments under climate change conditions. This study prompts the consideration of climate change in planning for hydropower development and operations in China, to be further combined with a socioeconomic analysis for strategic expansion.« less

Intermodel spread of the double-ITCZ bias in coupled GCMs tied to land surface temperature in AMIP GCMs

NASA Astrophysics Data System (ADS)

Zhou, Wenyu; Xie, Shang-Ping

2017-08-01

Global climate models (GCMs) have long suffered from biases of excessive tropical precipitation in the Southern Hemisphere (SH). The severity of the double-Intertropical Convergence Zone (ITCZ) bias, defined here as the interhemispheric difference in zonal mean tropical precipitation, varies strongly among models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble. Models with a more severe double-ITCZ bias feature warmer tropical sea surface temperature (SST) in the SH, coupled with weaker southeast trades. While previous studies focus on coupled ocean-atmosphere interactions, here we show that the intermodel spread in the severity of the double-ITCZ bias is closely related to land surface temperature biases, which can be further traced back to those in the Atmosphere Model Intercomparison Project (AMIP) simulations. By perturbing land temperature in models, we demonstrate that cooler land can indeed lead to a more severe double-ITCZ bias by inducing the above coupled SST-trade wind pattern in the tropics. The response to land temperature can be consistently explained from both the dynamic and energetic perspectives. Although this intermodel spread from the land temperature variation does not account for the ensemble model mean double-ITCZ bias, identifying the land temperature effect provides insights into simulating a realistic ITCZ for the right reasons.

Land Cover and Climate Change May Limit Invasiveness of Rhododendron ponticum in Wales.

PubMed

Manzoor, Syed A; Griffiths, Geoffrey; Iizuka, Kotaro; Lukac, Martin

2018-01-01

Invasive plant species represent a serious threat to biodiversity precipitating a sustained global effort to eradicate or at least control the spread of this phenomenon. Current distribution ranges of many invasive species are likely to be modified in the future by land cover and climate change. Thus, invasion management can be made more effective by forecasting the potential spread of invasive species. Rhododendron ponticum (L.) is an aggressive invasive species which appears well suited to western areas of the UK. We made use of MAXENT modeling environment to develop a current distribution model and to assess the likely effects of land cover and climatic conditions (LCCs) on the future distribution of this species in the Snowdonia National park in Wales. Six global circulation models (GCMs) and two representative concentration pathways (RCPs), together with a land cover simulation for 2050 were used to investigate species' response to future environmental conditions. Having considered a range of environmental variables as predictors and carried out the AICc-based model selection, we find that under all LCCs considered in this study, the range of R. ponticum in Wales is likely to contract in the future. Land cover and topographic variables were found to be the most important predictors of the distribution of R. ponticum . This information, together with maps indicating future distribution trends will aid the development of mitigation practices to control R. ponticum .

An effective parameter optimization with radiation balance constraints in the CAM5

NASA Astrophysics Data System (ADS)

Wu, L.; Zhang, T.; Qin, Y.; Lin, Y.; Xue, W.; Zhang, M.

2017-12-01

Uncertain parameters in physical parameterizations of General Circulation Models (GCMs) greatly impact model performance. Traditional parameter tuning methods are mostly unconstrained optimization, leading to the simulation results with optimal parameters may not meet the conditions that models have to keep. In this study, the radiation balance constraint is taken as an example, which is involved in the automatic parameter optimization procedure. The Lagrangian multiplier method is used to solve this optimization problem with constrains. In our experiment, we use CAM5 atmosphere model under 5-yr AMIP simulation with prescribed seasonal climatology of SST and sea ice. We consider the synthesized metrics using global means of radiation, precipitation, relative humidity, and temperature as the goal of optimization, and simultaneously consider the conditions that FLUT and FSNTOA should satisfy as constraints. The global average of the output variables FLUT and FSNTOA are set to be approximately equal to 240 Wm-2 in CAM5. Experiment results show that the synthesized metrics is 13.6% better than the control run. At the same time, both FLUT and FSNTOA are close to the constrained conditions. The FLUT condition is well satisfied, which is obviously better than the average annual FLUT obtained with the default parameters. The FSNTOA has a slight deviation from the observed value, but the relative error is less than 7.7‰.

Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

NASA Astrophysics Data System (ADS)

Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

2015-04-01

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean precipitation/evaporation may be up to 10 Wm-2 (about 0.35 mm day-1) larger than the estimate obtained from GPCP. While the main part of this discrepancy is thought to be due to the underestimation of remotely-sensed ocean precipitation, there is also considerable uncertainty about 'unobserved' precipitation over land, in particular in the form of snow in regions of high latitude/altitude. We aim to contribute to this discussion, at least at a qualitative level, by considering case studies of how area-averaged mountain precipitation is represented in different observational datasets and by HadGEM3-GA3 at different resolutions. Our results show that the AGCM simulates considerably more orographic precipitation at higher resolution. We find this at the global scale both for the winter and summer hemispheres, as well as in several case studies in mid-latitude regions. Gridded observations based on gauge measurements generally capture the mesoscale spatial variability of precipitation, but differ strongly from one another in the magnitude of area-averaged precipitation, so that they are of very limited use for evaluating this aspect of the modelled climate. We are currently conducting a sensitivity experiment (coarse-grained orography in high-resolution HadGEM3) to further investigate the resolution sensitivity seen in the model.

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.