scholarly journals Skill, Correction, and Downscaling of GCM-Simulated Precipitation

2012 ◽  
Vol 25 (11) ◽  
pp. 3970-3984 ◽  
Author(s):  
Jonathan M. Eden ◽  
Martin Widmann ◽  
David Grawe ◽  
Sebastian Rast
Keyword(s):  
Real World ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Atmospheric Variability ◽  
Promising Alternative ◽  
Global Correlation ◽  
Simulated Precipitation ◽  
Simple Scaling ◽  
Set Up

The ability of general circulation models (GCMs) to correctly simulate precipitation is usually assessed by comparing simulated mean precipitation with observed climatologies. However, to what extent the skill in simulating average precipitation indicates how well the models represent temporal changes is unclear. A direct assessment of the latter is hampered by the fact that freely evolving climate simulations for past periods are not set up to reproduce the specific evolution of internal atmospheric variability. Therefore, model-to-real-world comparisons of time series of daily, monthly, or annual precipitation are not meaningful. Here, for the first time, the authors quantify GCM skill in simulating precipitation variability using simulations in which the temporal evolution of the large-scale atmospheric state closely matches that of the real world. This is achieved by nudging the atmospheric states in the ECHAM5 GCM, but crucially not the precipitation field itself, toward the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). Global correlation maps between observed and simulated seasonal precipitation allow areas in which simulated future precipitation changes are likely to be meaningful to be identified. In many areas, correlations higher than 0.8 are found. This means also that in these regions the simulated precipitation is a very good predictor for the true precipitation, and thus a statistical correction of the simulated precipitation, which can include a downscaling component, can provide useful estimates for local-scale precipitation. The authors show that a simple scaling of the simulated precipitation performs well in a cross validation and thus appears to be a promising alternative to standard statistical downscaling approaches.

scholarly journals Downscaling of GCM-Simulated Precipitation Using Model Output Statistics

2014 ◽  
Vol 27 (1) ◽  
pp. 312-324 ◽  
Author(s):  
Jonathan M. Eden ◽  
Martin Widmann
Keyword(s):  
Statistical Downscaling ◽  
Temporal Variability ◽  
General Circulation ◽  
Large Scale ◽  
Principal Component ◽  
General Circulation Models ◽  
Model Output ◽  
Local Scaling ◽  
Simulated Precipitation ◽  
Model Output Statistics

Abstract Producing reliable estimates of changes in precipitation at local and regional scales remains an important challenge in climate science. Statistical downscaling methods are often utilized to bridge the gap between the coarse resolution of general circulation models (GCMs) and the higher resolutions at which information is required by end users. As the skill of GCM precipitation, particularly in simulating temporal variability, is not fully understood, statistical downscaling typically adopts a perfect prognosis (PP) approach in which high-resolution precipitation projections are based on real-world statistical relationships between large-scale atmospheric predictors and local-scale precipitation. Using a nudged simulation of the ECHAM5 GCM, in which the large-scale weather states are forced toward observations of large-scale circulation and temperature for the period 1958–2001, previous work has shown ECHAM5 skill in simulating temporal variability of precipitation to be high in many parts of the world. Here, the same nudged simulation is used in an alternative downscaling approach, based on model output statistics (MOS), in which statistical corrections are derived for simulated precipitation. Cross-validated MOS corrections based on maximum covariance analysis (MCA) and principal component regression (PCR), in addition to a simple local scaling, are shown to perform strongly throughout much of the extratropics. Correlation between downscaled and observed monthly-mean precipitation is as high as 0.8–0.9 in many parts of Europe, North America, and Australia. For these regions, MOS clearly outperforms PP methods that use temperature and circulation as predictors. The strong performance of MOS makes such an approach to downscaling attractive and potentially applicable to climate change simulations.

Local Regimes of Atmospheric Variability: A Case Study of Southern California

2006 ◽  
Vol 19 (17) ◽  
pp. 4308-4325 ◽  
Author(s):  
Sebastien Conil ◽  
Alex Hall
Keyword(s):  
Spatial Structure ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Spatial Scales ◽  
Surface Wind ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Atmospheric Variability ◽  
Composite Surface

Abstract The primary regimes of local atmospheric variability are examined in a 6-km regional atmospheric model of the southern third of California, an area of significant land surface heterogeneity, intense topography, and climate diversity. The model was forced by reanalysis boundary conditions over the period 1995–2003. The region is approximately the same size as a typical grid box of the current generation of general circulation models used for global climate prediction and reanalysis product generation, and so can be thought of as a laboratory for the study of climate at spatial scales smaller than those resolved by global simulations and reanalysis products. It is found that the simulated circulation during the October–March wet season, when variability is most significant, can be understood through an objective classification technique in terms of three wind regimes. The composite surface wind patterns associated with these regimes exhibit significant spatial structure within the model domain, consistent with the complex topography of the region. These regimes also correspond nearly perfectly with the simulation’s highly structured patterns of variability in hydrology and temperature, and therefore are the main contributors to the local climate variability. The regimes are approximately equally likely to occur regardless of the phase of the classical large-scale modes of atmospheric variability prevailing in the Pacific–North American sector. The high degree of spatial structure of the local regimes and their tightly associated climate impacts, as well as their ambiguous relationship with the primary modes of large-scale variability, demonstrate that the local perspective offered by the high-resolution model is necessary to understand and predict the climate variations of the region.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

scholarly journals Cloud and Precipitation Parameterizations in Modeling and Variational Data Assimilation: A Review

2007 ◽  
Vol 64 (11) ◽  
pp. 3766-3784 ◽  
Author(s):  
Philippe Lopez
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Large Scale ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Variational Data Assimilation ◽  
Current Status ◽  
General Question ◽  
Observation Error ◽  
Moist Processes

Abstract This paper first reviews the current status, issues, and limitations of the parameterizations of atmospheric large-scale and convective moist processes that are used in numerical weather prediction and climate general circulation models. Both large-scale (resolved) and convective (subgrid scale) moist processes are dealt with. Then, the general question of the inclusion of diabatic processes in variational data assimilation systems is addressed. The focus is put on linearity and resolution issues, the specification of model and observation error statistics, the formulation of the control vector, and the problems specific to the assimilation of observations directly affected by clouds and precipitation.

scholarly journals PDO-Related Wintertime Atmospheric Anomalies over the Midlatitude North Pacific: Local versus Remote SST Forcing

2020 ◽  
Vol 33 (16) ◽  
pp. 6989-7010 ◽  
Author(s):  
Lingfeng Tao ◽  
Xiu-Qun Yang ◽  
Jiabei Fang ◽  
Xuguang Sun
Keyword(s):  
North Pacific ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Transient Eddy ◽  
Atmospheric Variability ◽  
Ridge Structure ◽  
Sst Gradient ◽  
Meridional Sst Gradient ◽  
Sst Anomalies

AbstractObserved wintertime atmospheric anomalies over the central North Pacific associated with the Pacific decadal oscillation (PDO) are characterized by a cold/trough (warm/ridge) structure, that is, an anomalous equivalent barotropic low (high) over a negative (positive) sea surface temperature (SST) anomaly. While the midlatitude atmosphere has its own strong internal variabilities, to what degree local SST anomalies can affect the midlatitude atmospheric variability remains unclear. To identify such an impact, three atmospheric general circulation model experiments each having a 63-yr-long simulation are conducted. The control run forced by observed global SST reproduces well the observed PDO-related cold/trough (warm/ridge) structure. However, the removal of the midlatitude North Pacific SST variabilities in the first sensitivity run reduces the atmospheric response by roughly one-third. In the second sensitivity run in which large-scale North Pacific SST variabilities are mostly kept, but their frontal-scale meridional gradients are sharply smoothed, simulated PDO-related cold/trough (warm/ridge) anomalies are also reduced by nearly one-third. Dynamical diagnoses exhibit that such a reduction is primarily due to the weakened transient eddy activities that are induced by weakened meridional SST gradient anomalies, in which the transient eddy vorticity forcing plays a crucial role. Therefore, it is suggested that midlatitude North Pacific SST anomalies make a considerable (approximately one-third) contribution to the observed PDO-related cold/trough (warm/ridge) anomalies in which the frontal-scale meridional SST gradient (oceanic front) is a key player, although most of those atmospheric anomalies are determined by the SST variabilities outside of the midlatitude North Pacific.

scholarly journals Assessment of Numerical Simulations of Deep Circulation and Variability in the Gulf of Mexico Using Recent Observations

2020 ◽  
Vol 50 (4) ◽  
pp. 1045-1064 ◽  
Author(s):  
Steven L. Morey ◽  
Ganesh Gopalakrishnan ◽  
Enric Pallás Sanz ◽  
Joao Marcos Azevedo Correia De Souza ◽  
Kathleen Donohue ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Numerical Simulations ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Striking Difference ◽  
Loop Current ◽  
Deep Circulation ◽  
Velocity Statistics ◽  
Current Region

AbstractThree simulations of the circulation in the Gulf of Mexico (the “Gulf”) using different numerical general circulation models are compared with results of recent large-scale observational campaigns conducted throughout the deep (>1500 m) Gulf. Analyses of these observations have provided new understanding of large-scale mean circulation features and variability throughout the deep Gulf. Important features include cyclonic flow along the continental slope, deep cyclonic circulation in the western Gulf, a counterrotating pair of cells under the Loop Current region, and a cyclonic cell to the south of this pair. These dominant circulation features are represented in each of the ocean model simulations, although with some obvious differences. A striking difference between all the models and the observations is that the simulated deep eddy kinetic energy under the Loop Current region is generally less than one-half of that computed from observations. A multidecadal integration of one of these numerical simulations is used to evaluate the uncertainty of estimates of velocity statistics in the deep Gulf computed from limited-length (4 years) observational or model records. This analysis shows that the main deep circulation features identified from the observational studies appear to be robust and are not substantially impacted by variability on time scales longer than the observational records. Differences in strengths and structures of the circulation features are identified, however, and quantified through standard error analysis of the statistical estimates using the model solutions.

scholarly journals The Canadian Earth System Model version 5 (CanESM5.0.3)

2019 ◽  
Vol 12 (11) ◽  
pp. 4823-4873 ◽  
Author(s):  
Neil C. Swart ◽  
Jason N. S. Cole ◽  
Viatcheslav V. Kharin ◽  
Mike Lazare ◽  
John F. Scinocca ◽  
...  
Keyword(s):  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Earth System Model ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Historical Climate ◽  
Model Version

Abstract. The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization, and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large-scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three-dimensional atmosphere (T63 spectral resolution equivalent roughly to 2.8∘) and ocean (nominally 1∘) general circulation models, a sea-ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science and service applications in Canada.

scholarly journals Futurizing politics and the sustainability of real-world experiments: what role for innovation and exnovation in the German energy transition?

2019 ◽  
Vol 14 (4) ◽  
pp. 991-1000 ◽  
Author(s):  
Martin David ◽  
Matthias Gross
Keyword(s):  
Real World ◽  
Energy Production ◽  
Large Scale ◽  
Energy Transition ◽  
System Transformation ◽  
Conceptual Strategy ◽  
Set Up

Abstract The German energy transition towards more sustainable forms of energy production has been characterized as a large-scale or real-world experiment. Whereas experiments are open-ended processes set up explicitly to allow (or even generate) surprises, by contrast sustainability implies the pursuit of clearly defined, normative ends. Whereas much of the literature on system transformation builds on the concept of innovation, our hypothesis is that focusing on the “natural” flipside of innovation—called here “exnovation,” i.e., departing from unsustainable pathways—should also be seen as a valuable conceptual strategy for coping with the tension between the unavoidable indeterminacy resulting from unknown risks and the necessary amendment and redefinition of goals and rules. In this paper the German energy transition (Energiewende) is used to exemplify the recursive processes of experimentation that make it possible to accommodate surprise, and, thus, to conceptualize the unavoidable tension between innovation and the maintenance of older, unsustainable structures.

Hadley Cell Widening: Model Simulations versus Observations

2009 ◽  
Vol 22 (10) ◽  
pp. 2713-2725 ◽  
Author(s):  
Celeste M. Johanson ◽  
Qiang Fu
Keyword(s):  
Twentieth Century ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Hadley Cell ◽  
Climate Projections ◽  
The West ◽  
Model Simulations ◽  
Stratospheric Cooling ◽  
Future Climate Projections

Abstract Observations show that the Hadley cell has widened by about 2°–5° since 1979. This widening and the concomitant poleward displacement of the subtropical dry zones may be accompanied by large-scale drying near 30°N and 30°S. Such drying poses a risk to inhabitants of these regions who are accustomed to established rainfall patterns. Simple and comprehensive general circulation models (GCMs) indicate that the Hadley cell may widen in response to global warming, warming of the west Pacific, or polar stratospheric cooling. The combination of these factors may be responsible for the recent observations. But there is no study so far that has compared the observed widening to GCM simulations of twentieth-century climate integrated with historical changes in forcings. Here the Hadley cell widening is assessed in current GCMs from historical simulations of the twentieth century as well as future climate projections and preindustrial control runs. The authors find that observed widening cannot be explained by natural variability. This observed widening is also significantly larger than in simulations of the twentieth and twenty-first centuries. These results illustrate the need for further investigation into the discrepancy between the observed and simulated widening of the Hadley cell.

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