Application of Scale-Selective Data Assimilation to Regional Climate Modeling and Prediction

2010 ◽  
Vol 138 (4) ◽  
pp. 1307-1318 ◽  
Author(s):  
Shiqiu Peng ◽  
Lian Xie ◽  
Bin Liu ◽  
Fredrick Semazzi
Keyword(s):  
Data Assimilation ◽  
Regional Climate Model ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Model ◽  
Global Model ◽  
Small Scale ◽  
Pass Filter

Abstract A method referred to as scale-selective data assimilation (SSDA) is designed to inject the large-scale components of the atmospheric circulation from a global model into a regional model to improve regional climate simulations and predictions. The SSDA is implemented through the following procedure: 1) using a low-pass filter to extract the large-scale components of the atmospheric circulation from global analysis or model forecasts; 2) applying the filter to extract the regional-scale and the large-scale components of the atmospheric circulation from the regional model simulations or forecasts; 3) assimilating the large-scale circulation obtained from the global model into the corresponding component simulated by the regional model using the method of three-dimensional variational data assimilation (3DVAR) while maintaining the small-scale components from the regional model during the assimilation cycle; 4) combining the small-scale and the assimilated large-scale components as the adjusted forecasts by the regional climate model and allowing the two components to mutually adjust outside the data assimilation cycle. A case study of summer 2005 seasonal climate hindcasting for the regions of the Atlantic and the eastern United States indicates that the large-scale components from the Global Forecast System (GFS) analysis can be effectively assimilated into the regional model using the scale-selective data assimilation method devised in this study, resulting in an improvement in the overall results from the regional climate model.

scholarly journals A Hybrid Downscaling Approach for Future Temperature and Precipitation Change

2020 ◽  
Vol 59 (11) ◽  
pp. 1793-1807 ◽  
Author(s):  
Helene Birkelund Erlandsen ◽  
Kajsa M. Parding ◽  
Rasmus Benestad ◽  
Abdelkader Mezghani ◽  
Marie Pontoppidan
Keyword(s):  
Regional Climate Model ◽  
Statistical Models ◽  
Large Scale ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Small Scale ◽  
Regional Climate Model Output

AbstractWe used empirical–statistical downscaling in a pseudoreality context, in which both large-scale predictors and small-scale predictands were based on climate model results. The large-scale conditions were taken from a global climate model, and the small-scale conditions were taken from dynamical downscaling of the same global model with a convection-permitting regional climate model covering southern Norway. This hybrid downscaling approach, a “perfect model”–type experiment, provided 120 years of data under the CMIP5 high-emission scenario. Ample calibration samples made rigorous testing possible, enabling us to evaluate the effect of empirical–statistical model configurations and predictor choices and to assess the stationarity of the statistical models by investigating their sensitivity to different calibration intervals. The skill of the statistical models was evaluated in terms of their ability to reproduce the interannual correlation and long-term trends in seasonal 2-m temperature T2m, wet-day frequency fw, and wet-day mean precipitation μ. We found that different 30-yr calibration intervals often resulted in differing statistical models, depending on the specific choice of years. The hybrid downscaling approach allowed us to emulate seasonal mean regional climate model output with a high spatial resolution (0.05° latitude and 0.1° longitude grid) for up to 100 GCM runs while circumventing the issue of short calibration time, and it provides a robust set of empirically downscaled GCM runs.

scholarly journals Regional climate model experiments to investigate the Asian monsoon in the Late Miocene

2011 ◽  
Vol 7 (2) ◽  
pp. 841-886
Author(s):  
H. Tang ◽  
A. Micheels ◽  
J. Eronen ◽  
M. Fortelius
Keyword(s):  
Regional Climate Model ◽  
Summer Monsoon ◽  
Late Miocene ◽  
Asian Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Model ◽  
Global Model ◽  
Monsoon Climate ◽  
Northern Tibetan Plateau

Abstract. The Late Miocene (11.6–5.3 Ma) is a crucial period for the Asian monsoon evolution. However, the spatiotemporal changes of the Asian monsoon system in the Late Miocene are still ambiguous, and the mechanisms responsible for these changes are debated. Here, we present a simulation of the Asian monsoon climate (0 to 60° N and 50 to 140° E) in the Tortonian (11–7 Ma) using the regional climate model CCLM3.2. We employ relatively high spatial resolution (1° × 1°) and adapt the physical boundary conditions such as topography, land-sea distribution and vegetation in the regional model to represent the Late Miocene. As climatological forcing, the output of a Tortonian run with a fully-coupled atmosphere-ocean general circulation model is used. Our results show a stronger-than-present E-Asian winter monsoon wind in the Tortonian, as a result of the enhanced mid-latitude westerly wind of our global forcing and the lowered northern Tibetan Plateau in the regional model. The summer monsoon circulation is generally weakened in our regional Tortonian run compared to today. However, the changes of summer monsoon precipitation exhibit major regional differences. The precipitation decreases in N-China and N-India, but increases in S-China, the western coast and the southern tip of India. This can be attributed to the combined effect of both the regional topographical changes and the other forcings related to our global model. The spread of the dry summer conditions over N-China and NW-India further implies that the monsoonal climate may not be fully established over these regions in the Tortonain. Compared with the global model, the high resolution regional model highlights the spatial differences of the Asian monsoon climate in the Tortonian, and better characterizes the convective activity and its response to topographical changes. It therefore provides a useful and compared to global models complementary tool to improve our understanding of the Asian monsoon evolution in the Late Miocene.

scholarly journals The Effect of Regional Climate Model Domain Choice on the Simulation of Tropical Cyclone–Like Vortices in the Southwestern Indian Ocean

2005 ◽  
Vol 18 (8) ◽  
pp. 1263-1274 ◽  
Author(s):  
Willem A. Landman ◽  
Anji Seth ◽  
Suzana J. Camargo
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Regional Climate Model ◽  
Tropical Cyclones ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Model ◽  
Model Domain ◽  
Southwestern Indian Ocean

Abstract A regional climate model is tested for several domain configurations over the southwestern Indian Ocean to examine the ability of the model to reproduce observed cyclones and their landfalling tracks. The interaction between large-scale and local terrain forcing of tropical storms approaching and transiting the island landmass of Madagascar makes the southwestern Indian Ocean a unique and interesting study area. In addition, tropical cyclones across the southern Indian Ocean are likely to be significantly affected by the large-scale zonal flow. Therefore, the effects of model domain size and the positioning of its lateral boundaries on the simulation of tropical cyclone–like vortices and their tracks on a seasonal time scale are investigated. Four tropical cyclones, which occurred over the southwestern Indian Ocean in January of the years 1995–97, are studied, and four domains are tested. The regional climate model is driven by atmospheric lateral boundary conditions that are derived from large-scale meteorological analyses. The use of analyzed boundary forcing enables comparison with observed cyclones in these tests. Simulations are performed using a 60-km horizontal resolution and for an extended time integration of about 6 weeks. Results show that the positioning of the eastern boundary of the regional model domain is of major importance in the life cycle of simulated tropical cyclone–like vortices: a vortex entering through the eastern boundary of the regional model is generally well simulated. The size of the domain also has a bearing on the ability of the regional model to simulate vortices in the Mozambique Channel, and the island landmass of Madagascar additionally influences storm tracks. These results show that the regional model can produce cyclonelike vortices and their tracks (with some deficiencies) given analyzed lateral boundary forcing. Statistical analyses of GCM-driven nested model ensemble integrations are now required to further address predictive skill of cyclones in the southwestern Indian Ocean and to test if the model can realistically simulate tropical storm genesis as opposed to advecting existing tropical disturbances entering through the model boundaries.

A Methodology for the Regional-Scale-Decomposed Atmospheric Water Budget: Application to a Simulation of the Canadian Regional Climate Model Nested by NCEP–NCAR Reanalyses over North America

2006 ◽  
Vol 134 (3) ◽  
pp. 854-873 ◽  
Author(s):  
Soline Bielli ◽  
René Laprise
Keyword(s):  
Regional Climate Model ◽  
Large Scale ◽  
Climate Model ◽  
Spatial Scales ◽  
Regional Climate ◽  
Moisture Flux ◽  
Added Value ◽  
Small Scale ◽  
Flux Divergence ◽  
Moisture Flux Divergence

Abstract The purpose of this work is to study the added value of a regional climate model with respect to the global analyses used to drive the regional simulation, with a special emphasis on the nonlinear interactions between different spatial scales, focusing on the moisture flux divergence. The atmospheric water budget is used to apply the spatial-scale decomposition approach, as it is a key factor in the energetics of the climate. A Fourier analysis is performed individually for each field on pressure levels. Each field involved in the computation of moisture flux divergence is separated into three components that represent selected scale bands, using the discrete cosine transform. The divergence of the moisture flux is computed from the filtered fields. Instantaneous and monthly mean fields from a simulation performed with the Canadian Regional Climate Model are decomposed and allowed to separate the added value of the model to the total fields. Results show that the added value resides in the nonlinear interactions between large (greater than 1000 km) and small (smaller than 600 km) scales. The main small-scale forcing of the wind is topographic, whereas the humidity tends to show more small scales over the ocean. The time-mean divergence of moisture flux is also decomposed into contributions from stationary eddies and transient eddies. Both stationary and transient eddies are decomposed into different spatial scales and show very different patterns. The time-mean divergence due to transient eddies is dominated by large-scale (synoptic scale) features with little small scales. The divergence due to stationary eddies is a combination of small- and large-scale terms, and the main small-scale contribution occurs over the topography. The same decomposition has been applied to the NCEP–NCAR reanalyses used to drive the regional simulation; the results show that the model best reproduces the time-fluctuation component of the moisture flux divergence, with a correlation between the model simulation and the NCEP–NCAR reanalyses above 0.90.

scholarly journals A Scale-Selective Data Assimilation Approach to Improving Tropical Cyclone Track and Intensity Forecasts in a Limited-Area Model: A Case Study of Hurricane Felix (2007)

2012 ◽  
Vol 27 (1) ◽  
pp. 124-140 ◽  
Author(s):  
Bin Liu ◽  
Lian Xie
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Weather Forecasting ◽  
Forecast Error ◽  
Regional Model ◽  
Small Scale ◽  
Limited Area ◽  
Track Forecast ◽  
Global Models

Abstract Accurately forecasting a tropical cyclone’s (TC) track and intensity remains one of the top priorities in weather forecasting. A dynamical downscaling approach based on the scale-selective data assimilation (SSDA) method is applied to demonstrate its effectiveness in TC track and intensity forecasting. The SSDA approach retains the merits of global models in representing large-scale environmental flows and regional models in describing small-scale characteristics. The regional model is driven from the model domain interior by assimilating large-scale flows from global models, as well as from the model lateral boundaries by the conventional sponge zone relaxation. By using Hurricane Felix (2007) as a demonstration case, it is shown that, by assimilating large-scale flows from the Global Forecast System (GFS) forecasts into the regional model, the SSDA experiments perform better than both the original GFS forecasts and the control experiments, in which the regional model is only driven by lateral boundary conditions. The overall mean track forecast error for the SSDA experiments is reduced by over 40% relative to the control experiments, and by about 30% relative to the GFS forecasts, respectively. In terms of TC intensity, benefiting from higher grid resolution that better represents regional and small-scale processes, both the control and SSDA runs outperform the GFS forecasts. The SSDA runs show approximately 14% less overall mean intensity forecast error than do the control runs. It should be noted that, for the Felix case, the advantage of SSDA becomes more evident for forecasts with a lead time longer than 48 h.

scholarly journals Comparison of 20th century and pre-industrial climate over South America in regional model simulations

2012 ◽  
Vol 8 (5) ◽  
pp. 1599-1620 ◽  
Author(s):  
S. Wagner ◽  
I. Fast ◽  
F. Kaspar
Keyword(s):  
South America ◽  
Greenhouse Gas ◽  
Atmospheric Circulation ◽  
20Th Century ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Model ◽  
Andes Mountains ◽  
Southern South America ◽  
The Andes

Abstract. In this study, we assess how the anthropogenically induced increase in greenhouse gas concentrations affects the climate of central and southern South America. We utilise two regional climate simulations for present day (PD) and pre-industrial (PI) times. These simulations are compared to historical reconstructions in order to investigate the driving processes responsible for climatic changes between the different periods. The regional climate model is validated against observations for both re-analysis data and GCM-driven regional simulations for the second half of the 20th century. Model biases are also taken into account for the interpretation of the model results. The added value of the regional simulation over global-scale modelling relates to a better representation of hydrological processes that are particularly evident in the proximity of the Andes Mountains. Climatic differences between the simulated PD minus PI period agree qualitatively well with proxy-based temperature reconstructions, albeit the regional model overestimates the amplitude of the temperature increase. For precipitation the most important changes between the PD and PI simulation relate to a dipole pattern along the Andes Mountains with increased precipitation over the southern parts and reduced precipitation over the central parts. Here only a few regions show robust similarity with studies based on empirical evidence. However, from a dynamical point-of-view, atmospheric circulation changes related to an increase in high-latitude zonal wind speed simulated by the regional climate model are consistent with numerical modelling studies addressing changes in greenhouse gas concentrations. Our results indicate that besides the direct effect of greenhouse gas changes, large-scale changes in atmospheric circulation and sea surface temperatures also exert an influence on temperature and precipitation changes in southern South America. These combined changes in turn affect the relationship between climate and atmospheric circulation between PD and PI times and should be considered for the statistical reconstruction of climate indices calibrated within present-day climate data.

scholarly journals Regional climate model experiments to investigate the Asian monsoon in the Late Miocene

2011 ◽  
Vol 7 (3) ◽  
pp. 847-868 ◽  
Author(s):  
H. Tang ◽  
A. Micheels ◽  
J. Eronen ◽  
M. Fortelius
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Late Miocene ◽  
Asian Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Northern China ◽  
Regional Model ◽  
Monsoon Climate ◽  
Northern Tibetan Plateau

Abstract. The Late Miocene (11.6–5.3 Ma) is a crucial period in the history of the Asian monsoon. Significant changes in the Asian climate regime have been documented for this period, which saw the formation of the modern Asian monsoon system. However, the spatiotemporal structure of these changes is still ambiguous, and the associated mechanisms are debated. Here, we present a simulation of the average state of the Asian monsoon climate for the Tortonian (11–7 Ma) using the regional climate model CCLM3.2. We employ relatively high spatial resolution (1° × 1°) and adapt the physical boundary conditions such as topography, land-sea distribution and vegetation in the regional model to represent the Late Miocene. As climatological forcing, the output of a Tortonian run with a fully-coupled atmosphere-ocean general circulation model is used. Our regional Tortonian run shows a stronger-than-present East Asian winter monsoon wind as a result of the enhanced mid-latitude westerly wind of our global forcing and the lowered present-day northern Tibetan Plateau in the regional model. The summer monsoon circulation is generally weakened in our regional Tortonian run compared to today. However, the changes of summer monsoon precipitation exhibit major regional differences. Precipitation decreases in northern China and northern India, but increases in southern China, the western coast and the southern tip of India. This can be attributed to the changes in both the regional topography (e.g. the lower northern Tibetan Plateau) and the global climate conditions (e.g. the higher sea surface temperature). The spread of dry summer conditions over northern China and northern Pakistan in our Tortonian run further implies that the monsoonal climate may not have been fully established in these regions in the Tortonian. Compared with the global model, the high resolution regional model highlights the spatial differences of the Asian monsoon climate in the Tortonian, and better characterizes the convective activity and its response to regional topographical changes. It therefore provides a useful and compared to global models, a complementary tool to improve our understanding of the Asian monsoon evolution in the Late Miocene.

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