scholarly journals How well do general circulation models represent low-frequency rainfall variability?

2014 ◽  
Vol 50 (3) ◽  
pp. 2108-2123 ◽  
Author(s):  
Eytan Rocheta ◽  
Michael Sugiyanto ◽  
Fiona Johnson ◽  
Jason Evans ◽  
Ashish Sharma
Keyword(s):  
General Circulation ◽  
Rainfall Variability ◽  
Low Frequency ◽  
General Circulation Models

An applied mathematics perspective on stochastic modelling for climate

2008 ◽  
Vol 366 (1875) ◽  
pp. 2427-2453 ◽  
Author(s):  
Andrew J Majda ◽  
Christian Franzke ◽  
Boualem Khouider
Keyword(s):  
Stochastic Model ◽  
General Circulation ◽  
Applied Mathematics ◽  
Low Frequency ◽  
Lattice Models ◽  
Stochastic Modelling ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Slowing Down ◽  
Low Dimensional

Systematic strategies from applied mathematics for stochastic modelling in climate are reviewed here. One of the topics discussed is the stochastic modelling of mid-latitude low-frequency variability through a few teleconnection patterns, including the central role and physical mechanisms responsible for multiplicative noise. A new low-dimensional stochastic model is developed here, which mimics key features of atmospheric general circulation models, to test the fidelity of stochastic mode reduction procedures. The second topic discussed here is the systematic design of stochastic lattice models to capture irregular and highly intermittent features that are not resolved by a deterministic parametrization. A recent applied mathematics design principle for stochastic column modelling with intermittency is illustrated in an idealized setting for deep tropical convection; the practical effect of this stochastic model in both slowing down convectively coupled waves and increasing their fluctuations is presented here.

scholarly journals An Investigation into the Future Changes in Onset and Cessation of Rain and Their Variability over the Aswa Catchment, Uganda

Climate ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 67
Author(s):  
Michael Iwadra ◽  
P. T. Odirile ◽  
B. P. Parida ◽  
D. B. Moalafhi
Keyword(s):  
General Circulation ◽  
Rainfall Variability ◽  
Standardized Precipitation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Kendall Test ◽  
Close Correlation ◽  
General Circulation Models ◽  
Extreme Precipitation Events ◽  
Future Global Warming ◽  
The Future

Future global warming may result in extreme precipitation events leading to crop, environment and infrastructure damage. Rainfall is a major input for the livelihood of peasant farmers in the Aswa catchment where the future rainfall variability, onset and cessation are also likely to be affected. The Aswa catchment has limited rainfall data; therefore, use of secondary datasets from Tropical Rainfall Measuring Mission (TRMM) is considered in this study, based on the close correlation of the recorded and TRMM rainfall. The latter was used to calibrate the statistical downscaling model for downscaling of two general circulation models to simulate future changes in rainfall. These data were analyzed for trends, wet and dry conditions/variability; onset and cessations of rain using the Mann–Kendall test, Standardized Precipitation Index (SPI) and the cumulative percentage mean rainfall method, respectively. Results show future rainfall is likely to increase, accompanied by increasing variability reaching as high as 118.5%. The frequency of SPI values above 2 (extreme wetness) is to increase above current level during mid and end of the century. The highest rainfall variability is expected especially during the onset and cessation months, which are generally expected to come earlier and later, by up to four and five weeks, respectively. The reliability worsens from the midterm (2036–2065) to long term (2066–2099). These likely changes in rainfall quantities, variability, onset and cessation months are some of the key rainfall dynamics that have implications for future arable agriculture, environment and water resource availability and planning over the Aswa catchment, as is increasingly the case elsewhere.

scholarly journals An Assessment of GCM Skill in Simulating Persistence across Multiple Time Scales

2011 ◽  
Vol 24 (14) ◽  
pp. 3609-3623 ◽  
Author(s):  
Fiona Johnson ◽  
Seth Westra ◽  
Ashish Sharma ◽  
Andrew J. Pitman
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Large Scale ◽  
Low Frequency ◽  
General Circulation Models ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Max Planck ◽  
Reservoir Storage ◽  
Low Frequency Variability

Abstract Climate change impact studies for water resource applications, such as the development of projections of reservoir yields or the assessment of likely frequency and amplitude of drought under a future climate, require that the year-to-year persistence in a range of hydrological variables such as catchment average rainfall be properly represented. This persistence is often attributable to low-frequency variability in the global sea surface temperature (SST) field and other large-scale climate variables through a complex sequence of teleconnections. To evaluate the capacity of general circulation models (GCMs) to accurately represent this low-frequency variability, a set of wavelet-based skill measures has been developed to compare GCM performance in representing interannual variability with the observed global SST data, as well as to assess the extent to which this variability is imparted in precipitation and surface pressure anomaly fields. A validation of the derived skill measures is performed using GCM precipitation as an input in a reservoir storage context, with the accuracy of reservoir storage estimates shown to be improved by using GCM outputs that correctly represent the observed low-frequency variability. Significant differences in the performance of different GCMs is demonstrated, suggesting that judicious selection of models is required if the climate impact assessment is sensitive to low-frequency variability. The two GCMs that were found to exhibit the most appropriate representation of global low-frequency variability for individual variables assessed were the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ECHAM4 and L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4); when considering all three variables, the Max Planck Institute (MPI) ECHAM5 performed well. Importantly, models that represented interannual variability well for SST also performed well for the other two variables, while models that performed poorly for SST also had consistently low skill across the remaining variables.

scholarly journals An assessment of the skill of downscaled GCM outputs in simulating historical patterns of rainfall variability in South Africa

2013 ◽  
Vol 45 (1) ◽  
pp. 134-147 ◽  
Author(s):  
D. A. Hughes ◽  
S. Mantel ◽  
T. Mohobane
Keyword(s):  
South Africa ◽  
Water Resources ◽  
General Circulation ◽  
Hydrological Model ◽  
Rainfall Variability ◽  
General Circulation Models ◽  
Local Scale ◽  
Coastal Areas ◽  
General Applicability ◽  
Modelling Studies

Uncertainties associated with General Circulation Models (GCMs) and the downscaling methods used for regional or local scale hydrological modelling can result in substantial differences in estimates of future water resources availability. This paper assesses the skill of nine statistically downscaled GCMs in reproducing historical climate for 15 catchments in five regions of South Africa. The identification of skilled GCMs may reduce the uncertainty in future predictions and the focus is on rainfall skill as the GCMs show very similar patterns of change in temperature. The skill tests were designed to assess whether the GCMs are able to realistically reproduce precipitation distribution statistics and patterns of seasonality, persistence and extremes. Some models are consistently less skilful for the regions assessed, while some are generally more skilful with some regionally specific exceptions. There are differences in the GCMs skill across the different regions and in the skill ranking between coastal areas and inland regions. However, only a limited reduction in uncertainty is achieved when using only the downscaled GCM outputs identified as being skilled in a hydrological model for one of the regions. Further modelling studies are required to determine the general applicability of this observation.

scholarly journals Multidecadal to Centennial Variability of the AMOC: HadCM3 and a Perturbed Physics Ensemble

2013 ◽  
Vol 26 (7) ◽  
pp. 2390-2407 ◽  
Author(s):  
Laura Jackson ◽  
Michael Vellinga
Keyword(s):  
General Circulation ◽  
Low Frequency ◽  
Coupled Model ◽  
General Circulation Models ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Equatorial Atlantic ◽  
Small Ensemble ◽  
Background Climate ◽  
Perturbed Physics

Abstract Multidecadal to centennial variability of the Atlantic meridional overturning circulation (AMOC) is investigated in a multi-thousand-year simulation of the third version of the Hadley Centre Coupled Model (HadCM3) and in an ensemble of general circulation models (GCMs) based on HadCM3 with perturbed physics. Large changes in the AMOC in the standard HadCM3 are strongly related to salinity anomalies in the deep-water formation regions, with anomalies arriving via two pathways. The first is from a coupled feedback in the equatorial Atlantic Ocean, described previously by Vellinga and Wu, and the second is from variability in the Arctic Ocean, possibly driven by stochastic sea level pressure. The low-frequency variability of the AMOC in HadCM3 is well predicted from salinity anomalies from these two pathways. The sensitivity of these processes to model physics is investigated using a small ensemble based on HadCM3 where parameters relating to physical processes are varied. The AMOC responds consistently to the salinity anomalies in the ensemble members. However, 1) the timing of the response depends on the background climate state and 2) some ensemble members have significantly larger AMOC and salinity variability than in standard HadCM3 simulations. In this small ensemble, the presence and strength of multidecadal to centennial AMOC variability is associated with the variability of salinity exported from the Arctic, with little multidecadal to centennial variability of either in the coldest members. This demonstrates how the background climate state can alter the frequency and strength of AMOC variability and is a first step toward understanding how AMOC variability differs within a multimodel context.

scholarly journals The Importance of High-Frequency Sea Surface Temperature Variability to the Intraseasonal Oscillation of Indian Monsoon Rainfall

2008 ◽  
Vol 21 (23) ◽  
pp. 6119-6140 ◽  
Author(s):  
Nicholas P. Klingaman ◽  
Peter M. Inness ◽  
Hilary Weller ◽  
Julia M. Slingo
Keyword(s):  
High Frequency ◽  
General Circulation ◽  
Climate Models ◽  
Indian Monsoon ◽  
Rainfall Variability ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Propagation Speed ◽  
General Circulation Models ◽  
Atmospheric Model

Abstract While the Indian monsoon exhibits substantial variability on interannual time scales, its intraseasonal variability (ISV) is of greater magnitude and hence of critical importance for monsoon predictability. This ISV comprises a 30–50-day northward-propagating oscillation (NPISO) between active and break events of enhanced and reduced rainfall, respectively, over the subcontinent. Recent studies have implied that coupled general circulation models (CGCMs) were better able to simulate the NPISO than their atmosphere-only counterparts (AGCMs). These studies have forced their AGCMs with SSTs from coupled integrations or observations from satellite-based infrared sounders, both of which underestimate the ISV of tropical SSTs. The authors have forced the 1.25° × 0.83° Hadley Centre Atmospheric Model (HadAM3) with a daily, high-resolution, observed SST analysis from the United Kingdom National Center for Ocean Forecasting that contains greater ISV in the Indian Ocean than past products. One ensemble of simulations was forced by daily SSTs, a second with monthly means, and a third with 5-day means. The ensemble with daily SSTs displayed significantly greater variability in 30–50-day rainfall across the monsoon domain than the ensemble with monthly mean SSTs, variability similar to satellite-derived precipitation analyses. Individual ensemble members with daily SSTs contained intraseasonal events with a strength, a propagation speed, and an organization that closely matched observed events. When ensemble members with monthly mean SSTs displayed power in intraseasonal rainfall, the events were weak and disorganized, and they propagated too quickly. The ensemble with 5-day means had less intraseasonal rainfall variability than the ensemble with daily SSTs but still produced coherent NPISO-like events, indicating that SST variability at frequencies higher than 5 days contributes to but is not critical for simulations of the NPISO. It is concluded that high-frequency SST anomalies not only increased variance in intraseasonal rainfall but helped to organize and maintain coherent NPISO-like convective events. Further, the results indicate that an AGCM can respond to realistic and frequent SST forcing to generate an NPISO that closely resembles observations. These results have important implications for simulating the NPISO in AGCMs and coupled climate models, as well as for predicting tropical ISV in short- and medium-range weather forecasts.

scholarly journals Change in Coherence of Interannual Variability of Summer Rainfall over the Western Pacific around the Early 2000s: Role of Indo-Pacific Ocean Forcing

2018 ◽  
Vol 31 (9) ◽  
pp. 3525-3538 ◽  
Author(s):  
Zhuoqi He ◽  
Renguang Wu
Keyword(s):  
Indian Ocean ◽  
North Pacific ◽  
General Circulation ◽  
Rainfall Variability ◽  
Summer Rainfall ◽  
General Circulation Models ◽  
North Indian Ocean ◽  
Western Pacific ◽  
Sst Forcing ◽  
The Western Pacific

The observations show that the covariability between the western North Pacific (WNP) and the South China Sea (SCS) summer rainfall has experienced an obvious weakening since the early 2000s. During the period 1982–2003, the combined north Indian Ocean (NIO), central North Pacific (CNP), and central equatorial Pacific (CEP) sea surface temperature (SST) forcing results in a high coherence between the WNP and SCS summer rainfall variations via a zonally elongated anomalous lower-level cyclone over the western Pacific. During the period 2004–16, the Indian Ocean SST contribution is largely weakened, and the WNP rainfall variability is dominated by the enhanced Pacific SST forcing with an eastward retreated lower-level wind and rainfall anomalies, whereas the SCS rainfall variability is mainly associated with local air–sea interaction processes. The results obtained from observational analysis are supported by numerical experiments with atmospheric and coupled general circulation models. The change in the coherence of interannual summer rainfall variability over the WNP and SCS has important implications for regional climate prediction in South and East Asia.

An Improved Daily Weather Generator for the Assessment of Regional Climate Change Impacts

2021 ◽  
Author(s):  
Mohammad Reza Khazaei ◽  
Mehraveh Hasirchian ◽  
Bagher Zahabiyoun
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Regional Climate ◽  
Low Frequency ◽  
Climate Change Impacts ◽  
Regional Climate Change ◽  
General Circulation Models ◽  
Weather Generator ◽  
Weather Data ◽  
Monthly Precipitation

Abstract Weather Generators (WGs) are one of the major downscaling tools for assessing regional climate change impacts. However, some deficiencies in the performance of WGs have limited their usage. This paper presents a method for correcting the low-frequency variability (LFV) of precipitation in the Improved Weather Generator (IWG) model. The method is based on bias correction in the monthly precipitation distribution of the generated daily series. The performance of the modified model was tested directly by comparing the statistics of generated and observed weather data for 14 stations, and also indirectly by comparing the characteristics of simulated stream-flows of a basin from the simulations run based on generated and observed weather data. The results showed that the method not only corrected the LFV of precipitation but also improved the reproduction of many other statistics. The provided IWG2 model can serve as a useful tool for the downscaling of General Circulation Models (GCMs) scenarios to assess regional climate change impacts, especially hydrological effects.

scholarly journals An Evaluation of Statistical Downscaling Techniques for Simulating Daily Rainfall Occurrences in the Upper Ping River Basin

Hydrology ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 63
Author(s):  
Sirikanya Cheevaprasert ◽  
Rajeshwar Mehrotra ◽  
Sansarith Thianpopirug ◽  
Nutchanart Sriwongsitanon
Keyword(s):  
River Basin ◽  
Statistical Downscaling ◽  
General Circulation ◽  
Low Frequency ◽  
Daily Rainfall ◽  
General Circulation Models ◽  
Research Area ◽  
Single Site ◽  
Future Research ◽  
Rainfall Occurrences

This study presents an exhaustive evaluation of the performance of three statistical downscaling techniques for generating daily rainfall occurrences at 22 rainfall stations in the upper Ping river basin (UPRB), Thailand. The three downscaling techniques considered are the modified Markov model (MMM), a stochastic model, and two variants of regression models, statistical models, one with single relationship for all days of the year (RegressionYrly) and the other with individual relationships for each of the 366 days (Regression366). A stepwise regression is applied to identify the significant atmospheric (ATM) variables to be used as predictors in the downscaling models. Aggregated wetness state indicators (WIs), representing the recent past wetness state for the previous 30, 90 or 365 days, are also considered as additional potential predictors since they have been effectively used to represent the low-frequency variability in the downscaled sequences. Grouping of ATM and all possible combinations of WI is used to form eight predictor sets comprising ATM, ATM-WI30, ATM-WI90, ATM-WI365, ATM-WI30&90, ATM-WI30&365, ATM-WI90&365 and ATM-WI30&90&365. These eight predictor sets were used to run the three downscaling techniques to create 24 combination cases. These cases were first applied at each station individually (single site simulation) and thereafter collectively at all sites (multisite simulations) following multisite downscaling models leading to 48 combination cases in total that were run and evaluated. The downscaling models were calibrated using atmospheric variables from the National Centers for Environmental Prediction (NCEP) reanalysis database and validated using representative General Circulation Models (GCM) data. Identification of meaningful predictors to be used in downscaling, calibration and setting up of downscaling models, running all 48 possible predictor combinations and a thorough evaluation of results required considerable efforts and knowledge of the research area. The validation results show that the use of WIs remarkably improves the accuracy of downscaling models in terms of simulation of standard deviations of annual, monthly and seasonal wet days. By comparing the overall performance of the three downscaling techniques keeping common sets of predictors, MMM provides the best results of the simulated wet and dry spells as well as the standard deviation of monthly, seasonal and annual wet days. These findings are consistent across both single site and multisite simulations. Overall, the MMM multisite model with ATM and wetness indicators provides the best results. Upon evaluating the combinations of ATM and sets of wetness indicators, ATM-WI30&90 and ATM-WI30&365 were found to perform well during calibration in reproducing the overall rainfall occurrence statistics while ATM-WI30&365 was found to significantly improve the accuracy of monthly wet spells over the region. However, these models perform poorly during validation at annual time scale. The use of multi-dimension bias correction approaches is recommended for future research.

scholarly journals Stochastic Parameterization Schemes for Use in Realistic Climate Models

2011 ◽  
Vol 68 (2) ◽  
pp. 284-299 ◽  
Author(s):  
Joel Culina ◽  
Sergey Kravtsov ◽  
Adam H. Monahan
Keyword(s):  
General Circulation ◽  
Ad Hoc ◽  
Climate Models ◽  
Low Frequency ◽  
General Circulation Models ◽  
Planetary Scale ◽  
Low Frequency Variability ◽  
Quasigeostrophic Model ◽  
Low Dimensional ◽  
O 10

Abstract Stochastic parameterizations of fast-evolving, subgrid-scale processes are increasingly being used in a range of models from conceptual models to general circulation models. However, stochastic terms are generally included in an ad hoc fashion. In this study, a systematic method—“Hasselmann’s method”—of stochastic parameterization is developed through the direct application of rigorously justified limit theorems that predict the effective slow dynamics in systems with coupled slow and fast variables. The multiple Hasselmann models form a hierarchy of models ordered by the time scales over which they are expected to provide good approximations to the slowly evolving variables. Adaptable, efficient algorithms for integrating these reduced models are developed that require minimal changes to the unreduced model. Hasselmann’s method is tested on an O(10 000)-dimensional (planetary and synoptic scale) quasigeostrophic model of atmospheric low-frequency variability. Low-dimensional deterministic and stochastic models in the planetary-scale modes alone are derived, which accurately generate the statistics of the corresponding modes of the unreduced model, including the statistical signatures of jet regime behavior. It is shown that deterministic nonlinearity through slow forcing averaged with respect to the fast modes distribution dominates over multiplicative noise in generating the regime behavior.

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