Downscaling of precipitation on a lake basin: evaluation of rule and decision tree induction algorithms

2012 ◽  
Vol 43 (3) ◽  
pp. 215-230 ◽  
Author(s):  
Manish Kumar Goyal ◽  
C. S. P. Ojha
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Lake Basin ◽  
Monthly Precipitation ◽  
M5 Model Tree ◽  
Reanalysis Dataset ◽  
Model Tree ◽  
Basin Scale ◽  
M5 Model

We investigate the performance of existing state-of-the-art rule induction and tree algorithms, namely Single Conjunctive Rule Learner, Decision Table, M5 Model Tree, Decision Stump and REPTree. Downscaling models are developed using these algorithms to obtain projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of these algorithms is evaluated through application to downscale the predictand for the Lake Pichola region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centre for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000 and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. M5 Model Tree algorithm was found to yield better performance among all other learning techniques explored in the present study. The precipitation is projected to increase in future for A2 and A1B scenarios, whereas it is least for B1 and COMMIT scenarios using predictors.

scholarly journals Internal Variability of the Canadian RCM’s Hydrological Variables at the Basin Scale in Quebec and Labrador

2012 ◽  
Vol 13 (2) ◽  
pp. 443-462 ◽  
Author(s):  
Marco Braun ◽  
Daniel Caya ◽  
Anne Frigon ◽  
Michel Slivitzky
Keyword(s):  
Climate Model ◽  
Model Simulation ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Internal Variability ◽  
Spectral Nudging ◽  
Model Driven ◽  
Basin Scale ◽  
Hydrological Variables

Abstract The effect of a regional climate model’s (RCM’s) internal variability (IV) on climate statistics of annual series of hydrological variables is investigated at the scale of 21 eastern Canada watersheds in Quebec and Labrador. The analysis is carried out on 30-yr pairs of simulations (twins), performed with the Canadian Regional Climate Model (CRCM) for present (reanalysis and global climate model driven) and future (global climate model driven) climates. The twins differ only by the starting date of the regional simulation—a standard procedure used to trigger internal variability in RCMs. Two different domain sizes are considered: one comparable to domains used for RCM simulations over Europe and the other comparable to domains used for North America. Results for the larger North American domain indicate that mean relative differences between twin pairs of 30-yr climates reach ±5% when spectral nudging is used. Larger differences are found for extreme annual events, reaching about ±10% for 10% and 90% quantiles (Q10 and Q90). IV is smaller by about one order of magnitude in the smaller domain. Internal variability is unaffected by the period (past versus future climate) and by the type of driving data (reanalysis versus global climate model simulation) but shows a dependence on watershed size. When spectral nudging is deactivated in the large domain, the relative difference between pairs of 30-yr climate means almost doubles and approaches the magnitude of a global climate model’s internal variability. This IV at the level of the natural climate variability has a profound impact on the interpretation, analysis, and validation of RCM simulations over large domains.

scholarly journals Optimal Spectral Nudging for Global Dynamic Downscaling

2017 ◽  
Vol 145 (3) ◽  
pp. 909-927 ◽  
Author(s):  
Martina Schubert-Frisius ◽  
Frauke Feser ◽  
Hans von Storch ◽  
Sebastian Rast
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Spatial Scales ◽  
Global Climate Model ◽  
Circulation Model ◽  
Prognostic Variables ◽  
Reanalysis Dataset ◽  
Spectral Nudging ◽  
High Dependency

This study analyzes a method of constructing a homogeneous, high-resolution global atmospheric hindcast. The method is the spectral nudging technique, which was applied to a state-of-the-art general circulation model (ECHAM6, T255L95). Large spatial scales of the global climate model prognostic variables were spectrally nudged toward a reanalysis dataset (NCEP-1, T62L28) for the past few decades. The main idea is the addition of dynamically consistent regional weather details to the coarse-grid NCEP-1 reanalysis. A large number of sensitivity experiments was performed, using different nudging e-folding times, vertical profiles, wavenumbers, and variables. Comparisons with observations and several reanalyses showed a high dependency on the variations of the nudging configuration. At the global scale, the accordance is very high for extratropical regions and lower in the tropics. A wavenumber truncation of 30, a relatively short e-folding time of 50 min, and a plateau-shaped nudging profile applied only to divergence and vorticity generally yielded the best results. This is one of the first global spectral nudging hindcast studies and the first applying an altitude-dependent profile to selected prognostic variables. The method can be applied to reconstructing the history of extreme events such as intense storms within the context of ongoing climate change.

scholarly journals Evaluating Hydroclimatic Change Signals from Statistically and Dynamically Downscaled GCMs and Hydrologic Models

2014 ◽  
Vol 15 (2) ◽  
pp. 844-860 ◽  
Author(s):  
Rajesh R. Shrestha ◽  
Markus A. Schnorbus ◽  
Arelia T. Werner ◽  
Francis W. Zwiers
Keyword(s):  
River Basin ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Peace River ◽  
Simulated Precipitation ◽  
Basin Scale ◽  
Hydroclimatic Change

Abstract This study analyzed potential hydroclimatic change in the Peace River basin in the province of British Columbia, Canada, based on two structurally different approaches: (i) statistically downscaled global climate models (GCMs) using the bias-corrected spatial disaggregation (BCSD) and (ii) dynamically downscaled GCM with the Canadian Regional Climate Model (CRCM). Additionally, simulated hydrologic changes from the GCM–BCSD-driven Variable Infiltration Capacity (VIC) model were compared to the CRCM integrated Canadian Land Surface Scheme (CLASS) output. The results show good agreements of the GCM–BCSD–VIC simulated precipitation, temperature, and runoff with observations, while the CRCM-simulated results differ substantially from observations. Nevertheless, differences (between the 2050s and 1970s) obtained from the two approaches are qualitatively similar for precipitation and temperature, although they are substantially different for snow water equivalent and runoff. The results obtained from the five Coupled Global Climate Model, version 3, (CGCM3)-driven CRCM runs are similar, suggesting that the multidecadal internal variability is not a large source of uncertainty for the Peace River basin. Overall, the GCM–BCSD–VIC approach, for now, remains the preferred approach for projecting basin-scale future hydrologic changes, provided that it explicitly accounts for the biases and includes plausible snow and runoff parameterizations. However, even with the GCM–BCSD–VIC approach, projections differ considerably depending on which of an ensemble of eight GCMs is used. Such differences reemphasize the uncertain nature of future hydroclimatic projections.

scholarly journals Hydrological simulations driven by RCM climate scenarios at basin scale in the Po River, Italy

2014 ◽  
Vol 364 ◽  
pp. 128-133 ◽  
Author(s):  
R. Vezzoli ◽  
M. Del Longo ◽  
P. Mercogliano ◽  
M. Montesarchio ◽  
S. Pecora ◽  
...  
Keyword(s):  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Balance Model ◽  
Climate Change Scenarios ◽  
Po River ◽  
Basin Scale ◽  
The Future

Abstract. River discharges are the main expression of the hydrological cycle and are the results of climate natural variability. The signal of climate changes occurrence raises the question of how it will impact on river flows and on their extreme manifestations: floods and droughts. This question can be addressed through numerical simulations spanning from the past (1971) to future (2100) under different climate change scenarios. This work addresses the capability of a modelling chain to reproduce the observed discharge of the Po River over the period 1971–2000. The modelling chain includes climate and hydrological/hydraulic models and its performance is evaluated through indices based on the flow duration curve. The climate datasets used for the 1971–2000 period are (a) a high resolution observed climate dataset, and COSMO-CLM regional climate model outputs with (b) perfect boundary condition, ERA40 Reanalysis, and (c) suboptimal boundary conditions provided by the global climate model CMCC–CM. The aim of the different simulations is to evaluate how the uncertainties introduced by the choice of the regional and/or global climate models propagate in the simulated discharges. This point is relevant to interpret the results of the simulated discharges when scenarios for the future are considered. The hydrological/hydraulic components are simulated through a physically-based distributed model (TOPKAPI) and a water balance model at the basin scale (RIBASIM). The aim of these first simulations is to quantify the uncertainties introduced by each component of the modelling chain and their propagation. Estimation of the overall uncertainty is relevant to correctly understand the future river flow regimes. The results show how bias correction algorithms can help in reducing the overall uncertainty associated to the different stages of the modelling chain.

scholarly journals Trends in projections of standardized precipitation indices in a future climate in Poland

2016 ◽  
Vol 20 (5) ◽  
pp. 1947-1969 ◽  
Author(s):  
Marzena Osuch ◽  
Renata J. Romanowicz ◽  
Deborah Lawrence ◽  
Wai K. Wong
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Standardized Precipitation Index ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Projections ◽  
Monthly Precipitation

Abstract. Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann–Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons.

High bit rate ACTS experiments for performing global science - Keck Telescope and global climate model

1996 ◽  
Author(s):  
Larry Bergman ◽  
J. Gary ◽  
Burt Edelson ◽  
Neil Helm ◽  
Judith Cohen ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Bit Rate ◽  
Global Science ◽  
High Bit Rate
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