scholarly journals Means and Extremes: Evaluation of a CMIP6 Multi-Model Ensemble in Reproducing Historical Climate Characteristics across Alberta, Canada

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 737
Author(s):  
Badrul Masud ◽  
Quan Cui ◽  
Mohamed E. Ammar ◽  
Barrie R. Bonsal ◽  
Zahidul Islam ◽  
...  
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Hybrid Approach ◽  
Generalized Pareto Distribution ◽  
General Circulation Models ◽  
Mean Annual Precipitation ◽  
Daily Maximum ◽  
Mountainous Area ◽  
Tail Behaviour ◽  
Extreme Indices

This study evaluates General Circulation Models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for their ability in simulating historical means and extremes of daily precipitation (P), and daily maximum (Tmax), and minimum temperature (Tmin). Models are evaluated against hybrid observations at 2255 sub-basins across Alberta, Canada using established statistical metrics for the 1983–2014 period. Three extreme indices including consecutive wet days (CWD), summer days (SD), and warm nights (WN) are defined based on the peak over the threshold approach and characterized by duration and frequency. The tail behaviour of extremes is evaluated using the Generalized Pareto Distribution. Regional evaluations are also conducted for four climate sub-regions across the study area. For both mean annual precipitation and mean annual daily temperature, most GCMs more accurately reproduce the observations in northern Alberta and follow a gradient toward the south having the poorest representation in the western mountainous area. Model simulations show statistically better performance in reproducing mean annual daily Tmax than Tmin, and in reproducing annual mean duration compared to the frequency of extreme indices across the province. The Kernel density curves of duration and frequency as simulated by GCMs show closer agreement to that of observations in the case of CWD. However, it is slightly (completely) overestimated (underestimated) by GCMs for warm nights (summer days). The tail behaviour of extremes indicates that GCMs may not incorporate some local processes such as the convective parameterization scheme in the simulation of daily precipitation. Model performances in each of the four sub-regions are quite similar to their performances at the provincial scale. Bias-corrected and downscaled GCM simulations using a hybrid approach show that the downscaled GCM simulations better represent the means and extremes of P characteristics compared to Tmax and Tmin. There is no clear indication of an improved tail behaviour of GPD based on downscaled simulations.

Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models

2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Lower Troposphere ◽  
General Circulation Models ◽  
Intercomparison Project ◽  
Cloud Tops ◽  
The Tropics ◽  
Fraction Models

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.

scholarly journals Performance Assessment of General Circulation Model in Simulating Daily Precipitation and Temperature Using Multiple Gridded Datasets

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1793 ◽  
Author(s):  
Najeebullah Khan ◽  
Shamsuddin Shahid ◽  
Kamal Ahmed ◽  
Tarmizi Ismail ◽  
Nadeem Nawaz ◽  
...  
Keyword(s):  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
General Circulation Models ◽  
Daily Maximum ◽  
Gridded Data ◽  
Max Planck ◽  
Meteorological Forcing ◽  
Temperature And Precipitation ◽  
Feature Selection Approach

The performance of general circulation models (GCMs) in a region are generally assessed according to their capability to simulate historical temperature and precipitation of the region. The performance of 31 GCMs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) is evaluated in this study to identify a suitable ensemble for daily maximum, minimum temperature and precipitation for Pakistan using multiple sets of gridded data, namely: Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Berkeley Earth Surface Temperature (BEST), Princeton Global Meteorological Forcing (PGF) and Climate Prediction Centre (CPC) data. An entropy-based robust feature selection approach known as symmetrical uncertainty (SU) is used for the ranking of GCM. It is known from the results of this study that the spatial distribution of best-ranked GCMs varies for different sets of gridded data. The performance of GCMs is also found to vary for both temperatures and precipitation. The Commonwealth Scientific and Industrial Research Organization, Australia (CSIRO)-Mk3-6-0 and Max Planck Institute (MPI)-ESM-LR perform well for temperature while EC-Earth and MIROC5 perform well for precipitation. A trade-off is formulated to select the common GCMs for different climatic variables and gridded data sets, which identify six GCMs, namely: ACCESS1-3, CESM1-BGC, CMCC-CM, HadGEM2-CC, HadGEM2-ES and MIROC5 for the reliable projection of temperature and precipitation of Pakistan.

Beneficial impacts of climate change on pastoral and broadacre agriculture in cool-temperate Tasmania

2014 ◽  
Vol 65 (2) ◽  
pp. 194 ◽  
Author(s):  
D. C. Phelan ◽  
D. Parsons ◽  
S. N. Lisson ◽  
G. K. Holz ◽  
N. D. MacLeod
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
General Circulation Models ◽  
Annual Rainfall ◽  
Wheat Crop ◽  
Daily Maximum ◽  
Climate Data ◽  
Diverse Range ◽  
Wheat Production ◽  
Elevated Atmospheric Co2

Although geographically small, Tasmania has a diverse range of regional climates that are affected by different synoptic influences. Consequently, changes in climate variables and climate-change impacts will likely vary in different regions of the state. This study aims to quantify the regional effects of projected climate change on the productivity of rainfed pastoral and wheat crop systems at five sites across Tasmania. Projected climate data for each site were obtained from the Climate Futures for Tasmania project (CFT). Six General Circulation Models were dynamically downscaled to ~10-km grid cells using the CSIRO Conformal Cubic Atmospheric Model under the A2 emissions scenario for the period 1961–2100. Mean daily maximum and minimum temperatures at each site are projected to increase from a baseline period (1981–2010) to 2085 (2071–2100) by 2.3–2.7°C. Mean annual rainfall is projected to increase slightly at all sites. Impacts on pasture and wheat production were simulated for each site using the projected CFT climate data. Mean annual pasture yields are projected to increase from the baseline to 2085 largely due to an increase in spring pasture growth. However, summer growth of temperate pasture species may become limited by 2085 due to greater soil moisture deficits. Wheat yields are also projected to increase, particularly at sites presently temperature-limited. This study suggests that increased temperatures and elevated atmospheric CO2 concentrations are likely to increase regional rainfed pasture and wheat production in the absence of any significant changes in rainfall patterns.

Downscaling general circulation model output: a review of methods and limitations

1997 ◽  
Vol 21 (4) ◽  
pp. 530-548 ◽  
Author(s):  
R.L. Wilby ◽  
T.M.L. Wigley
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Circulation Model ◽  
General Circulation Models ◽  
Limited Area ◽  
Regression Methods ◽  
Present Generation ◽  
Precipitation Characteristics

General circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. What is less clear is the extent to which local (subgrid) scale meteorological processes will be affected. So-called 'downscaling' techniques have subsequently emerged as a means of bridging the gap between what climate modellers are currently able to provide and what impact assessors require. This article reviews the present generation of downscaling tools under four main headings: regression methods; weather pattern (circulation)-based approaches; stochastic weather generators; and limited-area climate models. The penultimate section summarizes the results of an international experiment to intercompare several precipitation models used for downscaling. It shows that circulation-based downscaling methods perform well in simulating present observed and model-generated daily precipitation characteristics, but are able to capture only part of the daily precipitation variability changes associated with model-derived changes in climate. The final section examines a number of ongoing challenges to the future development of climate downscaling.

scholarly journals Long-Term Maximum and Minimum Temperature Projections Over Metro Vancouver, Canada

2021 ◽  
Vol 9 ◽  
Author(s):  
Chuyin Tian ◽  
Guohe Huang ◽  
Yanli Liu ◽  
Denghua Yan ◽  
Feng Wang ◽  
...  
Keyword(s):  
Seasonal Variability ◽  
Minimum Temperature ◽  
General Circulation ◽  
Energy Requirement ◽  
General Circulation Models ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Projections ◽  
Metro Vancouver

Evident climate change has been observed and projected in observation records and General Circulation Models (GCMs), respectively. This change is expected to reshape current seasonal variability; the degree varies between regions. High-resolution climate projections are thereby necessary to support further regional impact assessment. In this study, a gated recurrent unit-based recurrent neural network statistical downscaling model is developed to project future temperature change (both daily maximum temperature and minimum temperature) over Metro Vancouver, Canada. Three indexes (i.e., coefficient of determinant, root mean square error, and correlation coefficient) are estimated for model validation, indicating the developed model’s competitive ability to simulate the regional climatology of Metro Vancouver. Monthly comparisons between simulation and observation also highlight the effectiveness of the proposed downscaling method. The projected results (under one model set-up, WRF-MPI-ESM-LR, RCP 8.5) show that both maximum and minimum temperature will consistently increase between 2,035 and 2,100 over the 12 selected meteorological stations. By the end of this century, the daily maximum temperature and minimum temperature are expected to increase by an average of 2.91°C and 2.98°C. Nevertheless, with trivial increases in summer and significant rises in winter and spring, the seasonal variability will be reduced substantially, which indicates less energy requirement over Metro Vancouver. This is quite favorable for Metro Vancouver to switch from fossil fuel-based energy sources to renewable and clean forms of energy. Further, the cold extremes’ frequency of minimum temperature will be reduced as expected; however, despite evident warming trend, the hot extremes of maximum temperature will become less frequent.

Applying the new spatially distributed Added Value Index and Climate Change Downscaling Signal for Regional Climate Models to high-resolution EURO-CORDEX and convection permitting scale simulations

2021 ◽  
Author(s):  
James Ciarlo ◽  
Erika Coppola ◽  
Emanuela Pichelli ◽  
Jose Abraham Torres Alavez ◽  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
General Circulation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Added Value ◽  
Spatially Distributed

<p>Downscaling data from General Circulation Models (GCMs) with Regional Climate Models (RCMs) is a computationally expensive process, even more so running at the convection permitting scale (CP). Despite the high-resolution products of these simulations, the Added Value (AV) of these runs compared to their driving models is an important factor for consideration. A new method was recently developed to quantify the AV of historical simulations as well as the Climate Change Downscaling Signal (CCDS) of forecast runs. This method presents these quantities spatially and thus the specific regions with the most AV can be identified and understood.</p><p>An analysis of daily precipitation from a 55-model EURO-CORDEX ensemble (at 12 km resolution) was assessed using this method. It revealed positive AV throughout the domain with greater emphasis in regions of complex topography, coast-lines, and the tropics. Similar CCDS was obtained when assessing the RCP 8.5 far future runs in these domains. This paper looks more closely at the CCDS obtained with this method and compares it to other climate change signals described in other studies.</p><p>The same method is now being applied to assess the AV and CCDS of daily precipitation from an ensemble of models at the CP scale (~3 km) over different domains within Europe. The current stage of the analysis is also looking into the AV of using hourly precipitation instead of daily.</p>

scholarly journals The Key Role of Heavy Precipitation Events in Climate Model Disagreements of Future Annual Precipitation Changes in California

2013 ◽  
Vol 26 (16) ◽  
pp. 5879-5896 ◽  
Author(s):  
David W. Pierce ◽  
Daniel R. Cayan ◽  
Tapash Das ◽  
Edwin P. Maurer ◽  
Norman L. Miller ◽  
...  
Keyword(s):  
Bias Correction ◽  
General Circulation ◽  
Climate Model ◽  
Daily Precipitation ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Precipitation Frequency ◽  
Model Average ◽  
Projected Change ◽  
Precipitation Events

Abstract Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change. This disagreement is explored in terms of daily precipitation frequency and intensity. It is found that divergent model projections of changes in the incidence of rare heavy (>60 mm day−1) daily precipitation events explain much of the model disagreement on annual time scales, yet represent only 0.3% of precipitating days and 9% of annual precipitation volume. Of the 25 downscaled model projections examined here, 21 agree that precipitation frequency will decrease by the 2060s, with a mean reduction of 6–14 days yr−1. This reduces California's mean annual precipitation by about 5.7%. Partly offsetting this, 16 of the 25 projections agree that daily precipitation intensity will increase, which accounts for a model average 5.3% increase in annual precipitation. Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods [Weather Research and Forecasting (WRF), Regional Spectral Model (RSM), and version 3 of the Regional Climate Model (RegCM3)] and statistical methods [bias correction with spatial disaggregation (BCSD) and bias correction with constructed analogs (BCCA)], although not all downscaling methods were applied to each global model. Model disagreements in the projected change in occurrence of the heaviest precipitation days (>60 mm day−1) account for the majority of disagreement in the projected change in annual precipitation, and occur preferentially over the Sierra Nevada and Northern California. When such events are excluded, nearly twice as many projections show drier future conditions.

scholarly journals SPLINE MODELS OF CONTEMPORARY, 2030, 2060 AND 2090 CLIMATES FOR MICHOACÁN STATE, MÉXICO. IMPACTS ON THE VEGETATION

2012 ◽  
Vol 35 (4) ◽  
pp. 333
Author(s):  
Cuauhtémoc Sáenz-Romero ◽  
Gerald E. Rehfeldt ◽  
Nicholas L. Crookston ◽  
Pierre Duval ◽  
Jean Beaulieu
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Aridity Index ◽  
General Circulation Models ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Emission Scenarios ◽  
Weather Stations

Climate data from 149 weather stations of Michoacán State, at Western México, were extracted from a spline climate model developed for México’s contemporary climate (1961-1990), and for climate projected for the decades centered in years 2030, 2060 and 2090. The model was constructed using outputs from three general circulation models (GCMs: Canadian, Hadley and Geophysical Fluid Dynamics) from two emission scenarios (A “pessimistic” and B “optimistic”). Mean annual temperature (MAT), mean annual precipitation (MAP), annual degree days > 5 °C (DD5), and annual aridity index (DD50.5/MAP) were mapped for Michoacán at an 1 km2 scale, and means were estimated averaging all weather stations. The state average in GCMs and emission scenarios point out that mean annual temperature would increase 1.4 °C by year 2030, 2.2 °C by year 2060 and 3.6 °C by year 2090; whereas annual precipitation would decrease 5.6 % by year 2030, 5.9 % by year 2060 and 7.8 % by year 2090. Climate models can be used for inferring plant-climate relationships and for developing programs to counteract global warming effects. Climate variables were estimated also at Pinus hartwegii and Pinus pseudostrobus growth locations, at Pico de Tancítaro in Central Western Michoacán and Nuevo San Juan Parangaricutiro (near Tancítaro), respectively. According to the annual aridity index values estimated for such locations, it is necessary to conduct assisted migration to match current genotypes to projected climates. This translates into an altitudinal shift of 400 to 450 m higher to match 2030 climates predicted by Canadian Model scenario A2, and 600 to 800 m to match 2060 climates.

scholarly journals Modelling the Present and Future Water Level and Discharge of the Tidal Betna River

Geosciences ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 271 ◽  
Author(s):  
M. Islam ◽  
Nynke Hofstra ◽  
Ekaterina Sokolova
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Sea Level ◽  
River Basin ◽  
General Circulation ◽  
Risk Mitigation ◽  
General Circulation Models ◽  
Local Scale ◽  
Daily Maximum ◽  
Major Floods

Climate change, comprising of changes in precipitation patterns, higher temperatures and sea level rises, increases the likelihood of future flooding in the Betna River basin, Bangladesh. Hydrodynamic modelling was performed to simulate the present and future water level and discharge for different scenarios using bias-corrected, downscaled data from two general circulation models. The modelling results indicated that, compared to the baseline year (2014–2015), the water level is expected to increase by 11–16% by the 2040s and 14–23% by the 2090s, and the monsoon daily maximum discharge is expected to increase by up to 13% by the 2040s and 21% by the 2090s. Sea level rise is mostly responsible for the increase in water level. The duration of water level exceedance of the established danger threshold and extreme discharge events can increase by up to half a month by the 2040s and above one month by the 2090s. The combined influence of the increased water level and discharge has the potential to cause major floods in the Betna River basin. The results of our study increase the knowledge base on climate change influence on water level and discharge at a local scale. This is valuable for water managers in flood-risk mitigation and water management.

scholarly journals A Hybrid Approach for Model Order Reduction of Barotropic Quasi-Geostrophic Turbulence

Fluids ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 86 ◽  
Author(s):  
Sk. Rahman ◽  
Omer San ◽  
Adil Rasheed
Keyword(s):  
Neural Network ◽  
General Circulation ◽  
Hybrid Approach ◽  
Single Layer ◽  
General Circulation Models ◽  
Projection Methods ◽  
Ocean Model ◽  
Galerkin Projection ◽  
Mean Flow ◽  
Modeling Framework

We put forth a robust reduced-order modeling approach for near real-time prediction of mesoscale flows. In our hybrid-modeling framework, we combine physics-based projection methods with neural network closures to account for truncated modes. We introduce a weighting parameter between the Galerkin projection and extreme learning machine models and explore its effectiveness, accuracy and generalizability. To illustrate the success of the proposed modeling paradigm, we predict both the mean flow pattern and the time series response of a single-layer quasi-geostrophic ocean model, which is a simplified prototype for wind-driven general circulation models. We demonstrate that our approach yields significant improvements over both the standard Galerkin projection and fully non-intrusive neural network methods with a negligible computational overhead.

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